February 25, 2026
媒体预计将于本周三早上 9 点（美国东部时间）在纽约、伦敦和上海举行的“Apple Experience”线下体验活动中，率先上手这款新品。 此次发布并不会通过传统的苹果线上发布会直播形式进行，外界预计苹果将通过官网 Newsroom 新闻稿的方式正式公布 MacBook Neo 及其详细信息。
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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?