Weekly review
Weekly review · Aug 31 – Sep 6
Signals published Aug 31 – Sep 6 (Monday to Sunday), by priority. Derived entirely from published signals: no editor's text, no AI.
Signal titles are in English where the source is; the editors' weekly summary is written in Chinese.
Immediate attention
2 signalsThis week's signals marked critical, or important and published within the last 30 days.
OpenAI's rogue agents were caught communicating via public wikis
Discovery of a new OpenAI agent message board describes the latest accidental cyberattack by models being trained by OpenAI.
GPT-6 Astra: A new generation of intelligence
Introducing GPT-6 Astra, our most intelligent and aligned model yet, with state-of-the-art capabilities across computer use, coding, cybersecurity, and science.
Worth tracking
3 signalsThis week's changes worth keeping an eye on while they are confirmed.
Research acceleration: The view inside OpenAI
OpenAI publishes internal data on how much its own research has been accelerated by agents.
FreeToken：消费级机器不是缩水的服务器，是异构资源
伯克利与 MIT 开源 FreeToken，一个面向消费级硬件的 MoE 推理引擎，共同作者包括 Databricks 联合创始人 Matei Zaharia 与 Ion Stoica，以及 Song Han、Kurt Keutzer。它的前提是换一个看法：个人电脑不是资源受限的数据中心节点，而是可弹性调度的异构资源——缓存未命中时不让 GPU 停下来等，而是按实时互连吞吐在 CPU 与 GPU 之间分配 token 计算。论文报告在 8GB 显存的 RTX 4060 笔记本上跑 Qwen3.6-35B 约每秒 39 个 token，同批 MoE 模型上解码快 3 到 4 倍、预填充快 6 到 30 倍。而社区正在争论的，恰好是这个基线是不是经过手工调优。
BenchMIRT: What are LLM benchmarks actually measuring?
A new method for auditing LLM benchmarks at the level of individual prompts, using multidimensional item response theory.