Tools like Gemini can be useful at work, but they're limited to the information you give them when it comes to personal help. With Chat integration, Gemini can see a great deal more information from what's often the fastest-moving part of your day. Of course, how useful it is depends on how heavily your team relies on Chat. If this implementation works, Chat could seriously threaten other workplace communication options like Slack and Teams.
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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