Scott Alexander discusses recent research unifying predictive coding in the brain with backpropagation in machine learning, exploring its implications for AI and neuroscience.
Longer summary
Scott Alexander discusses a recent paper and Less Wrong post that unify predictive coding, a theory of how the brain works, with backpropagation, an algorithm used in machine learning. The post explains the significance of this unification, which shows that predictive coding can approximate backpropagation without needing backwards information transfer in neurons. Scott explores the implications of this research, including the potential fusion of AI and neuroscience into a single mathematical field and possibilities for neuromorphic computing hardware.
Shorter summary