It is oddly mesmerising. The robotic ping-pong paddle swishes relentlessly. Like a cyborg Forrest Gump it returns each shot and is ready for the next. Eventually, the human falters. The robot does not. This week for the first time \u2014 impressively, pointlessly \u2014 a robot taught itself to beat elite ping-pong players. Or was it pointless? When I saw this terminator of table tennis I thought not of ping-pong but Pong.<\/p>\n
Back in 2013 a British tech start-up wanted to program a computer to win at the classic Atari game. They had an odd approach. They didn\u2019t tell it what to do. They thought it could learn, make mistakes, iterate and improve \u2014 like a human. For weeks the pixellated bat flapped uselessly. Then one day, it returned the ball and scored a point. The next day it won a game. Soon after, it never lost. It was impressive. It was also, I felt at the time, pointless. What confused me even more was why Google then paid hundreds of millions for this company.<\/p>\n
Well, the company is DeepMind, it runs Google\u2019s AI division, and I am confused no more. All of which is to say, don\u2019t make the mistake of thinking this week\u2019s ping-pong news is just good fun. Instead, a lot of money is betting it\u2019s something rather more serious. Robots are, increasingly, moving out of factories into the messy, unpredictable, real world. Over the past year we have seen Chinese robots dancing, American robots walking. Just this week, one ran a half marathon.<\/p>\n
Sometimes, they look sinister. More often, just silly. They fall over. They fail. This year a domestic kitchen robot was unveiled. Someone on social media likened watching the video of it painfully stacking the dishwasher to \u201csimulating the experience of a room-mate with ketamine\u201d. This is, increasingly, our consolation. AI might threaten the professions but for jobs in the fuzzy three-dimensional world of gravity, uncertainty and scraping the red onion gravy off the plate before washing up? Well, there, surely, we have primacy?<\/p>\n
I wouldn\u2019t rush to plumbing courses just yet. It may be that the reason computers can hold fluent conversations and answer (semi-plausibly) any question about the world, but not change a washer, is because discoursing on, say, philosophy is easy. Or maybe it\u2019s because, unlike with language, they\u2019ve almost never seen a tap installed.<\/p>\n
The advantage large language models such as ChatGPT had is that they could steal all the writing there has ever been. Trillions of words \u2014 all human knowledge, nicked from the internet in the heist of the century. Physical robots don\u2019t have that. Yet.<\/p>\n
There is a lab in MIT where people chop carrots, load dishwashers, clean surfaces \u2014 their every movement recorded for robots. Google and Meta both have thousands of hours of footage of humans. Nvidia has 20,000 hours of hand movements. Toyota is developing a robotic \u201clarge behaviour model\u201d. They are betting that with enough data will come a sudden, almost magical, moment of emergent competence. They want a ChatGPT moment for physical robotics.<\/p>\n
Maybe it\u2019s a dud bet. Ping-pong is a long way from, say, cooking and cleaning. But then, Pong is a long way from automatic language translation, photorealistic image generation and \u2014 the direct descendant of that 2013 Pong program \u2014 getting a Nobel prize for solving protein folding.
So don\u2019t be too deceived by the ketamine-addled domestic servant. As it drops plates and puts\u00ad cups in the cutlery basket, it is biding its time, awaiting its software upgrade \u2026 and our usefulness downgrade.<\/p>\n","protected":false},"excerpt":{"rendered":"It is oddly mesmerising. The robotic ping-pong paddle swishes relentlessly. Like a cyborg Forrest Gump it returns each…\n","protected":false},"author":2,"featured_media":549413,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[554,733,4308,86,56,54,55],"class_list":{"0":"post-549412","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-artificialintelligence","11":"tag-technology","12":"tag-uk","13":"tag-united-kingdom","14":"tag-unitedkingdom"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/549412","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/comments?post=549412"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/549412\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media\/549413"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media?parent=549412"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/categories?post=549412"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/tags?post=549412"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}