leelazero作者gcp采访

lu01

https://www.eurogofed.org/?id=205

lu01

EGN: What are the goals for Leela Zero?

GCP: They've been shifting as the community has continued to provide computing resources (and enthusiasm!). Originally I just wanted to demonstrate that Alpha Zero could be replicated by a distributed effort and see if their results were reproducible. After that, I was really happy when it surpassed the regular Leela (and a bit later, all other public programs), which made me feel good as there was now really something to show for all the people who had contributed their computer time. Then beating a professional, and eventually surpassing humans altogether. I'm sure we've reached that point now. Strength-wise the only reason to continue much further now is to create some margin and get the same level on mobile phones.

By making everything free, it also provides a lower baseline for the public availability of good software and data. I can't say exactly how Leela Zero influenced things, but at least the TensorFlow team at Google, Facebook's PyTorch team and Tencent (to some extent) have now open sourced their Go efforts. Ironically only the original DeepMind team did not do so. Facebook's effort followed Leela Zero rather closely and their results gave us some good insight of where we'd end up. We were able to make some changes to improve performance when playing against a handicap based on seeing the weaknesses of their result.

EGN: Have you been able to make money from Leela Zero?

GCP: No. But I think it has made a lot of Go players happy.

EGN: Post AlphaGo, do you think that the work involved in Computer Go will retain its interest to developers? Or will it become a stale area?

GCP: It's hard to say. Computer chess had some decent years after Deep Blue. It's not because an IBM mainframe can beat the World Champion that this helps the players at home. It took some time before PC software was clearly stronger than humans. With Go things went fast though. Leela Zero already beats strong professionals on a home desktop. There are a few things to address such as playing better with handicap, different komi and maybe even Japanese rules. As long as there is a market, you will find developers. But for researchers, it's probably more fun to push the boundary at something that computers are still bad at, than pushing it even further past human limits.
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EGN：Leela Zero的目标是什么？

GCP：随着社区持续提供计算资源（以及热情！），目标一直在转变。最初我只是想证明Alpha Zero可以通过分布式的努力进行复制，并看看它们的结果是否可重现。在那之后，当它超过了正常的Leela（以及其他所有公共程序）之后，我感到非常高兴，这让我感觉很好，因为现在真的有什么东西可以显示给所有贡献他们电脑时间的人。然后打败专业人士，最终完全超越人类。我相信我们现在已经达到了这一点。在实力方面，现在进一步延续的唯一理由是创造一些边界并在手机上获得相同的水平。

通过使所有的东西都免费，它也为公共可用性良好的软件和数据提供了更低的基准。我不能确切地说Leela Zero如何影响事情，但至少谷歌的TensorFlow团队，Facebook的PyTorch团队和腾讯（在某种程度上）现在已经开源了他们的Go工作。具有讽刺意味的是，只有最初的DeepMind团队没有这样做。 Facebook的努力紧跟着Leela Zero，他们的结果让我们对最终结果有了很好的认识。我们能够做出一些改变，以便在看到其结果的弱点时对付让子棋时提高表现。

EGN：你能从Leela Zero赚钱吗？

GCP：不，但我认为这让很多围棋选手感到高兴。

EGN：AlphaGo后，你认为Computer Go的工作会保持对开发者的兴趣吗？或者它会成为一个陈旧的领域？

GCP：很难说。电脑国际象棋在'深蓝'之后有一些不错的年份。这不是因为IBM大型机可以击败世界冠军，这有助于家用选手。 PC软件明显比人类强大了一段时间。随着去东西走得很快。 Leela Zero已经在家用台式机上击败了强大的专业人士。有几件事情需要解决，比如在让子，不同的贴目甚至日本规则上打得更好。只要有市场，你就会找到开发者。但对于研究人员来说，将计算机仍然不擅长的东西推向极限可能更有趣，甚至比推动人类极限更为有趣。

棋争一路

没有AI的棋不是当代的棋！

围棋棋友的福气。

lu01

EGN: Do you actually play go yourself? I guess that the audience is bound to want to know your rank!

GCP: I last played Go almost 20 years ago. I played for some months in a club while I was a student but got distracted by other interests. I never had a real rank but my strength must have been about 15-20 kyu or so. Obviously, this is no hindrance for making a strong computer program. When developing visions systems for self-driving cars, nobody is asking for engineers with 20/20 vision either.

EGN: Are you interested in other strategy games, or do your hobbies lie elsewhere?

