RAG vs. Fine Tuning

Join Cedric Clyburn as he explores the differences and use cases of Retrieval Augmented Generation (RAG) and fine-tuning in enhancing large language models. This video covers the strengths, weaknesses, and common applications of both techniques, and provides insights on how to choose between them using machine learning and natural language processing principles

#AI #LargeLanguageModels #FineTuning #RAG #ReinforcementLearning #MachineLearning #NaturalLanguageProcessing

[Kk-edgr]

Thank you for the clarification, I had this question in mind last week, and I am glad that you have provided the answers I need.

[FauziFayyad]

I have just watched the 1 years ago, then it updated today. Amazingg 🎉

[educationrepublic]

Love IBM's short and sharp explainers! Thank you for an excellent video once again :)

[yusufersayyem]

35 minutes after downloading the clip, I received a notification, perhaps due to the weak internet in my country.... Finally, I would like to thank you sir for this wonderful explanation

[florentromanet]

I wanted to scream "WHY NOT BOTH⁉️) until 7:35 😂

[johannvgeorge]

Thank you for this helpful video🙂. Could you please explain the implementation of how we can update the RAG system with the latest information?

[bharathYerukola-gtvt]

Make a vedio on termonolgioes are often used on ai like benchmark and art of the state and etcc ❤

[bharathYerukola-gtvt]

Nice vedio and also make a vedio on neural networks in deep like how neiral network is interlinked with deep learning and machine learning and what is actaully neuarl network and architecuture and why architectute is inporatnt fir neural networks and what is neural network actalkuy like a technique or mathematical expression or anything else so make a vedio on all these

[Criszusep]

Euro 2024 World Championship. Nice... of course the LLM could't give a response 😂

[shrutisingh]

can u make a video about reinforcement learning and performance evaliation of llm models?

[CalvHobbes]

Thank you, this is very useful. I'm curious about how the volume of data might affect the choice of FT vs RAG. If we tune the model again with the new data, would it become much larger over time? On the other hand, if we use RAG, would the restrictions on context length hold us back (i.e. if we don't want a very expensive model)?

[mark-lqrk]

Thank you for the fascinating presentation. Assume certain conditions are similar, how would the cost of rag and fine-tuning differ?

[ggggdyeye]

sir can you tell me how to make the vectorstore and store it in a specific file to use it every time.

[choofficial]

I thought the retriever was on the far right, and llm in the middle of both, was I wrong, partially, is that schematic representation doesn't fathom all of the architecture, I'd like to go deeper on that matter.

[Siapanpeteellis]

What happens to a model when it is fine-tuned? do you use a database for RAG?

[hiwifi-s]

Using “Fine Tuning”, then machine ( accounting software) can be a bookkeeper to prepare financial records for …?

[GG-uzus]

I would like to see a real app that is in production with RAG and fine-tuning.

[einjim]

So, You are all told to wear your watch on your right hand right?!

[atanasmatev]

Large Language model is "LMM"?

[SandraGarcia-tk]

White Deborah Wilson Susan Garcia Cynthia