4 ms·

> the worthiness of the adoption was blindingly obvious at that point Everything is so "blindingly obvious" yet nobody can point to ANY serious peer reviewed s

by oblio 4mo ago

> the worthiness of the adoption was blindingly obvious at that point Everything is so "blindingly obvious" yet nobody can point to ANY serious peer reviewed studies that prove it. I'm patient, I'll wait.

TeMPOraL 4mo ago
You don't need peer reviewed studies to tell you water is wet. Peer review is a technique to get evidence from data when SNR is low. It's not "science", it's just a technique. So is "throwing shit at a wall and seeing what sticks". Don't turn techniques into rituals, and science into religion.
- walt_grata 4mo ago
  Vibes are not evidence, neither is a curated demo. You need actual measured evidence that has an adversarial review to actually prove something without falling to confirmation bias.
  - TeMPOraL 4mo ago
    Proof is not binary, it depends on the claim and the constraints you put around it, and the nature of the subject of your claim. Most of the general LLM discourse in our industry is still closer to "proof of the pudding is in the eating" than to "double-blind studies on large cohorts, p<0.01, effect size is still so small that result is useless in practice"[0]. And we're not talking about curated demos either - most of the contested value can be proven for your own specific cases with little to no expenditure of money and time, at a PoC level (it gets more expensive once you try to operationalize it and find kinks that are hard to iron out). And that is, the article claims (and I agree), the point of last 6-12 months of tokenmaxxing policies and top-down push - it's putting pressure on people to actually go and do those PoC-s for themselves, because just giving the opportunity and permission turned out insufficient for significant part of the workforce. -- [0] - Ironically, I remember it was the opposite around the time GPT-4 came out. Back then people talked more about specific claims and demanded measured evidence, because it was hard to get the models to reliably do something interesting. But now that the models can handle bad prompting and can understand you even when you're drunk, suddenly people are denying the general capability of LLMs and asking for randomized control trials. (For double irony, nowadays one can just ask an LLM for randomized trials; the current SOTA models will happily design you a bespoke eval pipeline if you ask them to.)
    - ben_w 4mo ago
      > And that is, the article claims (and I agree), the point of last 6-12 months of tokenmaxxing policies and top-down push - it's putting pressure on people to actually go and do those PoC-s for themselves, because just giving the opportunity and permission turned out insufficient for significant part of the workforce. FWIW, I think most tokenmaxxing is, to riff of what you said earlier, turning a technique into a ritual and science into religion. This isn't specific to AI, we've had it before with pretty much everything in software (and since well before software), from "object-oriented solves every problem" to "clean code [where every function is] two, or three, or four lines long", to reporting your daily kloc, to bounties for every bug reported and/or fixed. Humans do what doomers are afraid AI will do: make a sounds-good utility function (tokens, lines of code, bugs, dead cobras) and get surprised when it is easily gamed for something far less helpful than the vision of whoever set the goal.
- bluGill 4mo ago
  > You don't need peer reviewed studies to tell you water is wet. You don't need a peer reviewed study to tell you that a heavy rock will fall faster than a light rock. Which is why we have peer review even for obvious things.
