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Ep 47: Chief AI Scientist of Databricks Jonathan Frankle on Why New Model Architectures are Unlikely, When to Pre-Train or Fine Tune, and Hopes for Future AI Policy

Unsupervised Learning

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This chapter explores the intricacies of AI model training, fine-tuning, and prompt engineering, drawing on experiences from a diverse customer base. The discussion highlights lessons learned, new product launches, and the importance of creative team motivation in the context of sensitive AI applications.

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