I would think that reproducing cortical learning would require a good deal of work and experimentation, and I wouldn’t expect working out the “algorithm” to happen all at once
I agree; working out the “algorithm” is already happening, and has been for decades. My claim instead is that by the time you can get the algorithm to do something importantly useful and impressive—something that LLMs and deep learning can’t already do much cheaper and better—then you’re almost at ASI. Note that we have not passed this threshold yet (no offense). See §1.7.1.
or to be vastly more efficient than LLMs (since they are optimized for the computers used to simulate them, whereas cortical learning is optimized for the spatially localized processing available to biology
I think people will try to get the algorithms to work efficiently on computers in the toy-model phase, long before the algorithms are doing anything importantly useful and impressive. Indeed, people are already doing that today (e.g.). So in that gap between “doing something importantly useful and impressive” and ASI, people won’t be starting from scratch on the question of “how do we make this run efficiently on existing chips”, instead they’ll be building on all the progress they made during the toy-model phase.
I agree; working out the “algorithm” is already happening, and has been for decades. My claim instead is that by the time you can get the algorithm to do something importantly useful and impressive—something that LLMs and deep learning can’t already do much cheaper and better—then you’re almost at ASI. Note that we have not passed this threshold yet (no offense). See §1.7.1.
I think people will try to get the algorithms to work efficiently on computers in the toy-model phase, long before the algorithms are doing anything importantly useful and impressive. Indeed, people are already doing that today (e.g.). So in that gap between “doing something importantly useful and impressive” and ASI, people won’t be starting from scratch on the question of “how do we make this run efficiently on existing chips”, instead they’ll be building on all the progress they made during the toy-model phase.