今年32歲的Amu來自印尼爪哇島中部。七年前，他懷抱賺錢成家的夢想來到台灣。和數十萬名來台工作的外籍移工一樣，他為了支付高昂的仲介費借貸，即使工作了一年多，薪資仍在填補債務的缺口。
Sainsbury's to cut 3,000 jobs and shut cafés，更多细节参见夫子
with the Endowment's Members and the open source community.。51吃瓜对此有专业解读
Фото: James Lang / Imagn Images / Reuters
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?