5 ms·

This is just false. Outside of the visual cortex there isn't any evidence that brains work anything like GPT-4 or neural nets. Producing the same outputs isn't

This is just false. Outside of the visual cortex there isn't any evidence that brains work anything like GPT-4 or neural nets. Producing the same outputs isn't evidence of anything. At best you have just stated a hypothesis of how the brain might work, not any actual evidence supporting it.

HarHarVeryFunny 3y ago
Sure - you can't just look at how an ANN works and assume that's how the brain does that too, but the ANN's operation can act as inspiration to suggest or confirm the way the brain might be doing something. It seems neuroscientists are good at discovering low level detail and perhaps not so good in general (visual cortex being somewhat of an exception) at putting the pieces together to suggest high level operations. ANNs seem complementary in that while their low level details are little like the brain, the connectionist architectures can be comparable, and we do know the top down operation (even though interpretation is an issue, more for some ANNs than others). If we assume that the cortex is doing some type of prediction error minimization then it's likely to have found similar solutions to an ANN in cases where problem and connectivity are similar.
- foobarqux 3y ago
  Again this is just a hypothesis and nothing has come from it despite the fact that it is very old. There isn't any good reason for it to be true and no one has done anything to show that it is.
  - HarHarVeryFunny 3y ago
    Not sure what you're referring to - what's a hypothesis/old ?
    - foobarqux 3y ago
      Pretty much any claim that the brain (outside the visual cortex) work anything like the way neural nets do.
      - HarHarVeryFunny 3y ago
        So why do you believe that the visual cortex works similarly to an ANN, but the rest of the cortex doesn't ?! Of course we know that CNNs and the visual cortex both learn similar low level orientated-line feature detectors, etc, so there is evidence of them operating in similar fashion. The thing is, the entire cortex is a very regular structure with the same 6-layer architecture across all areas and same thalamo-cortical loop connectivity. So, it's very unlikely that one area of cortex is operating in a fashion much different to any other area. If you're willing to accept that the visual cortex has close parallels to a CNN in terms of how it is operating, then that is highly suggestive that the abstraction of a CNN/ANN does indeed capture the essence of at least some aspects of cortical operation. Nobody is saying that the brain and ANNs are exactly the same, but there seems to be close enough correspondence to at least some types of ANN architecture that lessons learned there can inspire understanding of the latter. Another example - before seq-2-seq neural net language translation, would you have believed that an a variable length sentence could have it's meaning captured by a fixed size sentence embedding ? Intuition might have suggested that some complex structured variable length representation would be needed, but now we know that's not the case, and it helps understand how similar representations are likely also used in the brain.
        foobarqux 3y ago
        > So why do you believe that the visual cortex works similarly to an ANN, but the rest of the cortex doesn't ?! Because there are actual (unethical on humans) experiments on cats (which have similar visual systems to humans) so we know some things about how the visual system works. There is nothing equivalent for the rest of the mind. > Nobody is saying that the brain and ANNs are exactly the same, but there seems to be close enough correspondence to at least some types of ANN architecture that lessons learned there can inspire understanding of the latter. Again this is a hypothesis, the burden is on the person making that claim to provide evidence. > Another example - [...] This is a much worse example because we specifically know that LLMs don't work the way the human language faculty do because they can "learn" languages that are impossible for humans.
        3y ago
rTX5CMRXIfFG 3y ago
Isn’t the hypothesis the point though? If you have existential evidence of a logical phenomenon occurring in a machine, then it’s worth directing your study to look for a similar (though not necessarily the exact) mechanism in organic matter, because logic is independent of the anatomy and physiology of the machine/organism performing it? Besides, the propagation of 1’s and 0’s in computers has a very strong parallel with, say, how the brain transmits action potential to skeletal muscle, for example.
astrange 3y ago
Human speech processes seem similar to how LLMs work. There are brain injuries (Korsakoff's syndrome) that cause confabulation, which is like ChatGPT hallucinating the answer to questions.
breck 3y ago
> Outside of the visual cortex there isn't any evidence that brains work anything like GPT-4 or neural nets. Are you sure? If you had to pick a number what would you pick? I have never built a useful neural network myself so I can't speak confidently, but I've read enough McCullough & Pitts, Cybernetics, Minsky, et cetera, to have the knowledge that there's a direct connection between a multitude of lab experiments done in the early 1900's to quantify the behavior of neurons in various animals, and then develop the principle ideas of ANNs from those findings. Of course, there are hundreds, if not thousands or more of "components" in the brain, and I'm not sure how many of those components we have digital analogs for. But I feel like GPT-4 makes me think we've crossed the 10% threshold.
sheepscreek 3y ago
I think it is absurd to dismiss a comment for the lack of evidence on how the brain works. This is a thought experiment - nobody has any proof. So you can’t say “this is just false” without providing counter evidence, which you don’t have. The point here is to have a reference point, something to compare against, as we learn more about the brain.
- jillesvangurp 3y ago
  The response is a bit knee-jerky and emotional. A lot of people find it upsetting that human thinking can be approximated by AI. The demands for proof stem from this emotional response and a misunderstanding of how science actually works. There is plenty of evidence and theories. Most of that evidence is of an empirical nature. It suggests that GPT 4 can do some interesting things and that artificial neurons cluster and fire in ways similar to those in real brains. That's a theory that is backed by some of this evidence. And it is of course not completely accidental because that sort of was the intention by those that constructed the neural networks. You could say that neural networks apparently work as intended. The scientific way to dismiss that theory would be proving it wrong. That's what science does: gather evidence and facts, come up with theories that explain those, and then try to find proof that counters those theories and explanations. And then you replace them with better ones. Falsifying theories is how science move forward. You don't prove them right but you fail to prove them wrong. Insisting something is false without doing that is very unscientific. Human brains are more than just neurons of course. The article actually calls that out. There's a lot of chemistry in our brains that directly controls what it does. That's why people enjoy taking certain drugs; those literally change the way our brain operates. Coffee is a drug that many people find useful. Learning especially is associated with endorphins. You get a little endorphin rush when you figure something out. Some people like this so much that they become scientists. Artificial neural networks don't really model any of that. But nobody is saying that they are the same; just that they do similar things in similar ways; as can be observed via experiments and the use of MRI scanners. We don't really understand why that is but the similarity is easily observed and a valid theory is that an ANN captures enough of the complexity of a brain to be able to do interesting things. Which is of course backed up by plenty of empirical evidence in the form of people having used GOT-4. People seem to struggle to articulate what it is that is missing exactly that would prove that theory wrong. Lots of people that want that to be wrong, not a lot coming up with better theories. But of course some scientists are working on that and the prospect of them figuring this out is what truly scares some people.

