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          Azure Machine Learning Development: 3 Deploying and Managing Models      Cache   Translate Page      
Azure Machine Learning Development: 3 Deploying and Managing Models
Azure Machine Learning Development: 3 Deploying and Managing Models
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 50M | 110 MB
Genre: eLearning | Language: English

Azure Machine Learning Studio brings the power of AI into the professional developer's hands. In this course, learn how to deploy and manage models in Azure Machine Learning Studio. Instructor Sahil Malik picks up from earlier Azure Machine Learning Development courses and dives directly into the more advanced topics of deploying, scaling, logging, and managing your trained models in production scenarios.


          iPhone Xs A12 Bionic chip features 7nm design, next-gen Neural Engine      Cache   Translate Page      
Article Image

In revealing the iPhone Xs on Wednesday, Apple also detailed its core processor, the 7-nanometer A12 Bionic, which includes a new iteration of its "Neural Engine" for tasks related to machine learning, such as Face ID and animoji.
          AQR hires head of machine learning      Cache   Translate Page      
Marcos Lopez de Prado joined AQR Capital Management as principal and head of machine learning.
          Engineer/Scientist - Machine Learning for Autonomous Driving      Cache   Translate Page      
CA-Agoura Hills, Moving mobility forward We are Aptiv - a new technology company with a proven history of enabling mobility. Operating as Delphi, we pioneered advances in the industry. Now, as Aptiv, we're more dedicated than ever to bringing the next generation of autonomous vehicles, smart cities and connectivity to life. Join our innovative team Want to do more than just imagine the ways our world will move tom
          Sr Manager, AI/ML Solutions Architecture - Amazon.com - Seattle, WA      Cache   Translate Page      
Drive new business and product initiatives, championing ideas that move our business forward. 2+ years machine learning experience....
From Amazon.com - Sun, 26 Aug 2018 08:18:34 GMT - View all Seattle, WA jobs
          Principal Business Development Manager for Mobile Compute Infrastructure - Amazon.com - Seattle, WA      Cache   Translate Page      
AWS customers are looking for ways to change their business models and solve complex business challenges with machine learning (ML) and deep learning (DL)...
From Amazon.com - Thu, 16 Aug 2018 01:20:19 GMT - View all Seattle, WA jobs
          Software Development Engineer - Amazon.com - Seattle, WA      Cache   Translate Page      
Extensive, varied internal and external customer base. Knowledge of statistical analysis, big data, machine learning....
From Amazon.com - Sat, 23 Jun 2018 14:22:29 GMT - View all Seattle, WA jobs
          SAP and Supply Chain      Cache   Translate Page      
Earlier we worked with SAP for optimizing the manufacturing supply chain.  Some elements of automatic augmentation based on predictions.

SAP introduces intelligent capabilities for digital supply chain

CHICAGO, Sept. 10, 2018 /PRNewswire/ -- SAP SE (NYSE : SAP ) today announced new features to digitally optimize the supply chain and infuse it with intelligence from product design and production to delivery, operations and service. With the integration of SAP S/4HANA® to digital supply chain solutions from SAP, companies can gain new insights, make predictions and instantly adapt in an agile supply chain that extends to customers and supplier networks. The announcement was made at IMTS USA, being held Sept. 10–15 in Chicago, Illinois.

SAP's leading presence and innovation in supply chain management continues to help companies around the world embrace Industry 4.0 technologies including the Internet of Things (IoT), Big Data, and machine learning–enabled automation. The latest solution updates enable an integrated supply chain and manufacturing environment with enhanced capabilities for production planning and scheduling, availability and fulfillment, compliance, health and safety, and production engineering and operations.

"Intelligent technologies help businesses make better sense of data, plan and predict outcomes, and optimize the entire product lifecycle including the customer experience," said Hala Zeine, president, Digital Supply Chain and Manufacturing, SAP. "SAP helps companies embrace smarter business based on data-driven insights to run supply chains with greater insight, speed and purpose."

Highlights of the new capabilities include:

Support for highly engineered products — consolidated operations including bill of materials, intelligent process planning, shop floor execution and integrated system testing. Production engineering and operations can be synchronized across manufacturing execution for complex assembly and low-volume operations, such as in aerospace and defense, which traditionally required manual processing.

3D visualization and production — providing visualization from design through production to service and maintenance, and supporting the network of digital twins. Core business processing is combined with complete product lifecycle management to support decision-making, production and maintenance operations, and 3D printing of components. .... "


          Comment on How To Make Your Job Resume Appealing? by How Should A Resume Of Engineering Student Look Like      Cache   Translate Page      
[…] “It is also advisable to include subjects that you learned in college, and many colleges offer upcoming subjects like AI, Machine Learning, etc. which other colleges don’t offer. It is in your favor to include these in your engineering resume and attract the attention of the recruiter.” […]
          Sales Engineer - Hitachi Vantara - New York, NY      Cache   Translate Page      
Account Managers, internal specialists and customers. Understanding of Data Science and Machine Learning....
From Hitachi Vantara - Sat, 04 Aug 2018 04:47:47 GMT - View all New York, NY jobs
          AI Solutions Architect - Industrial - Petuum - Sunnyvale, CA      Cache   Translate Page      
Machine learning or IIoT preferred. PaaS, SaaS, IaaS and business intelligence/analytics implementation experience are a plus....
From Petuum - Fri, 07 Sep 2018 20:07:58 GMT - View all Sunnyvale, CA jobs
          Product Designer: Wombat Studio      Cache   Translate Page      
Wombat Studio is building the world's first platform that empowers everyone, not just professional artists, to create amazing 3D animation with help of machine learning. Our first app, Magic Poser, helps artists/hobbyists create 3D scenes which can either be used for art pieces themselves or for art reference. Magic Poser has received great traction on both Android/iOS, accumulating 2 million+ downloads worldwide and 4.7 stars on App Store.  We are looking for highly competent product designers who are excited about reinventing 3D animation. You will be working with an exceptionally talented team with experiences at top companies and universities such as Google, Uber, Blizzard, Stanford, MIT and Yale.   WHAT YOU WILL ACCOMPLISH Lead the ideation and design of features that makes the 3D creative process easy and fun. Design gamification features that increase engagement and conversion rate, especially with the community and the asset store. Collaborate with engineering and art team to produce effective and achievable designs. Evaluate effectiveness of different designs based on user feedback and data analytics tools such as Firebase. Conduct user interviews and collaborate with the community manager to gain product insights from user feedback. Produce marketing material designs for our website, app store home page and social media channels.   TALENTS YOU BRING TO THE TEAM Experience designing mobile applications, examples required in portfolio. Understanding of interaction design and information architecture. Experience developing wireframes and prototypes from concepts and user feedback. Proficient in at least one of the commonly used design software, such as Sketch, Photoshop, Illustrator. Passionate about anime and video games. Familiarity with the fandom/dojin culture is a BIG plus!   HOW TO APPLY Please email your resume to admin@thewombatstudio.com, and we will get back to you asap.  
          I quit my high-paying job to travel the world — and came back as the CEO of my own company      Cache   Translate Page      

Quit my job

  • I quit my job after 10 years of working at an aerospace brand and in finance.
  • By many measures, I had excelled in those roles — I earned great money and ran prestigious teams all over the world.
  • However, the 12-hour days and little free time became too much to bear, and I felt that life was passing me by.
  • So I quit my job to travel the world — and unexpectedly became a CEO. 

 

Ever since I was five years old, all I've ever wanted was to travel and meet people around the world. I grew up in communist Poland. The borders were closed, and passports were nearly impossible to get. Everyone around me said  I would never be able to see the world.

But I never believed it. I've always felt like a global citizen. 

Soon after communism collapsed in Poland, I put all of my drive and ambition into my education.

I came to the US, finished college in three years while working full time, graduating summa cum laude. I quickly got recruited by a multi billion-dollar global aerospace brand.

Within six months, I began leading global IT programs, creating and managing remote teams on four different continents and training thousands of members around the world from my laptop.

We accomplished amazing things, and soon new career opportunities poured in. I wanted to challenge myself and grow, so I moved to the financial industry.

I had finally made it to the VP level. Running large global programs and leading high-performance teams sounded prestigious. But each new career step was becoming more intrusive, stressful, office-bound, and time-consuming.

I spent agonizing hours in traffic getting to and from a job that was less than inspiring. My 12-hour work days were filled with spreadsheets, slide presentations, endless meetings, and canceled vacations.

Swiveling in my chair in my almost-corner office, I wondered: Is this all there is to life?

I started wondering what had happened. Where was the adventurous soul who wanted to travel the world? Now I could barely scrape together a week to get away.

Life was passing me by

Like many people I know, I was living on autopilot: finishing school, giving up the best years of my life to work, and postponing my dreams for the elusive idea of retirement. Deferring life was my norm.

Essentially, I was betting my entire life on the possibility of truly enjoying it near the end. The more I thought about it, the more the idea sounded like an irresponsible and risky gamble. There was only one option: I had to take time off to begin living — now.

Quit my job

The stakes were high — I was leaving behind my entire 10-year career and giving up the security of my income in exchange for one year of travel and living. I was scared, but the more I looked around, the more I realized that there are no guarantees in life.

We have only one life, and there is no do-over. I began to see that quitting my office job to finally live my life was not the riskiest decision — staying in my taxing job and not giving my life a chance was. So I packed my bags and bought a one-way ticket to Spain.

I traveled — and started a business

I visited over 50 countries and six continents, soaking up the sun in Bali, sipping wine in Santorini, climbing to the base camp of Mount Everest, and scuba diving at the Great Barrier Reef. Travel became my new life.

Quit my job

Every time I visited a new country, I was blown away by the talented people I met — amazing people with so much untapped potential and so few opportunities. I couldn’t stand it.

I could clearly see how many of the people I met could drive innovation for top companies worldwide, if only given a chance. 

Drawing on my own remote-work experience, I quickly realized that I didn't have to give up my dream of travel and helping people around the world to accomplish my career goals.

All of a sudden, my vision was clear: Everybody deserves a chance to live up to their potential, and the flexibility of remote work can help them do it.

Quit my job.

So I created my first Facebook group for remote and travel jobs, and began working with progressive and forward-thinking employers worldwide who shared remote work opportunities daily.

Initially, there were only 100 members, but when the community reached 3,500 people, I knew this was bigger than me. These were extremely talented people from all over the world. I believed in them, and they counted on me.

So I did everything I could to help. I reached out to every employer I could to bring more remote job opportunities and I went to every meetup out there to learn more about how to create a successful business.

Eventually, I met entrepreneur Gregg Pollack, who recommended that I apply to Starter Studio, an innovative hub he created for entrepreneurs.

Quit my job

I made a few slides showing how amazing our community is. After many subsequent steps, I was accepted to the program. For the next three months, I spent every waking hour learning from top entrepreneurs how to build a successful business.

At the end of the program, Pangian, our borderless digital nation, was born.

Today, Pangian is platform powered by machine learning and AI, matching top talent around the world with high-quality, long-term remote work. We just expanded to 121 countries with top global companies and over 39,000 members united by our goal of flexible work that has meaning and fulfills us.

And this is just the beginning.

SEE ALSO: I'm a burned-out millennial who quit a high-paying 9-to-5 job to travel full time

Join the conversation about this story »

NOW WATCH: What drinking diet soda does to your body and brain


          Principal Program Manager - Microsoft - Redmond, WA      Cache   Translate Page      
Our internal customers use machine learning models to analyze multi-exabyte datasets. The Big Data team builds solutions that enable customers to tackle...
From Microsoft - Sat, 28 Jul 2018 02:13:20 GMT - View all Redmond, WA jobs
          Software Development Manager - Core Video Delivery Technologies, Prime Video - Amazon.com - Seattle, WA      Cache   Translate Page      
Strong business and technical vision. Experience in machine learning technologies and big data is a plus. We leverage Amazon Web Services (AWS) technologies...
From Amazon.com - Thu, 02 Aug 2018 19:21:25 GMT - View all Seattle, WA jobs
          Solutions Architect - Amazon Web Services - Amazon.com - San Francisco, CA      Cache   Translate Page      
DevOps, Big Data, Machine Learning, Serverless computing etc. High level of comfort communicating effectively across internal and external organizations....
From Amazon.com - Sun, 02 Sep 2018 07:30:50 GMT - View all San Francisco, CA jobs
          Sr. Solutions Architect - AWS - Amazon.com - San Francisco, CA      Cache   Translate Page      
DevOps, Big Data, Machine Learning, Serverless computing etc. High level of comfort communicating effectively across internal and external organizations....
From Amazon.com - Fri, 25 May 2018 19:20:02 GMT - View all San Francisco, CA jobs
          Nov 9, 2018: Joy Buolamwini Lecture at TBD      Cache   Translate Page      

Joy Buolamwini is founder of the Algorithmic Justice League to fight bias in machine learning. Learn more about Joy's work at https://www.poetofcode.com

View on site | Email this event


          Principal Market Validation Specialist - PTC - Needham, MA      Cache   Translate Page      
Advance knowledge and experience with Machine Learning / Data Science / Analytics. Customer Satisfaction focus, both internal and external, with strong...
From PTC - Wed, 16 May 2018 14:29:21 GMT - View all Needham, MA jobs
          MACHINE LEARNING ENGINEER FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page      
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Engineer for Speech related Applications (6 months contract)....
From Huawei Canada - Mon, 18 Jun 2018 23:46:16 GMT - View all Montréal, QC jobs
          MACHINE LEARNING INTERN FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page      
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Intern for Speech related Applications....
From Huawei Canada - Mon, 18 Jun 2018 17:50:57 GMT - View all Montréal, QC jobs
          MACHINE LEARNING HARDWARE RESEARCHER OR DEVELOPER - Huawei Canada - Montréal, QC      Cache   Translate Page      
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Hardware Researcher or Developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:32 GMT - View all Montréal, QC jobs
          Machine Learning Software Developer - Huawei Canada - Montréal, QC      Cache   Translate Page      
We thank all applicants for their interest in career opportunities with Huawei. ML Software developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:31 GMT - View all Montréal, QC jobs
          Zoox Smart Data lança novo software na Equipotel 2018      Cache   Translate Page      
A Zoox Smart Data, empresa de alta tecnologia pioneira na aplicação de soluções integradas de inteligência artificial, machine learning e big data, anuncia o lançamento do Zoox Smart Pass, software que integra big data e reconhecimento facial, na Equipotel deste ano, que acontece de 18 a 21 de setembro, no São Paulo Expo, em São […]
          Apple unveils 3 iPhones with dual SIM, impressive cameras      Cache   Translate Page      

San Francisco, Sep 13 (IANS) Apple officially introduced its 2018 line-up of iPhones -- the premium iPhone XS, iPhone XS Max and iPhone XR at an event in California late on Wednesday.

The iPhone XS and iPhone XS Max will support dual SIM and dual standby functionality.

The premium iPhone XS and XS Max come with upgraded 12MP + 12MP camera and 2x optical zoom. There is an improved TrueTone quad-LED flash as well. Both the models have a 7MP RGB camera sensor in the front with F/2.2 aperture while the iPhone XR has a single 12MP camera at the rear.

The iPhone XS and iPhone XS Max would be available in 64GB, 256GB and 512GB storage variants in space grey, silver and a new gold colour starting at Rs 99,900 and Rs 1,09,900, respectively through Apple authorised resellers in India.

The cheapest of the lot -- the iPhone XR -- has a starting price of Rs 76,900.

The premium iPhone XS is made with stainless surgical grade steel with a new glass formulation and has edge-to-edge screen, Apple said in a statement.

Both the iPhone XS and XS Max are fueled by Apple's latest A12 Bionic chipset built on 7-nm design, which allows for 6.9 billion transistors on the chip. Also, there is a new neural engine with an 8-core dedicated machine learning (ML) processor.

The iPhone X comes with a 5.8-inch OLED display while the iPhone XS has 6.5-inch OLED screen -- the biggest ever on an iPhone. Other than the size, both the models have 3D Touch and HDR.

The Face ID in these models is said to work faster this time than last year's iPhone X.

The affordable iPhone XR has a 6.1-inch LCD screen with liquid Retina display and aluminium body instead of a steel one.

The Cupertino-based company also unveiled its new Apple Watch Series 4 with improved health features.

Its next generation of Apple Watch features edge-to-edge display with smaller bezels, which is 30 per cent bigger.

The device brings a design overhaul to the Apple Watch as the iPhone-maker is now using a new dual-core 64-bit chipset, custom designed to improve performance.

"Apple Watch isn't just the number one smart watch, it is the number one watch in the world period," Tim Cook, CEO of Apple said.

Apart from heartbeat data, the devices would now also track heart rhythm and notify users.

The new series has been approved by FDA for ECG recording as well but this feature would be limited to only US-based users initially.

The tech giant said it is working to introduce this feature in other countries as well.

--IANS

ksc/qd


          Live Coverage of Apple's iPhone XS, iPhone XR, and Apple Watch Event      Cache   Translate Page      
Apple's "Gather round" event at the Steve Jobs Theater at Apple Park begins at 10:00 a.m. Pacific Time, where it is widely expected to unveil three new iPhones (XS, XS Max, and XR) as well as new, slightly larger Apple Watch models.

Steve Jobs Theater via Apple CEO Tim Cook

We should also be hearing final details and the official release date for iOS 12, and likely macOS Mojave, watchOS 5, and tvOS 12 as well. And, of course, there may be other announcements and surprises in the cards.

Apple itself leaked a number of details this morning by prematurely updating its store site maps, and we have a summary of what's been revealed right here.

Apple is providing a live video stream on its website, via the Apple Events app on Apple TV, and on Twitter. We've shared instructions on how to watch along with a list of when the keynote starts in time zones around the world.

In addition to Apple's video stream, we will be updating this article with live blog coverage—no need to refresh—and issuing Twitter updates through our @MacRumorsLive account as the keynote unfolds.

Highlights from the event and separate news stories regarding today's announcements will go out through our @MacRumors account.

Sign up for our newsletter to keep up with Apple news and rumors.



Apple's online store is currently down in advance of the event. It should be accessible again shortly after the keynote.

Live blog in chronological order is after the jump.

8:26 am: Members of the press are checking in and milling around waiting to be admitted to the theater. As usual, Apple is providing light breakfast options.










8:31 am: Apple staff members currently blocking access to the actual theater.

9:15 am: The crowd is continuing to gather. Apple should be opening up the theater shortly.

9:22 am: Apple has opened the stairs, and members of the press are now heading down to the theater.




9:56 am: Five minutes to showtime!

10:01 am: Event is getting started with a video showing people heading down to the theater.

10:03 am: Mission: Impossible themed video showing someone rushing a last-minute item from Apple Park to the theater. Kevin Lynch beams himself directly to the theater using his watch.

10:04 am: Apple employee's badge denied access to backstage at the theater, but Kevin Lynch materializes to let her in. Tim Cook opens the briefcase and takes out his presentation clicker.


10:06 am: Cook giving an intro. We've reinvented several product categories, retail, etc. Showing Apple Piazza Liberty in Milan. Over 500 million visitors per year at Apple stores. We love that so many customers have the chance to experience our products there. We aim to put the customer at the center of everything we do.


10:07 am: We're about to ship our 2 billionth iOS device. iOS has changed the way we live, learn, work. It's changed entertainment, how we shop, how we stay in touch with each other. It's only fitting that today we're going to tell you about two of our most personal products. The ones that go with you everywhere.

10:07 am: Starting with Apple Watch.




10:09 am: This category didn't even exist a few years ago. Apple Watch is now the #1 watch, period. It's redefined what a watch can do for you. It's become indispensable for millions of people around the world. Jeff Williams on stage.

10:10 am: Apple Watch is becoming indispensable in three areas: communication, fitness, and health. Talking about heart rate monitoring..."an intelligent guardian for your health."

10:10 am: We're taking Apple Watch to the next level in all of these areas.

10:11 am: Intro video for next generation of Apple Watch.




10:12 am: Apple Watch Series 4. Everything about it has been redesigned and reengineered. It's just beautiful.




10:13 am: Stunning new display pushed right to the corners. Screens are significantly larger...over 30% larger. Minimal size increase, but it's thinner, so volume is actually less.




10:14 am: Brand-new watch face with up to 8 complications. Customize with the things you care about. Add loved ones and tap their faces to connect. Track time zones. Create the ultimate health and fitness watch. Modular face also redesigned with more detail from stock and third-party apps.


10:14 am: Breathe app is now available as a watch face. Raise your wrist, and it will guide you through a breathing sessions. Three breathe faces available.


10:15 am: New fire, water, and vapor faces offer dynamic visuals behind the watch hands.



10:16 am: Digital crown reengineered with haptic feedback. Speaker is 50% louder, which is great for phone calls, Walkie-Talkie, and Siri. Back is made entirely of black ceramic and sapphire crystal. Radio waves can now pass through front and back for improved cellular reception.




10:17 am: Series 4 is just as impressive on the inside. S4 package with 64-bit dual-core processor up to 2x faster.

10:18 am: Accelerometer and gyroscope have 2x the dynamic range with 8x faster sampling and up to 32 g-forces.







10:19 am: Apple Watch Series 4 can automatically detect falls. We did studies with thousands of people and captured data on real-world falls. There are repeatable motions involved to falls, trips, and slips, and the watch can detect them. It can then alert you and offer an Emergency SOS call. Will start call automatically if you're immobile for a minute after the fall.


10:21 am: Optical heart sensor has been integral since the beginning. Count calories, measure heart rate, and high heart rate notifications. Announcing three new heart features. First, low heart rate notification. Low heart rate can be a sign of something serious if not enough blood being pumped.


10:21 am: Second, Apple Watch can screen heart rhythm in the background and can notify you if it detects atrial fibrillation.


10:22 am: Third feature is with a new electrocardiogram (ECG) sensor in the back of the watch. First over-the-counter ECG product offered directly to consumers.





10:23 am: Can take an ECG anytime, anywhere. Open the app, and put your finger on the digital crown. Takes 30 seconds and gives you a heart rhythm classifications...sinus rhythm, atrial fibrillation. Results all stored and can be shared as a PDF with your doctor.

10:25 am: Ivor Benjamin, president of the American Heart Association, on stage. Applauds Apple's commitment to health. People often report symptoms that are absent during a doctor's visit. On-demand ECG is game-changing, especially for atrial fibrillation, which can increase risk of stroke, heart failure, and other complications.




10:27 am: Jeff Williams back on stage. It's great to have the support of the AHA, and we've also received clearance from the FDA. This is the first of its kind. Also, the irregular heart rhythm feature has received FDA clearance. Both features will be available in the U.S. later this year.


10:27 am: It's amazing to think the watch you wear everyday can now take an ECG.

10:28 am: Your personal data remains protected. You should decide who gets to see it. All data is encrypted on device and in the cloud.






10:29 am: Recapping features of the Apple Watch Series 4. You're probably wondering about battery life. Same 18-hour battery life customers have become used to. Increased outdoor workout battery life to six hours.

10:29 am: Showing another Apple Watch video. Jony Ive discussing the redesign and reengineering.


10:31 am: We've developed and refined the form, also making it thinner. New display is seamlessly integrated. The interface has been redesigned for the new display...more information with richer detail. Navigating with digital crown has been entirely reengineered with haptic feedback. New Apple-designed electrical sensor for ECG...a momentous achievement for a wearable device.


10:32 am: Accelerometer, gyroscope, and altimeter give you the ability to track more. Cellular capabilities give you more freedom. Series 4 is a device so powerful, personal, liberating...it can change the way you live each day.






10:33 am: Jeff Williams back on stage. Series 4 available in silver. gold, and space gray aluminum. Stainless steel is even more beautiful...silver, space gray, and gold. All band styles fit all generations of Apple Watch.


10:34 am: Nike+ has been optimized with full-screen interface. Nike Sport Loops have reflective yarn for better visibility. New Hermes models.

10:34 am: Series 4 starts at $399, cellular at $499. Series 3 sticking around starting at $279.










10:35 am: Order starting Friday, available September 21. Series 3 at new prices available right after the show. watchOS 5 available September 17. That's Apple Watch, and now back to Tim.

10:36 am: Showing Apple Watch Series 4 commercial set to the Hokey Pokey.


10:37 am: We love what Apple Watch is doing to get the world moving. Now let's talk about iPhone.


10:38 am: Recapping iPhone X technology and capabilities. So many technologies, all powered by most advanced mobile operating system. iPhone became number one smartphone in the world. Also most loved with 98% customer satisfaction.

10:38 am: Today we're going to take iPhone X to the next level. By far the most advanced smartphone we've ever created. Showing intro video of new iPhone with gold finish.




10:39 am: This is iPhone Xs. Phil Schiller coming up to tell you about it.






10:40 am: It is made of surgical grade stainless steel. Gorgeous new gold finish. Most beautiful iPhone we've ever made. Most durable glass ever in a smartphone. Three finishes: gold, silver, space gray. IP68 protects against water up to 2 meters up to 30 minutes.

10:41 am: Tested in many different liquids, even beer. Some of the most fun, intense testing we get to do.


10:41 am: 5.8" Super Retina OLED display. Plus-size display in a smaller design. So many customers love that. And it looks incredible.








10:43 am: 60% greater dynamic range in display. Not just one, but two sizes available. New 6.5" model. 2688x1242. Same size phone as current Plus size, but bigger display. What's bigger than plus size? iPhone Xs Max.




10:44 am: HDR displays, 120 Hz touch sensing, 3D Touch, tap to wake, True Tone, Wide color.




10:44 am: Stereo sound better than any iPhone to date. Wider field...great for movies, games, and music.




10:45 am: Face ID is a huge step forward. So much technology in that little space. Designed with multiple neural networks so it's secure and seamless. On iPhone Xs has faster algorithms and faster Secure Enclave. Most secure facial authentication ever in a smartphone.


10:46 am: Powering Face ID is our A-series chip. What the team has done is truly breakthrough. A12 Bionic. Industry's first 7nm chip.




10:48 am: Packed with 6.9 billion transistors. 6-core CPU, 4-core GPU, neural engine. CPU has 2 high performance and 4 high efficiency cores. GPU is up to 50% faster. Real blow away thing is the neural engine. 8-core dedicated machine learning engine with smart compute to determined where to run a task.


10:48 am: A11 could process 600 billion operations per second. A12 can process 5 trillion.


10:49 am: Next-generation image signal processor, HEVC encoder/decoder, faster memory controller for up to 512 GB of storage.


10:49 am: A12 Bionic without question the smartest and most powerful in a smartphone. Enables so many great experiences that weren't possible before.


10:52 am: Apps launch up to 30% faster on A12 Bionic. Apps and processes that rely on machine learning...we've used it for years, but what's remarkable this year is it unlocks the power of real-time machine learning. Portrait mode, Animojis, immersive AR, and new Clips app coming this fall will all benefit.

10:53 am: Siri Shortcuts will let you get more done. Demoing "keynote day" shortcut. Launches Home app scene, orders coffee, starts Apple Music playlists, gets directions.






10:54 am: Opening up neural engine to Core ML, which gets up to 9x faster on 1/10th the energy. Frees up GPU for other features like AR, which is another area we're focusing on this year.

10:55 am: ARKit 2, new Measure app, AR Quick Look brings items into the real-world with just a tap.

10:55 am: A12 Bionic enables next-generation apps. We've got three developers to briefly show you. Todd Howard from Bethesda Game Studios on stage for a demo.


10:56 am: I wrote my first game when I was 12 on an Apple II. It's amazing how far we've come. We can now start reaching for games that are more than simple diversions. Let's take a look at new Elder Scrolls game, Blades.


10:57 am: We can pull out all of the detail you'd usually miss from the light and the dark. Lighting can bounce off of the wall. Even reflect off of your sword. We can use stereo widening on the new iPhone to hear the forest around you without headphones.


10:58 am: What used to be limited to your living room is now available on your phone. We can pull off some incredible environments that just weren't possible before.

10:59 am: It's not just immersive, it transports you. Blades coming to iOS this fall. Available for pre-order now.


11:00 am: David Lee from Nex Team and NBA hall of famer Steve Nash on stage to talk about Homecourt.




11:01 am: New tool to revolutionize basketball training. Recognizes hoop and court automatically, then tracks makes and misses, drawn as an overlay on the court. Real-time player detection. Shot science...measures shooting form and more to analyze performance.

11:02 am: Gives players immediate feedback on form, release time, and more. As players train with real-time feedback, they gain muscle memory. Great for beginners and pros. Shipping as an update this fall.




11:03 am: Atli Mar from Directive Games on stage to introduce AR-generated arcade cabinet. And with multi-player AR, everybody can experience it together. Showing Galaga AR.


11:06 am: Now back to Phil. Talking about camera. You all know it's the most popular smartphone camera, and for great reason.

11:06 am: Showing a portrait mode photo that appeared on the cover of Time magazine.


11:09 am: You are going to be blown away with iPhone Xs dual camera system. 12MP wide-angle with all-new sensor, 12MP telephoto. Improved True Tone flash. On the front, TrueDepth 7MP camera has new sensor as well. Image signal processor works with CPU to set exposure, white balance, focus, noise reduction, etc. A12 Bionic does this better than before, but also connects it to the neural engine to do better face detection, facial landmarking with instant red-eye reduction, and better segmentation for portrait mode. 1 trillion operations per photo.






11:10 am: New Smart HDR feature. Takes HDR so much further. If subject is moving, A12 shoots a 4-frame buffer and interframes to bring out details. Plus a long exposure for better shadow detail. Automatically selects best parts of each and combines them for beautiful photos.












11:14 am: Showing examples of Smart HDR photos. Now showing breakthrough bokeh capabilities. New depth slider in portrait mode to adjust depth of field after taking the picture.




11:16 am: iPhone Xs has four microphones to record stereo sound. Showing demo video of cyclists.








11:17 am: Battery life: iPhone Xs has up to 30 minutes more than iPhone X. iPhone Xs Max up to 90 minutes longer than iPhone X.




11:19 am: Dual SIM capability...keep two phone numbers, two different plans, or travel with local plan. Dual SIM Dual Standby (DSDS): both lines are active, and whichever gets the call goes active. Uses eSIM, and software helps you easily keep track od which line is which. Needs carrier support, and we're working with many to roll it out this fall. Physical SIM and eSIM worldwide on Xs and Xs Max, except in China, where it's dual physical SIMs.


11:21 am: Recapping iPhone Xs features. Lisa Jackson on stage to talk environmental friendliness.

11:23 am: Apple now runs on 100% renewable energy. That includes Apple Park with solar panels and directed biogas. But also our data centers. People said it couldn't be done, but we did it. Now we're on to our next challenge...ending mining of materials. So let's take a look at material innovations in iPhone Xs. Now using recycled tin in the logic board. This prevents mining of over 10,000 tons of tin ore per year. Reducing use of traditional plastics and transitioning to recycled and bio-based.

11:25 am: Focus on durability. Everything back to the iPhone 5s runs iOS 12, and keeping devices longer is the best thing for the planet. And when you're done, we have Apple GiveBack. Bring it in or mail it in, and we'll assess it. Either give you value if it can be reused, or recycle it.

11:26 am: Phil back on stage. So iPhone Xs, iPhone Xs Max. They are stunning, best phones we've ever made. We want to reach as many customers as we can, so that's why we're excited to show you one more iPhone. Video time!






11:27 am: So excited to introduce you to the iPhone Xr. 7000 series aerospace grade aluminum. Incredible new finishes...white, black, blue, coral, yellow.






11:29 am: Even a Product Red one. All of these have IP67 protection against dust and liquids. Display is what strikes you. LCD, but for the first time goes edge to edge. Most advanced LCD ever in a smartphone...calling it Liquid Retina. 6.1" on the diagonal 1792x828, 326 ppi.






11:30 am: Tap to wake, 120 Hz touch sensitivity, True Tone, wide color, no home button. Same gestures as iPhone X. No 3D Touch, but new feature called Haptic touch. Face ID.






11:32 am: Faster Face ID algorithms, faster Secure Enclave. A12 Bionic chip with real-time machine learning. 12MP single camera. Same exact wide-angle camera as in Xs and Xs Max.




11:32 am: Can do portrait mode photos, showing examples. Same bokeh as Xs and Xs Max, and depth control.


11:34 am: TrueDepth camera with portrait selfies. Battery life 90 minutes longer than iPhone 8 Plus.




11:35 am: Huge day for iPhone...three new models. Showing a product video with Jony Ive.


11:38 am: iPhone Xs is completely uncompromising. iPhone Xs Max has the largest display ever on an iPhone. Custom developed stainless steel in three finishes including new gold. Better water and dust resistance, most durable glass ever on a smartphone. Face ID reinvents secure unlock, login, and payments. A12 Bionic is the smartest and most powerful chip ever in a smartphone. More advanced dual camera system and neural engine takes us to a new era of photography. Smart HDR gives us images like never before.


11:39 am: iPhone Xr integrates the same breakthrough technologies. Entirely new range of finishes. All-screen Liquid Retina display is most advanced and color accurate display in smartphone. Machine learning can recognize subjects, depth of field is adjustable, and more.

11:40 am: iPhone Xr in 64/128/256 GB options starting at $749. Pre-order October 19, shipping October 26.










11:41 am: iPhone Xs in 64/256/512 GB, starts at $999. iPhone Xs Max in same configurations starting at $1099. Pre-order September 14, ships September 21. Second wave comes just a week later on September 28. Fastest geographic rollout we've ever had.


11:41 am: iPhone 7 and 7 Plus from $449, iPhone 8 and 8 Plus from $599.






11:42 am: iOS 12 launches Monday.


11:43 am: Tim Cook back on stage with brief HomePod update. Talking about stereo pairing and AirPlay 2. Identify songs by lyrics, multiple timers, make and receive calls, find your iPhone. Apple TV to get Dolby Atmos. Updates coming Monday.


11:44 am: macOS Mojave coming September 24.

11:44 am: Tim is now recapping today's announcements.


11:46 am: Tim thanking everyone for watching, and everyone at Apple. Event is over.


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          MIT taught a neural network how to show its work      Cache   Translate Page      

MIT’s Lincoln Laboratory Intelligence and Decision Technologies Group yesterday unveiled a neural network capable of explaining its reasoning. It’s the latest attack on the black box problem, and a new tool for combating biased AI. Dubbed the Transparency by Design Network (TbD-net), MIT’s latest machine learning marvel is a neural network designed to answer complex questions about images. The network parses a query by breaking it down into subtasks that are handled by individual modules. If you asked it to determine the color of “the large square” in a picture showing several different shapes of varying size and color, for…

This story continues at The Next Web

          Prime Focus Introduces CLEAR Vision Cloud Module with Built-In Voice Search Functionality      Cache   Translate Page      
The CLEAR™ MAM Module of Media ERP Suite is used for building Machine Learning models for solving specific problems in collecting, curating and annotating content. The platform can identify complex sequences, actions and video segments. It is embedded with standard AI engines that offer intelligence by recognizing objects, faces, actors, locations, transcript, sound and individual video frames. The CLEAR Vision platform is now available with media recognition AI platform.

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          PRACTICAL SQL 2017 Online Training (Delhi)      Cache   Translate Page      
SQL School is one of the best training institutes for Microsoft SQL Server Developer Training, SQL DBA Training, MSBI Training, Power BI Training, Azure Training, Data Science Training, Python Training, Hadoop Training, Tableau Training, Machine Learning ...
          Apple iPhone Xs and iPhone Xs Max Launched      Cache   Translate Page      

The much awaited successor to the iPhone X is here. Apple has launched the brand new iPhone Xs and iPhone Xs Max, shedding the ‘Plus’ tag for its smartphone.

Design:

 

The devices are made of surgical grade stainless steel and have a gold finish on the front and glass back. The devices also have rounded corners. Apple claims to have used the most durable glass ever in a smartphone for the display. The devices also have a silver and space grey finish other than the gold finish. The iPhone Xs and iPhone Xs Max have IP68 dust and water protection.

Display:

The iPhone Xs has a Super Retina OLED, 5.8 inch display. This is a bigger display than the iPhone 8 Plus but an overall smaller device in size. The device has a native resolution of 2436 x 1125 pixels and a pixel density of 458 ppi.

The iPhone Xs Max has a massive 6.5 inch with a Super Retina OLED display. The display has a resolution of 2688 x 1242 and a pixel density of 458 ppi. The massive size of the iPhone Xs Max allows for a ‘split view’ in some apps while the device is in the horizontal position. This allows for more utility in one app.

