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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三十年前，秘鲁在恶性通胀与内战阴影中推进产权改革，经济一度重回增长轨道；三十年后，总统频繁更替、政治对立加剧、制度信任崩塌。德索托的名字，既象征一种发展理论的希望，同时也提醒我们：一个国家的命运，从来不只是经济学问题，更是制度能否持续运转的问题。，更多细节参见搜狗输入法下载
在這波補課潮下，還是大學生的李靜玟提出反問：與其受到一部傷害台灣社會的電影影響而去補課，為什麼不一開始就把這門課學好？但她也認為，對這個社會而言，補課是遲早的事情，「如果傷痕沒有被好好的撫平，歷史的真相沒有被社會所看見，那這話題爭議就會像舊傷復發一樣，反覆發生。」