Semantic Kernel
The latest news from the Semantic Kernel team for developers
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Announcing Semantic Kernel for Java 1.4.0
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 Vector Store functionality moving out of the experimental namespace and into general availability. This means that the Vector Store in the Semantic Kernel for Java is now stable and ready for production use. You can read more about Vector Stores in the Microsoft Learn do...
Managing Chat History for Large Language Models (LLMs)
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 involves effectively managing chat history and implementing strategies to truncate it when it becomes too large. Key Considerations for Truncating Chat History When truncating chat history, consider the following: Example Scenario Imagine you are developi...
Introducing AWS Bedrock with Semantic Kernel
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 Embeddings, depending on the chosen model. AWS Bedrock AWS Bedrock is a fully managed service offering a serverless experience. It provides access to a diverse range of models from providers like Amazon, Anthropic, AI21 Labs, Cohere, and Meta, among others. If you are a ...
Productive AI at Microsoft Ignite 2024
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 our Semantic Kernel session – Productive AI with Semantic Kernel. During our session you will learn how Semantic Kernel can be used to enhance your current business processes with AI. You will learn about the latest AI innovations to ensure AI enables your employees...
세계로 뻗어갑니다: “G3J Learn Semantic Kernel” 쇼 – 한국어로 배우는 Semantic Kernel!
세계로 뻗어갑니다: “G3J Learn Semantic Kernel” 쇼 – 한국어로 배우는 Semantic Kernel! https://aka.ms/g3jlearnsk/live/ep01 다국어 컨텐츠 관련 수요가 늘어나고 있습니다 다국어로 Semantic Kernel 관련 내용을 방송한 이후, 개발자들 사이에서 현지화한 콘텐츠에 대한 수요가 크게 증가한 것을 확인했습니다. 각 지역의 개발자들이 Semantic Kernel에 대해 더 깊이 배우고자 하는 열정을 보여주었고, 이를 반영하여 저희는 다양한 언어로 더욱 심층적인 학습 콘텐츠를 제공하기로 결정했습니다. 이 관심에 부응하기 위해 그 첫 번째 시작을 바로 한국어로 진행하게 되어 너무 뿌듯합니다. 이 쇼를 통해 한국어 사용자들도 Semantic Kernel을 좀 더 깊이 이해하고 활용할 수 있을 것입니다. "G3J Learn Semantic Kernel" 쇼는? "G3J Learn Semantic Kernel"이라 이름 붙인 이 쇼는 지난 10월 17일부터 공식적으로 시작을 했으며, 매월 첫번째, 세번째 주에 Microsoft Developer Korea 유튜브 채널을 통해 방송합니다. 이 시리즈를 통해 개발자들이 ...
Microsoft.Extensions.VectorData.Abstractions: Now Available
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 learn more about Microsoft.Extensions.AI from our previous post. The introduction of Microsoft.Extensions.VectorData allows Vector Store vendors to implement .NET abstractions through a streamlined, lightweight package. This will make it easier for developers to integra...
Diving into Function Calling and its JSON Schema in Semantic Kernel .NET
Diving into Function Calling and its JSON Schema in Semantic Kernel .NET Function-calling is one of the most exciting features of certain Large Language Models (LLMs), enabling developers to execute code directly in response to user queries. In Semantic Kernel, we streamline the process by allowing you to use built-in plugins or integrate your own code with ease. Today, we’ll explore how Semantic Kernel creates a function-calling JSON schema—a critical component that helps the model determine which function to invoke in various contexts. For those unfamiliar, function-calling refers to running local code, oft...
Process Framework gets Python support and more!
As we continue to empower developers in embedding AI into their workflows, we are thrilled to announce significant updates to the Microsoft Semantic Kernel's Process Framework. Building on our introductory blog, we’ve made enhancements that further streamline business process automation and AI integration and help you to be successful with the Semantic Kernel Process Framework even more quickly. What’s New? Embrace the Future of AI-driven Processes As organizations strive to enhance efficiency and decision-making, the integration of AI into business processes is more...
AI Digital Transformation Discovering Rome’s hidden treasures with an AI virtual assistant and Semantic Kernel
Today we want to highlight a customer story featuring Semantic Kernel here: Discovering Rome’s hidden treasures with an AI virtual assistant - Source EMEA On a sunny Monday morning in late September, a river of travelers flowed slowly through the Piazza della Rotonda. The focal point of the piazza is the Pantheon, the nearly 2,000- year-old temple to all the Roman gods, and is one of the city’s most popular landmarks. Fronted by imposing rows of Corinthian columns, it merits the attention it draws. Nearly every visitor slowed down for a photo or selfie, vainly attempting to capture its perfect proportio...