The screen on both the devices have a 60 % greater dynamic range, offering better experiences than before.The devices also continue to support 3D touching and have True Tone display.

Processor:

The iPhone Xs and iPhone Xs Max use the highly anticipated A12 Bionic chip. This is the first 7 nanometer production chip in a smartphone and houses  6.9 billion transistors.  The iPhone Xs and iPhone Xs Max have a 6 core CPU. This consists of 2 high performance cores and 4 high efficiency cores. This makes the new iPhone 15 % faster while using 40 % lower power.

The GPU has 4 cores and is  50 % faster than A11 bionic. This gives a  huge jump in graphics, according to Apple. The Neural engine has an 8 core design compared to 2 cores on the A11. It also has Dedicated Machine Learning.

The new A12 bionic can process 5 trillion operations per second. The devices will be available in storage options of upto 512 GB internal storage.The A12 bionic also improves the daily use of the device. It helps apps launch upto 30% faster. Providing a smoother every day experience.

Camera:

 

The iPhone Xs and iPhone Xs Max have a dual rear camera setup. Apple has improved this setup and it features a 12 MP wide lens and a 12 Mp telephoto lens. This is supported by an improved true tone flash.The devices use larger sensors and the lenses have an aperture of f/1.8.The smartphones also have Optical Image Stabilisation

The front camera setup hosts a 7 MP sensor. The front true depth system contains the sensor along with an IR camera and dot projector. This also provides depth in selfie portraits.

The new A12 bionic has an Image signal processor (ISP). This works to automatically adjust exposure, white balance, focus, noise reduction, and many more features whenever an image is taken.The chip also connects the [...]

The post Apple iPhone Xs and iPhone Xs Max Launched appeared first on iGyaan Network.


          Apple Unveils iPhone XS And iPhone XS Max With Dual-SIM Support      Cache   Translate Page      
[Click here to view the video in this article]



Apple kicked off its ‘Gather Round’ flagship event on Wednesday, finally unleashing its new iPhones. Fans had a lot of fun guessing the names of iPhone X’s successors, and can now put their uncertainties to rest with the iPhone XS, iPhone XS Max, and iPhone XR.

“iPhone Tennis” jokes aside, 2018’s higher-end iPhone XS models are extensions of 2017’s iPhone X, and come with OLED screens, the notch, 3D Touch, and TrueDepth technology powering Face ID.

What sets them apart, though, is their supercharged performance, dual-SIM support, and ‘Super Retina’ resolutions.

They’re also decked in surgical-grade stainless steel, have IP68 water resistance, and are available in silver, space gray, as well as a new gold sheen.

Have a closer look at the new generation of flagship iPhones below.




Display



The iPhone XS has a 5.8-inch ‘Super Retina’ OLED display with a resolution of 2436 x 1125, and remarkably has 60-percent higher color dynamic than the iPhone X.

The iPhone XS Max, on the other hand, has Apple’s largest smartphone display yet with a ‘Super Retina’ OLED screen measuring 6.5 inches, as well as a 2688 x 1242 resolution. While it’s the same size as the iPhone 8, the end-to-end screen means there’s more to be seen.


Performance

This year, Apple decided to double down on performance. The XS models run on the new ‘A12 Bionic’ chip that promises to be 15-percent faster than the A11 chip—which Apple says was already the quickest processor in the smartphone industry—and with 40-percent less power.

To give you an idea of A12’s prowess, Apple says that while the A11 could run 600 million operations, the new chip can launch five trillion. The iPhones XS and XS Max are thus able to launch apps 30-percent quicker than iPhone X.

Apart from its speed, the all-new processor allows for machine learning to be processed 900-percent faster, sharpening the visual quality of features like ‘Memoji’ and Group ‘FaceTime’.

Coupled with the new iOS 12 performance updates, the two iPhones are expected to launch apps 30-percent faster.


Battery

The iPhone XS lasts 30 minutes longer than the iPhone X, which supposedly stayed alive for about 11 hours on a full charge.

The iPhone XS Max runs a little longer, and lasts about an hour-and-a-half longer than the iPhone X.


Camera



The iPhones are equipped with 12MP wide-angle dual-rear cameras and 7MP front cameras, which means they haven’t deviated much in physical design from that of the iPhone X.



More notably, Apple has introduced an all-powerful ‘Smart HDR’ feature, which snaps more photos at various exposures, including long exposures. The camera then chooses the best frames to stitch into the perfect picture.

Phil Schiller, Apple’s senior vice president of worldwide marketing, pointed out that you’re typically not supposed to point your camera at the sun, but ‘Smart HDR’ defies the odds by meticulously refining highlights and shadows in the image below.



There’s now also an option to toggle the depth-of-field of your snapshots for a more atmosphere feel. It’s the “new era of photography,” Schiller said.






Storage

Both iPhones can hold up to 512GB of storage, thanks to the new A12 chip. They’re also available in 64GB and 256GB options.


Dual-SIM Support



At long last, Apple has decided to pack its iPhones XS and XS Max with dual-SIM support, and it has its own name: ‘Dual SIM Dual Standby’ (DSDS).

Now, you’ll be able to have two different numbers and two different mobile carriers in one iPhone—perfect for work purposes. During incoming calls, the feature also lets you know which line is being called, so you’ll be able to ignore clients during vacations.


Colors



Both iPhones XS and XS Max come in three colorways: a brand new ‘Gold’, ‘Space Gray’, and ‘Silver’.


Price



Similar to last year’s iPhone X, the iPhone XS starts at US$999. The XS Max, on the other hand, starts at US$1,099.

Additionally, Apple removed the original iPhone X from its lineup, and has brought the starting prices of the home button-equipped iPhones 7 and 8 down to US$449 and US$599 respectively.



The iPhone XS and XS Max are poised for preorders on Friday, 14 September 2018, and will begin shipping the week after on Friday, 21 September 2018.

For more details on iPhone XR, please visit here.






[via Apple]
          Logistics Technology: How New Solutions Are Reshaping Supply Chains      Cache   Translate Page      
Technology has always played a critical freight transportation role, but there's never been a time with more solutions available, more focus on new and potentially transformative concepts, and more confusion about how to navigate this environment. From blockchain, machine learning, and autonomous vehicles to IoT, robotics and bots, shippers are...
          "Panic And Dismay": Leaked Video Reveals Distraught Google Execs Grappling With Hillary Clinton's Loss      Cache   Translate Page      

Days after Google was exposed trying to help Hillary Clinton win the 2016 election, a leaked "internal only" video published by Breitbart Senior Tech correspondent Allum Bokhari reveals a panel of Google executives who are absolutely beside themselves following Hillary Clinton's historic loss. 

The video is a full recording of Google’s first all-hands meeting following the 2016 election (these weekly meetings are known inside the company as “TGIF” or “Thank God It’s Friday” meetings). Sent to Breitbart News by an anonymous source, it features co-founders Larry Page and Sergey Brin, VPs Kent Walker and Eileen Naughton, CFO Ruth Porat, and CEO Sundar Pichai. -Breitbart

In the video, Brin can be heard comparing Trump supporters to fascists and extremists - arguing that like other extremists, Trump voters suffered from "boredom" which has, he claims, historically led to fascism and communism.

He then asks his company what they can do to ensure a "better quality of governance and decision-making." 

And according to Kent Walker, VP for Global Affairs, those who support populist causes like the MAGA movement are motivated by "fear, xenophobia, hatred and a desire for answers that may or may not be there." 

He later says that Google needs to fight to ensure that populist movements around the world are merely a "blip" and a "hiccup" in the arc of history that "bends towards progress." 

The video can be seen below, however scroll down for a list of timestamped segments to note, courtesy of Breitbart

 
  • (00:00:00 – 00:01:12) Google co-founder Sergey Brin states that the weekly meeting is “probably not the most joyous we’ve had” and that “most people here are pretty upset and pretty sad.”
  • (00:00:24) Brin contrasts the disappointment of Trump’s election with his excitement at the legalization of cannabis in California, triggering laughs and applause from the audience of Google employees.
  • (00:01:12) Returning to seriousness, Brin says he is “deeply offen[ded]” by the election of Trump, and that the election “conflicts with many of [Google’s] values.”
  • (00:09:10) Trying to explain the motivations of Trump supporters, Senior VP for Global Affairs, Kent Walker concludes: “fear, not just in the United States, but around the world is fueling concerns, xenophobia, hatred, and a desire for answers that may or may not be there.”
  • (00:09:35) Walker goes on to describe the Trump phenomenon as a sign of “tribalism that’s self-destructive [in] the long-term.”
  • (00:09:55) Striking an optimistic tone, Walker assures Google employees that despite the election, “history is on our side” and that the “moral arc of history bends towards progress.”
  • (00:10:45) Walker approvingly quotes former Italian Prime Minister Matteo Renzi’s comparison between “the world of the wall” with its “isolation and defensiveness” and the “world of the square, the piazza, the marketplace, where people come together into a community and enrich each other’s lives.”
  • (00:13:10) CFO Ruth Porat appears to break down in tears when discussing the election result.
  • (00:15:20) Porat promises that Google will “use the great strength and resources and reach we have to continue to advance really important values.”
  • (00:16:50) Stating “we all need a hug,” she then instructs the audience of Google employees to hug the person closest to them.
  • (00:20:24) Eileen Noughton, VP of People Operations, promises that Google’s policy team in DC is “all over” the immigration issue and that the company will “keep a close watch on it.”
  • (00:21:26) Noughton jokes about Google employees asking, ‘Can I move to Canada?’ after the election. She goes on to seriously discuss the options available to Google employees who wish to leave the country.
  • (00:23:12) Noughton does acknowledge “diversity of opinion and political persuasion” and notes that she has heard from conservative Google employees who say they “haven’t felt entirely comfortable revealing who [they] are.” and urged “tolerance.” (Several months later, the company would fire James Damore allegedly for disagreeing with progressive narratives.)
  • (00:27:00) Responding to a question about “filter bubbles,” Sundar Pichai promises to work towards “correcting” Google’s role in them
  • (00:27:30) Sergey Brin praises an audience member’s suggestion of increasing matched Google employee donations to progressive groups.
  • (00:34:40) Brin compares Trump voters to “extremists,” arguing for a correlation between the economic background of Trump supporters and the kinds of voters who back extremist movements. Brin says that “voting is not a rational act” and that not all of Trump’s support can be attributed to “income disparity.” He suggests that Trump voters might have been motivated by boredom rather than legitimate concerns.
  • (00:49:10) An employee asks if Google is willing to “invest in grassroots, hyper-local efforts to bring tools and services and understanding of Google products and knowledge” so that people can “make informed decisions that are best for themselves.” Pichai’s response: Google will ensure its “educational products” reach “segments of the population [they] are not [currently] fully reaching.”
  • (00:54:33) An employee asks what Google is going to do about “misinformation” and “fake news” shared by “low-information voters.” Pichai responds by stating that “investments in machine learning and AI” are a “big opportunity” to fix the problem.
  • (00:56:12) Responding to an audience member, Walker says Google must ensure the rise of populism doesn’t turn into “a world war or something catastrophic … and instead is a blip, a hiccup.”
  • (00:58:22) Brin compares Trump voters to supporters of fascism and communism, linking the former movement to “boredom,” which Brin previously linked to Trump voters. “It sort of sneaks up sometimes, really bad things” says Brin.
  • (01:01:15) A Google employee states: “speaking to white men, there’s an opportunity for you right now to understand your privilege” and urges employees to “go through the bias-busting training, read about privilege, read about the real history of oppression in our country.” He urges employees to “discuss the issues you are passionate about during Thanksgiving dinner and don’t back down and laugh it off when you hear the voice of oppression speak through metaphors.” Every executive on stage – the CEO, CFO, two VPs and the two Co-founders – applaud the employee.
  • (01:01:57) An audience member asks if the executives see “anything positive from this election result.” The audience of Google employees, and the executives on stage, burst into laughter. “Boy, that’s a really tough one right now” says Brin.

          Brave Browser Launches Trial for Relevant Public Advertisement Program for MacOS      Cache   Translate Page      

Brave Browser has announced the launch of a trial run for its relevant public advertisement program for MacOS users. The program is intended to help calibrate Brave’s machine learning advertisement model, which will serve to provide users 70 percent of the ad revenue for viewing content on the fully launched Brave browsing platform. The new […]

Post source: Brave Browser Launches Trial for Relevant Public Advertisement Program for MacOS

More Bitcoin News and Cryptocurrency News on TheBitcoinNews.com


          Google Ads no Brasil agora conta com recurso que usa AI para automatizar campanhas      Cache   Translate Page      
Com uso de machine learning, novo recurso permite a pequenas e médias empresas anunciar on-line de forma mais simples e obter resultados até três vezes melhores
          Facebook cria AI para identificar textos ofensivos em imagens e vídeos      Cache   Translate Page      
Chamado de Rosetta, sistema da rede social usa Machine Learning para analisar diaraiemente cerca de 1 bilhão de imagens e frames de vídeos no FB e no Instagram.
          Sr Professional, Science & Analytics - CoreLogic - Milwaukee, WI      Cache   Translate Page      
Perform pattern recognition model creation and training using various types of algorithms and machine learning modeling techniques for unknown or less well...
From CoreLogic - Tue, 04 Sep 2018 23:54:48 GMT - View all Milwaukee, WI jobs
          Socure Webinar to Explore Future of Robots in Digital Identity Verification      Cache   Translate Page      
...company's predictive analytics platform applies artificial intelligence and machine learning to trusted online/offline sources including email, phone, address, IP address, social media and traditional GLBA/DPPA data to authenticate identities in real-time. The Socure ID+ platform reduces fraud ...

          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page      
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:13 GMT - View all Seattle, WA jobs
          Data Architect - Remote West coast - Insight Enterprises, Inc. - Dallas, TX      Cache   Translate Page      
R, Azure Machine Learning. 2017 Arizona’s Most Admired Companies (AZ Business Magazine), 2016 Best Places to Work (Phoenix Business Journal)....
From Insight - Mon, 14 May 2018 23:57:10 GMT - View all Dallas, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Portland, OR      Cache   Translate Page      
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:10 GMT - View all Portland, OR jobs
          Consultant, Business Analytics & Data Science - Lincoln Financial - Boston, MA      Cache   Translate Page      
Phoenix, AZ (Arizona). Knowledge and experience on applying statistical and machine learning techniques on real business data....
From Lincoln Financial Group - Mon, 27 Aug 2018 18:47:26 GMT - View all Boston, MA jobs
          AWS Architect - Insight Enterprises, Inc. - Chicago, IL      Cache   Translate Page      
Database architecture, Big Data, Machine Learning, Business Intelligence, Advanced Analytics, Data Mining, ETL. Internal teammate application guidelines:....
From Insight - Thu, 12 Jul 2018 01:56:10 GMT - View all Chicago, IL jobs
          Più intelligenti e veloci, iPhone Xs e Xs Max non temono confronti      Cache   Translate Page      
Il nuovo melafonino con schermo Oled Super Retina si sdoppia nei formati 5,8 e 6,5 pollici. Il chip A12 Bionic porta miglioramenti di prestazioni di calcolo e grafiche, ma soprattutto potenzia il machine learning. Presentato a Cupertino anche l’Apple Watch Serie 4, con quadrante più grande.
          The Data Day: August 31, 2018      Cache   Translate Page      

AWS and VMware announce Amazon RDS on VMware. And more.

For @451Research clients: On the Yellowbrick road: data-warehousing vendor emerges with funding and flash-based EDW https://t.co/shKUTosHlS By @jmscrts

― Matt Aslett’s The Data Day (@thedataday) August 31, 2018

For @451Research clients: Automated analytics: the role of the machine in corporate decision-making https://t.co/3PkCXnGfhR By Krishna Roy

― Matt Aslett’s The Data Day (@thedataday) August 28, 2018

For @451Research clients: @prophix does cloud and on-premises CPM, with machine learning up next https://t.co/8FKKvRrJDb By Krishna Roy

― Matt Aslett’s The Data Day (@thedataday) August 28, 2018

AWS and VMware have announced Amazon Relational Database Service on VMware, supporting Microsoft SQL Server, Oracle, PostgreSQL, mysql, and MariaDB. https://t.co/hy5F1g8dTA

― Matt Aslett’s The Data Day (@thedataday) August 27, 2018

Cloudera has launched Cloudera Data Warehouse (previously Cloudera Analytic DB) as well as Cloudera Altus Data Warehouse as-a-service https://t.co/386z7HaT6Q and also Cloudera Workload XM, an intelligent workload experience management cloud service https://t.co/v5jGb3Hkp0

― Matt Aslett’s The Data Day (@thedataday) August 30, 2018

Alteryx has announced version 2018.3 of the Alteryx analytics platform, including Visualytics for real-time, interactive visualizations https://t.co/8ewTXJqs5T

― Matt Aslett’s The Data Day (@thedataday) August 28, 2018

Informatica has updated its Master Data Management, Intelligent Cloud Services and Data Privacy and Protection products with a focus on hybrid, multi-cloud and on-premises environments. https://t.co/eGGrA28trh

― Matt Aslett’s The Data Day (@thedataday) August 29, 2018

SnapLogic has announced the general availability of SnapLogic eXtreme, providing data transformation support for big data architectures in the cloud. https://t.co/NijnMNLTx0

― Matt Aslett’s The Data Day (@thedataday) August 28, 2018

VoltDB has enhanced its open source VoltDB Community Edition to support real-time data snapshots, advanced clustering technology, exporter services, manual scale-out on commodity servers and access to the VoltDB Management Console. https://t.co/tEHblf4J7v

― Matt Aslett’s The Data Day (@thedataday) August 30, 2018

ODPi has announced the Egeria project for the open sharing, exchange and governance of metadata https://t.co/tEb0jRHV8F

― Matt Aslett’s The Data Day (@thedataday) August 28, 2018

And that’s the data day


          Machine Learning with Swift      Cache   Translate Page      

eBook Details: Paperback: 378 pages Publisher: WOW! eBook (February 28, 2018) Language: English ISBN-10: 1787121518 ISBN-13: 978-1787121515 eBook Description: Machine Learning with Swift: Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease

The post Machine Learning with Swift appeared first on eBookee: Free eBooks & Video Tutorials Download.


          UR - Corporate Engineering - Precision Systems Engineer (Maplewood, MN) - 3M - Maplewood, MN      Cache   Translate Page      
Proactively collaborate with business partners to connect and extend process data management solutions with complimentary machine learning and analytics efforts...
From 3M - Wed, 05 Sep 2018 17:09:45 GMT - View all Maplewood, MN jobs
          Data Science Manager - Micron - Boise, ID      Cache   Translate Page      
Create server based visualization applications that use machine learning and predictive analytic to bring new insights and solution to the business....
From Micron - Wed, 05 Sep 2018 11:18:49 GMT - View all Boise, ID jobs
          Intern - Data Scientist (NAND) - Micron - Boise, ID      Cache   Translate Page      
Machine learning and other advanced analytical methods. To ensure our software meets Micron's internal standards....
From Micron - Wed, 29 Aug 2018 20:54:50 GMT - View all Boise, ID jobs
          Intern - Data Scientist (DRAM) - Micron - Boise, ID      Cache   Translate Page      
Machine learning and other advanced analytical methods. To ensure our software meets Micron's internal standards....
From Micron - Mon, 20 Aug 2018 20:48:37 GMT - View all Boise, ID jobs
          Data Analytics Specialist - Align Technology - San Jose, CA      Cache   Translate Page      
Experience with machine learning. Excellent understanding of machine learning techniques and algorithms....
From Align Technology - Thu, 28 Jun 2018 06:01:20 GMT - View all San Jose, CA jobs
          Enterprise Account Executive - Wade & Wendy - New York, NY      Cache   Translate Page      
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Mon, 10 Sep 2018 14:31:19 GMT - View all New York, NY jobs
          VP of Product - Wade & Wendy - New York, NY      Cache   Translate Page      
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Tue, 21 Aug 2018 18:51:24 GMT - View all New York, NY jobs
          Product Manager, Marketplace Growth - Wade & Wendy - New York, NY      Cache   Translate Page      
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sat, 14 Jul 2018 06:23:30 GMT - View all New York, NY jobs
          QA Engineer - Wade & Wendy - New York, NY      Cache   Translate Page      
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Fri, 08 Jun 2018 16:35:13 GMT - View all New York, NY jobs
          Data Scientist - Wade & Wendy - New York, NY      Cache   Translate Page      
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Tue, 05 Jun 2018 16:15:49 GMT - View all New York, NY jobs
          Back End Engineer - Wade & Wendy - New York, NY      Cache   Translate Page      
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sun, 03 Jun 2018 06:21:49 GMT - View all New York, NY jobs
          UI Engineer - Wade & Wendy - New York, NY      Cache   Translate Page      
Our team is backed by Slack, ffVC, Randstad and other great VCs, as we bring AI and machine learning to the recruiting/HR space - all in order to make the...
From Wade & Wendy - Sun, 27 May 2018 20:27:03 GMT - View all New York, NY jobs
          Senior Software Development Engineer - Distributed Computing Services (Hex) - Amazon.com - Seattle, WA      Cache   Translate Page      
Knowledge and experience with machine learning technologies. We enable Amazon’s internal developers to improve time-to-market by allowing them to simply launch...
From Amazon.com - Thu, 26 Jul 2018 19:20:25 GMT - View all Seattle, WA jobs
          Senior Site Reliability Engineer - Sift Science - Seattle, WA      Cache   Translate Page      
The Sift Science Trust PlatformTM uses real-time machine learning to accurately predict which users businesses can trust, and which ones they can't....
From Sift Science - Fri, 22 Jun 2018 20:18:59 GMT - View all Seattle, WA jobs
          Senior Software Engineer - Revenue Optimization - WeWork Global Technology - New York, NY      Cache   Translate Page      
Experience building Linear Programming solutions and Machine learning applications highly desired. Deep understanding of Amazon Web Services including ECS,...
From WeWork - Wed, 06 Jun 2018 05:19:01 GMT - View all New York, NY jobs
          Executive Director- Machine Learning & Big Data - JP Morgan Chase - Jersey City, NJ      Cache   Translate Page      
We would be partnering very closely with individual lines of business to build these solutions to run on either the internal and public cloud....
From JPMorgan Chase - Fri, 20 Jul 2018 13:57:18 GMT - View all Jersey City, NJ jobs
          Integration of Machine Learning and Deep Learning with GIS - the new paradigm      Cache   Translate Page      
none
          Cloudreach Boosts MultiCloud Effort with Relus Acquisition      Cache   Translate Page      
Relus is an AWS premier consulting partner. Cloudreach also gets expertise in machine learning and IoT-based applications with the acquisition.
          AI tracks down strange cosmic radio bursts      Cache   Translate Page      
A machine learning algorithm has located some mysterious cosmic radio bursts and the application has additionally been used to search for different types of signals which might suggest extraterrestrial intelligence.
          MLflow On-Demand Webinar and FAQ Now Available!      Cache   Translate Page      

On August 30th, our team hosted a live webinar—Introducing MLflow: Infrastructure for a complete Machine Learning lifecycle—with Matei Zaharia, Co-Founder and Chief Technologist at Databricks. In this webinar, we walked you through MLflow, a new open source project from Databricks that aims to design an open ML platform where organizations can use any ML library […]

The post MLflow On-Demand Webinar and FAQ Now Available! appeared first on Databricks.


          MACHINE LEARNING ENGINEER FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page      
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Engineer for Speech related Applications (6 months contract)....
From Huawei Canada - Mon, 18 Jun 2018 23:46:16 GMT - View all Montréal, QC jobs
          MACHINE LEARNING INTERN FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page      
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Intern for Speech related Applications....
From Huawei Canada - Mon, 18 Jun 2018 17:50:57 GMT - View all Montréal, QC jobs
          MACHINE LEARNING HARDWARE RESEARCHER OR DEVELOPER - Huawei Canada - Montréal, QC      Cache   Translate Page      
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Hardware Researcher or Developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:32 GMT - View all Montréal, QC jobs
          Machine Learning Software Developer - Huawei Canada - Montréal, QC      Cache   Translate Page      
We thank all applicants for their interest in career opportunities with Huawei. ML Software developer....
From Huawei Canada - Wed, 06 Jun 2018 23:47:31 GMT - View all Montréal, QC jobs
          Data Scientist - Yamaha - Cypress, CA      Cache   Translate Page      
Develop statistical models, machine learning-based tools or processes to measure and manage business performance....
From Yamaha - Wed, 22 Aug 2018 00:54:18 GMT - View all Cypress, CA jobs
          MapR packages services to help customers move up the AI learning curve      Cache   Translate Page      
MapR Technologies Inc. today announced six new data science service packages aimed at helping customers get started with machine learning and artificial intelligence. The customized offerings apply MapR data scientists to specific customer problems and projects to demonstrate the use of advanced analytics. The AI/ML Hack-a-thon has a MapR data science team working with an organization […]

The post MapR packages services to help customers move up the AI learning curve appeared first on SiliconANGLE.


          Principal Technologist - Machine Learning and Data Science - Blue Origin - Kent, WA      Cache   Translate Page      
While in this role, you will leverage your extensive experience in machine learning and data science to accelerate and innovate across business areas to drive...
From Blue Origin - Wed, 13 Jun 2018 05:31:45 GMT - View all Kent, WA jobs
          Google AI with Jeff Dean      Cache   Translate Page      

Jeff Dean, the lead of Google AI, is on the podcast this week to talk with Melanie and Mark about AI and machine learning research, his upcoming talk at Deep Learning Indaba and his educational pursuit of parallel processing and computer systems was how his career path got him into AI. We covered topics from his team’s work with TPUs and TensorFlow, the impact computer vision and speech recognition is having on AI advancements and how simulations are being used to help advance science in areas like quantum chemistry. We also discussed his passion for the development of AI talent in the content of Africa and the opening of Google AI Ghana. It’s a full episode where we cover a lot of ground. One piece of advice he left us with, “the way to do interesting things is to partner with people who know things you don’t.”

Listen for the end of the podcast where our colleague, Gabe Weiss, helps us answer the question of the week about how to get data from IoT core to display in real time on a web front end.

Jeff Dean

Jeff Dean joined Google in 1999 and is currently a Google Senior Fellow, leading Google AI and related research efforts. His teams are working on systems for speech recognition, computer vision, language understanding, and various other machine learning tasks. He has co-designed/implemented many generations of Google’s crawling, indexing, and query serving systems, and co-designed/implemented major pieces of Google’s initial advertising and AdSense for Content systems. He is also a co-designer and co-implementor of Google’s distributed computing infrastructure, including the MapReduce, BigTable and Spanner systems, protocol buffers, the open-source TensorFlow system for machine learning, and a variety of internal and external libraries and developer tools.

Jeff received a Ph.D. in Computer Science from the University of Washington in 1996, working with Craig Chambers on whole-program optimization techniques for object-oriented languages. He received a B.S. in computer science & economics from the University of Minnesota in 1990. He is a member of the National Academy of Engineering, and of the American Academy of Arts and Sciences, a Fellow of the Association for Computing Machinery (ACM), a Fellow of the American Association for the Advancement of Sciences (AAAS), and a winner of the ACM Prize in Computing.

Cool things of the week
  • Google Dataset Search is in beta site
  • Expanding our Public Datasets for geospatial and ML-based analytics blog
    • Zip Code Tabulation Area (ZCTA) site
  • Google AI and Kaggle Inclusive Images Challenge site
  • We are rated in the top 100 technology podcasts on iTunes site
  • What makes TPUs fine-tuned for deep learning? blog
Interview
  • Jeff Dean on Google AI profile
  • Deep Learning Indaba site
  • Google AI site
  • Google AI in Ghana blog
  • Google Brain site
  • Google Cloud site
  • DeepMind site
  • Cloud TPU site
  • Google I/O Effective ML with Cloud TPUs video
  • Liquid cooling system article
  • DAWNBench Results site
  • Waymo (Alphabet’s Autonomous Car) site
  • DeepMind AlphaGo site
  • Open AI Dota 2 blog
  • Moustapha Cisse profile
  • Sanjay Ghemawat profile
  • Neural Information Processing Systems Conference site
  • Previous Podcasts
    • GCP Podcast Episode 117: Cloud AI with Dr. Fei-Fei Li podcast
    • GCP Podcast Episode 136: Robotics, Navigation, and Reinforcement Learning with Raia Hadsell podcast
    • TWiML & AI Systems and Software for ML at Scale with Jeff Dean podcast
  • Additional Resources
    • arXiv.org site
    • Chris Olah blog
    • Distill Journal site
    • Google’s Machine Learning Crash Course site
    • Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville book and site
    • NAE Grand Challenges for Engineering site
    • Senior Thesis Parallel Implementations of Neural Network Training: Two Back-Propagation Approaches by Jeff Dean paper and tweet
    • Machine Learning for Systems and Systems for Machine Learning slides
Question of the week

How do I get data from IoT core to display in real time on a web front end?

  • Building IoT Applications on Google Cloud video
  • MQTT site
  • Cloud Pub/Sub site
  • Cloud Functions site
  • Cloud Firestore site
Where can you find us next?

Melanie is at Deep Learning Indaba and Mark is at Tokyo NEXT. We’ll both be at Strangeloop end of the month.

Gabe will be at Cloud Next London and the IoT World Congress.


          Machine Learning with Swift      Cache   Translate Page      
none
          FICO Makes Artificial Intelligence Explainable with Latest Release of its Analytics Workbench      Cache   Translate Page      
Leading analytics firm FICO announced the latest version of FICO® Analytics Workbench™, a cloud-based advanced analytics development environment that empowers business users and data scientists with sophisticated, yet easy-to-use, data exploration, visual data wrangling, decision strategy design and machine learning.
          Machine Learning Engineer - TECHNICA CORPORATION - Dulles, VA      Cache   Translate Page      
Technica Corporation is seeking a Machine Learning. Engineer to support our internal Innovation, Research....
From Technica Corporation - Thu, 23 Aug 2018 10:27:08 GMT - View all Dulles, VA jobs
          Richmond Global Compass opens ESG fund to outside investors      Cache   Translate Page      
Opalesque Industry Update - Richmond Global Compass Capital, LP, the first-ever sustainability focused global multi-asset fund employing machine learning to extract material metrics in Environment, Social, and Governance, is now officially open to outside investment. Compass' general partners have i...
Article Link
          (Senior) Product Specialist - SAP Machine Learning for Sales and Service - SAP - Walldorf      Cache   Translate Page      
SAP's vision for Machine Learning is to focus on solving real business problems that will have huge business impact....
Gefunden bei SAP - Wed, 04 Jul 2018 11:34:10 GMT - Zeige alle Walldorf Jobs
          Senior Developer/Development Architect SAP S/4 HANA & SAP Cloud Platform (F/M) SAP INNOVATIVE B - SAP - Sankt Leon-Rot      Cache   Translate Page      
We make innovation real by using the latest technologies around the Internet of Things, blockchain, artificial intelligence / machine learning, and big data and...
Gefunden bei SAP - Tue, 11 Sep 2018 17:37:26 GMT - Zeige alle Sankt Leon-Rot Jobs
          Management Assistant (f/m) SAP Innovative Business Solutions - SAP - Sankt Leon-Rot      Cache   Translate Page      
We make innovation real by using the latest technologies around the Internet of Things, blockchain, artificial intelligence / machine learning, and big data and...
Gefunden bei SAP - Tue, 11 Sep 2018 17:36:57 GMT - Zeige alle Sankt Leon-Rot Jobs
          Google and the God-Emperor      Cache   Translate Page      
Allum Bokhari breaks the news of a video showing the reaction of Google's executives to the ascension of the God-Emperor:
A video recorded by Google shortly after the 2016 presidential election reveals an atmosphere of panic and dismay amongst the tech giant’s leadership, coupled with a determination to thwart both the Trump agenda and the broader populist movement emerging around the globe.

The video is a full recording of Google’s first all-hands meeting following the 2016 election (these weekly meetings are known inside the company as “TGIF” or “Thank God It’s Friday” meetings). Sent to Breitbart News by an anonymous source, it features co-founders Larry Page and Sergey Brin, VPs Kent Walker and Eileen Naughton, CFO Ruth Porat, and CEO Sundar Pichai. It can be watched in full above. It can and should be watched in full above in order to get the full context of the meeting and the statements made.

It was reported earlier this week that Google tried to boost turnout among the Latino population to help Hillary Clinton, only to be dismayed as the usually solid Democratic voting bloc switched to the GOP in record numbers. This video shows a similar level of dismay among Google’s most high-profile figures.

These individuals, who preside over a company with unrivaled influence over the flow of information, can be seen disparaging the motivations of Trump voters and plotting ways to use their vast resources to thwart the Trump agenda.

Co-founder Sergey Brin can be heard comparing Trump supporters to fascists and extremists. Brin argues that like other extremists, Trump voters were motivated by “boredom,” which he says in the past led to fascism and communism.

The Google co-founder then asks his company to consider what it can do to ensure a “better quality of governance and decision-making.”

VP for Global Affairs Kent Walker argues that supporters of populist causes like the Trump campaign are motivated by “fear, xenophobia, hatred, and a desire for answers that may or may not be there.”

Later, Walker says that Google should fight to ensure the populist movement – not just in the U.S. but around the world – is merely a “blip” and a “hiccup” in a historical arc that “bends toward progress.”

