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Other: Quantitative Analytics Mgr 1 / Lead - Model Monitoring and Quality Review - AI MD CoE - Irving, TexasCache
|Important Note During the application process, ensure your contact information (email and phone number) is up to date and upload your current resume prior to submitting your application for consideration. To participate in some selection activities you will need to respond to an invitation. The invitation can be sent by both email and text message. In order to receive text message invitations, your profile must include a mobile phone number designated as Personal Cell or Cellular in the contact information of application. At Wells Fargo, we want to satisfy our customers financial needs and help them succeed financially. We re looking for talented people who will put ou customers at the center of everything we do. Join our diverse and inclusive team where you ll feel valued and inspired to contribute your unique skills and experience. Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you. Data Management and Insights (DMI) is transforming the way that Wells Fargo uses and manages data. Our work enables Wells Fargo to empower and inform our team members, deliver exceptional experiences for our customers, and meet the elevated expectations of our regulators. The team is responsible for designing the future data environment, defining data governance and oversight, and partnering with technology to operate the data infrastructure for the company. This team also provides next generation analytic insights to drive business strategies and help meet our commitment to satisfy our customers financial needs. The Artificial Intelligence Model Development Center of Excellence (AI MD CoE) team is a data science team, responsible for developing and deploying machine learning and AI solutions for a number of domain areas such as fraud prevention, credit risk, experience personalization, customer listening, anomaly detection and operational cost improvement. The CoE partners closely with the AI Enterprise Solutions and the AI Technology teams at the bank, and brings a cross-functional approach to identifying, developing and deploying AI solutions. The CoE requires high-skill/ high-motivation individuals who enjoy working collaboratively in a team setting, used to taking decisions autonomously and comfortable with a dynamic work environment. The Lead Model Monitoring and Review role would be responsibl executing on the model monitoring and model rapid refresh functions of the CoE. The role would create a standardized and efficient process for model monitoring so that risks around model degradation and failure are identified in a consistent and timely way. Also that the model retraining on a fresh set of data is performed in a speedy manner, but with the appropriate controls to ensure model robustness and stability. Additional responsibilities would include the quality review of model related technical documentation going to Model Risk Mgmt as well as other audit and regulatory bodies. A key requirement out of this role would be to make sure that industry best practices for model monitoring and refresh are appropriately brought into the processes followed by the AI Model Development CoE. This would include identification and selection of the potential external solutions that meet this overall requirement, as well as bringing in useful open source frameworks. The role of the Leader would be to hire and manage a team of data scientists and documentation review experts that can deliver on the objectives of the role. Key_Responsibilities_Include * Defining the operating framework for model monitoring operations monitoring, drift monitoring, performance etc. * Defining the framework for rapid refresh of models and operational approach. * Undertaking the model monitoring and simple model refresh tasks, per the model monitoring and update framework (see above) and per the needs of specific models, defined by the Model Developer. Also identification of solutions to improve process efficiency through automation approaches, and implementing the same working closely with AI Enterprise Solutions and WF Technology. * Working closely with Model Risk and other governance partners to ensure that the model refresh framework is implemented in a controlled manner, within the current policy framework. * Define and implement a documentation and artifact review process for model documentation and artifacts, created as part of the model development work performed by model development teams. * People management responsibilities such as hiring, performance management, routine travel and equipment/ software related approvals. As a Team Member Manager, you are expected to achieve success by leading yourself, your team, and the business. Specifically you will * Lead your team with integrity and create an environment where your team members feel included, valued, and supported to do work that energizes them. * Accomplish management responsibilities which include sourcing and hiring talented team members, providing ongoing coaching and feedback, recognizing and developing team members, identifying and managing risks, and completing daily management tasks. Required_Qualifications * 4+ years of experience in an advanced scientific or mathematical field * 2+ years of leadership experience * A master's degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science * 2+ years of experience in Artificial Intelligence, Natural Language Processing, Machine Learning, Distributed Computing, Chatbot, and Virtual Assistant * 2+ years of Python experience Other_Desired_Qualifications * Experience with building advanced statistical and machine learning models, in a banking or financial services context * Experience with building NLP (Natural Language Processing) solutions in the financial industry * Experience with monitoring or retraining advanced statistical and machine learning models * Close familiarity with machine learning and statistical modeling techniques using open-source languages like Python or R * Solid understanding of Model Risk Management requirements for banks and financial services companies * Familiarity with Big Data technology for Data Management and Data Science * Disclaimer All offers for employment with Wells Fargo are contingent upon the candidate having successfully completed a criminal background check. Wells Fargo will consider qualified candidates with criminal histories in a manner consistent with the requirements of applicable local, state and Federal law, including Section 19 of the Federal Deposit Insurance Act. Relevant military experience is considered for veterans and transitioning service men and women. Wells Fargo is an Affirmative Action and Equal Opportunity Employer, Minority/ Female/Disabled/Veteran/Gender Identity/Sexual Orientation. Reference Number *******-6 ()|
Dell was always been relevant for small business and education markets but is now in an exalted position to stake its claim within the enterprise segment and the new battleground – the midmarket firms. In this Techaisle Take analysis I cover Dell Technologies’ On Demand offering, Progress Made Real initiative, expanded PCaaS for SMBs, focus on customer advocacy, continued SMB investment, new converged infrastructure PowerOne, Unified workspace solution and channel partner strategy.
Dell Technologies Summit in Austin was a showcase of bold announcements and understated commitments to corporate social good and customer advocacy. Dell has certainly transformed in the last five years. It has moved along a path from a PC company to end-to-end solutions provider to a digital transformation partner to a place where it is driving its own transformation through the power of analytics with a goal of delivering customer success. Dell has catapulted itself into relevancy for the next decade.
In 1984, when Michael Dell founded his namesake company in his college dorm, I was a freshly minted engineering college graduate working through my first job at a tractor manufacturing plant in India. My first interaction with Dell was in early nineties when an India-based firm was awarded a contract manufacturing deal. I was then running the secretariat of a computer manufacturer’s association in India. Since then not only technology has progressed but both the consumers and commercial buyers have evolved. Dell has not only moved with the times but sometimes has been ahead of the curve. One such “ahead of the curve” initiative is “Progress Made Real for 2030” announced at the summit.
Progress Made Real for 2030 stands on four pillars:
Enabled by a combination of pervasive use of technology and vastly-expanded solution options, the technology user and buyer community has become more diverse in both composition and focus. Business decision makers (BDMs) are not content to await IT’s blessing to pursue technology options that align with business needs: an increasingly tech-savvy business user/management community plays an ever-expanding role in assessing technology options, and even in specifying solutions and managing their rollout. At the same time, the solution options themselves have expanded to become more accessible to non-IT staff. Some technologies, such as analytics and IoT, directly address business management questions. Others, notably cloud, provide support and delivery options that give business units the option of avoiding IT oversight. Even core IT functions, such as storage management (especially with respect to Big Data) and security (particularly with regard to cloud and mobility) are reshaped by system requirements imposed by BDM needs. It is not out of place, as an analyst, to say that Dell has been a little late in recognizing and pursuing the shifting patterns. Regardless, Dell has been a believer of technology democratization and has begun a concerted effort to manage technology chaos with a differentiated customer strategy and drive the ability to scale human capacity. These are very lofty and moonshot initiatives. But then Dell is a founder-led company whose founder is skilled at assembling the proverbial ship piece-by-piece and navigating it through uncharted and occasionally choppy waters.
Dell Technologies differentiated customer strategy is built on four key points:
Dell’s customer advocacy team is constantly analyzing 9.5K social conversations per day, looks at 33K customer verbatims in addition to its 16K sales team members sharing feedback. Dell’s plan to delivering a seamless and simplified customer experience is not very different from recently announced customer lifecycle experience, aka race track, by Cisco. End goals are the same, approaches are slightly different. But the fact that all suppliers are landing at the same end-state is significant on how the technology industry has evolved.
