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uludag 5 hours ago

Wouldn't "general intelligence" require so much more than scoring well (or even amazingly) on benchmarks?

Like what about having some "AGI model" embodied in something (maybe humanoid), and test it by having it step in an assortment of cars and park them. Does bodily-kinesthetic intelligence account for nothing? Humans are intelligent creatures and can dynamically adapt to the physical shape of a variety of vehicles and their movement characteristics. And there's so many things like this that are extremely basic, which some people dismiss since practically every human has the capability to do it, but actually requires a high degree of intelligence.

dgunay 33 minutes ago | parent | next [-]

This is a big reason why I feel like even though LLMs are _effectively_ AGI in some regard, they also are a hack around what most people figured AGI would look like before the advent of LLMs. Humans can do metacognition, output multimodally at the same time (verbal _and_ physical intelligence go together to produce an expressive face while one talks), have a good sense for what they do and don't know, continuously take in and respond to the world around them in a (mostly) uninterrupted fashion without "turns", learn knew knowledge and retain it for their whole lives, etc. When you reduce a human to a text generator, yes obviously SOTA LLMs perform way better, but rather than invent something that can operate as an always-running "being", we've grafted a harness around an intelligence that is bound purely to speak only when spoken to. Maybe organic intelligence is already that, playing out at a super high refresh rate, but I don't know.

fidotron 3 hours ago | parent | prev | next [-]

This is a much underappreciated point.

That said, a look at the state of self driving and the recent robot olympics shows that advancement on that has accelerated enormously, though whether it's reflected in any of the LLMs is something else entirely.

cryptoz 4 hours ago | parent | prev | next [-]

What you've described is just a new benchmark, though. It'll be called CarParkBench, various embodied LLMs will then be run against that benchmark, and some will score better than others.

I do see where you're going, but that's already what's happening: we have so many different benchmarks because there's no real single way to test for general intelligence.

Also, it takes a human probably at least a decade of world experience, growth, learning, etc, to pass your benchmark. I'm quite confident that it will be very soon that an embodied LLM will pass your new benchmark, much sooner than a human would take if born today.

strken 3 hours ago | parent [-]

I think the issue is less about creating a new benchmark and more that the existing benchmarks shouldn't be called anything related to AGI unless they measure AGI.

If a model couldn't go to work as e.g. a first year apprentice plumber on their first day and perform anywhere remotely close to the median, but can pass a benchmark that claims to measure AGI, the benchmark is wrong and the model is not exhibiting general intelligence yet. ApprenticePlumberBench sounds like it's genuinely better than ARC-AGI at measuring AGI and that's a bit silly.

(Edit: I wrote ARC-GIS the first time around, for some silly reason)

visarga 3 hours ago | parent [-]

It's not measuring AGI at all, it starts from human "core knowledge" so it is parochial. It is made of tests that still fail so by definition next version will also start low. Moving goalpost.

dist-epoch 3 hours ago | parent | prev [-]

AGI has a pretty precise definition, covering only cognitive tasks.

Running a marathon is not needed to claim AGI.

visarga 3 hours ago | parent | next [-]

> can match or exceed human cognitive abilities across a wide range of tasks

If you go by definition AGI is not general, just "smart ape" shaped.

Barrin92 2 hours ago | parent | prev [-]

>AGI has a pretty precise definition, covering only cognitive tasks.

OpenAI's own charter defines AGI as "Highly autonomous systems that outperform humans at most economically valuable work". This is actually fairly sensible and involves obviously a ton of non-cognitive, emotional, social and physical activity. In other words, if you can replace most or all human beings with a machine, you have something that's generally intelligent.

That's obviously not even remotely where we're at, AI chatbots do well on narrow usually text based or programmatic problems, but can't even replace a barista or a plumber.

ilaksh 40 minutes ago | parent [-]

There is rapid progress in generality in humanoid robotics though. I think within the next year or less we will get the ChatGPT moment for humanoid robots. If you look at progression of capabilities such as the recent Skild AI demos.