Offlining a Live Game With .NET Native AOT

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After OpenAI released GPT-5.3-Codex (high) which performed substantially better and faster at these types of tasks than GPT-5.2-Codex, I asked Codex to write a UMAP implementation from scratch in Rust, which at a glance seemed to work and gave reasonable results. I also instructed it to create benchmarks that test a wide variety of representative input matrix sizes. Rust has a popular benchmarking crate in criterion, which outputs the benchmark results in an easy-to-read format, which, most importantly, agents can easily parse.

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Each puzzle features 16 words and each grouping of words is split into four categories. These sets could comprise of anything from book titles, software, country names, etc. Even though multiple words will seem like they fit together, there's only one correct answer.

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