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Failing to Understand the Exponential, Again

julian.ac

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Re: Failing to Understand the Exponential, Again

#171

Post by bwfan123 »

doug_durham wrote: post #101

The 50% success rate is the problem. It means you can’t reliably automate tasks unattended. That seems to be where it becomes non-exponential. It’s like having cars that go twice as far as the last year but will only get you to your destination 50% of the time.

> It’s like having cars that go twice as far as the last year but will only get you to your destination 50% of the time

Nice analogy. All human progress is based on tight-abstractions describing a well-defined machine model. Leaky abstractions with an undefined machine are useful too but only as recommendations or for communication. It is harder to build on top of them. Precisely why programming in english is a non-starter - or - just using english in math/science instead of formalism.

Re: Failing to Understand the Exponential, Again

#172

Post by Nevermark »

I don't think I have ever seen a page on HN where so many people missed the main point.

The phenomenon of people having trouble understanding the implications of exponential progress is really well known. Well known, I think, by many people here.

And yet an alarming number of comments here interpret small pauses as serious trend breakers. False assumptions that we are anywhere near the limits of computing power relative to fundamental physics limits. Etc.

Recent progress, which is unprecedented in speed looking backward, is dismissed because people have acclimatized to change so quickly.

The title of the article "Failing to Understand the Exponential, Again" is far more apt than I could have imagined, on HN.

See my other comments here for specific arguments. See lots of comments here for examples of those who are skeptical of a strong inevitability here.

The "information revolution" started the first time design information was separated from the thing it could construct. I.e. the first DNA or perhaps RNA life. And it has unrelentingly accelerated from there for over 4.5 billion years.

The known physics limits of computation per gram are astronomical. We are nowhere near any hard limit. And that is before any speculation of what could be done with the components of spacetime fragments we don't understand yet. Or physics beyond that.

The information revolution has hardly begun.

With all humor, this was the last place I expected people to not understand how different information technology progresses vs. any other kind. Or to revert to linear based arguments, in an exponentially relevant situation.

If there is any S-curve for information technology in general, it won't be apparent until long after humans are a distant memory.

Re: Failing to Understand the Exponential, Again

#173

Post by danlitt »

oofbey wrote: post #163
danlitt wrote: post #142

I am constantly astonished that articles like this even pass the smell test. It is not rational to predict exponential growth just because you've seen exponential growth before! Incidentally, that is not what people did during COVID, they predicted exponential growth for reasons . Specific, articulable reasons, that consisted of more than just "look, like go up. line go up more?". Incidentally, the benchmarks quoted…

"It’s Difficult to Make Predictions, Especially About the Future" - Yogi Berra. It's funny because it's true. So if you want to try to do this difficult task, because say there's billions of dollars and millions of people's livelihoods on the line, how do you do it? Gather a bunch of data, and see if there's some trend? Then maybe it makes sense to extrapolate. Seems pretty reasonable to me. Definitely passes the sni…

It's a stupid concept because it's behind every ponzi scheme.

Re: Failing to Understand the Exponential, Again

#174

Post by insane_dreamer »

crazygringo wrote: post #7

> Given consistent trends of exponential performance improvements over many years and across many industries, it would be extremely surprising if these improvements suddenly stopped. I'm sure people were saying that about commercial airline speeds in the 1970's too. But a lot of technologies turn out to be S-shaped, not purely exponential, because there are limiting factors. With LLM's at the moment, the limiting fac…

> I'm sure people were saying that about commercial airline speeds in the 1970's too.

They were also saying that about CPU clock speeds.

Re: Failing to Understand the Exponential, Again

#175

Post by insane_dreamer »

> The evaluation tasks are sourced from experienced industry professionals (avg. 14 years' experience), 30 tasks per occupation for a total of 1320 tasks. Grading is performed by blinded comparison of human and model-generated solutions, allowing for both clear preferences and ties.

It's important to carefully scrutinize the tasks to understand they actually reflect tasks that are unique to industry professionals. I just looked quickly at the nursing ones (my wife is a nurse) and half of them were creating presentations, drafting reports, and the like, which is the primary strength of LLMs but a very small portion of nursing duties.

The computer programming tests are more straightforward. I'd take the other ones with a grain of salt for now.

