The world of table tennis may be in for a shake-up after Sony’s AI division unveiled Ace — an autonomous robot that can compete with expert table tennis players.
This is the first time a robot has achieved “expert-level play in a commonly played competitive sport in the physical world,” Sony AI representatives said in a statement.
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“This breakthrough is much bigger than table tennis,” Peter Stone, chief scientist at Sony AI, said in the statement. “It represents a landmark moment in AI research, showing, for the first time, that an AI system can perceive, reason, and act effectively in complex, rapidly changing real-world environments that demand precision and speed.”
A study detailing how the robot works was published April 22 in the journal Nature.
Where hardware meets software
AI systems have already shown prowess in strategy games, such as Go, chess and role-playing games.
However, moving AI into a robotic body, where quick reflexes are paired with physical movements, can be more challenging. Here, the software and hardware components have to work seamlessly — and in table tennis, where speed and hand-eye coordination are vital, this pairing has to work to win.
“Table tennis is a game of enormous complexity that requires split-second decisions as well as speed and power,” Peter Dürr, director of Sony AI in Zurich and project lead for Ace, said in the statement. “This research breakthrough highlights the potential of physical AI agents to perform real-time interactive tasks, and represents a significant step toward creating robots with broader applications in fast, precise, and real-time human interactions.”
Ace’s strategy builds on Sony AI’s previous research on its AI agent Gran Turismo Sophy, with Ace using advanced sensors and high-speed software to perceive its environment. These sensors include nine active pixel sensor cameras that help Ace identify the ball’s exact position in 3D space, along with three gaze systems that use mirrors and event-based vision cameras to measure the ball’s spin and angular velocity as it moves through the air.
Running these cameras is Sony AI’s proprietary AI control system, which is based on model-free reinforcement learning, where an AI agent learns directly from interactions in its environment without making a predictive model first. This technology allows Ace to adapt and make decisions faster, without relying on a preprogrammed model.
Lastly, Ace’s robotic body, which includes a swiveling arm with a paddle-like appendage at its end, was created with the company’s robotic hardware.
Beating the pros
In April 2025, scientists had Ace play against five elite players (each with over 10 years of experience and around 20 hours of weekly training) and two professional table tennis players (Minami Ando and Kakeru Sone, both in the Japanese professional league). While players in both tiers are skilled at table tennis, professional athletes make their living by playing table tennis, whereas elite players may not have the same caliber to make the sport their livelihood.
Ace won three out of five matches with the elite players and boasted a 75% serve return rate. Its autonomous system also allowed the robot to return unusual shots, such as balls bouncing off the net. It however lost both matches against the pros.
Then, in December 2025, Sony AI had Ace play a series of separate matches in which it competed against two professional and two elite players. This time, Ace beat both elite players and one of the professionals. Company representatives said the robot moved closer to the table edge, had higher shot speeds and launched faster-paced volleys against its opponents.
Given that less than two years ago, Google DeepMind’s robotic table tennis robot was defeated by elite players, Ace’s victories show how quickly this field of robotics is advancing in a short time.
“Once AI can operate at an expert human level under these conditions, it opens the door to an entirely new class of real-world applications that were previously out of reach,” Stone said in the statement.
