Google DeepMind claims it has made a “historic” 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.
A version of the company’s 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.
In a performance that the tech company called a “profound leap in abstract problem-solving”, 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.
None of the human teams, including the top performers from universities in Russia, China and Japan, got it right.
It failed two of the 12 tasks it was set, but its overall performance ranked it in second place out of 139 of the world’s strongest college-level computer programmers. Google said it was a “historic moment, towards AGI [artificial general intelligence]”, which is widely considered human-level intelligence at a wide range of tasks.
“For me it’s a moment that is equivalent to Deep Blue for Chess and AlphaGo for Go,” said Quoc Le, Google DeepMind’s vice-president. “Even bigger, it is reasoning more towards the real world, not just a constrained environment [like Chess and Go] … Because of that I think this advance has the potential to transform many scientific and engineering disciplines.” He cited drug and chip design.
The model is a general purpose AI but was specially trained to solve very hard coding, maths and reasoning problems. It performed “as well as a top 20 coder in the world”, Google said.
“Solving 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,” the company said.
Speaking before the details were made public, Stuart Russell, a professor of computer science at the University of California at Berkeley, said the “claims of epochal significance seem overblown”. He said AI systems had been doing well on programming tasks for a while and the Deep Blue chess breakthrough had “essentially no impact on the real world of applied AI”.
However, he said “to 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”.
He added: “The pressure on AI companies to keep claiming breakthroughs is enormous”.
Michael Wooldridge, Ashall professor of the foundations of artificial intelligence at the…
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