> How would you characterize the differences and similarities between AlphaGo and the best human players?
The alphago that played Lee Sedol was still very machine-like. But the master series online felt like strong superiority. It started playing some novel moves that being at least reasonable, would make it harder to play against. In a way, it was like the radical new kid with new ideas that shakes up the foundations.
So far in this game (move 40~0) i read calmness from white ,a calculated calmness. As if it knew that it would win.
Note: in Go, you perceive a lot of feelings from your opponent, as the moves selected express a state of mind or emotion. AlphaGo is getting hard to distinguish from human beings.
> How has human play style changed since AlphaGo's introduction?
Hard to say, but alphago is definitely changing the fields of study. Professional go really is like brute-forcing the game. A professinoal chooses to go through an unstudied path because he thinks its superior, and then another professional tries to ravage that path. That adversity over professional games is what advances theory.
In this game, black playing 3-3 (bottom right corner invasion) would have never been played before AlphaGo in the state of human theory. I was taught 15 years ago in my first beginner class how bad doing that is.
> What is the answer to the question you most want to be asked?
I guess that the most important question is what is the future of Go. Sure, current professionals will still live their lives by the game, but what is the point of being a professional in something a computer will just be better.
As soon as AlphaGo beat lee sedol once last year, i said that the only future of Go right now is finding out if humans still posesss a skill AlphaGo doesnt. And thats why the pair go in this series is actually most interesting to me. Can a pro + alphaGo beat AlphaGo consistently? if so, it means humans still have something of an identity.
> what is the point of being a professional in something a computer will just be better.
Chess was conquered by computers a long long time (in computer time) ago and the popularity of chess has only gone up, not down. There are many professionals making a living out of chess. The art of Go will live on for sure.
From a professional standpoint, thats pretty terrible.
Sure, Catan is also easily solvable, but its played for fun.
When you play as a professional you make a commitment to the board, to advance and explore the frontiers of the universe contained in the game. If the bot explores better than you every single time, you are just dedicating your life to trying to beat a calculator at arithmetics.
It's become a sport, with all that that implies. Training and supporting an olympic sprinter is a multi-million dollar investment. But olympic sprinters haven't been the fastest mode of travel in centuries. If all you want to do is go fast, you buy a really fast car or an aircraft and you go fast. But simply going fast isn't what the sport is about. It's about pushing humans to their limits and seeing what humans can do. It's a race. And chess has become the same. If you just want to win at chess, you ask a computer. But if you want to play a game of chess, or watch a game of chess, it's all about the humans.
I agree with this point, but to me its a degradation of the game. It degrades into a sport.
Go has something amazing about how we study pattenrs that are 100's of years old. Many current and active training materiels have up to 400 years old!
Go is something were each generation looks at the previous one and builds on that, and its been a very old and iterative process. If go becomes an exercise by how little we lose to machines for, its a major degradation of the purpose of continuing that history.
As a pro, you are just working towards the inevitable goal of solving the game, and then we are all free to never play that damn game ever again :)
That is something to mourn, yes. It is in some way disappointing to see such an old culture, one that's been the focus of so much effort, be overtaken and undercut by newcomers that don't have that culture. It's interesting, though; in topics that lives depend on, medicine and industry, we celebrate the advent of new techniques that remove the burden and dependence on the old guard. Like you said, "Free to never play that damn game ever again". But in this case, where the mastery of the game is the end in itself instead of a means to some other end...
I don't know. My perspective is likely decidedly odd, as I've read a great deal of far-future science fiction and done AI research and have already spent a lot of time thinking about what it means to be human when machines will inevitably outperform us all in every way. The key, I think, is that there still are - will always be - things for us to enjoy. We can always find achievement in our own accomplishments, even if they're insignificant next to what someone or something else can do. I don't care that I run slower than a supercar; I take satisfaction in being able to run faster than I could yesterday. Not all is lost. :)
As Kasparov said, people still have foot races even though cars are faster.
Having said that, it's much easier to see someone is on foot than to know someone isn't cheating in a chess tournament every few moves.
As for computers letting new kids on the block overtake old cultures, look at the black cab in London being overtaken by Uber. They have "The Knowldge" and Uber has a GPS.
My gut feeling is that Go is a technique if you put it in the perspective of winner/looser. If you put in it in the perspective of cultural legacy, apprenticeship, etc. then it's more of an art. The technique can be beaten by computers, but the art is what humans do of go, so it can't be beaten.
