Part 5: Google's biggest press conference ever: AI versus Mankind (The historic match of deep learning AlphaGo vs. Lee Sedol)

Google's biggest press conference ever: opening of the match AI vs. Mankind

[NL Versie]

On Tuesday March 8th, 10 AM Korean time, hundreds and hundreds of curious and mouth watering photographers, reporters, journalists, media specialists, commentators, broadcast stations, newspapers, press, Go-fans and AI scientists worldwide, have gathered for the biggest press conference ever held by Google: the official opening of the most spectacular, remarkable, and pioneering match in the history of the most ancient of games of the world. 

Compared to the minutes-long, continuous flashing of the hundreds of cameras focused on Lee Sedol and Demis Hassabis during the opening of the match, the flashlights on the red carpet at the première of a new James Bond movie is wholly negligible.

The throughout the past half year with anabolic steroids super-trained AlphaGo will combat against the legendary Lee Sedol, world's strongest Go-prof. Apparently, Lee Sedol has prepared himself extensively for this match and accommodated himself by a special team be able to handle the enormous psychological pressure and worldwide media attention during this match.

With Lee Sedol's all-or-nothing-at-all character and his immensely strong wanting to show AlphaGo all corners of the Go-board in a sensational manner, he is willing to go to any extreme to eclipse, surpass, and try to annihilate the program completely. To show once and for all for the eyes of the whole world that the program --for what concerns playing Go-- does know nothing. And should have subscribed already many years ago for the Go-lessons at Lee Sedol's own Go-dojo in Seoul. 

Lee Sedol will have to pull out all the stops to identify and exploit AlphaGo's weaknesses. But how difficult must it be to play against an opponent about which you know almost nothing, of which you virtually don't know how it plays, who you, both physically and mentally, cannot sense or notice, and aren't able to assess it's strength and way of playing. 

To whom you just can't say or signal something in between, and who shows no respect or appreciation at all for the most fantastic, profound, and admirable moves that you play in order to win the game and have victory. How strikingly different this must be as compared to when you play against a human opponent, who you can make clear, with just a rapid eye blink already, during the final of an international tournament that you've blind faith to attain the title.

Ahead of the match Lee Sedol explained to the BBC: "Playing against a machine is very different from an actual human opponent. Normally, you can sense your opponent's breathing, their energy. And lots of times you make decisions which are dependent on the physical reactions of the person you're playing against. With a machine, you can't do that".

While Lee Sedol continuously has to guess and ask himself how and where AlphaGo will play, what the program's strong power is, which strategies it will apply, for AlphaGo it is as easy as pie (and a piece of cake) to judge a position calmly by invariably assuming the best possible opponent's move. That is something we humans are not always capable of, or prefer from time to time to take some risk by underestimating the opponent unnecessarily (unconscious or conscious) or whose reputation is not very high a priori (for whatever colored reasons).

And you ask yourself: "how will it be for Lee Sedol to do everything he can (and more) with each move in a four to five hour game under absolute, high-voltage pressure while he realizes that another nerve-wrecking and back-breaking --over hundred million people watching-- game will be waiting for him in less than 20 hours"? Under enormous mental pressure with all eyes of the world focused (and counting) on you. 

While AlphaGo has a continuously playing (and thinking) backup running in the background on Google's data centers in the west of the US, Lee Sedol needs to analyse, process and digest all experiences, patterns, moves, and positions of the previous game in his sleep (without a backup clone who can take over insensibly in case things may become momentarily too heavy and difficult).

Hassabis explained to the press: "the DeepMind team will enter this match, in which everything is possible, open minded and unprejudiced". Lee Sedol will begin the match, however, on the basis of the Fan Hui games and above all have the strong feeling that he surely would have exploited AlphaGo's weaknesses (and simply never would have played some of Fan Hui's overplays). 

One thing is for sure: the match between AlphaGo and Lee Sedol will be an extremely important chapter in the history of artificial intelligence. Experts and official distinguished ones in AI all agree that if AlphaGo wins this match, that will open a new door and will be a completely new chapter in the future development of AI. 

For many, that will be a very bitter pill to swallow and hard to digest turning point: that our superior intuition when judging a Go-position and our immense creativity to come up with the most effective move, allowing all stones on the Go-board to work together and cooperate as good and efficient as possible, will be completely overpowered and superseded by a computer program. 

