Thank you for watching my video, if you have any suggestions please reach out! Join me her www.youtube.com/@RagnarPitla?sub_confirmation=1 If you enjoyed the content and want to stay updated with more insights on AI, innovation, and productivity, don't forget to subscribe to my channel using the link below. Your support means the world to me! Also, let's connect on LinkedIn for even more conversations and updates-I'd love to hear your thoughts and ideas. www.linkedin.com/in/ragnarpitla/
Simply Saying Thankyou for this awesome content! can you do provide the codes . e.g you talking about rag with agentic ai. it will much more helpful for us.
Thank you for the introduction about RAG 🙏 It got me thinking: How does RAG manage data retrieval at scale? Does it rely on pre-configured integrations with specific data sources, or can it dynamically scale to query and adapt to new datasets via APIs or other mechanisms?
MemGPT is one of the many fascinating areas of development in this space- I am still reaserching and learnign how we are using it with some good exampels. thakns for the comment, appreciate it.
@Rakeshkumar-if6oc In the education sector, Memory RAG stands out as a powerful tool for personalized learning. By incorporating a persistent memory component, it can store and retrieve past interactions or facts, delivering coherent and customized outputs. Have you looked at Khanmigo? This capability makes it particularly effective in adapting to each student’s unique progress and learning needs, creating a more engaging and tailored educational experience. Moreover, advanced RAG models such as EMG-RAG (Eigen Memory Graph RAG) and GEM-RAG (Graphical Eigen Memories RAG) take personalization to the next level. These models dynamically retrieve and organize educational content based on individual student performance, preferences, and learning paths, ensuring a highly adaptive and responsive learning environment
Thank you for watching my video, if you have any suggestions please reach out!
Join me her www.youtube.com/@RagnarPitla?sub_confirmation=1
If you enjoyed the content and want to stay updated with more insights on AI, innovation, and productivity, don't forget to subscribe to my channel using the link below.
Your support means the world to me!
Also, let's connect on LinkedIn for even more conversations and updates-I'd love to hear your thoughts and ideas.
www.linkedin.com/in/ragnarpitla/
Really helpful video. Thank you for making it. Already incorporated RAG into my platform. MemGPT is now on my list
Thanks @ianfoster99 - its everywhere and knowing what type works is key going forward.
Thanks for the comment here.
very informative sir thank you
I am glad you found it helpful!- thanks for watching @MohaMmedAnnus
Awesome video and production :)
Thanks for the kind words, I appreciate it.
Thanks a lot, very interesting video
Thanks, glad you found it interesting!
Simply Saying Thankyou for this awesome content! can you do provide the codes . e.g you talking about rag with agentic ai. it will much more helpful for us.
Thank you for the introduction about RAG 🙏
It got me thinking: How does RAG manage data retrieval at scale? Does it rely on pre-configured integrations with specific data sources, or can it dynamically scale to query and adapt to new datasets via APIs or other mechanisms?
Hey Tamara!
That’s a great question!
Yes, it can scale, but the key is to make sure the vector indexing is effective and efficient.
Interesting thoughts about MemGPT's future use cases
MemGPT is one of the many fascinating areas of development in this space- I am still reaserching and learnign how we are using it with some good exampels.
thakns for the comment, appreciate it.
@RagnarPitla In Education sector esp. for personalized learning which RAGs should be used? Memory RAG?
@Rakeshkumar-if6oc
In the education sector, Memory RAG stands out as a powerful tool for personalized learning. By incorporating a persistent memory component, it can store and retrieve past interactions or facts, delivering coherent and customized outputs.
Have you looked at Khanmigo?
This capability makes it particularly effective in adapting to each student’s unique progress and learning needs, creating a more engaging and tailored educational experience.
Moreover, advanced RAG models such as EMG-RAG (Eigen Memory Graph RAG) and GEM-RAG (Graphical Eigen Memories RAG) take personalization to the next level. These models dynamically retrieve and organize educational content based on individual student performance, preferences, and learning paths, ensuring a highly adaptive and responsive learning environment
Thank you Ragnar, I need to learn this for my job. Can you point me toward any training for it?
Thanks! @vaydaMaymeTheo - if possible reach me on LinkedIn, I am not aware of any specific training on RAG but most AI courses will cover.
Search for Learn Microsoft AI videos on TH-cam. Lots of great oversight stuff and coding examples stuff
Sure, thanks