Moreover, as OP says, there are subjects where machine are absolutely nowhere and those subjects already do matter : world peace, ethics, etc. These are so human... Even if you had a world of machines (à la matrix), these questions would be of the utmost importance to us humans because that's an emanation of what we are.
Honestly, unless the rate of progress of technology changes, the topics you mention will not be machine-less for too long. It's relatively easy to imagine a general artificial intelligence (however far off in the future that may be), that can out-think us on the topics of world peace and ethics. Unless you reject the very possibility of a true general artificial intelligence (or assert some kind of metaphysical superiority of our biological existence), the list of things we're truly best at gets smaller and smaller.
It all depends on what AI machine you make. If I take a few artificially created billion neurons and group them into something very close to the brain, then, well I may have made an artificial AI, but it's so close to a human brain that it's not what we currently think of it. Heck, if I want to do that , I just need to have a few moments with someone of the other sex and I may make that machine.
That machine, could indeed think like us.
But if you think programs, neural networks and big data, I'ma afraid we are very far away of anything close to a machine than can think about ethics. Ethics is not a mathematical problem, it has to do with gut feelings, culture, bodies, etc. And I don't see anybody with the smallest idea on how to teach that to a computer, other than in very toyish way (such as a Tamagochi)
Currently (and prior to now), most of the research in AI went into immediately usable solutions; I myself ended up doing my MSc in what is effectively optimisation (using certain "AI" techniques), rather than what really interested me (which would have been "real AI"). In a sense, this is correct; we want to have real value out of research investment, so that side of AI will be ahead for a time. Basically, why have something that taught itself to play chess, when we can use a human-engineered heuristic that beats it every time?
That said, this line of thinking is coming under attack on several fronts. AlphaGo is a good example - it's tacking problems where we're not good enough at coming up with heuristics. So, essentially, we've hit a tier where machines are really better at that topic than we are. Think about that for a second; a computer is a better programmer than the best of our guys, and it's early days yet. Not just running computations, but actually determining what computations to run.
Problems like Go are complex enough that if you want to have AI be good at it, you actually need to invest in the meta-level goal creation and other things that go along with it. This is happening on many levels, and researchers are actively trying to understand how exactly the human brain handles these topics (or even what consciousness is, on a practical level).
If you follow these developments to their logical conclusion, I'm pretty sure a "real AI" will be on the cards relatively shortly, whatever that time period may be (100 years is nothing on the grand scale). Initially, this will likely have some architectural similarities to human brains, but will essentially be free to do its own thing and restructure. Eventually, it will have gut feelings and culture that are far beyond what our feeble little brains can comprehend.
I like your argument. But somehow, I remain stuck on mine. The nature of AlphaGo is indeed very complex. But to me the question remains : AlphaGo is able to demonstrate skill to play go, and maybe, in the context of the game, than can be called true intelligence. But to know if we are on the path of true (!) AI, we might want to compare AlphaGo and a human intelligence qualitatively. Which we can't. Because we may (I dunno, didn't write it!) not know for sure what AlphaGo actually "guessed" while learning and we know even less about human intelligence...
So I think AI will, as you say, reach more and more goals and we'll go the upper level with more meta stuff. But is this a road that ends on true AI or is there a "conceptual" gap ? I dunno, I think my life would be better if there was such a gap. But that's just because I love humans... Thanks for the conversation :-)
The game was combinatorial search from the start, so you could argue that it did not degrade the game, but it dispelled the illusion that it was deeper and something more than a sport.
Computers will undoubtedly become so good that computer + pro human would be like pro human + amateur, where the amateur has the final say about which move to make. The best strategy is to just do what the computer says.
This has become the case in Chess [1]. However, it took 15 years for that to happen. Chess engines now are orders of magnitude stronger now than they were when Deep Blue beat Kasparov. So this is definitely the case, it'll just take a while.
Go's difficulty comes from predicting a future game state, which is discrete and highly multiplicative. Novice players play on smaller boards. So humans are definitely going to lose to (relatively) simple discrete computation machines.
For professionals, finding usable strategies will still be a challenge, since unassisted humans are still far from solving Go or Chess. Unassisted humans have been pretty much kicked out of the top leagues, though.
It winds up making humans into race horses though, ultimately pointless but done so long as there remains some irrational mystique or cultural admiration for the practice. When there isn't, like bullfighting, the sport dies out.
