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>but also still arrive at those results via completely different means. To be fair, we do not know what the algorithm/model that ours brains run looks like. If

>but also still arrive at those results via completely different means. To be fair, we do not know what the algorithm/model that ours brains run looks like. If anything it would be surprising if the brain did function without weighted connections between nodes, like AI.

jjk166 2y ago
Yeah, but a computer isn't using such algorithms to do addition. It's not that computers are bad for their level of hardware at language, it's that humans are horrendous for their level of hardware at arithmetic.
- marcus_holmes 2y ago
  Some humans can do incredibly complicated arithmetic in an instant. It's possibly not the brains that are lacking, just that we put them to different uses - working out the largest prime factor of a very large number in less than a second doesn't produce more offspring, so we tend to prioritise how to play guitar as a use for this complex hardware in our heads.
  - jjk166 2y ago
    That there is a good reason we're bad at math doesn't really change the fact we're bad at math. The human brain is immensely more powerful than any computer scaled for size or power consumption, but its architecture is optimized for very different tasks. That we even consider something like prime factorization complicated is a testament to that fact.
    - mrkstu 2y ago
      It’s interesting though that the hardware and software is all there, but something prevents accessing it- autistic savants ala ‘rainman’ can do instantaneous math at computer-like speed. There are humans who have near total recall. I think if we can understand why/how they can access this layer, so that it can become a generalized human attribute, without the autistic downsides, it’d be more revolutionary than LLMs.
      - randomdata 2y ago
        Are these autistics/savants actually accessing some kind of different layer, or is it, like the earlier comment suggests, that they've tuned/shaped/however to describe it their brain in a different way? It seems reasonable that the brain has a certain amount of capacity that, in theory, anyone could focus towards being a computer-like math machine, but in doing so you have to give up being the aforementioned guitar player. Hence why "autistic downsides" seem to come part and parcel with "special minds". That is tradeoff made to allow the brain do something else.
bunderbunder 2y ago
Oh, we know it's weighted connections. But there are many, many different ways to arrange those weighted connections. Human brains seem to have structures that resemble aspects of some, but not all, popular deep learning architectures. They also have many mechanisms that have yet to be replicated in artificial neural networks. For example, I continue to question two propositions that many others seem to take for granted when they try to predict what LLMs can and cannot do well: 1. LLMs can do generalized symbolic reasoning. 2. If a human does it symbolically, that's how it must be done. Over the past couple years I've grown to be much more sympathetic to Searle's Chinese Room argument. LLMs are incredibly good at mimicking human behavior and performing tasks that were previously impossible for machines. But as you examine what they're doing more closely you start to see them failing in all sorts of interesting ways that remind you that they're still very much in an uncanny valley of sorts. Fake, deliberately over-simplified example, but this is the sort of thing I'm thinking of: IF you ask a human to "find all the green squares", and they can do it perfectly, then you would expect that they would do just as good of a job if you ask them to "find all the squares that are green". That sort of expectation does not work with GPT-4. Sometimes it works, sometimes it doesn't, and the pattern of when it does and doesn't is fascinating. I still don't know what to make of it, except to conclude that it's a very strong indication that assuming - explicitly or implicitly - that LLMs internally resemble human cognition is very much in keeping with the spirit (if not the actual letter) of Clarke's Third Law.
- thornewolf 2y ago
  I always found the Chinese room to be self-evident as intelligent
- stickfigure 2y ago
  I think you're anthropomorphizing humans too much. Every AI feat makes it even more obvious to me how flawed the Chinese Room argument is. We just need to get past the realization "oh wow, I'm a machine too". Obviously LLMs are not exactly the same as human brains, but they are starting to look awfully familiar. And not all human brains are the same! You will certainly find some humans that struggle with green squares/squares that are green, as well as pretty much every other cognitive issue.

jjk166 2y ago

Yeah, but a computer isn't using such algorithms to do addition. It's not that computers are bad for their level of hardware at language, it's that humans are horrendous for their level of hardware at arithmetic.

marcus_holmes 2y ago
Some humans can do incredibly complicated arithmetic in an instant. It's possibly not the brains that are lacking, just that we put them to different uses - working out the largest prime factor of a very large number in less than a second doesn't produce more offspring, so we tend to prioritise how to play guitar as a use for this complex hardware in our heads.
- jjk166 2y ago
  That there is a good reason we're bad at math doesn't really change the fact we're bad at math. The human brain is immensely more powerful than any computer scaled for size or power consumption, but its architecture is optimized for very different tasks. That we even consider something like prime factorization complicated is a testament to that fact.
  - mrkstu 2y ago
    It’s interesting though that the hardware and software is all there, but something prevents accessing it- autistic savants ala ‘rainman’ can do instantaneous math at computer-like speed. There are humans who have near total recall. I think if we can understand why/how they can access this layer, so that it can become a generalized human attribute, without the autistic downsides, it’d be more revolutionary than LLMs.
    - randomdata 2y ago
      Are these autistics/savants actually accessing some kind of different layer, or is it, like the earlier comment suggests, that they've tuned/shaped/however to describe it their brain in a different way? It seems reasonable that the brain has a certain amount of capacity that, in theory, anyone could focus towards being a computer-like math machine, but in doing so you have to give up being the aforementioned guitar player. Hence why "autistic downsides" seem to come part and parcel with "special minds". That is tradeoff made to allow the brain do something else.

bunderbunder 2y ago

Oh, we know it's weighted connections. But there are many, many different ways to arrange those weighted connections. Human brains seem to have structures that resemble aspects of some, but not all, popular deep learning architectures. They also have many mechanisms that have yet to be replicated in artificial neural networks. For example, I continue to question two propositions that many others seem to take for granted when they try to predict what LLMs can and cannot do well: 1. LLMs can do generalized symbolic reasoning. 2. If a human does it symbolically, that's how it must be done. Over the past couple years I've grown to be much more sympathetic to Searle's Chinese Room argument. LLMs are incredibly good at mimicking human behavior and performing tasks that were previously impossible for machines. But as you examine what they're doing more closely you start to see them failing in all sorts of interesting ways that remind you that they're still very much in an uncanny valley of sorts. Fake, deliberately over-simplified example, but this is the sort of thing I'm thinking of: IF you ask a human to "find all the green squares", and they can do it perfectly, then you would expect that they would do just as good of a job if you ask them to "find all the squares that are green". That sort of expectation does not work with GPT-4. Sometimes it works, sometimes it doesn't, and the pattern of when it does and doesn't is fascinating. I still don't know what to make of it, except to conclude that it's a very strong indication that assuming - explicitly or implicitly - that LLMs internally resemble human cognition is very much in keeping with the spirit (if not the actual letter) of Clarke's Third Law.

thornewolf 2y ago
I always found the Chinese room to be self-evident as intelligent
stickfigure 2y ago
I think you're anthropomorphizing humans too much. Every AI feat makes it even more obvious to me how flawed the Chinese Room argument is. We just need to get past the realization "oh wow, I'm a machine too". Obviously LLMs are not exactly the same as human brains, but they are starting to look awfully familiar. And not all human brains are the same! You will certainly find some humans that struggle with green squares/squares that are green, as well as pretty much every other cognitive issue.