🤖 Gemini 4 Argon for democratizing robotics:
Google's Gemini 4 Argon adds robot control and simulation-based training
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Paige Bailey shares a quoted summary of Google's Gemini 4 Argon, a unified model for robotics that combines robot control, physical reasoning, and simulation generation. The quoted post says training on more than 4,500 simulated episodes raised task success from 56% to 75% and cut completion time from 35 to 24 seconds.
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👩💻 Paige BaileyVerified on X
@DynamicWebPaige
what google devs also say about gemini 4 argon for robotics in their blog - a unified model for robotics — argon combines robot control, physical reasoning, simulation generation, and skill improvement - simulation-based training — the model can create digital simulations from real-world data and test actions in a virtual environment before deploying them on a physical robot - improved real-world performance — training on more than 4,500 simulated episodes increased the task success rate from 56% to 75% and reduced completion time from 35 to 24 seconds - autonomous error correction — argon can analyze failed attempts, adjust its actions, and retry tasks to improve accuracy and speed. for example, over three iterations, the so-101 robotic arm reduced the time needed to complete a pick-and-place task from 58.9 to 17.4 seconds, making it 3.4 times faster gemini 4 argon could simplify robot development and training by reducing the need to manually program every individual action
Source: 👩💻 Paige Bailey · x.comPublished · added here