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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644 OPR_R - TMPB UNL RD D ; TMPB = popped SS; read ES
（二）在英雄烈士纪念设施保护范围内从事有损纪念英雄烈士环境和氛围的活动，不听劝阻的，或者侵占、破坏、污损英雄烈士纪念设施的；
京东京造前不久刚上线的第二批自研AI玩具，最大的看点就是新开发了针对年轻人和老年人的AI玩具，比如专为银发设计的“唠唠鹰”，具备紧急呼救、京东健康服务联动等各种安全功能，而且支持支持天津话、四川话、广东话等多种主流方言识别。