Manias go back a long way.

The history of the UK's railway mania in the 1840s is worth researching, because it's uncannily similar, with a stock bubble, fraudsters and chancers, huge hype, cutthroat competition, boardroom intrigue and drama, miles and miles of unnecessary infrastructure in the wrong places, and eventually a technology that became useful, but could have been developed more intelligently.

"most" is a hell of a claim, yea. "they're going to be useful sometimes and will stick around in some form" has been rather clear from early on (they're Transformer++, of course they'd be useful sometimes), but every session I spend with one still turns into lengthy deeply-misleading wild goose chases until I learn enough to force them down the right path[1]. quality/size of the model hasn't mattered for that, it always happens at some points (and it's just luck whether or not it's a critical point), and I see no reason to expect that it will change.

>From memory, the last time I was given a presentation on it, by actual Snowflake staff, they reported that ideal configuration results in something like ~92% accuracy due to the complexity of data at a large business ...

it's exactly this problem. nobody has solved it. lots of companies are trying to sell that they have solved it.

when I don't care about the end result that might be fine (I have used wordpress too), but frequently it ends up that they helped find relevant docs (they're quite good at finding that from vague descriptions, and it's very easy to verify) and I would have been quicker if I had simply read those docs in full. and then I'd have a more complete understanding of the space too. my biggest worry for personal use is that LLMs will write those docs in the future, and be riddled with mistakes :\

1: ...and then they're quite good code dictation tools. people who think "writing code isn't the bottleneck" just haven't spent enough time in well-understood spaces or rebuilt enough wheels. it absolutely can be a several-multiples bottleneck in day-to-day work, or when re-doing something you've done before and fully understand.

> having lived through the dot-com hype in the 1990s

Having not lived through this, I'm actually curious as to how similar it was to the current hype cycle. Was there a general sense that something singularity-like was approaching?

I don't and wouldn't claim that AI is completely useless, I personally use it for at least a couple hours out of each working day and feel that it boosts my productivity significantly. My point is that the kind of benefits we're seeing from AI are not the ones we expected, and the difference between expectation and reality doesn't seem to have sunk in for most. I regularly hear friends talk of the post-scarcity future which is just around the corner, something like the culture Minds from Ian M. Banks, and this pseudoreligious narrative seems to be what the big AI players are deliberately selling. What I'm actually seeing is something more akin to Mr Meeseeks from Rick and Morty.

> So, you’re committed to falling for the next one, too, eh?

Haha, no. The point was that I've seen better things in the long winters between hype cycles than in any hype cycle.

This hype cycle is much more like the NFT hype cycle — it's just that it has a more easily understood product. Impossible to see Beeple's Everydays as anything other than a harbinger, IMO.