Trained — weights learned from data by any training algorithm (SGD, Adam, evolutionary search, etc.). The algorithm must be generic — it should work with any model and dataset, not just this specific problem. This encourages creative ideas around data format, tokenization, curriculum learning, and architecture search.
This month, OpenAI announced their Codex app and my coworkers were asking questions. So I downloaded it, and as a test case for the GPT-5.2-Codex (high) model, I asked it to reimplement the UMAP algorithm in Rust. UMAP is a dimensionality reduction technique that can take in a high-dimensional matrix of data and simultaneously cluster and visualize data in lower dimensions. However, it is a very computationally-intensive algorithm and the only tool that can do it quickly is NVIDIA’s cuML which requires CUDA dependency hell. If I can create a UMAP package in Rust that’s superfast with minimal dependencies, that is an massive productivity gain for the type of work I do and can enable fun applications if fast enough.
Go to technology，这一点在同城约会中也有详细论述
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I'm picking on rust here because it's no secret it has a long history of having some very... enthusiastic users. But my broader point is that tools are just tools. They're not our identity, a mark of our wisdom, or a moral choice. Other people have different perspectives, tastes, and skills - and they may prefer different tools to us.。关于这个话题，im钱包官方下载提供了深入分析
На Западе подчинили рой насекомых для разведки в интересах НАТО08:43