Yes but that doesn’t mean you won’t need new architectures or training methods to get there, or data that doesn’t currently exist. We also don’t know how many neurons / layers we’d need, etc.
The brain itself is infinitely more complex than artificial neural networks. Maybe we don’t need all of what nature does to get there, but we are so many orders of magnitude off its redonk. People talk about number of neurons of the brain as if there’s a 1:1 mapping with an ANN. Real neurons have chemical, physical properties, along with other things probably not yet discovered going on.
This is an interesting comment. I agree that I hear the "all we need is 86 billion neurons and we will habe parity with the human brain", and I feel it is dubious to think this way because there is no reason why this arbitrary number must work.
I also think it is a bit strange to use the human brain as an analogy because biological neurons supposedly are booleans and act in groups to achieve float level behavior. For example I can have neurologic pain in my fingers that isn't on off, but rather, has differences in magnitude.
I think we should move away from the biology comparisons and just seek to understand if "more neurons = more better" is true, and if it is, how do we shove more into RAM and handle the exploding compute complexity.
The brain itself is infinitely more complex than artificial neural networks. Maybe we don’t need all of what nature does to get there, but we are so many orders of magnitude off its redonk. People talk about number of neurons of the brain as if there’s a 1:1 mapping with an ANN. Real neurons have chemical, physical properties, along with other things probably not yet discovered going on.