This long-winded screed appears to be an AI proselytizer trying to convince people that, no, actually, you're just holding the model wrong if you don't believe they're exponentially growing in intelligence every generation. The proof? His react client.

I'm pretty confused by most of the article.

The focus is placed on "AI Literacy", but it seems to use this to just mean 'volume of AI use'. The discussion of the Netflix case study is extra perplexing, since the summary here admits they didn't find any actual productivity improvement, just that only a few hours of "training" could induce on the order of $50/person/day on tokens.

That seems... the opposite of literacy?

I found a lot of interesting, if speculative, thoughts in the article, but...

> Superhuman means unverifiable

is not true for at least large classes of problems. The recent solution of the "unit distance" problem comes to mind, or any future AI-solved math problem that was beyond the capabilities of humans. You can tell it's superhuman (it's doing things humans can't) and you can easily verify its results are correct.

For other classes of problems (eg, policy suggestions for large scale systems like the economy), the point is fair.

GPT-2 was already extremely dangerous.

Far too dismissive of oss models. This sounds like MS employees talking about linux circa 2002. This attitude would have written off linux in the early 00s as doomed for not "keeping up" with windows. The oss option will always appear behind the curve but they inevitably catch up... if they even need too. AI is no different. The free/oss option will be niche and disregarded by the bigs but it will survive and thrive, just as linux has.

I disagree with Steve Yegge's assessment that the curve is close to leveling off. It's not the models, it's the harnesses and the result automation possibilities that are the true unlock. LLMs stabilizing around a current local maximum is actually not much of a big deal. If we just use the models we have today there is so much more unlock available.

We have only just begun our ascent up the hockey stick and the most intense change is yet to come.

The real danger is how big of a gap will exist once the curve does level off. If we are just at the start of the sigmoid curve and starting our ascent, then many jobs will be thrown off by the time we hit the peak and begin to level off.

No politician or corporation is preparing for this sufficiently.

Is this a troll

If the most expensive models yet to come will end up behind bars by default, what is the economic incentive to make them in the first place?