Showing results for Category: Semantic Kernel from Semantic Kernel

Customer Case Study: Fujitsu Kozuchi AI Agent Powered by Semantic Kernel Japanese multinational Fujitsu, a pioneer of information and communications technology, has been transforming industries since 1935. With a workforce of 124,000 dedicated professionals across 50 countries, Fujitsu’s mission is to “make the world more sustainable by building t...

Until now, Semantic Kernel Python only allowed for the development of text-based AI applications. However, this is no longer the case, as we have expanded its capabilities to include audio as one of the supported modalities. In this article, I will provide a detailed, step-by-step guide on how to create a chatbot that can both speak to and listen t...

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...

We are pleased to announce the arrival of audio support in Semantic Kernel Python. This new audio functionality will enable you to create more interactive and accessible user experiences. In this blog post, I will detail the new interface, the existing connectors, and provide samples. Please continue reading for more information. Audio-to-Text Th...

Suntory Global Spirits is the spirits division of Suntory Holdings, a multinational beverage and food company based in Japan. Suntory is renowned for its high-quality alcoholic beverages, including premium Japanese whisky, gin, vodka, and other spirits. We'll turn it over to Urko Benito from Suntory to dive into their AI journey with Semantic K...

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...

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 ...