[Part 4: AI versus Human: Expectations and Predictions]

[Deep Learning AlphaGo vs. Lee Sedol Match Overview]

AlphaGo wins fifth game after not knowing a known tesuji

[NL Versie]

In the fifth and exciting last game of the Google DeepMind challenging match, deep learning AlphaGo played an impressive and very balanced moyo-building game. Even though Lee Sedol had substantial (secure) territory already early in the game and although he was able to thwart AlphaGo's huge moyo plans, the program succeeded in getting enough compensation to stay ahead by a small margin of just a few points. 

Both Lee Sedol and AlphaGo played a very solid opening and after move 40 (circle, white is AlphaGo) the outcome of the game appears completely open from their opposing forces of moyo and territory.

Then AlphaGo miscomputes the effectiveness of a tesuji and looses some points in the bottom right corner. Fortunately, it played those moves in territory already realized by black and it got some sente moves at the outside which would be quite handy if AlphaGo would want to turn it's moyo potential into real territory later in the game.

After Lee Sedol's move (triangle) to keep AlphaGo under pressure in the upper left while at the same time reducing AlphaGo's moyo potential around the center, AlphaGo came up with a great response (move 70, circle) turning around the flow of the game by putting high pressure on black.

Lee Sedol needs to create a living group but in return, AlphaGo adds up strength to gradually help it's moyo building strategy. In a complicated middle game, Lee Sedol is forced to find efficient manners to prevent AlphaGo from realizing it's entire moyo by playing smart reduction moves. He succeeds but it comes at a price after AlphaGo plays a beautiful counter attack move (circle, move 136), putting again ultra-high pressure on Lee Sedol.  

In the final phase of the game, Lee Sedol wonderfully manages to reduce most of the entire moyo built up by AlphaGo (triangle, after move 183). But, despite Lee Sedol's great moyo reduction skills, it is still deep learning AlphaGo that is ahead due to the sufficient compensation it got along the way. 

For the top Go professionals commenting on this fifth game, it is difficult to say where Lee Sedol perhaps made a mistake. But one way or another AlphaGo managed to catch up again after falling behind when misreading a tesuji earlier in the game. Overall, the flow of the game and the way of playing, both of Lee Sedol and AlphaGo, seemed to be very balanced.

In the remaining 100 moves in the endgame, Lee Sedol was unable to overcome his arrears of just a few points. Even though he was ahead on the board, he would lose by about 2.5 points when including white's komi (7.5 points). This was the first time in the match a game developed so close in counting. 

Lee Sedol resigned after move 280 (circle) while less than a handful of small endgame moves were left. This was another stunning and incredible exciting historic game where the distinctions in playing strength between the world's top Go-professional Lee Sedol and deep learning program AlphaGo during the match were most of the time very hard to discover. 

So the final outcome of the match is: AlphaGo defeats Lee Sedol by 4 - 1. A result that only a small minority ( < 10-15%)  of the more than 100 million people worldwide who watched this match online, would have predicted in advance. AlphaGo has impressed all Go players worldwide with rock-solid, deep reading, sometimes unexpected and really wonderful, effective moves in these games.

During the post-match press conference Lee Sedol said: "I am sorry because the match comes to an end". Answering a question about whether the five games might have changed his understanding of the game of Go, Lee Sedol responded: "Basically, I don't necessarily think that AlphaGo is superior to me. I believe there is still more that a human being can do to fight against the AI program. That's why I felt a little bit regrettable because there is more that a human could have shown during this match."

Lee Sedol concluded: "Enjoyment is the essence of Go. I do wonder whether I've always been enjoying the game but I do want to admit that yes, I did enjoy the games against AlphaGo. Creativity of human beings and also all the traditional and classical beliefs that we have had, well I've come to question them a little bit based on my experience with AlphaGo. So I've more studying to do down the road". 

Commentator Chris Garlock remarked: "this match has triggered unprecedented global attention to the game of Go. We could not have asked for a more wonderful or generous gift to this game. The five historic and beautiful games of this once-in-a-lifetime challenging match will be studied over and over again in the years to come, launching what I'm sure is going to be a new era in the most ancient of games. I'm really looking forward to that".