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22 - Shard Theory with Quintin Pope

AXRP - the AI X-risk Research Podcast

CHAPTER

The Effects of Noise on the Learning Process

The brain and deep learning both have inductive biases that are derived from the presence of noise a randomness in their two optimization procedures. The per neuron level of noise in activation patterns is pretty high much higher than dropout or regularizers we tend to apply to machine learning systems well I guess that depends on how much noise you introduce into a machine learning system like you can introduce more noise than the brain has but the brain has a respect of noise is my point.

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