Which, judging by the terrible PR optics AI has nowadays, could unfortunately seep into academia too. Fund grants wouldn't want their names associated with anything with "AI" in its name even if it's a return to expert systems.
I'm using "AI" broadly here even if the current investor darling is just LLMs because, well, the term AI has been front and center of all promotions and investors and the general consumer public isn't really a discerning bunch. So I stand by my prediction that a "soft taboo" is likely where investors and consumers shy away from anything even remotely AI. The consumer backlash has arguably already started.
The models work remarkably well for several classes of problem that seemed impossible a few years ago. They're not going away. There will still absolutely be a lot of ups and down and crazy stuff that happens in AI, but it won't be that AI almost completely stops being developed/funded for a decade or more. The biggest risk, I think, is regulatory capture; it's what Anthropic and OpenAI seem to be aiming for with their scaremongering about how capable and dangerous their models are. That'll put a damper on the industry for everyone except the companies that bribe the right people.
That's the first time in my life I hear this definition. Until now, the word "smart" has meant doing exactly the things LLMs do, and mice don't.
I guess it is a sign we are re-evaluating what makes humans special.
Always has been: https://en.wikipedia.org/wiki/AI_effect
Tangentially: https://en.wikipedia.org/wiki/Moravec%27s_paradox
For example, initially, a "planet" was just a big body in space. Then when people started to see more and more nuances, the definition just refined, and some objects stopped being called "planet".
I would not be surprised if there is a bias that pushes some people to redefine "intelligence" away from machine, but I would not be surprised if there is a bias that pushes some people to ignore newly discovered nuance and put into the same "intelligence" bag things that are in fact very different. I personally can see how LLM are not really "intelligent", and I don't think it is a good idea to say: well, yesterday we said the minimum criteria is X, now that we noticed that X can be reached without really doing the real thing, let's just ignore that and pretend it is the same thing.
(
: the biggest clue for me is to use an early model, and see that it sometimes looks very intelligent, and then sometimes you can see that it gets it wrong in a way that shows that it never "understood" it at all. Newer models are better, but because it is an iteration on the same bases, the increase of performances cannot really due to replacing the things that "looked smart by aren't" by "real smart", but more replacing the things that "don't look smart" by "look smart by aren't")and then models learned that they can back track and error correct
so much for "mathematically impossible..."
I very commonly see someone make some small mistake and end up going in the wrong direction, “accumulating stupid” as they go, sometimes for years.
For me, "smart" means doing things less based on instinct. Things humans can do but mice cannot, things mathematicians can do but normal people cannot, etc.
Considering the unit distance conjecture was disproved by OAI's model last month, I think maybe LLMs should count as "smart".
I never ask Opus or Fable a question and think "what a stupid response".
Quite the opposite. It has actually raised the bar of what I consider an intelligent response to my inquiry. So much so that most responses from humans on most subjects to most forms of inquiry seem stupid and not really thought out.
This isn’t exactly saying how stupid anyone is but I’d definitely have been concerned about a human’s reasoning ability and understanding of logic if they’d given me similar answers.
I'd be interested in the "retention rate" for these two products. I wouldn't be surprised if the average original Xbox was used 2 orders of magnitude more than the average Meta Quest, which is collecting dust on some shelf.
I'd wager the typical MQ2 owner is someone with 20 hours of Beat Saber on it and 5000 hours total on Steam or PS.
I don't think we even need to go into tech and AI for an example. The intelligence or lack thereof of pets surprise us. Sometimes a cat is surprisingly smart when it is able to open a door to get food it wasn't supposed to. But then same cat gets bamboozled by walls and simple optical illusions. We generally expect that if something/a human is smart enough to do the former, then it shouldn't be dumb enough to fall for the latter.
Coming back to AI, this dissonance is how AI-generated images are detected for example. If a human can render something so well, you wouldn't expect them to make small but nonetheless elementary line art mistakes.
AI can not.
For those disagreeing: please explain how a static hardware can learn.
Not only that... AI is NOT only learning during the training phase... LLMs learn in real time the minute you talk to it. It learns something and saves those learnings in a context window or somewhere else if you want it to exist beyond the context window.
All of the above runs on static hardware. Don't understand how someone can say a profoundly wrong statement and get voted up.
You mean "Human developers learned ...", yes? Or was there really an all AI-driven, self-improving aspect to this?
I doubt that this was AI self-improvement.
heohk•6h ago
ramon156•3h ago