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That only answers half of the question. Maybe ML uses some weird shortcut, but how do we know the human brain doesn't use the same shortcut? If it's possible

That only answers half of the question. Maybe ML uses some weird shortcut, but how do we know the human brain doesn't use the same shortcut? If it's possible to use some simple hack to do something, why didn't we evolve to work that way?

rileyphone 4y ago
Brains are radically different from GPUs.
- celu 4y ago
  The same calculations can be performed by an abacus. What is doing the calculation is irrelevant. The question is what the calculation is
  - vlovich123 4y ago
    That's kind of a philosophical question no? Is being able to model an analog behavior accurately the same thing as the analog behavior itself? While we know from math there's an equivalence / bounded error rate, it certainly seems like emulation in the digital domain is far more power intensive which would indicate that it's not the thing itself. A clearer example is photon collisions. Simulating that behavior on a computer is not the same thing as colliding the photons. Could be wrong though.
    - kzrdude 4y ago
      Does it matter if the simulations of photons is on an abacus or using a GPU? I think that's the question. Neither of those are "reality", just a simulation.
      - vlovich123 4y ago
        >>>> Maybe ML uses some weird shortcut, but how do we know the human brain doesn't use the same shortcut? If it's possible to use some simple hack to do something, why didn't we evolve to work that way? >>> Brains are radically different from GPUs. >> The same calculations can be performed by an abacus. What is doing the calculation is irrelevant. The question is what the calculation is > Does it matter if the simulations of photons is on an abacus or using a GPU? I think that's the question. Neither of those are "reality", just a simulation. I think so, yes, specifically with respect to the question of "how do we know the human brain doesn't use the same shortcut?". Simulations likely use very different shortcuts because they're optimizing for the structural design of a man-made machine that exists today and uses numerical and CS tricks to cheapen the computation cost while maintaining error rates on training data. The brain uses physical shortcuts to minimize energy expenditure, for survival of the host, and resiliency of the species (i.e. OK if flaws exist sometimes as long as the species survival is improved long-term). So not only is ML a fun-house mirror image of a brain (our model is extremely imperfect today), the optimization process is totally alien to how the brain figured out all its shortcuts.
  - unixlikeposting 4y ago
    Neurons do not fire like logic gates. stop it.
    - williamcotton 4y ago
      I’d just like to point out that if neurons do or don’t fire like logic gates that it basically doesn’t matter at all, not for this argument about Stable Diffusion or even in a deeper philosophical sense. It’s a silly question much like asking if a submarine can swim is a silly question. The irony here being we're a few layers deep in a thread started as a critique on this kind of pointless anthropomorphism.
  - jerf 4y ago
    This argument would be somewhat more compelling in a world where little bits of silicon were not on the order of quadrillions of times faster than we are at arithmetic, whereas those bits of silicon struggle to do at all things we casually do every waking second. The calculation is theoretically unimportant. Practically, it is of great importance.
- deleted 4y ago
  [deleted]
unixlikeposting 4y ago
>Maybe ML uses some weird shortcut, You do realize that there are people in this thread who can explain to you in fine grain detail how an ML model actually comes to conclusions, without speculating abstract "weird shortcuts".
Rastonbury 4y ago
I can't say with 100% certainty but I don't think our brains turn words into numbers and perform math calculations equations to make images. It's a bit of a cop out saying "we don't know how the brain works". If you apply the same analogy to ChatGPT we don't use math calculations to write words. If anything GPUs are not using shortcut, they use brute computation, to get to what our brains perceive as similar.
6gvONxR4sf7o 4y ago
Here's a concrete famous example. I'm sure I'll remember the details wrong, but the gist is the kind of thing that keeps happening. A while back, people built a model for medical imaging that learned to distinguish between images of patients with vs without some disease (can't remember that detail). It did well, but failed in the real world. It turned out that instead of learning to recognize features of the disease at hand, it learned to recognize some tiny feature of whether the image came from a specific hospital that collected part of the dataset, or something stupid like that. Saying "maybe model X does the same thing as humans" is proven wrong for X after X after X. At this point, the default assumption should be that ML techniques are different from humans unless proven otherwise.