CEO Sundar Pichai states that the company will develop machine learning and A.I. to combat what an employee described as “misinformation” shared by “low-information voters.”
Well, it's hardly as if we didn't know these people were openly and avowedly against the duly-elected President of the United States. But to see it, and hear it, confirmed so shamelessly is still rather shocking. They clearly cannot be trusted with even a modicum of monopoly power over the American people; AT&T was broken up for less.
          Ad Targeting Tool Leverages Real-World Relationships to Influence Buying Decisions      Cache   Translate Page      
Ad Targeting Tool Leverages Real-World Relationships to Influence Buying Decisions#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000 AdTheorent, which offers a machine learning platform for advertisers, has announced AdTheorent Relationship Targeting. This new product allows advertisers to harness the power of relationships with family members, cohabitants or friends to influence a consumer to take desired actions. Word ... Reported by E-Commerce Times 35 minutes ago.
          Instructor (Data Science, Artificial Intelligence, Machine Learning) - Cortechma Inc. - Thornhill, ON      Cache   Translate Page      
Cortechma Academy team is looking for professors, instructors and engineers with both academically and professionally strong background specializing in one of...
From Indeed - Wed, 01 Aug 2018 16:56:17 GMT - View all Thornhill, ON jobs
          Richmond Global Compass opens ESG fund to outside investors      Cache   Translate Page      
Opalesque Industry Update - Richmond Global Compass Capital, LP, the first-ever sustainability focused global multi-asset fund employing machine learning to extract material metrics in Environment, Social, and Governance, is now officially open to outside investment. Compass' general partners have invested over $20 million as part of the fund's seed capital and seek to raise $500 million. Foun...
Article Link
          Top KDnuggets tweets, Sep 5-11: 10 Free Must-Read Books for Machine Learning and Data Science      Cache   Translate Page      
Also: Data Science Cheat Sheet; Machine Learning Cheat Sheets; Journey to Machine Learning - 100 Days of ML Code.
          KDnuggets™ News 18:n34, Sep 12: Essential Math for Data Science; 100 Days of Machine Learning Code; Drop Dropout      Cache   Translate Page      
Also: Neural Networks and Deep Learning: A Textbook; Don't Use Dropout in Convolutional Networks; Ultimate Guide to Getting Started with TensorFlow.
          Comment on Phil Young: How machine learning will shake-up advice by Jim Vernall      Cache   Translate Page      
Am I right in thinking the Titanic had insufficient life boats?
          Nvidia launches the Tesla T4, its fastest data center inferencing platform yet      Cache   Translate Page      
Nvidia today announced its new GPU for machine learning and inferencing in the data center. The new Tesla T4 GPUs (where the ‘T’ stands for Nvidia’s new Turing architecture) are the successors to the current batch of P4 GPUs that virtually every major cloud computing provider now offers. Google, Nvidia said, will be among the […]
          Nvidia launches the Tesla T4, its fastest data center inferencing platform yet      Cache   Translate Page      
Nvidia today announced its new GPU for machine learning and inferencing in the data center. The new Tesla T4 GPUs (where the ‘T’ stands for Nvidia’s new Turing architecture) are the successors to the current batch of P4 GPUs that virtually every major cloud computing provider now offers. Google, Nvidia said, will be among the […]
          Desenvolvedor Java para projetos de IA e Machine Learning - Hop - Belo Horizonte, MG      Cache   Translate Page      
Nós somos a Hop, uma empresa que nasceu para dar vida às ideias inovadoras! Unimos metodologias de Design com Inteligência Artificial e Computação Cognitiva...
De Hop - Tue, 24 Jul 2018 13:51:19 GMT - Visualizar todas as empregos: Belo Horizonte, MG
          Go RVing Study Details Online Habits of New RVers      Cache   Translate Page      
Go RVing recently published a detailed report examining how the RV consumer of the future will use technology so that Go RVing could pinpoint the best ways to reach out to those potential customers. They called upon Influential, a company that uses IBM’s WATSON to join machine learning and natural language processing (NLP) to analyze the […]
          MIT taught a neural network how to show its work      Cache   Translate Page      

MIT’s Lincoln Laboratory Intelligence and Decision Technologies Group yesterday unveiled a neural network capable of explaining its reasoning. It’s the latest attack on the black box problem, and a new tool for combating biased AI. Dubbed the Transparency by Design Network (TbD-net), MIT’s latest machine learning marvel is a neural network designed to answer complex questions about images. The network parses a query by breaking it down into subtasks that are handled by individual modules. If you asked it to determine the color of “the large square” in a picture showing several different shapes of varying size and color, for…

This story continues at The Next Web
          UR - Corporate Engineering - Precision Systems Engineer (Maplewood, MN) - 3M - Maplewood, MN      Cache   Translate Page      
Proactively collaborate with business partners to connect and extend process data management solutions with complimentary machine learning and analytics efforts...
From 3M - Wed, 05 Sep 2018 17:09:45 GMT - View all Maplewood, MN jobs
          Sr. Product Marketing Manager - Automation Anywhere - San Jose, CA      Cache   Translate Page      
Experience in artificial intelligence, analytics, machine learning or business process management software especially in the enterprise space is a big plus but...
From Automation Anywhere - Sat, 16 Jun 2018 05:57:32 GMT - View all San Jose, CA jobs
          Director, Product Marketing - Security - Automation Anywhere - San Jose, CA      Cache   Translate Page      
Experience in artificial intelligence, analytics, machine learning or business process management software especially in the enterprise space is a big plus but...
From Automation Anywhere - Sat, 16 Jun 2018 05:57:32 GMT - View all San Jose, CA jobs
          Igloo Software launches new products at ICE conference      Cache   Translate Page      
SAN ANTONIO, TX – Kitchener-based intranet solution provider Igloo launches a partnership with California’s Lucidworks to “augment search capabilities with artificial intelligence, machine learning, and natural language processing.” A Sept. 12 press release said that the technology provided by Lucidworks, a company that helps build search-driven solutions, will help Igloo customers searching for content, in…
          베일 벗은 아이폰Xs & Xs Max, 소문보다 더 똑똑해진 아이폰.      Cache   Translate Page      

  미국 캘리포니아 현지 시간으로 9월 12일 오전 10시(한국 시간 13일 새벽 2시), 애플 파크(Apple Park, Head Office) 내에 자리한 스티브잡스 시어터(Steve Jobs Theater)에서 애플워치 시리즈4, 아이폰Xs, 아이폰Xs 맥스, 아이폰Xr 등 애플의 새로운 모바일 제품들이 공개되었습니다. 매년 그래왔듯이 이번에도 역시 디자인과 기본 스펙 등 하드웨어적인 요소들은 오래전부터 여러 매체들을 통해 알려진 루머를 피해갈 수 없었지만, 애플은 소프트웨어적으로 새로운 면모를 여러가지 보여주면서 많은 이들의 시선을 사로잡았습니다.

△ 한국 시간으로 13일 새벽 2시,

애플의 iPhone Xs, iPhone Xs Max, iPhone Xr이 모습을 드러냈다.

오는 9월 21일부터 1차 출시국에서 Xs/Xs Max가 공식 출시된다.


- 베일 벗은 iPhone Xs & Xs Max, 소문보다 더 똑똑해진 아이폰.

  5.8인치와 6.5인치 크기의 OLED디스플레이, A12바이오닉 탑재로 더욱 강력해진 성능, 더 길어진 배터리 지속 시간, 향상된 성능의 페이스ID, 블루투스 5.0, 무선 충전 기능의 향상, IP68 수준으로 높아진 등급의 방수 방진 기능, 듀얼심(Dual SIM) 등 익히 알려진 대로 '하드웨어'면에서는 한 층 향상된 면모를 보여주었습니다. 또한 '골드 색상(Gold Color)'이 추가되면서 골드, 실버, 스페이스 그레이 등 3가지 컬러의 제품이 판매될 예정인데 이 또한 루머를 통해 익히 알려졌던 내용입니다. 이처럼 하드웨어적인 측면의 여러가지 요소들은 소문을 확인하는 데 그쳤지만 한편으로는 머신 러닝(machine learning) 기능의 적용, 좀 더 똑똑해진 시리(Siri shortcuts), 증강현실(AR) 기능 강화, 똑똑해진 카메라와 조리개 값 수동 조절 옵션 제공 등 소프트웨어적으로 좀 더 강력해진 기능을 선보이면서 '애플' 다운 면모를 보여주었습니다.

△ iPhone Xs Max, Gold color

△ 6.5인치 Xs Max와 5.8인치 Xs


< iPhone Xs / iPhone Xs Max 기본 정보/스펙 >

 

 iPhone Xs

iPhone Xs Max 

참고

화면 크기 

5.8인치(2436x1125)

6.5인치(2688x1242)

갤노트9 - 6.38인치

방수/방진 기능

IP68 

IP68 

갤노트9 - IP68

배터리

2800mAh 

3400mAh 

갤노트9 - 4000mAh 
아이폰8플러스 - 2691mAh 

아이폰X - 2716mAh

메인 프로세서

A12 Bionic(7nm)

A12 Bionic(7nm) 

 

메인 카메라

1200만 화소 듀얼, smart HDR 

1200만 화소 듀얼, smart HDR 

갤노트9 - 1200만 듀얼

 셀피 카메라

700만, f/2.2 

700만, f/2.2 

노트9 - 800만, f/1.7 

 동영상

4k, 60fps 

4k, 60fps 

아이폰Xr - 4k, 60fps 

컬러 옵션

실버, 스페이스그레이, 골드 

실버, 스그, 골드 

'골드' 색상 추가 

저장 공간 옵션

64GB / 256GB / 512GB 

64 / 256 / 512 GB 

512GB 추가

가격(64GB)

999달러 

1099달러

갤노트9 미국 가격 - 999.99 달러

(공홈 언락폰 128GB) 

한국 예상 가격

130만원 중반 

140만원 중반 

한국 갤노트9 - 109만 4500원 

1차 출시국 예약 판매 시작

9월 14일

9월 14일  

아이폰Xr - 10월 19일

1차 출시국 출시일

9월 21일 

9월 21일 

아이폰Xr - 10월 26일

2차 출시국 출시일

9월 28일 

9월 28일 

한국 미포함. 

 '아이폰Xs/Xs맥스'에서 주목할 만한 부분은 머신러닝 기능이 도입됐다는 것과 애플이 작년부터 본격적으로 선보인 증강현실(AR)기능이 더욱 향상됐다는 점입니다. AR의 경우에는 '게임' 콘텐츠, 일상 생활과 관련하여 진화를 거듭하고 있다는 점을 눈여겨 볼 만 합니다. 또한 '머신러닝' 기능을 도입했다는 점에서 '아이폰' 스스로 사용자에게 최적화된 서비스를 제공할 수 있는 스마트폰으로 거듭났다는 점을 강조했는데, 이같은 변화는 '스마트폰'의 '스마트화'를 촉진할 것으로 예상되고 있습니다. 


△ 애플은 새로운 아이폰이 여러가지 면에서 업그레이드 되었다고 밝혔다.

△ 증강현실(AR) 기능이 더욱 강화되었다.

△ 좀 더 똑똑해진 시리.

애플은 러신머닝 기술을 적용하여 '똑똑해진 아이폰'을 구현했다고 밝혔다.


  또한 애플은 다른 스마트폰 기업들과 마찬가지로 '카메라'에 많은 역량을 투입하고 있다는 것을 보여주었습니다. 애플 역시 다른 기업들이 인공지능 기능을 카메라에 적용하고 있는 것과 궤를 같이하여 '최적화된 사진'을 찍을 수 있도록 했으며, 조리개 값을 사용자가 조절할 수 있도록 함으로써 기호에 맞는 초상화모드(bokeh mode) 사진을 만들 수 있도록 한 점도 눈에 띄는 점입니다.

△ 사진과 동영상 등 카메라 기능에 많은 역량을 투입한 애플.

△ 아이폰Xs & Xs Max의 메인 카메라 스펙.

△ 사용자가 조리개 값을 조절할 수 있도록 함으로써

 '초상화 모드' 사진을 기호에 맞게 찍을 수 있게 했다.


  가격적인 측면에서는 5.8인치 '아이폰Xs'가 999달러, 6.5인치 '아이폰Xs Max'가 1099달러(64GB)로 책정되면서 여전히 '높은 가격'을 유지하고 있음을 보여주었습니다. 기존에 전문가들은 '가격 인하'를 점치면서 '아이폰Xs'가 899달러에 판매될 것이라는 전망을 내놓았지만 애플은 '고가 정책'을 고수하는 모습을 보여주었습니다. '아이폰Xr'의 가격은 749달러로 최근 알려진 가격과 동일했으며, '아이폰X'는 단종되었습니다. '아이폰8'의 가격은 기존에 699달러에서 100달러 저렴해진 599달러로 내려갔습니다.


△ 아이폰Xs의 가격은 999달러, Xs 맥스의 가격은 1099달러이다.

아이폰X는 단종되었으며, 아이폰8의 가격은 100달러 저렴해진 599달러로 내려갔다.

△ 9월 21일 1차 출시국에서의 출시 이후, 

9월 28일에는 2차 출시국에서의 출시가 예정되어 있음을 이야기했다.

하지만 한국은 2차 출시국에 포함되지 않았으며,

작년의 경우와 비슷하게 10월 말, 'iPhone XR'이 출시될 때, 한국 출시가 이루어질 것으로 예상되고 있다.

△ 749달러, 보급형 제품인 'iPhone XR'

비교적 저렴한 가격, 페이스ID 탑재, 다양한 컬러 옵션 등으로 큰 인기를 누릴 것으로 예상되고 있다.

출시는 10월 26일이다.


  애플은 iPhone Xs와 Xs Max의 1차 출시국 출시일은 9월 21일이라고 밝혔지만, 6.1인치 보급형 제품인 'iPhone XR'의 출시일이 10월 26일이 될 것이라고 밝혔습니다. 많은 이들이 보급형 제품을 기다리고 있는 것으로 파악되고 있기에 '고가'의 Xs/Xs Max가 과연 한 달 동안 어떤 성과를 거둘 것인지도 큰 관심사 중 하나라 할 수 있습니다. 한편, 우리나라는 작년의 경우와 같이 '아이폰XR'이 출시될 즈음 '아이폰Xs/Xs 맥스'도 함께 출시될 것으로 예상되고 있습니다. 과연 애플이 예약판매에서 어떤 성과를 거두게 될 지 관심있게 지켜봐야겠습니다. 감사합니다.




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          Revive: Apple presenta tres nuevos iPhone      Cache   Translate Page      

La fecha esperada por los amantes de la tecnología finalmente llegó. Desde su sede en Cupertino, California, Apple presentó sus nuevos productos.

En el evento, tal y como se esperaba la compañía dio a conocer tres versiones de su teléfono y nuevos tamaños de pantalla.

La empresa fundada por Steve Jobs presentó un equipo bajo el nombre de iPhone XS, el cual tiene mejoras internas y de software; además de otro con pantalla más grande, bajo el nombre de iPhone XS Max. Asimismo, se cumplió el tercer rumor y se presentó un tercer equipo, bajo el nombre de iPhone Xr.

Revive a continuación cómo fue la presentación de todos estos productos, además de actualizaciones en el AppleWatch.


Finalmente, con un repaso de todo lo presentado y agradecimientos a quienes lo hacen posible, Tim terminó lo que llamó un "día mágico".


Otro anuncio importante: iOS 12 estará disponible a partir del 17 de septiembre.


En cuanto a costos y almacenamiento, esto es lo que ha develado Apple:

/media/top5/apple14sep18jpg.jpg /media/top5/apple15sep18jpg.jpg
/media/top5/apple13sep18jpg.jpg

En cuanto a batería, la del Xr dura una hora y media más que la del iPhone 8 Plus.


La cámara trasera del Xr es de 12MP, otras características son estabilización óptica, nuevo sensor, mejor apertura y el nuevo True Tone flash.


En cuanto a otras características, tiene el mismo Face ID que el Xs, así como gestos y control, pero no tiene 3D Touch.


/media/top5/apple12sep18jpg.jpg

El Xr cuenta con un LCD display, por primera vez sin bordes, el LCD más avanzado que se ha utilizado en un smartphone. Por si fuera poco, tiene Liquid Retina.


La búsqueda de Apple, mencionan, ha sido siempre llegar al mayor número de clientes, por ello, confirman el tercer rumor y presentan un tercer nuevo iPhone, el Xr.


Este nuevo producto cuenta además con Dual SIM, no sólo para llevar dos teléfonos, sino para usar planes de datos locales al viajar.


La batería del iPhone Xs dura 30 minutos más que en un iPhone X, y la del Max dura más de una hora y media que este modelo anterior.


Schiller también habla de la grabación de video, que ahora captura sonido estéreo y tiene un sensor dos veces más rápido.


Con las nuevas características, es posible tomar fotografías en las que se juegue con el fondo, pero además, éste puede ser editado en cuanto a profundidad incluso ya cuando la fotografía ha sido guardada, según se mostró en un video.

/media/top5/apple11sep18jpg.jpg
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Llegó el momento de hablar de la cámara, cuenta con dos, de 12MP, tiene nuevo sensor más grande para ganar en detalle y una nueva característica llamada Smart HDR.


Este nuevo iPhone, cuenta con una nueva generación de Machine Learning en tiempo real, además Siri llega a aprender tanto de tu comportamiento que prepara flujos de rutinas habituales.


/media/top5/apple8sep18jpg.jpg

Más novedades: A12 Bionic; la inclusión del primer chip de 7 nanómetros. 6.9 millones de transistores. Tiene un CPU de 6 núcleos que ha sido diseñado para ser un 15% mas rápido y con un consumo energético 40% menor. El Neural Engine tiene 8 núcleos. Como primera opción tiene 512GB como almacenamiento. Sencillamente, impresionante.


En cuanto a su Face ID, tiene algoritmos más rápidos y la protección de detección ha mejorado.


Ha sido creado también un iPhone Xs Max, que incluye sonido estéreo en altavoces más potentes.


iPhone Xs viene en tres colores, oro, plata y gris espacial. Según Schiller, el modelo normal tiene 5.5" y 6.5", "la pantalla más grande jamás puesta en un iPhone".

/media/top5/apple7sep18jpg.jpg

Primer rumor confirmado, se habla del iPhone Xs, calificado como "el más hermoso iPhone" que haya hecho Apple, en palabras de sus creadores.


Regresa Tim al escenario y finalmente pasa a lo que más se esperaba... ¡toca el turno de hablar del iPhone!


/media/top5/apple6sep18jpg.jpg

Los precios de esta nueva serie van desde los 399 dólares y 499 dólares con celular; además, el serie 3 baja de precio a 279 dólares.


/media/top5/apple5sep18jpg.jpg

Estas son algunas de las características de la serie 4 del AppleWatch, que contará, según Jeff, con la misma batería que series anteriores; es decir, durará lo mismo.


/media/top5/apple4sep18jpg.jpg

Ahora el AppleWatch cuenta con un increíble sensor cardíaco que incluso es capaz de tomar electrocardiogramas, puede detectar arritmias y notifica si hay algún problema posible con tu corazón.


Por supuesto, el procesador también ha sido mejorado. 64-Bit Dual Core, según Apple dos veces mas rápido que versiones anteriores. Se incluye un nuevo chip S4.

/media/top5/apple3sep18jpg.jpg

El sonido fue mejorado de forma que "no creerán que se escucha de este dispositivo", según Jeff, quien además anuncia una reubicación del micrófono.


El nuevo reloj tiene un diseño sin bordes, en sus distintas versiones, es 35% y 32% más largo. Espectaculares nuevas watch faces.


/media/top5/apple2sep18jpg.jpg

Enseguida, Jeff sobre el escenario, habla de la calificada como "nueva generación del Apple Watch".


De inmediato, Tim dio paso a hablar del Apple Watch, que, dijo, ha redefinido lo que un reloj puede hacer.


Tras el video, Tim Cook llegó al escenario, quien hizo un recuento de la historia de Apple con algunos de sus hitos más importantes.


La presentación comenzó con un video al más puro estilo de Misión Imposible.

/media/top5/apple1sep18jpg.jpg

¡FINALMENTE INICIÓ EL EVENTO! Sigue la cobertura al momento con nosotros.

/media/top5/Dm5ERkTXcAEn0vijpg.jpg

Como ocurre en cada presentación, la Apple Store en línea ha sido cerrada, antes del anuncio de los nuevos productos de la empresa.


Así luce el Auditorio Steve Jobs de Apple, a la espera de que arranque su evento:

/media/top5/Dm6E3CGXgAEKEZgjpg.jpg

Antes de que iniciara la presentación, en redes se ha filtrado que el código de la página web de Apple habría revelado los nombres de los nuevos modelos de iPhone. Esta es la imagen que circula:

/media/top5/Dm6GJ5QWwAE1Z0sjpg.jpg

Más información en El Siglo de Torreón


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          Apple présente l’iPhone XS (Max), l’iPhone XR, et de nouvelles Apple Watch      Cache   Translate Page      

Tim Cook a réussi son pari : les secrets d’Apple ne sortent plus des chaînes de production chinoises. Désormais, ils sortent directement des bureaux de Cupertino. En laissant traîner des images et des fichiers sur ses serveurs, Apple a (un peu) gâché la surprise de son événement « Gather round ». Pas de quoi tempérer l’enthousiasme que peut susciter la présentation de trois nouveaux iPhone et d’une nouvelle Apple Watch.

Retrouvez notre couverture minute par minute sur LeKeynote.fr.

iPhone XS et XS Max : des iPhone taille XXL

Nous sommes dans une année « S » : le successeur de l’iPhone X s’appelle logiquement l’iPhone XS1. Mais nous ne sommes pas une année sans nouveauté : l’iPhone XS, qui reprend l’écran 5,8 pouces de son prédécesseur, est accompagné par l’iPhone XS Max, doté d’un écran 6,5 pouces. Le voilà, le successeur de l’iPad mini… sauf qu’il n’est pas beaucoup plus encombrant que l’iPhone 8 Plus.

Les nouveaux iPhone XS.

Le nom « Max » a fait couler beaucoup d’encre, mais est plutôt censé, puisque le grand iPhone XS ne propose rien de plus que le petit. Il s’agit du même iPhone, en plus grand. Ainsi, les deux appareils possèdent un écran OLED d’une résolution de 458 ppp, doté d’une couche tactile (mais pas d’un affichage) à 120 Hz, offrant une gamme dynamique 60 % plus étendue que celle de l’écran de l’iPhone X, et surmonté d’un capteur Face ID plus rapide.

Les deux appareils sont certifiés IP68, et devraient donc résister pendant 30 minutes sous deux mètres d’eau. Les deux appareils intègrent un nouveau système sonore au champ stéréo élargi. Et les deux appareils embarquent la puce A12 Bionic, la première gravée à 7 nm mise sur le marché. Son processeur possède six cœurs, deux plus puissants et quatre plus économes, tous à la fois plus puissants et plus économes.

Le nouveau coloris acier doré. Une Apple Watch Series 4 assortie est disponible.

La puce graphique maison à quatre cœurs est 50 % plus rapide que celle de l’A11 Bionic, et surtout, le Neural Engine à huit cœurs est désormais capable de réaliser 5 billions d’opérations dédiées au machine learning par seconde. Ces chiffres peuvent sembler f(l)ous, mais se traduiront concrètement par des opérations plus fluides, un appareil photo plus précis et plus rapide, et un boom des performances des tâches liées à CoreML et ARKit.

Puisque l’on parle d’appareil photo : quand d’autres dépassent les 20 Mpx, Apple reste mordicus à 12 Mpx, mais continue d’améliorer le capteur et le processeur de traitement d’image. Un nouveau capteur aux photosites de 1,4 µm, qui devrait mieux résister à la montée en sensibilité, se cache derrière l’objectif grand-angle. Les deux objectifs sont toujours stabilisés, mais l’ouverture reste (relativement) limitée à f/1.8 en grand-angle et f/2.4 en télé — sauf en mode portrait, où elle peut atteindre f/1.4.

La simulation de l’ouverture en mode portrait, sur l’iPhone XS.

L’astuce ? Le logiciel travaille avec le matériel pour mieux détecter les différents plans de l’image, et simuler l’ouverture de l’objectif, que l’on pourra modifier après coup entre f/1.4 et f/16. De la même manière, le mode HDR a été considérablement amélioré, au point qu’Apple parle de « Smart HDR ». Les progrès résident moins dans le capteur et l’optique que dans le traitement, Google l’a montré avec ses Pixel. Nous sommes entrés dans l’ère de la photographie informatisée.

L’iPhone XS devrait tenir une demi-heure de plus que son prédécesseur sur une charge, et l’iPhone XS Max tiendra encore une heure supplémentaire. Apple adopte les puces LTE de « classe gigabit », même si les réseaux capables de suivre sont encore rares. Surtout et pour la première fois, les iPhone XS prennent en charge deux SIM, donc deux lignes téléphoniques. Apple étant Apple, elle ne fait pas les choses comme tout le monde : la deuxième SIM est une eSIM, cette puce virtuelle que l’on trouvait déjà dans l’iPad et l’Apple Watch.

Les iPhone XS prennent en charge deux SIM… dont une SIM virtuelle.

La capacité d’activer cette deuxième SIM dépendra des opérateurs — aucun opérateur français ne prend en charge cette configuration pour le moment, et aucun opérateur chinois ne le fera. Apple devra proposer une version de l’iPhone XS Max spécifique à la Chine, dont le chariot sera capable d’accueillir deux puces physiques, une de chaque côté. Le système a, bien sûr, été revu pour prendre en charge les deux lignes de front.

L’iPhone XS et l’iPhone XS Max sont déclinés dans trois capacités (64, 256 et 512 Go) et trois coloris (gris sidéral, argent et or). L’iPhone XS sera proposé à partir de 1 159 €, et l’iPhone XS Max à partir de 1 259 €. Les précommandes ouvriront le 14 septembre, pour une livraison le 21 septembre.

iPhone XR : un arc-en-ciel d’iPhone

Ne parlez pas d’iPhone low cost : l’iPhone XR est un iPhone « moins cher », mais pas un iPhone « pas cher ». Il troque l’acier contre l’aluminium 7000, la protection IP68 contre la protection IP67, 3D Touch contre un appui long avec retour haptique, et l’écran OLED contre l’écran LCD. Un écran « Liquid Retina » de 6,1 pouces et d’une résolution de 326 ppp, qui affleure les bords du châssis, sauf là où le système True Depth doit empiéter sur la surface d’affichage.

iPhone XR.

Autrement dit, l’iPhone XR est un successeur de l’iPhone 8 adoptant les technologies de l’iPhone XS. Il ne possède qu’un seul objectif, mais il reprend les caractéristiques de l’objectif grand-angle de l’iPhone XS, donc le nouveau capteur 12 Mpx. Mieux : malgré l’absence d’un deuxième capteur, il possède un mode Portrait et un contrôle a posteriori de l’ouverture, preuve des progrès du machine learning.

Tout aussi puissant que les iPhone XS, l’iPhone XR est beaucoup plus coloré. Son dos en verre est ainsi décliné dans six couleurs que l’on retrouve sur le pourtour en aluminium : blanc, noir, bleu, corail, jaune, et rouge. L’iPhone XR est décliné dans trois capacités (64, 128 et 256 Go), et sera proposé à partir de 859 € quand les précommandes ouvriront le 19 octobre prochain.

La nouvelle gamme d’iPhone.

Apple profite de l’occasion pour revoir sensiblement la gamme d’iPhone : l’iPhone 7 tombe à 529 €, et l’iPhone 8 poursuit sa carrière à partir de 689 €, accompagnés de leurs modèles Plus. Les nouveaux modèles seront livrés avec iOS 12, dont la version finale sera livrée le 17 septembre prochain. (Glissons au passage que macOS Mojave sera disponible le 24 septembre.)

Apple Watch Series 4 : un petit téléphone… avec ECG intégré

Aucune montre — connectée ou pas — n’est aussi populaire que l’Apple Watch. La firme de Cupertino ne cherche plus à chasser sur les terres des horlogers : elle se positionne clairement sur le terrain des communications, de l’activité physique, et de la santé. Trois terrains sur lesquels elle progresse avec l’Apple Watch Series 4.

L’Apple Watch Series 4.

Les communications, d’abord. Pour la première fois, Apple présente sa montre comme un petit téléphone, et le fait avec insistance. En abandonnant le métal au profit de la céramique et du saphir, le fond du boîtier est radio-transparent, et participe donc à l’amélioration de la réception cellulaire. Le micro a été replacé à l’opposé du haut-parleur, 50 % plus puissant.

L’activité physique et le bien-être, ensuite. Les coins de l’écran sont désormais arrondis, et frôlent les coins du boîtier lui-même, pour une surface d’affichage augmentée d’un tiers. L’écran pousse le boîtier à 40 ou 44 mm de hauteur, contre 38 et 42 mm jusqu’ici, mais la montre est plus fine. La plupart des cadrans ont été redessinés pour ce nouvel écran, comme les complications, plus denses et plus dynamiques.

Les variations du nouveau cadran Respirer.

Le rapport avec l’activité ? Un nouveau cadran permet d’afficher jusqu’à 8 complications, dont un ensemble entièrement dédié au suivi de l’activité. Un autre s’inspire de l’application Respirer, et propose trois variations invitant à la détente. La couronne digitale intègre un retour haptique pour faciliter les manipulations en mouvement.

La santé, enfin. La nouvelle cellule gyroscopique, plus précise, participe à la détection des chutes. En cas d’accident, la montre peut appeler les secours, y compris sans votre intervention si vous êtes inconscient. Le nouveau cardiofréquencemètre intègre des électrodes : l’Apple Watch Series 4 est le premier appareil capable de prendre un électrocardiogramme disponible sans ordonnance et certifié par les autorités américaines de santé.

Le nouveau cardiofréquencemètre, qui intègre un électrocardiographe.

La notification de rythme cardiaque trop élevée est rejointe par une notification de rythme trop bas, ainsi qu’une alerte lorsque la montre pense détecter une fibrillation atriale. Les données de l’ECG sont directement transmises et analysées par le SIP Apple S4, qui comporte un processeur double-cœur 64 bits (une première sur une montre connectée) et une puce graphique maison. Si l’on doutait encore des intentions d’Apple sur le marché de la santé prédictive, c’est désormais terminé.

Apple le promet : toutes ces nouveautés ne grèvent pas l’autonomie. L’attache des bracelets ne change pas non plus : tous les bracelets pourront être montés sur l’Apple Watch S4, qui sera bien sûr accompagnée de nouveaux bracelets, dont un bracelet milanais doré assorti à l’Apple Watch S4 en acier doré. Les versions griffées par Nike et Hermès bénéficient des mêmes nouveautés, et intègrent donc de nouveaux cadrans et de nouveaux bracelets.

La couronne du modèle cellulaire est beaucoup plus discrète.

L’Apple Watch Series 4 est proposée à partir de 429 € pour le modèle GPS, à partir de 529 € pour le modèle cellulaire. L’Apple Watch Series 3 reste au catalogue, à partir de 299 €. Les nouvelles montres seront fournies avec watchOS 5, présenté au début de l’été. Les précommandes ouvriront le 14 septembre, pour une livraison le 21 septembre.

  1. Si vous voulez respecter les choix d'Apple, prononcez « iPhone 10 S », et ne l’écrivez ni avec une minuscule ni avec une capitale, mais avec une petite capitale. Bon courage. ↩︎

          Nvidia launches the Tesla T4, its fastest data center inferencing platform yet      Cache   Translate Page      
Nvidia today announced its new GPU for machine learning and inferencing in the data center. The new Tesla T4 GPUs (where the ‘T’ stands for Nvidia’s new Turing architecture) are the successors to the current batch of P4 GPUs that virtually every major cloud computing provider now offers. Google, Nvidia said, will be among the […]
          Software Engineer - Machine Learning - Convoy - Seattle, WA      Cache   Translate Page      
Today, we use machine learning to figure out freight prices, shipment relevance for carriers, auction bidding strategy, and other internal processes....
From Convoy - Sat, 19 May 2018 10:13:22 GMT - View all Seattle, WA jobs
          Community Manager - Alation Inc. - Redwood City, CA      Cache   Translate Page      
Machine Learning Data Catalogs, 2018. Act as a liaison between Alation’s internal teams and the Community. You’ll work with a strong set of brand-name customers...
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          All Levels Marketing Sciences - Hypothesis Group - Los Angeles, CA      Cache   Translate Page      
Understanding of machine learning techniques and algorithms. Active support in research design for new business....
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          Rosetta: Understanding text in images and videos with machine learning -- Facebook Code      Cache   Translate Page      
Check the full post for details
"A significant number of the photos shared on Facebook and Instagram contain text in various forms. It might be overlaid on an image in a meme, or inlaid in a photo of a storefront, street sign, or restaurant menu. Taking into account the sheer volume of photos shared each day on Facebook and Instagram, the number of languages supported on our global platform, and the variations of the text, the problem of understanding text in images is quite different from those solved by traditional optical character recognition (OCR) systems, which recognize the characters but don’t understand the context of the associated image.

To address our specific needs, we built and deployed a large-scale machine learning system named Rosetta. It extracts text from more than a billion public Facebook and Instagram images and video frames (in a wide variety of languages), daily and in real time, and inputs it into a text recognition model that has been trained on classifiers to understand the context of the text and the image together."
Rosetta: Understanding text in images and videos with machine learning -- Facebook Code

          AQR hires head of machine learning      Cache   Translate Page      
none
          Agrograph Raises $500K in Seed Funding      Cache   Translate Page      

Agrograph, a Madison, WI-based agtech startup, raised $500k in seed funding. The Idea Fund of La Crosse made the investment. Co-founded by Mutlu Ozdogan and James O’Brien, Agrograph provides software that combines satellite imagery and field data with machine learning algorithms to predict crop yields at the field level. The company sells to three main […]

The post Agrograph Raises $500K in Seed Funding appeared first on FinSMEs.


          Software Engineer - Machine Learning - Convoy - Seattle, WA      Cache   Translate Page      
Today, we use machine learning to figure out freight prices, shipment relevance for carriers, auction bidding strategy, and other internal processes....
From Convoy - Sat, 19 May 2018 10:13:22 GMT - View all Seattle, WA jobs
          Community Manager - Alation Inc. - Redwood City, CA      Cache   Translate Page      
Machine Learning Data Catalogs, 2018. Act as a liaison between Alation’s internal teams and the Community. You’ll work with a strong set of brand-name customers...
From Alation Inc. - Thu, 23 Aug 2018 20:35:18 GMT - View all Redwood City, CA jobs
          All Levels Marketing Sciences - Hypothesis Group - Los Angeles, CA      Cache   Translate Page      
Understanding of machine learning techniques and algorithms. Active support in research design for new business....
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          Học máy là gì và cách hiểu về nó?      Cache   Translate Page      
Học máy (machine learning), hay còn gọi là máy học là một thuật ngữ được giới công nghệ được nhắc đến khá nhiều trong thời gian gần đây. Nói nôm na, học máy có nghĩa là việc chúng ta "dạy" cho máy móc biết tự học hỏi và cập nhật kiến thức, để chúng ngày càng trở nên thông minh hơn.
          Apple Unveils iPhone Xs and Xs Max      Cache   Translate Page      
If you’re an Apple fan, then, today marks the most extravagant day of your calendar as the tech giant officially unleashed its latest premium smartphones – the iPhone Xs, iPhone Xs Max, and the iPhone XR.

Apple Unveils iPhone Xs and Xs Max
Apple Unveils iPhone Xs and Xs Max

Right now, let’s put our spotlight first on the two brothers who share almost the same specs and features. Having nearly identical offerings, the iPhone Xs and Xs Max just differ in size. The regular variant flashes a 2436 x 1125 resolution, while the Max model flaunts a bigger 2688 x 1242 pixels. Nevertheless, the two devices boast Super Retina OLED display with 120Hz touch sensing, True Tone, 3D Touch, Tap to wake, and Dolby Vision HDR 10 support.

Also, both handsets are dressed with a premium-looking physique with IP68 certification. To make it more sophisticated, it comes with three classy color variants: gold, silver, and space gray.

Under the hood, the Xs and Xs Max are powered by the new A12 hexa-core bionic chip complemented with a quad-core GPU which is said to be 50% faster than the A11, and an octa-core Neural Engine that focuses on Dedicated Machine Learning and Smart Compute System. Just like before, it won’t feature an expandable storage, but Apple elevated its offerings with up to 512GB of ROM.

See Also: Apple Becomes 1st Company to Hit USD 1 Trillion Mark on a Public Stock Market

iPhone Xs and iPhone Xs Max
iPhone Xs and iPhone Xs Max

Jumping off to its camera department, Apple mounted it with dual rear cameras composed of 12-megapixel wide-angle f/1.8 and another 12-megapixel f/2.4 telephoto sensors. For selfie, it sports a 7-megapixel snapper that features depth portrait mode.

When it comes to its stamina, Apple claimed that the iPhone Xs and Xs Max are juiced with a battery that can last 30 minutes longer and 1.5 hours longer than the iPhone X, respectively.

Meanwhile, Apple finally allows user to utilize two SIMs as it equipped the devices with Dual SIM capability through eSIM technology.

The devices run on iOS 12 software, too.

Consumers can pre-order the iPhone Xs and iPhone Xs Max starting September 14, while it will start sailing in 30 shores beginning September 21. It will have a starting price of USD 999 and USD 1,099, correspondingly.

Meanwhile, there are no words yet about its local availability and pricing.

