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Figure AI has made a massive bet on humanoid robotics: access to up to 100,000 NVIDIA Vera Rubin GPUs through Nscale.
But does more compute actually mean smarter robots?
In this video, we break down Figure’s $3.5 billion initial compute commitment, its Helix Vision-Language-Action model, and why massive AI infrastructure could become critical for training physical AI.
We also examine the real challenges: robot data, reliability, manufacturing costs, safety, and whether compute alone can turn impressive demonstrations into robots that work reliably in the real world.
The headline is 100,000 GPUs. The real question is whether Figure can turn that compute into useful, affordable, and dependable humanoid robots.
Do you think the biggest compute cluster—or the best real-world data—will win humanoid robotics?
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Credit to : AI Futivus