[le-mark]

Nausea aside, what evidence does anyone have that “super intelligence” of the sort your argument alludes to is even possible? Because that’s what we’re really talking about; greater than human intelligence on this sort of academic task. For example; When llms start contributing meaningfully to their own development, that would be a convincing indicator imo.

[jeremyjh]

This discussion is not about superintelligence, it is about continued progress. Fully general human intelligence at much lower cost than humans is all that is required to profoundly reshape society, but it is not clear even that will happen soon.

As the blog points out - this is one particular subfield where LLMs have much easier prospects - lots of low hanging fruit that “just” requires a couple weeks of PHD candidate research.

Mathematics itself is one of a small handful of endeavors where automated reinforcement training is extremely straightforward and can be done at massive scale without humans.

Neither of these factors place a structural bound on the kind of thing LLMs can be good at, but we are far from certain we can achieve performance at this level in other fields economically and in the near future.

[programjames]

Well, a decent GPU runs on 20x the wattage of a human brain. That's evidence humans are constrained in ways artificial intelligences will not be.

[filipn]

You're comparing a gpu to a human brain?

[sesteel]

Why wouldn't you? From both emerge intelligence.

[bdangubic]

> When llms start contributing meaningfully to their own development, that would be a convincing indicator imo.

This has been the case for awhile now already…

https://kersai.com/the-48-hours-that-changed-ai-forever-clau...

[le-mark]

> The model essentially served as an on-call teammate across MLOps and DevOps tasks, compressing feedback cycles that typically consume expert time

I personally would not characterize automating training processes as “meaningfully”.

[eiieue]

And yet the world hasn’t changed all that much except people getting laid off in response to over-hiring prior to the diffusion of llm’s.

[daishi55]

> over-hiring

For how long should you be allowed to use this excuse? It’s nearly 5 years since the peak of COVID hiring. What’s an acceptable limit - 10 years? Of course at that point you can just switch over to outsourcing and “stupid MBAs”, the other two of Reddit’s favorite scapegoats. I find a lot of the AI skepticism to be totally unfalsifiable.

[wtetzner]

> I find a lot of the AI skepticism to be totally unfalsifiable.

A lot of the discourse around AI in general is unfalsifiable. It's just a bunch of people "predicting" the future. Seems smarter to just avoid making assumptions about it at this point.

[daishi55]

I don’t make predictions about the future. But in reality, LLMs have already profoundly changed the world, including software development and tech industry.

The people who pretend that’s not the case are not living in reality. To them - let’s call them “ed Zitron readers” - there is no evidence that could change their view that none of this is really happening, it’s all hype, and the collapse is just around the corner, after which we’ll all go back to normal and LLMs will sound like a bad dream.

[bdangubic]

facts!

but we can see trends and for your livehoood it is important to be able to make educated predictions based on trends. not saying everyone should start making AI predictions (though many already do)

[oblio]

And the same can be said for AI exuberance.

Yes, LLMs are a great technology. Yes, we will probably all use them all the time in 20 years. No, we don't know how we will use them (to generate cat memes or to cure cancer) in 20 years time.

Especially for software developers it looks increasingly that after huge turmoil it's likely we will need +/- the same number of developers in the world.

[bdangubic]

> Especially for software developers it looks increasingly that after huge turmoil it's likely we will need +/- the same number of developers in the world.

what exactly are you basing this opinion on? All I am seeing personally across multiple projects I am working on and other friends at other places is that downsizing is either begun or is planned (to exclude from here all the “public” layoffs we see on the news). Given how most business operate in the USA I think most of “AI strategies” are “we can do same with -40% staff” vs. “we can do XX% more work with same staff.”

[jrumbut]

The past couple of years have been chaotic and fearful. Hopefully that won't last forever.

If we can get a little stability, people will begin thinking less in terms of "how do we do the same thing cheaper" and more in terms of "how do we do new things."