Man vs. machine: DeepMind’s new robot serves up a table tennis triumph [Ars Technica]

Human-beating ping-pong AI learned to play in a simulated environment.

Enlarge (credit: Benj Edwards / Google DeepMind)

On Wednesday, researchers at Google DeepMind revealed the first AI-powered robotic table tennis player capable of competing at an amateur human level. The system combines an industrial robot arm called the ABB IRB 1100 and custom AI software from DeepMind. While an expert human player can still defeat the bot, the system demonstrates the potential for machines to master complex physical tasks that require split-second decision-making and adaptability.

“This is the first robot agent capable of playing a sport with humans at human level,” the researchers wrote in a preprint paper listed on arXiv. “It represents a milestone in robot learning and control.”

The unnamed robot agent (we suggest “AlphaPong”), developed by a team that includes David B. D’Ambrosio, Saminda Abeyruwan, and Laura Graesser, showed notable performance in a series of matches against human players of varying skill levels. In a study involving 29 participants, the AI-powered robot won 45 percent of its matches, demonstrating solid amateur-level play. Most notably, it achieved a 100 percent win rate against beginners and a 55 percent win rate against intermediate players, though it struggled against advanced opponents.

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industrial robot