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How AI study helped improve my go Wednesday March 25, 2020 by Benjamin Teuber 6d (Germany) For many years, I was considered the “eternal second” of the German championship. I finished as runner-up nine times – while never winning the title. No matter how well I did, I always managed to lose the decisive game. Until November of last year, when, to my own and everyone else’s big surprise, I finally became German Champion with a perfect 7-0 record. After the tournament, I got a lot of comments like “you clearly improved” or “you must have studied a lot” from people. But, to be honest, I didn’t prepare much for this tournament. I did no go problems at all, I didn’t play many tournaments, I didn’t take any pro lessons. Please don’t get me wrong, I highly recommend these measures and have used them a lot in the past; that’s how I became 6 Dan, after all. They just can’t be responsible for my recent improvement. What I have been doing though, was creating my own go study website, ai-sensei.com. It allows you to upload your games and quickly get them analyzed by very strong AI. I believe the key feature of this tool is the focus on big mistakes; that way you can work on your biggest weaknesses instead of getting lost in minor details. So while I didn’t spend as much time studying as I had previously, I did use AI Sensei to review every one of my games and find my biggest mistakes. I would also check an old game every now and then to review my past mistakes. Looking back, I believe this was a very efficient way to spend the limited time I had to study, and it might well be the biggest factor of my recent improvements. So here’s my advice to anyone using go AI to study: Focus on your biggest mistakes in each game Don’t waste time exploring all the variations Think about the AI recommendations in terms of shape, direction, and strength of groups Revisit your past mistakes I invite you to try out AI Sensei yourself; it can be used for free. But whatever tool or AI you are using, I think you’ll find these recommendations useful. |
发表于 2020-12-6 15:01
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发表于 2020-12-13 20:26
