4 ms·
And if the brain is overfitted, how can it generate out-of-distribution samples? Seems like wildly cyclical reasoning.
by toxik 5y ago
And if the brain is overfitted, how can it generate out-of-distribution samples? Seems like wildly cyclical reasoning.
- boardwaalk 5y agoHow can computers calculate more accurately than the human brain but also have PRNGs or even true hardware RNGs?
- toxik 5y agoBut that’s the thing, it’s NOT random. It’s just unlikely scenarios. Dreams still follows the general model of the world.
- DavidSJ 5y agoThe brain is a lot of different components working together. Perhaps the bits which do statistical learning are functionally distinguishable from the bits which generate permutations on the data. (This is in fact how modern neural network training often works: start with a set of 50,000 images, run them through a bunch of permutations — translation, rotation, lighting changes, etc. — and produce a training set of 1 million images which yield better generalization when trained against.)
- deleted 5y ago[deleted]
- canjobear 5y agoYou'd have to posit multiple models in the brain. For example, one which simulates the world (call it the "world model"), and one which determines the best actions to take in the world (call it the "policy"). The policy might be overfit even while the world model is not. In dreaming, you are drawing samples from the world model and using them to train the policy.
- fennecfoxen 5y agoI can't remember what it was, but I've read something within the past 3 months, possibly on these pages, which very much suggested human cognition being derived from a series of overlapping partial models of the world, similar to what you described (but with more simulation models in that layer)
- slaymaker1907 5y agoMaybe something like turning up the exploration vs exploitation parameter for tree search AI algorithms.