HarHarVeryFunny 3y ago

Sure - you can't just look at how an ANN works and assume that's how the brain does that too, but the ANN's operation can act as inspiration to suggest or confirm the way the brain might be doing something. It seems neuroscientists are good at discovering low level detail and perhaps not so good in general (visual cortex being somewhat of an exception) at putting the pieces together to suggest high level operations. ANNs seem complementary in that while their low level details are little like the brain, the connectionist architectures can be comparable, and we do know the top down operation (even though interpretation is an issue, more for some ANNs than others). If we assume that the cortex is doing some type of prediction error minimization then it's likely to have found similar solutions to an ANN in cases where problem and connectivity are similar.

foobarqux 3y ago
Again this is just a hypothesis and nothing has come from it despite the fact that it is very old. There isn't any good reason for it to be true and no one has done anything to show that it is.
- HarHarVeryFunny 3y ago
  Not sure what you're referring to - what's a hypothesis/old ?
  - foobarqux 3y ago
    Pretty much any claim that the brain (outside the visual cortex) work anything like the way neural nets do.
    - HarHarVeryFunny 3y ago
      So why do you believe that the visual cortex works similarly to an ANN, but the rest of the cortex doesn't ?! Of course we know that CNNs and the visual cortex both learn similar low level orientated-line feature detectors, etc, so there is evidence of them operating in similar fashion. The thing is, the entire cortex is a very regular structure with the same 6-layer architecture across all areas and same thalamo-cortical loop connectivity. So, it's very unlikely that one area of cortex is operating in a fashion much different to any other area. If you're willing to accept that the visual cortex has close parallels to a CNN in terms of how it is operating, then that is highly suggestive that the abstraction of a CNN/ANN does indeed capture the essence of at least some aspects of cortical operation. Nobody is saying that the brain and ANNs are exactly the same, but there seems to be close enough correspondence to at least some types of ANN architecture that lessons learned there can inspire understanding of the latter. Another example - before seq-2-seq neural net language translation, would you have believed that an a variable length sentence could have it's meaning captured by a fixed size sentence embedding ? Intuition might have suggested that some complex structured variable length representation would be needed, but now we know that's not the case, and it helps understand how similar representations are likely also used in the brain.
      - foobarqux 3y ago
        > So why do you believe that the visual cortex works similarly to an ANN, but the rest of the cortex doesn't ?! Because there are actual (unethical on humans) experiments on cats (which have similar visual systems to humans) so we know some things about how the visual system works. There is nothing equivalent for the rest of the mind. > Nobody is saying that the brain and ANNs are exactly the same, but there seems to be close enough correspondence to at least some types of ANN architecture that lessons learned there can inspire understanding of the latter. Again this is a hypothesis, the burden is on the person making that claim to provide evidence. > Another example - [...] This is a much worse example because we specifically know that LLMs don't work the way the human language faculty do because they can "learn" languages that are impossible for humans.
        3y ago

