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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.

The Humanoid Labs

1,170 subscribers

15,270 次观看 • 7 个月前 •via X (Twitter)

Anya Rossi• Live Now

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7 条评论

meet me in orbit 的头像

meet me in orbit7 个月前

Can't happen soon enough

NewAIWorld 的头像

NewAIWorld7 个月前

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.

Gary Myers 的头像

Gary Myers7 个月前

SBOL is that breakthrough.

Himanshu Kumar 的头像

Himanshu Kumar7 个月前

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

Tommy AutoTech 的头像

Tommy AutoTech7 个月前

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

Mike Takac 的头像

Mike Takac7 个月前

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

Today in AI 的头像

Today in AI7 个月前

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.

"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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