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Comment by Barrin92 | Hacker News Reader

>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.

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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.

Hard disagree.

The problem is sensors.

There are simply no technologies today that can replicate the density, precision, and versatility of human touch sensors. Until then, there is simply no way to create generally capable robots that can operate at the level of a human.

And unlike LLMs, advancement is held back by physical limitations like materials science, so progress has been and will continue to be much slower.

What task do you think that humanoid robots can't do? Also, we don't need fully equivalent touch to get useful performance.

If you look you will see a really broad range of tasks accomplished already, including thing like manipulating screws, picking up pills, inserting wire harnesses, folding clothes, putting away dishes. And there are several companies with built in or component advanced touch sensors like Figure or leading edge touch sensor companies like SynTouch and GelSight.

Peel an orange? Crack an egg? Thread a needle? (Heh, drive a car...) There's a huge range of tasks that a non-specialized, general purpose robot simply cannot do yet. I'd be easier to enumerate the things they can do than the things they can't given the current state of the art.

Sure, build an orange peeling machine and it'll do great. But that's not what we're talking about here.

As for those demos videos we often see, those are very highly choreographed demonstrations. Show me a real life humanoid robot operating free form on a factor floor and doing those things and I'll be impressed.

And to be clear, this is not meant to understate what's been accomplished. I'm just saying the path for advancement is a lot harder and based in physical rather than computational limitations, which are much harder to overcome and go much slower. We simply cannot look at the growth curve of LLMs and expect robotics to advance at the same rate.

peeling an orange and cracking an egg already demonstrated. Figure 02 worked on BMW's actual Spartanburg production line for about 1,250 hours running 10-hour shifts.

keep paying attention, you will see how wrong you are about it being physical limitations as the physical AI continues to rapidly improve.

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