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Ep 58: Google Researchers Noam Shazeer and Jack Rae on Scaling Test-time Compute, Reactions to Ilya & AGI

Unsupervised Learning with Jacob Effron

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Exploring AI's Test-Time Compute and Innovation

This chapter examines the limitations and potential of test-time computation in AI, emphasizing the cost-effectiveness of large language models compared to traditional methods and human labor. It also highlights the evolving role of AI in mathematical research, exploring its capacity for innovation and generating new findings. The discussion delves into the cultural dynamics that facilitate innovation in AI, drawing parallels between historical breakthroughs and contemporary advancements in technology.

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