Perhaps the most important announcement at Dell Tech Summit was its On Demand offering. Dell went to great lengths to explain its genesis and development but it is clear that it a direct response to the growing popularity of HPE GreenLake. Regardless of HPE commanding the media-waves Dell has jumped headlong into the as-a-service, post-transactional market with Dell Technologies On Demand Autonomous Infrastructure available via DT Cloud. Dell is prepared to deliver solutions today and at scale. And it is also within reach of midmarket businesses. Key takeaways of Dell’s On Demand solutions are:
Pay As You Grow is for committed workloads. The metering coverage in Flex On Demand includes processor, memory, and GB consumed. Data Center Utility adds metering based on VM and per port. The solution is still in its early stages and Dell views this as a journey rather than a destination. But the offering, in early stages, is finding acceptance at many of Dell’s customers. Scalar (a CDW company) has been configuring on-demand solutions with unlimited scalability for major Hollywood studios.
Relative to the cost of conventional hardware and software, on-demand cloud solutions are generally more cost effective than equivalent CAPEX-based on-premise alternatives, and its OPEX-based billing model works well for cash-constrained SMBs and midmarket firms. Cloud’s ‘as-a-Service’ delivery model reduces the need for individual SMBs and midmarket firms to attract and retain specialized IT staff; scale up as the organization grows, and cloud provides SMBs and midmarket firms that are often unable to maintain refresh cycles with ‘always-on’ access to current technology.
SMBs are not being left out from Dell’s strategy. In fact, small and midmarket businesses are two of the fastest growing segments for Dell. Its small business advisory has witnessed tremendous success but the team is not resting on its laurels. It aims to add 100 more small business advisors in the next one year. Each advisor goes through 160 hours of in-person classroom training. Dell has built a progressive hierarchical advisory structure, based on “needs complexity” to help SMBs learn, identify, buy and deploy technology. Small businesses with specific and simple requirements can also use Eva – a chatbot – to help guide through product selection and purchase.
Grazie alle chatbot derivate dallo sviluppo dell'intelligenza artificiale l'assistente intelligente parlerà "con sentiment"
L'articolo Voce di Amazon Alexa: delusione ed eccitazione con i toni realistici è un contenuto originale di Digitalic.
Business Insider reports that over 80% businesses are expected to have Chatbot automation implemented by 2020, given its efficiency and versatility. Chatbots are on rising and gaining lot of popularity! And why wouldn’t they? The progress in NLP – Natural Language Processing – field is scaling new heights everyday and with that Natural Language Understanding…
The post Launch your own Business Information Bot on Google Assistant and Facebook Messenger appeared first on Pragnakalp Techlabs.
Czym jest i jak działa chatbot rekrutacyjny? Czy to na pewno narzędzie tylko dla osób wchodzących na rynek pracy? Które narzędzia i kompetencje będą kluczowe dla działów HR oraz EB w przyszłości? Jak dziś skutecznie i efektywnie szukać pracowników? Jak zmienia się proces rekrutacji - zarówno dla rekruterów jak i kandydatów? O tym Paweł Zawadzki rozmawia z Jakubem Granatem, założycielem firmy JoBot24. Zapraszamy!
AWS Chatbot now supports running AWS commands and actions from Slack. You can retrieve diagnostic information, invoke Lambda functions and create AWS Support cases right from your Slack channels, so your team can collaborate and respond to events faster. AWS Chatbot supports commands using the already familiar AWS Command Line Interface syntax that you can use from Slack on desktop or mobile devices. In addition to running commands, you can also retrieve Amazon CloudWatch logs by simply clicking the “Show logs” button on CloudWatch Alarms notifications in Slack. AWS Chatbot supports actions for displaying logs for AWS Lambda and Amazon API Gateway.
