Step by step implementation of Question and answer bot using large language models and langchain: kzitem.info/news/bejne/wKt62nmEsIeEfXY
@starlord7526
5 ай бұрын
i watched bunch of videos about RAG but none explained like you did with flowchart. Crystal clear
@shanthiagarajan5560
6 ай бұрын
Really Very good presenation. Thank you for such a wonderful presentation and explanation.
@AshutoshTripathi_AI
6 ай бұрын
Thank you
@abhijeetsinha1803
5 ай бұрын
Thanks for explaining so nicely. Thank you for such a wonderful presentation and explanation.
@vinayakganji5017
7 ай бұрын
Simply Awesome
@AshutoshTripathi_AI
7 ай бұрын
Thank you dost 🙏
@teetanrobotics5363
4 ай бұрын
One of the best explainations professor. Watched the whole video. Thank you so much. Could you please explain more cutting edge AI research papers ?
@nasamind
2 ай бұрын
Nice
@AshutoshTripathi_AI
2 ай бұрын
Thank you
@priyanshusingh_0716
9 ай бұрын
Thank you sir ✌
@AshutoshTripathi_AI
9 ай бұрын
Welcome 😊
@geetatripathi9335
9 ай бұрын
Good
@AshutoshTripathi_AI
9 ай бұрын
Thank you 🙏
@ChetnaTripathi
9 ай бұрын
🎉🎉
@sambotsector101
5 ай бұрын
THANK YOU!!
@samarthinani3870
7 ай бұрын
Great video, Ashutosh. For a given query, how would you know if its better answered using RAG or the original LLM?
@AshutoshTripathi_AI
7 ай бұрын
Indeed a good question. In the Generative AI world, response evaluation is a big challenge. Conceptually it is right to say that RAG will have better performance on customised data as it has better understanding through vector db knowledge base. LLM are more generic and may not be specific to your query. But if LLM has knowledge of your specific dataset then it will also perform similarly. However, evaluation needs a lot of research in this field.
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