MacBook Pro was built with the environment in mind, and brings Apple even closer to reaching its ambitious plan to be carbon neutral across its entire footprint by 2030. It is made with 45 percent recycled content,8 including 100 percent recycled aluminum in the enclosure and 100 percent recycled cobalt in the battery. It is manufactured with 50 percent renewable electricity, such as wind and solar, across the supply chain. The new MacBook Pro is designed to be durable and repairable, and also offers industry-leading software support, while meeting Apple’s high standards for energy efficiency and safer chemistry. The paper packaging is 100 percent fiber-based and can be easily recycled.9
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Базу США в Ираке атаковал беспилотник08:44
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?