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From games to biology and beyond: 10 years of AlphaGo’s impact
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Google DeepMind

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AI LabsGoogle DeepMind

From games to biology and beyond: 10 years of AlphaGo’s impact

March 10, 2026 Research

Demis Hassabis

Ten years ago, our AI system AlphaGo became the first program to defeat a world champion at the complex game of Go – reaching a milestone in the field a decade before many experts thought possible.

The achievement heralded the beginning of what is now recognized as the modern era in artificial intelligence (AI). With a single creative play, the famous ‘Move 37,’ AlphaGo demonstrated the potential of AI and signaled that we now had the techniques to begin tackling real-world scientific problems.

Today, this breakthrough continues to inform our work building systems on the path to artificial general intelligence (AGI). We believe AGI will be the most profound technology ever invented and potentially the ultimate tool to advance science, medicine, and productivity.

A creative spark

In 2016, over 200 million people watched AlphaGo face world-champion Go player Lee Sae Dol in Seoul. The match was defined by ‘Move 37’ in Game 2, a play so unconventional that professional commentators initially thought it was a mistake. But it proved to be decisive. One hundred or so moves later, the stone was in exactly the right position for AlphaGo to win the game. It was a display of incredible foresight and the AI system’s ability to go beyond mimicking human experts and find entirely new strategies.

Go has long been a proving ground for AI research because of the game’s sheer complexity. There are 10170 possible positions on the board—far more than the number of atoms in the observable universe.

To make the game tractable, AlphaGo used deep neural networks combined with advanced search and reinforcement learning – an AI approach DeepMind pioneered.

It was further proof of what I knew the moment we won the match in Seoul - the technology was ready to be applied to our real goal of accelerating scientific breakthroughs.

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