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
My Links 🔗
👉🏻 Subscribe (free): https://www.youtube.com/technovangelist
👉🏻 Join and Support: https://www.youtube.com/channel/UCHaF9kM2wn8C3CLRwLkC2GQ/join
👉🏻 Newsletter: https://technovangelist.substack.com/subscribe
👉🏻 Twitter: https://www.twitter.com/technovangelist
👉🏻 Discord: https://discord.gg/uS4gJMCRH2
👉🏻 Patreon: https://patreon.com/technovangelist
👉🏻 Instagram: https://www.instagram.com/technovangelist/
👉🏻 Threads: https://www.threads.net/@technovangelist?xmt=AQGzoMzVWwEq8qrkEGV8xEpbZ1FIcTl8Dhx9VpF1bkSBQp4
👉🏻 LinkedIn: https://www.linkedin.com/in/technovangelist/
👉🏻 All Source Code: https://github.com/technovangelist/videoprojects
Want to sponsor this channel? Let me know what your plans are here: https://www.technovangelist.com/sponsor
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