[jaggederest]

That has ever been the case. As soon as it works reliably, it's not "AI" any more. Take spellcheckers or collaborative filtering as examples, but there are lots more. Hofstadter in G.E.B. said it well:

> There is a related “Theorem” about progress in AI: once some mental function is programmed, people soon cease to consider it as an essential ingredient of “real thinking”. The ineluctable core of intelligence is always in that next thing which hasn’t yet been programmed. This “Theorem” was first proposed to me by Larry Tesler, so I call it Tesler’s Theorem: “AI is whatever hasn’t been done yet.”

[jerf]

In this moment, the opposite is happening. Everything is getting called "AI", whether it uses LLMs to prompt LLMs about how to prompt LLMs, uses "conventional" machine learning, or just looks mysterious enough that they can expect the market to not ask questions.

I am reminded of "game AI", which for the most part has historically been just giant decision trees, encoded one way or another, because if you hook up any sort of real AI to a game entity or collection of game entities that does any sort of learning or training, even simple 1980s-era reinforcement learning, it turns out the game entities will roflstomp the human players, and the human players aren't interested in paying for that experience. We've been calling those collections of if statements and for loops "AI" for a long time, though, because who wants to hear about how deliberately stupid their opponents are?

[ambicapter]

Sure, or maybe the actual applications of “AI” are small and unobtrusive, like the dictation of doctor’s notes example, and it’s not actually the massive revolution it’s claimed to be.

[jaggederest]

I struggle to reconcile this attitude with, among other things, the massive number of exploits being discovered and the pretty straightforward utility for coding. Have you used codex recently?

[variadix]

Perhaps, but I think what people mean by intelligence is something that learns and adapts. If LLMs couldn’t do in context learning I don’t think people would think of them as AI, more as a kind of queryable database via natural language. There are other algorithms that learn and adapt, but in much more narrow circumstances that most people won’t obviously interact with.

[jaggederest]

Right, and my point is that now that is the bar. If you'd told me in 2008 that markov chains would be smart enough to one-shot even a trivial video game from scratch I would certainly have called that AI even if you had to do some major rigamarole to get it to work.

[inigyou]

Because AI meant "make computers smart like people".

We taught the computer to spell check, but the computer still didn't feel smart like a person, just smart like a machine so that obviously wasn't AI. We taught it to do algebra, same thing. With LLMs though, now it really does feel like an artificial human, so this time it really is AI.

[jaggederest]

Right, but I remember when spellcheck first started to be a thing, and people were like "Wow proofreaders are out of a job, ai is so cool", but then it became normal.