I’m not actually sure the scheming problems are “compatible” with good performance on these metrics, and even if they are, that doesn’t mean they’re likely or plausible given good performance on our metrics.
Human brains are way more similar to other natural brains
So I disagree with this, but likely because we are using different conceptions of similarity. In order to continue this conversation we’re going to need to figure out what “similar” means, because the term is almost meaningless in controversial cases— you can fill in whatever similarity metric you want. I used the term earlier as a shorthand for a more detailed story about randomly initialized singular statistical models learned with iterative, local update rules. I think both artificial and biological NNs fit that description, and this is an important notion of similarity.
I’m not actually sure the scheming problems are “compatible” with good performance on these metrics, and even if they are, that doesn’t mean they’re likely or plausible given good performance on our metrics.
So I disagree with this, but likely because we are using different conceptions of similarity. In order to continue this conversation we’re going to need to figure out what “similar” means, because the term is almost meaningless in controversial cases— you can fill in whatever similarity metric you want. I used the term earlier as a shorthand for a more detailed story about randomly initialized singular statistical models learned with iterative, local update rules. I think both artificial and biological NNs fit that description, and this is an important notion of similarity.