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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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writable: false means no code can reassign window.Audio to a different value. configurable: false means no code can even call Object.defineProperty again to change those settings. If fermaw’s initialisation code tried to restore the original Audio constructor (a perfectly sensible defensive move) the browser would either fail or throw a TypeError. The hook was permanent for the lifetime of the page.
1. 学制压缩与集成化： 2026年，日本等国正式实施本硕“五年一贯制”教育模式，旨在缩短人才进入社会的时间窗口 [52]。在中国，专业硕士（专硕）的招生规模持续扩大，且教学内容更加强调产教融合、订单式培养 [47, 53, 54]。
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Finch said she went back to the clinic and was put on a drip.
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