Early AI research drew heavily from neuroscience, using concepts like hippocampal replay and dopamine-based learning to build systems like DeepMind's Atari player. However, the "bitter lesson" emerged, suggesting that massive compute and data with simple methods, like transformers, were more effective than brain-inspired designs. Despite this, the author argues that neuroscience still holds valuable lessons for AI, particularly in understanding the "training signals" or reward functions that drive learning, an area where current AI remains underexplored. AI
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RANK_REASON This is an opinion piece by a named author discussing the historical and potential future relationship between neuroscience and AI.