6 ms·

It's also "out-brute forcing them." It just never gets tired. If a mathematician picks a research direction and spends a whole week on it and it doesn't pan out

It's also "out-brute forcing them." It just never gets tired. If a mathematician picks a research direction and spends a whole week on it and it doesn't pan out, they will likely be annoyed, need a break for a while, etc. This thing just does not ever get tired or discouraged or care; it's just onto the next thing until something ends up working.

thaumasiotes 2mo ago
> If a mathematician picks a research direction and spends a whole week on it and it doesn't pan out, they will likely be annoyed, need a break for a while, etc. Your timelines are a bit unambitious. There's nobody expecting to make significant progress with a week of work.
- nmstoker 2mo ago
  They were just illustrating their point, I wouldn't take that literally.
- bananaflag 2mo ago
  > There's nobody expecting to make significant progress with a week of work. You underestimate my ADHD. Source: I am mathematician.
  - dijksterhuis 2mo ago
    Hell, I underestimate my own ADHD. Source: the post-it notes, ALL OF THEM.
EA-3167 2mo ago
The key here is that it’s depending on the human inability to connect the sum of relevant knowledge, but said knowledge comes from humans. Theres going to be this field day of low-hanging fruit that ML can round up, but after that I suspect it will be in fits and starts as a “connection maker” rather than some proof producer.
- putlake 2mo ago
  It's not only going to be "connection maker". If and when robotics advance to a point where the LLMs are embodied, they can run experiments in the physical world and find new knowledge.
  - EA-3167 2mo ago
    Robots in labs already exist, but mercifully they're not hooked up to anything as unpredictable as an LLM. Robots tend to work best as specialists doing high-throughput, extremely repetitive tasks which nonetheless require a degree of precision. Giving a robot a "human" body makes very little sense if we're talking about the needs and productivity of a non-human; humanoid robots are marketing for humans.
    - AustinDev 2mo ago
      Humanoid robots are obviously more than marketing. The entirety of human civilization is human shaped. Making robots that are human shaped is easier and more efficient than redesigning and rebuilding everything that exists.
      - tsimionescu 2mo ago
        > Making robots that are human shaped is easier and more efficient than redesigning and rebuilding everything that exists. In the last 100-200 years, that has been proven wrong at every single step.
        red75prime 2mo ago
        Generalist humanoid robots that are able to operate in unstructured environments weren't an option (they still aren't an option for the majority of operations). The humanity had no ways of building them. Anyway, it's true that replacing an automated production line with a crowd of generalist robots doesn't make sense. Generalist humanoid robots are intended to replace the remaining human workers.
grebc 2mo ago
Ever heard of string theory. People go whole lives without being able to make it pan out.
- tengbretson 2mo ago
  String theory is a great example of a dead end kept alive by ego and sunk cost fallacy. An AI would have declared it dead and moved on 10 years earlier.
  - hilariously 2mo ago
    Ok Sabina, everyone is string theory is all just a bunch of egotistical morons.
    - chongli 2mo ago
      No, not morons, but people who have built a career on string theory. At this point, even if they regret their decisions, it’s too late to turn back now.
      - smallmancontrov 2mo ago
        As opposed to having built a career complaining about string theory on youtube?
        chongli 2mo ago
        And that's the reason she's wrong?
        cauch 2mo ago
        You were the one introducing the argument "they are getting advantages out of it so we should be careful to not take what they say as an impartial view". Same can be told of Hossenfelder (personally, I would say that Hossenfelder has shown more clues that indeed she is not very reliable and would prefer caricatural sensationalistic descriptions, which is not what the typical string theory physicist does).
bze12 2mo ago
AI has sitzfleisch https://en.wikipedia.org/wiki/J._Robert_Oppenheimer#:~:text=He%20didn't%20have,was%20fantastic.%5B63%5D https://en.wikipedia.org/wiki/J._Robert_Oppenheimer#:~:text=...
- ashleyn 2mo ago
  Wow, what a great comparison. LLMs are great at reasoning but absolute dogshit at simple arithmetic. If there's a raw calculation involved I always tell it to use python to add it all up.
  - enquirewithin 2mo ago
    The abacus seems to date back around 4500 years. If your goal is to implement an absurd comment you can use this one next time: instruct your LLM to implement Conway’s Game of Life to implement an abacus. Because, you know, humans are notoriously poor at implementing the x86-64 instruction set in their minds. This is why God had to create Guido van Rossum. Arguably Mathematica would be a better fit, but there are those who frequent this corner of the Internet who rather not have to read anything that might cause them to think about Stephen Wolfram. So I won’t mention it.
