161–170 of 270 posts
Earlier quoted context omitted.
>The whole point of AI is to create an intelligence modeled on humans and to compare it to humans. According to who? Everyone who's anyone is trying to create highly autonomous systems that do useful work. That's completely unrelated to modeling them on humans or comparing them to humans.
But since these things are more like humans than computers, to build these autonomous systems you are going to have think in terms of full industrial engineering, not just software engineering: pretend you are dealing with a surprisingly bright and yet ever distracted employee who doesn't really care about their job and ensure that they are able to provide the structure you place them in value without danger to your…
Earlier quoted context omitted.
Up to ten Nobel laureates have been unveiled as being three ducks in a trenchcoat.
Just to clarify, is it that all of those laureates combined were three ducks in a trenchcoat in total, or each of the laureates individually was three ducks (for a total of up to 30 ducks)?
According to the researchers, “the triggers are not contextual so humans ignore them when instructed to solve the problem”—but AIs do not.
Not all humans, unfortunately: https://en.wikipedia.org/wiki/Age_of_the_captain
Earlier quoted context omitted.
> We need to move past the humans vs ai discourse it's getting tired. You want a moratorium on comparing AI to other form of intelligence because you think it's tired? If I'm understanding you correctly, that's one of the worst takes on AI I think I've ever seen. The whole point of AI is to create an intelligence modeled on humans and to compare it to humans. Most people who talk about AI have no idea what the psycho…
>The whole point of AI is to create an intelligence modeled on humans and to compare it to humans. According to who? Everyone who's anyone is trying to create highly autonomous systems that do useful work. That's completely unrelated to modeling them on humans or comparing them to humans.
Nearly every component is based on humans
- neural net
- long/short term memory
- attention
- reasoning
- activation function
- learning
- hallucination
- evolutionary algorithm
If you're just consuming an AI to build a React app then you don't have to care. If you are building an artificial intelligence then in practice everyone who's anyone is very deliberately modeling it on humans.
There is more than one comment here asserting that the authors should have done a parallel comparison study against humans on the same question bank as if the study authors had set out to investigate whether humans or LLMs reason better in this situation. The authors do include the claim that humans would immediately disregard this information and maybe some would and some wouldn't that could be debated and seemingly…
> authors should have done a parallel comparison study against humans on the same question bank as if the study authors had set out to investigate whether humans or LLMs reason better in this situation. Only if they want to make statements about humans. The paper would have worked perfectly fine without those assertions. They are, as you are correctly observing, just a distraction from the main thrust of the paper. >…
while it is not realistic to insist every study account for every possible objection, i would argue that for this kind of capability work, it is in general worth at least modest effort to establish a human baseline.
i can understand why people might not care about this, for example if their only goal is assessing whether or not an llm-based component can achieve a certain level of reliability as part of a larger system. but i also think that there is similar, and perhaps even more pressing broad applicability for considering the degree to which llm failure patterns approximate human ones. this is because at this point, human are essentially the generic all-purpose subsystem used to fill gaps in larger systems which cannot be filled (practically, or in principle) by simpler deterministic systems. so when it comes to a problem domain like this one, it is hard to avoid the conclusion that humans provide a convenient universal benchmark to which comparison is strongly worth considering.
(that said, i acknowledge that authors probably cannot win here. if they provided even a modest-scale human study, i am confident commenters would criticize their sample size)
Earlier quoted context omitted.
Is the model thinking what is cat doing here? Then start thinking it is being tested?
I wonder if the problem here is simply hitting some internal quota on compute resources? Like, if you send the model on wild goose chase with irrelevant information it wastes enough compute time on it that it fails to arrive at correct answer to main question.
Earlier quoted context omitted.
>The whole point of AI is to create an intelligence modeled on humans and to compare it to humans. According to who? Everyone who's anyone is trying to create highly autonomous systems that do useful work. That's completely unrelated to modeling them on humans or comparing them to humans.
Go back and look at the history of AI, including current papers from the most advanced research teams. Nearly every component is based on humans - neural net - long/short term memory - attention - reasoning - activation function - learning - hallucination - evolutionary algorithm If you're just consuming an AI to build a React app then you don't have to care. If you are building an artificial intelligence then in pra…
Nothing in that list is based on humans, even remotely. Only neural networks were a vague form of biomimicry early on and currently have academic biomimicry approaches, of which all suck because they poorly map to available semiconductor manufacturing processes. Attention is misleadingly called that, reasoning is ill-defined, etc.
LLMs are trained on human-produced data, and ML in general shares many fundamentals and emergent phenomena with biological learning (a lot more than some people talking about "token predictors" realize). That's it. Producing artificial humans or imitating real ones was never the goal nor the point. We can split hairs all day long, but the point of AI as a field since 1950s is to produce systems that do something that is considered only doable by humans.
This looks like it'll be useful for CAPTCHA purposes. According to the researchers, “the triggers are not contextual so humans ignore them when instructed to solve the problem”—but AIs do not. Not all humans, unfortunately: https://en.wikipedia.org/wiki/Age_of_the_captain
Earlier quoted context omitted.
>The whole point of AI is to create an intelligence modeled on humans and to compare it to humans. According to who? Everyone who's anyone is trying to create highly autonomous systems that do useful work. That's completely unrelated to modeling them on humans or comparing them to humans.
But since these things are more like humans than computers, to build these autonomous systems you are going to have think in terms of full industrial engineering, not just software engineering: pretend you are dealing with a surprisingly bright and yet ever distracted employee who doesn't really care about their job and ensure that they are able to provide the structure you place them in value without danger to your…