Showing results for Tag: Microsoft Semantic Kernel from Semantic Kernel

Leap Forward with Modern AI using Microsoft 365 Agents SDK and Semantic Kernel Today we’re featuring a guest author, Arafat Tehsin, who’s a Microsoft Most Valuable Professional (MVP) for AI. He’s written an article we’re sharing below, focused on how to Leap Forward with Modern AI using Microsoft 365 Agents SDK and Semantic Kernel. We’ll turn ...

The Journey to Multi-Agent Innovation At ServiceNow, we embarked on an ambitious journey to redefine how AI systems collaborate in enterprise environments. Through our partnership with Microsoft, we set out to create something beyond traditional integration – a true multi-agent system across platform that could work effectively alongside human t...

Today I want to welcome back Arafat Tehsin, who’s a Microsoft Most Valuable Professional (MVP) for AI. He’s written an article we’re sharing below, focused on Building Multi-Agent Systems with Multi-Models in Semantic Kernel. We’ll turn it over to Arafat to share more! Imagine running a restaurant. Each of your team member, from the chef to ...

AI Connectors in Semantic Kernel are components that facilitate communication between the Kernel's core functionalities and various AI services. They abstract the intricate details of service-specific protocols, allowing developers to seamlessly interact with AI services for tasks like text generation, chat interactions, and more.   ...

Today the Semantic Kernel team is happy to welcome back our guest author, Akshay Kokane. We will turn it over to him to dive into his recent Medium article on Semantic Kernel. As we advance towards an Agentic Approach in the AI world, I would like to share my insights on how Semantic Kernel can assist in building AI agents and leveraging existin...

Global Expansion – "G3J Learn Semantic Kernel" Show – A Deep Dive in Korean! Localization Increases Demand Following the success of this multi-language delivery, we quickly noticed a surge in demand for localized content. Developers from different parts of the world have expressed interest in diving deeper into Semantic Kernel, and we couldn’t ...

ONNX GenAI Connector for Python (Experimental)  With the latest update we added support for running models locally with the onnxruntime-genai. The onnxruntime-genai package is powered by the ONNX Runtime in the background, but first let’s clarify what ONNX, ONNX Runtime and ONNX Runtime-GenAI are.  ONNX ONNX is an open-source format for AI model...

How to use Elasticsearch Vector Store Connector for Microsoft Semantic Kernel for AI Agent development Today we're excited to feature the Elastic team to share more about their Semantic Kernel Elasticsearch Vector Store connector for Microsoft Semantic Kernel. Read the entire announcement here. I'll turn it over to Srikanth Manvi and Florian Bernd...

We previously introduced observability within the Semantic Kernel. For further insights, please refer to our previous blog post, and you can also explore our learn site for additional details. To summarize, observability is an essential aspect of your application stack, particularly in today's landscape where AI plays a significant role in numer...

Semantic Kernel (SK) 是由微软开发的一款开源开发工具包，旨在帮助开发者和企业利用最新的人工智能技术构建更智能和复杂的AI驱动解决方案，例如检索增强生成 (RAG) 和智能体 (Agent)。 核心概念 内核（Kernel） 您可以将SK的内核视为一个容器，该容器包含您所需的所有与AI相关的组件，如提示语模板、AI服务和插件。如果将所有的服务和插件提供给内核，则AI会根据需求自动使用它们。SK还提供多项企业级功能，使您可以保证您的AI符合安全要求且在部署后能够持续监控AI的表现。 提示语（Prompt Engineering） 提示语在使用大型语言模型中至关重要。优质的提示语能够显著提升用户体验。SK通过提示语模板（template）的方式来实现自然语言与...