Fascinating talk on applying deep learning to detecting cheaters in CS:GO https://www.youtube.com/watch?v=kTiP0zKF9bc
The presenter discusses how they get machine-readable data out of matches, and how they still keep a human in the loop (ML just feeds the human analysis component).
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I've been really enjoying paru as a pacman substitute on Arch Linux: https://github.com/Morganamilo/paru
It allows you to update both normal and AUR packages in one go, which is super convenient. It also shows you PKGBUILD files, so there's still a human audit step for AUR.
A funny side effect of building software in Rust: my machine OOMs much more during development.
I'm not entirely sure why. I think Rust makes it easy to allocate data quickly, and sooner or later you write an infinite loop when coding.
I find it odd that people recommend Docker for sandboxing agentic coding tools. Isn't it easier to just create a separate user account on the machine?
It's an established security boundary, and viewing output is easy (just make the user's home directory world readable).