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?
So, what does it all mean?
動物權益及福祉協會賴嘉敏主席欣賞穆斯林佔比不低的新加坡,能在照顧伊斯蘭教認為狗唾液不潔的同時,允許私營餐飲場所讓寵物犬進入戶外用餐區,也欣賞台灣整體社會的寵物友善氣氛。以桃園為例,市政府農業局專門發佈了寵物友善餐廳名冊。。同城约会是该领域的重要参考
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Трамп высказался о непростом решении по Ирану09:14
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