this is why people should better study neuroscience, psychology if they want to advance research in AI.
also things related to graph topology in neural networks maybe, but probably not related to artificial NN.
I was given this video, which I found was pretty interesting: https://www.youtube.com/watch?v=nkdZRBFtqSs (How Developers might stop worrying about AI taking software jobs and Learn to Profit from LLMs - YouTube)
> 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.
There are loads of psychologists and neuroscientists today. Has any of them in the last few years produced anything advancing AI? The proof of the pudding is in the eating so if they have at a higher rate than just straight CS/Mathematics and related then there’s probably some truth to it.
also things related to graph topology in neural networks maybe, but probably not related to artificial NN.
I was given this video, which I found was pretty interesting: https://www.youtube.com/watch?v=nkdZRBFtqSs (How Developers might stop worrying about AI taking software jobs and Learn to Profit from LLMs - YouTube)