This podcast offers a comprehensive guide to AI engineering, based on the book "AI Engineering: Building Applications with Foundation Models" by Chip Huyen. The focus is on building and scaling generative AI systems. It covers the end-to-end process of adapting foundation models for real-world applications, explaining fundamental concepts like model architectures, scaling, and the training process, including supervised and preference finetuning. The podcast highlights critical aspects like evaluation methodologies, prompt engineering best practices, and inference optimization, while also addressing crucial topics such as data quality, synthesis, and processing. Furthermore, it explores the architecture of AI applications and the importance of user feedback in refining these systems.

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