Vector search, RAG, and Azure AI search
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- Опубликовано: 23 янв 2024
- I recorded myself giving the talk I gave at the SF AI tour.
Slides:
speakerdeck.com/pamelafox/vec...
Demos:
github.com/pamelafox/vector-s...
pamelafox.github.io/vectors-c...
github.com/Azure-Samples/azur... - Хобби
This is one of best video I have watched so far on RAG. Great explanation in simple terms and to the point. please keep making more videos.
This is one of the best talks on applied LLMs on youtube. Thank you.
I've struggled to explain to folks about how vector semantic is different from text search.. finally found somone who explained this so clearly. Thanks, enjoyed this highly informative session.
Nice session, please post more such sessions. got lot of clarity on embedding and search
cone analogy was really good. Thanks.
Thank you so much! I especially appreciate the vector similarity lesson in this video. 👏
Really enjoyed this explanation! Everything covered to really understand what's happening behind the scenes. Thank you! :)
Fantastic. Great work
Amazing Tutorial,
Thank you
Great Video.. very informative. Thanks
Amazing tutorial
very helpful thanks
Very helpful
Thanks a lot
Fantastic
Great Explanation. can you explain about ai enrichments that we can add in ai search especially reading text images from pdfs using ocr
Very nice Content on the video a different approach from others. Are you open to questions at any time?
Ai search + open ai seems to give different answers for same user prompts. Even the chunks returned for answering seem different based on citations even for same prompt. What causes this? Facing issues with consistency of outputs.
I've written up a guide to debugging answer variance here: github.com/Azure-Samples/azure-search-openai-demo/blob/main/docs/customization.md#improving-answer-quality ...that's specific to that repo but is also a general approach for other RAG apps. Does that help?