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Sony Robot Defeats Professional Table Tennis Players in AI Breakthrough

Sony's table tennis robot Ace has beaten expert human players, marking what researchers call the first time a robot has achieved elite-level performance in a competitive sport.

Synthesized from 6 sources

A table tennis robot developed by Sony has defeated professional human players, representing what researchers describe as a significant milestone in artificial intelligence and robotics. The robot, called Ace, was built by Sony's AI division and tested against elite athletes at the company's Tokyo headquarters.

The robot uses nine cameras positioned around an Olympic-sized court to track ball movement and spin, along with eight joints that allow it to position its paddle and execute shots. Ace learned to play through reinforcement learning, an AI method that allows machines to improve through experience rather than pre-programmed instructions.

In testing conducted in December 2024, Ace defeated three out of four high-skill players it competed against. The matches were overseen by umpires from the Japanese Table Tennis Association and followed official table tennis rules. Professional players Minami Ando and Kakeru Sone were among those who competed against the robot.

Sony researchers emphasized they designed Ace to compete fairly with humans rather than exploit superhuman capabilities. The robot's speed, reach, and performance were calibrated to match those of skilled athletes who train at least 20 hours per week. "The goal is to have some level of comparability, some level of fairness to the human," said Michael Spranger, president of Sony AI.

The achievement represents progress in moving AI from simulated environments to physical world applications. While other companies have developed table tennis robots before, including Google's DeepMind division, Sony claims Ace is the first to achieve expert-level play in a commonly played competitive sport.

The research was published in the journal Nature. Sony researchers said the technology could have applications in manufacturing and other industries that require robots to operate quickly in changing environments.

Sources (6)

Bias Scale:
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Fox NewsApr 22, 2026, 6:29 PM
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Financial TimesApr 22, 2026, 3:00 PM
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