I like that analogy a lot! It's not like "playing Go really well" ever solved any real-world problem, it has always been a competition among humans. What should change, there?
I feel like the author completely misunderstood why AlphaGo is exciting. It's about advancements in technology and soft AI, Go has almost nothing to do with it.
Well, we're on hackernews, we like the tech stuff. For most of the world, this news is where people learn about Go and the human player's "humiliation" (whether or not the Go community sees it that way) is the story.
I'd argue, though, that this is merely a proof of deep learning being able to solve "hard" problems. There's headlines everywhere about deep learning solving previously "impossible" image recognition problems, for example. Fields that are much more interesting and relevant in their real-world impact. AlphaGo, in comparison, seems like a PR/pet project. It mostly exists to play Go really well. It's a sub-branch of uses of the technology, not a start.
>Well, we're on hackernews, we like the tech stuff. For most of the world, this news is where people learn about Go and the human player's "humiliation" (whether or not the Go community sees it that way) is the story.
In that regard, Lee Sedol has done the game of Go a great service by being so gracious in defeat (and for once, the media headlines actually mirror his humility and maturity). That has actually been my lasting impression from the match.
Maybe that's why AlphaGo is exciting to you. I don't give a shit about technology and AI compared to how much I want to watch AlphaGo play more games of Go, and I suppose that professionals probably feel the same way.
we're slowly moving towards anticipation in continuous strategy games, and life. progressively better decisions/anticipation in progressively much much larger decision space is how this is relevant