Apple iPhone Xs and Xs Max Specs:


  • Dual SIM (single nano + eSIM), supports 4G VoLTE connectivity
  • 5.8-inch Super Retina OLED (2346 x 1125) capacitive touchscreen/6.5-inch Super Retina OLED (2688 x 1242) capacitive touchscreen
  • Dimensions: 143.6mm x 70.9mm x 7.7mm / 157.5mm x 77.4mm x 7.7mm
  • Weight: 177 grams / 208 grams
  • iOS 12
  • Apple A12 Bionic hexa-core chip, Apple GPU (4-core graphics)
  • 64GB/256GB/512GB non-expandable storage
  • 12MP wide-angle + 12MP dual rear cameras
  • 7MP f/2.2 front snapper + IR Camera
  • Wide Stereo Speakers
  • Wi-Fi 802.11ac 2x2 MIMO
  • Bluetooth 5.0
  • NFC
  • GPS with GLONASS, Galileo, and QZSS
  • Lightning Port
  • Sensors: Face ID, aceleremoter, gyro, proximity, compass, barometer
  • Non-removable Li-Ion battery
  • Colors: Space Gray, Silver, Gold
  • Price: USD 999, USD 1,149, USD 1,349 (iPhone Xs); USD 1,099, USD 1,249, USD 1,449 (iPhone Xs Max)

          Nvidia launches the Tesla T4, its fastest data center inferencing platform yet      Cache   Translate Page      
Nvidia today announced its new GPU for machine learning and inferencing in the data center. The new Tesla T4 GPUs (where the ‘T’ stands for Nvidia’s new Turing architecture) are the successors to the current batch of P4 GPUs that virtually every major cloud computing provider now offers. Google, Nvidia said, will be among the […]
          Principal Market Validation Specialist - PTC - Needham, MA      Cache   Translate Page      
Advance knowledge and experience with Machine Learning / Data Science / Analytics. Customer Satisfaction focus, both internal and external, with strong...
From PTC - Wed, 16 May 2018 14:29:21 GMT - View all Needham, MA jobs
          Senior Software Engineer (A.I)      Cache   Translate Page      
TX-Austin, To avoid delays in having your resume reviewed please forward directly to: ____________________________________________________________________________________ Sam.Major@RAndstadUSA.com ____________________________________________________________________________________ JOB TITLE: Senior Software Engineer (Computer Vision & Machine Learning) LOCATION: Austin, TX 78702 (Relocation Assistance Provid
          Machine Learning      Cache   Translate Page      
It started with a war. Like so many other events that give rise to the previously unimagined, this n
          Sr. Data Scientist - Microsoft - Redmond, WA      Cache   Translate Page      
Virtual machine switching); Large scale distributed systems, real-time data analysis, machine learning, windows internals (networking stack and other OS...
From Microsoft - Thu, 09 Aug 2018 04:41:50 GMT - View all Redmond, WA jobs
          Economist - Forecasting - Amazon.com - Seattle, WA      Cache   Translate Page      
Experience with machine learning applications. We are breaking fresh ground, pioneering in a program that is crucial for future Amazon growth, and our business...
From Amazon.com - Wed, 27 Jun 2018 07:21:23 GMT - View all Seattle, WA jobs
          Sr. Data Scientist - Life Sciences - Health Catalyst - Salt Lake City, UT      Cache   Translate Page      
Machine learning experience required. The role has great potential for a successful candidate as they will form the initial seed of a new business unit with...
From Health Catalyst - Tue, 11 Sep 2018 02:31:12 GMT - View all Salt Lake City, UT jobs
          Sr. Associate, ML Pipelines for AI Consultant - KPMG - Seattle, WA      Cache   Translate Page      
Modeling (regression, machine learning, feature selection, dimension reduction, validation); Strong aptitude for quickly learning business operational, process,...
From KPMG LLP - Fri, 07 Sep 2018 02:02:23 GMT - View all Seattle, WA jobs
          Data Scientist - Deloitte - Springfield, VA      Cache   Translate Page      
Demonstrated knowledge of machine learning techniques and algorithms. We believe that business has the power to inspire and transform....
From Deloitte - Fri, 10 Aug 2018 06:29:44 GMT - View all Springfield, VA jobs
          Database Administrator - Radiant Solutions - Springfield, VA      Cache   Translate Page      
Machine learning, data mining, and knowledge discovery. Work is non-routine and very complex, involving the application of advanced technical and business...
From Radiant Solutions - Wed, 04 Jul 2018 01:36:29 GMT - View all Springfield, VA jobs
          Sr. Associate, ML Pipelines for AI Consultant - KPMG - Dallas, TX      Cache   Translate Page      
Modeling (regression, machine learning, feature selection, dimension reduction, validation); Strong aptitude for quickly learning business operational, process,...
From KPMG LLP - Fri, 07 Sep 2018 02:02:14 GMT - View all Dallas, TX jobs
          Threat Finance Subject Matter Expert - People, Technology & Processes - Fort Bragg, NC      Cache   Translate Page      
The TF SME contractor shall have proficiency and experience with applied data processing and scientific analysis of large datasets and machine learning....
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          Apple's iPhone Xr Offers the All-Screen Look at a Lower Price      Cache   Translate Page      

Apple today announced the iPhone Xr, a more affordable all-screen iPhone. The Xr looks similar to the Xs and Xs Max, but has an LCD panel rather than OLED, and a 7000 series aluminum frame rather than stainless steel. The screen size sits between the 5.8-inch and 6.4-inch displays of the Xs and Xs Max, respectively, at 6.1 inches across the diagonal. Apple calls it the Liquid Retina display with 1,792 by 828 pixels and a pixel density of 326ppi. It supports tap-to-wake, and includes true-tone, 120Hz refreshing, and wide-color gamut. This iPhone will come in black, blue, green, yellow, and coral. The chassis are rated IP67 for protection from water and dust. A new shortcut from the home screen takes people directly to the camera. It includes the same bank of sensors for Face ID, such as infrared, proximity, and ambient light sensors. It is faster. This phone also includes the A12 Bionic and real-time machine learning. A single camera adorns the rear. It's a 12-megapixel wide-angle camera at f/1.8, OIS, Smart HDR, portrait mode, bokeh, 6-element lens, focus pixels, and a True Tone flash. The Xr also carries over the selfie camera from the Xs and Xs Max. Apple says the battery delivers more than 90 minutes more uptime than the iPhone 8+. The iPhone Xr starts at $799 and comes in 64 GB, 256 GB, and 512 GB variants. It will be available for preorder October 19 and reaches stores October 26.


          iPhone Xs and Xs Max Update Key Specs of Apple's Flagship      Cache   Translate Page      

Apple today announced the iPhone Xs and iPhone Xs Max. These devices are upgrades to last year's iPhone X and feature the same design. The new iPhones have an all-screen look with a notch at the top of the display. The front and back surfaces are made of glass and a stainless steel frame is in between. The Xs maintains the same 5.8-inch size as last year's phone, while the Xs Max pushes the screen size to 6.5 inches. Apple says it uses new glass that is the most durable ever on a mobile device. The OLED displays support Dolby Vision and HDR10, with a 60% greater dynamic range. The screens have True Tone for accurate whites, as well as 3D touch and 120Hz touch response. The iPhone Xs and Xs Max will be sold in gold, silver, and space gray. The phones are rated IP68 for protection against water, dust, and other liquids. Apple has improved the stereo speakers, giving them a wider sound stage. The 10x features an improved Face ID with better sensors and faster performance thanks to quicker algorithms. In order to power the new iPhones, Apple designed the A12 bionic, with a 7nm process, 6-core CPU (2 high-performance, 4 efficiency cores), 4-core GPU (50% faster), and an 8-core neural engine with dedicated machine learning. Apple says the device can process far more real-time information for the camera, Animoji, selfie scenes, and more. The A12 Bionic helps Apple bring new tools to the iPhone's camera. The Xs has a two-camera system, each with a 12-megapixel sensor. The main lens features a wide-angle field of view at f/1.8 while the secondary lens features a telephoto view at f/2.2. The cameras have optical image stabilization. The A12 Bionic can perform 1 trillion calculations on the photos to improve them. The selfie camera has a 7-megapixel sensor and uses the IR sensor to deliver depth information for portraits. The new Smart HDR feature relies on the A12's neural engine to enhance color and improve exposure. The improved portrait shooting allows people to adjust the background blur with a new depth-of-field slider in the editing tool. The iPhone can now record stereo sound with video. Apple says the battery should deliver 30 more minutes of uptime when compared to the iPhone X, and the Xs Max delivers 90 more minutes. The new iPhones introduce gigabit LTE, dual SIM card support (with dual SIM, dual standby provided by eSIM), wide support for worldwide LTE bands. Apple says AT&T, T-Mobile, and Verizon will support this dual SIM technology, which includes one physical SIM and one eSIM, this year. The iPhone Xs will start at $999 and the Xs Max will start at $1099. Both will be available in 64 GB, 256 GB, and 512 GB options. Preorders for the new iPhones start September 14, with in-store availability on September 21.


          Director, Customer Service Product and Tools - Kabam - Austin, TX      Cache   Translate Page      
Enthusiastic about the latest mobile trends and emerging technologies (IE Machine Learning, AI). Providing leadership and supporting for the technology...
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          Robotic Process Automation (RPA) Market Size and Share 2018 to 2025: North America Region Accounts for Largest Share Owing to High Development      Cache   Translate Page      

The report analyzes and presents an overview on "Global Robotic Process Automation (RPA) Market Insights, Forecast to 2025" worldwide.

Albany, NY -- (SBWIRE) -- 09/12/2018 -- This report presents the worldwide Robotic Process Automation (RPA) market size (value, production and consumption), splits the breakdown (data status 2013-2018 and forecast to 2025), by manufacturers, region, type and application.

This study also analyzes the market status, market share, growth rate, future trends, market drivers, opportunities and challenges, risks and entry barriers, sales channels, distributors and Porter's Five Forces Analysis.

Request For Sample Copy to Get More Insights @ https://www.marketresearchreports.biz/sample/sample/1895597

Robotic process automation is an application technology where software with capabilities of artificial intelligence and machine learning are used for handling high volume, repeatable tasks. RPA allows employees to configure and program a computer software or a robot to interpret exiting application in the organization for manipulating data, processing transactions and communicating with digital systems.

North America region accounts for largest share in robotic process automation market owing to high development in field of technology and presence of developed countries. Europe is one of the prominent player in the market of robotic process automation. Countries such as U.K., Germany and Italy are the major contributors in the market growth due to the rich manufacturing and automotive industry. Asia-Pacific is expected to emerge as fastest growing market during the forecast period. Development of Asian countries and demand for consumer electronic products is forcing the manufacturers to adopt a cost effective technology in the manufacturing process.

The Robotic Process Automation (RPA) market was valued at xx Million US$ in 2017 and is projected to reach xx Million US$ by 2025, at a CAGR of xx% during the forecast period. In this study, 2017 has been considered as the base year and 2018 to 2025 as the forecast period to estimate the market size for Robotic Process Automation (RPA).

The following manufacturers are covered in this report:
Automation Anywhere (U.S.)
Blue Prism (U.K.)
Celaton Ltd (U.K.)
Ipsoft (U.S.)
Nice Systems Ltd. (Israel)
Pegasystems (U.S.)
Redwood Software (U.S.)
Uipath (Romania)
Verint (U.S.)
Xerox Corporation (U.S.)

Robotic Process Automation (RPA) Breakdown Data by Type
Automated Solution
Decision Support And Management Solution
Interaction Solution
Robotic Process Automation (RPA) Breakdown Data by Application
BFSI
Healthcare & Pharmaceuticals
Manufacturing & Logistics
IT & Telecommunication
Retail
Travel
Hospitality
Transportation
Others

Request To Get List of Tables and Figures @ https://www.marketresearchreports.biz/reports/1895597/global-robotic-process-automation-rpa-market-research-reports/toc

Robotic Process Automation (RPA) Production by Region
United States
Europe
China
Japan
Other Regions

Robotic Process Automation (RPA) Consumption by Region
North America
United States
Canada
Mexico
Asia-Pacific
China
India
Japan
South Korea
Australia
Indonesia
Malaysia
Philippines
Thailand
Vietnam
Europe
Germany
France
UK
Italy
Russia
Rest of Europe
Central & South America
Brazil
Rest of South America
Middle East & Africa
GCC Countries
Turkey
Egypt
South Africa
Rest of Middle East & Africa

The study objectives are:
To analyze and research the global Robotic Process Automation (RPA) status and future forecastinvolving, production, revenue, consumption, historical and forecast.
To present the key Robotic Process Automation (RPA) manufacturers, production, revenue, market share, and recent development.
To split the breakdown data by regions, type, manufacturers and applications.
To analyze the global and key regions market potential and advantage, opportunity and challenge, restraints and risks.
To identify significant trends, drivers, influence factors in global and regions.
To analyze competitive developments such as expansions, agreements, new product launches, and acquisitions in the market.

In this study, the years considered to estimate the market size of Robotic Process Automation (RPA) :
History Year: 2013 - 2017
Base Year: 2017
Estimated Year: 2018
Forecast Year: 2018 - 2025

This report includes the estimation of market size for value (million USD) and volume (K Units). Both top-down and bottom-up approaches have been used to estimate and validate the market size of Robotic Process Automation (RPA) market, to estimate the size of various other dependent submarkets in the overall market. Key players in the market have been identified through secondary research, and their market shares have been determined through primary and secondary research. All percentage shares, splits, and breakdowns have been determined using secondary sources and verified primary sources.

Buy This Report From Here @ https://www.researchmoz.com/checkout?rep_id=1895597&licType=S

For the data information by region, company, type and application, 2017 is considered as the base year. Whenever data information was unavailable for the base year, the prior year has been considered.

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MarketResearchReports.biz is a seller of syndicated market studies, featuring an exhaustive collection of research reports from leading international publishers. Our repositoryis diverse, spanningvirtually every industrial sector and even more every category and sub-category within the industry. We also provide consulting services to enable our clients have adynamicbusiness perspective.

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          Machine Learning/AI Engineer - Groom & Associates - Montréal, QC      Cache   Translate Page      
Machine Learning/AI Engineer An international company is looking for Machine Learning/AI Engineers to join their new Montreal office! Title: Machine Learning...
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          Ingénieur en apprentissage automatique - Groom & Associates - Montréal, QC      Cache   Translate Page      
Machine Learning/AI Engineer An international company is looking for Machine Learning/AI Engineers to join their new Montreal office! Title: Machine Learning...
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          Software Engineer, AI Services - Shutterstock - Montréal, QC      Cache   Translate Page      
The Opportunity: As a API Algorithm Engineer, you will be responsible for building the innovative API endpoints using AI technologies (Machine Learning, Deep...
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          Senior Software Development Engineer - Distributed Computing Services (Hex) - Amazon.com - Seattle, WA      Cache   Translate Page      
Knowledge and experience with machine learning technologies. We enable Amazon’s internal developers to improve time-to-market by allowing them to simply launch...
From Amazon.com - Thu, 26 Jul 2018 19:20:25 GMT - View all Seattle, WA jobs
          Senior Site Reliability Engineer - Sift Science - Seattle, WA      Cache   Translate Page      
The Sift Science Trust PlatformTM uses real-time machine learning to accurately predict which users businesses can trust, and which ones they can't....
From Sift Science - Fri, 22 Jun 2018 20:18:59 GMT - View all Seattle, WA jobs
          Senior Software Engineer - Revenue Optimization - WeWork Global Technology - New York, NY      Cache   Translate Page      
Experience building Linear Programming solutions and Machine learning applications highly desired. Deep understanding of Amazon Web Services including ECS,...
From WeWork - Wed, 06 Jun 2018 05:19:01 GMT - View all New York, NY jobs
          Executive Director- Machine Learning & Big Data - JP Morgan Chase - Jersey City, NJ      Cache   Translate Page      
We would be partnering very closely with individual lines of business to build these solutions to run on either the internal and public cloud....
From JPMorgan Chase - Fri, 20 Jul 2018 13:57:18 GMT - View all Jersey City, NJ jobs
          UR - Corporate Engineering - Precision Systems Engineer (Maplewood, MN) - 3M - Maplewood, MN      Cache   Translate Page      
Proactively collaborate with business partners to connect and extend process data management solutions with complimentary machine learning and analytics efforts...
From 3M - Wed, 05 Sep 2018 17:09:45 GMT - View all Maplewood, MN jobs
          Data Science Manager - Micron - Boise, ID      Cache   Translate Page      
Create server based visualization applications that use machine learning and predictive analytic to bring new insights and solution to the business....
From Micron - Wed, 05 Sep 2018 11:18:49 GMT - View all Boise, ID jobs
          Intern - Data Scientist (NAND) - Micron - Boise, ID      Cache   Translate Page      
Machine learning and other advanced analytical methods. To ensure our software meets Micron's internal standards....
From Micron - Wed, 29 Aug 2018 20:54:50 GMT - View all Boise, ID jobs
          Intern - Data Scientist (DRAM) - Micron - Boise, ID      Cache   Translate Page      
Machine learning and other advanced analytical methods. To ensure our software meets Micron's internal standards....
From Micron - Mon, 20 Aug 2018 20:48:37 GMT - View all Boise, ID jobs
          Data Analytics Specialist - Align Technology - San Jose, CA      Cache   Translate Page      
Experience with machine learning. Excellent understanding of machine learning techniques and algorithms....
From Align Technology - Thu, 28 Jun 2018 06:01:20 GMT - View all San Jose, CA jobs
          PYTHON Developer - Klein Management Systems - San Jose, CA      Cache   Translate Page      
Work on the design, implementation, technical support and evaluation of new and existing systems. Machine Learning with Python, Tensorflow, SyntaxNet and R...
From Klein Management Systems - Thu, 09 Aug 2018 17:29:34 GMT - View all San Jose, CA jobs
          UR - Corporate Engineering - Precision Systems Engineer (Maplewood, MN) - 3M - Maplewood, MN      Cache   Translate Page      
Proactively collaborate with business partners to connect and extend process data management solutions with complimentary machine learning and analytics efforts...
From 3M - Wed, 05 Sep 2018 17:09:45 GMT - View all Maplewood, MN jobs
          Data Science Manager - Micron - Boise, ID      Cache   Translate Page      
Create server based visualization applications that use machine learning and predictive analytic to bring new insights and solution to the business....
From Micron - Wed, 05 Sep 2018 11:18:49 GMT - View all Boise, ID jobs
          Intern - Data Scientist (NAND) - Micron - Boise, ID      Cache   Translate Page      
Machine learning and other advanced analytical methods. To ensure our software meets Micron's internal standards....
From Micron - Wed, 29 Aug 2018 20:54:50 GMT - View all Boise, ID jobs
          Intern - Data Scientist (DRAM) - Micron - Boise, ID      Cache   Translate Page      
Machine learning and other advanced analytical methods. To ensure our software meets Micron's internal standards....
From Micron - Mon, 20 Aug 2018 20:48:37 GMT - View all Boise, ID jobs
          Data Analytics Specialist - Align Technology - San Jose, CA      Cache   Translate Page      
Experience with machine learning. Excellent understanding of machine learning techniques and algorithms....
From Align Technology - Thu, 28 Jun 2018 06:01:20 GMT - View all San Jose, CA jobs
          Nvidia launches the Tesla T4, its fastest data center inferencing platform yet      Cache   Translate Page      

Nvidia today announced its new GPU for machine learning and inferencing in the data center. The new Tesla T4 GPUs (where the ‘T’ stands for Nvidia’s new Turing architecture) are the successors to the current batch of P4 GPUs that virtually every major cloud computing provider now offers. Google, Nvidia said, will be among the […]

The post Nvidia launches the Tesla T4, its fastest data center inferencing platform yet appeared first on RocketNews | Top News Stories From Around the Globe.


          Episode 129: #129: Mohana the Shark      Cache   Translate Page      
We Give Thanks Special Guest: Mohana Ravindranath.
          Episode 122: #122: You’d Better Recognize      Cache   Translate Page      

This week Dave and Gunnar talk about recognition: facial recognition, keystroke recognition, Dothraki recognition.

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Cutting Room Floor

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           Trend Micro Internet Security       Cache   Translate Page      
Trend Micro Internet Security provides advanced online protection. Using machine learning based technology, it protects against viruses...
           Trend Micro Maximum Security       Cache   Translate Page      
Trend Micro Maximum Security provides comprehensive, multi-device protection using advanced machine learning based technology. It protects...
          Data Scientist      Cache   Translate Page      
CA-San Diego, job summary: Job Summary The Data Scientist who is passionate about data and want to apply machine learning techniques to solve real-world problems for our clients. This person will be expected to be proficient in the exploration and understanding of structured and unstructured data, machine learning and data mining techniques, statistical modeling methods, time series, text mining, recommendation
          iPhone XS, iPhone XS Max, iPhone XR y Apple Watch Series 4: primeras impresiones desde el Apple Park      Cache   Translate Page      

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Era la segunda vez que Apple ofrecía una keynote en el Apple Park desde su inauguración el año pasado, y nada más llegar, se notaba mucha más vida en el interior. Las paredes transparentes nos dejaban ver al personal de la compañía por los pasillos, y los prados exteriores ya lucían verde. El año pasado los autobuses que nos transportaban directo al Visitors Center, y ahora nos quedábamos muy cerca de la entrada principal del Apple Park.

La senda que sube al Steve Jobs Theater estaba acompañada de gente de Apple que nos animaba a subir al exterior del auditorio, donde se servía un desayuno ligero para prensa. Si habéis seguido los directos que he hecho en Instagram y YouTube, habréis dado un paseo conmigo por los alrededores que sirve un poco como la antesala y preparación para las sorpresas de la keynote.

Aunque no se haya mencionado en la keynote, el HomePod saldrá finalmente en España el próximo 26 de Octubre

Al comienzo de la presentación veíamos a un Tim Cook que nos adelantaba el contenido del evento: vamos a hablar únicamente de dispositivos iOS, perfecto para celebrar los dos mil millones de este tipo de dispositivos vendidos en todo el mundo. Quedará entonces para otro momento la presentación del iPad Pro sin marcos, o alguna actualización de la gama Mac. Sobre el HomePod, Cook comentó unas mejoras en el software que mejoran la calidad de sonido. No se ha hablado en la presentación de su aparición en España - por eso en mi vídeo resumen comento que no hay noticias sobre ello - pero una hora más tarde ya conocíamos por la web que el próximo 26 de Octubre por fin se podrá comprar en España.

Apple Watch Series 4, completamente reinventado

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Comenzamos con las primeras impresiones sobre el nuevo Apple Watch Series 4, que como bien reza su descripción en la web de la compañía “te resultará familiar pero es completamente distinto” - y sin duda así es. En directo, el nuevo reloj de Apple destaca por una pantalla mayor con una envergadura que llega hasta los 44mm (de los 42mm de las ediciones anteriores), pero se ganan en el plano vertical más que en el horizontal, por lo que todas las correas y accesorios que tengáis serán compatibles con él.

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En mano, es un reloj más ligero y que llama la atención por la pantalla que consigue reducir los bordes hasta la ondulación del cristal: se aprecia sobre todo en los fondos de pantalla y en las esferas que lo llenan, y da una apariencia futurista que va un poco más allá de lo que conocíamos. La nueva corona digital gana ahora feedback háptico: esto significa que al moverla en listas con desplazamiento, el reloj nos dará un “toque” en cada ítem para darnos la sensación ficticia de mover una rueda con muescas real.

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La pantalla mantiene la misma calidad que ya conocíamos en el Series 3, pero al ganar en tamaño es mucho más espectacular. Otra de las novedades importantes es la mejora en sensores tan importantes como el giroscopio, el sensor cardíaco o los sensores para los electrocardiogramas. El detalle lo tendremos de revisarlo en profundidad, pero una prueba rápida con los dispositivos sí me ha dado la impresión de que son más rápidos - también ayudado por el nuevo chip S4 de 64Bits - y al parecer más precisos. Mención especial a la detección caídas y puesta de llamadas de emergencia: esto no he podido probarlo aún, pero la gente de Apple nos ha asegurado que funciona de forma muy precisa.

iPhone XS y iPhone XS Max

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Los dos iPhone XS son exactamente iguales en características y potencia: la única diferencia del modelo Max es la mayor pantalla

La gran estrella de esta presentación han sido los dos nuevos iPhone XS y iPhone XS Max que heredan la tecnología que utilizó el iPhone X para sentar las bases de las siguiente evoluciones: un diseño sin marcos y un procesador basado en inteligencia artificial local (todo se calcula en el dispositivo, y no en una nube fuera del teléfono), que este año además cuenta con un “hermano mayor” al que Apple ha decidido llamar “Max” - y no es casualidad que no hayan empleado el apellido Plus: estos dos teléfonos sólo se diferencian por el tamaño de pantalla. Ni la capacidad de almacenamiento, ni las características hardware difieren entre ellos (ambos cuentan de forma idéntica incluso con las mismas cámaras). Son por lo tanto dos gemelos, sólo que uno con más tamaño de pantalla que el otro.

Iphone Xs Iphone Xs Max Iphone Xr

El aumento de la pantalla del Max no es incómoda en la mano. De hecho, os resultará muy familiar a los poseedores de un modelo Plus de cualquier generación porque es la misma envergadura, sólo que ahora todo es pantalla de borde a borde. Esto hace que se pueda conseguir una espectacular pantalla de 6,5” (una pulgada más que el Plus de otras generaciones con el mismo tamaño de dispositivo). Como digo, cómodo en mano, no desliza y la nueva pantalla luce realmente enorme lo que ofrece un campo de visión espectacular para juegos y aplicaciones. Los vídeos y fotografías permiten ver más los detalles de cada una de ellas, y las interfaces preparadas para trabajar en modo horizontal (como Mail) ahora dan mucho más juego. Si os gustaban los modelos Plus, sin duda los Max de esta generación os van a encantar.

Iphone Xs Iphone Xs Max Iphone Xr

Por dentro, todo un compendio de tecnología, desde la fabricación de las placas base es un material más fácilmente recicable que el plástico, la compatibilidad con IP68 para poder sumergir el teléfono hasta dos metros y medio, o el cristal ultraresistente de la pantalla y la parte trasera. Pero sin duda, donde el teléfono destaca en las demos es al utilizar el nuevo A12 Bionic, un monstruo de proceso que alcanza los cinco trillones de operaciones por segundo, compuesto por una CPU y una GPU de 6 y 4 núcleos respectivamente. El procesador de Machine Learning cuenta con ocho núcleos de proceso, y en conjunto, la potencia empieza a poner en evidencia no sólo a los procesadores de las demás compañías, también incluso a algunos procesadores de escritorio.

En las demos, los juegos lucen de forma absolutamente increíble con gráficos que - como nos han recordado en las demos de la keynote - se acercan mucho a consolas de sobremesa. El juego de Bethesda, Blades, es ciertamente un anticipo del futuro de lo que nos puede ofrecer el A12: rol en primera persona con efectos gráficos de iluminación sorprendentes para un dispositivo de bolsillo. Y la potencia no se nota sólo aquí: la soltura de la interfaz de iOS 12 en este nuevo hardware hace comodísima la navegación por gestos y la apertura de las apps es prácticamente instantánea. También ayuda a que Face ID sea todavía mejor utilizando la misma barra de sensores (o notch, como lo conocemos) de la generación anterior: se han mejorado los algoritmos de detección facial y la identificación es todavía más instantánea que en un iPhone X.

iPhone XR, un iPhone diferente que no renuncia a nada

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Como sorpresa, hemos contado con la llegada del iPhone XR, un teléfono que recuerda en posición a la que ocupaba el iPhone 5c, pero va mucho más allá del concepto que nos proponía la compañía en aquel año: ya no hablamos de plástico para la carcasa trasera, contamos con los mismos materiales y construcción de los iPhone XS pero la pantalla es un poco más grande que el modelo XS, llegando a los 6,1” (respecto a las 5,8” del XS). La envergadura un poco más grande no se nota en la mano, aunque la separación de la pantalla con los bordes es mayor. Es muy cómodo y ese toque “diferente” del modelo conocido como iPhone X le aporta un extra muy atractivo.

Iphone Xs Iphone Xs Max Iphone Xr

En directo este nuevo teléfono es el más espectacular a primera vista yo diría de los tres: se ayuda por el hecho de contar con seis colores distintos y una continuidad de la parte posterior que llega hasta la pantalla. Le da en mano un toque más “deportivo” pero no deja de perder jamás el aspecto premium que destilan los componentes de construcción. La pantalla no es OLED respecto al XD, pero Apple nos tenía preparado una nueva pantalla Liquid Retina que según la compañía es la mejor LCD recién fabricada. A primeras vistas no se ha apreciado diferencias apreciables, aunque la inmensa sala de pruebas no era el mejor lugar para revisar la profundidad de los negros o la diferencia con la pantalla HDR, que detallaremos en nuestro análisis. Aún así, una buena noticia y muy buen trabajo al conseguir una pantalla LCD con esta calidad.

Iphone Xs Iphone Xs Max Iphone Xr

La cámara no cuenta con lentes duales en el modelo XR, pero al apoyar parte de la traducción de la imagen en el aprendizaje del motor neuronal del A12 (que incluye exactamente el mismo que los XS) permite que podamos tener también el control de profundidad que el procesador se encarga de gestionar, logrando efectos por ejemplo de Bokeh muy impresionantes para un móvil. Lo he podido probar en la zona de demostración y funciona de forma realmente suave y completamente en tiempo real también en el XR. Este XR sin duda será un modelo muy llamativo orientado sobre todo a la gente que no necesita todas las características extra del XS, pero que no quiere renunciar a su potencia, ya que cuenta con el mismo procesador. Los colores y ese toque diferencial del diseño lo convertirán en uno de los modelos más populares de este año.

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En Applesfera | Todo sobre la keynote del 12 de Septiembre 2018

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La noticia iPhone XS, iPhone XS Max, iPhone XR y Apple Watch Series 4: primeras impresiones desde el Apple Park fue publicada originalmente en Applesfera por Pedro Aznar .


          Sr Professional, Science & Analytics - CoreLogic - Milwaukee, WI      Cache   Translate Page      
Perform pattern recognition model creation and training using various types of algorithms and machine learning modeling techniques for unknown or less well...
From CoreLogic - Tue, 04 Sep 2018 23:54:48 GMT - View all Milwaukee, WI jobs
          AQR hires head of machine learning      Cache   Translate Page      
Marcos Lopez de Prado joined AQR Capital Management as principal and head of machine learning.
          Senior Software Engineer (A.I)      Cache   Translate Page      
TX-Austin, To avoid delays in having your resume reviewed please forward directly to: ____________________________________________________________________________________ Sam.Major@RAndstadUSA.com ____________________________________________________________________________________ JOB TITLE: Senior Software Engineer (Computer Vision & Machine Learning) LOCATION: Austin, TX 78702 (Relocation Assistance Provid
          Tech Mahindra and Avaamo to partner for conversational AI solutions      Cache   Translate Page      
Tech Mahindra will evangelize Avaamo’s enterprise products and build solutions around platforms in areas such as the internet of things, artificial intelligence, and machine learning
          Top 10 High Demand IT Jobs In The Future      Cache   Translate Page      

As new technologies are emerging year by year, the scope of new occupations is increasing. Here are some of the high demand’s jobs in the field of technology- 1. Web developer Web developer develops software that is online according to clients’ demand. He is aware of many programming languages. As technology is rising at a quicker pace, the employees want someone who knows about programming, software, etc. 2. Machine learning engineer The age of technology is of artificial intelligence. The future will be of AI. Machine learning engineers develop the AI software, and that operate and manage them. Every field is adapting artificial intelligent technology, so the demand for these engineers is going to be very high. 3. Cloud engineer More industries are going towards cloud storage. It’s going to be immense in the forthcoming years. The demand for cloud engineers will boom. 4. Mobile app developers They develop apps on the phone. The big industries, the government they all have their apps, and mobile phones are the best way to gain popularity and success. Even there are many courses in mobile app development. By the year 2020 the mobile app developers demand will rise by 57%. 5. Database administrator […]

The post Top 10 High Demand IT Jobs In The Future appeared first on Techyv.com.


          How data analytics-rich business networks help close the digital transformation gap      Cache   Translate Page      
The next BriefingsDirect thought leadership discussion explores how intelligence gleaned from business applications, data, and networks provides the best new hope for closing the digital transformation gap at many companies.

A recent global survey of procurement officers shows a major gap between where companies are and where they want to be when it comes to digital transformation. While 82 percent surveyed see digital transformation as having a major impact on processes -- only five percent so far see significant automation across their processes.

How can business networks and the cloud-based applications underlying them better help companies reach a more strategic level of business intelligence and automation?

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy

To find out, BriefingsDirect recently visited SAP in Palo Alto, Calif. to sit down with Darren Koch, Chief Product Officer at SAP Ariba. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner:What's holding companies back when it comes to becoming more strategic in their processes? They don’t seem to be able to leverage intelligence and automation to allow people to rise to a higher breed of productivity.

Koch
Koch: I think a lot of it is inertia. The ingrained systems and processes that exist at companies impact a lot of people. The ability for those companies to run their core operations relies on people and technology working together. The change management required by our customers as they deploy solutions -- particularly in the move from on-premises to the cloud -- is a major inhibitor.

But it's not just the capabilities and the change in the new technology. It's really re-looking at -- and reimagining -- the processes, the things that existed in the highly customized on-premises world, and the way those things change in a digital-centric cloud world. They are fundamentally different. 

Gardner: It's always hard to change behavior. It seems like you have to give people a huge incentive to move past that inertia. Maybe that's what we are all thinking about when we bring new data analytics capabilities to bear. Is that what you looking at, incentivization -- or how do we get that gap closed?

Reimagining change in the cloud

Koch: You are seeing more thought leadership on the executive side. You are seeing companies more willing to look holistically at their processes and saying, “Is this something that truly differentiates my company and adds sustainable competitive advantage?” And the answer on some processes is, “No."


And so, we see more moving away from the complex, on-premises deployments that were built in a world where a truckload of consultants would show up and configure your software to do exactly what you wanted. Instead, we’re moving to a data-centric best-practices type of world that gives scale, where everybody operates in the same general business fabric. You see the emergence of things like business networks.

Gardner: And why the procurement and supply chain management folks? Why are they in an advantageous position to leverage these holistic benefits, and then evangelize them?

Koch: There'sbeen a ton of talk and innovation on the selling side, on the customer resource management (CRM) side, such as our announcement of C/4HANAat Sapphire 2018 and the success in the cloud generally in the CRM space. What most people stop at is, for every seller there's a buyer. We represent the buy-side, the supply chain, the purchasing departments. And now from that buy-side we have the opportunity to follow the same thought processes on the sell-side.

The beauty at SAP Ariba is that we have the world's biggest business network. We have over $2 trillion of buy-side spend and our ability to take that spend and find real insights and real actionable change to drive value at the intersection of buyers and sellers. This is where we’re headed.

Gardner: It seems like we are moving rapidly beyond the buy and sell being just transactional and moving more to deeper partnerships, visibility, of understanding the processes on both sides of the equation. That can then bring about a whole greater than the sum of the parts.

Understanding partners 

Koch: Exactly. I spent 10 years working in the consumer travel space, and my team in particular was working on how consumers choose hotels. It's a very complex purchasing decision.

There are location aspects, there are quality aspects, there are amenities, room size, obviously price, and there are a lot of non-price actors that go into the purchase decision, too. When you look at what a procurement audience is doing, what a company is doing, there are a lot of such non-price factors. It’s exactly the same problem.

The investments that we are making inside of SAP Ariba get at allowing you to see things like supplier risk. You are seeing things like the Ariba Network handling direct materials. You are seeing time, quality, and risk factors -- and these other non-price dimensions -- coming in, in the same way that consumers do when choosing a hotel. Nobody chooses the cheapest one, or very few people do. Usually it’s a proper balance of all of these factors and how they best meet the total needs. We are seeing the same thing on the business procurement side.
When you look at what a procurement audience is doing, what a company is doing, there are now a lot of non-price factors.

Gardner: As consumers we have information at our fingertips -- so we can be savvy and smart – probably better than at any other time in history. But that doesn’t always translate to a larger business-to-business (B2B) decisions.

What sort of insights do you think businesses will want when it comes that broader visibility?

Koch: It starts with the basics. It starts with, “How do I know my suppliers? How do I add scale? Is this supplier General Data Protection Regulation (GDPR)-compliant? Do they have slavery or forced labor in their supply chain? Where are they sourcing their materials?” All of these aspects around supplier risk are the basics; knowing your supplier well is the basic element.

Then when you go beyond that, it's about things like, “Well how do I weigh geographic risk? How do I weigh supply chain risk?” And all the things that the practitioners of those disciplines have been screaming about for the rest of their companies to pay attention to.

That’s the new value they are providing. It's that progression and looking at the huge opportunity to see the way companies collaborate and share data strategically to drive efficiency into processes. That can drive efficiency ultimately into the whole value chain that leads to a better customer experience at the end.

Gardner: Customer experience is so important across the board. It must be a big challenge for you on the product side to be able to contextually bring the right information and options to the end-user at the right time. Otherwise they are overwhelmed, or they don't get the benefit of what the technology and the business networks can do.

What are you doing at SAP Ariba to help bring that right decision-making -- almost anticipating where the user needs to go -- into the actual applications and services?

Intelligent enterprise

Koch: That begins with our investments in re-platforming to SAP HANA. That feeds into the broader story about the intelligent enterprise. Purchasing is one facet, supply-chain management is a facet, sales is a facet, and production -- all of these components are elements of a broader story of how you synthesize data into a means where you have a digital twin of the whole enterprise.

Then you can start doing things like leveraging the in-memory capabilities of HANA around scenario planning, and around, “What are the implications of making this decision?”

What happens when a hurricane hits Puerto Rico and your supply chain is dramatically disrupted? Does that extend to my suppliers’ suppliers?  Who are my people on the ground there, and how are they disrupted? How should my business respond in an intelligent way to these world events that happen all the time?

Gardner: We have talked about the intelligent enterprise. Let's hypothetically say that when one or two -- or a dozen -- enterprises become intelligent that they gain certain advantages, which compels the rest of their marketplace to follow suit.

When we get to the point where we have a critical mass of intelligent enterprises, how does that elevate to an intelligent economy? What can we do when everyone is behaving with this insight, of having tools like SAP Ariba at their disposal?

Koch: You hit on a really valuable and important point. Way back, I was an economics major and there was a core thing that I took away 20 years ago from my intro to macroeconomics class. The core of it was that everything is either value or waste. Every bit of effort, everything that's produced around the world, all goods or services are either valuable or a waste. There is nothing in between.

