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by reinitctxoffset 13 days ago
As a vocal advocate for the use of machine intelligence in certain contexts and a skeptic of claims they are useless or always hallucinate or whatever...

It hasn't been even close to even the recent claims! It's been like three straight years where it was supposed to utterly transform society any minute now.

I think we more or less have a fragile consensus that in like, computer programming and really very little else, that on a good day you're probably going to come out ahead with the AI assist. That seems relatively uncontroversial now. But it also seems like success with AI is largely about working hard to get good at it, as a first order concern. It is not at all obvious that blind, uncritical use by anyone is a net win.

It's pretty unclear, sone might say dubious, that anyone has made serious, aboveboard money net of debt and equity, other than the hardware vendors. There's some pretty serious revenue, but it's a drop in the proverbial bucket against the outlay. There like a two trillion dollar balance sheet hole in the US alone where investment into AI has gone.

While I personally don't agree with them, multiple S-tier machine learning researchers think we've got our wheels stuck in the mud, that autoregressive decoder architectures on a tokin-suffix pre-train is tapped out as a paradigm.

It's ok to say "AI is starting to get useful in pretty durable ways" and not sound like an Anthropic shareholder/employee, i.e. completely full of shit.

1 comments

Uncritical use of today's AI beats all of the optimized use of yesterday's AI by far. I think people like the idea that their success is a result of their efforts, but this is just not the truth.
I don't think anyone's disputing that the models are better than a year ago (though clearly all this, recursive self improvement stuff is utterly hypothetical and that's being generous, most of the progress has been on cost and fit and finish stuff). When it's on the plan, I'll use Fable for some stuff. If I'm paying for Opus? It's 4.5 or 4.6 which were dramatically better aligned and token efficient in the trace at a capability gap that's "you win some and lose some".

That can be true while it also being the case that to someone who has no idea how this stuff works under the hood, it's basically Dunning Kreuger in a box. The next person to go /u/PhdInEverything on me with Fable is getting an education in the history of hardware support for mixed precision training or something. Fable is a masterclass in refusal to ground and a dozen other alignment catastrophes.

So yeah, the models are still getting a little better, but from here out I think it's rapidly becoming a skill game.