CAG vs RAG: Which One is Right for You?
Description
In the early days of LLMs, context windows, which is what we send them as text, were small, often capped at just 4,000 tokens (or 3,000 words), making it impossible to load all relevant context.
This limitation gave rise to approaches like Retrieval-Augmented Generation (RAG) in 2023, which dynamically fetches the necessary context.
As LLMs evolved to support much larger context windows—up to 100k or even millions of tokens—new approaches like caching, or CAG, began to emerge, offering a true alternative to RAG...
►Full article and references: https://www.louisbouchard.ai/cag-vs-rag/
►Build Your First Scalable Product with LLMs: https://academy.towardsai.net/courses/beginner-to-advanced-llm-dev?ref=1f9b29
►Master LLMs and Get Industry-ready Now: https://academy.towardsai.net/?ref=1f9b29
►Our ebook: https://academy.towardsai.net/courses/buildingllmsforproduction?ref=1f9b29
►Twitter: https://twitter.com/Whats_AI
►My Newsletter (My AI updates and news clearly explained): https://louisbouchard.substack.com/
►Join Our AI Discord: https://discord.gg/learnaitogether
United States
