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Gemini 4 Argon scores 87% on an embodied-reasoning benchmark

developers.googleblog.com 16 min read Editor score 6/10

Google reports an 87% score on ERQA and presents robotics workflows spanning control, simulation reconstruction and physical understanding. Engineers building embodied AI can see the claimed capabilities and intended applications, though the excerpt gives little evaluation detail.

What: Gemini 4 Argon is presented as a general-purpose physical-reasoning model for tasks across the robotics lifecycle.
How: For Spot manipulation, Argon creates a MuJoCo digital twin to practice before acting on a physical bin; foot-verifier and hand-verifier check alignment.
Why it matters: The workflow combines simulation practice, visual reasoning and robot actions, relevant to engineers building systems that connect models to hardware.

Argon uses a MuJoCo digital twin for practice, then verification agents check Spot's alignment. Sketched from the article's own text.

Read on developers.googleblog.com → Hacker News · 56 comments

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