3 de cada 5 compras realizadas en Black Friday serán fallidas por no encontrarse el cliente en destinoCache
Según datos de Happy Box, startup delivery dedicada a la aplicación de Inteligencia Artificial y chatbots para la última milla, el lunes 2 de diciembre será el día del año que más paquetes se entregarán debido a la fiebre del Black Friday y del Ciber Monday. Además, este año aumentará hasta un 10 por 100 el número de envíos.
Los datos analizados por Happy Box afirman que 3 de cada 5 paquetes a entregar no llegarán correctamente a su destino por no hallarse el destinatario en el lugar y hora de la recogida. Estas entregas fallidas ocasionarán miles de euros de pérdidas a los negocios online.
Los datos de la startup revelan que un año más el e-commerce seguirá creciendo y se convierte así en la opción preferida para las compras navideñas. De hecho, Happy Box calcula que el 65 por 100 de los regalos de Navidad se comprarán esta semana y de ellos, el 40 por 100 hoy viernes 29 de noviembre.
Todo esto apunta al lunes 2 de diciembre, como el día de entrega de todas estas compras por parte de los repartidores y riders. Uno de las dificultades que aparecen cuando se entregan los paquetes a lo largo del día 2 de diciembre, es que, la mayoría de destinatarios se encontrarán en el trabajo por lo que se complicará la recepción de los paquetes.
Las entregas fallidas suponen uno de los mayores retos para los transportistas, y para los propios negocios online que ven como sus gastos se incrementan hasta un 27 por 100.
Aumenta la demanda de riders para evitar el colapso
El aumento de consumo a través de e-commerce lleva aparejado una necesidad de más repartidores para evitar el colapso de envío sufrido en años anteriores. En 2017 y 2018 los repartidores no fueron suficientes y se retrasaron las entregas de media 3 días. Concretamente, para Navidad y Reyes puede ocasionar pérdidas de ventas de hasta un 20 por 100 del total de la campaña.
Desde la compañía se calcula que el sector de los repartidos necesitaría contratar hasta 8.000 nuevos repartidores para cubrir la alta demanda que existirá desde el 1 de diciembre hasta el 7 de enero. Precisamente para esta campaña se espera un repunte del 15 por 100 en el número de pedidos a repartir.
Ciudades grandes como Madrid y Barcelona serán las que concentren el mayor movimiento de repartidores.
Master CHATBOT development w/o coding : IBM Watson Assistant, Develop chatbot using IBM Watson Assistant. Learn Watson Text to Speech, Speech to Text and Visual Recognition Service. In this course you would learn about building a chatbot from scratch. We would explore a range of Cognitive services offered by IBM on Bluemix cloud, exploring how […]
The post Master CHATBOT development w/o coding : IBM Watson Assistant appeared first on Online Tutorials.
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ChatBot Digital Marketing that makes use Expert system modern technologies can be made use of a crucial component in any company’s advertising and marketing method in regards to directing clients through an advertising and marketing sales channel. The marketing channel that would be set into the AI ChatBot would be defined in relationship to the […]
La tecnología está impactando en todo el proceso de reserva de viajes y Expedia, consciente de ello, ha lanzado nuevas funcionalidades como el chatbot de Partner Central o un nuevo motor de recomendaciones, tal y como publicó Hosteltur en Expedia expande su ecosistema a través de la inteligencia artificial. Pero ¿qué impacto tienen estas tecnologías en los hoteles?
Con motivo de la celebración de Explore '19, convención anual de Expedia, Hosteltur ha tenido la oportunidad de hablar con Melissa Maher, Senior Vice President for Marketing and Industry Engagement Travel Partners Group de Expedia Group, sobre el papel de la tecnología en la distribución hotelera y su uso en Expedia.
¿Cómo están afectando los cambios en los hábitos del cliente en el producto de Expedia?
