Did Tim Cook just tease a touchscreen MacBook? Sure looks like it.

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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?

As part of their research, they have put together a set of proposed improvements for Node.js' Web streams implementation that will eliminate promises in certain code paths which can yield a significant performance boost up to 10x faster, which only goes to prove the point: promises, while useful, add significant overhead. As one of the core maintainers of Node.js, I am looking forward to helping Malte and the folks at Vercel get their proposed improvements landed!,详情可参考Line官方版本下载

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