Artificial Neural Nets Finally Yield Clues to How Brains Learn
quantamagazine.org
Artificial Neural Nets Finally Yield Clues to How Brains Learn
1–10 of 40 posts
Re: Artificial Neural Nets Finally Yield Clues to How Brains Learn
#2With articles like this, I want a "check back in 2 years" reminder, to see how the science shakes out. I'm not smart or informed enough to judge these current events style updates for myself.
Re: Artificial Neural Nets Finally Yield Clues to How Brains Learn
#3With articles like this, I want a "check back in 2 years" reminder, to see how the science shakes out. I'm not smart or informed enough to judge these current events style updates for myself.
You could favorite the post and add a calendar reminder but I agree it would be a useful HN feature.
Re: Artificial Neural Nets Finally Yield Clues to How Brains Learn
#4[deleted]
Re: Artificial Neural Nets Finally Yield Clues to How Brains Learn
#5> Nonetheless, Hinton and a few others immediately took up the challenge of working on biologically plausible variations of backpropagation.
Trying to prove the plausibility of a theory is one approach to science I guess... The researchers have already concluded that brains are simply information processing machines and that AI techniques are a sufficiently representative model to use to learn what brains are like.
I don't see how this research could give us clues to anything other than what is already presumed to be true by the researchers.
Re: Artificial Neural Nets Finally Yield Clues to How Brains Learn
#6I may be missing something, but it’s just a click bait title with no substance.
Re: Artificial Neural Nets Finally Yield Clues to How Brains Learn
#7With articles like this, I want a "check back in 2 years" reminder, to see how the science shakes out. I'm not smart or informed enough to judge these current events style updates for myself.
Reddit has the remindMe bot for that, HN should give us an exobrain too
Re: Artificial Neural Nets Finally Yield Clues to How Brains Learn
#8With articles like this, I want a "check back in 2 years" reminder, to see how the science shakes out. I'm not smart or informed enough to judge these current events style updates for myself.
Reddit has the remindMe bot for that, HN should give us an exobrain too
Please, if somebody does this, let's not augment HN by littering the comments with bots.
Re: Artificial Neural Nets Finally Yield Clues to How Brains Learn
#9> Nonetheless, Hinton and a few others immediately took up the challenge of working on biologically plausible variations of backpropagation. Trying to prove the plausibility of a theory is one approach to science I guess... The researchers have already concluded that brains are simply information processing machines and that AI techniques are a sufficiently representative model to use to learn what brains are like. I…
You're downvoted but this is correct. It is much like when the analogy was "springs and cogs", and an academic department created in that era "cog-nitive" science, would be the attempt to rotate enough gears in the right way.
Many presumptions are being made here in "computational cognitive science" which preclude including many relevant features of animal learning and animal biology.
Their whole world view is that "patterns of electrical signals in neurons" is where learning takes place. This is very likely to be false: it fails, for example, to note that the brain grows.
Organic growth isn't even scoped here. A brain is a time-evolving dynamic system, whose architecture is at every level dynamic. (& Not least, embedded in a motor system which has a profound effect on its structure ).
Re: Artificial Neural Nets Finally Yield Clues to How Brains Learn
#10> Nonetheless, Hinton and a few others immediately took up the challenge of working on biologically plausible variations of backpropagation. Trying to prove the plausibility of a theory is one approach to science I guess... The researchers have already concluded that brains are simply information processing machines and that AI techniques are a sufficiently representative model to use to learn what brains are like. I…
You're downvoted but this is correct. It is much like when the analogy was "springs and cogs", and an academic department created in that era "cog-nitive" science, would be the attempt to rotate enough gears in the right way. Many presumptions are being made here in "computational cognitive science" which preclude including many relevant features of animal learning and animal biology. Their whole world view is that "…
>Many presumptions are being made here in "computational cognitive science" which preclude including many relevant features of animal learning and animal biology.
This post doesn't actually seem to be citing computational cog-sci, which is usually a bit better about these things. Instead it's addressing the field of biologically plausible (ie: with Hebbian learning rules) deep learning.
> (& Not least, embedded in a motor system which has a profound effect on its structure ).
Sure, but that would expose how weak so much of the present AI work actually is when it comes to studying the motor system.