As a data scientist, I’ve been frustrated that there haven’t been any impactful new Python data science tools released in the past few years other than polars. Unsurprisingly, research into AI and LLMs has subsumed traditional DS research, where developments such as text embeddings have had extremely valuable gains for typical data science natural language processing tasks. The traditional machine learning algorithms are still valuable, but no one has invented Gradient Boosted Decision Trees 2: Electric Boogaloo. Additionally, as a data scientist in San Francisco I am legally required to use a MacBook, but there haven’t been data science utilities that actually use the GPU in an Apple Silicon MacBook as they don’t support its Metal API; data science tooling is exclusively in CUDA for NVIDIA GPUs. What if agents could now port these algorithms to a) run on Rust with Python bindings for its speed benefits and b) run on GPUs without complex dependencies?
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2026-03-02 00:00:00:0本报记者 颜 珂 孙 超3014296910http://paper.people.com.cn/rmrb/pc/content/202603/02/content_30142969.htmlhttp://paper.people.com.cn/rmrb/pad/content/202603/02/content_30142969.html11921 湖南持续用力打造科技创新高地（“十五五”开好局起好步）。体育直播对此有专业解读
创始人奥特曼因此巡回世界，与各国领导人会面，登上杂志封面。OpenAI的品牌价值在于“让AI触手可及”。