Generative AI: Comparing Domain-Specific Finetuning and Retriever-Augmented Generation Techniques

Explore the transformative power of generative AI in business operations and user experiences through an in-depth comparison of Domain-Specific Finetuning (DSF) and Retriever-Augmented Generation (RAG) techniques. Gain insights into how these methodologies are revolutionizing sectors like banking, legal, and medical services. Discover the functions, benefits, and optimal use cases of DSF and RAG, while learning about cutting-edge techniques such as RAFT and comparisons between Llama2-7B and GPT-4. Dive into the RAG pipeline, RAFT training dataset preparation, inference processes, and practical applications of these AI tools to create intelligent, responsive interfaces that anticipate user needs across various domains.

Introduction
RAG
RAG Pipeline
RAFT Training Dataset Preparation
RAFT: Inference
Comparisons
RAFT
How to Use RAFT