I got asked about a month ago by two PhD students from China whether they could enter and operate Leela Zero for this tournament. I hesitated for a bit, because IMHO entering Leela Zero into competitions for computer go bots is somewhat besides the point and detracts from the project's goal.
To me it feels pointless because you can literally take the weights and data (and even the code, depending on morals and tournament rules), improve it a bit (I suggest adding some go knowledge!), and you should have a stronger program if you understand how to test properly.
The problem of open source bots and competitions is not new. Computer chess has a particularly bad history with this and it's one of the reasons I went into go programming. In the end, it is up to the tournament organizers to set rules that ensure fair play and actually have the balls to enforce them.
The phenomenon of these private matches with open source (or just public) bots and secret bots is not something I've seen before though. It may be a sign of the times when you can now "hide" the program easier behind online services, or simply super-corporations finding games useful for publicity (cough IBM cough Google). A program that the user can buy commercially can't really "hide" it's real strength for long, as the user can (and does, CCRL, TCEC, etc) run tournaments with it.
On the other hand, I considered that not entering doesn't do anything either, does it? By entering, we are a well known benchmark for the public and other teams to beat. I'd rather have more people finding out about the project, all things considered. So I gave permission to enter Leela Zero. I have not heard back, but I assume from the above at least it got entered somehow.
Anyway, my point, if anything, from all the above is that it is not worth getting too worked up over these kind of uses of the program, code and data even if it seems it occasionally allows other teams to score "victories" or PR you consider questionable. A collaborative effort has the property that it can outlast secret or proprietary projects and eventually bring more value to the users.
I don't know about you, but I'm still using Stockfish to analyze my chess games, and not Alpha Zero or Deep Blue.
I'm not so much bothered about the disparity in hardware (which of course makes it unfair, but that is capitalism for you), but about the fact that settings/networks/hardware are apparently being changed mid match.
This means a simple thing: it was not tested properly. Before you play the match or tournament, you figure out the optimal configuration. If you are even so much as tempted to change the configuration during the games, it means you did not test properly, because what information can you possibly have gotten in that time period that invalidates your prior test for the optimal configuration?
Now, given that
this match is apparently not to be taken seriously, due to the above, and it seems even operator errors stand(?!)
people are starting to lose their shit over it
there's no usable info for the development of LZ due to the above and lack of transparency
From what I learned in the QQ group they are in, the participants are the same guys who are running LZ for the Golaxy game.
From my email, they know each other but it's not the same people. Aaaanyway, I'll send them the guidance I can regarding "test things exhaustively in advance not during the tournament" and "only consider statistically significant results when doing not-default things" and I hope some of it takes hold and lessons were learned from the Golaxy debacle.
https://github.com/gcp/leela-zero/issues/1220作者: lu01 时间: 2018-4-20 08:17 提问
because are there any legal case precedents on derivation use of networks trained from community deep learning? The license only applies to the code, but I don't see it covering all imaginable derivative use of that code. the training data is already public.
FWIW all networks that come off of my training machine should be considered public domain, at least that was the intention. I don't think it makes sense to do otherwise as the training code is public (GPL) and data to generate them is already public domain.
I can't speak for the 256x20 that were contributed. I assume there's at least an implicit license to serve them off of zero.sjeng.org.
因为在推导使用社区深度学习培训网络方面是否有任何法律案例先例？ 该许可证仅适用于代码，但我没有看到它涵盖了该代码的所有可想象的派生用法。 训练数据已经公开。
