What's the problem, really? Given the direction the U.S. has been heading in recent years, I wonder what really sets it apart from China. Europe needs to maintain an equal distance from both the U.S. and China.
Good point and it's actually worse than that : the thinking tokens aren't affected by this at all (the model still reasons normally internally). Only the visible output that gets compressed into caveman... and maybe the model actually need more thinking tokens to figure out how to rephrase its answer into caveman style
I don't play it much anymore, but I used to be a heavy player: the latency isn't 50 ms on GeForce Now (with a French connection, which is pretty good).
That's true, I'm not saying it comes without trade-offs. But in return you get a perfectly consistent and physically accurate simulation. It would mostly be expensive, I think, but it's technically feasible (services like Shadow or GeForce Now already demonstrate that).
Wouldn't it have been simpler (even if technically heavy) to host the game on a single machine and just stream each player's camera? That way all the physics would be computed in real time on one computer, and each player would just receive a different video stream.
i'm experimenting with a different approach (no CDP/ARIA trees, just Chrome extension messaging that returns a numbered list of interactive elements).
Way lighter on tokens and undetectable but still very experimental : https://github.com/DimitriBouriez/navagent-mcp
One thing to consider: we don’t know if these LLMs are wrapped with server-side logic that injects randomness (e.g. using actual code or external RNG). The outputs might not come purely from the model's token probabilities, but from some opaque post-processing layer. That’s a major blind spot in this kind of testing.