Фото: @yeva_mishalova
当我写完这篇体验将它关机放回抽屉时，我意识到这次折腾的收获并不是复古情怀。而是重新确认了一件事：有些产品即使失败了，也依然值得被记住。，详情可参考im钱包官方下载
Very interested in feedback about these!。谷歌浏览器【最新下载地址】对此有专业解读
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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?