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?
The 80286 introduced "Protected Mode" in 1982. It was not popular. The mode was difficult to use, lacked paging, and offered no way to return to real mode without a hardware reset. The 80386, arriving three years later, made protection usable -- adding paging, a flat 32-bit address space, per-page User/Supervisor control, and Virtual 8086 mode so that DOS programs could run inside a protected multitasking system. These features made possible Windows 3.0, OS/2, and early Linux.
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06:20, 28 февраля 2026Мир
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