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Failing to Understand the Exponential, Again

julian.ac

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Re: Failing to Understand the Exponential, Again

#41

Post by drc500free »

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.

Re: Failing to Understand the Exponential, Again

#42

Post by lapcat »

It should be noted that the article author is an AI researcher at Anthropic and therefore benefits financially from the bubble: https://www.julian.ac/about/

> The current discourse around AI progress and a supposed “bubble” reminds me a lot of the early weeks of the Covid-19 pandemic. Long after the timing and scale of the coming global pandemic was obvious from extrapolating the exponential trends, politicians, journalists and most public commentators kept treating it as a remote possibility or a localized phenomenon.

That's not what I remember. On the contrary, I remember widespread panic. (For some reason, people thought the world was going to run out of toilet paper, which became a self-fulfilling prophesy.) Of course some people were in denial, especially some politicians, though that had everything to do with politics and nothing to do with math and science.

In any case, the public spread of infectious diseases is a relatively well understood phenomenon. I don't see the analogy with some new tech, although the public spread of hype is also a relatively well understood phenomenon.

Re: Failing to Understand the Exponential, Again

#43

Post by jsnell »

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 a year of visibility into the pipeline, unlike anyone outside.

So at least my heuristic is to wait until a frontier lab starts warning about diminishing returns and slowdowns before calling the midpoint or multiple labs start winding down capex. The first component might have misaligned incentives, but if we're in a realistic danger of hitting a wall in the next year, the capex spending would not be accelerating the way it is.

Re: Failing to Understand the Exponential, Again

#45

Post by fhe »

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 am getting the sense that the 2nd deriative of the curve is already hitting negative teritory. models get updated, and I don't feel I'm getting better answers from the LLMs.

On the application front though, it feels that the advancements from a couple of years ago are just beginning to trickle down to product space. I used to do some video editing as a hobby. Recently I picked it up again, and was blown away by how much AI has chipped away the repetitive stuff, and even made attempts at the more creative aspects of production, with mixed but promising results.

Re: Failing to Understand the Exponential, Again

#46

Post by analog31 »

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.

It's possible to understand both exponential and limiting behavior at the same time. I work in an office full of scientists. Our team scrammed the workplace on March 10, 2020.

To the scientists, it was intuitively obvious that the curve could not surpass 100% of the population. An exponential curve with no turning point is almost always seen as a sure sign that something is wrong with your model. But we didn't have a clue as to the actual limit, and any putative limit below 100% would need a justification, which we didn't have, or some dramatic change to the fundamental conditions, which we couldn't guess.

The typical practice is to watch the curve for any sign of a departure from exponential behavior, and then say: "I told you so." ;-)

The first change may have been social isolation. In fact that was pretty much the only arrow in our quivers. The second change was the vaccine, which changed both the infection rate and the mortality rate, dramatically.

Re: Failing to Understand the Exponential, Again

#47

Post by analog31 »

nkrisc wrote: post #20
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 Ray…

Right. Nobody believed that the intensity would go to infinity. What they believed was that the theory was incomplete, but they didn't know how or why. And the solution required inventing a completely new theory.

Re: Failing to Understand the Exponential, Again

#48

Post by zwnow »

hnlmorg wrote: post #30

Just because something exhibits an exponential growth at one point in time, that doesn’t mean that a particular subject is capable of sustaining exponential growth. Their Covid example is a great counter argument to their point in that covid isn’t still growing exponentially. Where the AI skeptics (or even just pragmatists, like myself) chime in is saying “yeah AI will improve. But LLMs are a limited technology that…

> Just because something exhibits an exponential growth at one point in time, that doesn’t mean that a particular subject is capable of sustaining exponential growth.

Which is pretty ironic given the title of the post

Re: Failing to Understand the Exponential, Again

#49

Post by yojo »

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…

Capex requirements might be on a different curve than model improvements.

E.g. you might need to accelerate spending to get sub-linear growth in model output.

If valuations depend on hitting the curves described in the article, you might see accelerating capex at precisely the time improvements are dropping off.

I don’t think frontier labs are going to be a trustworthy canary. If Anthropic says they’re reaching the limit and OpenAI holds the line that AGI is imminent, talent and funding will flee Anthropic for OpenAI. There’s a strong incentive to keep your mouth shut if things aren’t going well.

Re: Failing to Understand the Exponential, Again

#50

Post by marginalia_nu »

_fizz_buzz_ wrote: post #21
ttoinou wrote: post #14

Earlier quoted context omitted.

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…

That is even true for covid for obvious reasons, because Covid runs out of people it can infect at some point.

Infectious diseases rarely see actual exponential growth for logistical reasons. It's a pretty unrealistic model that ignores that the disease actually needs to find additional hosts to spread, the local availability of which starts to go down from the first victim.
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