Fine-tuning vs RAG
Practical AI
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Navigating Generative AI and Language Models
This chapter delves into the practical applications of generative AI and large language models, discussing recent survey findings on their use cases and technological foundations. The speakers critically examine the challenges of model evaluation and the misconceptions surrounding fine-tuning versus retrieval augmented generation. Emphasizing simplicity in building applications, they outline the need for clarity in assessing AI performance while reflecting on the complexities of model outputs and user perceptions.
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