Trabajamos mucho en la investigación y realizamos pruebas con usuarios para implementar cambios en nuestra web orientados a reducir la fricción en el proceso de compra online. Gracias a esta investigación hemos comprobado que muchos clientes quieren usar la tecnología para hacer sus reservas y que gran parte de ellos prefiere comprar sus viajes a través de un sistema informático que hablando con una persona.
Por otro lado, queremos que nuestra plataforma sea global pero que, al mismo tiempo, pueda satisfacer las necesidades de los mercados locales. Para eso, nos fijamos en detalles concretos sobre el uso de la tecnología en cada mercado. En Japón, por ejemplo, hemos comprobado que los usuarios prefieren navegar en la web móvil haciendo clic que arrastrando con el dedo. Identificar estas tendencias nos ayuda a adaptar el producto a cada cliente.
¿Qué tipo de tecnología está teniendo más impacto?
Donde estamos viendo mayor adopción es, probablemente, en los chatbots. También estamos trabajando con sistemas de reconocimiento de voz, pero todavía se necesita más tiempo para que los clientes se sientan cómodos con ellos.
¿Cuáles son los principales obstáculos con los que se encuentran los hoteles a la hora de adaptar la tecnología?
El mayor obstáculo de todos es el coste, especialmente para los hoteles independientes. A la hora de implementar un nueva tecnología, hemos detectado que las cadenas hoteleras están priorizando la tecnología basándose en cómo la tecnología encaja en sus actuales sistemas, mientras que los hoteles independientes, aunque son conscientes de la importancia de la tecnología, están más preocupados por su coste.
¿Cómo ayuda Expedia a los hoteleros a adaptarse a la tecnología?
Estamos en contacto constantemente con miles de hoteles que nos envían sus comentarios sobre las mejoras que detectan en nuestra tecnología. También utilizamos inteligencia artificial para predecir tendencias que pueden ayudar a los revenue managers.
Una de las herramientas de las que disponen los hoteleros que forman parte de Expedia es Red Plus. Ofrece datos sobre la competencia y recomendaciones sobre cuándo pueden subir o bajar los precios de acuerdo a la demanda. Esto está siendo especialmente útil para los hoteles independientes que no tienen un departamento propio de revenue.
¿Qué ventajas tiene para el hotel estar en Expedia?
La visibilidad y el alcance es el principal beneficio. Por otro lado, la información que obtienen a través de nuestra plataforma sobre el cliente, sobre las reservas de última hora o sobre cómo establecer una estrategia de precios. También es de utilidad para los hoteles nuestro sistema de análisis de opiniones, que utiliza inteligencia artificial para extraer conclusiones de todas las opiniones de los clientes.
Einstein Chatbots are doing a tremendous job for its customers to automate the repetitive tasks and allowing the Agents to concentrate more on the complex tasks, but given a fact that not more than 10 einstein bots can be active in an org at a given point of time.
There are use cases and scenarios where we need to have more than 10 einstein bots to support our agents.
Considering the Salesforce CI and R & D, we would love to have more einstein active bots with no limitations and hope a positive note around this.
Please make this a reality, we love Einstein Bots.!
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Bespoke’s Chatbot Assistant “Bebot” Now Provides Expert Information and Japanese Hospitality to Riders on the Ginza Subway Line and at All of Its 19 Stations. the Proven Solution Allows Foreign Tourists to Easily Discover Hidden Gems in the Area and Encourages In-Market Spend by Visitors. Bebot Also Helps Cities and Transport Authorities to Promote Sustainable […]
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Centar za poduzetništvo d.o.o. organizirao je prezentaciju „Kako pronaći klijente i uspješno poslovati uz korištenje Facebook oglašavanja?” koja je održana u prostorijama Poduzetničkog inkubatora Dubrovnik. Certificirani Messenger marketing stručnjak, polaznicima je prezentirao prednosti koje Facebook oglašavanje omogućuje u poslovanju. Prezentacija je također obuhvatila primjenu Messenger chatbotova kao jedne od mogućnosti u Facebook oglašavanju. Naime, Messenger chatbotovi […]
Post Dubrovački poduzetnici učili kako što bolje koristiti Facebook oglašavanje je prvi puta viđen na ŽUPANIJA DUBROVAČKO NERETVANSKA.
