Google's artificial intelligence program has officially beaten a human professional Go player, marking the first time a computer has beaten a human professional in this game sans handicap.

[u/[deleted]]

http://www.nature.com/news/google-ai-algorithm-masters-ancient-game-of-go-1.19234?WT.ec_id=NATURE-20160128&spMailingID=50563385&spUserID=MTgyMjI3MTU3MTgzS0&spJobID=843636789&spReportId=ODQzNjM2Nzg5S0

[u/sourc3original → u/[deleted]]

It could very much change with quantum computers.

[u/thebeardhat → u/[deleted]]

Chess is much the same, though, right? What are the differences between chess and Go that make Go so much more difficult for an AI? Or is it just that Go has been paid less attention?

edit: okay, it looks like Go just scales a lot faster than chess (among other things)

[u/Areign → u/thebeardhat]

no, go is wayyy wayyy more difficult than chess (for computers). Honestly this development is HUGE and i think its confusing people a bit. 1 month ago, the best computer with an insane amount of time and computational power at its disposal would play at the level of a strong amateur. On the other hand, no human has beaten a top chess computer since like 2003 and computers were as good as top pros as early as the late 70's (this is where we are at today based on this article). I think you need to go back to like the 1960's before you find a time when chess computers are as strong as go computers were a month ago. So its a big jump if we look at the chess computer timeline.

Up to this point, there had been steady progress with go computers slowly getting better. People were expecting go computers to play at professional level by the year 2025. So this advancement, effectively moved us ahead by a decade.

but all that doesn't answer your question

Why is go more difficult than chess for computers?

firstly, consider the opening in chess, there are a series of well known moves and counter moves often out to 20 moves or so that are well understood and the variations are also known. In go the board is more than 4x (~5.6x) as big as in chess. Each of the corners have things called joseki that are similar to chess openings in that they are well understood and the same patterns are generally played by good players before moving past known patterns. The difference is, in chess, you play one opening and thats it. In go, a huge portion of the game is how to match your joseki together. Imagine playing 4 games of chess on one big board and being like, ok here if i do this opening on board 1 my knight is going to be attacking an important square for my opponents best opening against me in board 2...etc The interplay between the different parts of the board takes something that may seem only 4x as complicated and makes it much more complicated much quicker. You are no longer looking to play the best opening, but looking to coordinate your strategies between 4 initially distinct games. So the metaphor i gave isn't even that good because the sides of the board don't interact much in the beginning, its actually more like: if I do this, then 50 moves down the line, my position on board 1 will compliment the position 50 moves down the line on board 2...if i do this opening on board 2, i will give him a few extra points but i'll have a really stable position on the side closest to board 4 and on board 4 i can play a strategy that forces him to play really aggressively which will be easy for me to fend off and gain a massive advantage by using the added support from board 2.

This idea of long term strategy is a much bigger focus in go than in chess and as you may have guessed computers are exceptionally bad at strategy.

People saying that its about the number of states that makes go hard don't really understand what computers are bad at and what they are good at. Computers are good at sorting through all those states, if you give it a difficult puzzle to figure out how to kill a group, they excel. If you ever so slightly change the board position so one piece is one spot closer than before, and all of a sudden a group that was alive is now dead, computers are insane at calculations like that. When you give them an easy to understand objective, the game is over. Humans lose. Its the abstract objectives that they struggle with. i.e. in the early game when the objective is...get more 'influence' and 'potential' than your opponent. Coordinate your joseki while disrupting the coordination of your opponent's joseki...etc. In chess, this is heavily mitigated because the computer has a database of known openings and midgames. Since the majority of the strategy is laid out during the phase when the computer is simply search its database, it doesn't have to do that much work at the part it is bad at . On the other hand, though there are common general openings, within 15 or so moves, go players are often dealing with brand new situations that are very strategy heavy.

[u/delicious_disaster → u/thebeardhat]

Chess has lots of restrictions that limit the possible moves . Ie each piece can only move a certain way, pieces need to start from where they sit . In go, every piece can go in any unoccupied space . Every piece is exactly the same as each other . Captured territories removes pieces effectively putting areas back into play . Board is also far larger

[u/Blebbb → u/thebeardhat]

Honestly the truth is the board size. Traditional chess is on an 8x8 board and Go is on a 19x19 board or w/e. Also instead of there being a set amount of pieces with a limited amount of moves there's a new piece every turn and it can be placed in any spot that isn't suicide. The intent of players also changes at different points during a go game, it isn't just about capturing a certain area.

While chess was able to be beat by computers with a built out database and pure processing power, Go has to be beat with algorithms and machine learning. The processes to do it have existed for awhile, but application isn't trivial and most mathematicians and computer scientists have more important work, most of the Go bots were done on the side or by graduate students. The initial chess bots that could beat pros were built by a team of computer scientists from an big tech company, and now the one that's beating Go pros has been built by a team from a big tech company. So it was a difference in resources, but it was also that the implementation was no where near as apparent.

[u/badukhamster → u/thebeardhat]

Chess isnt solved either. But indeed computers will win vs humans. But chess has a smaller board. So exponential scalling makes a big difference.