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Recent Top Pro Go Games Fully Explained

With Discussion of the Impact of AI Programs

Yuan Zhou

Buy the full book in the Go Books app

In his very thorough analyses of these three games by the world’s strongest human players, Yuan Zhou gives special attention to the impact of the AI programs on their play.

About the Author

Yuan Zhou (American Go Association 7 dan) was born in Tianjin, China. Tianjin is a major city in the northern part of China, near Beijing. His father taught him to play go at the age of six, and a year later he won the Tanggu District Junior Go Championship. After this auspicious beginning, Zhou began professional go training while he was still seven years old. He was twice invited to represent Tianjin in the All China Prodigy Cup.

In 1989 Zhou immigrated to the USA, becoming a US citizen and joining the American Go Association (AGA). Zhou was the president of the University of Maryland Go Club, from which he earned a BS in Electrical Engineering, and became increasingly involved in AGA events, winning many go tournaments. Zhou was also elected to the AGA board of directors in 2005.

Zhou is one of the top competitors on the American go scene, winning the Eastern US Open, one of the biggest US tournaments in 1992. He also won the New Jersey Open, one of the biggest US tournaments, four times. Twice he has won the Maryland Open, another major tournament that attracts strong players. Zhou has placed in the top ten in the US Open many times, as well as in the North American Ing Masters Cup and the North American Fujitsu Qualifying Tournament. These tournaments involve the strongest North American go players and include pros. In Zhou’s go career, he has defeated pros many times, including four times in even tournament games: Hak Soo Kim 6p in the 1996 Fujitsu, Xuefen Lin 1p in the 2001 Eastern Oza, Huiren Yang 1p in the 2009 North American Ing Masters, and Feng Yun 9p in the 2011 SAMG World Team Go US Team Qualifier. Zhou also won the US Pair Go Championship four times. Zhou represented the USA in international tournaments many times (WAGC, Korea Prime Minister Cup, World Pair Go Championship, etc).

In 2009, Zhou represented USA in the 4th Korea Prime Minister Cup World Go Championship in Jeonju, Korea and finished 5th place.

In addition to his competitive successes, Zhou has become a popular teacher and lecturer, frequently giving lectures and teaching lessons at various go clubs in the Eastern US region. He has also published many go books with Slate & Shell (www.slateandshell.com) and SmartGo Books (gobooks.com). Zhou resides in Germantown, Maryland, USA. His website is at www.zhouyuan.com.

Copyright Page

(c) 2019 Yuan Zhou

All rights reserved. Reproduction in whole or in part is prohibited.

Slate & Shell

www.slateandshell.com

Edited by William Cobb

Conversion to SmartGo Books by William Cobb

Table of Contents

Recent Top Pro Go Games Fully Explained
With Discussion of the Impact of the AI Programs

About the Author

Copyright Page

Introduction

Game One: Xie Ke 8p vs. Ichiriki Ryo 8p

The chapters in gray are included only in the full book.

Game Two: Ke Jie 9p vs. Shin Jinseo 9

Game Three: Tuo Jiaxi 9p vs. Mi Yuting 9p

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Introduction

These very thorough game commentaries are somewhat similar to those published in my Deep Thought books. However, I give a lot of attention to the impact of the AI programs in these new commentaries. These programs did not exist before those earlier books were published. The top pros generally study the games of the AI programs extensively.
It is important to realize that the AI programs are still exploring the game. After millions of games they are still making changes in how they play. Some of the recent changes in how the AI programs play come up in the games in this book.

One of the striking things about the AI programs that has not changed yet is that they all see White as having an initial advantage in the game with the seven and a half point komi. The AI programs have not yet discovered how Black can gain the advantage in the opening. This advantage is not huge: something like a two or three percent better chance of winning. Nevertheless, the message seems to be that Black cannot expect to gain an advantage in the first fifty or so moves unless White makes a mistake. This means that Black has to focus on finding a way to get ahead in the middle or end game. Even after playing millions of games, there are still possibilities in the middle and end game that the AI programs have not had a chance to thoroughly explore.

This means that Black must play more aggressively while White can play calmly and solidly.

Since AlphaGo retired, many AI programs have been developed. The Chinese AI program Fine Arts is the strongest at this point and functions as the coach of the Chinese national pro team. It is still able to push the top players to a handicap of two stones without komi.

