[kijin]

We'll probably be able to tell if and when Yudkowsky's AGI arrives.

Once AI can improve itself, frontier labs will no longer need human developers. So we might see a massive layoff of top talent and a dramatic increase in product quality at the same time. This usually doesn't happen in human businesses. It is also very much against the interest of anyone who is already at the top of the pay table at those labs.

[mirekrusin]

Layoffs would be a poor indicator that recursive self-improvement had occurred as you need people with knowledge around domain/layer the work is done on.

Also, if the lab truly has a self-improving superintelligence, the cost of retaining staff at any level would be a rounding error relative to its operating costs and the value the system creates.

There would be little economic pressure to fire them immediately, especially while they remain useful for oversight, interpretation, risk management or simply as "interface" to the rest of the world etc.

If anything, they would probably hire more people to pursue more opportunities in parallel.

[ben_w]

> Layoffs would be a poor indicator that recursive self-improvement had occurred as you need people with knowledge around domain/layer the work is done on.

This is why I keep saying we can't all agree even on a single letter of "A", "G", and "I".

Before ChatGPT, I would have said "obviously a generally intelligent system can do all the things". While LLMs are much more general than AI before them, the quality of their performance in all the things is distributed in a very un-human-like way.

Some fast-moving optimiser can be a threat well before it stops needing any humans for part of their labour. Cancer and viruses are examples of this: they're the same category of thing as a paperclip optimiser, but for biology instead of manufacturing office supplies.

But some others will argue LLM-spikey isn't "AGI", they'll demand something which reaches the performance of the best human (or the mean human, or the mean domain expert, because we can't agree on "I"), and a standard of "≥ best human" would mean that no, you don't need "people with knowledge around domain/layer the work is done on".

[brookst]

AI is already improving itself. Most / all of the coding harnesses are AI-written.

And yet… there are still people telling AI how to improve itself.

IMO there will always be a level of abstraction at which AI needs guidance. Perhaps ASI means it decides everything on its own, but I don’t think so. Genius humans often excel at the how but not the why, or even the what. So far there’s no indication that AI is different.

[dinfinity]

> AI is already improving itself. Most / all of the coding harnesses are AI-written.

AI has not improved the network topology much yet. The next (and possibly 'last') big thing is enabling AI to come up with something as impactful as the transformer architecture.

[brookst]

It’s a fair point, but I’d argue “AI” is the whole stack, not just model weights. And AI is absolutely improving the whole stack in ways that make it smarter (from a consumer’s perspective).

[simonw]

It's not exactly discovering the transformer, but GPT-5.6 Sol apparently just found optimizations that reduced OpenAI's cost of serving it by 20%: https://twitter.com/reach_vb/status/2082581596608376980

I'm guessing that's hundreds of millions and maybe even billions of dollars per month in savings.