4 ms·

IMO it's worse: they aren't just subsuming the terminology. There's a strain of folks in tech that think that somehow AI researchers have actually uncovered ho

IMO it's worse: they aren't just subsuming the terminology. There's a strain of folks in tech that think that somehow AI researchers have actually uncovered how the brain works. The "neural net" started out as an analogy for a particular kind of statistical model. Now that analogy is being mistaken for some sort of fundamental truth. And if you suggest otherwise, it's the technologists who have it right, not the neuroscientists.

CuriouslyC 3y ago
That's not a fair characterization. There are patterns that emerge in complexity given certain basic things hold true. It doesn't matter whether it's neurons or code, if the system has those property, it will also have those dynamics. This is a lot easier to understand in the abstract, whereas a neuroscientist might ask "why does the brain do XYZ" because they don't understand system dynamics.
- BaseballPhysics 3y ago
  I'd suggest paying closer attention to conversations about ChatGPT and purported sentience before claiming my comments are a mischaracterization. I can't count the number of times I've seen people argue that LLMs are proof that the human mind is just a statistical model. Meanwhile, any neuroscientists will be the first to tell you that we know surprisingly little about how neurons actually work together within the human brain, and certainly don't understand how consciousness emerges.
  - mandmandam 3y ago
    Seconded. I even got called arrogant for very politely pointing out that this was wrong once, because the arguer had been in a computer science class, and so "knew what they were talking about". Neurons are complex. It's arrogant to think we fully understand them.
    - deleted 3y ago
      [deleted]
- YeGoblynQueenne 3y ago
  >> There are patterns that emerge in complexity given certain basic things hold true. Do you mean that in the abstract sense, or do you know what patterns are those, and when they "emerge"? Could you describe them? For example, can you give a mathematical formula for them?
  - nh23423fefe 3y ago
    phase transitions in scale free interactions
    - YeGoblynQueenne 3y ago
      That is word salad.
      - nh23423fefe 3y ago
        remain ignorant
        YeGoblynQueenne 3y ago
        You're an idiot.
        nh23423fefe 3y ago
        *your
bippihippi1 3y ago
i think it's part marketing hype to convince people it's cooler than it is, and that ai companies are not stealing your work by training models on it. ai doesn't generate content, all models learned by gradient descent are kernel machines. it's just a black box version of a function that approximates points in the training set. if they convince people ai is close to sentient and creative, it seems less like copyright infringement
- nerdponx 3y ago
  The term "neural network" has been in widespread use for decades now, And the debate over the terminology has gone on for almost as long. The "neuron" analogy is certainly convenient for marketing field with the general public, but it's not some new conspiracy.
naasking 3y ago
> Now that analogy is being mistaken for some sort of fundamental truth. I think some of the pushback you receive is because you're calling it a mistake when you yourself just admitted that you can't know if it's a mistake because of our incomplete knowledge of neurology. On the other side of this, there are straightforward arguments that there is some deep connection here. Since LLMs infer statistical relationships of languages produced by human brains, they are in a real sense building a statistical model of how the human brain processes language. It could be the case that this is merely an approximation of some kind, but it could also be exactly how it works.
- BaseballPhysics 3y ago
  > I think some of the pushback you receive is because you're calling it a mistake when you yourself just admitted that you can't know if it's a mistake because of our incomplete knowledge of neurology. I'm not the one making the affirmative claim absent evidence. I'm the one pointing out the lack of evidence for the claim. If someone says "there are aliens on the far side of the moon," it's not a mistake to say "there is no evidence for your extraordinary claim". > On the other side of this, there are straightforward arguments that there is some deep connection here. No, there isn't. Humans can perform math. Computers can perform math. No one would claim that's evidence computers think like humans or vice versa. > they are in a real sense building a statistical model of how the human brain processes language. And there you go, making exactly the kind of claim I'm talking about. I'm going to make this very clear: there is absolutely no evidence that supports this claim. Period.
  - doctor_eval 3y ago
    I agree with most of your points and I think there’s a good argument that CS should use different terms that don’t overlap with biology, but I don’t agree with this: > there is absolutely no evidence that supports this claim. Period The evidence is that it understands and can respond with human language which arose from purely biological processes. So until we understand how this happens we can’t say for sure that these things are not statistical models of part of the human brain. Maybe these models are picking up on Chomsky’s universal grammar or maybe they are emulating brains. We just don’t know. It might not be strong evidence, it might be indirect, but it is not a total and irrefutable absence of evidence.

