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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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Navigating AI Policy and Responsibility

This chapter emphasizes the vital role of community engagement and ethical considerations in AI policy discussions. It highlights the importance of trust, transparency, and cautious innovation, particularly in sensitive areas like law enforcement and healthcare. The authors advocate for a collaborative approach in shaping AI's future while showcasing unique AI tools and opportunities at Databricks.

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