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Ryan Greenblatt - Solving ARC with GPT4o

Machine Learning Street Talk (MLST)

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Exploring Agency in Neural Networks

This chapter examines the parallel and contrasting elements of agency between human cognition and neural networks, particularly focusing on language models. It discusses the spectrum of agency, the nature of learning, and the limitations of AI in replicating human-like reasoning. The conversation emphasizes the evolving capabilities of AI systems while reinforcing their status as tools rather than fully autonomous agents.

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