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?
5年来，中央财政衔接资金累计用于产业发展占比超过60%，指导832个脱贫县编制实施“十四五”特色产业发展规划，分类推进帮扶产业提质增效、全链条开发。
target.toString = function () {，推荐阅读91视频获取更多信息
They accumulate across 20+ projects with the same stale API key
，这一点在旺商聊官方下载中也有详细论述
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