NVIDIA (Jensen Huang / AI infrastructure)
你收到的每一条AI回复,最初都始于一个电子⚡
黄仁勋近期接受红杉资本采访时将AI基础设施比作五层蛋糕:在芯片、数据中心、模型之下的最底层是能源。智能时代的核心约束并非算力、软件,而是电力。英伟达将AI工厂称作当代发电机,输入电子、输出智能token,这场人类史上最大规模基建已投数千亿美元,仍需数万亿跟进,核心问题是电网能否跟上AI扩容节奏⬆️
AI Signal Daily Digest
追踪 AI 一线声音:做事的人、写代码的人、下注的人。今天重点从 GitHub 源池拉取 X / Twitter、播客和 arXiv,保留原文链接,页面只放可快速阅读的卡片摘要。
你收到的每一条AI回复,最初都始于一个电子⚡
黄仁勋近期接受红杉资本采访时将AI基础设施比作五层蛋糕:在芯片、数据中心、模型之下的最底层是能源。智能时代的核心约束并非算力、软件,而是电力。英伟达将AI工厂称作当代发电机,输入电子、输出智能token,这场人类史上最大规模基建已投数千亿美元,仍需数万亿跟进,核心问题是电网能否跟上AI扩容节奏⬆️
Claude Code现已支持在桌面应用内打开任意网站。Claude可使用你的生产应用、打开它发送给你的链接、浏览Twitter,甚至观看FIFA世界杯。
我们已了解企业对AI成本的顾虑,5.6 sol在降低单位任务美元成本上取得巨大进展,terra和luna同样如此。
GPT-5.6 现已成为微软 365 Copilot 的首选模型。
源池已读取,但这一栏没有通过筛选的高质量中文摘要。
Geometry Foundation Models (GFMs) have substantially advanced monocular 3D reconstruction, yet extending this capability to 4D dynamic understanding remains a fundamental challenge.
LLM training is shifting from manual design and annotation to interaction-driven self-evolution.
To effectively integrate AI into high-stakes, critical environments such as healthcare, autonomous driving, and aviation--and to advance toward higher levels of automation and seamless human-AI collaboration--building trust in AI-driven solutions is essential.
Adding procedural skills to an LLM agent is typically evaluated by average improvement in task success.
In this paper, we propose a new solution for addressing the content cold-start problem in industry-scale search and recommender systems.
A central design principle in modern machine learning and artificial intelligence is to align a model's inductive bias with the structure of its input data.