Remember that AlphaGo has spent months developing its own style and theory of the game in a way that no human has ever seen. Its style is sure to have weaknesses, but humans will have a hard time figuring them out on first sight.
Similarly chess computers do better in some positions than others (they love open tactics!) and one of the games that Kasparov won against Deep Blue he won by playing an extreme anti-silicon style that took advantage of computer weaknesses. However Kasparov didn't have to figure out what that style was because there was a lot of knowledge floating around about how to do that.
Therefore I'd expect that Lee Sedol from a year from now could beat AlphaGo from today. And human Go will improve in general from trying to figure out what AlphaGo has discovered.
However that won't help humans going forward. AlphaGo is not done figuring out the game. At its current rate of improvement, AlphaGo a year from now, running on a single PC, should be able to beat the full distributed version of AlphaGo that is playing today. Now the march of progress is not whether computers can beat professionals. It is going to be how small a computing device can be and still beat the best player in the world.
But when the weaknesses it has require looking 20 ply into the game, can anyone exploit those weaknesses? And furthermore, if the computer itself is able to see 20 ply into the game, then it can spot its own weaknesses and you need to look even further, making the question of whether it's really a weakness.
Weaknesses are only relative to capabilities of the opponent to exploit them. If a tank has a weak spot that rockets can hit, but it's being opposed by humans on horseback, is it really a weakness in that context?
The weaknesses that it has will be of the form that it has wrong opinions about certain kinds of positions. In the case of chess, those weaknesses showed up in closed positions where the program owned the center and large amounts of space. In the case of AlphaGo, the weaknesses will be much more subtle, but will be discoverable and exploitable in time.
Additionally AlphaGo has the advantage that it started with a database of human play, so it has some ideas what kinds of positions humans miscalculate.
As for your tank vs horseback analogy, that's flawed at the moment. AlphaGo is probably reasonably close in strength to the human facing him. Improved human knowledge could tip the balance.
However in the future it will become an apt analogy. Computers are going to become so good that knowing the relative weaknesses in their style of play may reduce the handicap you need against them, but won't give you a chance of becoming even with them. That happened close to 20 years ago in chess, and is now only a question of time in Go.
I wonder if AlphaGo has some specialized knowledge to handle ladders, where stones can have an effect at a distance that might only come into play after 20 moves.
20 moves may sound like a huge number of variations but when you prune things early, it can be quite manageable. The alphabeta algorithm in chess does pruning quite a lot.
Remember that AlphaGo has spent months developing its own style and theory of the game in a way that no human has ever seen. Its style is sure to have weaknesses, but humans will have a hard time figuring them out on first sight.
Similarly chess computers do better in some positions than others (they love open tactics!) and one of the games that Kasparov won against Deep Blue he won by playing an extreme anti-silicon style that took advantage of computer weaknesses. However Kasparov didn't have to figure out what that style was because there was a lot of knowledge floating around about how to do that.
Therefore I'd expect that Lee Sedol from a year from now could beat AlphaGo from today. And human Go will improve in general from trying to figure out what AlphaGo has discovered.
However that won't help humans going forward. AlphaGo is not done figuring out the game. At its current rate of improvement, AlphaGo a year from now, running on a single PC, should be able to beat the full distributed version of AlphaGo that is playing today. Now the march of progress is not whether computers can beat professionals. It is going to be how small a computing device can be and still beat the best player in the world.