This is from the Amazon description of @GaryMarcus new book, though I'm guessing there's a high probability these are not precisely his words. Nonetheless, the same argument pops up in other places too.
-
-
Indeed. E.g. we cannot solve intelligence under the feedforward networks paradigm which seems particularly suited for motor control but not for reasoning and general problem solving. NNs with supervised learning based on 'output' values are nowhere to be seen in the brain
-
oh, i think the brain does some supervised learning, even if we aren’t sure yet of the mechanisms.
- 4 more replies
New conversation -
-
-
Deep learning researchers will certainly agree that none of the specialized brain components (i.e. hippocampus, cortex, cerebellum, etc) have not been implemented in artificial form. In fact, it's an unusual track to try to replicate a brain component given how little we know.
-
The more common approach is to design a network architecture and then argue backward as to why it replicates a specific brain function. This is what DeepMind has argued with the PFC and meta-learning.https://deepmind.com/blog/article/prefrontal-cortex-meta-reinforcement-learning-system …
End of conversation
New conversation -
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.