GCP: I started playing chess competitively again end of last year after one of my daughters asked me to teach her the game and I realized that they are old enough that I can afford to have such hobbies again :-)

EGN: For the non-experts out there, can you explain what the essential difference between Leela and LeelaZero is?

GCP: Leela has been trained on games from strong human players, and has quite some (human) knowledge and heuristics about the game programmed into it. She uses a combination of neural networks and Monte Carlo playouts. Leela Zero only knows the basic rules, nothing more, and only uses a neural network with no Monte Carlo simulations.

EGN: Were you surprised by the interest of LeelaZero generated?

GCP: Yes, very much. Based on the amount of contribution Stockfish's distributed testing effort gets, and the comparatively much larger amount of chess players in the west, I estimated we would get perhaps 10 or so computer go enthusiasts to run the client. In fact it's been generally over 500! Similarly there have been some very high quality code contributions as well.

EGN: Already a lot of projects are starting to make use of LeelaZero. I have seen Lizzie, SabakiLeela, and Iceelz. Do you have an idea yourself for a future teaching tool linked to Leela?

GCP: I will leave this to others as it's not so much fun for me. There is a basic GUI for the regular Leela out of necessity - many people that are less confident around computers would have big problems to download and install a separate engine and GUI, and I wanted to help them. At some point it will be upgraded to Leela Zero. I would be happy to just have a good game analysis GUI that handles variations well, with some kind of fuseki/joseki database and with a strong engine backing it, as chess players have had and used as their workhorse for decades. I hope that having open sourced Leela Zero accomplishes this. I also made the resulting networks and data public domain. If someone makes something really nice based on it and wants to charge money for their work, they can do so.

EGN：你真的下围棋了吗？我想，观众一定想知道你的等级！

GCP：我近20年前玩过围棋。在我还是个学生的时候，我在一家俱乐部玩了几个月，但被其他兴趣分散了。我从来没有真正的排名，但我的棋力一定是大约15-20级左右。显然，这对于制作强大的计算机程序来说并不是什么障碍。在开发用于自驾车的视景系统时，没有人要求20/20视野的工程师。

EGN：你对其他战略游戏感兴趣吗？或者你的业余爱好在别处？

GCP：去年年底，我的一个女儿让我教她玩国际象棋游戏，并且我意识到他们已经足够大了，以至于我可以再次拥有这样的爱好，所以我在去年年底再次开始下棋.-)

EGN：对于非专业人士，你能解释一下Leela和LeelaZero的本质区别吗？

GCP：Leela接受过来自强大棋手的游戏的培训，并且具有相当一些（人类）关于编入其中的游戏的知识和启发。她使用神经网络和蒙特卡洛播放的组合。 Leela Zero只知道基本规则，仅仅使用没有蒙特卡洛模拟的神经网络。

EGN：您对LeelaZero的兴趣感到惊讶吗？

GCP：是的，非常吃惊。根据Stockfish的分布式测试努力所获得的贡献量以及西方国际象棋运动员数量相对较多，我估计我们可能会有大约10位电脑爱好者来运行客户端。实际上客户端一般都超过500！同样，也有一些非常高质量的代码贡献。

EGN：已经有很多项目开始使用LeelaZero。我见过 Lizzie, SabakiLeela和Iceelz.。你有没有想过与Leela有关的未来教学工具？

GCP：我会把它留给别人，因为它对我来说并不是很有趣。对于经常使用Leela的人来说，有一个基本的图形用户界面 - 很多人对计算机的信心不足很难下载和安装单独的引擎和GUI，我想帮助他们。在某个时候它会升级到Leela Zero。我很乐意拥有一个能够很好地处理各种变化的好的游戏分析GUI，以及一些fuseki / joseki（定式）数据库以及一个强大的引擎支持它，就像国际象棋棋手几十年来一直使用它的主力。我希望有开放源代码Leela Zero来完成这一点。我也把由此产生的网络和数据开放到公共领域。如果有人根据它做出了非常好的事情，并且想要为自己的工作收取资金，他们可以这样做。

txh6062

大神

hred9D

谷歌停止围棋AI开发，那是因为，把阿尔法元的人工智能原理，移植到其他领域，比如医学中的诊断治疗等。
显然里拉的作者，纯研究AI围棋，没有其他想法。

罗浩宇

这是一位伟大的程序员！

扳黏童男

很帥