The question then as we look at value chains, when we look at these webs of value, is how much of that is transaction cost? How much of that is information asymmetry? How much of that is basic barriers that get in the way of ultimately providing value to the end consumer? Where is all of that waste?

When you look at complex value chains, at all of the inventory sitting in warehouses, the things that go unsold, the mismatches between supply and demand across a value chain -- whether you are talking about direct materials or about pens and paper sitting in a supply closet -- it really doesn't matter.
When you look at complex value chains ... how much of that goes into actually delivering on what your customers and employees value -- and how much of it is waste?

It’s all about how much of that goes to actually delivering on what your customers, your employees, and your stakeholders’ value -- and how much of it is waste? As we link these data sets together -- the real production planning, understanding end-user demand, and all the way back through the supply chain – we can develop new transparency that brings a ton of value. And by ultimately everyone in the value chain understanding what the consumers’ actually value, then they can innovate in the right ways.

So, I see this all dramatically changing as you link these intelligent companies together. As companies move in the same way -- into a sharing mindset – then the sharing economy uses resources in a far more efficient way, in the exact same way as we use our data resources in a more efficient way.

Gardner: This also dovetails well with being purposeful as a business. If many organizations are encouraging higher productivity, which reduces inefficiencies and helps raise wages, it can lead to better standards of life. So, the stakes here are pretty high.

We’re not just talking about adding some dollars to the bottom and top lines. We’re also talking about a better economy that raises all boats.

Purposeful interconnections 

Koch: Yes, absolutely. You see companies like Johnson and Johnson, who at their core, from their founding principles, have the importance of their community as one of the core founding principles. You see it in companies like Ford and their long heritage. Those ideals are really coming back from the decade of the 1980s where greed was good and now back to a more holistic understanding of the interconnectedness of all of this.

And it’s good as humans. It’s also good from the business perspective because of the need to attract and retain the talent required to run a modern enterprise. And building the brands that our consumers are demanding, and holding companies accountable, they all go hand-in-hand.

And so, the purpose aspect really addresses the broader stakeholder aspects of creating a sustainable planet, a sustainable business, sustainable employment, and things like that.

Gardner: When we think about attaining this level of efficiency through insights and predictive analytics -- taking advantage of business networks and applications and services -- we are also on the cusp of getting even better tools.

We’re seeing a lot more information about machine learning (ML). We’re starting to tease out the benefits of artificial intelligence (AI). When these technologies are maturing and available, you need to be in a position to take advantage of them.

So, moving toward the intelligent enterprise and digital transformation are not just good or nice to have, they are essential because of what's going to come next in just a few years.

Efficiency in the digital future 

Koch: Yes, you see this very tactically in the chief procurement officers (CPOs) that I've talked with as I've entered this role. I have yet to run across any business leader who says, “I have so many resources, I don't know what to do.” That’s not usually what I hear. Usually, it's the opposite. It’s, “I'm being asked to do more with less.”

When you look at the core of AI, and the core of ML, it’s how do you increase efficiency? And that’s whether it's all the way on the full process automation side, or it’s along the spectrum of bringing the right intelligence and insights to streamline processes to make better decisions.

All of that is an effort to up-level the work that people do, so that raises wages, it raises productivity, all of those things. We have an example inside of our team. I was meeting with the head of our customer value organization, Chris Haydon, over dinner last night.  Chris was talking about how we were applying ML to enhance our capability to onboard new customers.

And he said the work that we've done has allowed him to redeploy 80 people in his team on to higher productivity use cases. All of those people became more valuable in the company because they were working on things that were at the next level of creating new solutions and better customer experiences, instead of turning the crank in the proverbial factory of deploying software.

Gardner: I happen to personally believe that a lot of the talk about robots taking over people’s jobs is hooey. And that, in fact, what's more likely is this elevation of people to do what they can do best and uniquely. Then let the machines do what they do best and uniquely.

How is that translating both into SAP Ariba products and services, and also into the synergy between SAP and SAP Ariba?
We're just getting through a major re-platforming to S/4 HANA and that's really exciting because of HANA's maturity and scale. We're using ML algorithms and applying them.

Koch: We are at a really exciting time inside of our products and services. We're just getting through a major re-platforming to S/4 HANA, and that’s really exciting because of HANA’s maturity and scale. It’s moving beyond basic infrastructure in the way that [SAP Co-Founder] Hasso Plattner had envisioned it.

We’re really getting to the point of not replicating data. We are using the ML algorithms and applying them, building them once and applying them at large. And so, the company’s investments in HANA and in Leonardo are helping to create a toolkit of capabilities that applications like SAP Ariba can leverage. Like with any good infrastructure investment, when you have the right foundation you see scale and innovation happen quickly.

You'll see a lot more of how we leverage the data that we have both inside the company as well as across the network to drive intelligence into our process. You will just see that come through more as we move from the infrastructure foundation setting stage to building the capabilities on top of that.

Gardner: Getting back to that concept of closing the transformation gap for companies, what is it they should be thinking about when these services and technologies become available? How can they help close their own technology gap by becoming acquainted in advances and taking some initiative to best use these new tools?

Digital transformation leadership 

Koch: The companies that are forward-leading on digital transformation are the ones that made the cloud move early. The next big move for them is to tap into business networks. How can they start sharing across their value chains and drive higher efficiency? I think you'll see from that the shift from tactical procurement to strategic procurement.

The relationships need to move from transactional to a true partnership, of how do we create value together? That change involves rethinking the ways you look at data and of how you share data across value chains.

Gardner: Let’s also think about spend management conceptually. Congratulations, by the way, on your recent Gartner Magic Quadrant positioning on pay-to-procure processes. How does spend management also become more strategic?

Koch: The building blocks for spend management always come down to what is our tactical spend and where should we focus our efforts for strategic spend? Whether that is in the services area, travel, direct materials, or indirect, what customers are asking SAP for is, how do all of these pieces fit together?

What's the difference between a request for proposal (RFP) for a hotel in New York City versus an RFP for chemicals in Southeast Asia? They're both a series of business processes of selecting the right vendor that balances all of the critical dimensions: Price and everything else that makes for a good decision and that has longevity.

We see a lot of shared elements in the way you interact with your suppliers. We see a lot of shared elements in the way that you deploy applications inside of your company. We’re exploring how well the different facets of the applications can work together, how seamless the user experience is, and how well all of these tie together for all the stakeholders.

Ultimately, each element of the team, each element of the company, has a role to play. That includes the finance organization’s desire to ensure that value is being created in a way that the company can afford. It means that the shareholders, employees, management, and end-users are all on the same page.

This is the core of spend management – and the intelligent enterprise as a whole. It means being able to see everything, by bringing it all together, so the company can manage its full operations and how they create value.

Gardner: The vision is very compelling. I can certainly see where this is not going to be just a small change -- but a step-change -- in terms of how companies can benefit in productivity.

As you were alluding to earlier, architecture is destiny when it comes to making this possible. By re-architecting around, as for S/4 HANA, by taking advantage of business networks, you are well on the way to delivering this. Let’s talk about the platform changes that grease the skids toward the larger holistic benefits.

Shifting to the cloud 

Koch: It's firmly our belief that the world is moving to mega-platforms. SAP has a long history of bringing the ecosystem along, whether the ecosystem is delivering process innovation or is building capabilities on top of other capabilities embedded deeply into the products.

What we're now seeing is the shift from the on-premises world to a cloud world where it's API-first, business events driven, and where you see a decoupling of the various components. Underneath the covers it doesn't matter what technology stack things are built on. It doesn't matter how quickly they evolve. It's the assumption that we have this API contract between two different pieces of technology: An SAP Ariba piece of technology, an SAP S/4 Cloud piece of technology, or a partner ecosystem piece of technology.

For example, a company like Solenis was recently up on stage with us at Ariba Live in Amsterdam. That's one of the fastest-growing companies. They have raised a B round at $1 billion valuation. Having companies that are driving innovation like that in partnership with an SAP platform brings not just near-term value for us and our customers, it brings future-proofing. It brings extensibility when there is a specific requirement that comes in for a specific industry or geography. It provides a way a customer can differentiate. You can just plug-in.
We're now seeing the shift from on-premises to cloud where you see a decoupling of the components. It doesn't matter what the technology stack is. ... It's now about API-first business events.

[SAP business unit] Concur has been down this path for a long time. The president of SAP Ariba, Barry Padgett, actually started the initiative of opening up the Concur platform. So deep at our core -- in our roots -- we believe that networks, ecosystems, and openness will ensure that our customers get the most value out of their solutions.

Gardner:Because SAP is an early adopter of multicloud, SAP can be everywhere at the most efficient level given what the hyperscale cloud providers are providing with global reach and efficiency. This approach also allows you to service small- to medium-sized businesses (SMBs), for example, essentially anywhere in the world.

Tell me why this long-term vision of a hyperscale-, multicloud-supported future benefits SAP, SAP Ariba, and its customers.

A hyperscale, multicloud landscape

Koch: When you look across the landscape of the hyperscalers and you look at the pace of innovation and the level of scale that that they are able to deliver, our lead time is slashed. We can also scale up and down as required. The cloud benefits apply to speed compared to having boxes installed in data centers, as well as ease in workload variability -- whether it's test variability or our ability to run ML-training models.

The idea that we still suffer multi-month lead times to get our physical boxes installed in our data centers is something that we just can't afford. Our customers demand more.

Thankfully there are multiple solutions around the world that solve these problems while at the same time giving us things like world-class security, geographic footprints, and localized expertise. When a server fails halfway around the world and the expert is somewhere else, the hyperscalers provide a solution to that problem.

They have somebody who walks through every data center and makes sure that the routers are upgraded, and the switches and load balancers are working the way they should. They determine whether data correctly rests inside of a Chinese firewall or inside of Europe [due to compliance requirements]. They are responsible for how those systems interact.

We still need to do our investment on the applications tier and in working with our customers to handle all of the needed changes in the landscape around data and security.

But the hyperscalers give us a base-level of infrastructure so we don't need to think about things like, “Is our air conditioner capacity inside of the data center sufficient to run the latest technology for the computing power?” We don't worry about that. We worry about delivering value on top of that base-level of infrastructure and so that takes our applications to the next level.

In the same way we were talking earlier about ML and AI freeing up our resources to work on higher-value things, [the multicloud approach] allows us to stop thinking about these base-level things that are still critical for the delivery of our service. It allows us to focus on the innovation aspects of what we need to do.

Gardner: It really is about driving value higher and higher and then making use of that in a way that's a most impactful to the consumers -- and ultimately the whole economy.

Koch: You got it.


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          Benjamin Weber: Learning from Pain      Cache   Translate Page      

Pain is something we generally try to avoid; pain is unpleasant, but it also serves an important purpose.

Acute pain can be feedback that we need to avoid doing something harmful to our body, or protect something while it heals. Pain helps us remember the cause of injuries and adapt our behaviour to avoid a repeat.

As a cyclist I occasionally get joint pain that indicates I need to adjust my riding position. If I just took painkillers and ignored the pain I’d permanently injure myself over time.

I’m currently recovering from a fracture after an abrupt encounter with a pothole. The pain is helping me rest and allow time for the healing process. The memory of the pain will also encourage me to consider the risk of potholes when riding with poor visibility in the future.

We have similar feedback mechanisms when planning, building, and running software; we often find things painful.

Alas, rather than learn from pain and let it guide us, we all too often stock up on painkillers in the form of tooling or practices that let us press on obstinately doing the same thing that caused the pain in the first place.

Here are some examples…

Painful Tests

Automated tests can be a fantastic source of feedback that helps us improve our software and learn to write better software in the future. Tests that are hard to write are a sign something could be better.

The tests only help us if we listen to the pain we feel when tests are hard to write and read. If we reach for increasingly sophisticated tooling to allow us to continue doing the painful things, then we won’t realise the benefits. Or worse, if we avoid unit testing in favour of higher level tests, we’ll miss out on this valuable feedback altogether.

Here’s an example of a test that was painful to write and read, testing the sending of a booking confirmation email.

@Test // Click to Expand, Full code in link above
public void sendsBookingConfirmationEmail() {
    var emailSender = new EmailSender() {
        String message;
        String to;

        public void sendEmail(String to, String message) {
            this.to = to;
            this.message = message;
        }

        public void sendHtmlEmail(String to, String message) {

        }

        public int queueSize() {
            return 0;
        }
    };

    var support = new Support() {
        @Override
        public AccountManager accountManagerFor(Customer customer) {
            return new AccountManager("Bob Smith");
        }

        @Override
        public void calculateSupportRota() {

        }

        @Override
        public AccountManager superviserFor(AccountManager accountManager) {
            return null;
        }
    };


    BookingNotifier bookingNotifier = new BookingNotifier(emailSender, support);

    Customer customer = new Customer("jane@example.com", "Jane", "Jones");
    bookingNotifier.sendBookingConfirmation(customer, new Service("Best Service Ever"));

    assertEquals("Should send email to customer", customer.email, emailSender.to);
    assertEquals(
        "Should compose correct email",
        emailSender.message,
        "Dear Jane Jones, you have successfully booked Best Service Ever on " + LocalDate.now() + ". Your account manager is Bob Smith"
    );

}
  • The test method is very long at around 50 lines of code
  • We have boilerplate setting up stubbing for things irrelevant to the test such as queue sizes and supervisors
  • We’ve got flakiness from assuming the current date will be the same in two places—the test might not pass if run at midnight, or when changing the time
  • There’s multiple assertions for multiple responsibilities
  • We’ve had to work hard to capture side effects

Feeling this pain, one response would be to reach for painkillers in the form of more powerful mocking tools. If we do so we end up with something like this. Note that we haven’t improved the implementation at all (it’s unchanged), but now we’re feeling a lot less pain from the test.

@Test // Click to Expand, Full code in link above
public void sendsBookingConfirmationEmail() throws Exception {
    var emailSender = mock(EmailSender.class);
    var support = mock(Support.class);

    BookingNotifier bookingNotifier = new BookingNotifier(emailSender, support);

    LocalDate expectedDate = LocalDate.parse("2000-01-01");
    Customer customer = new Customer("jane@example.com", "Jane", "Jones");
    when(support.accountManagerFor(customer)).thenReturn(new AccountManager("Bob Smith"));
    mockStatic(LocalDate.class, args -> expectedDate);

    bookingNotifier.sendBookingConfirmation(customer, new Service("Best Service Ever"));

    verify(emailSender).sendEmail(
        customer.email,
        "Dear Jane Jones, you have successfully booked Best Service Ever on 2000-01-01. Your account manager is Bob Smith"
    );

}
  • The test method is a quarter the length—-but the implementation is as complex
  • The flakiness is gone as the date is mocked to a constant value—but the implementation still has a hard dependency on the system time.
  • We’re no longer forced to stub irrelevant detail—but the implementation still has dependencies on collaborators with too many responsibilities.
  • We only have a single assertion—but there are still as many responsibilities in the implementation
  • It’s easier to capture the side effects—but they’re still there

A better response would be to reflect on the underlying causes of the pain. Here’s one direction we could go that removes much of the pain and doesn’t need complex frameworks

@Test // Click to Expand, Full code in link above
public void composesBookingConfirmationEmail() {

    AccountManagers dummyAllocation = customer -> new AccountManager("Bob Smith");
    Clock stoppedClock = () -> LocalDate.parse("2000-01-01");

    BookingNotificationTemplate bookingNotifier = new BookingNotificationTemplate(dummyAllocation, stoppedClock);

    Customer customer = new Customer("jane@example.com", "Jane", "Jones");

    assertEquals(
        "Should compose correct email",
        bookingNotifier.composeBookingEmail(customer, new Service("Best Service Ever")),
        "Dear Jane Jones, you have successfully booked Best Service Ever on 2000-01-01. Your account manager is Bob Smith"
    );

}
  • The test method is shorter, and the implementation does less
  • The flakiness is gone as the implementation no longer has a hard dependency on the system time
  • We’re no longer forced to stub irrelevant detail because the implementation only depends on what it needs
  • We only have a single assertion, because we’ve reduced the scope of the implementation to merely composing the email. We’ve factored out the responsibility of sending the email.
  • We’ve factored out the side effects so we can test them separately

My point is not that the third example is perfect (it’s quickly thrown together), nor am I arguing that mocking frameworks are bad. My point is that by learning from the pain (rather than rushing to hide it with tooling before we’ve learnt anything) we can end up with something better.

The pain we feel when writing tests can also be a prompt to reflect on our development process—do we spend enough time refactoring when writing the tests, or do we move onto the next thing as soon as they go green? Are we working in excessively large steps that let us get into messes like the above that are painful to clean up?

n.b. there’s lots of better examples of learning from test feedback in chapter 20 of the GOOS book.

Painful Dependency Injection

Dependency injection seems to have become synonymous with frameworks like spring, guice, dagger; as opposed to the relatively simple idea of “passing stuff in”. Often people reach for dependency injection frameworks out of habit, but sometimes they’re used as a way of avoiding design feedback.

If you start building a trivial application from scratch you’ll likely not feel the need for a dependency injection framework at the outset. You can wire up your few dependencies yourself, passing them to constructors or function calls.

As complexity increases this can become unwieldy, tedious, even painful. It’s easy to reach for a dependency injection framework to magically wire all your dependencies together to remove that boilerplate.

However, doing so prematurely can deprive you of the opportunity to listen to the design feedback that this pain is communicating.

Could you reduce the wiring pain through increased modularity—adding, removing, or finding better abstractions?

Does the wiring code have more detail than you’d include in a document explaining how it works? How can you align the code with how you’d naturally explain it? Is the wiring code understandable to a domain expert? How can you make it more so?

Here’s a little example of some manual wiring of dependencies. While short, it’s quite painful:

// Click to Expand, Full code in link above
public static void main(String... args) {
    var credentialStore = new CredentialStore();

    var eventStore = new InfluxDbEventStore(credentialStore);

    var probeStatusReporter = new ProbeStatusReporter(eventStore);

    var probeExecutor = new ProbeExecutor(new ScheduledThreadPoolExecutor(2), probeStatusReporter, credentialStore, new ProbeConfiguration(new File("/etc/probes.conf")));

    var alertingRules = new AlertingRules(new OnCallRota(new PostgresRotaPersistence(), LocalDateTime::now), eventStore, probeStatusReporter)

    var pager = new Pager(new SMSGateway(), new EmailGateway(), alertingRules, probeStatusReporter);

    var dashboard = new Dashboard(alertingRules, probeExecutor, new HttpsServer());
}
  • There’s a lot of components to wire together
  • There’s a mixture of domain concepts and details like database choices
  • The ordering is difficult to get right to resolve dependencies, and it obscures intent

At this point we could reach for a DI framework and @Autowire or @Inject these dependencies and the wiring pain would disappear almost completely.

However, if instead we listen to the pain, we can spot some opportunities to improve the design. Here’s an example of one direction we could go

// Click to Expand, Full code in link above
public static void main(String... args) {

    var probeStatus = probeExecutor();
    var probeVisibility = visibilityOf(probeStatus);
    var dashboard = dashboardFor(probeVisibility);
    var pager = pagerFor(probeVisibility);

}

private static ProbeVisibility visibilityOf(ProbeStatusReporter probeStatus) {
    var credentialStore = new CredentialStore();
    var eventStore = new InfluxDbEventStore(credentialStore);
    AlertingRules alertingRules = new AlertingRules(new OnCallRota(new PostgresRotaPersistence(), LocalDateTime::now), eventStore, probeStatus);
    return new ProbeVisibility(alertingRules, probeStatus);
}

static class ProbeVisibility {
    AlertingRules alertingRules;
    ProbeStatusReporter probeStatus;

    public ProbeVisibility(AlertingRules alertingRules, ProbeStatusReporter probeStatus) {
        this.alertingRules = alertingRules;
        this.probeStatus = probeStatus;
    }
}

private static Pager pagerFor(ProbeVisibility probeVisibility) {
    return new Pager(new SMSGateway(), new EmailGateway(), probeVisibility.alertingRules, probeVisibility.probeStatus);
}

private static Dashboard dashboardFor(ProbeVisibility probeVisibility) {
    return new Dashboard(probeVisibility.alertingRules, probeVisibility.probeStatus, new HttpsServer());
}

private static ProbeStatusReporter probeExecutor() {
    var credentialStore = new CredentialStore();
    var eventStore = new InfluxDbEventStore(credentialStore);

    var probeStatusReporter = new ProbeStatusReporter(eventStore);
    var executor = new ProbeExecutor(new ScheduledThreadPoolExecutor(2), probeStatusReporter, credentialStore, new ProbeConfiguration(new File("/etc/probes.conf")));
    executor.start();
    return probeStatusReporter;
}
  • We’ve spotted and fixed the dashboard’s direct dependency on the probe executor, it now uses the status reporter like the pager.
  • The dashboard and pager shared a lot of wiring as they had a common purpose in providing visibility on the status of probes. There was a missing concept here, adding it has simplified the wiring considerably.
  • We’ve separated the wiring of the probe executor from the rest.

After applying these refactorings the top level wiring reads more like a description of our intent.

Clearly this is just a toy example, and the refactoring is far from complete, but I hope it illustrates the point: dependency injection frameworks are useful, but be aware of the valuable design feedback they may be hiding from you.

Painful Integration

It’s common to experience “merge pain” when trying to integrate long lived branches of code and big changesets to create a releasable build. Sometimes the large changesets don’t even pass tests, sometimes your changes conflict with changes others on the team have made.

One response to this pain is to reach for increasingly sophisticated build infrastructure to hide some of the pain. Infrastructure that continually runs tests against branched code, or continually checks merges between branches can alert you to problems early. Sadly, by making the pain more bearable, we risk depriving ourselves of valuable feedback.

Ironically continuous-integration tooling often seems to be used to reduce the pain felt when working on large, long lived changesets; a practice I like to call “continuous isolation”.

You can’t automate away the human feedback available when integrating your changes with the rest of the team—without continuous integration you miss out on others noticing that they’re working in the same area, or spotting problems with your approach early.

You also can’t replace the production feedback possible from integrating small changes all the way to production (or a canary deployment) frequently.

Sophisticated build infrastructure can give you the illusion of safety by hiding the pain from your un-integrated code. By continuing to work in isolation you risk more substantial pain later when you integrate and deploy your larger, riskier changeset. You’ll have a higher risk of breaking production, a higher risk of merge conflicts, as well as a higher risk of feedback from colleagues being late, and thus requiring substantial re-work.

Painful Alerting

Over-alerting is a serious problem; paging people spuriously for non-existent problems or issues that do not require immediate attention undermines confidence, just like flaky test suites.

It’s easy to respond to overalerting by paying less and less attention to production alerts until they are all but ignored. Learning to ignore the pain rather than listening to its feedback.

Another popular reaction is to desire increasingly sophisticated tooling to handle the flakiness—from flap detection algorithms, to machine learning, to people doing triage. These often work for a while—tools can assuage some of the pain, but they don’t address the underlying causes.

The situation won’t significantly improve without a feedback mechanism in place, where you improve both your production infrastructure and approach to alerting based on reality.

The only effective strategy for reducing alerting noise that I’ve seen is: every alert results in somebody taking action to remediate it and stop it happening again—even if that action is to delete the offending alerting rule or amend it. Analyse the factors that resulted in the alert firing, and make a change to improve the reliability of the system.

Yes, this sometimes does mean more sophisticated tooling when it’s not possible to prevent the alert firing in similar spurious circumstances with the tooling available.

However it also means considering the alerts themselves. Did the alert go off because there was an impact to users, the business, or a threat to our error budget that we consider unacceptable? If not, how can we make it more reliable or relevant?

Are we alerting on symptoms and causes rather than things that people actually care about?
Who cares about a server dying if no users are affected? Who cares about a traffic spike if our systems handle it with ease?

We can also consider the reliability of the production system itself. Was the alert legitimate? Maybe our production system isn’t reliable enough to run (without constant human supervision) at the level of service we desire? If improving the sophistication of our monitoring is challenging, maybe we can make the system being monitored simpler instead?

Getting alerted or paged is painful, particularly if it’s in the middle of the night. It’ll only get less painful long-term if you address the factors causing the pain rather than trying hard to ignore it.

Painful Deployments

If you’ve been developing software for a while you can probably regale us with tales of breaking production. These anecdotes are usually entertaining, and people enjoy telling them once enough time has passed that it’s not painful to re-live the situation. It’s fantastic to learn from other people’s painful experiences without having to live through them ourselves.

It’s often painful when you personally make a change and it results in a production problem, at least at the time—not something you want to repeat.

Making a change to a production system is a risky activity. It’s easy to associate the pain felt when something goes wrong, with the activity of deploying to production, and seek to avoid the risk by deploying less frequently.

It’s also common to indulge in risk-management theatre: adding rules, processes, signoff and other bureaucracy—either because we mistakenly believe it reduces the risk, or because it helps us look better to stakeholders or customers. If there’s someone else to blame when things go wrong, the pain feels less acute.

Unfortunately, deploying less frequently results in bigger changes that we understand less well; inadvertently increasing risk in the long run.

Risk-management theatre can even threaten the ability of the organisation to respond quickly to the kind of unavoidable incidents it seeks to protect against.

Yes, most production issues are caused by an intentional change made to the system, but not all are. Production issues get caused by leap second bugs, changes in user behaviour, spikes in traffic, hardware failures and more. Being able to rapidly respond to these issues and make changes to production systems at short notice reduces the impact of such incidents.

Responding to the pain of deployments that break production by changing production less often, is pain avoidance rather than addressing the cause.

Deploying to production is like bike maintenance. If you do it infrequently it’s a difficult job each time and you’re liable to break something. Components seize together, the procedures are unfamiliar, and if you don’t test-ride it when you’re done then it’s unlikely to work when you want to ride. If this pain leads you to postpone maintenance, then you increase the risk of an accident from a worn chain or ineffective brakes.

A better response with both bikes and production systems is to keep them in good working order through regular, small, safe changes.

With production software changes we should think about how we can make it a safe and boring activity—-how can we reduce the risk of deploying changes to production, or how can we reduce the impact of deploying bad changes to production.

Could the production failure have been prevented through better tests?

Would the problem have been less severe if our production monitoring had caught it sooner?

Might we have spotted the problem ourselves if we had a culture of testing in production and were actually checking that our stuff worked once in production?

Perhaps canary deploys would reduce the risk of a business-impacting breakage?

Would blue-green deployments reduce the risk by enabling swift recovery?

Can we improve our architecture to reduce the risk of data damage from bad deployments?

There are many many ways to reduce the risk of deployments, we can channel the pain of bad deployments into improvements to our working practices, tooling, and architecture.

Painful Change

After spending days or weeks building a new product or feature, it’s quite painful to finally demo it to the person who asked for it and discover that it’s no longer what they want. It’s also painful to release a change into production and discover it doesn’t achieve the desired result, maybe no-one uses it, or it’s not resulting in an uptick to your KPI.

It’s tempting to react to this by trying to nail down requirements first before we build. If we agree exactly what we’re building up front and nail down the acceptance criteria then we’ll eliminate the pain, won’t we?

Doing so may reduce our own personal pain—we can feel satisfied that we’ve consistently delivered what was asked of us. Unfortunately, reducing our own pain has not reduced the damage to our organisation. We’re still wasting time and money by building valueless things. Moreover, we’re liable to waste even more of our time now that we’re not feeling the pain.

Again, we need to listen to what the pain’s telling us; what are the underlying factors that are leading to us building the wrong things?

Fundamentally, we’re never going to have perfect knowledge about what to build, unless we’re building low value things that have been built many times before. So instead let’s try to create an environment where it’s safe to be wrong in small ways. Let’s listen to the feedback from small pain signals that encourage us to adapt, and act on it, rather than building up a big risky bet that could result in a serious injury to the organisation if we’re wrong.

If we’re frequently finding we’re building the wrong things, maybe there are things we can change about how we work, to see if it reduces the pain.

Do we need to understand the domain better? We could spend time with domain experts, and explore the domain using a cheaper mechanism than software development, such as eventstorming.

Perhaps we’re not having frequent and quality discussions with our stakeholders? Sometimes minutes of conversation can save weeks of coding.

Are we not close enough to our customers or users? Could we increase empathy using personas, or attending sales meetings, or getting out of the building and doing some user testing?

Perhaps having a mechanism to experiment and test our hypotheses in production cheaply would help?

Are there are lighter-weight ways we can learn that don’t involve building software? Could we try selling the capabilities optimistically, or get feedback from paper prototypes, or could we hack together a UI facade and put it in front of some real users?

We can listen to the pain we feel when we’ve built something that doesn’t deliver value, and feed it into improving not just the product, but also our working practices and habits. Let’s make it more likely that we’ll build things of value in the future.

Acute Pain

Many people do not have the privilege of living pain-free most of the time, sadly we have imperfect bodies and many live with chronic pain. Acute pain, however, can be a useful feedback mechanism.

When we find experiences and day to day work painful, it’s often helpful to think about what’s causing that pain and, what we can do to eliminate the underlying causes, before we reach for tools and processes to work around or hide the pain.

Listening to small amounts of acute pain, looking for the cause and taking action sets up feedback loops that help us improve over time; ignoring the pain leads to escalating risks that build until something far more painful happens.

What examples do you have of people treating the pain rather than the underlying causes?


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          Ini Bukti Kalau Samsung Galaxy Note 9 Optimal Buat Main Gim      Cache   Translate Page      

Liputan6.com, Jakarta Bagi kamu yang sering main gim mobile di smartphone, pasti setuju bila waktu dan akurasi adalah segalanya. Perubahan sedikit saja pada kinerja smartphone, seperti rasio FPS (frame per second) yang tidak stabil, bisa jadi antara hidup dan mati.

Kamu juga ingin memastikan smartphone kesayangan sudah dilengkapi dengan hardware dan software yang dapat diandalkan. Samsung mengklaim, Galaxy Note 9 memiliki spesifikasi yang bisa mengoptimalkan berbagai jenis gim mobile.

Mau bukti? Yuk, kita lihat lebih dekat beberapa teknologi inovatif yang membuat gim di Galaxy Note 9 terasa ringan dan begitu menyenangkan.

Ketika kamu berada di tengah-tengah pertempuran epik atau yang begitu dekat dengan pencapaian skor tinggi, ada beberapa hal yang membuat frustrasi.

Salah satu hal tersebut adalah saat prosesor terlalu banyak bekerja, sehingga menyebabkan penurunan tiba-tiba pada frekuensi gambar yang membuat kamu kehilangan fokus atau menjadi sasaran empuk serangan musuh. 

Karena kinerja CPU dan GPU smartphone bisa menempatkan kamu ke posisi menang atau kalah. Samsung mengoptimalkan Galaxy Note 9 dengan prosesor 10-nanometer terkini, dan diklaim mampu menangani gim dengan grafis yang intensif secara mudah.

Hal ini memungkinkan perangkat untuk memberikan kinerja CPU dan GPU 33 persen dan 23 persen lebih baik daripada Galaxy Note 8.

Dalam keterangan resminya, Kamis (13/9/2018), Samsung menyebut Galaxy Note 9 juga dilengkapi algoritme penyesuaian kinerja perangkat berbasis artificial intelligence (AI/kecerdasan buatan).

Dengan begini, AI mampu secara teratur memantau panas dan kinerja perangkat, mendukung hingga 40 persen FPS yang lebih stabil saat bermain gim.

Samsung Galaxy Note 9. Dok: Samsung Indonesia#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

Berkat teknologi machine learning, perangkat dapat memprediksi perubahan suhu sebelum mencapai titik panas yang tinggi serta menyesuaikan CPU dan GPU, sebelum penurunan FPS terjadi.

Itu berarti visual yang ditampilkan akan lebih halus dan pengalaman lebih menyenangkan saat bermain gim dengan grafis yang intensif seperti Fortnite.

 

 

Tetap Dingin Meski di Bawah Tekanan

Tampak depan Samsung Galaxy Note 9. Liputan6.com/ Aditya Eka Prawira#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

Memainkan gim dengan grafis yang intensif dalam waktu lama dapat membuat tekanan tinggi pada CPU dan GPU smartphone.

Untuk membantu Galaxy Note 9 bekerja secara konsisten pada level maksimum di seluruh gim, sistem pendinginan baru dibuat lebih cepat dan efisien daripada generasi sebelumnya.

Water Carbon Cooling System pada Galaxy Note 9 dirancang khusus memungkinkan perangkat menjadi dingin selama sesi permainan berat.

Sistem yang pertama kali diperkenalkan di Galaxy S7 ini menggunakan perubahan dalam fase cairan (cairan pendingin) untuk memancarkan panas secara efisien, dengan siklus di mana cairan dalam struktur berpori menyerap panas, berubah menjadi uap, bergerak melalui pipa dan akhirnya menjadi cairan untuk mendinginkan kembali.

Samsung meningkatkan sistem di Galaxy Note 9 dengan heat pipe, atau thermal spreader, yang tiga kali lebih besar dari Galaxy Note 8, dan membuang panas lebih efektif.

Selain itu juga meningkatkan asupan cairan pada internal sistem untuk melakukan penyerapan panas lebih besar, dan menggabungkan serat karbon TIM (thermal interface material) yang bisa mentransfer panas dari prosesor ke penyebar termal dengan efisiensi 3,5 kali lebih besar, sehingga meningkatkan konduktivitas termal.  

Inovasi ini memungkinkan Galaxy Note 9 berjalan lancar meski dipakai bermain gim berlama-lama, sehingga membuat kami lebih nyaman saat bermain gim favorit.

Kontrol Lebih Banyak

Hamish Daud ketika mencoba secara langsung Samsung Galaxy Note 8 di New York. Liputan6.com/ Aditya Eka Prawira#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

Gangguan seperti panggilan telepon dan notifikasi pesan bisa menjadi tidak menyenangkan saat bermain gim di smartphone. Game Launcher, one-stop hub untuk mobile gaming pada perangkat Samsung Galaxy, merupakan solusi untuk mengatasi masalah tersebut.

Menawarkan berbagai tools dan fitur inovatif, Game Launcher memungkinkan pemain berkonsentrasi penuh saat bermain gim dengan mencegah notifikasi atau pun menyentuh layar secara tidak sengaja. Kamu juga dapat berbagi pengalaman bermain gim menggunakan screenshot atau fungsi rekam video.

Game Launcher yang ditingkatkan di Galaxy Note 9 juga memungkinkan kamu untuk menentukan frame rate, resolusi, dan tingkat penggunaan baterai.

Selain itu, fungsi window pop-up juga telah ditambahkan, sehingga kamu bisa membuka meluncurkan aplikasi tertentu dengan mudah, seperti mencari tips dan trik menang di YouTube atau berbagi informasi gim online selama bermain gim.

Baterai yang bisa tahan seharian pada Galaxy Note 9 membuat kamu bisa bermain gim lebih intens dan imersif. Kapasitas baterai 4.000 mAh yang ada juga bisa membuat kamu mengatur gim dengan grafis tinggi.

Galaxy Note 9 memungkinkan kamu menikmati permainan tanpa perlu terus-menerus mengawasi sisa baterai, atau khawatir harus melakukan charge smartphone untuk memperpanjang sesi gim. Dengan speaker stereo yang didukung oleh AKG, Galaxy Note 9 juga menawarkan output audio yang mendalam.

(Isk/Ysl)

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We require a motivated person to find the main contact number of companies. A spreadsheet of company names will be provided. We just need to check that they have a google maps listing with a telephone number. The number will then need to be cut and pasted into the correct field in the spreadsheet provided. We need as many gathering a possible everyday.

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          Multi-Person Pose Estimation in OpenCV using OpenPose      Cache   Translate Page      

In ourprevious post, we used the OpenPose model to perform Human Pose Estimation for a single person. In this post, we will discuss how to perform multi-person pose estimation.

When there are multiple people in a photo, pose estimation produces multiple independent keypoints. We need to figure out which set of keypoints belong to the same person.

We will be using the 18 point model trained on the COCO dataset for this article. The keypoints along with their numbering used by the COCO Dataset is given below:

COCO Output Format

Nose 0, Neck 1, Right Shoulder 2, Right Elbow 3, Right Wrist 4,

Left Shoulder 5, Left Elbow 6, Left Wrist 7, Right Hip 8,

Right Knee 9, Right Ankle 10, Left Hip 11, Left Knee 12,

LAnkle 13, Right Eye 14, Left Eye 15, Right Ear 16,

Left Ear 17, Background 18

1. Network Architecture

The OpenPose architecture is shown below. Click to enlarge the image.


Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 1: Multi-Person Pose Estimation model architecture

The model takes as input a color image of size h x w and produces, as output, an array of matrices which consists of the confidence maps of Keypoints and Part Affinity Heatmaps for each keypoint pair. The above network architecture consists of two stages as explained below:

Stage 0 : The first 10 layers of the VGGNet are used to create feature maps for the input image. Stage 1 : A 2-branch multi-stage CNN is used where The first branch predicts a set of 2D Confidence Maps

(S) of body part locations ( e.g. elbow, knee etc.). A Confidence Map is a grayscale image which has a high value at locations where the likelihood of a certain body part is high. For example, the Confidence Map for the Left Shoulder is shown in Figure 2 below. It has high values at all locations where the there is a left shoulder.

For the 18 point model, the first 19 matrices of the output correspond to the Confidence Maps.


Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 2 : Showing confidence maps for Left Shoulder for the given image The second branch predicts a set of 2D vector fields (L) of Part Affinities (PAF), which encode the degree of association between parts (keypoints). The 20th to 57th matrices are the PAF matrices. In the figure below part affinity between the Neck and Left shoulder is shown. Notice there is a large affinity between parts belonging to the same person.
Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 3 : Showing Part Affinity maps for Neck Left Shoulder pair for the given image

The Confidence Maps are used to find the keypoints and the Affinity Maps are used to get the valid connections between the keypoints.

Please download code using the link below to follow along with the tutorial.

I would like to thank my teammate Chandrashekara Keralapura for writing the C++ version of the code.

Download Code

To easily follow along this tutorial, please download code by clicking on the button below. It’s FREE!

Download Code

2. Download Model Weights

Use the getModels.sh file provided with the code to download the model weights file. Note that the configuration proto files are already present in the folders.

From the command line, execute the following from the downloaded folder.

sudo chmod a+x getModels.sh ./getModels.sh

Check the folders to ensure that the model binaries (.caffemodel files ) have been downloaded. If you are not able to run the above script, then you can download the model by clicking here . Once you download the weight file, put it in the “pose/coco/” folder.

3. Step 1: Generate output from image 3.1. Load Network python protoFile = "pose/coco/pose_deploy_linevec.prototxt" weightsFile = "pose/coco/pose_iter_440000.caffemodel" net = cv2.dnn.readNetFromCaffe(protoFile, weightsFile) C++ cv::dnn::Net inputNet = cv::dnn::readNetFromCaffe("./pose/coco/pose_deploy_linevec.prototxt","./pose/coco/pose_iter_440000.caffemodel"); 3.2. Load Image and create input blob Python image1 = cv2.imread("group.jpg") # Fix the input Height and get the width according to the Aspect Ratio inHeight = 368 inWidth = int((inHeight/frameHeight)*frameWidth) inpBlob = cv2.dnn.blobFromImage(image1, 1.0 / 255, (inWidth, inHeight), (0, 0, 0), swapRB=False, crop=False) C++ std::string inputFile = "./group.jpg"; if(argc > 1){ inputFile = std::string(argv[1]); } cv::Mat input = cv::imread(inputFile,CV_LOAD_IMAGE_COLOR); cv::Mat inputBlob = cv::dnn::blobFromImage(input,1.0/255.0, cv::Size((int)((368*input.cols)/input.rows),368), cv::Scalar(0,0,0),false,false); 3.3. Forward pass through the Net Python net.setInput(inpBlob) output = net.forward() C++ inputNet.setInput(inputBlob); cv::Mat netOutputBlob = inputNet.forward(); 3.4. Sample Output

We first resize the output to the same size as that of the input. Then we check the confidence map corresponding to the nose keypoint. You can also use cv2.addWeighted function for alpha blending the probMap on the image.

i = 0 probMap = output[0, i, :, :] probMap = cv2.resize(probMap, (frameWidth, frameHeight)) plt.imshow(cv2.cvtColor(image1, cv2.COLOR_BGR2RGB)) plt.imshow(probMap, alpha=0.6)
Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 4 : Showing the confidence map corresponding to the nose Keypoint. 4. Step 2: Detection of keypoints

As seen from the above figure, the zeroth matrix gives the confidence map for the nose. Similarly, the first Matrix corresponds to the neck and so on. As discussed in our previous post, for a single person, it is very easy to find the location of each keypoint just by finding the maximum of the confidence map. But for multi-person scenario, we can’t do this.

NOTE:The explanation and code snippets in this section belong to the getKeypoints() function.

For every keypoint, we apply a threshold ( 0.1 in this case ) to the confidence map.

Python mapSmooth = cv2.GaussianBlur(probMap,(3,3),0,0) mapMask = np.uint8(mapSmooth>threshold) C++ cv::Mat smoothProbMap; cv::GaussianBlur( probMap, smoothProbMap, cv::Size( 3, 3 ), 0, 0 ); cv::Mat maskedProbMap; cv::threshold(smoothProbMap,maskedProbMap,threshold,255,cv::THRESH_BINARY);

This gives a matrix containing blobs in the region corresponding to the keypoint as shown below.


Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 5 : Confidence Map after applying threshold

In order to find the exact location of the keypoints, we need to find the maxima for each blob. We do the following :

First find all the contours of the region corresponding to the keypoints. Create a mask for this region. Extract the probMap for this region by multiplying the probMap with this mask. Find the local maxima for this region. This is done for each contour ( keypoint region ). Python #find the blobs _, contours, _ = cv2.findContours(mapMask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) #for each blob find the maxima for cnt in contours: blobMask = np.zeros(mapMask.shape) blobMask = cv2.fillConvexPoly(blobMask, cnt, 1) maskedProbMap = mapSmooth * blobMask _, maxVal, _, maxLoc = cv2.minMaxLoc(maskedProbMap) keypoints.append(maxLoc + (probMap[maxLoc[1], maxLoc[0]],)) C++ std::vector<std::vector<cv::Point> > contours; cv::findContours(maskedProbMap,contours,cv::RETR_TREE,cv::CHAIN_APPROX_SIMPLE); for(int i = 0; i < contours.size();++i){ cv::Mat blobMask = cv::Mat::zeros(smoothProbMap.rows,smoothProbMap.cols,smoothProbMap.type()); cv::fillConvexPoly(blobMask,contours[i],cv::Scalar(1)); double maxVal; cv::Point maxLoc; cv::minMaxLoc(smoothProbMap.mul(blobMask),0,&maxVal,0,&maxLoc); keyPoints.push_back(KeyPoint(maxLoc, probMap.at<float>(maxLoc.y,maxLoc.x)));

We save the x, y coordinates and the probability score for each keypoint. We also assign an ID to each key point that we have found. This will be used later while joining the parts or connections between keypoint pairs.

Given below are the detected keypoints for the input image. You can see that it does a nice job even for partly visible person and even for person facing away from the camera.


Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 6 : Detected Keypoints overlayed on the input image

Also, the keypoints without overlaying it on the input image is shown below.


Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 7 : Detected points overlayed on a black background.

From the first image, you can see that we have found all the keypoints. But when the keypoints are not overlayed on the image (Figure 7), we cannot tell which part belongs to which person. We have to robustly map each keypoint to a person. This part is not trivial and can result in a lot of errors if not done correctly. For this, we will find the valid connections ( or valid pairs ) between the keypoints and then assemble these connections to create skeletons for each person.

5. Step 3 : Find Valid Pairs

A valid pair is a body part joining two keypoints, belonging to the same person. One simple way of finding the valid pairs would be to find the minimum distance between one joint and all possible other joints. For example, in the figure given below, we can find the distance between the marked Nose and all other Necks. The minimum distance pair should be the one corresponding to the same person.


Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 8 : Getting the connection between keypoints by using a simple distance measure.

This approach might not work for all pairs; specially, when the image contains too many people or there is occlusion of parts. For example, for the pair, Left-Elbow -> Left Wrist The wrist of the 3rd person is closer to the elbow of the 2nd person as compared to his own wrist. Thus, it will not result in a valid pair.


Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 9 : Only using distance between keypoints might fail in some cases.

This is where the Part Affinity Maps come into play. They give the direction along with the affinity between two joint pairs. So, the pair should not only have minimum distance, but their direction should also comply with the PAF Heatmaps direction.

Given below is the Heatmap for the Left-Elbow -> Left-Wrist connection.


Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 10 : Showing Part Affinity Heatmaps for the Left-Elbow -> Left-Wrist pair.

Thus, in the above case, even though the distance measure wrongly identifies the pair, OpenPose gives correct result since the PAF will comply only with the unit vector joining Elbow and Wrist of the 2nd person.

The approach taken in the paper is as follows : Divide the line joining the two points comprising the pair. Find “n” points on this line. Check if the PAF on these points have the same direction as that of the line joining the points for this pair. If the direction matches to a certain extent, then it is valid pair.

Let’s see how it is done in code; The code snippets belong to the getValidPairs() function in code provided.

For each body part pair, we do the following :

Take the keypoints belonging to a pair. Put them in separate lists (candA and candB). Each point from candA will be connected to some point in candB. The figure given below shows the points in candA and candB for the pair Neck -> Right-Shoulder.
Multi-Person Pose Estimation in OpenCV using OpenPose
Figure 11 : Showing the candidates for matching for the pair Neck -> Nose. Python pafA = output[0, mapIdx[k][0], :, :] pafB = output[0, mapIdx[k][1], :, :] pafA = cv2.resize(pafA, (frameWidth, frameHeight)) pafB = cv2.resize(pafB, (frameWidth, frameHeight)) # Find the keypoints for the first and second limb candA = detected_keypoints[POSE_PAIRS[k][0]] candB = detected_keypoints[POSE_PAIRS[k][1]] C++ //A->B constitute a limb cv::Mat pafA = netOutputParts[mapIdx[k].first]; cv::Mat pafB = netOutputParts[mapIdx[k].second]; //Find the keypoints for the first and second limb const std::vector<KeyPoint>& candA = detectedKeypoints[posePairs[k].first]; const std::vector<KeyPoint>& candB = detectedKeypoints[posePairs[k].second]; Find the unit vector joining the two points in consideration. This gives the direction of the line joining them. Python d_ij = np.subtract(candB[j][:2], candA[i][:2]) norm = np.linalg.norm(d_ij) if norm: d_ij = d_ij / norm C++ std::pair<float,float> distance(candB[j].point.x - candA[i].point.x,candB[j].point.y - candA[i].point.y); float norm = std::sqrt(distance.first*distance.first + distance.second*distance.second); if(!norm){ continue; } distance.first /= norm; distance.second /= norm; Create an array of 10 interpolated points on the line joining the two points. Python # Find p(u) interp_coord = list(zip(np.linspace(candA[i][0], candB[j][0], num=n_interp_samples), np.linspace(candA[i][1], candB[j][1], num=n_interp_samples))) # Find L(p(u)) paf_interp = [] for k in range(len(interp_coord)): paf_interp.append([pafA[int(round(interp_coord[k][1])), int(round(interp_coord[k][0]))], pafB[int(round(interp_coord[k][1])), int(round(interp_coord[k][0]))] ]) C++ //Find p(u) std::vector<cv::Point> interpCoords; populateInterpPoints(candA[i].point,candB[j].point,nInterpSamples,interpCoords); //Find L(p(u)) std::vector<std::pair<float,float>> pafInterp; for(int l = 0; l < interpCoords.size();++l){ pafInterp.push_back( std::pair<float,float>( pafA.at<float>(interpCoords[l].y,interpCoords[l].x), pafB.at<float>(interpCoords[l].y,interpCoords[l].x) )); } Take the dot product between the PAF on these points and the unit vector d_ij Python # Find E paf_scores = np.dot(paf_interp, d_ij) avg_paf_score = sum(paf_scores)/len(paf_scores) C++ std::vector<float> pafScores; float sumOfPafScores = 0; int numOverTh = 0; for(int l = 0; l< pafInterp.size();++l){ float score = pafInterp[l].first*distance.first + pafInterp[l].second*distance.second; sumOfPafScores += score; if(score > pafScoreTh){ ++numOverTh; } pafScores.push_back(score); } float avgPafScore = sumOfPafScores/((float)pafInterp.size()); Term the pair as valid if 70% of the points satisfy the criteria. Python # Check if the connection is valid # If the fraction of interpolated vectors aligned with PAF is higher then threshold -> Valid Pair if ( len(np.where(paf_scores > paf_score_th)[0]) / n_interp_samples ) > conf_th : if avg_paf_score > maxScore: max_j = j maxScore = avg_paf_score C++ if(((float)numOverTh)/((float)nInterpSamples) > confTh){ if(avgPafScore > maxScore){ maxJ = j; maxScore = avgPafScore; found = true; } } 6. Step 4 : Assemble Person-wise Keypoints

Now that we have joined all the keypoints into pairs, we can assemble the pairs that share the same part detection candidates into full-body poses of multiple people.

Let us see how it is done in code; The code snippets in this section belong to the getPersonwiseKeypoints() function in the provided code

We first create empty lists to store the keypoints for each person. Then we go over each pair, check if partA of the pair is already present in any of the lists. If it is present, then it means that the keypoint belongs to this list and partB of this pair should also belong to this person. Thus, add partB of this pair to the list where partA was found. Python for j in range(len(personwiseKeypoints)): if personwiseKeypoints[j][indexA] == partAs[i]: person_idx = j found = 1 break if found: personwiseKeypoints[person_idx][indexB] = partBs[i] C++ for(int j = 0; !found && j < personwiseKeypoints.size();++j){ if(indexA < personwiseKeypoints[j].size() && personwiseKeypoints[j][indexA] == localValidPairs[i].aId){ personIdx = j; found = true; } }/* j */ if(found){ personwiseKeypoints[personIdx].at(indexB) = localValidPairs[i].bId; } If partA is not present in any of the lists, then it means that the pair belongs to a new person not in the list and thus, a new list is created. Python # if find no partA in the subset, create a new subset elif not found and k < 17: row = -1 * np.ones(19) row[indexA] = partAs[i] row[indexB] = partBs[i] C++ else if(k < 17){ std::vector<int> lpkp(std::vector<int>(18,-1)); lpkp.at(indexA) = localValidPairs[i].aId; lpkp.at(indexB) = localValidPairs[i].bId; personwiseKeypoints.push_back(lpkp); } 7. Results

We go over each each person and plot the skeleton on the input image

Python for i in range(17): for n in range(len(personwiseKeypoints)): index = personwiseKeypoints[n][np.array(POSE_PAIRS[i])] if -1 in index: continue B = np.int32(keypoints_list[index.astype(int), 0]) A = np.int32(keypoints_list[index.astype(int), 1]) cv2.line(frameClone, (B[0], A[0]), (B[1], A[1]), colors[i], 2, cv2.LINE_AA) cv2.imshow("Detected Pose" , frameClone) cv2.waitKey(0) C++ for(int i = 0; i< nPoints-1;++i){ for(int n = 0; n < personwiseKeypoints.size();++n){ const std::pair<int,int>& posePair = posePairs[i]; int indexA = personwiseKeypoints[n][posePair.first]; int indexB = personwiseKeypoints[n][posePair.second]; if(indexA == -1 || indexB == -1){ continue; } const KeyPoint& kpA = keyPointsList[indexA]; const KeyPoint& kpB = keyPointsList[indexB]; cv::line(outputFrame,kpA.point,kpB.point,colors[i],2,cv::LINE_AA); } } cv::imshow("Detected Pose",outputFrame); cv::waitKey(0);

The figure below shows the skeletons for each of the detected persons!


Multi-Person Pose Estimation in OpenCV using OpenPose

Do check out the code provided with the post!

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References

[Video used for demo] [OpenPose Paper] [OpenPose reimplementation in Keras]
          Research Scientist Machine Learning - Intel - Hillsboro, OR      Cache   Translate Page      
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          Systech Announces Partnership with FarmaTrust to Deliver Foolproof Pharmaceutical Blockchain Solution      Cache   Translate Page      

Revolutionary solution provides authentic, safe and connected products throughout the pharmaceutical supply chain

PRINCETON, New Jersey and LONDON, Sept. 12, 2018 /PRNewswire/ -- Systech, a global technology leader in brand protection and product authentication, and FarmaTrust, a leader in pharmaceutical supply chain security, today announced their strategic partnership. This partnership provides a revolutionary blockchain-enabled solution for the pharmaceutical industry that leverages FarmaTrust's blockchain and AI technologies. The Systech platform will now provide a solution that goes beyond today's current compliance, traceability, anti-counterfeit and product safety solutions, enabling clients to ensure product authenticity from the manufacturing floor to a patient's hands.

The counterfeit drugs trade is thought to be the world's largest fraud market. The WHO estimates counterfeit drug revenue at around $200 billion, with an estimated 10-15 percent of worldwide pharmaceutical trade sold on the black market, internet and to patients via prescription medication.

"In Systech's continued commitment to advance supply chain security, we have partnered with FarmaTrust to integrate their proven blockchain solutions," said Ara Ohanian, CEO of Systech. Mr. Ohanian continued, "By combining their bulletproof blockchain and AI solution with our authenticated and trusted e-Fingerprint® technology, we have created a foolproof solution in the fight for pharmaceutical supply chain safety and authenticity."

Raja Sharif, FarmaTrust's CEO stated "This is a significant deal and we are fortunate to work with Systech and integrate our blockchain technology with their compliance, traceability and authentication solutions. This combination is the only non-additive solution that can guarantee product authenticity throughout the supply chain journey. It's also great to have a partner who has global coverage as well as a 32-year history of partnering with the world's 20 largest pharma companies."

About FarmaTrust
FarmaTrust is the most efficient global pharmaceutical tracking system, ensuring that counterfeit drugs do not enter the supply chain and providing security to pharmaceutical companies, governments, regulators and the public. FarmaTrust's blockchain based system utilizes Artificial Intelligence, Machine Learning, and big data analysis to deliver value added services, efficiency, and a transparent supply chain. The FarmaTrust system is safe, secure, encrypted, immutable and future proof. FarmaTrust is based in London, United Kingdom.

About Systech
Systech is the global technology leader in supply chain security and product authentication. For more than 32 years, we have put technology on the line. Systech pioneered pharmaceutical serialization as well as innovations in line vision and inspection, overall packaging line management and track and trace. The Systech platform is implemented in over 500 customer sites spanning 47 countries, supporting 1700+ active lines.

Today, Systech is revolutionizing brand protection. Our software solutions ensure products are authentic, safe and connected--from manufacturing to the consumer's hands.

Contacts:
Systech
Stacey Owens-Perrotta
T +1 609 235 3639
stacey.owens-perrotta@systechone.com

FarmaTrust
Motti Peer
motti@blonde20.com

Related Links :

http://systechone.com


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Security experts from Trend Micro have spotted a new strain of ransomware involved in attacks in July and August, the malicious code was posing as the Locky ransomware. Researchers at Trend Micro have detected a new ransomware family, dubbed PyLocky, that was used in attacks between July and August, the malware was posing as the Locky ransomware using its ransom […]

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          (USA-NY-New York) Engineering Director, Data Science      Cache   Translate Page      
*The Team:* The Data science team is a newly formed applied research team within S&P Global Ratings that will be responsible for building and executing a bold vision around using Machine Learning, Natural Language Processing, Data Science, knowledge engineering, and human computer interfaces for augmenting various business processes. *The Impact:* This role will have a significant impact on the success of our data science projects ranging from choosing which projects should be undertaken, to delivering highest quality solution, ultimately enabling our business processes and products with AI and Data Science solutions. *What s in it for you:* This is a high visibility leadership role with an opportunity to make meaningful impact on the future direction of the company. You will define new opportunities for business impact and will work closely with other senior leaders to work on the entire pipeline from ideation to production to user adoption. *Responsibilities:* As a Director you will be the technical lead on projects and be responsible for solution design and implementation. You will need to work closely with internal stakeholders and users, mentor junior scientists, and identify opportunities that lead to business impact and ultimately drive the Data Science vision. You will be responsible for determining the algorithmic implementation best suited for a use case, and the experimental design for testing its efficacy. *Basic Qualifications:* MS in Computer Science, Computational Linguistics, Artificial Intelligence or related field with 10 years of relevant industry experience *Preferred Qualifications:* * Degree in Computer Science, Computational Linguistics, Artificial Intelligence or related field with 7 years of relevant industry experience * Experience in mentoring or managing junior scientists and engineers, working with business stakeholders and users, providing research direction and solution design * Knowledge and working experience in one or more of the following areas:* Natural Language Processing, Machine Learning, Question Answering, Text Mining, Information Retrieval, Distributional Semantics, Data Science, Knowledge Engineering * Proficient programming skills in a high-level language (e.g. Java, Scala, Python, C - C , Perl, Matlab, R) * Experience with statistical data analysis, experimental design, and hypotheses validation * Project-based experience with some of the following tools:* * Applied machine learning (e.g. libSVM, Shogun, Scikit-learn or similar) * Natural Language Processing (e.g., ClearTK, ScalaNLP - Breeze, ClearNLP, OpenNLP, NLTK, or similar) * Statistical data analysis and experimental design (e.g., using R, Matlab, iPython, etc.) * Information retrieval and search engines, e.g. Solr - Lucene * Distributed computing platforms, such as Hadoop (Hive, HBase, Pig), Spark, GraphLab * Databases (traditional and noSQL)
          (Senior) Product Specialist - SAP Machine Learning for Sales and Service - SAP - Walldorf      Cache   Translate Page      
SAP's vision for Machine Learning is to focus on solving real business problems that will have huge business impact....
Gefunden bei SAP - Wed, 04 Jul 2018 11:34:10 GMT - Zeige alle Walldorf Jobs
          Senior Developer/Development Architect SAP S/4 HANA & SAP Cloud Platform (F/M) SAP INNOVATIVE B - SAP - Sankt Leon-Rot      Cache   Translate Page      
We make innovation real by using the latest technologies around the Internet of Things, blockchain, artificial intelligence / machine learning, and big data and...
Gefunden bei SAP - Tue, 11 Sep 2018 17:37:26 GMT - Zeige alle Sankt Leon-Rot Jobs
          Management Assistant (f/m) SAP Innovative Business Solutions - SAP - Sankt Leon-Rot      Cache   Translate Page      
We make innovation real by using the latest technologies around the Internet of Things, blockchain, artificial intelligence / machine learning, and big data and...
Gefunden bei SAP - Tue, 11 Sep 2018 17:36:57 GMT - Zeige alle Sankt Leon-Rot Jobs
          Senior Software Engineer (A.I)      Cache   Translate Page      
TX-Austin, To avoid delays in having your resume reviewed please forward directly to: ____________________________________________________________________________________ Sam.Major@RAndstadUSA.com ____________________________________________________________________________________ JOB TITLE: Senior Software Engineer (Computer Vision & Machine Learning) LOCATION: Austin, TX 78702 (Relocation Assistance Provid
          AI Carving The Niche Of Digital Advertising      Cache   Translate Page      


AI Carving The Niche Of Digital Advertising

Artificial Intelligence (AI) is one of the complicated terms of the modern age, many sectors feel intimidated by the concept of using machines to make decisions. People feel uneasiness in relying on machines to take actions and consider AI as a threat to mankind.

On the other hand, marketing & advertising industry is among those sectors who have utilized AI technology in creating better business opportunities. In digital advertising using data to make a decision isn't a new concept. The online advertising industry has been familiar with AI and has used the technology for creating better decisions to inspire innovation. Artificial intelligence has been a catalyst in the constant growth of digital advertising.  

Data Learning System

In digital advertising, the term AI is closely linked with machine learning, where the computer system improves its performance by data analysis without any human intrusion. In digital advertising the technology is often used to observe the consumer online behavior and then create a personalized advertisement for the customer. For example, if the consumer makes 10 impressions on an individual product then ads featuring the same and similar products will appear on his wall. This form of artificial intelligence is also termed as data learning system which has played a vital role in generating sales.

Natural Learning Process

Natural learning process (NLP) is a technique that involves the learning of human language by a machine. Due to variation in language and accents, it often gets difficult for machines to understand the human language. Natural learning process improves machine learning for better communication and interaction between humans and machines.

Currently, the NLP in artificial intelligence can be found in multiple devices such as Amazon - Alexa, Apple -Siri, Google - Assistant etc. have shown how technology can make our lives easier and hassle-free. In the present world our life revolves around AI, such devices have transformed into a part of our day to day life.  Advertising and marketing industry has used NLP to improve the customer buying behavior.

Chatbots

In the present-day majority of advertisers use chatbots as another form of artificial intelligence to make customer shopping experience smooth and memorable. A chatbot is an automated chat system specially designed to help the customer with all his queries. Chatbots are fed with commonly asked questionnaires and data based on the user's online habit. In case the user asks anything out of their data then the chatbots forward the query to the advertiser. Currently, these chatbots operate in form of chat pop ups but in near future, we can expect chatbots to be designed with sensory techniques that show human-like features such as voice, touch capabilities that will imitate like a real person.

Augmented Reality

Augmented reality (AR) is the buzzword of present-day online advertising industry. The best example of augmented reality was previously seen in the Pokémon GO, an online mobile game that became a leading trend in the gaming sector. In present day many marketers use the technology for advertising purpose because they give real-life experience to the consumer. Augmented reality ads are immersive, it gives the user a realistic product experience without the physical presence of the product. Augmented ads have been a trendsetter in the e-commerce industry where the advertisers have used it to beat the offline retail market. Earlier there used to be a conflict between online vs offline market. Users felt more secured and trusted offline stores as they can feel and see the product which was not possible in online shopping.  It seemed like a risky job to invest money in an online product, but AR has totally changed the way consumer shopping behavior.

Ever since the involvement of artificial intelligence marketers and advertisers have been using it for monetary benefits. The present-day advertising methods are laced with latest AI innovations that not only allure consumers into taking actions but have also changed their perception of online purchase. The modern-day advertisers have transformed AI into a part of our day to day browsing experience that helps them to cater us the desired and most relevant product rather than catering anything irrelevant. Seeing this we can assure that the AI is the future of digital advertising industry and with its help, the digital industry will surely boom in coming years.

https://www.entrepreneur.com/article/319977

===

by Idham Azhari


          Tech Data to distribute Cloudera services in Australia, New Zealand      Cache   Translate Page      
(Telecompaper) Cloudera, the platform for machine learning and analytics optimized for the cloud, has appointed Tech Data as its first Australian and New Zealand distributor...
          Senior Software Engineer (A.I)      Cache   Translate Page      
TX-Austin, To avoid delays in having your resume reviewed please forward directly to: ____________________________________________________________________________________ Sam.Major@RAndstadUSA.com ____________________________________________________________________________________ JOB TITLE: Senior Software Engineer (Computer Vision & Machine Learning) LOCATION: Austin, TX 78702 (Relocation Assistance Provid
          L’iPhone Xs d’Apple tire toute sa puissance du Machine Learning      Cache   Translate Page      

L’iPhone Xs d’Apple embarque une nouvelle puce A12 Bionic, équipée d’un Neural Engine dédié au Machine Learning. Ce puissant composant …

Cet article L’iPhone Xs d’Apple tire toute sa puissance du Machine Learning a été publié sur LeBigData.fr.


          User and Entity Behavior Analytics Market Research Report by Key Players Analysis 2025      Cache   Translate Page      
(EMAILWIRE.COM, September 13, 2018 ) A product that uses advanced algorithms and incorporates machine learning capabilities to track, collect, and analyze behavior of users as well as entities that include employees of an organization, third party contractors or outsiders connected to the network...
          iPhone XS and iPhone XS Max, iPhone XR      Cache   Translate Page      
Apple announced two new flagship iPhones in the iPhone XS and iPhone XS Max. The iPhone XS returns to the tick-tock naming scheme for mid-cycle iPhone models. The iPhone XS shares the same design as the iPhone X but brings overhauled internals. The iPhone XS Max is a new super-sized iPhone coming in with a 6.5-inch display. The iPhone XS Max is the physical size of the iPhone 8 Plus with its 5.5-inch display.

When I got the iPhone X, I wondered what it would look like in the iPhone Plus footprint, so I guess the Max was a logical next step.

The new iPhone models feature the new A12 Bionic chip. The CPU is an industry-first 7nm chip with a 6-core CPU, 4-core GPU, and a Neural Engine. The neural engine is a dedicated capacity for machine learning. Apple says the A12 Neural Engine can do 5 trillion operations per second compared to 600 billion in the A11. Apple says the CPU is 15 percent faster with 40 percent lower power consumption. Additionally, the GPU is up to 50 percent faster.

We####ll see how this all pans out, but the improved power efficiency should be apparent. Depending usage and whatever does with machine learning, the big boost with the Neural Engine could be significant.

The iPhone XS and iPhone XS Max feature improved rear and front-facing cameras. The camera hardware improvements seem hard to qualify, but internally the new iPhones offer improved image processing. Using the Neural Engine, the iPhone will be able to better analyze photos and features of people to improve photos. The new iPhones also features Smart HDR that will pull together a composite of four photos with zero lag. Portrait mode also received improvements with a cool ability to modify the depth of field as a post-edit. A new slider will allow you to bring the background in and out of focus during editing.

Generally, the camera is my most important feature with each new iPhone. The iPhone X offered a notable jump, but it hard to realize this with just specs.

The iPhone XS offers up to 30 minutes longer than the iPhone X, while the iPhone XS Max is up to 90 minutes.

The new iPhones also brings dual-SIM capabilities. The iPhone XS and XS Max has one physical SIM and a software eSIM. Essentially this allows you to install two SIM card to the device so that can have two phone numbers and/or data plans on one device. This would be handy for people who carry two devices for personal and work calls or those traveling and want flexibility with providers.

The iPhone XS and XS Max goes on pre-order starting September 14th and available in stores and delivery starting September 21st. Pricing starts at $999 for the XS and $1099 for the XS Max. It seems the $1000 price point has been established for flagship devices. Also worth noting that the iPhone XS starts out at only 64 GB for that $1000. Also, no more free headphone jack dongles.

Apple also announced a new entry-level iPhone XR. The XR has a 6.1-inch LCD display. The display is a cheaper option than the OLED on the other iPhone X models, although it is larger than the iPhone XS. The iPhone XR also supports Face ID and has the A12 processor. It as a single rear camera vs the two on the other models

The iPhone XR starts at $749. The XR pre-order stars October 19th and ships the 26th.

Article Link
          [آموزش] دانلود Lynda MATLAB 2018 Essential Training - آموزش دوره متلب 2018      Cache   Translate Page      

دانلود Lynda MATLAB 2018 Essential Training - آموزش دوره متلب 2018#source%3Dgooglier%2Ecom#https%3A%2F%2Fgooglier%2Ecom%2Fpage%2F%2F10000

نرم‌افزار متلب (MATLAB)  تقریباً در تمامی رشته‌های مهندسی و بطورکلی هر رشته‌ای كه نیاز به محاسبات ریاضی، ترسیم منحنی، شبیه‌سازی مدل، آنالیز عددی و ... باشد برای انجام محاسبات عددی کاربرد دارد. این نرم افزار دارای رویکردی ماتریس محور است به لین معنی که در آن حتی اعداد منفرد هم به عنوان ماتریس در نظر گرفته می ‌شوند.. مسایلی كه در رشته‌های مهندسی معمولاً با استفاده از زبان‌های برنامه‌نویسی C و Fortran حل می‌شوند، با استفاده از MATLAB بسیار راحت‌تر و سریع‌تر حل می‌شوند. این نرم‌افزار دارای جعبه‌ ابزارهای مختلفی است كه دانشجویان و مهندسان هر رشته می‌توانند از ...


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          SAP’s cloud analytics update offers insights in seconds, not months      Cache   Translate Page      

With a refresh of its cloud analytics tools, SAP hopes to bring users new insights into their data more quickly and take some of the workload off the IT department.

It’s not that the previous analytics tools were all that slow; it’s just that to get the most out of some of their features, you needed a team of data scientists to build the right reports.

Now the company is using machine learning to help SAP Analytics Cloud users zoom in on key data correlations, according to Mike Flannagan, SAP’s senior vice president of analytics.

To read this article in full, please click here


          Object Detection      Cache   Translate Page      
Looking for a python developer to work in tensor flow object detection project. (Budget: ₹1500 - ₹12500 INR, Jobs: C Programming, Java, Machine Learning, Python, Software Architecture)
          Artificial Intelligence for Robotics      Cache   Translate Page      

Bring a new degree of interconnectivity to your world by building your own intelligent robots Key Features Leverage fundamentals of AI and robotics Work through use cases to implement various machine learning algorithms Explore Natural Language Processing (NLP) concepts for efficient decision making in robots Book Description Artificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence. What you will learn Get started with robotics and artificial intelligence Apply simulation techniques to give your robot an artificial personality Understand object recognition using neural networks and supervised learning techniques Pick up objects using genetic algorithms for manipulation Teach your robot to listen using NLP via an expert system Use machine learning and computer vision to teach your robot how to avoid obstacles Understand path planning, decision trees, and search algorithms in order to enhance your robot Who this book is for If you have basic knowledge about robotics and want to build or enhance your existing robot's intelligence, then Artificial Intelligence for Robotics is for you. This book is also for enthusiasts who want to gain knowledge of AI and robotics. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.


          Search/Relevance - Staff Data Scientist - Walmart eCommerce - Sunnyvale, CA      Cache   Translate Page      
Design and implement state of the art Machine Learning approaches. With the help of some of the brightest minds in technology, merchandising, marketing, supply...
From Walmart eCommerce - Thu, 13 Sep 2018 09:14:57 GMT - View all Sunnyvale, CA jobs
          Senior Software Engineer (A.I)      Cache   Translate Page      
TX-Austin, To avoid delays in having your resume reviewed please forward directly to: ____________________________________________________________________________________ Sam.Major@RAndstadUSA.com ____________________________________________________________________________________ JOB TITLE: Senior Software Engineer (Computer Vision & Machine Learning) LOCATION: Austin, TX 78702 (Relocation Assistance Provid
          Comment on How To Estimate The Performance of Machine Learning Algorithms in Weka by Jason Brownlee      Cache   Translate Page      
Thanks, I'm happy to hear that.
          Comment on How To Estimate The Performance of Machine Learning Algorithms in Weka by Chynna Sevilleno      Cache   Translate Page      
Really helpful! Big thanks.
          Comment on How to Setup a Python Environment for Machine Learning and Deep Learning with Anaconda by Jason Brownlee      Cache   Translate Page      
Well done!
          Machine Learning Researcher - PARC, a Xerox company - Palo Alto, CA      Cache   Translate Page      
PARC, a Xerox company, is in the Business of Breakthroughs®. We create new business options, accelerate time to market, augment internal capabilities, and...
From PARC, a Xerox company - Sun, 26 Aug 2018 12:12:32 GMT - View all Palo Alto, CA jobs
          How to Add AI Solutions to Your Cloud Service Offerings      Cache   Translate Page      
Adopting AI and associated technologies such as machine learning and automation can give small cloud resellers the tools they need to compete, retain and gain customers, increase the bottom line, and more importantly stay in business. Here is how AI can be integrated into several cloud services.

16 Vote(s)

          It's official: This is the iPhone XS (AAPL)      Cache   Translate Page      

iPhone Xs

CUPERTINO, California — Apple has unveiled its new lineup of iPhones, introducing several new versions of the flagship iPhone X model in various sizes and configurations.

The iPhone XS — pronounced "iPhone 10 S" — is the new version of Apple's middle-size smartphone, with a 5.8-inch screen and a starting price of $999. Preorders start on Friday, and the device hits store shelves on September 21.

In keeping with Apple’s usual two-year product cycle cadence, the iPhone XS is an update to the year-old iPhone X, with a design nearly identical to it — a refinement, rather than a completely new phone.

At the launch event here on Wednesday, Apple executives reeled off a list of new features and improvements, including longer battery life, faster photo capture, and a new dual SIM capability that allows the phone to have two separate phone numbers.

The XS comes in gold, silver, and dark gray.

The phone can be configured with as much as 512 GB of storage, which is enough to store 200,000 photos, Apple's marketing head, Phil Schiller, said at the event.

There's also a larger version of the iPhone XS with a 6.5-inch screen, called the iPhone XS Max.