  - irishcoffee 4mo ago
    > You don't need a peer reviewed study to tell you that a heavy rock will fall faster than a light rock. Either I don't understand gravity, or you might want to pick a different analogy...
    - bluGill 4mo ago
      Aristotle didn't understand gravity like you do, see https://en.wikipedia.org/wiki/Galileo%27s_Leaning_Tower_of_Pisa_experiment https://en.wikipedia.org/wiki/Galileo%27s_Leaning_Tower_of_P....
    - sebastiennight 4mo ago
      I think GP is being sarcastic, and pointing out that 1. "heavy rock falls faster" is what common sense will tell you (I was literally told this by multiple laypeople just a few days ago when sightseeing atop a tall tower) 2. This is disproven by a trivial experiment that nobody thought worthy of trying for millenia 3. therefore we do need peer reviewed studies to confirm even "obvious" knowledge. Also, note that GP's parent post about "water being wet" is quite the subject of contention in scientific and philosophical circles, so that wasn't the best example either.
      - TeMPOraL 4mo ago
        4. And we need.... something? to realize that both "common sense" / "multiple laypeople" and peer-reviewed studies are right. Indeed, as per 2., no one is doing the experiments with rocks of different weight, and sufficient heights to easily measure time of fall. However, people have a lot of everyday experience with feathers, grains, leaves, wood, and rocks, as well as objects of various weight made of metal, paper, plastics. And in everyday experience, the heuristic actually holds out well: lighter stuff falls slower, or gets carried away by the wind. This "heuristic" is purely empirical. You can't disprove it with peer-reviewed studies, because within its scope, it's literally the most basic, purest form of science: direct observation. So in 1., the mistake is that of incorrect generalization. "Lighter stuff falls slower" is correct for everyday experience, it's the "therefore, heavy rock falls faster than light rock" is wrong. Not because it doesn't fall faster, mind you - it does[0] - it's just that everyday experience is dominated by aerodynamic effects, and laypeople sometimes[1] mistakenly assign it to gravity. Which I guess makes it a great analogy for the LLM story. Turns out everyday experience is actually valid in everyday situations. Generalizing from it is usually badly wrong, even if it sometimes arrives at correct answer for wrong reasons (and at wrong scales). Generalization is hard. -- [0] - Surprise. It's actually a heavy idealized particle falls at the same rate as light idealized particle. Actual matter is not an infinitely small point in space, and generates its own gravity field, so the heavy rock will land a tiny bit sooner than the lighter one, because it pulls Earth stronger towards itself - but then only if you drop the test bodies one by one (serially), and not together (in parallel, where the difference cancels out). But then it also turns out the mass canceling out for idealized particles isn't just a mathematical simplification, but a very deep truth about the universe... [1] - Or don't. The question as phrased is, "does heavy rock fall faster than light rock"? This isn't a "specific physics theory question", it's a "real life" question. Treating a positive answer as belief on gravity is an error made by the asker.
- sebastiennight 4mo ago
  > You don't need peer reviewed studies to tell you water is wet. I'm afraid I have bad news for you...
  - oblio 4mo ago
    I guess you mean that physics fact/joke that water isn't wet? It makes things wet.

