This really suggests that going the path of being the strongest is no longer sensical. Why would a human try to be the best calculator in the world, knowing it will never beat any calculator ever? Just to prove itself to other human caculator wannabes? Senseless.
This is a real paradigm shift and we still need to understand what to do. But obliviously ignore AlphaGo is akin should be unfathomable for a professional aspiring player.
As a professional, the first question to ask is what will AlphaGo bring to Go Theory. We still dont know how much stronger it is than Lee Sedol (or how far it is from "God"). Pushing it to its limits will show us insights we havent found yet and we will update ourselves as players to the most current theory.
The second step is answering the following question: Can human + AlphaGo beat Alpha Go? A human potentiated with AlphaGo's reading power can intuitively pick variations that would give it an edge? If so, we have found that Go still harbors a human secret that is jsut overly compensated by reading.
The last step would be, even if human participation gives negligible results, can human + Alpha Go create better games than Alpha Go?
The super GMs of the world - and basically all of the chess loving public with them - seem to have acknowledged it and moved on; why would such a transition be impossible in Go?
I cannot speak for Chess's mindset but as a Devoted Go Player, we are collectively trying to solve it, and so we have for centuries. We play Go to explore its universe and reach utmost understanding of the game(and a glimpse of ourselves). If we ever find(which eventually we shuold) the exact single pattern that is best for both players, and we solve the game, it becomes something different. Maybe it becomes something senseless, or something artful(I can explain the 'art' part if someone asks) but trying to be competitive is silly.
If I devoted my life to Go today, I would not aim at becoming better competing, I'd have to aim at a more effective way to solve the game. Competing was the only thing we had to figure out what was best, but now we can have a companion that will prevent us from faulty variations and logic, and give us instant validation. We can discover more fuseki with a focus group and AlphaGo in a month than in a decade of tournaments.
Competing for the sake of competing is a petty goal.
Is there a particular reason why a chess computer would be any more undefeatable than a Go computer? Even though Kasparov lost, Nakamura destroyed Rybka 10 years later. Now that we have a competitive Go AI, isn't it likely the game of Go will shift and be even more competitive since now more players can get world-class practice and suggestions on their own?
It played better because it knew the exact consequences of the options it was presented, and could calculate it and make better decisions than human intuition. No human can develop that reading power, and its not reasonable to think a human in the future will have intuition that beats the calculation of AlphaGo.
Since reading, the core ability of Go can now be completely replaced by a computer, the question is what others decisions can a player make. Can he make strategic decisions better than AlphaGo? Can intuition still best AlphaGo calculating capacity?
Eventually, we can think that we will have computational power to actually solve Go, and if there is any sense at all to play Go after that, its about finding those beautiful games, from beginning to end, that provoke emotions and turn Go purely into art.
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.
I don't think they are the same things. Marathon is about the physical limit of human beings, while Go is about mental limit.
Before there are cars, or trains, we all know we are not the fastest in the world. A rabbit can easily overrun an adult human.
However, we never thought that a dog or a bird will beat us in a game like GO. Thinking a machine beating the human champion in the game of GO, is like admitting that we are intelligently inferior to machines.
Is this Poe's Law in action?
Likewise, if machines can do quality accounting, does that mean that accounts will be relegated to special accounting events, just like there are marathon events, where people come for aesthetic enjoyment or audience spectacle?
There's real cases of similar technology putting people out of jobs, for example I recently read that more and more finance firms more or less completely automate a lot of processes, even those where you'd traditionally would have counted on people's "gut feelings". Deep learning is eerily good at simulating "gut feelings".
However, cheating with computer assistance is likely to become a problem, as it is in chess.[1] (The state of the art in computer chess is now roughly at "laptop with off the shelf program can curb-stomp human world champion.")
[1] http://en.chessbase.com/post/yet-another-case-of-cheating-in...
[1] https://twitter.com/demishassabis/status/708489093676568576
So to me this underscores the relative importance of the deep learning model vs the tree search.
[1] http://noenthuda.com/blog/2016/03/11/how-computers-have-chan...
The relevant paragraph is the one with the heading "Machine changes human", at the end.
http://www.wired.com/2016/03/sadness-beauty-watching-googles...
Actually I would expect game-players and game-instructors to do better than the median profession under such a scenario, because playing games against other humans for entertainment & pure enjoyment of competition is a very human pursuit.
Hell, Google should organize a "AlphaGo against the world" on internet.
