Failing to Understand the Exponential, Again • Hacker News Board

Re: Failing to Understand the Exponential, Again

#11

Post by IshKebab » Sun, Sep 28, 2025, 2:06 PM UTC

> Again we can observe a similar trend, with the latest GPT-5 already astonishingly close to human performance:

Yes but only if you measure "performance" as "better than the other option more than 50% of the time" which is a terrible way to measure performance, especially for bullshitting AI.

Imagine comparing chocolate brands. One is tastier than the other one 60% of the time. Clear winner right? Yeah except it's also deadly poisonous 5% of the time. Still tastier on average though!

Re: Failing to Understand the Exponential, Again

#12

Post by konmok » Sun, Sep 28, 2025, 2:08 PM UTC

As they say, every exponential is a sigmoid in disguise. I think the exponential phase of growth for LLM architectures is drawing to a close, and fundamentally new architectures will be necessary for meaningful advances.

I'm also not convinced by the graphs in this article. OpenAI is notoriously deceptive with their graphs, and as Gary Marcus has already noted, that METR study comes with a lot of caveats: [https://garymarcus.substack.com/p/the-latest-ai-scaling-grap...]

Re: Failing to Understand the Exponential, Again

#13

Post by airstrike » Sun, Sep 28, 2025, 2:08 PM UTC

Failing to understand the sigmoid, again

Re: Failing to Understand the Exponential, Again

#14

Post by ttoinou » Sun, Sep 28, 2025, 2:09 PM UTC

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…

Yes exponential is only an approximation of the first part of S curves. And this author claims that he understands the exponential better than others…

Re: Failing to Understand the Exponential, Again

#15

Post by ctrlp » Sun, Sep 28, 2025, 2:11 PM UTC

Where in nature/reality do we actually see exponential trends continued long? It seems like they typically encounter a governing effect quite quickly.

Re: Failing to Understand the Exponential, Again

#16

Post by k__ » Sun, Sep 28, 2025, 2:12 PM UTC

I didn't plot it, but I had the impression the Aider benchmark success rates for SOTA over time were a hockey curve.

Like the improvements between 60 and 70 felt much faster than those between 80 and 90.

Re: Failing to Understand the Exponential, Again

#17

Post by smohare » Sun, Sep 28, 2025, 2:14 PM UTC

HexDecOctBin wrote: post #6

Exponential curves don't last for long fortunately, or the universe would have turned into a quark soup. The example of COVID is especially ironic, considering it stopped being a real concern within 3 years of its advent despite the exponential growth in the early years. Those who understand exponentials should also try to understand stock and flow.

Stopped being a concern primarily due to heavy vaccination campaigns though. It is still raging, just not nearly as many people are dying. The immunity from infection these days is pretty paltry.

Re: Failing to Understand the Exponential, Again

#18

Post by cs702 » Sun, Sep 28, 2025, 2:15 PM UTC

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…

Yes. It's true that we don't know, with any certainty, (1) whether we are hitting limits to growth intrinsic to current hardware and software, (2) whether we will need new hardware or software breakthroughs to continue improving models, and (3) what the timing of any necessary breakthroughs, because innovation doesn't happen on a predictable schedule. There are unknown unknowns.[a]

However, there's no doubt that at a global scale, we're sure trying to maintain current rates of improvement in AI. I mean, the scale and breadth of global investment dedicated to improving AI, presently, is truly unprecedented. Whether all this investment is driven by FOMO or by foresight, is irrelevant. The underlying assumption in all cases is the same: We will figure out, somehow, how to overcome all known and unknown challenges along the way. I have no idea what the odds of success may be, but they're not zero. We sure live in interesting times!

---

[a] https://en.wikipedia.org/wiki/There_are_unknown_unknowns

Re: Failing to Understand the Exponential, Again

#19

Post by entee » Sun, Sep 28, 2025, 2:16 PM UTC

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 contained tasks that take ~1 day of work. That means at least one of a few things could be true:

1. The tasks aren’t defined in a way that makes real world sense

2. The tasks require iteration, which wasn’t tested, for real world success (as many tasks do)

I think while interesting and a very worthy research avenue, this paper is only the first in a still early area of understanding how AI will affect with the real world, and it’s hard to project well from this one paper.

https://cdn.openai.com/pdf/d5eb7428-c4e9-4a33-bd86-86dd4bcf1...

Re: Failing to Understand the Exponential, Again

#20

Post by nkrisc » Sun, Sep 28, 2025, 2:18 PM UTC

HexDecOctBin wrote: post #6

Exponential curves don't last for long fortunately, or the universe would have turned into a quark soup. The example of COVID is especially ironic, considering it stopped being a real concern within 3 years of its advent despite the exponential growth in the early years. Those who understand exponentials should also try to understand stock and flow.

Reminds me a bit of the "ultraviolet catastrophe".

> The ultraviolet catastrophe, also called the Rayleigh–Jeans catastrophe, was the prediction of late 19th century and early 20th century classical physics that an ideal black body at thermal equilibrium would emit an unbounded quantity of energy as wavelength decreased into the ultraviolet range.

[...]

> The phrase refers to the fact that the empirically derived Rayleigh–Jeans law, which accurately predicted experimental results at large wavelengths, failed to do so for short wavelengths.

https://en.wikipedia.org/wiki/Ultraviolet_catastrophe