Pretraining vs. Fine-Tuning vs. RAG: Choosing the Right AI Approach

What this post added

This post introduces and compares three primary approaches to building AI models: pretraining, fine-tuning, and Retrieval-Augmented Generation (RAG). It details the pros, cons, costs, and time investments associated with each approach, offering guidance on selecting the most suitable method for different project needs. The post also provides real-world examples and discusses hybrid strategies, including the use of techniques like LoRA, QLoRA, multi-hop retrieval, and query decomposition.