Re: Failing to Understand the Exponential, Again

#176

Post by viernullvier »

drc500free wrote: post #41
entee wrote: post #19

A lot of this post relies on the recent open ai result they call GDPval (link below). They note some limitations (lack of iteration in the tasks and others) which are key complaints and possibly fundamental limitations of current models. But more interesting is the 50% win rate stat that represents expert human performance in the paper. That seems absurdly low, most employees don’t have a 50% success rate on self con…

That's not 50% success rate at completing the task, that's the win rate of a head-to-head comparison of an algorithm and an expert. 50% means the expert and the algorithm each "win" half the time.

For the METR rating (first half of the article), it is indeed 50% success rate at completing the task. The win rate only applies to the GDPval rating (second half of the article).

Re: Failing to Understand the Exponential, Again

#177

Post by airstrike »

jsnell wrote: post #43
crazygringo wrote: post #7

> Given consistent trends of exponential performance improvements over many years and across many industries, it would be extremely surprising if these improvements suddenly stopped. I'm sure people were saying that about commercial airline speeds in the 1970's too. But a lot of technologies turn out to be S-shaped, not purely exponential, because there are limiting factors. With LLM's at the moment, the limiting fac…

Indeed you can't be sure. But on the other hand a bunch of the commentariat has been claiming (with no evidence) that we're at the midpoint of the sigmoid for the last three years. They were wrong. And then you had the AI frontier lab insiders who predicted an accelerating pace of progress for the last three years. They were right. Now, the frontier labs rarely (never?) provide evidence either, but they do have about…

> And then you had the AI frontier lab insiders who predicted an accelerating pace of progress for the last three years.

Progress has most definitely not been happening at an _accelerating_ pace.

Re: Failing to Understand the Exponential, Again

#178

Post by tim333 »

Nevermark wrote: post #172

I don't think I have ever seen a page on HN where so many people missed the main point. The phenomenon of people having trouble understanding the implications of exponential progress is really well known. Well known, I think, by many people here. And yet an alarming number of comments here interpret small pauses as serious trend breakers. False assumptions that we are anywhere near the limits of computing power relat…

I'm a little surprised too. A lot of the arguments are along the lines of but LLMs aren't very good. But really LLMs are a brief phase in the information revolution you mention that will be superseded.

To me saying we won't get AGI because LLMs aren't suitable is like saying we were not going to get powered flight because steam engines weren't suitable. Fair enough they weren't but they got modified into internal combustion engines and then were. Something like that will happen.

Re: Failing to Understand the Exponential, Again

#179

Post by szatkus »

Tenemo wrote: post #104
coldtea wrote: post #39

> People notice that while AI can now write programs, design websites, etc, it still often makes mistakes or goes in a wrong direction, and then they somehow jump to the conclusion that AI will never be able to do these tasks at human levels, or will only have a minor impact. When just a few years ago, having AI do these things was complete science fiction! Both things can be true, since they're orthogonal. Having AI…

I agree with all your points, just wanted to say that transistor count is probably a counter example. We have been keeping with the Moore's Law more or less[1] and M3 Max, a 2023 consumer-grade CPU, has ~100B of transistors, "just" one order of magnitude away from yout 1T. I think that shows we haven't stagnated much in transistor density and the progress is just staggering! [1] https://en.m.wikipedia.org/wiki/Transi…

That one order of magnitude is about 7 years behind the Moore's Law. We're still progressing but it's slower, more expensive and we hit way more walls than before.

Re: Failing to Understand the Exponential, Again

#180

Post by mmcnl »

theptip wrote: post #98
crazygringo wrote: post #7

> Given consistent trends of exponential performance improvements over many years and across many industries, it would be extremely surprising if these improvements suddenly stopped. I'm sure people were saying that about commercial airline speeds in the 1970's too. But a lot of technologies turn out to be S-shaped, not purely exponential, because there are limiting factors. With LLM's at the moment, the limiting fac…

> a lot of technologies turn out to be S-shaped, not purely exponential, because there are limiting factors. Yes of course it’s not going to increase exponentially forever. The point is, why predict that the growth rate is going to slow exactly now? What evidence are you going to look at? It’s possible to make informed predictions (eg “Moore’s law can’t get you further than 1nm with silicon due to fundamental physica…

It has already been trained on all the data. The other obvious next step is to increase context window, but that's apparently very hard/costly.
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