Interesting, nuanced discussion of Leela Chess Zero (a neural net) beating Stockfish in a recent competition: https://news.ycombinator.com/item?id=20027838
Whilst the original DeepMind result was impressive, it's great to see reproducible results and a project that's available to the public.
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LLMs are surprisingly good at reducing crash samples.
I've had success with "this project crashes my static analysis tool with the following command, try to shrink the repro whilst preserving the crash. Commit each smaller version to a branch".
One subtle behaviour of Claude that wasn't obvious to me: whilst each conversation is transient, permissions persist across conversations.
So if you've given permission to run e.g. 'cargo test' or even 'cargo run', you need to be sure that all future invocations are safe too.
You can see the current permissions with /permissions.
Whilst LLMs don't always give an accurate answer, the UI is really compelling. I keep finding users whose favourite way of doing research is an LLM.