salt4034

Yes, chess has been dealing with AI for decades at this point, and it's amusing/frustrating that so many other communities are deciding to re-discover everything from scratch, rather than just learn from the chess experience.

If CTF is a player-vs-player event, then AI should just be banned outright, otherwise it will devolve into AI-vs-AI, which is just not an interesting competition format, as we learned in chess. Compared to FIDE top events (which bans AI), only a tiny niche audience actually watches the Top Chess Engine Championship (AI-centered). It turns out what we care about is not whether chess can be solved by any means available, but what are the limits of the human mind in learning chess.

Pretty much all chess coaches/educators also warn against relying heavily on AI during learning; engines only give you an illusion of understanding.

If you're directly using AOSP, can't you just change the code to remove the check?

It's hard in general, but for instruct/chat models in particular, which already assume a turn-based approach, could they not use a special token that switches control from LLM output to user input? The LLM architecture could be made so it's literally impossible for the model to even produce this token. In the example above, the LLM could then recognize this is not a legitimate user input, as it lacks the token. I'm probably overlooking something obvious.

Not sure how I feel about this. If Take Take Take becomes very large, and most current Lichess users eventually switch to using that platform's mobile apps and website (say, because it has a few nicer features, and it's perceived as open source anyways), couldn't TTT suddenly decide to cut ties and entrap the community into yet another closed garden? By that time, there may not be a meaningful Lichess community left for users to switch back.

The author of Claude Code himself mentioned this in a recent interview. If I recall correctly, he mentioned that the best programmers he knows have an understanding of the "layer below the layer", which I think it's a good way of putting it. You're a better C programmer if you understand assembly, and you're a better "vibe coder" if you can actually understand the LLM generated code.

Here's how academics do it:

> Sam Altman confirmed power was indeed a major constraint [1].

> [1]: Personal communication.

Or even better:

> Power is a major constraint (Sam Altman, personal communication, December 9, 2025).

This part is unclear; what exactly did you change? Are you saying that the LP relaxation has value 271.666, but, when you enforce integrality, Gurobi can actually find and prove optimality of a solution with value 218?

Were you really just solving LPs up to this point in the article? How can these intermediate LPs be so slow to solve (6+ years) and yet Gurobi is able to solve the integer-restricted problem?

I think that was an intermediate model. The author updated it, then Gurobi solved the new model to optimality (i.e., the bound became equal to the value of the best solution found).

> With this improved model, I tried again and after ~23 000 seconds, Gurobi solved it to optimality!

In addition to the value of the best integer solution found so far, Gurobi also provides a bound on the value of the best possible solution, computed using the linear relaxation of the problem, cutting planes and other techniques. So, assuming there are no bugs in the solver, this is truly the optimal solution.

Maybe the sender edited the LinkedIn message? The email shows the original version, before the user edits.