Personalizing content is a complex, dynamic problem where labor-intensive machine learning workflows and costly A/B testing fail to catch up to the nuances of user’s behavior. How do the pros, like XBox One, approach this? In this session we’ll show how businesses can use the new Cognitive Services Personalizer to improve business outcomes and user experience by letting it learn directly from user’s behavior. Personalizer (public preview) makes applied enterprise use of reinforcement learning. It enables full learning loop that runs at digital speed and learns from a simple reward score that optimizes towards your business’s goals. In this session we’ll show you how Personalizer works with your content and data, how it autonomously learns to make optimal decisions, how you can add it to your app with two lines of code, and how to understand what’s under the hood. We’ll share results Personalizer achieved on the Xbox One home page and practices you can use to apply it in your applications today.
Discover the latest updates about Project Personality Chat – Project Personality Chat enhances your bot’s conversational capabilities by handling small talk, in line with a chosen personality. Choose a personality that aligns with your brand's voice, by choosing from available default personas.
AI, machine learning, deep learning, and advanced analytics are being infused into every team and service at Microsoft—understanding customers and the business, operating services, and delivering innovative new features. But doing machine learning at the scale of Microsoft is challenging. ONNX (open neural network exchange format) has bridged the different model formats for ML frameworks (e.g. TensorFlow, Pytorch, MXNet) to a single execution environment with the ONNX Runtime. Learn how Bing, Ads, Speech, Office, Cognitive Services, and others use frameworks like TensorFlow, PyTorch, Scikit-learn, Caffe for training and rely on ONNX Runtime for high performance inferencing. You’ll also learn how to use ONNX and ONNX Runtime in your AI application with Azure ML.
Learn how Bing APIs can help business’s solve real world challenges with scenarios such as fraud detection, plagiarism detection, and extracting sentiments from across the web, as well as how easy it is to infuse applications with contextual intelligence.
Bot Framework allows developers to seamlessly build conversational bots which can later be published to services such as Slack, Skype, Messenger and more! However, there might be particular cases in which bots need to be deployed as local services (e.g. Intranets, data compliance, limited external-networks access) and also use language understanding capabilities. Enter Docker containers. Certain Azure Cognitive Services can now be deployed as containers to deliver AI-driven solutions which doesn't send the data to an external network but to an internal server. One of these services is Language Understanding (LUIS), which provides query predictions and whose packages can be integrated in the server for local consumption. In this session, the following scenario will be explored: A cross-platform mobile app which establishes a connection to a bot (which was created by using Bot Framework and which uses a LUIS package produced from utterances and examples) that is used by customers who want to obtain products and services information. Data comes from a local SQL Server database.
Microsoft Teams is shaping up as the hottest tool on the collaboration block, and bots are shaping up as the way to scale out interaction with complex internal IT systems. Furthermore, the performance of your team relies on the presence of the sweet aroma, taste, and heart-starting impact of caffeinated beverages. Using Microsoft Teams, Microsoft’s Bot Framework and Language Understanding (LUIS) from Azure Cognitive Services, learn how to add a bot to a Team, manage channel and private conversations to ask one of the most critical questions in today’s modern workplace – “who wants a coffee”?
From smart sensors and actuating devices to integrated robotic systems, industrial organizations are employing increasingly sophisticated automation technologies to drive efficiency and productivity. Microsoft is accelerating the journey toward a world where machines operate in more dynamic and intuitive ways. From smart buildings, to industrial machinery, to robotics, Microsoft is democratizing the development of increasingly autonomous systems by providing domain experts, developers, and data scientists with the tools they need to seamlessly develop and manage autonomous systems.
The SQL Server 2019 big data cluster platform provides a scalable and enterprise ready technology that can handle data of any sort. Next to the native support for R, Python, Spark, SQL and HDFS, it also provides a way to deploy applications and machine learning models on the cluster. In this session, we will explore various scenarios for doing Machine Learning on big data clusters, including hybrid, and leveraging AI with containerized Cognitive Services.
Come learn how to apply AI to understand your business documents. Cognitive search allows you to apply AI (Cognitive Skills) to your data to extract entities and relationships from your unstructured documents, turning them into your private knowledge store. In this session, you'll learn how to deploy a cognitive search solution on your data, including customer testimonies and demos. We will also introduce the new Knowledge Store that is now part of Cognitive Search, and explore new features and capabilities (complex type, storage-optimized SKU, etc.).
Microsoft Speech delivered remarkable service enhancements over the past year with industry leading Neural Speech Synthesis. In this session you will learn about our new features in real time and batch speech processing, enhancements to customize speech recognition for enterprise, deploying speech services on-prem using Docker containers, audio content generation and much more. We will also cover how to get started utilizing our speech stack to enable your speech scenarios such as call center automation and intelligent transcription.