Unleash the Power: Retrieval-Augmented Generation for AI

Unleash the Power: Retrieval-Augmented Generation for AI

In this video, we explore the power of retrieval-augmented generation for AI. Learn how this technology can revolutionize the field of artificial intelligence!

RAG stands for Retrieval-Augmented Generation. It's a technique used to improve the accuracy and reliability of large language models (LLMs) like me. Here's the gist:

LLMs are great: They can generate text, translate languages, and answer your questions in creative ways.
But they have limitations: LLMs are trained on massive amounts of data, but they can't access real-time information or the latest updates. This can lead to factual errors.

RAG fixes this by:
Looking things up: When you ask a question, RAG consults an external knowledge base like a giant encyclopedia to find relevant information.
Combining knowledge: The LLM then combines this retrieved information with its own knowledge to craft a response that's both creative and factually on point.
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Chapters
00:00:00 Introduction to Large Language Models
00:01:15 Challenges
00:02:29 Explaining RAG
00:03:42 Benefits of RAG
00:04:52 Real-World Applications of RAG
00:05:59 Future of RAG
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