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?
此前在华为，郭锐深度参与了华为手机品牌建设，被视为“黄金一代”，见证了华为手机品牌从电信贴牌机到高端代名词的成长历程。此外，郭锐早期曾任职于宝洁、中粮蒙牛等快消巨头，非常善于和C端消费者打成一片，积累了丰富的品牌建设和市场运营经验。
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Овечкин продлил безголевую серию в составе Вашингтона09:40
Трамп высказался о непростом решении по Ирану09:14，这一点在同城约会中也有详细论述