I think it's slightly less ridiculous than it sounds, because governments have much more power over their own citizens. As an American I would dramatically prefer the Chinese government to spy on me than the American government, because the Chinese government probably isn't going to do anything about whatever they find out.

(That logic breaks down somewhat in the case of explicitly negotiated surveillance sharing agreements.)

> I don’t know who operates this agent, and I’m not going to speculate about why they did what they did.

I don't really understand the criticism. The authors aren't claiming to have the strongest chess engine without search. They are just showing that they got a chess engine to a respectable level with their process, which is somewhat different from LC0. They do in fact explain that explicitly:

> Leela Chess Zero’s networks, which are trained with self-play and RL, achieve higher Elo ratings without using explicit search at test time than our transformers, which we trained via supervised learning. However, in contrast to our work, very strong chess performance (at low computational cost) is the explicit goal of this open source project (which they have clearly achieved via domain-specific adaptations). We refer interested readers to [https://arxiv.org/abs/2409.12272] (which was published concurrently to our work) for details on the current state-of-the-art and a comparison against our network.

And I don't think the criticism of their writing is on point either. I don't think they are secretly implying that their engine is better than Stockfish. And it's 100% plausible for human masters to rigorously analyze many positions with engine assistance and correctly establish whether Stockfish's evaluation is right or not.

That's great, I'm going to use that one in the future.

I recommend Matthew Sadler's Game Changer and The Silicon Road To Chess Improvement.