Think of a generative model as something like “This thing I’m looking at is a red bouncy ball”. Just looking at it you can guess pretty well how much it would weigh if you lifted it, how it would feel if you rubbed it, how it would smell if you smelled it, and how it would bounce if you threw it. Lots of ways to query these models! Powerful stuff!
some predictions that the cortex seems to be bad at
If a model is trained to minimize a loss function L, that doesn’t mean that, after training, it winds up with a very low value of L in every possible case. Right? I’m confused about why you’re confused. :-P
Think of a generative model as something like “This thing I’m looking at is a red bouncy ball”. Just looking at it you can guess pretty well how much it would weigh if you lifted it, how it would feel if you rubbed it, how it would smell if you smelled it, and how it would bounce if you threw it. Lots of ways to query these models! Powerful stuff!
If a model is trained to minimize a loss function L, that doesn’t mean that, after training, it winds up with a very low value of L in every possible case. Right? I’m confused about why you’re confused. :-P