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.
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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.
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.