Here are some specs:

Apple iPhone event 2018

Apple iPhone event 2018

Apple iPhone event 2018

Apple iPhone event 2018

Other new details and features:

  • It's equipped with a dual-lens 12-megapixel camera on the back of the phone.
  • Its battery lasts 30 minutes longer than last year's iPhone X, Apple said.
  • The camera has "zero shutter lag," Apple said, so it should be able to snap photos fairly quickly.
  • It also supports two SIM cards, allowing you to use two phone numbers on one phone.
  • It has IP68 water-resistance, so it can be submerged in water about 6 feet deep for up to 30 minutes.
  • Apple's chip is called A12 Bionic and has special hardware for machine learning.
  • Apple said its facial-recognition software, Face ID, is the "most secure facial authentication ever in a smartphone."
  • The display is covered with a "new formulation" of glass that Apple said is stronger than that of previous iPhones.
  • The display has a high-dynamic color range that's 60% wider than previous models.

Now tell us what you think!

Want to take more surveys? Become a BI insider today!


Read more from Wednesday's Apple iPhone launch event:

SEE ALSO: Verizon's ultrafast 5G home internet service will begin rolling out October 1 and offer download speeds 10 times as fast as the US average

Join the conversation about this story »

NOW WATCH: Everything we know about Samsung’s foldable phone


          Machine learning and AI are changing the world – here's how to do it better      Cache   Translate Page      

Join us next month at MCubed

Events Even if news coverage of machine learning and AI leaves you wondering whether to laugh or cry, you know these technologies are going to profoundly change your organisation as either you adopt them or your partners and rivals do.…


          Machine Learning/AI Engineer - Groom & Associates - Montréal, QC      Cache   Translate Page      
Machine Learning/AI Engineer An international company is looking for Machine Learning/AI Engineers to join their new Montreal office! Title: Machine Learning...
From Groom & Associates - Thu, 06 Sep 2018 08:57:48 GMT - View all Montréal, QC jobs
          Ingénieur en apprentissage automatique - Groom & Associates - Montréal, QC      Cache   Translate Page      
Machine Learning/AI Engineer An international company is looking for Machine Learning/AI Engineers to join their new Montreal office! Title: Machine Learning...
From Groom & Associates - Thu, 06 Sep 2018 05:09:54 GMT - View all Montréal, QC jobs
          Software Engineer, AI Services - Shutterstock - Montréal, QC      Cache   Translate Page      
The Opportunity: As a API Algorithm Engineer, you will be responsible for building the innovative API endpoints using AI technologies (Machine Learning, Deep...
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          Principal Technologist - Machine Learning and Data Science - Blue Origin - Kent, WA      Cache   Translate Page      
While in this role, you will leverage your extensive experience in machine learning and data science to accelerate and innovate across business areas to drive...
From Blue Origin - Wed, 13 Jun 2018 05:31:45 GMT - View all Kent, WA jobs
          NBA Star Steve Nash & Classic Galaga Game Come to AR to Show Off ARKit 2.0 as Apple Unveils New iPhone Lineup      Cache   Translate Page      

On Wednesday, as expected, Apple unveiled the next generation of iPhones, namely the iPhone XS and iPhone XS Max along with the more affordable iPhone XR, each equipped with a TrueDepth sensor. Alongside the iPhone launch, CEO Tim Cook and company demonstrated what these new devices, equipped with iOS 12 and ARKit 2.0, can do for augmented reality apps. Apple got an assist from NBA Hall of Famer Steve Nash and NEX Team, Inc. CEO David Lee to show off how machine learning on the new iPhone X lineup running the A12 Bionic chip is able to improve their HomeCourt app. (In case you were wondering... more


          O Machine Learning Workshop Galicia lévanos da man á era da intelixencia artificial      Cache   Translate Page      
O mes que vén a cidade de Vigo vai acoller un evento que é unha xanela ao futuro e, máis polo miúdo, á nosa relación coas máquinas, cada vez máis pensantes, intelixentes e con meirande capacidade para ... - Fuente: www.codigocero.com
          Software Engineer - Machine Learning - Convoy - Seattle, WA      Cache   Translate Page      
Today, we use machine learning to figure out freight prices, shipment relevance for carriers, auction bidding strategy, and other internal processes....
From Convoy - Sat, 19 May 2018 10:13:22 GMT - View all Seattle, WA jobs
          Community Manager - Alation Inc. - Redwood City, CA      Cache   Translate Page      
Machine Learning Data Catalogs, 2018. Act as a liaison between Alation’s internal teams and the Community. You’ll work with a strong set of brand-name customers...
From Alation Inc. - Thu, 23 Aug 2018 20:35:18 GMT - View all Redwood City, CA jobs
          All Levels Marketing Sciences - Hypothesis Group - Los Angeles, CA      Cache   Translate Page      
Understanding of machine learning techniques and algorithms. Active support in research design for new business....
From Hypothesis Group - Tue, 11 Sep 2018 20:07:41 GMT - View all Los Angeles, CA jobs
          Sr Software Engineer - Applied Machine Learning - Apple - Austin, TX      Cache   Translate Page      
We work on many high-impact projects that serve various Apple lines of business. Understanding of machine learning, statistics....
From Apple - Fri, 15 Jun 2018 01:48:26 GMT - View all Austin, TX jobs
          Director, Customer Service Product and Tools - Kabam - Austin, TX      Cache   Translate Page      
Enthusiastic about the latest mobile trends and emerging technologies (IE Machine Learning, AI). Providing leadership and supporting for the technology...
From Kabam - Thu, 24 May 2018 02:31:26 GMT - View all Austin, TX jobs
          How to extract building footprints from satellite images using deep learning      Cache   Translate Page      
As part of the AI for Earth team, I work with our partners and other researchers inside Microsoft to develop new ways to use machine learning and other AI approaches to solve global environmental challenges. In this post, we highlight a sample project of using Azure infrastructure for training a deep learning model to gain insight from geospatial data.
          Kickstart your artificial intelligence/machine learning journey with the Healthcare Blueprint      Cache   Translate Page      
Azure blueprints are far more than models drawn on paper or solution descriptions in a document. They are packages of scripts, data, and other artifacts needed to install and exercise a reference implementation solution on Azure.
          Software Developer (Machine Learning) - Lincoln Electric - Cleveland, OH      Cache   Translate Page      
Experience with popular languages (C++, C#, Java, Python, and R). 3 - 10 years of experience with Windows, Linux, or Java platforms....
From The Lincoln Electric Company - Sat, 18 Aug 2018 08:48:39 GMT - View all Cleveland, OH jobs
          (Senior) Product Specialist - SAP Machine Learning for Sales and Service - SAP - Walldorf      Cache   Translate Page      
SAP's vision for Machine Learning is to focus on solving real business problems that will have huge business impact....
Gefunden bei SAP - Wed, 04 Jul 2018 11:34:10 GMT - Zeige alle Walldorf Jobs
          Senior Developer/Development Architekt für Banking for IBSO - SAP - Sankt Leon-Rot      Cache   Translate Page      
We make innovation real by using the latest technologies around the Internet of Things, blockchain, artificial intelligence / machine learning, and big data and...
Gefunden bei SAP - Tue, 11 Sep 2018 17:37:26 GMT - Zeige alle Sankt Leon-Rot Jobs
          Management Assistant (f/m) SAP Innovative Business Solutions - SAP - Sankt Leon-Rot      Cache   Translate Page      
We make innovation real by using the latest technologies around the Internet of Things, blockchain, artificial intelligence / machine learning, and big data and...
Gefunden bei SAP - Tue, 11 Sep 2018 17:36:57 GMT - Zeige alle Sankt Leon-Rot Jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Seattle, WA      Cache   Translate Page      
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:37:13 GMT - View all Seattle, WA jobs
          Data Architect - Remote West coast - Insight Enterprises, Inc. - Dallas, TX      Cache   Translate Page      
R, Azure Machine Learning. 2017 Arizona’s Most Admired Companies (AZ Business Magazine), 2016 Best Places to Work (Phoenix Business Journal)....
From Insight - Wed, 12 Sep 2018 07:52:59 GMT - View all Dallas, TX jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Portland, OR      Cache   Translate Page      
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:10 GMT - View all Portland, OR jobs
          Consultant, Business Analytics & Data Science - Lincoln Financial - Boston, MA      Cache   Translate Page      
Phoenix, AZ (Arizona). Knowledge and experience on applying statistical and machine learning techniques on real business data....
From Lincoln Financial Group - Mon, 27 Aug 2018 18:47:26 GMT - View all Boston, MA jobs
          AWS Architect - Insight Enterprises, Inc. - Chicago, IL      Cache   Translate Page      
Database architecture, Big Data, Machine Learning, Business Intelligence, Advanced Analytics, Data Mining, ETL. Internal teammate application guidelines:....
From Insight - Thu, 12 Jul 2018 01:56:10 GMT - View all Chicago, IL jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - San Francisco, CA      Cache   Translate Page      
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:12 GMT - View all San Francisco, CA jobs
          Mindsphere Principal PreSales Solutions Consultant - West, US - Siemens - Los Angeles, CA      Cache   Translate Page      
Business Analytics, Analytics / Machine Learning tools such as R, SAS, Tableau, or scikit-learn. Analytics and machine learning....
From Siemens - Tue, 31 Jul 2018 13:41:13 GMT - View all Los Angeles, CA jobs
          Java Software Engineer (Back-End)      Cache   Translate Page      
Java Software Engineer (Back-End) Job Description: We are seeking a uniquely talented, insatiably curious Java Software Engineer with experience in designing and implementing web-based backend Java systems. You will be part of a talented software team that works on a new, cloud-native, first of its kind application that employs Machine Learning to change how business does recruiting. The responsibilities of the role span across the full software development lifecycle including design, development, testing, deployment and application management. You will be expected to apply...
          Data Scientist - Yamaha - Cypress, CA      Cache   Translate Page      
Develop statistical models, machine learning-based tools or processes to measure and manage business performance....
From Yamaha - Wed, 22 Aug 2018 00:54:18 GMT - View all Cypress, CA jobs
          Sr Software Engineer ( Big Data, NoSQL, distributed systems ) - Stride Search - Los Altos, CA      Cache   Translate Page      
Experience with text search platforms, machine learning platforms. Mastery over Linux system internals, ability to troubleshoot performance problems using tools...
From Stride Search - Tue, 03 Jul 2018 06:48:29 GMT - View all Los Altos, CA jobs
          Machine Learning, Augmented Reality: Apple macht iPhones fit für künftige Aufgaben       Cache   Translate Page      
Apple hat geliefert wie erwartet: CEO Tim Cook und seine Kollegen stellten im „Steve Jobs Theater“ des Headquarters in Cupertino drei neue iPhones vor. Die Geräte nutzen den neuen A12-Prozessor, der erstmals in einem Sieben-Nanometer-Verfahren gefertigt wird.
          Sr. Associate, ML Pipelines for AI Consultant - KPMG - Seattle, WA      Cache   Translate Page      
Modeling (regression, machine learning, feature selection, dimension reduction, validation); Strong aptitude for quickly learning business operational, process,...
From KPMG LLP - Fri, 07 Sep 2018 02:02:23 GMT - View all Seattle, WA jobs
          Data Scientist - Deloitte - Springfield, VA      Cache   Translate Page      
Demonstrated knowledge of machine learning techniques and algorithms. We believe that business has the power to inspire and transform....
From Deloitte - Fri, 10 Aug 2018 06:29:44 GMT - View all Springfield, VA jobs
          Database Administrator - Radiant Solutions - Springfield, VA      Cache   Translate Page      
Machine learning, data mining, and knowledge discovery. Work is non-routine and very complex, involving the application of advanced technical and business...
From Radiant Solutions - Wed, 04 Jul 2018 01:36:29 GMT - View all Springfield, VA jobs
          Sr. Associate, ML Pipelines for AI Consultant - KPMG - Dallas, TX      Cache   Translate Page      
Modeling (regression, machine learning, feature selection, dimension reduction, validation); Strong aptitude for quickly learning business operational, process,...
From KPMG LLP - Fri, 07 Sep 2018 02:02:14 GMT - View all Dallas, TX jobs
          Offer - KNIME Development Services for Mining Fresh Insight - USA      Cache   Translate Page      
Ecosmob’s KNIME software developers helps users leverage its data mining and machine learning features through its modular data pipelining concept. They also enable KNIME nodes for data processing for data modelling, analysis and visualisation. All these can be done without too much programming hurdles.Key Services offered by Ecosmob :-Installation and Configuration Services-Design Architecture-Model Creation and Augmenting Current Models-Building Workflow and Process Templates-Training and Development servicesContact us today to learn how we can help your business with Knime node development and Machine Learning.Contact:Email : sales@ecosmob.comCall : 1-303-997-3139or Visit : https://www.ecosmob.com/knime-development/
          Threat Finance Subject Matter Expert - People, Technology & Processes - Fort Bragg, NC      Cache   Translate Page      
The TF SME contractor shall have proficiency and experience with applied data processing and scientific analysis of large datasets and machine learning....
From People, Technology & Processes - Tue, 17 Jul 2018 03:09:42 GMT - View all Fort Bragg, NC jobs
          Artificial Intelligence for Robotics      Cache   Translate Page      

Bring a new degree of interconnectivity to your world by building your own intelligent robots Key Features Leverage fundamentals of AI and robotics Work through use cases to implement various machine learning algorithms Explore Natural Language Processing (NLP) concepts for efficient decision making in robots Book Description Artificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence. What you will learn Get started with robotics and artificial intelligence Apply simulation techniques to give your robot an artificial personality Understand object recognition using neural networks and supervised learning techniques Pick up objects using genetic algorithms for manipulation Teach your robot to listen using NLP via an expert system Use machine learning and computer vision to teach your robot how to avoid obstacles Understand path planning, decision trees, and search algorithms in order to enhance your robot Who this book is for If you have basic knowledge about robotics and want to build or enhance your existing robot's intelligence, then Artificial Intelligence for Robotics is for you. This book is also for enthusiasts who want to gain knowledge of AI and robotics. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.


          Senior Software Engineer (A.I)      Cache   Translate Page      
TX-Austin, To avoid delays in having your resume reviewed please forward directly to: ____________________________________________________________________________________ Sam.Major@RAndstadUSA.com ____________________________________________________________________________________ JOB TITLE: Senior Software Engineer (Computer Vision & Machine Learning) LOCATION: Austin, TX 78702 (Relocation Assistance Provid
          Director, Data & AI - Lightspeed - Montréal, QC      Cache   Translate Page      
Furthermore, we will apply our advanced data analytics, artificial intelligence/machine learning knowledge and experience in combination with our business...
From LightSpeed - Thu, 12 Jul 2018 14:31:24 GMT - View all Montréal, QC jobs
          Solution Architect - Data & Analytics - Neudesic LLC - Seattle, WA      Cache   Translate Page      
Machine Learning Solutions:. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in...
From Neudesic LLC - Mon, 02 Jul 2018 10:04:49 GMT - View all Seattle, WA jobs
          Order Processing Specialist - Pure Storage - Salt Lake City, UT      Cache   Translate Page      
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Tue, 28 Aug 2018 06:24:19 GMT - View all Salt Lake City, UT jobs
          Travel and Expense Specialist - Pure Storage - Salt Lake City, UT      Cache   Translate Page      
Bachelor's degree in business, finance and accounting related field. The world is experiencing a technological revolution driven by AI, machine learning,...
From Pure Storage - Tue, 28 Aug 2018 06:23:33 GMT - View all Salt Lake City, UT jobs
          Designated Support Engineer - Pure Storage - Lehi, UT      Cache   Translate Page      
The world is experiencing a technological revolution encouraged by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of...
From Pure Storage - Fri, 07 Sep 2018 22:36:41 GMT - View all Lehi, UT jobs
          Technical Support Engineer I - Pure Storage - Lehi, UT      Cache   Translate Page      
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Fri, 24 Aug 2018 06:20:16 GMT - View all Lehi, UT jobs
          Technical Support Engineer II - NAS/ Storage - Pure Storage - Lehi, UT      Cache   Translate Page      
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Wed, 01 Aug 2018 06:20:10 GMT - View all Lehi, UT jobs
          Sr. BI Engineer - Republic Finance - Plano, TX      Cache   Translate Page      
Continuously explore and recommend new BI technology, including those powered by machine learning, A.I., and natural language processing, to improve the value...
From Republic Finance - Fri, 24 Aug 2018 10:15:47 GMT - View all Plano, TX jobs
          Solution Architect - Data & Analytics - Neudesic LLC - New York, NY      Cache   Translate Page      
Machine Learning Solutions:. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in...
From Neudesic LLC - Sat, 16 Jun 2018 09:58:39 GMT - View all New York, NY jobs
          SAP Analytics Cloud Helps Business Users Make Better Decisions with Augmented Analytics      Cache   Translate Page      

According to a new press release out of the company, “SAP SE today announced the SAP Analytics Cloud solution is now available with new machine learning features to uncover correlations in an organization’s data and help users make faster, more confident decisions… Data scientists, who use scientific methods to extract knowledge from data, are a […]

The post SAP Analytics Cloud Helps Business Users Make Better Decisions with Augmented Analytics appeared first on DATAVERSITY.


          Playground Global - Investment Associate (Venture Capital Team) - playground.global - Palo Alto, CA      Cache   Translate Page      
Artificial intelligence, robotics, sensors, new compute platforms, quantum technologies, next generation manufacturing, machine learning, space technologies,...
From Playground.global - Fri, 18 May 2018 18:05:13 GMT - View all Palo Alto, CA jobs
          Distilled News      Cache   Translate Page      
Artificial Intelligence, Machine Learning and Big Data – A Comprehensive Report Artificial Intelligence and Machine Learning are the hottest jobs …

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          Whats new on arXiv      Cache   Translate Page      
Performance Metrics (Error Measures) in Machine Learning Regression, Forecasting and Prognostics: Properties and Typology Performance metrics (error measures) are vital …

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          Solution Architect - Data & Analytics - Neudesic LLC - Seattle, WA      Cache   Translate Page      
Machine Learning Solutions:. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in...
From Neudesic LLC - Mon, 02 Jul 2018 10:04:49 GMT - View all Seattle, WA jobs
          Order Processing Specialist - Pure Storage - Salt Lake City, UT      Cache   Translate Page      
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Tue, 28 Aug 2018 06:24:19 GMT - View all Salt Lake City, UT jobs
          Travel and Expense Specialist - Pure Storage - Salt Lake City, UT      Cache   Translate Page      
Bachelor's degree in business, finance and accounting related field. The world is experiencing a technological revolution driven by AI, machine learning,...
From Pure Storage - Tue, 28 Aug 2018 06:23:33 GMT - View all Salt Lake City, UT jobs
          Designated Support Engineer - Pure Storage - Lehi, UT      Cache   Translate Page      
The world is experiencing a technological revolution encouraged by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of...
From Pure Storage - Fri, 07 Sep 2018 22:36:41 GMT - View all Lehi, UT jobs
          Technical Support Engineer I - Pure Storage - Lehi, UT      Cache   Translate Page      
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Fri, 24 Aug 2018 06:20:16 GMT - View all Lehi, UT jobs
          Technical Support Engineer II - NAS/ Storage - Pure Storage - Lehi, UT      Cache   Translate Page      
The world is experiencing a technological revolution driven by AI, machine learning, virtual reality, quantum computing and self-driving cars -- all of which...
From Pure Storage - Wed, 01 Aug 2018 06:20:10 GMT - View all Lehi, UT jobs
          Sr. BI Engineer - Republic Finance - Plano, TX      Cache   Translate Page      
Continuously explore and recommend new BI technology, including those powered by machine learning, A.I., and natural language processing, to improve the value...
From Republic Finance - Fri, 24 Aug 2018 10:15:47 GMT - View all Plano, TX jobs
          Solution Architect - Data & Analytics - Neudesic LLC - New York, NY      Cache   Translate Page      
Machine Learning Solutions:. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in...
From Neudesic LLC - Sat, 16 Jun 2018 09:58:39 GMT - View all New York, NY jobs
          Playground Global - Investment Associate (Venture Capital Team) - playground.global - Palo Alto, CA      Cache   Translate Page      
Artificial intelligence, robotics, sensors, new compute platforms, quantum technologies, next generation manufacturing, machine learning, space technologies,...
From Playground.global - Fri, 18 May 2018 18:05:13 GMT - View all Palo Alto, CA jobs
          Lynda.com: Azure Machine Learning Development: 3 Deploying and Managing Models      Cache   Translate Page      
Azure Machine Learning Studio brings the power of AI into the professional developer's hands. In this course, learn how to deploy and manage models in Azure Machine Learning Studio. Instructor Sahil Malik picks up from earlier Azure Machine Learning Development courses and dives directly into the more advanced topics of deploying, scaling, logging, and managing your trained models in production scenarios. Learn how to deploy an experiment as a web service, make your service available globally, enable and view logs, use machine learning with API management, and more.
          Data Scientist      Cache   Translate Page      
CA-San Diego, job summary: Job Summary The Data Scientist who is passionate about data and want to apply machine learning techniques to solve real-world problems for our clients. This person will be expected to be proficient in the exploration and understanding of structured and unstructured data, machine learning and data mining techniques, statistical modeling methods, time series, text mining, recommendation
          4 Trends Giving CISOs Sleepless Nights      Cache   Translate Page      

IoT attacks, budget shortfalls, and the skills gap are among the problems keeping security pros up at night.

The world of cybersecurity gets more intriguing every year. In 2017, security professionals saw their share of attacks, but the increasing sophistication of the skirmishes is notable ― with almost machine-like weaponization of code on the attackers' side and an increasing alliance with the forces of machine learning and artificial intelligence on the defenders' side.

As we continue through 2018, figures remain similar to last year's. While the security industry struggles to fill more than a million jobs, attackers ― including sophisticated criminal organizations and nation-states ― have more than enough talent to continue their efforts.

We're seeing changes in the nature of cyberattacks arising from the continuing "digital transformation" going on in all markets. As companies make their devices intelligent, and as more consumers welcome intelligent devices and digital assistants into their homes, attack vectors are multiplying and bad actors are finding new ways to exploit those platforms.

Here are some of the trends affecting security pros in 2018:

1. Attacks involving IoT are increasing, resulting in a call for increased IT security budgets.

The Internet of Things (IoT) is the next great frontier in the business world, and it's making its way into people's homes as well, in the form of smart thermostats, refrigerators, and even complete home control systems. IoT is a high-growth industry that is looking to cross the $1 trillion mark sooner than later.

For hackers, all those connected "things" represent a vast source of new code to exploit. IoT devices are a tantalizing backdoor to gain entry and reach more powerful systems with critical information. For example, earlier this year Kaspersky Lab releasedresults from a study exposing the risk when Bluetooth devices don't require basic security protocols such as authentication and authorization of encrypted tokens and coordinates. Hackers could exploit these vulnerabilities to take the devices over, spread malware, and gain access to critical data or physical entry to homes and buildings ― and could even do so wirelessly.

At a fundamental level, consumers and companies are at risk of having financial information stolen. Attacks on critical infrastructure such as transit centers or dams can be even more costly or even life-threatening.

This makes securing an IT environment more complicated as companies must consider not just the connected devices and products themselves, but sensors, firmware, applications, application programming interfaces (APIs), networks, and databases. With that in mind, device-makers need to ensure their engineers and developers understand the various security vulnerabilities in the IoT devices they’re putting on the market. This challenge is a central focus for security orgs in the coming months ― and until the industry really gets a handle on this, there will be breaches.

2. The security skill-set gap continues to widen due to talent scarcity, leading more companies to adopt AI and machine learning technology to detect and manage attacks.

Like everyone else in IT, security organizations have to search for efficiencies. Throughout 2018, we're continuing to expect much of those efforts to come from either outsourced services or machines.

As the industry scrambles to solve the talent shortage, one strategy is to automate as much as possible. In doing so, companies would be wise to pay attention to the respective strengths of humans (creativity) and machines (consistency), and build both into their strategies.

Through 2018 and beyond, good security practices will seek to automate functions that are based purely on large sets of data, and bring in more people with diverse opinions, perspectives, and backgrounds to perform the lateral, out-of-the-box thinking that's necessary to combat today's sophisticated adversaries.

3. Security orgs are prioritizing risk-reducing solutions and consumption-based services in an attempt to relieve sagging budgets.

It's not just talent that the security industry is struggling to find enough of, it's also dollars. In response, CISOs are having toget inventive. One of the top emerging trends we're seeing in 2018 is the continued maturation of security-as-a-service models. It's not just web application firewall and DDoS mitigation, but also ID- and access-as-a-service, compliance-as-a-service, encryption, and more.

These tactics provide some cost predictability and make it easy to determine total cost of ownership. But there's a limit to how much can be done in this manner, and companies will always need to consider the risks unique to their industry and way of operating.

In addition, we're seeing the security industry taking on other efficiency-improving efforts, such as the adoption of modern infrastructure as code or " NoOps " capabilities normally found in advanced cloud-based development environments. This has become possible because of the availability of APIs in standard security software and gear, and the rise of security automation tools, including Phantom and Demisto. When four lines of code can replace 40 manual entries in a management user interface, the opportunity and the appeal are hard to ignore.

4. More enterprises are relying on CISOs to devise strategies and set provisions for security requirements that abide by GDPR standards.

The EU's General Data Protection Regulation (GDPR) recently kicked into gear, and noncompliance carries the potential for significant penalties. Globally, organizations have been actively assessing the impact of GDPR on their business and data privacy and management operations. Any organization doing business in the EU or processing personally identifiable information from EU residents has needed to deploy additional processes, policies, and technologies to avoid significant fines.

CISOs are accountable for data security and must provide confidence to executives, auditors, and regulators that personal information is secure. This means maintaining (or achieving) full visibility into where data resides and determining if proper controls are in place.

Longer term, expect similar regulations to arise in other regions as GDPR becomes a prototype for a new class of privacy regulations worldwide.

Related Content: 10 Lessons From an IoT Demo Lab The Role of Incident Response in ICS Security Compliance Automation Exacerbates Cybersecurity Skills Gap There's No Automating Your Way Out of Security Hiring Woes
4 Trends Giving CISOs Sleepless Nights
Black Hat Europe returns to London Dec. 3-6, 2018, with hands-on technical Trainings, cutting-edge Briefings, Arsenal open-source tool demonstrations, top-tier security solutions, and service providers in the Busin
          5 Ways Artificial Intelligence Is Already Transforming the Banking Industry      Cache   Translate Page      

Opinions expressed by Entrepreneur contributors are their own.

Artificial Intelligence (AI) -- and its growing impact on and applicability for individuals and businesses alike -- is one of today’s most widely discussed topics. From virtual assistants like Siri and Alexa,to chatbots created by Facebook and Drift , AI is having a significant impact on the lives of consumers.

Related:#Five Technology Trends That Will Disrupt Your Banking Style

A study from Statista showed that the number of consumers using virtual assistants worldwide is expected to exceed one billion in 2018. Additionally, a 2018 survey by Accenture projected that 37 percent of U.S. consumers will own a digital voice assistant (DVA) device by the end of 2018.

It is readily apparent how AI-powered technology is making inroads into everyday life through DVAs and other consumer products, but AI is also having a transformative effect on an industry that impacts virtually all consumers and businesses: banking. Here are five ways that AI is already transforming the banking industry.

Customer service automation

As natural language processing technology evolves, consumers find it increasingly difficult to distinguish between a voice bot and a human customer service representative. This stems from improved abilities on the part of voice and chatbots to resolve customer issues without human intervention.

The benefits to banks of customer service automation are obvious: AIcould lead to significant cost reductions. A recent study by Autonomous predicted that AI could lead to 1.2 million jobs being cut in the banking and lending industry, resulting in up to $450 billion in industrysavings by 2030.

Despite the potential rewards customer service automation promises, banks and other businesses need to proceed with caution in relying too heavily on voice and chatbots. The popularity of GetHuman illustrates this: It'sa website that connects consumers with human CSRs to resolve their issue. In fact, voice and chatbots often work best when augmenting rather than replacing humans. At a minimum, the option to speak to a human, if necessary, should be readily available.

Related:This Banker Explains Why Confluence of Fintech and Banks is Unavoidable

Want an example of how banks are creatively employing AI to serve customers? The Swiss bank UBS, ranked number 35 globally for its volume of assets, according to Accuity’s August 2018 global bank rankings --has partnered with Amazon to incorporate its “ Ask UBS ” service into Alexa-powered Echo speaker devices.

Ask UBS, which is aimed at UBS’s European wealth management clients, enables users to receive wide-ranging advice and analysis on global financial marketsjust by “asking” Alexa. “Ask UBS” also acts as a teaching resource, offering definitions and examples of acronyms and jargon related to the financial industry.

While Ask UBS can make a call from a UBS financial advisor to a customer’s phone upon request, it is not yet able to access individual portfolios, execute trades or perform other transactions; it can'toffer personalized advice based on a client’s holdings and goals. According to the Wall Street Journal , the reason is primarily security and privacy concerns. More in-depth and personalized service through a DVA may not be far off, though. In the article, a UBS spokesman stated that the company's aim isto make “Ask UBS” and similar tools “secure, compliant, and trustable for clients.”

Personalization

Banks have access to a wealth of customer data, including detailed demographics, website analyticsand records of online and offline transactions. By utilizing machine learning to integrate and analyze information from multiple, discrete databases to form a 360-degree customer view, banks are better positioned to personalize products, servicesand interactions based on the behavior of individual clients.

According to James Eardley , global director of industry marketing for enterprise software giant SAP, “The next step within the digital service model is for banks to price for the individual, and to negotiate that price in real time, taking personalization to the ultimate level.”

While personalized pricing of this kind may only become prevalent in the future, banks are already utilizingAI-processed behavioral data to advise individual clients on appropriate credit and savings products, based on their goals and habits. Santander, the world’s 14th largest bank , measured by its current assets, even hosted a competition , with a prize of $60,000, on the machine learning crowdsourcing site Kaggle , encouraging data scientists to write code that better “pairs products with people.”

Security

In the banking and payments industry, personalization extends far beyond marketing and product customization,into security. A growing number of banks are utilizing biometric data, like fingerprints, to replace or augment passwords and other forms of client verification.

A report by Goode Intelligence forecast that 1.9 billion bank customers will be using some form of biometric identification by 2021. The Guardian reported that U.K. bank Halifax even experimented with Bluetooth wristbands that identified a client’s unique heartbeat to authenticate account access.

In a widely discussed innovation to its popular iPhone, Apple has evolved its Face ID so that it now uses AI-powered facial-recognition techno
          Office VBA + AMSI: Parting the veil on malicious macros      Cache   Translate Page      

As part of our continued efforts to tackle entire classes of threats, Office 365 client applications now integrate with Antimalware Scan Interface (AMSI) , enabling antivirus and other security solutions to scan macros and other scripts at runtime to check for malicious behavior.

Macro-based threats have always been a prevalent entry point for malware, but we have observed a resurgence in recent years. Continuous improvements in platform and application security have led to the decline of software exploits, and attackers have found a viable alternative infection vector in social engineering attacks that abuse functionalities like VBA macros. Microsoft, along with the rest of the industry, observed attackers transition from exploits to using malicious macros to infect endpoints. Malicious macros have since showed up in commodity malware campaigns, targeted attacks, and in red-team activities.


Office VBA + AMSI: Parting the veil on malicious macros
Figure 1. Prevalence of the exploit vs macro attack vector observed via windows Defender ATP telemetry

To counter this threat, we invested in building better detection mechanisms that expose macro behavior through runtime instrumentation within our threat protection solutions in the cloud. Were bringing this instrumentation directly into Office 365 client applications. More importantly, were exposing this capability through AMSI, an open interface, making it accessible to any antivirus solution.

Obfuscation and other forms of detection evasion

Macros are popular among attackers because of the rich capabilities that the VBA runtime exposes and the privileged context in which macros execute. Notably, as with all scripting languages, attackers have another advantage: they can hide malicious code through obfuscation.

To evade detection, malware needs to hide intent. The most common way that attackers do this is through code obfuscation. Macro source codes are easy to obfuscate, and a plethora of free tools are available for attackers to automatically do this. This results in polymorphic malware, with evolving obfuscation patterns and multiple obfuscated variants of the same malicious macro.

Theres more: malicious code can be taken out of the macro source and hidden in other document components like text labels, forms, Excel cells, and others. Or why hide at all? A small piece of malicious code can be embedded somewhere in a huge legitimate source and keep a low profile.

How can antivirus and other security solutions cope? Today, antivirus solutions can extract and scan the obfuscated macro source code from an Office document. How can the macros intent be exposed? What if security solutions can observe a macros behavior at runtime and gain visibility into system interactions? Enter Office and AMSI integration.

AMSI on Windows 10

If AMSI rings a bell, its because we talked about how PowerShell adopted AMSI in a blog post when AMSI was introduced back in 2015.

Antimalware Scan Interface (AMSI) is an open interface available on Windows 10 for applications to request, at runtime, a synchronous scan of a memory buffer by an installed antivirus or security solution. Any application can interface with AMSI and request a scan for any data that may be untrusted or suspicious.

Any antivirus can become an AMSI provider and inspect data sent by applications via the AMSI interface. If the content submitted for scan is detected as malicious, the requesting application can take action to deal with the threat and ensure the safety of the device. To learn more, refer to the AMSI documentation .

AMSI also integrates with the javascript, VBScript, and PowerShell scripting engines. Over the years, we have been steadily increasing our investments in providing security solutions with deeper visibility into script-based threats. Insights seen via AMSI is consumed by our own security products. The new Office and AMSI integration is yet another addition to the arsenal of protection against script-based malware. Windows Defender Advanced Threat Protection ( Windows Defender ATP ) leverages AMSI and machine learning to combat script-based threats that live off the land (read our previous blog post to learn more).

Office VBA integration with AMSI

The Office VBA integration with AMSI is made up of three parts: (a) logging macro behavior, (b) triggering a scan on suspicious behavior, and (c) stopping a malicious macro upon detection.


Office VBA + AMSI: Parting the veil on malicious macros
Figure 2. Runtime scanning of macros via AMSI Logging macro behavior

The VBA language offers macros a rich set of functions that can be used to interface with the operating system to run commands, access the file system, etc. Additionally, it allows the ability to issue direct calls to COM methods and Win32 APIs. The VBA scripting engine handles calls from macro code to COM and APIs via internal interfaces that implement the transition between the caller and the callee. These interfaces are instrumented such that the behavior of a macro is trapped and all relevant information, including the function name and its parameters, are logged in a circular buffer.

This monitoring is not tied to specific functions; its generic and works on any COM method or Win32 API. The logged calls can come in two formats:

<COM_Object>.<COM_Method>(Parameter 1, , Parameter n); <API_or_function_Name>(Parameter 1, , Parameter n);

Invoked functions, methods, and APIs need to receive the parameters in the clear (plaintext) in order to work; thus, this behavioral instrumentation is not affected by obfuscation. This instrumentation thus reveals a weak spot for macro codes; the antivirus now has visibility on relevant activity of the macro in the clear.

To illustrate, consider the following string obfuscation in a shell command:

Shell(ma+l+ wa+ r + e.e + xe)

With the Office VBA and AMSI integration, this is logged like so:

Shell(malware.exe);

Triggering on suspicious behavior

When a potentially high-risk function or method (a trigger; for example, CreateProcess or ShellExecute) is invoked, Office halts the execution of the macro and requests a scan of the macro behavior logged up to that moment, via the AMSI interface. The AMSI provider (e.g., antivirus software) is invoked synchronously and returns a verdict indicating whether or not the observed behavior is malicious.

The list of high-risk functions or triggers are meant to cover actions at various stages of an attack chain (e.g., payload download, persistence, execution, etc.) and are selected based on their prevalence among malicious and benign macros. The behavior log sent over AMSI can include information like suspicious URLs from which malicious data was downloaded, suspicious file names known to be associated with malware, and others. This data is valuable in determining if the macro is malicious, as well as in the creation of detection indicators all without any influence from obfuscation.

Stopping malicious macros upon detection

If behavior is assessed malicious, macro execution is stopped. The user is notified by the Office application, and the application session is shut down to avoid any further damage. This can stop an attack in its tracks, protecting the device and user.


Office VBA + AMSI: Parting the veil on malicious macros
Figure 3. Malicious macro notification Case study 1: Heavily obfuscated macro code

(SHA-256: 10955f54aa38dbf4eb510b8e7903398d9896ee13d799fdc980f4ec7182dbcecd)

To illustrate how the Office VBA and AMSI integration can expose malicious macro code, lets look at a recent social engineering attack that uses macro-based malware. The initial vector is a Word document with instructions in the Chinese language to Enable content.


Office VBA + AMSI: Parting the veil on malicious macros
Figure 4: The malicious document instructs to enable the content

If the recipient falls for the lure and enables content, the malicious macro code runs and launches a command to download the payload from a command-and-control server controlled by the attacker. The payload, an installer file, is then run.

