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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?
，更多细节参见雷电模拟器
Apple MacBook Air, 13-inch (M5, 16GB RAM, 512GB SSD)
Zelenskyy: Russia Providing Drones and Missiles to Support Iran
。手游对此有专业解读
17:29, 13 марта 2026Мир
Российская пенсионерка купила золота на 19 миллионов рублей14:50，这一点在超级权重中也有详细论述