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Dario says robotics will be revolutionized once AI models can control them, whether through human-like learning, training on simulations, or in-context learning. The path doesn't matter. Both robot design and control will improve, happening maybe 1-2 years after key AI breakthroughs.

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The Humanoid Labs

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15,270 просмотров • 7 месяцев назад •via X (Twitter)

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Комментарии: 7

Фото профиля meet me in orbit
meet me in orbit7 месяцев назад

Can't happen soon enough

Фото профиля NewAIWorld
NewAIWorld7 месяцев назад

We are essentially building the nervous system before the body. The physical world has much higher stakes and zero tolerance for hallucinations. Hardware is the only thing keeping reality from moving at the speed of silicon.

Фото профиля Gary Myers
Gary Myers7 месяцев назад

SBOL is that breakthrough.

Фото профиля Himanshu Kumar
Himanshu Kumar7 месяцев назад

@TheHumanoidLabs, Dario's right, AI-driven control will indeed change robotics significantly, especially with advanced learning.

Фото профиля Tommy AutoTech
Tommy AutoTech7 месяцев назад

AI-controlled robots? Now my warehouse automation dreams might finally come true! Bring on the revolution!

Фото профиля Mike Takac
Mike Takac7 месяцев назад

Race to quantum AGI, “Global Civility,” an AI-generated sci-fi movie based on a nonfiction book:

Фото профиля Today in AI
Today in AI7 месяцев назад

Amodei's 2026-2027 timeline for Nobel-level intelligence hinges on the transition to end-to-end SWE automation. The 50% white-collar job delta is the inevitable result of 300GW compute scaling benchmarks.

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"Will the robotics industry will be generating trillions of dollars of revenue?", "YES." Dario Amodei says breakthroughs in robotics could emerge in several ways, such as through continual learning or generalization. Once achieved, these models will revolutionize both robot design and control. However, it will likely take another year or two from that point for the technology to diffuse through the economy.
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.Oliver Cameron says one of the biggest applications for world models will be training AI inside simulated environments. "One of the killer applications of world models will be as a learning environment where language models and other types of AI can learn. It gets very much philosophical."
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