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TA们不惜重金投入，意在将硬件作为打入用户生活、采集全景数据、导流生态服务的“特洛伊木马”，Meta与雷朋合作的眼镜已卖出超百万副，目标不是撒瓜俩枣的硬件利润，而是巩固其社交与内容王国的前端感知节点。
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Жители Санкт-Петербурга устроили «крысогон»17:52
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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