{"id":10530,"date":"2026-04-26T13:00:00","date_gmt":"2026-04-26T13:00:00","guid":{"rendered":"https:\/\/musictechohio.online\/site\/ai-powered-robot-destroy-table-tennis-pros\/"},"modified":"2026-04-26T13:00:00","modified_gmt":"2026-04-26T13:00:00","slug":"ai-powered-robot-destroy-table-tennis-pros","status":"publish","type":"post","link":"https:\/\/musictechohio.online\/site\/ai-powered-robot-destroy-table-tennis-pros\/","title":{"rendered":"New AI-Powered Robot Can Destroy Human Champions at Ping Pong"},"content":{"rendered":"
\n

First, they learned how to play tennis<\/a> on two feet. Then, they came for our half-marathon world record<\/a>.<\/p>\n

Now, robots are set to overtake us in the sport of table tennis as well. In a recent paper<\/a>, published this week in the journal Nature<\/em>, researchers detailed how they\u2019ve leveraging AI to teach a robot arm built by Sony, dubbed Ace, to repeatedly beat \u201celite and professional players under official competition rules.\u201d<\/p>\n

Sony claims<\/a> it\u2019s the first robot to achieve expert-level performance in any competitive physical sport, following decades of table tennis robot development.<\/p>\n

A promotional video<\/a> put together by Sony\u2019s AI division shows the paddle-wielding robot bounding back and forth at staggering speeds to counter aggressive strikes. The human experts don\u2019t appear to be holding back, either, smacking challenging shots at it with full strength.<\/p>\n

\n
\n<\/div>\n<\/figure>\n

It\u2019s an impressive technological feat and a major milestone for the application of AI in robotics, a confluence of two areas of research that has been at the core of the ongoing boom in humanoid robotics over the last few years.<\/p>\n

While teaching a robot arm to play ping pong may not sound like the kind of thing that will lead to the next industrial revolution, many of Ace\u2019s achievements could eventually trickle down to other areas of research.<\/p>\n

\u201cThe success of Ace, with its perception system \u200band learning-based control algorithm, suggests that similar techniques could be applied to other areas requiring fast, real-time control and human interaction,\u201d lead author and project lead at Sony AI Peter D\u00fcrr told Reuters<\/em><\/a>, \u201csuch as manufacturing and service robotics, as well as applications across sports, entertainment and \u200bsafety-critical physical domains.\u201d<\/p>\n

According to their paper, Ace won three out of five games against elite players with more than ten years of experience, but lost two games against top-level pros as of April 2025. However, Sony claims that Ace went on to beat more professional players in December, as well as last month.<\/p>\n

The level of complexity is staggering. The robot needs to have extremely fast reaction times, not only to track the ball, but to also determine its trajectory in real-time using nine cameras and three vision systems.<\/p>\n

The overall system can \u201ctrack a ball at 200 Hz\u00a0with millimeter accuracy and around ten millisecond latency while measuring the spin at up to 700 Hz,\u201d explains an accompanying Sony AI blog post<\/a>. \u201cThis is fast enough to capture motion that would be a blur to the human eye.\u201d<\/p>\n

Deep reinforcement learning allows it to seamlessly predict ball behavior and choose how to counter its opponent.<\/p>\n

Meanwhile, many high-level players were baffled by the apparatus. It\u2019s essentially \u201cimpossible to sense what kind of shots it dislikes or struggles with, and that makes it even more difficult to play against,\u201d table tennis pro Mayuka Taira told Reuters<\/em>.<\/p>\n

Nonetheless, D\u00fcrr noted that pro players will still have an edge \u2014 at least for now \u2014 since they remain \u201cvery good at adapting to their opponent and finding weaknesses, which is an area that we are working on.\u201d<\/p>\n

More on table tennis:<\/strong> This Video of a Humanoid Robot Playing Tennis Is Extremely Impressive<\/em><\/a><\/p>\n

The post New AI-Powered Robot Can Destroy Human Champions at Ping Pong<\/a> appeared first on Futurism<\/a>.<\/p>\n<\/div>\n

<\/div>","protected":false},"excerpt":{"rendered":"

First, they learned how to play tennis on two feet. Then, they came for our half-marathon world record. Now, robots are set to overtake us in the sport of table…<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[177,2700,3845],"tags":[],"class_list":["post-10530","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","category-robotics","category-robots-and-machines"],"_links":{"self":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts\/10530","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/comments?post=10530"}],"version-history":[{"count":0,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/posts\/10530\/revisions"}],"wp:attachment":[{"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/media?parent=10530"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/categories?post=10530"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/musictechohio.online\/site\/wp-json\/wp\/v2\/tags?post=10530"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}