Edit: fortunately the fine article brings this up and goes further to point out that go is fundamental to self improvement in some cultures and will likely have a long life after AlphaGo.
Humanity has very limited purpose in the Culture. On the surface, it looks nice, but they're effectively pets. Their willingness to ascend was cut off right along with their willingness to live.
All of which is done by social engineering. If you want to go the intelligence-enhancement route, they'll help. They just make sure that very few people do.
It's also mentioned that you can have your mind transferred into a drone busy, and vice versa, but it's seen as terribly gauche.
The manners as laws thing is cute, but I don't see it working without invasive non-consensual modification of humans.
E.g. from my own perspective, if I live in a world where there are humans and human-created demigods, then obviously I want to be one of the demigods. Not to enslave the humans, but to look inside of black holes, to travel between stars, to fully understand how biology works, etc.
So not everyone wants to be a scientist or engineer, but wouldn't almost all engineers and scientists want to wield the very best mental and technological tools of their civilization?
Its kind of like climbing mount Everest 'because it was there'. Its just not 'there' anymore.
We still enjoy trivia games even though it is easy to google the answers. I dunno, I think it is a bit of a stretch to think AlphaGo has ended serious competitive human Go.
The analogy to chess is an interesting one, though, not quite as straightforward as it may seem. Chess, when it was first conquered by computers a couple of decades ago, was a triumph of computer vs human, sure, but in such a different way from the way humans play it. Chess is amenable to brute force search in a way that go isn't (though I understand the chess programs really aren't pure brute force), but human chess players don't (as far as I know) really don't play chess in a brute force way, they rely in intuition, experience, and even a bit of gambling and hedging whether their opponent will "see" or "realize" the strategy in time.
As a result, the chess programs were winning through a "reasoning" process that was very different from what you experience watching people play the game. Something very different is going on when humans play, which makes it interesting - in that sense you can sort of dismiss the machine as playing a different game, albeit one with the same board, pieces, and rules. Instead, it's a giant calculation that happens to beat the more intuitive approach once you can search and score X positions per second through an entirely alternate approach to the game.
This current breakthrough with go sounds different, in that it may mean that computers now play go in a way that is much more similar to the way humans play it (it would be interesting to see if a chess program designed more like the go program would have a huge edge over the brute force search approach). Or, if not the same, perhaps a way that is equally if not more interesting.
I'm kind of bummed that I'm out of my depth on this one (I don't know go or chess well enough to really say), but it's an interesting question.
I also expect that more people will start playing Go, or like me, get a renewed interest in the game.
I read that Lee Sidol is planning on retiring from active play in a few years and move to the USA to evangelize the game in the West.
I played the South Korean national champion and the women's world champion in handicapped exhibition games in the 1970s. It would be awesome to get to do the same with Lee Sidol!
“A dolphin swims faster than Michael Phelps, but we still want to see how fast he can go,” Lockhart said. “We’re humans and we care about other humans and what they can do.”
Too many words, too little information for one article.
And if the answer is yes, why isn't anyone trying to use robots for that purpose?
I gather this may be a Big Deal, but except insofar as it kills the sport by a thousand cuts, 'Young Go Prodigies' have nothing to worry about.
Since the computer can tell for every single move whether you played perfectly or if not, by how much you decreased your chances of winning against perfect competition, you'll be able to get a hundred signals out of a game into your elo calculation, instead of just one win/loss condition.
They already do that for catching cheaters in chess. In essence, you treat the positions that occur in a game not as a logical sequence, but as a series of multiple-choice questions.
You're thinking in terms of 'The AI has solved Go mathematically', but that's not the case; Just because you can run a Monte Carlo best-choice-picker/guesser algorithm doesn't mean you can meaningfully rank how deliberate choices compare with each other more than a few plays away.
Go hasn't been solved to that level, but it's apparently been solved to higher level than humans ever reached.
I am just parroting http://www.uschess.org/content/view/12677/763 here, so I might as well quote:
"To catch an alleged cheater, Regan takes a set of chess positions played by a single player—ideally 200 or more but his analysis can work with as few as 20—and treats each position like a question on a multiple-choice exam. The score on this exam translates to an Elo rating, a score Regan calls an Intrinsic Performance Rating (IPR)."
This approach also allows to score historic players absolutely, instead of only relatively and trying to find sets of overlapping lifetimes until we reach the modern age.
But there's so much more to this than human obsolescence. This is the cusp of a new stage in evolution.
Why are there so many young programmers adopting the Go
programming language, throughout Asia, exclusively?