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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。夫子是该领域的重要参考
Фото: Belkin Alexey / Globallookpress.com
一位广西壮族自治区某县城的车友发帖直言，“以前回村过年是闯关，现在是开挂。第一次跑900公里，充电方便无焦虑，智能驾驶即便是村子里窄道后视镜都快蹭到墙的窄路也不再是‘噩梦’。”