CuriouslyC 3y ago

That's not a fair characterization. There are patterns that emerge in complexity given certain basic things hold true. It doesn't matter whether it's neurons or code, if the system has those property, it will also have those dynamics. This is a lot easier to understand in the abstract, whereas a neuroscientist might ask "why does the brain do XYZ" because they don't understand system dynamics.

BaseballPhysics 3y ago
I'd suggest paying closer attention to conversations about ChatGPT and purported sentience before claiming my comments are a mischaracterization. I can't count the number of times I've seen people argue that LLMs are proof that the human mind is just a statistical model. Meanwhile, any neuroscientists will be the first to tell you that we know surprisingly little about how neurons actually work together within the human brain, and certainly don't understand how consciousness emerges.
- mandmandam 3y ago
  Seconded. I even got called arrogant for very politely pointing out that this was wrong once, because the arguer had been in a computer science class, and so "knew what they were talking about". Neurons are complex. It's arrogant to think we fully understand them.
  - deleted 3y ago
    [deleted]
YeGoblynQueenne 3y ago
>> There are patterns that emerge in complexity given certain basic things hold true. Do you mean that in the abstract sense, or do you know what patterns are those, and when they "emerge"? Could you describe them? For example, can you give a mathematical formula for them?
- nh23423fefe 3y ago
  phase transitions in scale free interactions
  - YeGoblynQueenne 3y ago
    That is word salad.
    - nh23423fefe 3y ago
      remain ignorant
      - YeGoblynQueenne 3y ago
        You're an idiot.
        nh23423fefe 3y ago
        *your

bippihippi1 3y ago

i think it's part marketing hype to convince people it's cooler than it is, and that ai companies are not stealing your work by training models on it. ai doesn't generate content, all models learned by gradient descent are kernel machines. it's just a black box version of a function that approximates points in the training set. if they convince people ai is close to sentient and creative, it seems less like copyright infringement

nerdponx 3y ago
The term "neural network" has been in widespread use for decades now, And the debate over the terminology has gone on for almost as long. The "neuron" analogy is certainly convenient for marketing field with the general public, but it's not some new conspiracy.

naasking 3y ago

> Now that analogy is being mistaken for some sort of fundamental truth. I think some of the pushback you receive is because you're calling it a mistake when you yourself just admitted that you can't know if it's a mistake because of our incomplete knowledge of neurology. On the other side of this, there are straightforward arguments that there is some deep connection here. Since LLMs infer statistical relationships of languages produced by human brains, they are in a real sense building a statistical model of how the human brain processes language. It could be the case that this is merely an approximation of some kind, but it could also be exactly how it works.

BaseballPhysics 3y ago
> I think some of the pushback you receive is because you're calling it a mistake when you yourself just admitted that you can't know if it's a mistake because of our incomplete knowledge of neurology. I'm not the one making the affirmative claim absent evidence. I'm the one pointing out the lack of evidence for the claim. If someone says "there are aliens on the far side of the moon," it's not a mistake to say "there is no evidence for your extraordinary claim". > On the other side of this, there are straightforward arguments that there is some deep connection here. No, there isn't. Humans can perform math. Computers can perform math. No one would claim that's evidence computers think like humans or vice versa. > they are in a real sense building a statistical model of how the human brain processes language. And there you go, making exactly the kind of claim I'm talking about. I'm going to make this very clear: there is absolutely no evidence that supports this claim. Period.
- doctor_eval 3y ago
  I agree with most of your points and I think there’s a good argument that CS should use different terms that don’t overlap with biology, but I don’t agree with this: > there is absolutely no evidence that supports this claim. Period The evidence is that it understands and can respond with human language which arose from purely biological processes. So until we understand how this happens we can’t say for sure that these things are not statistical models of part of the human brain. Maybe these models are picking up on Chomsky’s universal grammar or maybe they are emulating brains. We just don’t know. It might not be strong evidence, it might be indirect, but it is not a total and irrefutable absence of evidence.