This project is currently in active development and may contain breaking changes. Updates and modifications are being made frequently, which may impact stability or functionality. This notice will be ...

To perform semantic searches, you must first generate embedding vectors from a model, store them in a vector database, and then query the embeddings. You'll create a database, populate it with sample ...

Tools like Semantic Kernel, TypeChat, and LangChain make it possible to build applications around generative AI technologies like Azure OpenAI. That’s because they allow you to put constraints around ...

As developers look to harness the power of AI in their applications, one of the most exciting advancements is the ability to enrich existing databases with semantic understanding through vector search ...

Microsoft has updated its Azure AI Search service to increase storage capacity and vector index size at no additional cost, a move it said will make it more economical for enterprises to run ...