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

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Date: 1.8.2018

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