Yuan Zhou, Summer 2020

Game One
Xie Ke 8p vs. Ichiriki Ryo 8p

This game between the Chinese pro Xie Ke 8p and the Japanese pro Ichiriki Ryo 8p was played in the quarter finals of the 4th international MLily Cup on April 27, 2020. Because of the corona virus pandemic, the game was played on the internet. At this point in the tournament, Ichiriki was the only non-Chinese pro still playing. If he loses, the event becomes in effect a national Chinese tournament. Ichiriki is currently the next generation’s leader in Japan, after Iyama Yuta 9p. Xie Ke is the next generation’s leader in China, after Ke Jie 9p. So there was a lot of interest in this game.

Xie Ke is White and Ichiriki Ryo is Black. The game is played under Chinese rules since it is sponsored by a Chinese company and played in China. The komi is seven and a half points.

Moves 1–4

＞＜ ▶︎

Starting on a 3–4 point is still considered playable by the AI programs, but the AI programs like at least one of the first two stones to be on a 4–4 point. So we do not see Black’s opposing 3–4 points opening very often these days.

White’s opening is also a little unusual now. The most popular opening for White these days is two 4–4 points.

Move 5

＞＜ ▶︎

Black decides to approach White’s 3–4 point corner rather than defend one of his own. The 3–4 point corner has higher priority than the 4–4 point corner in the lower right. This close approach with White 5 is the choice of the AI programs rather than a line farther away: This is more severe and Black needs to balance out komi. In the past Black was more concerned about White’s options for a pincer, which would be complicated. Playing a pincer in this situation as White has fallen out of favor nowadays since the AI programs do not play it.

Moves 6–8

＞＜ ▶︎

The AI programs do not pincer as White in this situation. They either make
the game move at White 6 or play at A.

White 8 is a simple way to defend the corner.

Move 9

＞＜ ▶︎

After Black 9, Black is pretty comfortable. In the past, White’s play in the lower left was seen as a little slow: the corner is not very big. Since Black 9 is high, the bottom right is an attractive area for both players. The game play increases the value of this area.

Move 10

＞＜ ▶︎

Of course, the corners are still more important at this point so White breaks Black’s upper right corner with 10. Note that the upper right corner is better than the upper left because of the low white stones on the lower left side. As I mentioned, due to the AI revolution, Black will not pincer.

Move 11

＞＜ ▶︎

Black could play as White did in the lower left, but White might approach the upper left corner after Black’s initial response instead of extending as Black did. So Black decides that defending that corner is a better option at this point. Black 11 creates a large corner enclosure: another tactic learned from the AI programs.

Move 12

＞＜ ▶︎

The AI programs consistently play this White 12 in this situation. They do not extend back along the top or pincer on the right side.

Moves 13–15

＞＜ ▶︎

Of course, Black must respond to White 12 or lose the corner.

In the past, there was a question of whether White’s response here is good. The AI programs seem to suggest just playing this way and not worrying about other possibilities.

Move 16

＞＜ ▶︎

The AI programs also approve of White 16, protecting this corner. The corners have high priority. In this case, a black approach to this corner from the left would obviously be big. White does not play at A, which would be big, since Black would then have the chance to invade at White 16.

Move 17

＞＜ ▶︎

Black takes sente to attack White with 17. This is a soft attack, of course. Black will be very happy if White just tries to live here so that Black can develop a huge position in the upper left. Black is asking White to invade in the upper left and start a fight. White’s response here is another move frequently used by the AI programs.

Move 18

＞＜ ▶︎

A contact move like White 18 can be very annoying to the opponent. If White simply comes in around A, Black will run out the stone and White will have two weak groups at the top. Since the corner is stronger than , White contacts there, aiming to come back and attack .

White 18 continued

＞＜ ▶︎

In this sort of situation, Black normally can consider two inside moves (A, B) or two outside moves (C, D): inside for defense and outside to fight. Here, A would be a very solid way to play, but White would jump one space to the right from 18 which would be a gain for White. If Black B, White will play C; then Black plays D and White pushes out from 18 to the center and ladders the black stone at D (or cuts at A). In this case the ladder would favor White so even if Black gets the corner, this would be better for White.

＞＜ ▶︎

If Black plays this way (Black 1 is C in the previous diagram), White will continue this way and have good moves at A and B: either getting the corner or developing a big area on the left side.

Move 19

＞＜ ▶︎

So Black avoids A, B, and C in the previous diagrams, and plays 19 (D), which is the best way for Black to fight back in this situation. White is not going to extend to A and allow Black B, which would be terrible for White.

Moves 20–22

＞＜ ▶︎

So White hanes with 20 and extends after Black cuts. Black still has serious weaknesses at A and B.

In the full book, this game is analyzed to the end.

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© 2020 Yuan Zhou

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