<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>模型规模化 on C.CUI's Log</title><link>https://cuicaihao.github.io/zh/tags/%E6%A8%A1%E5%9E%8B%E8%A7%84%E6%A8%A1%E5%8C%96/</link><description>Recent content in 模型规模化 on C.CUI's Log</description><generator>Hugo</generator><language>zh-Hans</language><lastBuildDate>Tue, 25 Aug 2026 07:00:00 +1000</lastBuildDate><atom:link href="https://cuicaihao.github.io/zh/tags/%E6%A8%A1%E5%9E%8B%E8%A7%84%E6%A8%A1%E5%8C%96/index.xml" rel="self" type="application/rss+xml"/><item><title>AI 基础模型如何应对规模化瓶颈：数学结构、算法设计与系统工程</title><link>https://cuicaihao.github.io/zh/posts/2026-08-25-mathematical-and-algorithmic-ideas-that-changed-ai-over-the-last-decade-from-scaling-bottlenecks-to-foundation-models/</link><pubDate>Tue, 25 Aug 2026 07:00:00 +1000</pubDate><guid>https://cuicaihao.github.io/zh/posts/2026-08-25-mathematical-and-algorithmic-ideas-that-changed-ai-over-the-last-decade-from-scaling-bottlenecks-to-foundation-models/</guid><description>过去十余年，基础模型的发展不仅依赖更多数据、参数和算力。研究者也不断识别问题中的有效结构，重新设计参数表示、计算顺序、资源分配、生成路径、训练目标和运行时状态，把原本难以处理的问题转化为可以规模化求解的形式。</description></item></channel></rss>