AI deep dive: A technical guide to the foundations of search and generative AI

This technical whitepaper takes you deep into the inner workings of generative AI and vector databases. It provides a detailed look at the technical foundations of vector embeddings, generative AI architecture, and how retrieval-augmented generation (RAG) works to provide LLMs with the critical domain-specific knowledge they need.

Highlights

• Demystifying ChatGPT: Different methods for building AI search
• Generative AI architectures with transformers explained from the ground up
• Grounding the parametric knowledge of a generative model with external source knowledge: Retrieval-augmented generation (RAG)
• A comparison of domain-specific knowledge integration into LLMs: Pre-training, fine-tuning, and RAG