The 99% success rate of the Robotic company Generalist's GEN-1 model shows us that humanoid robots are progressing faster than most people expect.

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arstechnica.com/ai/2026/04/generalists-new-phys…

"With GEN-1, though, Generalist says its physical models have reached a GPT-3-style inflection point, where some tasks are starting to “cross the level of performance needed to be deployed in economically useful settings.”

I think humanoid robots are one of the sleeper tech trends most people are underestimating. They don’t need AGI, or even ‘perfect’ AI, to do most unskilled & semi-skilled work. With enough development & training, today’s AI models will probably be fine. Here’s another sign that this hypothesis might be true.

How soon will they get there? At current rates of development, 2030 seems a reasonable estimate for general-purpose humanoids easily trainable for most unskilled/semi-skilled work. Just when most driving jobs will be disappearing to robo-taxis. No one seems prepared for this future rapidly bearing down upon us.

From folding boxes to fixing vacuums, GEN-1 robotics model hits 99% reliability: New model can respond to disruptions and figure out moves it wasn’t trained for.

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I don’t buy it.

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Yep. Just pumping the hype

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Neural networks are universal approximators. Anything with complex inputs and known correct outputs will gradually become tasks we expect to Just Work. Especially when failure is perfectly safe. A self-driving car has to be better than most humans, all of the time, before we’ll tolerate the cases where it’s already fine. An assembly line of arms folding cardboard does not have this problem. Nor does a Roomba that can sift a litterbox. Things can go wrong… but in a way that’s quietly hilarious, to everyone but you.

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There is nothing humanoid about the article’s shown robots.

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Robots engineers for a specific purpose have been better than humans for 50 years. That is no surprise.

Now they are doing a slightly broader set of tasks with the same robot. They are getting faster, more flexible and accurate, but that is about it.

Robots are a hell of a long way from being able to know that it should stop trying to do a job, without explicit guardrails and tightly controlled environments. Just look at the disaster of self driving cars doing stupid shit.

We simply do not have computing power for that to be practical yet.

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