Showing results for Category: Announcement from Semantic Kernel

We are thrilled to announce the General Availability (GA) of our Memory packages for .NET, Java, and Python! The Semantic Kernel team and our partners have been working hard to allow you to quickly connect to vector stores and make it easy for you to do embeddings and data retrieval between stores. Transforming Data Management with Vector Stores...

We are excited to announce the General Availability (GA) release of Filters for our .NET and Python Semantic Kernel! This vital enhancement strengthens the control and visibility developers have when running functions, ensuring responsible AI practices are instilled from the ground up. Filters not only improve security but also contribute to buildi...

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. This i...

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...