- password4321 2mo ago
  My browser doesn't do the fancy URL text selection... sitzfleisch: the ability to endure or carry on with an activity Something Oppenheimer did not have, apparently.
  - wongarsu 2mo ago
    loaned from German, where it's originally a way to say buttocks, literally "sitting flesh". If you have more Sitzfleisch you can sit for longer. Both in the literal sense (a bigger butt makes sitting more comfortable) and in the figurative sense (having the mental ability to sit for longer, get more desk work done)
    - 2mo ago
ralusek 2mo ago
We're just going to slowly deconstruct every element that could be a factor of intelligence. It's not out-thinking, it's just out-remembering It's not out-thinking, it's just out-working It's not out-thinking, it's just able to consider more things simultaneously It's not creative, it's just randomly generating things and then selecting viable ones
- B-Con 2mo ago
  It's almost as if we're building something that... mimics intelligence.
  - nomel 2mo ago
    Can you mimic intelligence?
    - satisfice 2mo ago
      You just did.
      - MajorTakeaway 2mo ago
        Boooom! Headshot!
- hn_throwaway_99 2mo ago
  But the difference really does matter and is not just a case of "whittling down" what intelligence really is. We have known for a very long time that computers and machines are much faster than humans, more accurate, are scalable in certain ways that humans aren't, and they don't tire. I think most people who are not in the "AI cult" would agree that LLMs and modern generative AI are really just an extension of those faster/more accurate/more scalable and never tiring traits. But there does seem to be (and I'm sure folks much smarter than I have quantified this or described it better than I can) a fundamental difference in how humans think, especially as it applies to what true "understanding" really entails, and for the ability to think up truly novel and unique things that are not just a rejiggering/recombination of training data. I believe those skills really are at the heart of human cognition, and as impressive as LLMs are in replicating what this looks like, there are plenty of "LLM failure modes" where it's clear that LLMs lack a true understanding of concepts or the ability to generate useful, completely novel ideas.
runarberg 2mo ago
In other words: Thousand monkeys with a thousand typewriters... https://news.ycombinator.com/item?id=48231974 https://news.ycombinator.com/item?id=48231974
- scarmig 2mo ago
  Take something like (1+x*y)^3*z+y^2*(1+x*y)*(4+3*x*y);y+3*x*(1+x*y)^2*z+3*x*y^2*(4+3*x*y);2*x-3*x^2*y-x^3*z|0,0,-1/4|1,-3/2,13/2 If a thousand monkeys typed at a character per second, on a keyboard with the 23 relevant characters, it would take roughly 10^136 years for them to come up with this counterexample. Though, to be fair to monkey scenario, there's a large family of them known now, so it's not quite this bad: suppose there are a trillion permutations and similar examples that fit in this string. Then we are down to 10^124 years. If LLMs are monkeys, somehow trained LLM weights allow them to model and prune massive numbers of universes in parallel.
  - awesome_dude 2mo ago
    Just FTR - 1 character per second is glacially slow - it's 12 wpm - fine for (slow) transcription, but the monkey typing exercise doesn't require them to know what they are typing out
    - traes 2mo ago
      How fast do your monkeys type?
      - awesome_dude 2mo ago
        Considering it's random characters being typed, and a skilled typist who is aiming to accurately type words out can hit between 70 and 100 words per minute - I would say that my monkeys could "type" an order of magnitude faster than 1 char per second
andai 2mo ago
Also out-speeding them, and that was before high speed inference. Out-ralphing them, you might say! https://ghuntley.com/ralph/ https://ghuntley.com/ralph/ AGI ≈ artificial stupidity × infinite persistence
jstummbillig 2mo ago
> It's also "out-brute forcing them." That is also approximately what people have always done to succeed.
fooker 2mo ago
Mathematicians routinely spend years on a problem without getting anywhere.
- paulpauper 2mo ago
  It helps though if you have many problems to work on
  - fooker 2mo ago
    You don't, at least traditionally in math research. This will almost surely change with AI.
bellowsgulch 2mo ago
Counterpoint: something has happened in frontier models, and yes they now get discouraged and will sometimes prefer to not continue working on a problem unless you tell them to anyway. I don't know how or why this would be trained on behavior, but no, it isn't true anymore that models don't say things like, "Ugh," or "this is going to take hours and maybe we should stop here."
- Xirdus 2mo ago
  I think it's to combat runaway token usage.