In episode #1217, we unpack a list of 7 ad opportunities that we are really excited about for next year. We discuss new things on Google, chatbots, TV spots, LinkedIn and more! Listen in to hear all about it!
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The retail sector is the poster child for the use of artificial intelligence. Self-driving delivery robots, automated warehouses, intelligent chatbots, personalized recommendations, and deep supply chain analytics have been making significant impact on the bottom line — if you’re Amazon.com.
Other retailers, however, are struggling to adapt. In fact, only 19 percent of large retailers in the U.S., UK, Canada and Europe have deployed AI and are using it in production, according to Gartner.
This post is co-authored by Anny Dow, Product Marketing Manager, Azure Cognitive Services.
In an age where low-latency and data security can be the lifeblood of an organization, containers make it possible for enterprises to meet these needs when harnessing artificial intelligence (AI).
Since introducing Azure Cognitive Services in containers this time last year, businesses across industries have unlocked new productivity gains and insights. The combination of both the most comprehensive set of domain-specific AI services in the market and containers enables enterprises to apply AI to more scenarios with Azure than with any other major cloud provider. Organizations ranging from healthcare to financial services have transformed their processes and customer experiences as a result.
These are some of the highlights from the past year:
Employing anomaly detection for predictive maintenance
Airbus Defense and Space, one of the world’s largest aerospace and defense companies, has tested Azure Cognitive Services in containers for developing a proof of concept in predictive maintenance. The company runs Anomaly Detector for immediately spotting unusual behavior in voltage levels to mitigate unexpected downtime. By employing advanced anomaly detection in containers without further burdening the data scientist team, Airbus can scale this critical capability across the business globally.
“Innovation has always been a driving force at Airbus. Using Anomaly Detector, an Azure Cognitive Service, we can solve some aircraft predictive maintenance use cases more easily.” —Peter Weckesser, Digital Transformation Officer, Airbus
Automating data extraction for highly-regulated businesses
As enterprises grow, they begin to acquire thousands of hours of repetitive but critically important work every week. High-value domain specialists spend too much of their time on this. Today, innovative organizations use robotic process automation (RPA) to help manage, scale, and accelerate processes, and in doing so free people to create more value.
Automation Anywhere, a leader in robotic process automation, partners with these companies eager to streamline operations by applying AI. IQ Bot, their unique RPA software, automates data extraction from documents of various types. By deploying Cognitive Services in containers, Automation Anywhere can now handle documents on-premises and at the edge for highly regulated industries:
“Azure Cognitive Services in containers gives us the headroom to scale, both on-premises and in the cloud, especially for verticals such as insurance, finance, and health care where there are millions of documents to process.” —Prince Kohli, Chief Technology Officer for Products and Engineering, Automation Anywhere
For more about Automation Anywhere's partnership with Microsoft to democratize AI for organizations, check out this blog post.
Delighting customers and employees with an intelligent virtual agent
Lowell, one of the largest credit management services in Europe, wants credit to work better for everybody. So, it works hard to make every consumer interaction as painless as possible with the AI. Partnering with Crayon, a global leader in cloud services and solutions, Lowell set out to solve the outdated processes that kept the company’s highly trained credit counselors too busy with routine inquiries and created friction in the customer experience. Lowell turned to Cognitive Services to create an AI-enabled virtual agent that now handles 40 percent of all inquiries—making it easier for service agents to deliver greater value to consumers and better outcomes for Lowell clients.
