When you're on that curve, it's indistinguishable until you hit the plateau. We're in an era where AI is continuing to improve and has already surpassed a level that many people doubted was achievable. Nobody knows when that progress will plateau. It's entirely possible that we plateau _after_ surpassing human-level intelligence.

If you have actual data you can take the derivative of the curve and see you're on the S curve with a lot of confidence by the time you hit the middle and long before the plateau: https://miro.medium.com/max/700/1*6A3A_rt4YmumHusvTvVTxw.png

Even small errors in measurement will greatly change the location of the projected plateau so this is not usually useful in practice.

Exactly correct. We really don't know if the progress is exponential or like a Sigmoid squashing function. You just changed my opinion, a bit, on this.

If we're limited to Earth and fossil fuels, then it's a sigmoid.

The AI technology today has practical value for some use cases but it's basically just clever parlor tricks. There has been near zero discernable progress toward artificial general intelligence. We don't yet have a computer that can learn and make optimal resource usage decisions in an open world environment as well as a mouse. In most respects we're not even at the insect level yet.

You're making the point that the linked article is trying to argue against.

How good is this model at fighting other insects?

> The AI technology today has practical value for some use cases but it's basically just clever parlor tricks.

Come on, you could have said the same thing about excel 30 years ago.

Yes Excel has more features today. So what? We're still not making any measurable progress towards true AGI. We don't even know what the development path or ultimate goal looks like except for some vague hand waving about passing the Turing Test.

I work for a company that provides "ai" services in a "boring" domain. The Time saved and accuracy (for a legally audited result) we provide is quantifiable, and when I saw the numbers I was surprised. So while a lot of the "AI" hype is stupid marketing bs, some of us are actually doing real stuff, it's not just parlor tricks. You might also be surprised in how many domains a small improvement has huge yield in terms of raw money and/or quality of life improvements.

The steep part of a sigmoid curve DOES grow almost exponentially though. What's the point of saying this? It's like saying, "sure we are making great progress, but eventually the universe will come to an end and we'll all be dead." Who cares? Why not worry about that when we're there?

The point is that it is a completely different framework to think about the future.

The exponential model is something close than what is behind Ray Kurzweil reasoning about the Great Singularity and how the future will be completely different and we're all going to be gods or immortals or doomed or something dramatic in that vein.

The S-Curve is more boring, it means that the future of computing technology might not be that mind blowing after all, we might already have reaped most of the low-hanging fruits.

A bit like airplanes, or space tech you know, have you seen those improving by a 10x factor recently?

>A bit like airplanes, or space tech you know, have you seen those improving by a 10x factor recently?

Is space tech included ironically here? There's been 10x (or more) improvements across dozens of space tech problems in the last couple decades.

Could we send people on the Moon if we wanted? We might but I am honestly not completely sure.

Would that be 1000x, 100x or even 10x easier than 60 years ago? Well, I don't think so.

From my perspective space tech has never quite leaved the prototype phase, for some reason.

No one knows the future for sure. But with current trend of dividing the world again, I would agree on your assumption.

But I still have hope for a undivided world, that one day even abolish the patent system. Then I would see potential for exponentional progress.

100% this. Exponential progress is only a thing if potential progress is infinite. If the potential progress is finite (hint: it is), eventually the rate of progress hit progressively diminishing returns.

What is the limit you foresee on computation, especially when such computations can optimise themselves without human intervention?

The underlying rule here, in my opinion, is the law of diminishing returns. (log shaped curve)

AlphaZero is already capable of optimizing itself in the limited problem space of Chess.

Infinitely increasing the computing power of this system won't give it properties it does not already have, there is no singularity point to be found ahead.

And I am not sure that there are any singularities lying ahead in any other domains with the current approach of ML/AI.

And building on that, the real bottleneck in most domains isn't going to be computer power, it's going to be human understanding of how to curate data or tweak parameters.

We've already seen in games with simple rules and win conditions that giving computers data on what we think are good human games can make them perform worse than not giving them data. Most problems aren't possible for humans to ebncapsulate perfectly in a set of rules and win conditions to just leave the processing power to fill in the details, and whilst curating data and calibrating learning processes is an area we've improved hugely on to get where we are with ML, it's not something where human knowledge seems more likely to reach an inflection point than hit diminishing returns.

We've seen with ML and Chess (an go to some extent) that brute forcing the problem space is clever than using heuristics.

I think this is only true because, so far, our heuristics are not that clever.

But, godlike though the human variants may appear to be, what happens when the system reaches the skill level of an above-average software architect?

There are physical limits to computation.

The number of orders of magnitude remaining, is not that large.

There is no such thing as truly unbounded exponential growth, it's always an S curve