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Safety in Numbers: Keeping AI Open

a16z Podcast

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Challenging Model Scaling Assumptions in AI Research

This chapter explores the early concepts related to foundation models in AI, emphasizing the importance of data in relation to model size. It highlights key insights from the Chinchilla paper, advocating for a balanced approach to compute, model size, and data to improve AI training strategies.

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