With GDPR requirements, chatbots weren’t an option for many businesses before containers became available. Now companies like Lowell can ensure the data handling meets stringent compliance standards while running Cognitive Services in containers. As Carl Udvang, Product Manager at Lowell explains:
"By taking advantage of container support in Cognitive Services, we built a bot that safeguards consumer information, analyzes it, and compares it to case studies about defaulted payments to find the solutions that work for each individual."
One-to-one customer care at scale in data-sensitive environments has become easier to achieve.
Empowering disaster relief organizations on the ground
A few years ago, there was a major Ebola outbreak in Liberia. A team from USAID was sent to help mitigate the crisis. Their first task on the ground was to find and categorize the information such as the state of healthcare facilities, wifi networks, and population density centers. They tracked this information manually and had to extract insights based on a complex corpus of data to determine the best course of action.
With the rugged versions of Azure Stack Edge, teams responding to such crises can carry a device running Cognitive Services in their backpack. They can upload unstructured data like maps, images, pictures of documents and then extract content, translate, draw relationships among entities, and apply a search layer. With these cloud AI capabilities available offline, at their fingertips, response teams can find the information they need in a matter of moments. In Satya’s Ignite 2019 keynote, Dean Paron, Partner Director of Azure Storage and Edge, walks us through how Cognitive Services in Azure Stack Edge can be applied in such disaster relief scenarios (starting at 27:07):
Transforming customer support with call center analytics
Call centers are a critical customer touchpoint for many businesses, and being able to derive insights from customer calls is key to improving customer support. With Cognitive Services, businesses can transcribe calls with Speech to Text, analyze sentiment in real-time with Text Analytics, and develop a virtual agent to respond to questions with Text to Speech. However, in highly regulated industries, businesses are typically prohibited from running AI services in the cloud due to policies against uploading, processing, and storing any data in public cloud environments. This is especially true for financial institutions.
A leading bank in Europe addressed regulatory requirements and brought the latest transcription technology to their own on-premises environment by deploying Cognitive Services in containers. Through transcribing calls, customer service agents could not only get real-time feedback on customer sentiment and call effectiveness, but also batch process data to identify broad themes and unlock deeper insights on millions of hours of audio. Using containers also gave them flexibility to integrate with their own custom workflows and scale throughput at low latency.
These stories touch on just a handful of the organizations leading innovation by bringing AI to where data lives. As running AI anywhere becomes more mainstream, the opportunities for empowering people and organizations will only be limited by the imagination.
Visit the container support page to get started with containers today.
For a deeper dive into these stories, visit the following
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BotChats App Software & OTO Upsell by Arron Williams – Best Create Your Very Own Chatbot Without Code Or Any Real Heavy Technical Stuff & Changing Your Blogs And Fanpages To Become Instant Lead Magnets BotChats App Software & OTO Upsell by Arron Williams is Create Your Very Own Chatbot Without Code Or Any Real […]
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|Cache||Еще 3 года назад руководитель Microsoft Сатья Наделла громко объявил, что "Боты - это новые приложения" и представил платформу Microsoft Bot Framework. Но использовать ее могли только программисты, а опыт показал, что лучше, когда бота может создать (и корректировать) наиболее заинтересованный в нем сотрудник - продажник, helpdesk-агент, HR-менеджер. Поэтому теперь компания запускает сервис Microsoft Power Virtual Agents, позволяющий создавать чат-ботов в визульном конструкторе без знаний программирования. Созданного бота можно встроить в любой мессенджер или разместить на сайте. Преимущество майкрософтовского сервиса над другими подобными решениями - в бесшовной интеграции с другим ПО компании. Таким образом, боты, например, могут использовать информацию из системы аналитики Microsoft Power BI или запускать процессы в Microsoft Flow.|
См. также: Топ 10 - Конструкторы чат-ботов
Chatbots are finally living up to their hype, with business leaders confirming that the AI-based machines are helping them save money as well as increase sales. What’s more, they are also performing well as virtual customer service agents. “Business leaders saved an average of US$300,000 in 2019 from their chatbots,” says the Chatbot Trends Report […]
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