rileyphone 4y ago

Brains are radically different from GPUs.

celu 4y ago
The same calculations can be performed by an abacus. What is doing the calculation is irrelevant. The question is what the calculation is
- vlovich123 4y ago
  That's kind of a philosophical question no? Is being able to model an analog behavior accurately the same thing as the analog behavior itself? While we know from math there's an equivalence / bounded error rate, it certainly seems like emulation in the digital domain is far more power intensive which would indicate that it's not the thing itself. A clearer example is photon collisions. Simulating that behavior on a computer is not the same thing as colliding the photons. Could be wrong though.
  - kzrdude 4y ago
    Does it matter if the simulations of photons is on an abacus or using a GPU? I think that's the question. Neither of those are "reality", just a simulation.
    - vlovich123 4y ago
      >>>> Maybe ML uses some weird shortcut, but how do we know the human brain doesn't use the same shortcut? If it's possible to use some simple hack to do something, why didn't we evolve to work that way? >>> Brains are radically different from GPUs. >> The same calculations can be performed by an abacus. What is doing the calculation is irrelevant. The question is what the calculation is > Does it matter if the simulations of photons is on an abacus or using a GPU? I think that's the question. Neither of those are "reality", just a simulation. I think so, yes, specifically with respect to the question of "how do we know the human brain doesn't use the same shortcut?". Simulations likely use very different shortcuts because they're optimizing for the structural design of a man-made machine that exists today and uses numerical and CS tricks to cheapen the computation cost while maintaining error rates on training data. The brain uses physical shortcuts to minimize energy expenditure, for survival of the host, and resiliency of the species (i.e. OK if flaws exist sometimes as long as the species survival is improved long-term). So not only is ML a fun-house mirror image of a brain (our model is extremely imperfect today), the optimization process is totally alien to how the brain figured out all its shortcuts.
- unixlikeposting 4y ago
  Neurons do not fire like logic gates. stop it.
  - williamcotton 4y ago
    I’d just like to point out that if neurons do or don’t fire like logic gates that it basically doesn’t matter at all, not for this argument about Stable Diffusion or even in a deeper philosophical sense. It’s a silly question much like asking if a submarine can swim is a silly question. The irony here being we're a few layers deep in a thread started as a critique on this kind of pointless anthropomorphism.
- jerf 4y ago
  This argument would be somewhat more compelling in a world where little bits of silicon were not on the order of quadrillions of times faster than we are at arithmetic, whereas those bits of silicon struggle to do at all things we casually do every waking second. The calculation is theoretically unimportant. Practically, it is of great importance.
deleted 4y ago
[deleted]

unixlikeposting 4y ago

>Maybe ML uses some weird shortcut, You do realize that there are people in this thread who can explain to you in fine grain detail how an ML model actually comes to conclusions, without speculating abstract "weird shortcuts".

Rastonbury 4y ago

I can't say with 100% certainty but I don't think our brains turn words into numbers and perform math calculations equations to make images. It's a bit of a cop out saying "we don't know how the brain works". If you apply the same analogy to ChatGPT we don't use math calculations to write words. If anything GPUs are not using shortcut, they use brute computation, to get to what our brains perceive as similar.

6gvONxR4sf7o 4y ago

Here's a concrete famous example. I'm sure I'll remember the details wrong, but the gist is the kind of thing that keeps happening. A while back, people built a model for medical imaging that learned to distinguish between images of patients with vs without some disease (can't remember that detail). It did well, but failed in the real world. It turned out that instead of learning to recognize features of the disease at hand, it learned to recognize some tiny feature of whether the image came from a specific hospital that collected part of the dataset, or something stupid like that. Saying "maybe model X does the same thing as humans" is proven wrong for X after X after X. At this point, the default assumption should be that ML techniques are different from humans unless proven otherwise.