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PaperclipPerfector  12d ago (text post)   28333 thread views

Culture War Roundup for the week of January 6, 2025

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OpenAI had what seemed like a 'comfortable' lead for about a year there, but if progress had remained exponential or even linear from the past models they should be running away with the game. Instead the other close competitors seem to be chomping steadily away at their lunch.

"When you see exponential, think logistic" seems to remain a useful rule-of-thumb. (I'm not sure of the source; I find only me when I search but I know I didn't originate it)

Maybe O'Reilly's "It's not exponential, it's sigmoidal"? https://web.archive.org/web/20240114184321/http://radar.oreilly.com/archives/2007/11/sigmoidal-not-exponential.html

I feel like I've seen your snappier version elsewhere, though. Maybe it's an echo of "When you hear hoofbeats, think horses, not zebras."

The tricky bit seems to be that it's very difficult to know where you're on on a logistic curve until you're past the midpoint. Though with the limits of pre-training people started running into last year, the claim that we're on still clearly on the left side is more tenuous.

Yep. I may be wrong but I seem to recall that there was a brief period of time where a lot of folks in the space did genuinely think improvements would continue to follow the exponential curve even if individual jumps between new models were a little smaller.

Or at least were willing to hype it that way. I'm prepared to be corrected if my memory is faulty there.

There was certainly a 'vibe' that we might have activated the fast takeoff scenario.

For what it's worth, this is still the vibe, indeed more than ever, and I do not understand what was the change you're implying you have noticed. After o3, the consensus of all top lab researchers seems to be "welp we're having superintelligence in under 5 years".

I guess I'd call it a bifurcation.

I read the material that suggests all the pieces are in place to achieve superintelligence.

But I'm also reading reports that the most recent training runs are seeing diminishing returns. So making the models BIGGER isn't giving the same results.

Which certainly explains why OpenAI hasn't pushed ChatGPT5 out the door, if it can't demonstrate as significant an improvement as 3-4 was.

So improvements and tweaks to existing models are giving us gains in the meantime, it isn't very clear to me where the quantum leap that will enable true AGI/Superintelligence is hiding. Which is more a me issue, I'm certainly not an insider. I'm just seeing two sides, those who think moar compute is good enough, and those who think its going to take some tricky engineering.

And Altman sure isn't telling us what he's seeing. So my question is whether he's playing cards close to the vest to avoid popping the hype bubble or because he really thinks he's going to blow us away with the next product. Possibly blow us away in the most literal meaning of the word.

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