On AlphaGo and sadness

AlphaGo won the last game against Lee Sedol and has completed a near perfect score of 4-1 in the match. That has proven how incredible what Google DeepMind team has accomplished with this AI system and paves the way for future applications of this engine.

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As I wrote this morning commenting at Slashdot, this is impressive and somewhat sad. I’ve been following the matches with the same expectation and anger I felt in 1997 during the Kasparov & Deep Blue rematch.

The final result has been similar, and although it has been well reasoned that chess and go are pretty different games and Deep Blue and AlphaGo are pretty different machines, the bittersweet sensation is identical. I had a naive hope in the human superiority just for a little more time, but I was pretty sad after the final game: Lee Sedol seemed really disappointed and sad himself.

I can’t imagine the pressure he’s felt throughout the event, and his face -that’s my impression- seemed to tell us “I’ve failed you all“. He later told in the press conference that he felt he could have done more in the games -I’m sure he’d like to play more games to test himself again- and I wonder what could have happened if the matches would have been played without general knowledge.

Feeling that kind of coverage must have been really stressful. If you ever read this, Mr. Sedol, thank you. And please, don’t ever feel disappointed, you’ve done a fantastic job.

The triumph of AI

AlphaGo has beaten Lee Se-dol, one of the best Go players in the world. A machine has showed us its superiority at something that during decades was dominated by human intelligence. And that proves once again that Artificial Intelligence has an incredible path ahead, one that is both incredibly promising and incredibly disturbing.

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The feat was accomplished a few hours ago, and it really doesn’t matter that this is only the first of five games. The victory of the machine shows that AI can go beyond what chess programs accomplished in the 90s. Playing chess against a computer is useless even for grandmasters, because even a mobile phone with the right software can beat most professional players right now.

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This will happen too with Go, a much more complicated board game that relies not only on raw power to calculate future movements and positions: it relies on intuition. Google has given AlphaGo that intuition, and we must wonder what will be the next disturbing marvel we’ll watch in this area.

We should be amazed, but I can’t help thinking if we should be more and more worried about what this can lead us to. Coming from a computer nerd, the situation is more and more troubling.

Bumpy road ahead.