If the post drops long before the IPO, it's vain boosterism. If it's near the IPO, it's fattening the pig. If it's after the IPO, it's pumping the stock price.
He's been vibecoding some stuff himself personally, on one of his scuba projects. You could take people as actually believing in the things they do and say.
Are you aware of how productivity has increased over the past century in general? That didn't lead to 100x wage increases or more free time. Labour is a market commodity and follows market rules. Increased productivity means more gets done in less time. It doesn't mean you spend less time working
You get AIs to prove their code is correct in precisely the same ways you get humans to prove their code is correct. You make them demonstrate it through tests or evidence (screenshots, logs of successful runs).
Tao's broad project, which he has spoken about a few times, is for mathematics to move beyond the current game of solving individual theorems to being able to make statements about broad categories of problems. So not 'X property is true for this specific magma' but 'X property is true for all possible magmas', as an example I just came up with. He has experimented with this via crowdsourcing problems in a given domain on GitHub before, and I think the implications of how to use AI here are obvious.
Does a system being deterministic really matter if it's complex enough you can't predict it? How many stories are there about 'you need to do it in this specific way, and not this other specific way, to get 500x better codegen'?
It's an extension of how I've noticed that AIs will generally write very buttoned-down, cross-the-ts-and-dot-the-is code. Everything gets commented, every method has a try-catch with a log statement, every return type is checked, etc. I think it's a consequence of them not feeling fatigue. These things (accessibility included) are all things humans generally know they 'should' do, but there never seems to be enough time in the day; we'll get to it later when we're less tired. But the ghost in the machine doesn't care. It operates at the same level all the time
You can recognise that the technology has a poor user interface and is wrought with subtleties without denying its underlying capabilities. People misuse good technology all the time. It's kind of what users do. I would not expect a radically new form of computing which is under five years old to be intuitive to most people.
A system having terminal failure modes doesn't inherently negate the rest of the system. Human intelligences fall prey to plenty of similarly bad behaviours like addiction.
I wouldn't really say it's embarassing. If most human tasks required perfection (or at least high levels of correctness at all times), society would probably not have gotten to where we are. Imagine a world where every job was as hard as open-heart surgery! In a sense, it's an achievement of humanity that we're able to recognise when 'good enough' will let us achieve the things we want.