Introducing Semantic Workbench: Your Gateway to Agentic AI Development
In the fast-paced world of artificial intelligence (AI), rapid prototyping and integration of intelligent assistants is crucial. Meet Semantic Workbench — a powerful, versatile tool designed to streamline the creation and management of AI agents. Developed within Microsoft and now available to the broader community, it simplifies the process of developing, testing, and deploying intelligent assistants.Join Microsoft experts for our Make Azure AI Real livestream series
Are you a developer who wants to learn how to use Microsoft AI tools and services, such as Azure AI Cognitive Search, Azure OpenAI Service, and more? Do you want to get insights into the latest AI trends and best practices from Microsoft AI experts? If you answered yes to any of these questions, then you should join Microsoft Reactor’s Make Azure AI Real livestream series kicking off today! We’re thrilled to bring you a collection of AI livestreams that are focused on in-depth AI technical content from experts at Microsoft where you will discover how to make AI real for your projects and goals and have the opportunity to ask questions directly to experts. Register now https://aka.ms/MAIR/RSVP
WebNN: Bringing AI Inference to the Browser
Unlock the Future of AI with WebNN: Bringing Machine Learning to Your Browser Discover how the groundbreaking Web Neural Network API (WebNN) is revolutionizing web development by enabling powerful machine learning computations directly in your browser. From real-time AI interactions to privacy-preserving data processing, WebNN opens up a world of possibilities for creating intelligent, responsive web applications. Dive into our comprehensive guide to understand the architecture, see code examples, and explore exciting use cases that showcase the true potential of WebNN. Whether you're a seasoned developer or just curious about the future of web-based AI, this article is your gateway to the cutting-edge of technology. Read on to find out more!Using Bing with GenAI: from Sales Strategy to Compete Analysis
In today's data-driven world, understanding and leveraging data is crucial for maintaining a competitive edge. The integration of Bing as a search engine for extracting data from the internet is transforming how businesses interact with external and internal data sources. This approach not only enriches internal data repositories but also enhances decision-making and operational management processes. Key Highlights: Robust Data Extraction: Establish a sophisticated system for data extraction to access a wealth of information from the internet, crucial for understanding market dynamics and opportunities. Advanced Search Capabilities: Develop an internal data search engine using Bing, enabling rapid and reliable information retrieval to better understand the operational environment. Customized Data Handling: Differentiate between handling external and internal data to optimize data usage — external data for strategic insights and internal data for operational intelligence. Leverage Disruptive Technologies: Utilize Bing combined with generative AI to analyze market shares, customer reviews, and social media, providing deeper insights into market trends and consumer preferences.Uncover the Future: Microsoft Autonomous AI Agents analyzing SAP Data Insights
Microsoft TaskWeaver is a framework that lets developers build and manage tasks across different platforms and applications. Frameworks such as Langchain, Semantic Kernel, Transformers Agent, Agents, AutoGen and JARVIS, which use LLMs for task-oriented conversations, are crucial in this transformation. They allow easy, natural language interactions with AI systems, making complex data analytics and domain-specific tasks more available. However, the real challenge and opportunity are in improving these frameworks to overcome current limitations, especially in specialized areas like SAP and data analytics. This involves adding domain-specific knowledge into GenAI models, improving their ability to process and analyze industry-specific data and workflows. There are many examples of how TaskWeaver can handle different tasks effectively. For example, developers can build smart agents that communicate with users fluently and helpfully, improving user satisfaction through clever conversation. TaskWeaver's skill to understand user needs, control plugins, and run code safely makes it a very useful tool for various applications, from financial prediction to data exploration.
Microsoft Ignite 2023 Announcements for Azure AI Video Indexer
We are excited to share the latest updates that we have added to Azure AI Video Indexer (VI), the video analysis solution that helps you to extract insights from your video and audio files, based on AIs. Here are some of the highlights: Edge version of Azure VI, enabled by Arc: You can use Azure VI on your own edge on premise environment, without sending your video data to the cloud. This will ensure you adhere to local regulation and privacy constrains or optimize your hardware use, while still enjoying the same functionalities that Azure VI offers on the cloud. It the first hybrid Video AI managed solution in Azure. Bring-your-own AI feature: You can use models from Hugging Face, Azure Florence, or any other AI models and connect them to VI insights. This will allow you to customize and enhance your video analysis with your own models, and to benefit from a single joint experience. Enrich your video metadata and video search experience: You can now add custom tags and free text as video metadata for any specific video in your account. This will help you to annotate your videos with any information that is relevant to your business. You can also search for videos based on the custom tags and free text that you have added to them. Features improving the efficiency of customized people model (subjected to limited access features program) All features were delivered as preview features.Building Real-Time, Intelligent AI Copilots with Confluent Cloud, Azure OpenAI & Azure Data Services
Real-time application scenarios such as airline booking systems often provide suboptimal user experiences, with customers having to navigate complex systems and rules to perform simple tasks. In this blog post, we will explain how to build intelligent agents on top of Confluent, Azure data services and Azure Open AI to deliver real-time insights and help customers conduct business transactions.
