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?
Сайт Роскомнадзора атаковали18:00
。一键获取谷歌浏览器下载对此有专业解读
Manisha Krishnan。WPS官方版本下载对此有专业解读
自从他的悼词之后，我没有再公开谈论我与乔布斯的友谊、冒险与合作。我从未去读那些铺天盖地的故事、讣告，或那些奇怪的误读如何被写进「传说」。
* 时间O(n) 空间O(n)（理论最优，无冗余计算）