by oblio 4mo ago

TeMPOraL 4mo ago

You don't need peer reviewed studies to tell you water is wet. Peer review is a technique to get evidence from data when SNR is low. It's not "science", it's just a technique. So is "throwing shit at a wall and seeing what sticks". Don't turn techniques into rituals, and science into religion.

walt_grata 4mo ago
Vibes are not evidence, neither is a curated demo. You need actual measured evidence that has an adversarial review to actually prove something without falling to confirmation bias.
- TeMPOraL 4mo ago
  Proof is not binary, it depends on the claim and the constraints you put around it, and the nature of the subject of your claim. Most of the general LLM discourse in our industry is still closer to "proof of the pudding is in the eating" than to "double-blind studies on large cohorts, p<0.01, effect size is still so small that result is useless in practice"[0]. And we're not talking about curated demos either - most of the contested value can be proven for your own specific cases with little to no expenditure of money and time, at a PoC level (it gets more expensive once you try to operationalize it and find kinks that are hard to iron out). And that is, the article claims (and I agree), the point of last 6-12 months of tokenmaxxing policies and top-down push - it's putting pressure on people to actually go and do those PoC-s for themselves, because just giving the opportunity and permission turned out insufficient for significant part of the workforce. -- [0] - Ironically, I remember it was the opposite around the time GPT-4 came out. Back then people talked more about specific claims and demanded measured evidence, because it was hard to get the models to reliably do something interesting. But now that the models can handle bad prompting and can understand you even when you're drunk, suddenly people are denying the general capability of LLMs and asking for randomized control trials. (For double irony, nowadays one can just ask an LLM for randomized trials; the current SOTA models will happily design you a bespoke eval pipeline if you ask them to.)
  - ben_w 4mo ago
    > And that is, the article claims (and I agree), the point of last 6-12 months of tokenmaxxing policies and top-down push - it's putting pressure on people to actually go and do those PoC-s for themselves, because just giving the opportunity and permission turned out insufficient for significant part of the workforce. FWIW, I think most tokenmaxxing is, to riff of what you said earlier, turning a technique into a ritual and science into religion. This isn't specific to AI, we've had it before with pretty much everything in software (and since well before software), from "object-oriented solves every problem" to "clean code [where every function is] two, or three, or four lines long", to reporting your daily kloc, to bounties for every bug reported and/or fixed. Humans do what doomers are afraid AI will do: make a sounds-good utility function (tokens, lines of code, bugs, dead cobras) and get surprised when it is easily gamed for something far less helpful than the vision of whoever set the goal.
bluGill 4mo ago
> You don't need peer reviewed studies to tell you water is wet. You don't need a peer reviewed study to tell you that a heavy rock will fall faster than a light rock. Which is why we have peer review even for obvious things.
- irishcoffee 4mo ago
  > You don't need a peer reviewed study to tell you that a heavy rock will fall faster than a light rock. Either I don't understand gravity, or you might want to pick a different analogy...
  - bluGill 4mo ago
    Aristotle didn't understand gravity like you do, see https://en.wikipedia.org/wiki/Galileo%27s_Leaning_Tower_of_Pisa_experiment https://en.wikipedia.org/wiki/Galileo%27s_Leaning_Tower_of_P....
  - sebastiennight 4mo ago
    I think GP is being sarcastic, and pointing out that 1. "heavy rock falls faster" is what common sense will tell you (I was literally told this by multiple laypeople just a few days ago when sightseeing atop a tall tower) 2. This is disproven by a trivial experiment that nobody thought worthy of trying for millenia 3. therefore we do need peer reviewed studies to confirm even "obvious" knowledge. Also, note that GP's parent post about "water being wet" is quite the subject of contention in scientific and philosophical circles, so that wasn't the best example either.
    - TeMPOraL 4mo ago
      4. And we need.... something? to realize that both "common sense" / "multiple laypeople" and peer-reviewed studies are right. Indeed, as per 2., no one is doing the experiments with rocks of different weight, and sufficient heights to easily measure time of fall. However, people have a lot of everyday experience with feathers, grains, leaves, wood, and rocks, as well as objects of various weight made of metal, paper, plastics. And in everyday experience, the heuristic actually holds out well: lighter stuff falls slower, or gets carried away by the wind. This "heuristic" is purely empirical. You can't disprove it with peer-reviewed studies, because within its scope, it's literally the most basic, purest form of science: direct observation. So in 1., the mistake is that of incorrect generalization. "Lighter stuff falls slower" is correct for everyday experience, it's the "therefore, heavy rock falls faster than light rock" is wrong. Not because it doesn't fall faster, mind you - it does[0] - it's just that everyday experience is dominated by aerodynamic effects, and laypeople sometimes[1] mistakenly assign it to gravity. Which I guess makes it a great analogy for the LLM story. Turns out everyday experience is actually valid in everyday situations. Generalizing from it is usually badly wrong, even if it sometimes arrives at correct answer for wrong reasons (and at wrong scales). Generalization is hard. -- [0] - Surprise. It's actually a heavy idealized particle falls at the same rate as light idealized particle. Actual matter is not an infinitely small point in space, and generates its own gravity field, so the heavy rock will land a tiny bit sooner than the lighter one, because it pulls Earth stronger towards itself - but then only if you drop the test bodies one by one (serially), and not together (in parallel, where the difference cancels out). But then it also turns out the mass canceling out for idealized particles isn't just a mathematical simplification, but a very deep truth about the universe... [1] - Or don't. The question as phrased is, "does heavy rock fall faster than light rock"? This isn't a "specific physics theory question", it's a "real life" question. Treating a positive answer as belief on gravity is an error made by the asker.
sebastiennight 4mo ago
> You don't need peer reviewed studies to tell you water is wet. I'm afraid I have bad news for you...
- oblio 4mo ago
  I guess you mean that physics fact/joke that water isn't wet? It makes things wet.