thaumasiotes 2mo ago

> If a mathematician picks a research direction and spends a whole week on it and it doesn't pan out, they will likely be annoyed, need a break for a while, etc. Your timelines are a bit unambitious. There's nobody expecting to make significant progress with a week of work.

nmstoker 2mo ago
They were just illustrating their point, I wouldn't take that literally.
bananaflag 2mo ago
> There's nobody expecting to make significant progress with a week of work. You underestimate my ADHD. Source: I am mathematician.
- dijksterhuis 2mo ago
  Hell, I underestimate my own ADHD. Source: the post-it notes, ALL OF THEM.

EA-3167 2mo ago

The key here is that it’s depending on the human inability to connect the sum of relevant knowledge, but said knowledge comes from humans. Theres going to be this field day of low-hanging fruit that ML can round up, but after that I suspect it will be in fits and starts as a “connection maker” rather than some proof producer.

putlake 2mo ago
It's not only going to be "connection maker". If and when robotics advance to a point where the LLMs are embodied, they can run experiments in the physical world and find new knowledge.
- EA-3167 2mo ago
  Robots in labs already exist, but mercifully they're not hooked up to anything as unpredictable as an LLM. Robots tend to work best as specialists doing high-throughput, extremely repetitive tasks which nonetheless require a degree of precision. Giving a robot a "human" body makes very little sense if we're talking about the needs and productivity of a non-human; humanoid robots are marketing for humans.
  - AustinDev 2mo ago
    Humanoid robots are obviously more than marketing. The entirety of human civilization is human shaped. Making robots that are human shaped is easier and more efficient than redesigning and rebuilding everything that exists.
    - tsimionescu 2mo ago
      > Making robots that are human shaped is easier and more efficient than redesigning and rebuilding everything that exists. In the last 100-200 years, that has been proven wrong at every single step.
      - red75prime 2mo ago
        Generalist humanoid robots that are able to operate in unstructured environments weren't an option (they still aren't an option for the majority of operations). The humanity had no ways of building them. Anyway, it's true that replacing an automated production line with a crowd of generalist robots doesn't make sense. Generalist humanoid robots are intended to replace the remaining human workers.

grebc 2mo ago

Ever heard of string theory. People go whole lives without being able to make it pan out.

tengbretson 2mo ago
String theory is a great example of a dead end kept alive by ego and sunk cost fallacy. An AI would have declared it dead and moved on 10 years earlier.
- hilariously 2mo ago
  Ok Sabina, everyone is string theory is all just a bunch of egotistical morons.
  - chongli 2mo ago
    No, not morons, but people who have built a career on string theory. At this point, even if they regret their decisions, it’s too late to turn back now.
    - smallmancontrov 2mo ago
      As opposed to having built a career complaining about string theory on youtube?
      - chongli 2mo ago
        And that's the reason she's wrong?
        cauch 2mo ago
        You were the one introducing the argument "they are getting advantages out of it so we should be careful to not take what they say as an impartial view". Same can be told of Hossenfelder (personally, I would say that Hossenfelder has shown more clues that indeed she is not very reliable and would prefer caricatural sensationalistic descriptions, which is not what the typical string theory physicist does).

bze12 2mo ago

AI has sitzfleisch https://en.wikipedia.org/wiki/J._Robert_Oppenheimer#:~:text=He%20didn't%20have,was%20fantastic.%5B63%5D https://en.wikipedia.org/wiki/J._Robert_Oppenheimer#:~:text=...

ashleyn 2mo ago
Wow, what a great comparison. LLMs are great at reasoning but absolute dogshit at simple arithmetic. If there's a raw calculation involved I always tell it to use python to add it all up.
- enquirewithin 2mo ago
  The abacus seems to date back around 4500 years. If your goal is to implement an absurd comment you can use this one next time: instruct your LLM to implement Conway’s Game of Life to implement an abacus. Because, you know, humans are notoriously poor at implementing the x86-64 instruction set in their minds. This is why God had to create Guido van Rossum. Arguably Mathematica would be a better fit, but there are those who frequent this corner of the Internet who rather not have to read anything that might cause them to think about Stephen Wolfram. So I won’t mention it.
password4321 2mo ago
My browser doesn't do the fancy URL text selection... sitzfleisch: the ability to endure or carry on with an activity Something Oppenheimer did not have, apparently.
- wongarsu 2mo ago
  loaned from German, where it's originally a way to say buttocks, literally "sitting flesh". If you have more Sitzfleisch you can sit for longer. Both in the literal sense (a bigger butt makes sitting more comfortable) and in the figurative sense (having the mental ability to sit for longer, get more desk work done)
  - 2mo ago

