Fan Hui, the European Go champion, needed some fresh air. “I don’t understand myself anymore.”
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Hui was the first professional Go player to face AlphaGo, Google’s Artificial Intelligence knows many different definitions, but in general it can be defined as a machine completing complex tasks intelligently, meaning that it mirrors human intelligence and evolves with time. system and the title of a new documentary by Greg Kohs that debuted last week at the Tribeca Film Festival in New York. When Hui was invited to visit Google’s London office housing the DeepMind research group that developed AlphaGo, he was feeling confident. After all, as Hui puts it, “it is just a program.”
Human vs. Machine
Hui had reason to be confident. Although has achieved impressive feats in the last few years, Go has been a longstanding and especially daunting challenge—the “pinnacle of board games” says Demis Hassabis, cofounder and CEO of Google DeepMind and a world-class game player himself. No program had ever defeated a human professional on a full-sized board, and when Hui played that afternoon in London, he wasn’t expecting a challenge.
But AlphaGo was no ordinary Go program. It was the product of innovative engineering, and the teamwork of a couple dozen scientists at DeepMind. Importantly, it also played a superhuman amount of Go, using that experience to train its deep Neural Networks are simplified abstract models of the human brain. Usually they have different layers and many nodes. Each layer receives input on which it carries out simple computations, and passes on the result to the next layer, by the final layer the answer to whatever problem will be produced. and improve its play. By the time it faced Hui, AlphaGo had trained on 160,000 games recorded from top Go players, and then on 30 million more games it played against itself. As Hui found himself losing to AlphaGo, he knew that his world—and the world of professional Go—was about to change forever.
Cinematic documentation of a de-throning
In a film that documents a technical achievement, I saw two human stories. There is the work of the DeepMind scientists and their impressive quest to reach this milestone. But there is also the story of Fan Hui and others who dedicate their lives to studying this game. Cinematically, the latter story shines. How does it feel to no longer be the best? If mastering Go “requires human intuition,” what is it like to have a piece of one’s humanity challenged?