{"id":234319,"date":"2025-09-17T17:20:14","date_gmt":"2025-09-17T17:20:14","guid":{"rendered":"https:\/\/www.europesays.com\/us\/234319\/"},"modified":"2025-09-17T17:20:14","modified_gmt":"2025-09-17T17:20:14","slug":"google-deepmind-claims-historic-ai-breakthrough-in-problem-solving-artificial-intelligence-ai","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/us\/234319\/","title":{"rendered":"Google DeepMind claims \u2018historic\u2019 AI breakthrough in problem solving | Artificial intelligence (AI)"},"content":{"rendered":"

Google DeepMind<\/a> claims it has made a \u201chistoric\u201d artificial intelligence breakthrough akin to the Deep Blue computer defeating Garry Kasparov at chess in 1997 and an AI beating a human Go champion in 2016.<\/p>\n

A version of the company\u2019s Gemini 2.5 AI model solved a complex real-world problem that stumped human computer programmers to become the first AI model to win a gold medal at an international programming competition held earlier this month in Azerbaijan.<\/p>\n

In a performance that the tech company called a \u201cprofound leap in abstract problem-solving\u201d it took less than half an hour to work out how to weigh up an infinite number of possibilities in order to send a liquid through a network of ducts to a set of interconnected reservoirs. The goal was to distribute it as quickly as possible.<\/p>\n

None of the human teams, including the top performers from universities in Russia, China and Japan, got it right.<\/p>\n

It failed on two out of the 12 tasks it was set, but its overall performance ranked it in second place out of 139 of the world\u2019s strongest college level computer programmers. Google<\/a> said it was a \u201chistoric moment, towards AGI [artificial general intelligence],\u201d which is widely considered human-level intelligence at a wide range of tasks.<\/p>\n

\u201cFor me it\u2019s a moment that is equivalent to Deep Blue for Chess and AlphaGo for Go,\u201d said Quoc Le, Google DeepMind\u2019s vice-president. \u201cEven bigger it is reasoning more towards the real world, not just a constrained environment [like Chess and Go] \u2026 Because of that I think this advance has the potential to transform many scientific and engineering disciplines.\u201d He cited drug and chip design.<\/p>\n

The model is a general purpose AI but was specially trained to solve very hard coding, maths and reasoning problems. It performed \u201cas well as a top 20 coder in the world\u201d, Google said.<\/p>\n

\u201cSolving complex tasks at these competitions requires deep abstract reasoning, creativity, the ability to synthesise novel solutions to problems never seen before and a genuine spark of ingenuity,\u201d the company said.<\/p>\n

Speaking before the details were made public, Stuart Russell, professor of computer science at the University of California at Berkeley, cautioned the \u201cclaims of epochal significance seem overblown\u201d. He said AI systems have been doing well on programming tasks for a while and the Deep Blue chess breakthrough had \u201cessentially no impact on the real world of applied AI\u201d.<\/p>\n

However, he said \u201cto get an ICPC question right, the code actually has to work correctly (at least on a finite number of test cases), so this performance may show progress towards making AI-based coding systems sufficiently accurate for producing high-quality code\u201d.<\/p>\n

He added: \u201cThe pressure on AI companies to keep claiming breakthroughs is enormous\u201d.<\/p>\n

Michael Wooldridge, Ashall professor of the foundations of artificial intelligence at the University of Oxford, said it sounded like an impressive achievement and \u201cbeing able to solve problems at this level is exciting\u201d. But he questioned how much computing power was needed. Google declined to say, apart from confirming it was more than available to an average subscriber to its $250-a-month Google AI Ultra service using the lightweight version of Gemini 2.5 Deep Think in the Gemini App.<\/p>\n

Dr Bill Poucher, executive director of the ICPC, said: \u201cGemini successfully joining this arena, and achieving gold-level results, marks a key moment in defining the AI tools and academic standards needed for the next generation.\u201d<\/p>\n

Four machine intelligence breakthroughs<\/p>\n

1957 <\/strong>The Perceptron<\/p>\n

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An academic at Cornell University, Frank Rosenblatt, worked out that it should be possible to create a \u201cperceiving and recognising automaton\u201d. He dubbed it the Perceptron and said<\/a> an electronic system would be able to learn to recognised patterns in optical, electrical or tonal information \u201cin a manner which may be closely analogous to the perceptual process of a biological brain\u201d. The following year he built the device, which was the size of a small room. It was considered one of the early breakthroughs in artificial intelligence based on neural networks.<\/p>\n

1997 <\/strong>Big Blue<\/p>\n

In May 1997, IBM\u2019s Big Blue became the first computer system to defeat a reigning world chess champion in a match under standard tournament controls. It beat<\/a> Garry Kasparov in what became an inflection point in computing power, but the contest was close. Kasparov won the first game, Deep Blue the second followed by three draws. Deep Blue won game 6 to secure the win. It showed how brute force computing power could create a system to defeat a human, albeit at a narrow task. \u201cThe computer is far stronger than anybody expected,\u201d said Kasparov, conceding defeat.<\/p>\n

2016 <\/strong>AlphaGo<\/p>\n

Go is one of the most complex games ever devised, and one of the world\u2019s master players was Lee Sedol, a South Korean professional. In 2016, DeepMind, the UK AI company set up by Demis Hassabis, took him on with its computer AlphaGo. It won 4-1 and some of its moves seemed to display truly original thinking. Move 37 in particular went down in lore. Hassibis said<\/a> it \u201cmight be the first glimpse of a bright and bold future where humanity harnesses AI as a powerful new tool, helping us discover new knowledge that can solve some of our most pressing scientific problems\u201d.<\/p>\n

2020 <\/strong>AlphaFold<\/p>\n

Another breakthrough by Hassibis and DeepMind was an AI program that can predict how proteins fold into 3D shapes, a highly complex process fundamental to understanding life\u2019s biological machinery. It was called<\/a> \u201ca stunning advance\u201d by the Royal Society, the 360-year old London scientific institution.<\/p>\n

When researchers know how a protein folds up, they can start to uncover mysteries such as how insulin controls sugar levels in the blood or how antibodies fight viruses. After further iterations, the system helped Hassibis and his colleague John Jumper share a Nobel prize for chemistry in 2024.<\/p>\n","protected":false},"excerpt":{"rendered":"Google DeepMind claims it has made a \u201chistoric\u201d artificial intelligence breakthrough akin to the Deep Blue computer defeating…\n","protected":false},"author":3,"featured_media":234320,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[691,738,158,67,132,68],"class_list":{"0":"post-234319","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-technology","11":"tag-united-states","12":"tag-unitedstates","13":"tag-us"},"share_on_mastodon":{"url":"https:\/\/pubeurope.com\/@us\/115220789544475498","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/posts\/234319","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/comments?post=234319"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/posts\/234319\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/media\/234320"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/media?parent=234319"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/categories?post=234319"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/tags?post=234319"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}