hey can we use this for microsoft sharepoint documents also? and if so can we use the same document access based on the users (document level wise access for the bot answers )?
Hello there, continuing to watch the sessions of RAG Deep Dive at more European times 😊. Did you make any evaluation of chunking, vectorization and indexing when using python script vs Integrated vectorization? I mean are there any drawbacks just from looking at answer quality point of view?
I compared those two options in the follow-up talk about AI Search: aka.ms/ragdeepdive/aisearch/slides Check out slide 30 for a comparison. There's definitely a difference in splitting, like the biggest issue of no page numbers for the integrated vectorization splitter, but also they're just different splitting libraries, so you'll see different results.
@@PamelaFox thanks, for this I know. Let me ask in simpler way: is there any difference in the quality of results/answers when using Integrated Vectorization or manual indexing code?
hey can we use this for microsoft sharepoint documents also? and if so can we use the same document access based on the users (document level wise access for the bot answers )?
Hello there, continuing to watch the sessions of RAG Deep Dive at more European times 😊. Did you make any evaluation of chunking, vectorization and indexing when using python script vs Integrated vectorization? I mean are there any drawbacks just from looking at answer quality point of view?
I compared those two options in the follow-up talk about AI Search: aka.ms/ragdeepdive/aisearch/slides
Check out slide 30 for a comparison. There's definitely a difference in splitting, like the biggest issue of no page numbers for the integrated vectorization splitter, but also they're just different splitting libraries, so you'll see different results.
@@PamelaFox thanks, for this I know. Let me ask in simpler way: is there any difference in the quality of results/answers when using Integrated Vectorization or manual indexing code?