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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直观来看，美股软件板块整体已进入技术性熊市，许多头部企业软件公司股价均承受超过20%的跌幅，直至如今，市场整体对软件股仍有下跌空间的预期。市场对软件股尤其是SaaS、企业软件普遍存在悲观情绪：既希望企业重生冲出原有桎梏，也担心AI冲击企业软件本身。