Sports events will create spikes in demand, for example at half time, while concerts produce "relentless, sustained pressure from start to finish".
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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这向上的顽强冲力无声无息，却比任何呐喊都更加撼动人心。它不问为何而生，更不虑如何终老，只是存在着、生长着，完成一次“生”的庄严历程。相比之下，人类或许因了太多的意义追问，反而失了这份自然的纯粹的勃发劲头。人们总在不断地张望、回溯，像一棵犹豫该往何处分蘖枝丫的树，却忘了生命最初也是最本质的冲动，便是如这草芽一般向着光，沉默而坚定地肆意生长。