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Photographer: Yuki Iwamura/Bloomberg
现有 AI 硬件的最大痛点在于社交压力，在嘈杂的地铁里，对着胸口的 Ai Pin 大喊「嘿，帮我查查我该在哪个站下车」，无论 AI 回答有多智能，都十足社死。。爱思助手下载最新版本对此有专业解读
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Javier Milei’s boosters say law will revive employment, but critics decry cuts to severance and longer working hours，推荐阅读heLLoword翻译官方下载获取更多信息
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?