An Introduction to RAG - Part of the Free Ollama Course

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In this video from the free Ollama Course, we look into the world of Retrieval Augmented Generation (RAG), a powerful technique to overcome common limitations of AI models. Learn how RAG can help AI access recent information and specialized knowledge, making it an invaluable tool for developers and businesses alike.

## Key topics covered:

- Limitations of current AI models

- Introduction to RAG (Retrieval Augmented Generation)

- Document preparation and text extraction challenges

- Chunking strategies for effective information retrieval

- The role of embeddings in semantic understanding

- Vector databases and their importance in RAG systems

- Building effective prompts with retrieved information

This video is part of our free Ollama course, designed to teach you how to run AI models locally on your computer or in the cloud. Whether you're new to AI or looking to expand your knowledge, this in-depth exploration of RAG will provide you with practical insights and techniques to enhance your AI implementations.

Join us as we uncover the potential of RAG and learn how to make AI models more knowledgeable about recent events and specialized information. Stay tuned for upcoming videos where we'll dive deeper into RAG components and build a complete RAG system from scratch!

#ArtificialIntelligence #RAG #MachineLearning #Ollama #AITutorial

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00:00 - AI Issues
01:01 - Introduction
01:55 - Consider the Doc Type
03:59 - Get the Text Out
04:46 - Chunk the Text
05:13 - Embedding
06:09 - Vector Stores
07:13 - Querying the db

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This channel is hidden gem. Really appreciate the content!

brunocarvalho

This video is just poetry. Wonderful and clear explanation about RAG systems. The whole playlist is wonderful, I would even pay for such clear no-bullshit content! Thank you for the wonderful work, Matt! Appreciate it!

clintonmusix

Thank you for these. One of the best channels out there on how to use LLMs/Ollama for private data.

chansalyker

The size doesn't matter pixelating was a nice touch.

eric

i love the fact that you had a history lesson about pdf and printers that required Fonts . also i love you to know that i dont like youtubers who talk instead of coding and showing it on the code editor but somehow i love how you describe the lessons. maybe its your voice or your experience whatever it is, its unique to you. Thx Matt🌹

vfxmaster

This is awesome Matt! Thank you so much! Will be doing ALL OF THIS TONIGHT xD

BORCHLEO

This is great I'm planning on adding RAG to my project in the next 2-3 weeks

pcriged

Hi Matt Williams, thanks for the video. just a suggestion. I think a flow diagram to show how the RAG works at a high level can better explain the concept. I have known how RAG works and while watching the video and put myself in a situation which i never known RAG before, it would still confuse me how RAG works.

tspang

btw re pdf, "the" (proposed) method to "do it" is using a vision model instead of OCR

themaxgo

Great explanation. Thanks.
I recently used Excel's Get Dara from a folder using power query, which did a great job extracting data from a hundred bank statements. Question: If i may, are Excel files okay, or is convering to CSV better? Cheers.

stevegannon

As always, great channel!

Loved the explanation, though not using it explicitly for building a rag database, i've been using PyMuPDF to parse PDFs with various NLP libraries and LLMs and I've been receiving meh results.

After your explanation, im considering if it would make more sense to first convert the PDFs to text (i dont have access to the original text), and then try to use them.... either way... thanks!

JBLU

How do you take care of the indices on the embeddings column to make the query fast? I am working on a similar problem and want to build a RAG solution for some of my use case. I am really looking forward to the next part of it. Hope it comes out soon.

PalashVijayO

I want to do this with my bank statements so I can ask things like "How much did I spend on Pizza Hut last year".

marcusk

matt can ollama do prompt caching? like claude and gemini do? they said it can fasten the Inference by more than half, rather than rag...

NLPprompter

Keep it coming! Would also loves video of books or courses on this type of learning in detail to augment your videos. Maybe a paid course one day too!

pdevito

im in the middle on of training my llama 3.1 model to right now and i stopped to watch this vidto.

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