Bringing Memory to your AI Apps with Azure Cognitive Search! | Intro to Semantic Kernel
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- Опубліковано 19 вер 2024
- Want to bring the power of vector search to your AI applications? Curious about the Microsoft memory service powering many of their internal Copilots?
Watch Devis Lucato, principal architect for the Semantic Kernel, walk through Azure Cognitive Search and their latest support for vectors and how you can bring this to your own AI projects!
Read the Semantic Kernel blog post here: devblogs.micro...
And the announcement from Azure: techcommunity....
And the code for the demo: github.com/dlu...
01:00 What is Azure Vector Search?
05:02 Let's see a demo in C#!
14:01 Let's see a demo in Python!
16:30 Concluding thoughts and the future of AI memory
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How are you going to incorporate memory into your AI applications? Leave your thoughts in a comment below!
Great video and great feature. The 'recall' function being the one thing that brings all together! Thanks.
Love that you have python and C# here. Great stuff.
Well it is clear, after this video and reading some documentation , that Hybrid and multi modal embedding, is the way. Thanks for the outstanding video - and work!!
SK integration with Azure cognitive search , for embedding can we use OpenAI endpoint directly or it only works with Azure OpenAI deployment?
I believe you can bring your own vectors to Azure cognitive search! So if you want to use Open AI or any other model provider to create the embeddings, that should work!
You could use HuggingFace Embeddings etc.
Is there any update on when a Python tutorial might come for this for semantic kernel?
Devis shows off the Python example at 14:01 in the video! I'll put a timestamp. The code is already available in the latest pip package!