Showing results for Category: Announcement from Semantic Kernel

Today we're excited to feature the Elastic team to share more about their Semantic Kernel Elasticsearch connector. Read the entire announcement here. I'll turn it over to Srikanth Manvi to dive into it. In collaboration with the Microsoft Semantic Kernel team, we are announcing the availability of Semantic Kernel Elasticsearch Ve...

We are thrilled to announce the General Availability (GA) release of the OpenAPI package for Semantic Kernel, available for both .NET and Python! With this significant milestone, developers can easily integrate existing APIs as plugins, enhancing the capabilities of their AI agents while making them more versatile in real-world applications. Why O...

As the landscape of AI continues to evolve, meeting users where they are is vital. We want to spotlight the newly released Microsoft 365 Agents SDK and its seamless integration with Semantic Kernel. This powerful combination empowers developers to create robust AI agents capable of operating across multiple channels, engaging users wherever they ar...

Microsoft’s agentic AI frameworks, Semantic Kernel and AutoGen are deeply collaborating to provide the best-in-class agentic developer experience. With Semantic Kernel’s enterprise ready AI capabilities, customers can already use and get support for building agent applications and, moving forward, we’ll align the multi-agent runtime in AutoGen (cal...

Functions are a key component of Semantic Kernel. As an AI Orchestrator, Semantic Kernel coordinates function execution together with Large Language Model (LLM) inference to allow the model return better responses or take action. Semantic Kernel groups related functions as plugins and provides capabilities to generate plugins from native code (e.g....

Hello Java AI developers! We are announcing the 1.4.0 release of the Semantic Kernel for Java. Please see the full changelog here. You can find our updates on our GitHub repository and the artifacts on Maven Central. What's New in Semantic Kernel for Java 1.4.0? Vector Store Functionality Goes GA The central focus of this release is for the V...

Large Language Models (LLMs) operate with a defined limit on the number of tokens they can process at once, referred to as the context window. Exceeding this limit can have significant cost and performance implications. Therefore, it is essential to manage the size of the input sent to the LLM, particularly when using chat completion models. Th...

One of the principal features of Semantic Kernel is its ability to integrate various AI services seamlessly. We are pleased to announce that this capability now extends to AWS Bedrock. With AWS Bedrock, you can access foundational models such as the Amazon Titan models. The new connector supports Chat Completion, Text Generation, and Text Embedd...

Microsoft Ignite 2024 is almost here!  This year the in-person conference will be held in Chicago Illinois USA November 19th - 22nd and the Semantic Kernel team will be on site answering questions and sharing best practices and if you can't attend in-person you can also sign up for free and watch it online or On Demand. I’m thrilled to announce ...

We are thrilled to announce the launch of Microsoft.Extensions.VectorData for .NET! Our collaboration with the .NET team since the debut of Semantic Kernel has resulted in a powerful new feature that aligns with the best practices of both current and upcoming .NET releases.  This is the second new package as part of this collaboration.  You can lea...