Microsoft announced a range of new features for its tools at its annual Ignite conference, with new ways to customize Microsoft 365 and extra AI facilities for Azure.

The first major announcement related to Copilot for Microsoft 365. which, according to Microsoft, 70 percent of respondents to a survey said improved productivity. Copilot is AI-based and uses large language models (LLMs) to work with customer data in the Microsoft Graph and the Microsoft 365 apps. Microsoft describes it as helping "unleash creativity, unlock productivity and uplevel skills".

Alongside the customer-focused extras for Copilot for Microsoft 365 announced at Ignite, Microsoft announced Copilot Studio, a low-code tool designed to customize Microsoft Copilot for Microsoft 365. The tool is aimed at AI teams, and Microsoft says it works with connectors, plugins and GPTs to give IT teams a way to steer Copilot to the best data sources for specific queries.

Copilot Studio can be used to customize existing copilot features, or to create standalone copilots. It is based on Power Virtual Agents (and other Microsoft Power Platform technologies) and integrates with Microsoft Azure OpenAI Studio, Azure Cognitive Services, Azure Bot Service, and other Microsoft conversational AI technologies.

The second announcement of interest to developers related to improvements to Azure AI. A new Model-as-a-Service feature that was pre-announced at Microsoft Build is aimed at pro developers who want to integrate the latest AI models, such as Llama 2 from Meta and upcoming premium models from Mistral, and Jais from G42, as API endpoints to their applications. They can also customize these models with their own data without needing to worry about setting up and managing the GPU infrastructure, helping eliminate complexity.

Microsoft also showed off the preview of Azure AI Studio, which can be used to build your own copilots, train your own, or ground other foundational and open models with data that you bring. Microsoft says Azure AI Studio provides a suite of AI tools and models, including sophisticated hybrid and semantic search to power retrieval augmented generation (RAG) applications. Azure AI Studio also has a comprehensive model catalog, including the latest multimodal models like GPT-4 Turbo with Vision and open models like Falcon, Stable Diffusion, and the Llama 2 managed APIs. Developers can also integrate structured, unstructured, and real-time data using Microsoft Fabric.

Another Azure improvement that is now generally available is Vector Search, so organizations can generate highly accurate experiences for every user in their generative AI applications. Vector search in Azure AI Search can be used to store, index, query, filter and retrieve your AI data. It comes with client libraries for Python, JavaScript, .NET, and Java, and the latest version has new features including an improved semantic ranker, multi-vector queries, Exhaustive K-Nearest Neighbors (KNN) and pre-filtering.

More Information

Microsoft Ignite Website

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