Semantic Kernel

The latest news from the Semantic Kernel team for developers

GUEST POST: How to build a Kernel Memory connector and use Elasticsearch as vector database

This article will help readers to create their own connectors for Kernel Memory. It will introduce fundamental concepts of Kernel Memory and Elasticsearch and will show some practical use cases of how to use the interface IMemoryDb. The complete source code for the connector is located in the GitHub repository FreeMindLabs.KernelMemory....

GUEST POST: Semantic Kernel and Weaviate: Orchestrating interactions around LLMs with long-term memory

The Emerging LLM Stack In a recent interview, the co-founder of Cohere stated - “For the first time in the history of our planet, we have machines that we’ve created that can use our language.” A bold statement indeed, but it couldn’t be more accurate and we’ve all witnessed the incredible power of said machines. It would be an ...

AI tooling for Java developers with SK

Every system needs to be able to add AI to its workflow to empower the users to complete their task much faster.  The Semantic Kernel team and community have been working hard to create a Java based kernel to support Java developers to unleash AI into their apps.  I will walk you through this journey below. We will review the following ...

Announcing Semantic Kernel integration with Azure AI Search (formerly Azure Cognitive Search)

(image) We're excited to announce integration of Azure AI Search with Semantic Kernel, available in both C# and Python. This integration follows the existing Semantic Memory architecture, making it incredibly easy for developers to add memory to prompts and plugins. This integration unlocks the following key benefits...

Semantic Kernel + Qdrant = Persistent Memories Powered By Open Source

(image) (image) Interview with Qdrant CEO and co-founder Andre Zayarni Semantic Kernel now works seamlessly with the open-source vector database Qdrant — just launch an instance of Qdrant on Azure with one click and you're good to go. You can learn more about Qdrant's history in this interview with the CEO and co-founder, Andre Zayarni...

The Power of Persistent Memory with Semantic Kernel and Qdrant Vector Database

(image) A key component of leveraging machine learning large languages models (LLM) for natural language processing (NLP) in applications for chat search like ChatGPT, ranking and recommendation engines, anomaly detection, and semantic search is the ability to leverage massive amounts of unstructured data for search. But where would we ...