> I doubt neuroscience will either, but I’m not as sure on that
The stuff on spiking networks and neuromorphic computing is definitely interesting and inspired by neuroscience, but it currently seems mostly like vaporware
The question is whether current AI technologies represent any progress towards a true human equivalent artificial general intelligence. Most likely not, but no one knows for sure. If the answer turns out to be no then real progress will likely require theoretical insights from psychology, neuroscience, and other fields.
Fwiw, I don’t think we’re any closer to general intelligence then we were 5 years ago.
Other than that, I agree, especially since you added “and other fields.”
Psychology might eventually give us a useful definition of “intelligence,” so that’d be something.
Obviously all research can influence other areas of research.
It's easy to overstate, but shouldn't be understated either with, as an example, solving problems with learning in AI providing insights into how dopamine works in brains.
There are obvious, huge differences between what goes on in a computer and what happens in a a brain. Neurons can't do back propagation is a glaring one. But they do do something that ends up being analogous to back propagation and you can't tell a priori whether some property of AI or neuroscience might be applicable to the other or not.
The best way to learn about AI isn't to learn neuroscience. it's to learn AI. But if I were an AI lab I'd still hire someone to read neuroscience papers and check to see whether they might have something useful in them.
I doubt neuroscience will either, but I’m not as sure on that.
The more impressive AI systems we have moved further away from the neuron analogy that came from perceptions.
The whole “intelligence” and “neural” part of AI is a red herring imo. Really poor ambiguous word choice for a specific, technical idea.