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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?
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But no one is ready to say when hundreds of new missile silos, dug from the windswept Great Plains, will be finished, how much they cost, or, for that matter, how many nuclear warheads each Sentinel missile could actually carry.
屏幕变大，处理器变强，电量消耗再也回不去了。
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Agar is prized among chefs for its ability to form firm, heat-stable gels at remarkably low concentrations — typically just 0.5-2 percent by weight. Culinary agar is available as powder, flakes, strips, or blocks, and makes up about 90 percent of the global use of agar. Unlike gelatine, which melts at body temperature, agar gels remain solid up to about 185°F (85°C), making it ideal for setting dishes served at room temperature or warmer. It is also flavorless and odorless, vegan and halal, and can create both delicate jellies and firm aspics. Yet, while increasingly employed in kitchens worldwide, agar had not yet entered the laboratory.。关于这个话题，爱思助手下载最新版本提供了深入分析
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