unfortunately, ai is not search or social. there are no network-effects here. so, get-big-fast is not going to work. and slowly the masses start waking up and asking what the hell is this good for except as a fancy auto-complete.
So there's this thread of taking two assumptions at face value I see a lot here and elsewhere:
1. What we call "AI" now is actually some kind of AI, and the rest is just scaling up.
2. It's inevitable that AGI would conform to sci-fi tropes.
Meanwhile we've been watching BILLIONS spent on data centers, power for data centers, water for data centers... all of that going in one end, and LLM's coming out the other.
As long as the future AI overlord requires enough power and water to run a city, and the best it can manage amounts to a fun show, I'll keep my alarmism in check.
But Altman, man he really know his audience, and he's going to sell sell sell, to an audience that's been primed on fiction and religion to believe in him like some kind of blank-faced prophet.
We're in Feb '25. ARC-AGI (at least the version they're referencing) already has been solved by AI at above average human level.
>everything points to incremental progress with signs of diminishing returns.
Seems like everything in just Dec '24/ Jan '25 points the other way. These models are already helping PhDs in novel research, they're already getting super human at coding (yes yes, they're not perfect and I'm sure someone on HN has this weird coding job that AI can't replace yet and they're very excited to shit over AI), but they've already replaced a lot of real software dev jobs.
Also aren't you contradicting yourself?
> everything points to incremental progress with signs of diminishing returns
> corporation replacing employees with AI
If we have incremental progress, how are corporations going to replace employees with AI?
They're getting super-human at _competitive coding_, which is essentially identifying and writing algorithms. They _are not_ good at general coding, as demonstrated by their subpar scores at benchmarks like SWE-bench, and even those aren't particularly representative of what a real coding job is.
The last few models have remarkably improved on SWE-bench too. o3 scores 73%, this number was in the low teens 16 months ago. Willing to wager that SWE benchmark gets saturated before the end of 2025.
> aren't particularly representative of what a real coding job
I don't know about that, large swath of "real world" coding is writing plumbing and UIs for CRUD apps, they're getting really good at that as well. Anecdotally, engineers I know have gotten insanely productive with tools like Cursor.
PhD novel research ? What is the novel research discovered by an LLM ever since the emergence of ChatGPT ? None. Despite all the knowledge these models accumulate in their weights they haven't been able to connect the dots and discover a lot of things humans haven't discovered, autonomously.
Replace which software engineering job ? They are useful, sure; good at benchmarks, yes; but not a drop in replacement of any software engineer.
That's not what he is saying. He is saying that this investment in AI will yield incredible returns and power. The investor will dominate the next decade(s) and thus you should invest. Of course, he has to say it in a careful way not to alarm politically correct people. But, in essence, he is trying to create investor FOMO to drive his next round.
> 1. The intelligence of an AI model roughly equals the log of the resources used to train and run it.