At least right now, computers explore the frontiers of the universe only if we humans tell them to. They explore the way we program them to. If I want to explore the frontiers of Go, I would not care about winning or losing. I would enjoy the art, the beauty, and the philosophy of Go.
That struck me as well, but thinking about it a bit more, I could see there being a set of correct decisions in trading, which could be taken as assumptions. I'm not sure such a set exists, but after playing a good deal of Catan, I think they might. In a game where everyone knows what they're doing, the trades are very predictable, and it's pretty clear when someone has made a dumb trade. It seems like there are still too many unknowns to consider it "solvable", but it seems less open ended than poker, for instance.
That might be why you would choose to play as a professional. Clearly, those who continue to play chess as a profession do so for other reasons.
That said, humans still contribute heavily. Computers may calculate a position as advantageous to one side or another, but it takes a human to explain why in heuristic terms that others can use to evaluate similar positions.
Well, to nitpick, the reason anyone becomes professional is to make money, kind of by definition.
Go has something of a higher order attached, its not a sport, its a philosophy of life. Its a way to devote yourself to an art. What you do with that contribution is very important.
We could build robots that paint more and better than what we do, but as humans we are very likely to still be able to produce things computers dont. The great question is if that is true with Go as well, or effectively, its a purely tactical game and all our philosophy, ideas and beauty appreciation is basically a projection of a silly life-form over appreciating tic-tac-toe.
> We could build robots that paint more and better than what we do, but as humans we are very likely to still be able to produce things computers dont.
I expect this to be the next big human activity where machines consistently beat humans within ten years.
We already have neural networks that can apply a painting style; creating a new style, and impacting a political or sentimental meaning to a painting, will soon be within grasp.
To quantify it, I offer a Turing-like test that I expect to be beat within ten years: there will be a machine-generated work of art that will be sold higher than human-made ones at an auction in which there are both human and machine works of art, but where nobody in the room knows which is which.
After seeing what passes for "art" at MoMA, I wouldn't be surprised if a painting made by a neural network today were sold higher than a human-made one at an auction.
>We could build robots that paint more and better than what we do.
For some definition of paint. Namely, if you give it an image created by a human; and call the computer a printer. We are nowhere near computers creating art at the quality of humans.
>The great question is if that is true with Go as well, or effectively, its a purely tactical game and all our philosophy, ideas and beauty appreciation is basically a projection of a silly life-form over appreciating tic-tac-toe.
Is this even a question? Go is a combinatorical game. There is a solution; one of the two players has a winning strategy. The only question we are facing is if it is feasible for us to find the winning strategy (a question which AlphaGo does not help us answer). With sufficient computational power, finding the winning strategy is trivial.
"With sufficient computational power, the whole universe is a trivial simulation."
Sometimes, a difference in quantity is a difference in quality :-) P=NP and all that.
It feels like you're talking past each other. Conanbatt says Go will never feel the same to humans, especially humans who see Go as the purpose, the "main course", of their life. Some fundamental psychological quality is lost.
You're saying that people enjoy doing even silly, "pointless" (sic!) things for a living, like playing sports. And that you can actually make great money doing that. Money and economy are human constructs, "for monkeys by monkeys", not a physical law.
> We are nowhere near computers creating art at the quality of humans.
This can change very quickly. Already google's machine learning with images created a sensation like a modern-day surrealist. There is technology that produces novel classical music that has been deemed undistiguishable from a human performance.
> Is this even a question? Go is a combinatorical game. There is a solution
Everything has a solution. There are no dice. With enough information you can choose what to roll everytime. With enough information you can have all the potential conceivable paintings. Perception is a combinatorial game. Physics is a combinatorial game.
Its more of a quest of identity: what can we do that bots cant, and why, and once we understand it we move on to the next thing, until we figure out everything.
> There are no dice. With enough information you can choose what to roll everytime. With enough information you can have all the potential conceivable paintings. Perception is a combinatorial game. Physics is a combinatorial game.
Small nitpick: Modern physics wants to have a word with you.
> We are nowhere near computers creating art at the quality of humans.
The same was said about playing Go. I would be careful with such statements.
The only problem about art is that we don't have a good measure for it. And for all kind of measures you could think of, I bet that it's not that hard to train some computer to beat a human in that measure.
> it takes a human to explain why in heuristic terms that others can use to evaluate similar positions.
That's not strictly true. With enough samples, or fast enough playing bots, you can explore that domain automatically. There are many different approaches from expert systems which are purely human heuristics to minmax which can be defined purely in terms of in-game points difference.
