
22 - Shard Theory with Quintin Pope
AXRP - the AI X-risk Research Podcast
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.
00:00
Transcript
Play full episode
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.