The macro code is heavily obfuscated:


Office VBA + AMSI: Parting the veil on malicious macros
Figure 5: Obfuscated macro

However, behavior monitoring is not hindered by obfuscation. It produces the following log, which it passes to AMSI for scanning by antivirus:


Office VBA + AMSI: Parting the veil on malicious macros
Figure 6: De-obfuscated behavior log

The action carried out by the macro code is logged, clearly exposing malicious actions that antivirus solutions can detect much more easily than if the code was obfuscated.

Case study 2: Macro threat that lives off the land

(SHA-256: 7952a9da1001be95eb63bc39647bacc66ab7029d8ee0b71ede62ac44973abf79)

The following is an example of macro malware that lives off the land, which means that it stays away from the disk and uses common tools to run code directly in memory. In this case, it uses shellcode and dynamic pages. Like the previous example, this attack uses social engineering to get users to click Enable Content and run the macro code, but this one uses instructions in the Spanish language in Excel.


Office VBA + AMSI: Parting the veil on malicious macros
Figure 7. Malicious Excel file with instructions to enable content

When run, the macro code dynamically allocates virtual memory, writes shellcode to the allocated location, and uses a system callback to transfer execution control. The malicious shellcode then achieves fileless persistence, being memory-resident without a file.


Office VBA + AMSI: Parting the veil on malicious macros
Figure 8. Macro code utilizing Win32 APIs to launch embedded shellcode

When the shellcode gets execution control, it launches a PowerShell command to download additional payload from a command-and-control server controlled by the attacker.


Office VBA + AMSI: Parting the veil on malicious macros
Figure 9. PowerShell command that downloads payload

Even if the macro code uses fileless code execution technique using shellcode, its behavior is exposed to antivirus solutions via the AMSI interface. Sample log is shown below:


Office VBA + AMSI: Parting the veil on malicious macros
Figure 10. De-obfuscated behavior log

With the AMSI scan integration in both Office VBA and PowerShell, security solutions like Windows Defender ATP can gain clear visibility into malicious behavior at multiple levels and successfully block attacks.

Windows Defender ATP: Force multiplier and protection for down-level platforms

In addition to protecting users running Office 365 applications on Windows 10, detections via AMSI allow modern endpoint protection platforms like Windows Defender ATP to extend protection to customers via the cloud.


Office VBA + AMSI: Parting the veil on malicious macros
Figure 11. Simplified diagram showing how AMSI detections in a few machines are extended to other customers via the cloud

In Windows Defender AVs cloud-delivered antivirus protection , the Office VBA and AMSI integration enriches the signals sent to the cloud, where multiple layers of machine learning models classify and make verdicts on files. When devices encounter documents with suspicious macro code, Windows Defender AV sends metadata and other machine learning features, coupled with signals from Office AMSI, to the cloud. Verdicts by machine learning translate to real-time protection for the rest of Windows Defender AV customers with cloud protection enabled.

This protection is also delivered to the rest of Microsoft 365 customers. Through the Microsoft Intelligent Security Graph , security signals are shared across components of Microsoft 365 threat protection. For example, in the case of macro malware, detections of malicious macro-laced documents by Windows Defender AV are shared with Office 365 ATP , which blocks emails carrying the document, stopping attacks before the documents land in users mailboxes.


Office VBA + AMSI: Parting the veil on malicious macros

Figure 12. The Office and AMSI integration enriches the orchestration of protection across Microsoft 365

Within a few weeks after the release of this new instrumentation in Office VBA and the adoption by Windows Defender ATP , we saw this multiplier effect, with signals from a few hundred devices protecting several tens of thousands of devices. Because Office AMSI feature exposes behaviors of the macro irrespective of content, language, or obfuscation, signals from one part of the world can translate to protection for the rest of the globe this is powerful.

Availability

AMSI integration is now available and turned on by default on the Monthly Channel for all Office 365 client applications that have the ability to run VBA macros including Word, Excel, PowerPoint, and Outlook.

In its default configuration, macros are scanned at runtime via AMSI except in the following scenarios:

Documents opened while macro security settings are set to “Enable All Macros” Documents opened from trusted locations Documents that are trusted documents Documents that contain VBA that is digitally signed by a trusted publisher

Office 365 applications also expose a new policy control for administrators to configure if and when macros are scanned at runtime via AMSI:

Group Policy setting name Macro Runtime Scan Scope Path User Configuration > Administrative templates > Microsoft Office 2016 > Security Settings Description

This policy setting specifies for which documents the VBA Runtime Scan feature is enabled.

Disable for all documents: If the feature is disabled for all documents, no runtime scanning of enabled macros will be performed.

Enable for low trust documents: If the feature is enabled for low trust documents, the feature will be enabled for all documents for which macros are enabled except:

Documents opened while macro security settings are set to “Enable All Macros” Documents opened from a Trusted Location Documents that are Trusted Documents Documents that contain VBA that is digitally signed by a Trusted Publisher

Enable for all documents: If the feature is enabled for all documents, then the above class of documents are not excluded from the behavior.

This protocol allows the VBA runtime to report to the Anti-Virus system certain high-risk code behaviors it is about to execute and allows the Anti-Virus to report back to the process if the sequence of observed behaviors indicates likely malicious activity so the Office application can take appropriate action.

When this feature is enabled, affected VBA projects’ runtime performance may be reduced.

Conclusion: Exposing hidden malicious intent

Macro-based malware continuously evolves and poses challenges in detection using techniques like sandbox evasion and code obfuscation. Antimalware Scan Interface (AMSI) s integration with Office 365 applications enable runtime scanning of macros, exposing malicious intent even with heavy obfuscation. This latest improvement to Office 365 allows modern endpoint security platforms like Windows Defender ATP to defeat macro-based threats.

Code instrumentation and runtime monitoring are powerful tools for threat protection. Combined with runtime scanning via AMSI, they enable antivirus and other security solutions to have greater visibility into the runtime behavior of a macro execution session at a very granular level, while also bypassing code obfuscation. This enables antivirus solutions to (1) detect a wide range of mutated or obfuscated malware that exhibit the same behavior using a smaller but more efficient set of detection algorithms, and (2) impose more granular restrictions on what macros are allowed to do at runtime.

Moreover, AMSI protection is not limited to macros. Other scripting engines like JavaScript, VBScript, and PowerShell also implement a form of code instrumentation and interface with AMSI. Attacks with multiple stages that use different scripts will be under scrutiny by AMSI at each step, exposing all behaviors and enabling detection by antivirus and other solutions.

We believe this is another step forward in elevating security for Microsoft 365 customers. More importantly, AMSI and Office 365 integration enables the broader ecosystem of security solutions to better detect and protect customers from malicious attacks without disrupting day-to-day productivity.

Giulia Biagini , Microsoft Threat Intelligence Center

Sriram Iyer , Office Security

Karthik Selvaraj , Windows Defender ATP Research

The post Office VBA + AMSI: Parting the veil on malicious macros appeared first on Microsoft Secure .


          A question of security: What is obfuscation and how does it work?      Cache   Translate Page      

Every day, new malware samples are uncovered ranging from zero-day exploits to ransomware variants.

With malware now so common and successful cyberattacks offering potentially high -- albeit criminal -- returns, there is little need for garden-variety hackers to learn how to develop exotic, custom malicious code.

Instead, off-the-shelf malware can be purchased easily by anyone. While some of the most sophisticated forms of malware out there can fetch prices of$7,000 and more, it is also possible to pick up exploit kits and more for far less,or even for free.

The problem with this so-called "commodity" malware is that antivirus companies are well aware of their existence and so prepare their solutions accordingly with signatures that detect the malware families before they can cause damage.

So, how do threat actors circumvent such protection?

This is known as obfuscation.

The goal of obfuscation is to anonymize cyberattackers, reduce the risk of exposure, and hide malware by changing the overall signature and fingerprint of malicious code -- despite the payload being a known threat.

In a Threat Intelligence Bulletin , cybersecurity firm Cylance has explained how the technique works.

"The signature is just a hash," the researchers note. "In this context, a hash refers to a unique, alphanumeric representation of a piece of malware. Signatures very often are hashes, but they can also be some other brief representation of a unique bit of code inside a piece of malware."

CNET: Apple is building an online portal for police to make data requests

Rather than attempt to create a new signature through changing malware itself, obfuscation instead focuses on delivery mechanisms in an attempt to dupe antivirus solutions which rely heavily on signatures. (In comparison to the use of machine learning, predictive analytics, and AI to bolster AV, some researchers argue this has the potential to become obsolete.)

See also: Mirai, Gafgyt IoT botnets stab systems with Apache Struts, SonicWall exploits

Obfuscation can include a variety of techniques to hide malware, creating layers of obscurity which Cylance compares to "nested figures in a Russian doll."

These techniques include:

Packers: These software packages will compress malware programs to hide their presence, making original code unreadable. Crypters: Crypters may encrypt malware programs, or portions of software, to restrict access to code which could alarm an antivirus product to familiar signatures. Dead code insertion: Ineffective, useless code can be added to malware to disguise a program's appearance. Instruction changes: Threat actors may alter instruction codes in malware from original samples that end up changing the appearance of the code -- but not the behavior -- as well as change the order and sequence of scripts. Exclusive or operation (XOR): This common method of obfuscation hides data so it cannot be read unless trained eyes apply XOR values of 0x55 to code. ROT13: This technique is an ASM instruction for "rotate" which substitutes code for random letters.

TechRepublic: Why higher education is one of the worst industries at handling cyberattacks

"While some antivirus products search for common obfuscating techniques so that they too may be blacklisted, this practice is not nearly as well established as the blacklisting of malware payload signatures," the researchers say.

In one interesting example of obfuscation which has recently come under the radar, Cylance found that a Microsoft windows tool called PowerShell is being abused by attackers.

A malware sample obtained by the company was a .ZIP file containing a PDF document and VBS script which used rudimentary Base64 encoding to obfuscate one layer.

This was followed by the use of string splitting, tick marks, and random letter capitalizations to split and alter the signature.

One particular file in the package, 1cr.dat, revealed the use of another obfuscation method. This was a string encryption setup, called SecureString, which is commonly used by legitimate applications to encrypt sensitive strings of code within applications using Microsoft's built-in DPAPI.

The payload also contained instructions to avoid sandboxes, which are used by security researchers to unpack and analyze malware.

At the time of discovery, only three antivirus signature engines detected the attempt at obfuscation and only two registered the malware at first deployment. This has now increased to 18 products.

For as long as malware exists, so too will obfuscation. While there is little that everyday users can do about the attack method, cybersecurity firms are taking notice -- as now, it is not just zero-days which are of concern, but the increasing use of common malware in creative ways.

Cylance said:

"Threat actors are increasingly using obfuscation techniques in combination with commodity malware. This trend runs counter to a widely-held assumption in the information security space which holds that highly customized malware paired with zero-day exploits are deserving of the most attention. And while use of those tools is concerning and should be monitored, attention should not be completely divested from those threat actors - including advanced threat actors - who are succeeding right now at bypassing antivirus products with tools that are not "zero- day" but "every day."


          Gurucul Introduces Managed Security Analytics Service      Cache   Translate Page      
Provides Dedicated Access to Data Science Experts for Design,
Management and Optimization of Behavior Based Security Systems to
Expedite Risk Detection and Response
Gurucul Introduces Managed Security Analytics Service

LOS ANGELES (BUSINESS WIRE) #EY ― Gurucul , a leader in behavior based

security and fraud analytics technology for on-premises and the cloud,

today announced Gurucul Labs, a turn-key managed security analytics

service based on the Gurucul Risk Analytics (GRA) platform which

provides the data science expertise many organizations lack to

operationalize their investments in behavior based security analytics.

Gurucul Labs combines people, processes and technology to help

organizations discover unknown threats in real-time and expedite

responses to malicious insiders, unusual usage activity, compromised

accounts or hosts, network intrusions, data exfiltration and more. The

service provides continuous machine learning algorithms and anomaly

model tuning and refinement by data scientists based on intelligence

gathered from the Carnegie Mellon US-CERT team, Gurucul’s other research

partners, and global customers.

The Gurucul Labs service provides customers the following resources:

Security Architect : to ensure a robust and scalable security
architecture (systems integration, cloud, hybrid, on-premise
deployment architecture, security architecture) and security data
validation GRA Engineer : to facilitate GRA implementation, administration
and maintenance activities Security Analyst : to support security threat research, use case
identification and design, first level triage of high-risk incidents,
case investigation, fine tuning feedback, case management and reporting Fraud Analyst: to research insider and third party fraud scenarios,
suggest data tagging and access control, investigate fraud cases,
perform impact analysis and suggest response actions Data Scientist : to review data sets, behavior models and tuning
suggestions

“Many organizations lack the in-house resources and expertise to

optimize their investments in behavior based security analytics,” said

Nilesh Dherange, chief technology officer for Gurucul. “Gurucul Labs

eliminates this roadblock, and enables customers to operationalize the

collective intelligence of Gurucul’s experts, research partners like the

Carnegie Mellon US-CERT team and best practices from the Gurucul

customer community ― to protect their environments.”

Gurucul Labs Highlights

Gurucul Labs provides an end-to-end security analytics platform

administration and maintenance service that includes:

Efficacy tracking and fine-tuning of out of the box analytical models
to find true positive incidents for real-time threat detection and
response Configuration of threat use cases to address organization specific
business and IT risks Implementation and operationalization of machine learning models
created in other systems using Gurucul STUDIO Assist organizations in deploying GRA as a centralized analytics and
risk engine to generate contextual risk prioritized alerts On-going anomaly detection, findings triage, first level
investigation, case management and reporting User and role administration, data validation, system configuration
and customization support Ongoing system maintenance and health check including resource
performance and utilization monitoring/optimization Quarterly results effectiveness reports for senior management Gurucul Labs scorecard to track anomalies, cases, model efficacy and
data ingestion trends

Availability

The Gurucul Labs managed security analytics

service is available immediately for cloud, hybrid,and on-premise

deployments.

About GRA

Gurucul Risk Analytics (GRA) is a multi-use

behavior based security and fraud analytics platform with an

architecture that supports an open choice of big data for scale, the

ability to ingest virtually any dataset for desired attributes and

includes configurable prepackaged analytics. The Gurucul GRA platform

includes UEBA, Fraud Analytics, Identity analytics and Cloud Analytics

products. In addition,

Gurucul

enables security teams to create custom machine learning

models to meet unique customer requirements without coding and minimal

data science knowledge. GRA ingests and analyzes huge volumes of data

generated when users access and interact with business applications, in

both the data center and the cloud, to generate risk scores, identify

security threats and prevent data breaches. The Gurucul GRA platform has

been successfully deployed by government agencies and Global Fortune 500

companies.

About Gurucul

Gurucul is a global cyber security and fraud

analytics company that is changing the way organizations protect their

most valuable assets, data and information from insider and external

threats both on-premises and in the cloud. Gurucul’s real-time security

analytics and fraud analytics technology combines machine learning

behavior profiling with predictive risk-scoring algorithms to predict,

prevent and detect breaches. Gurucul technology is used by Global 1000

companies and government agencies to fight cyber fraud, IP theft,

insider threat and account compromise. The company is based in Los

Angeles. To learn more, visit http://www.gurucul.com/

and follow us on LinkedIn

and Twitter .

Contacts

Marc Gendron PR

Marc Gendron, 781-237-0341

marc@mgpr.net
Gurucul Introduces Managed Security Analytics Service
Do you think you can beat this Sweet post? If so, you may have what it takes to become a Sweetcode contributor...Learn More.
          In the Know: Present and Future of Artificial Intelligence in Security      Cache   Translate Page      

You’ve seen that movie, the one where humans fabricate robots that are so human-like they end up taking over the world. What was once the plot line for every other sci-fi film is now leaking into the reality of our everyday lives.

The future of artificial intelligence isn’t so distant with voice-powered personal assistants like Siri and Alexa , and autonomously-powered self-driving vehicles already on the market. But these technologies still have a way to go and some would argue that these advancements aren’t true artificial intelligence because they lack the ability to learn. A pure artificial intelligence can improve on past iterations, becoming more intelligent and aware, creating pathways to enhance its capabilities and knowledge. In the movies, that’s when the machines really takeover. Artificial intelligence within the endpoint and network security context is still limited because it depends on benign and malicious content to “train” on. With new attack vectors, if the security solution didn’t have a chance to learn it then it is still vulnerable and on a par with legacy AV and network IPS where new threats remain undetected.

With our current technology, we tend to think more in terms of pseudo-artificial intelligence. Meaning, when a machine mimics cognitive functions that humans consider human. That includes learning, reasoning, and problem solving, which we also define as “ machine learning .”


In the Know: Present and Future of Artificial Intelligence in Security
Marketing Hype or Security Gold?

In the last few years, there has been a lot of buzz around artificial intelligence and machine learning. RSA conferences featuring companies claiming to use artificial intelligence raised a lot of interest, and provided participants with the opportunity to break through the marketing hype and really dig into the innovations that will one day advance the future of artificial intelligence in security.

As it turns out, many products marketed as using artificial intelligence are just well-established technology like machines that can recognize and identify hostile traffic. Spam filters, anyone?

As a result, Cybersecurity professionals are starting to see through the smoke and in a survey , 87% said “it will be more than three years before they really feel comfortable trusting AI to carry out any significant cybersecurity decisions.”

Future of Artificial Intelligence in Security Still Bright

While confidence behind the technology has room for improvement, the future of artificial intelligence is limitless. We are already witnessing machine learning quantify risk, detecting network attacks and traffic anomalies, and pinpointing malicious applications. But with an onslaught of threats like non-malware and fileless attacks, plus a lack of security manpower, we need the technology to evolve and fast. In North America alone, the infosec community is overloaded with roughly 10,000 security alerts per day .

Technological boons will help this perfect storm by offsetting the lack of experience among security workers. With the growing availability of big data and heavy-lifting graphic-processing units, we’re likely to see a renaissance period for artificial intelligence beginning this year.

The evolution won’t come easily or cheaply though. Artificial intelligence solutions require a great deal of backend infrastructure. And the massive computation power necessary for daily training and updating models is still quite expensive.

Machine vs. Machine

Cybercrime rings aren’t run by robots yet, but we can assume that as we are leveraging artificial intelligence, so are they. Using the same underlying technology, malicious actors can develop cleaner, more convincing attacks, which could even trick the keenest security professional.

While artificial intelligence is here to help improve detection, it is not a one-stop-shop. We will continue to need system-wide monitoring and a behavioral approach while current endpoint solutions with artificial intelligence are still static and blind to in-process threats.

SentinelOne takes the possibility of a machine vs. machine security scenario seriously. Our approach combines AI and machine learning in several detection layers, added with a visibility and monitoring capability that allows an unprecedented view into an endpoint’s activities.

Endpoints are the point of entry into your environment, your data, your credentials, and potentially your entire business. A compromised endpoint provides everything an attacker needs to gain a foothold on your network, steal data, and potentially hold it to ransom. Unless you secure your critical endpoints (including servers, laptops, and desktops), you may be leaving the front door wide open for attackers.

Attackers have figured out how to bypass traditional antivirus software with fileless attacks designed to hide within sanctioned applications and even within the OS itself.

According tothe SentinelOne H1 2018 Enterprise Risk Index Report , fileless-based attacks rose by 94%. So, even if you’re vigilant about installing patches and pushing out antivirus updates, your organization is likely still at risk. Keep reading to understand how attackers have adapted their tactics to evade traditional antivirus, how these increasingly common attacks work and how to quickly evolve your threat detection strategy.

Want to see how SentinelOne can effectively protect you from current security risks?

Get a Demo Now

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          Artificial Intelligence for Robotics      Cache   Translate Page      

Bring a new degree of interconnectivity to your world by building your own intelligent robots Key Features Leverage fundamentals of AI and robotics Work through use cases to implement various machine learning algorithms Explore Natural Language Processing (NLP) concepts for efficient decision making in robots Book Description Artificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence. What you will learn Get started with robotics and artificial intelligence Apply simulation techniques to give your robot an artificial personality Understand object recognition using neural networks and supervised learning techniques Pick up objects using genetic algorithms for manipulation Teach your robot to listen using NLP via an expert system Use machine learning and computer vision to teach your robot how to avoid obstacles Understand path planning, decision trees, and search algorithms in order to enhance your robot Who this book is for If you have basic knowledge about robotics and want to build or enhance your existing robot's intelligence, then Artificial Intelligence for Robotics is for you. This book is also for enthusiasts who want to gain knowledge of AI and robotics. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.


          Research Scientist Machine Learning - Intel - Hillsboro, OR      Cache   Translate Page      
Intel Labs engages the leading thinkers in academia and industry in addition to partnering closely with Intel business units. Inside this Business Group....
From Intel - Fri, 27 Jul 2018 12:08:26 GMT - View all Hillsboro, OR jobs
          Healthcare General Manager - DataRobot - Boston, MA      Cache   Translate Page      
DataRobot is defining a category called automated machine learning and has already raised more than $122M from the likes of NEA, Intel Ventures and Accomplice...
From DataRobot - Thu, 26 Jul 2018 02:23:39 GMT - View all Boston, MA jobs
          Insurance General Manager - DataRobot - Boston, MA      Cache   Translate Page      
DataRobot is defining a category called automated machine learning and has already raised more than $122M from the likes of NEA, Intel Ventures and New York...
From DataRobot - Wed, 20 Jun 2018 20:26:05 GMT - View all Boston, MA jobs
          Sales Engineer - GoodData Corporation - Boston, MA      Cache   Translate Page      
Experience conducting business value assessments. Experience in Predictive Analytics and/or Machine Learning....
From GoodData Corporation - Thu, 19 Jul 2018 07:11:21 GMT - View all Boston, MA jobs
          Research Scientist Machine Learning - Intel - Hillsboro, OR      Cache   Translate Page      
Intel Labs engages the leading thinkers in academia and industry in addition to partnering closely with Intel business units. Inside this Business Group....
From Intel - Fri, 27 Jul 2018 12:08:26 GMT - View all Hillsboro, OR jobs
          Healthcare General Manager - DataRobot - Boston, MA      Cache   Translate Page      
DataRobot is defining a category called automated machine learning and has already raised more than $122M from the likes of NEA, Intel Ventures and Accomplice...
From DataRobot - Thu, 26 Jul 2018 02:23:39 GMT - View all Boston, MA jobs
          Insurance General Manager - DataRobot - Boston, MA      Cache   Translate Page      
DataRobot is defining a category called automated machine learning and has already raised more than $122M from the likes of NEA, Intel Ventures and New York...
From DataRobot - Wed, 20 Jun 2018 20:26:05 GMT - View all Boston, MA jobs
          Sales Engineer - GoodData Corporation - Boston, MA      Cache   Translate Page      
Experience conducting business value assessments. Experience in Predictive Analytics and/or Machine Learning....
From GoodData Corporation - Thu, 19 Jul 2018 07:11:21 GMT - View all Boston, MA jobs
          Setup and test an existing project written in Python, using Caffe and CUDA      Cache   Translate Page      
I'm creating a solution where a module will be added. This module will be extracted from a github, public project. This project is written in Python, and uses Caffe framework to make object classification over video files... (Budget: $30 - $250 USD, Jobs: Artificial Intelligence, CUDA, Machine Learning, Python)
          Artificial Intelligence for Robotics      Cache   Translate Page      

Bring a new degree of interconnectivity to your world by building your own intelligent robots Key Features Leverage fundamentals of AI and robotics Work through use cases to implement various machine learning algorithms Explore Natural Language Processing (NLP) concepts for efficient decision making in robots Book Description Artificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence. What you will learn Get started with robotics and artificial intelligence Apply simulation techniques to give your robot an artificial personality Understand object recognition using neural networks and supervised learning techniques Pick up objects using genetic algorithms for manipulation Teach your robot to listen using NLP via an expert system Use machine learning and computer vision to teach your robot how to avoid obstacles Understand path planning, decision trees, and search algorithms in order to enhance your robot Who this book is for If you have basic knowledge about robotics and want to build or enhance your existing robot's intelligence, then Artificial Intelligence for Robotics is for you. This book is also for enthusiasts who want to gain knowledge of AI and robotics. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.


          451 Research Survey Uncovers the Positive Benefits of AI and Machine Learning      Cache   Translate Page      

New Voice of the Enterprise survey cites gaining competitive advantages and improving customer experience with AI and machine learning as more important than lowering costs

(PRWeb September 13, 2018)

Read the full story at https://www.prweb.com/releases/451_research_survey_uncovers_the_positive_benefits_of_ai_and_machine_learning/prweb15759156.htm


          Ingénieur Analyse de Données et Logiciels - Intelligence Manufacturière - Data Analytics and Software Engineer – Manufacturing Intelligence - Alcoa Corp. - Deschambault, QC      Cache   Translate Page      
IoT, Connected Worker, Machine Learning, Cloud, Robotics, Augmented Reality. Ce poste peut être basé à l'une ou l'autre des Alumineries d'Alcoa dans le monde/...
From Alcoa Corp. - Fri, 29 Jun 2018 03:08:28 GMT - View all Deschambault, QC jobs
          Ingénieur Analyse de Données et Logiciels - Intelligence Manufacturière - Data Analytics and Software Engineer – Manufacturing Intelligence - Alcoa Corporation - Deschambault, QC      Cache   Translate Page      
IoT, Connected Worker, Machine Learning, Cloud, Robotics, Augmented Reality. Description du poste....
From Alcoa Corporation - Thu, 28 Jun 2018 15:45:09 GMT - View all Deschambault, QC jobs
          Senior Software Development Engineer - Distributed Computing Services (Hex) - Amazon.com - Seattle, WA      Cache   Translate Page      
Knowledge and experience with machine learning technologies. We enable Amazon’s internal developers to improve time-to-market by allowing them to simply launch...
From Amazon.com - Thu, 26 Jul 2018 19:20:25 GMT - View all Seattle, WA jobs
          Senior Site Reliability Engineer - Sift Science - Seattle, WA      Cache   Translate Page      
The Sift Science Trust PlatformTM uses real-time machine learning to accurately predict which users businesses can trust, and which ones they can't....
From Sift Science - Fri, 22 Jun 2018 20:18:59 GMT - View all Seattle, WA jobs
          Senior Software Engineer - Revenue Optimization - WeWork Global Technology - New York, NY      Cache   Translate Page      
Experience building Linear Programming solutions and Machine learning applications highly desired. Deep understanding of Amazon Web Services including ECS,...
From WeWork - Wed, 06 Jun 2018 05:19:01 GMT - View all New York, NY jobs
          Executive Director- Machine Learning & Big Data - JP Morgan Chase - Jersey City, NJ      Cache   Translate Page      
We would be partnering very closely with individual lines of business to build these solutions to run on either the internal and public cloud....
From JPMorgan Chase - Fri, 20 Jul 2018 13:57:18 GMT - View all Jersey City, NJ jobs
          Setup and test an existing project written in Python, using Caffe and CUDA      Cache   Translate Page      
I'm creating a solution where a module will be added. This module will be extracted from a github, public project. This project is written in Python, and uses Caffe framework to make object classification over video files... (Budget: $30 - $250 USD, Jobs: Artificial Intelligence, CUDA, Machine Learning, Python)
          Setup and test an existing project written in Python, using Caffe and CUDA      Cache   Translate Page      
I'm creating a solution where a module will be added. This module will be extracted from a github, public project. This project is written in Python, and uses Caffe framework to make object classification over video files... (Budget: $30 - $250 USD, Jobs: Artificial Intelligence, CUDA, Machine Learning, Python)
          Senior Software Engineer (A.I)      Cache   Translate Page      
TX-Austin, To avoid delays in having your resume reviewed please forward directly to: ____________________________________________________________________________________ Sam.Major@RAndstadUSA.com ____________________________________________________________________________________ JOB TITLE: Senior Software Engineer (Computer Vision & Machine Learning) LOCATION: Austin, TX 78702 (Relocation Assistance Provid
          Hot Topics of 2017: Behavior, Direct Electrical Stimulation, Computational Psychiatry, and more      Cache   Translate Page      

Hot topic is the way that we rhyme
Hot topic is the way that we rhyme
. . .
Carol Rama and Elanor Antin
Yoko Ono and Carolee Schneeman
You're getting old, that's what they'll say, but
Don't give a damn I'm listening anyway

Le Tigre, Hot Topic


What were some of the notable neuroscience topics and advances of 2017?
Here is a short and idiosyncratic list:


1. The Return of Behavior

Krakauer JW, Ghazanfar AA, Gomez-Marin A, MacIver MA, Poeppel D. Neuroscience Needs Behavior: Correcting a Reductionist Bias. Neuron. 2017 Feb 8;93(3):480-490.

see The Big Ideas in Cognitive Neuroscience, Explained


2. Direct Electrical Stimulation of the Human Brain (DARPA style)  but continuous DBS for nothing psychiatric yet.

Ezzyat Y, Kragel JE, Burke JF, Levy DF, Lyalenko A, Wanda P, O'Sullivan L, Hurley KB, Busygin S, Pedisich I, Sperling MR, Worrell GA, Kucewicz MT, Davis KA, Lucas TH, Inman CS, Lega BC, Jobst BC, Sheth SA, Zaghloul K, Jutras MJ, Stein JM, Das SR, Gorniak R, Rizzuto DS, Kahana MJ. (2017). Direct Brain Stimulation Modulates Encoding States and Memory Performance in Humans. Curr Biol. 27(9):1251-1258.

Wu H, Miller KJ, Blumenfeld Z, Williams NR, Ravikumar VK, Lee KE, Kakusa B, Sacchet MD, Wintermark M, Christoffel DJ, Rutt BK, Bronte-Stewart H, Knutson B, Malenka RC, Halpern CH. (2017). Closing the loop on impulsivity via nucleus accumbens delta-band activity in mice and man. Proc Natl Acad Sci Dec 18. [Epub ahead of print].

Inman CS, Manns JR, Bijanki KR, Bass DI, Hamann S, Drane DL, Fasano RE, Kovach CK, Gross RE, Willie JT. (2017). Direct electrical stimulation of the amygdala enhances declarative memory in humans. Proc Natl Acad Sci Dec 18. [Epub ahead of print].

see Amygdala Stimulation in the Absence of Emotional Experience Enhances Memory for Neutral Objects


3. Computational Psychiatry (in theory, not in reality)...  But how about:

Powers AR, Mathys C, Corlett PR. (2017). Pavlovian conditioning-induced hallucinations result from overweighting of perceptual priors. Science. 357(6351):596-600.


4. Debates About Prediction vs. Explanation

Yarkoni T, Westfall J. (2017). Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning. Perspect Psychol Sci. 12(6):1100-1122.



So many roads and so much opinion
So much shit to give in, give in to
So many rules and so much opinion
So much bullshit but we won't give in
Stop, we won't stop
Don't you stop
I can't live if you stop 

ibid



Hey neurokids! Forget about biology and psychology. Get your degree in engineering, statistics, mathematics, machine learning, or data science!! Or else you'll end up useless like the lost generation of neuroscience Ph.D.'s......


5. Opto-anything



Tammy Rae Carland and Sleater-Kinney
Vivienne Dick and Lorraine O'Grady
Gayatri Spivak and Angela Davis
Laurie Weeks and Dorothy Allison
Stop, don't you stop
Please don't stop
We won't stop

ibid



6. Pretty much anything by @KordingLab and by @gallantlab is revered.


7. Then there's all that Bayesian Brain Markov Blanket Free Energy Principle stuff, but @neuroconscience is way more qualified to tout this work.


8. Manifolds.


Gertrude Stein, Marlon Riggs, Billie Jean King, Ut, DJ Cuttin Candy,
David Wojnarowicz, Melissa York, Nina Simone, Ann Peebles, Tammy Hart,
The Slits, Hanin Elias, Hazel Dickens, Cathy Sissler, Shirley Muldowney,
Urvashi vaid, Valie Export, Cathy Opie, James Baldwin,
Diane Dimassa, Aretha Franklin, Joan Jett, Mia X, Krystal Wakem,
Kara Walker, Justin Bond, Bridget Irish, Juliana Lueking,
Cecelia Dougherty, Ariel Skrag, The Need, Vaginal Creme Davis,
Alice Gerard, Billy Tipton, Julie Doucet, Yayoi Kusama, Eileen Myles
Oh no no no don't stop stop............ 

ibid


{I don't know about you, but I'm a little burned out on functional connectivity and the human connectome.}





Kathleen Hanna on Becoming a Brand

          Tech Companies Poach AI Talent from Universities      Cache   Translate Page      
In a tight market for AI and machine learning, tech companies have always relied on a secret weapon -- tapping into the talent available in academia. But who will train tomorrow's AI experts?
          Machine Learning Engineer - TECHNICA CORPORATION - Dulles, VA      Cache   Translate Page      
Technica Corporation is seeking a Machine Learning. Engineer to support our internal Innovation, Research....
From Technica Corporation - Thu, 23 Aug 2018 10:27:08 GMT - View all Dulles, VA jobs
          H MediaTek έχει low-cost face unlocking τεχνολογία      Cache   Translate Page      
Είναι γνωστό πως το Face ID της Apple είναι μια από τις πιο ασφαλείς λύσεις σε θέμα ασφάλειας, αυτή τη στιγμή. Χρησιμοποιεί την τεχνολογία 3D Structured-Light, όμως πολύ λίγες Android συσκευές την έχουν ενσωματώσει, λόγω του κόστους της. Έτσι μόνο τα Xiaomi Mi 8 Explorer και το Oppo Find X, χρησιμοποιούν Structured-LIght 3D αισθητήρες για αναγνώριση προσώπου. Η MediaTek θέλει να κάνει πιο προσιτή την τεχνολογία.
Η αναγνώριση προσώπου είναι ένα χαρακτηριστικό που έχουν ακόμα και οι οικονομικές συσκευές, χωρίς όμως να διαθέτουν τους κατάλληλους αισθητήρες, ώστε να προσφέρουν τη μέγιστη δυνατή ασφάλεια. Η MediaTek πιστεύει πως έχει μια πιο πρακτική λύση, που μπορεί να δουλέψει το ίδιο καλά με το Face ID της Apple. Ονομάζει την τεχνολογία Active Stereo και είναι συμβατή με τον Helio P20 και τον Helio P22
Στην πρόσοψη των συσκευών θα βρούμε έναν προβολέα υπερύθρων, μαζί με δύο σετ από υπέρυθρους φακούς. Ο αλγόριθμός της αναγνώρισης προσώπου τροφοδοτείται από ένα machine learning software και μια μηχανή επιτάχυνσης βάθους πεδίου. Η μηχανή του Active Stereo Depth βρίσκεται ήδη στον Helio P60 και τον Helio P22 και η βασική του χρήση είναι ο υπολογισμός του βάθους για το bokeh effect και τα beauty modes της κάμερας. Όταν όμως συνδυαστεί με το κατάλληλο hardware, μπορεί να χρησιμοποιηθεί μέχρι και για επιβεβαίωση σε χρηματικές συναλλαγές.
Η MediaTek μας λέει πως ο προβολέας υπερύθρων είναι φτιαγμένος από την Himax, ενώ το λογισμικό έχει δημιουργηθεί από την Vision Technology Face++.
Η τεχνολογία φαίνεται πως είναι έτοιμη,όμως θα πρέπει να περιμένουμε μέχρι την πρώτη εμπορική υλοποίηση. Θα πρέπει λοιπόν να κάνουμε λίγο υπομονή μέχρι τότε. Όμως περιμένουμε και μια ακόμα υλοποίηση από την vivo, που ονομάζεται TOF (Time of Flight).
          MACHINE LEARNING ENGINEER FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page      
We thank all applicants for their interest in career opportunities with Huawei. Machine Learning Engineer for Speech related Applications (6 months contract)....
From Huawei Canada - Mon, 18 Jun 2018 23:46:16 GMT - View all Montréal, QC jobs
          Machine Learning/AI Engineer - Groom & Associates - Montréal, QC      Cache   Translate Page      
Machine Learning/AI Engineer An international company is looking for Machine Learning/AI Engineers to join their new Montreal office! Title: Machine Learning...
From Groom & Associates - Thu, 06 Sep 2018 08:57:48 GMT - View all Montréal, QC jobs
          MACHINE LEARNING INTERN FOR SPEECH RELATED APPLICATIONS - Huawei Canada - Montréal, QC      Cache   Translate Page      
We thank all applican