Why the situation is advantageous may be just "because enough Monte Carlo simulations starting with it end up winning".
Machines can be made to do better at just about any sport but we still have athletes because it's about human potential and competing within that regime, not pure unbounded scientific advancement. If that's what you want then there's plenty of opportunity to do so in academia rather than professional sports, and such pursuits coexist just fine.
>And thats why the pair go in this series is actually most interesting to me.
Is the pair game really going to test this though? Both sides are human + AlphaGo. Also, I have not read specifically what they are planning for this match, but when I hear "pair go", I think of teammates alternating moves without coordinating. If AlphaGo makes a "weird" move, the human teammate would have a chance to mess up in the follow up.
> In this game, black playing 3-3 (bottom right corner invasion) would have never been played before AlphaGo in the state of human theory. I was taught 15 years ago in my first beginner class how bad doing that is.
There are lots of 3-3 invasion joseki, though. Sometimes the context makes the invasion bad (e.g. when you end up giving a lot thickness to the opponent), but I don't see it here. What is it about the neighbouring corners that make the invasion bad?
The 3-3 joseki is not considered even. It is supposed to be played in circumstances where thickness is inefficient, or an invasion/normal approach is attractive.
Conventional theory is to play the approach move from the right hand, extending the top right formation.
Note; something Michael Redmond mentioned in the commentary which is false is that joseki is even. Its not correct: josekis are not even, but are the best recognized patterns given a specific purpose.
In a way, straying from joseki means that you failed to apply the best possible sequence for the pattern you wanted to play. There is some subtlety around this topic.
Whether a joseki is even or not depends on the context. However, when a joseki is played, it is considered to produce an even result by both players in that specific situation; otherwise, trivially, they would not play that way. The latter was precisely Redmond's point.
> Whether a joseki is even or not depends on the context
The whole point of joseki is its locality. Josekis do not depend on context to be joseki: it could be a bad joseki choice, but what they are, they are locally.
When you deviate from joseki you are; a) creating a new joseki b) recognizing that joseki is not applicable in the context, and its better to take a local loss to get a global gain.
Josekis are filled with non-even results, but that given
a tactical goal, they are the best choice possible.
I haven't studied AlphaGo games against Lee Sedol. I wonder if Ke Jie played that way because he saw AlphaGo playing a good counter to the more usual moves (an approach on the right side).
3-3 invasion means you're giving thickness to 2 sides. After studying the 60 master games I concluded that 3-3 invasion only makes sense if you can make the thickness on BOTH sides inefficient (AG only played it when it has stones on both sides)
> Can a pro + alphaGo beat AlphaGo consistently? if so, it means humans still have something of an identity.
Seems like a hard bet. The human professionals weren't trained to pair with machines to beat other machines. I don't think a human-only skill can even exist due to the nature of the game. Ultimately, each state of the board has a value and this value is estimable using reinforcement learning. Games where a state doesn't have a quantifiable value is where humans could shine. Such games however are not objectively decidable, such as fine arts like painting.
>Seems like a hard bet. The human professionals weren't trained to pair with machines to beat other machines. I don't think a human-only skill can even exist due to the nature of the game
The point is to find that out !
Also, Go has an intricate relationship between strength and beauty. Strong go tends to be beautiful. Does our capacity to perceive beauty give us a leg up on AlphaGo?
Do you not think that you see strong Go moves as beautiful because they're strong, rather than the other way around? Take AlphaGo's unexpected move in the first tournament - no-one thought it was beautiful, just weird, until it played out.
TBH, it's interesting reading your posts. You talk much more like a poet than a mathematician. This is surprising to me when talking advanced play in a strategic game.
That was true until a few years ago. Now humans cannot add value to computer chess programs and only slow them down. Implications for future economy and job markets are worth pondering.
What is going through Lee Sedol's mind, watching this? Does he wish he was the guy getting the later crack at the more advanced version we see today, or has he come to terms with his single victory against AlphaGo a year ago?
If these questions seem nonsensical it all, please feel free to reformulate them to something that has a more interesting answer.
I dont think he wants to play alphago again. Go is a game that relies a lot on confidence: professional players almost never play amateur players casually, for example. Thats because if they lose to an amateur player, it will affect their mindset, their confidence, and they could then perform worse in the real professional tournament.
