Fine-tuning updates model weights; retrieval adds external info without retraining.
Helps choose the right tool to adapt an AI system.
Fine-tune GPT on legal cases vs. plug in a legal database via retrieval
Fine-tuning = always better; retrieval = always cheaper
Retrieval-Augmented Generation (RAG) combines LLMs with vector search or DBs.
Use LangChain to build a RAG pipeline on your docs.
Fine-tuning is expensive; retrieval requires great source quality.
Persona
- Engineers
- Practitioners
Why it Matters
Helps choose the right tool to adapt an AI system.
Common Misconceptions
Fine-tuning = always better; retrieval = always cheaper
Try It Yourself
Use LangChain to build a RAG pipeline on your docs.
Cautions
Fine-tuning is expensive; retrieval requires great source quality.
Definition
Fine-tuning updates model weights; retrieval adds external info without retraining.
Real-World Examples
Fine-tune GPT on legal cases vs. plug in a legal database via retrieval
Technical Glimpse
Retrieval-Augmented Generation (RAG) combines LLMs with vector search or DBs.
