AWS re:Invent 2023 - Use RAG to improve responses in generative AI applications (AIM336)

[@codeinrust]

Most of the Amazon Bedrock presentations were not very well done, but this one is pretty easy to understand. Thanks for speaking clearly and knowing the topic you're talking about.

[@chrismiller3591]

I agree with the other commenters that this video is exceptional. You two are very good presenters. This was just enough depth covering the right surface area of these products and features. I absolutely love the Amazon KB for my use case, and I love how much of the process Amazon manages for me, which allows me to spend less time developing and more time selling.

[@amazonwebservices]

Thank you so much for your kind words! 😊

[@chatchaikomrangded960]

The best talk of RAG. easy to expain why they build KM for Bedrock.

[@mithunim]

What is KM? Did you mean KB?

[@sandeepreddy4178]

One of the best videos Ive seen which covered every aspect of building GenAI applications with RAG

[@saisantoshv]

Thank you Mani and Ruhaab for an excellent overview, example use case and links to the sample code. I appreciate it a lot.

[@bayyarajeshyadav3661]

Please post GitHub repository link as mentioned in the talk. @Mani & @Ruhaab.

[@curlyworlyscape9120]

So will presented. Great job!

[@sachinwagh6452]

Excellently explained. Thanks for the insightful presentation.

[@amazonwebservices]

It's our pleasure! 😀

[@parth191079]

Amazing talk!! Learned so much!! ❤❤

[@juangabriel2559]

excellent presentation

[@AWSEventsChannel]

Thank you for your feedback. 🙌

[@jampalanaresh5318]

How to improve latency issue in response in this RAG model approach using aws bedrock knowledge based Evnen though i created small pdf file having 10pages its giving response in 5 to 7 seconds I want with in 1 second in response what i do ? Please help...

[@awssupport]

Hi there. 👋 Our scope for tech support is limited on this platform. You can get some assistance from our community of experts on re:Post: go.aws/aws-repost. 🤓 If you still need help, check out these options: go.aws/get-help. 🤝 ^RW

[@MrJodyfleck]

I got as far as 43:00 when trying this out - knowledge base created, synched and status = ready. Go to test it though and there are no models available to me. I able to 'retrieve' so I know the data sync and embeddings were successful, but I cannot use that to generate anything from an FM. Amazon Q "can't answer my question". Stuck

[@awssupport]

Sorry to see the trouble! This doc will help clarify more context for using RAG with Amazon Q: go.aws/3TsFWbw. For further support on technical questions, I'd also recommend engaging our community of experts on re:Post: go.aws/aws-repost. ⬅️ ^AD

[@JimmySingh-o1k]

Using the retrieveAndGenerate API i am unable to get the cited references.

[@awssupport]

Oh no! Sorry to hear about this trouble. This would be a great question to post over at re:Post where our community of experts can chime in & share their knowledge: go.aws/aws-repost. 🤝 ^AK

[@JimmySingh-o1k]

@@awssupport Posted the question but not getting any response

[@awssupport]

Hello! Please understand that these posts are answered in the order they're received. It can take time before our collective of engineers reach out. In the meantime you may find this doc helpful: go.aws/3y5mVnj. 📝 ^AR

[@suran-kr2zr]

this is great but it is still cumbersome and far from production ready, it would be cool if an endpoint would be generated automatically to call it from an app directly without having to build another customer langchain app on top of it

[@GoonCity777]

don't see myself making a new LLAMA for the #4th option in the beginning

[@doochi2532]

51:50

[@stephengardner5746]

"uh" count overload.

[@doochi2532]

51:49