An argentinian amateur beat 2 strong professionals back then in 2001 in a major professional tournament: it was a huge sensation. Those two professionals basically disappeared from high ranking tournaments forever. It was said that the setback was so severe it affected them permanently(purely hearsay).
Its not good for a professional to play a game he thinks he will lose.
>Its not good for a professional to play a game he thinks he will lose.
That's interesting, any ideas where this attitude comes from? I feel like that's the opposite of a lot of other sports and games, where the ability to take a bad loss and come back improved is seen as an important skill.
I have no idea how to play Go but reading his responses are quite and interesting and insightful into the realm. Go does seem very different from other kinds of sport. I guess this stems from the fact that it can't be brute forced so it's very much a game that goes by feel, intuition and experience?
Go is also seen as a martial art and much of its underpinnings are spiritual in nature. It's a much different beast than chess from a cultural standpoint, hence the somewhat strange replies.
I feel like defeat in Go is much more intense, even at an amateur level. In Sport you get all these hormones throughout the game that you kind of feel good even if you lose. In Go if you lose it's a direct attack to your intelligence. Losing a Go game is really stressful (imo). But then I get really stressed when I play starcraft too.
To play go well you need balance. It requires intense emotional training. Any feeling you have during a game must be reigned in immediately because it will cloud your judgemnet and it does so in a way you cant understand.
Think of Go as a conversation. Lets stay you are having a civil conversation about a topic with someone, and the other person throws an insult in the middle. Will your next messages look the same as the ones before? Of course not, because you will be rattled, or offended, or something, and thus the tone and content of your messages will change immediately.
If that happens to you in Go, you are on a path of self destruction.
So losing a game to an amateur could be something in your mind, as an insult, that just modifies you a bit, even just temporary. But it does, so you feel contaminated.
As a relatively new player I do find losses extremely upsetting very often, unless I've only lost by a few points against someone at the same level as me; I guess I have some learning to do :)
Not really, I've seen amateur 1-2 Dan insulting the other player before leaving a game (online), or just trolling to piss off the other player. People get really childish in Go because it's hard to accept defeat in this game.
Sounds like this behaviour would limit new ideas. Doesn't that produce a culture where the top pros try to execute the old ideas against a known opponent better, rather than be great overall?
There is something related to effort as well. When i was studying in korea at a point, there was a small 9x9 board tournament in the school.
After playing move 2, i realized that i had become strong enugh to read the game until the outcome was decided. Its not like i was 9x9 perfect player, but i had enough reading power to count the score with an empty board.
It would take me 20-30 minutes to finish the game. I won that small tournament knowing exactly the score of each game and when i was losing and turned around games. After that, i never played 9x9 again. I dont like it, becuase i know i can lplay very well, but its a tremendous effort that i dont want to do.
A professional has to save face against an amateur, because losing would affect his reputation, his mindset etc. So a pro would be more reluctant to play a strong player than a weak player, where he might be able to use less effort.
A short way of putting it: professionals dont play for fun, so why would they play for free for anyone?
> A short way of putting it: professionals dont play for fun, so why would they play for free for anyone?
But fun is probably what got you guys into this game, right?
I got what you meant but for a lot of people it will probably read like it's not a pleasurable activity for you guys anymore.
A counter-example would be a pro Soccer playing saying he never plays casual matches with his friends anymore because he earns to do it. That does not happen and I believe it's the same with you guys in Go, right?
Thank you for answering all the questions and doubts, I've been reading everything and it's been a blast :)
> A counter-example would be a pro Soccer playing saying he never plays casual matches with his friends anymore because he earns to do it. That does not happen and I believe it's the same with you guys in Go, right?
OTOH, I know collegiate soccer players that can't handle "stepping down" to local rec leagues. They learn an aggressiveness appropriate to the one domain, and can't turn it off in the other. I consider that a maturity issue, but it is an issue for people accustomed to one level of performance and competition trying to step into another.
Do you know what Pro Go players play for fun? Catan :)
Once you step into the professional aspect, you do not enjoy the game anymore. Its a passion thing. If you wanted to spend more time on the board at any point, it would be studying, not goofing around playing.
> But fun is probably what got you guys into this game, right?
Hardly. Almsot all professional players were exposed to the game at 4 years old, more like indoctrination. And as a grown up, if you start late (like I did, at 16), when you dream of professionality, the joy goes away, its more like a passionate driven goal of self sacrifice.