ralusek 2mo ago

We're just going to slowly deconstruct every element that could be a factor of intelligence. It's not out-thinking, it's just out-remembering It's not out-thinking, it's just out-working It's not out-thinking, it's just able to consider more things simultaneously It's not creative, it's just randomly generating things and then selecting viable ones

B-Con 2mo ago
It's almost as if we're building something that... mimics intelligence.
- nomel 2mo ago
  Can you mimic intelligence?
  - satisfice 2mo ago
    You just did.
    - MajorTakeaway 2mo ago
      Boooom! Headshot!
hn_throwaway_99 2mo ago
But the difference really does matter and is not just a case of "whittling down" what intelligence really is. We have known for a very long time that computers and machines are much faster than humans, more accurate, are scalable in certain ways that humans aren't, and they don't tire. I think most people who are not in the "AI cult" would agree that LLMs and modern generative AI are really just an extension of those faster/more accurate/more scalable and never tiring traits. But there does seem to be (and I'm sure folks much smarter than I have quantified this or described it better than I can) a fundamental difference in how humans think, especially as it applies to what true "understanding" really entails, and for the ability to think up truly novel and unique things that are not just a rejiggering/recombination of training data. I believe those skills really are at the heart of human cognition, and as impressive as LLMs are in replicating what this looks like, there are plenty of "LLM failure modes" where it's clear that LLMs lack a true understanding of concepts or the ability to generate useful, completely novel ideas.

runarberg 2mo ago

In other words: Thousand monkeys with a thousand typewriters... https://news.ycombinator.com/item?id=48231974 https://news.ycombinator.com/item?id=48231974

scarmig 2mo ago
Take something like (1+x*y)^3*z+y^2*(1+x*y)*(4+3*x*y);y+3*x*(1+x*y)^2*z+3*x*y^2*(4+3*x*y);2*x-3*x^2*y-x^3*z|0,0,-1/4|1,-3/2,13/2 If a thousand monkeys typed at a character per second, on a keyboard with the 23 relevant characters, it would take roughly 10^136 years for them to come up with this counterexample. Though, to be fair to monkey scenario, there's a large family of them known now, so it's not quite this bad: suppose there are a trillion permutations and similar examples that fit in this string. Then we are down to 10^124 years. If LLMs are monkeys, somehow trained LLM weights allow them to model and prune massive numbers of universes in parallel.
- awesome_dude 2mo ago
  Just FTR - 1 character per second is glacially slow - it's 12 wpm - fine for (slow) transcription, but the monkey typing exercise doesn't require them to know what they are typing out
  - traes 2mo ago
    How fast do your monkeys type?
    - awesome_dude 2mo ago
      Considering it's random characters being typed, and a skilled typist who is aiming to accurately type words out can hit between 70 and 100 words per minute - I would say that my monkeys could "type" an order of magnitude faster than 1 char per second

andai 2mo ago

Also out-speeding them, and that was before high speed inference. Out-ralphing them, you might say! https://ghuntley.com/ralph/ https://ghuntley.com/ralph/ AGI ≈ artificial stupidity × infinite persistence

jstummbillig 2mo ago

> It's also "out-brute forcing them." That is also approximately what people have always done to succeed.

fooker 2mo ago

Mathematicians routinely spend years on a problem without getting anywhere.

paulpauper 2mo ago
It helps though if you have many problems to work on
- fooker 2mo ago
  You don't, at least traditionally in math research. This will almost surely change with AI.

bellowsgulch 2mo ago

Counterpoint: something has happened in frontier models, and yes they now get discouraged and will sometimes prefer to not continue working on a problem unless you tell them to anyway. I don't know how or why this would be trained on behavior, but no, it isn't true anymore that models don't say things like, "Ugh," or "this is going to take hours and maybe we should stop here."

Xirdus 2mo ago
I think it's to combat runaway token usage.