DeepSeek 又发论文了。 这一次，他们把重点聚焦到了一个很少被外界看到、却越来越影响 Agent 训练规模的地方：沙箱基础设施。 论文标题：DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale 论文链接：https://arxiv.org/pdf/26 ...

本内容遵循CC 4.0 BY-SA版权协议 这是一棵可增量生长的文章树。本系列只覆盖「单 Agent 范式」这一层：一个 LLM 在循环中基于环境反馈使用工具，直到任务完成或触发停止条件。 工作流范式（五种编排模式）、多 Agent 范式（拓扑与协调）、框架选型属于同级的 ...

文章浏览阅读140次。2026年9月1日到11日，海内外7家头部模型厂商迭代了新模型。过去大模型的升级周期以年计算，后来缩短到几个月，如今已经开始以周为单位。据OpenRouter平台数据，DeepSeek V4.1 Flash在发布24小时内被处理了约1万亿Token。当模型迭代进入“周更时代”，一个越来越尖锐的工程问题浮出水面：你的应用架构，跟得上这个节奏吗？

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