>I dont think he wants to play alphago again. Go is a game that relies a lot on confidence: professional players almost never play amateur players casually, for example. Thats because if they lose to an amateur player, it will affect their mindset, their confidence, and they could then perform worse in the real professional tournament.
Theres a famous anecdote by Kitani Minoru, a famous Go player from the early 1900's that made a go school where every major 70's japanese player came from.
He would scout talent in the country and once found a couple of brothers that played go. He played a game with the eldest, and he beat the eldest. He accepted his defeat quickly and offered Kitani to play again, that he wanted revenge.
Kitani politely refused and played his younger brother. Kitan wins again, but the youngest bursts into crying. He was deeply upset at the loss and could not play another game even if he wanted to.
Who do you think Kitani recommended to follow the path of a professional Go Player?
There is a famous player called Takemiya Masaki. His style of game is called Cosmic Go, and his games were some of the most beautiful games in history. He had an amazing ability of making this natural flows and building massive central territory: something against conventional theory.
His style died eventually because no-one could play like he did. Some professionals even mentioned that such a style could not be played unless Takemiya Masaki had amazing reading skills.
Alpha Go has amazing reading skills. So he can actually easily afford to play such a style. Its like the revamping of a theory we all know its playable but as humans have a hard time having a winning rate with.
On the other hand, alphago is definitely playing moves that are plain bad for conventional theory, but manages to get good positions regardless. Its possible that alphago is just more thorough, and human pattern matching naturally discard moves that most of the time are bad.
I only know a little about Go but you mentioned something here that I have discussed with a Go friend, reading skills. Is this the main reason AlphaGo is winning? It never gets tired and never misses a board position. It seems like computers finally have enough speed and memory to never miss a board position and humans (as a group) will never be able to match it, and only get further behind. Thoughts?
I don't understand your statement that AlphaGo doesn't have strategic considerations. Its neural networks evaluate positions for strength, including long-term (strategic) potential.
ITs another philosophical debate about what is strategy and what is tactics.
Tactics is a specific sequence of attack, with very well defined steps and a defined outcome. A strategy is a general guideline to guide overall decisions, with a general goal but without a specific objective.
AlphaGo cant say "I will play a territorial game from now on because the strength of my positions is enough to reduce the opponents influence". Alpha can say "Territory 56%, Influence 54%". Alpha Go makes tactical decisions.
I don't believe AlphaGo's MCTS, policy NN, or value NN support your last paragraph. Could you please explain what it is about Somehow construction that supports strategic categories with associated probabilities or why only tactical decisions are being made? I'm a bit confused by your last statement actually. Are you saying AlphaGo decides how much to emphasize certain strategic goals or that it doesn't (only makes tactical decisions)?
I could read more about Alphago's functioning to be sure, but alphago cant make a reasoned balance between two options based on strategical considerations, it can only decide between different winning probabilitlies. Thats not strategy, thats tactics. You are making decisions by objectives, not by goals.
For example, lets say you play soccer and have to do a series of penality shots. If you decided that you will kick the ball always at the same corner because you think that you will get better at aiming at the corner in successive hits than the goalie will, you are making a strategic decision "I will take advantage of learning how to repeat a shot better than a goalie can defend it".
If you make the decision because you know that shooting the ball always at the same corner has been prooven to have the highest probablity of scoring, you are making a tactical decision.
Strategy is what you use when the outcomes are very uncertain, and its one place where humans excel. Tactics is where computers excel, and humans faulter.
I'd be interested to see if something like what happened in computer backgammon occurs with AlphaGo in which long standing assumptions about how to play prove to be wrong.
TD-gammon, a computer backgammon player, explored "strategies that humans previously hadn't considered" [1] and led the backgammon playing community to re-evaluate some rules of thumb they used in opening moves [2].
If a slightly larger board were used, could human or computer adapt better given what they currently know? What about if the shape of the board were altered? Does alphago understand the underlying principles well enough to adapt them to unknown situation? I think that is the most interesting question left.
> Do you think that they will propose match with handicap?
They should, but i mentioned they probably wont because it could affect them psychologically. Nobody wants to be the first one to go down in history as a loser with handicap.
They would do it online, if it was an anonymous account, maybe. But it would still do them harm.
> Do you know if it will change the value of the komi?
Ke Jie already played an adaptative tactic the bot, that is playing in a very solid and stylish game. It almost feels like a teaching game so far.
As a former student of Lee Sedol and once aspiring professional Go player, i'd answer a few questions if you have any!