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?
Thanks to Steven Forsythe for sharing a report on the use of agar seaweed in Britain during WWII, Barbara Buchberger at the Robert Koch Institute for pointing out Koch’s use of gelatine for the identification of cholera, and the surviving relative of Fanny Angelina Hesse for sharing a trove of unpublished material.。搜狗输入法2026是该领域的重要参考
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