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Understanding Generative AI Dynamics

This chapter explores the mechanics of generative AI, focusing on Markov chains, the attention mechanism, and the transformative impact of the 'Attention is All You Need' paper. It discusses the limitations of generative models, addressing issues like contextual memory, hallucinations, and knowledge cut-offs, while introducing Retrieval Augmented Generation (RAG) as a potential solution. The chapter also compares RAG to fine-tuning, emphasizing the strengths of each approach in enhancing model performance and accuracy.

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