AlphaGo (2017)

I went into this documentary knowing nothing about Go, the centuries-old board game that is hugely popular across East Asia and is decided by who controls more territory on the board. What stayed with me is how long experts assumed a machine would need at least a decade before it could beat a top human player. Go has more possible board positions than there are atoms in the observable universe, and strong players lean on something close to intuition, which I assumed would be very hard for software to copy. The film follows the program that proved those assumptions wrong, and I found myself wondering whether future AI might simply learn to teach itself.

The story turns on Fan Hui, a professional player ranked well below the best, who lost a five-game series to AlphaGo in 2015. That loss set up a match against Lee Sedol, widely considered the strongest player in the world, and I was struck that Fan Hui later helped the team locate the program’s weak spots. Watching this, I kept thinking about how flexibly the human mind connects what it learns, compared with a system built around narrow goals.

What lingers is the speculation the film invites about what comes next, including medical tools that could support doctors, tailor treatments, and predict health outcomes. The documentary works as both entertainment and education, and its emotional moments, which echo the old John Henry legend of human against machine, hit hard. If the subject interests you at all, watch it and see how the match turns out.