self.seen_urls.add(url)
Salesforce 去年因 AI 技术进步裁员约 4000 人； Pinterest 裁员近 15%，将资源向 AI 相关岗位倾斜； Amazon 首席执行官 Andy Jassy 也明确表示，生成式 AI 将重塑企业运作方式，未来几年员工总数可能持续下降。
。搜狗输入法下载对此有专业解读
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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