rTX5CMRXIfFG 3y ago

Isn’t the hypothesis the point though? If you have existential evidence of a logical phenomenon occurring in a machine, then it’s worth directing your study to look for a similar (though not necessarily the exact) mechanism in organic matter, because logic is independent of the anatomy and physiology of the machine/organism performing it? Besides, the propagation of 1’s and 0’s in computers has a very strong parallel with, say, how the brain transmits action potential to skeletal muscle, for example.

astrange 3y ago

Human speech processes seem similar to how LLMs work. There are brain injuries (Korsakoff's syndrome) that cause confabulation, which is like ChatGPT hallucinating the answer to questions.

breck 3y ago

> Outside of the visual cortex there isn't any evidence that brains work anything like GPT-4 or neural nets. Are you sure? If you had to pick a number what would you pick? I have never built a useful neural network myself so I can't speak confidently, but I've read enough McCullough & Pitts, Cybernetics, Minsky, et cetera, to have the knowledge that there's a direct connection between a multitude of lab experiments done in the early 1900's to quantify the behavior of neurons in various animals, and then develop the principle ideas of ANNs from those findings. Of course, there are hundreds, if not thousands or more of "components" in the brain, and I'm not sure how many of those components we have digital analogs for. But I feel like GPT-4 makes me think we've crossed the 10% threshold.

sheepscreek 3y ago

I think it is absurd to dismiss a comment for the lack of evidence on how the brain works. This is a thought experiment - nobody has any proof. So you can’t say “this is just false” without providing counter evidence, which you don’t have. The point here is to have a reference point, something to compare against, as we learn more about the brain.

jillesvangurp 3y ago
The response is a bit knee-jerky and emotional. A lot of people find it upsetting that human thinking can be approximated by AI. The demands for proof stem from this emotional response and a misunderstanding of how science actually works. There is plenty of evidence and theories. Most of that evidence is of an empirical nature. It suggests that GPT 4 can do some interesting things and that artificial neurons cluster and fire in ways similar to those in real brains. That's a theory that is backed by some of this evidence. And it is of course not completely accidental because that sort of was the intention by those that constructed the neural networks. You could say that neural networks apparently work as intended. The scientific way to dismiss that theory would be proving it wrong. That's what science does: gather evidence and facts, come up with theories that explain those, and then try to find proof that counters those theories and explanations. And then you replace them with better ones. Falsifying theories is how science move forward. You don't prove them right but you fail to prove them wrong. Insisting something is false without doing that is very unscientific. Human brains are more than just neurons of course. The article actually calls that out. There's a lot of chemistry in our brains that directly controls what it does. That's why people enjoy taking certain drugs; those literally change the way our brain operates. Coffee is a drug that many people find useful. Learning especially is associated with endorphins. You get a little endorphin rush when you figure something out. Some people like this so much that they become scientists. Artificial neural networks don't really model any of that. But nobody is saying that they are the same; just that they do similar things in similar ways; as can be observed via experiments and the use of MRI scanners. We don't really understand why that is but the similarity is easily observed and a valid theory is that an ANN captures enough of the complexity of a brain to be able to do interesting things. Which is of course backed up by plenty of empirical evidence in the form of people having used GOT-4. People seem to struggle to articulate what it is that is missing exactly that would prove that theory wrong. Lots of people that want that to be wrong, not a lot coming up with better theories. But of course some scientists are working on that and the prospect of them figuring this out is what truly scares some people.