<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>权重蒸馏 on AI内参</title>
    <link>https://www.neican.ai/tags/%E6%9D%83%E9%87%8D%E8%92%B8%E9%A6%8F/</link>
    <description>Recent content in 权重蒸馏 on AI内参</description>
    <generator>Hugo</generator>
    <language>zh-cn</language>
    <lastBuildDate>Mon, 29 Jun 2026 08:10:04 +0800</lastBuildDate>
    <atom:link href="https://www.neican.ai/tags/%E6%9D%83%E9%87%8D%E8%92%B8%E9%A6%8F/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>超越刷题的智能：当AI训练范式从“静态预训练”走向“部署后持续经验进化”</title>
      <link>https://www.neican.ai/insights/article-20260629081004721-0/</link>
      <pubDate>Mon, 29 Jun 2026 08:10:04 +0800</pubDate>
      <guid>https://www.neican.ai/insights/article-20260629081004721-0/</guid>
      <description>下一代AI训练范式正在从离线预训练转向部署后的持续学习，通过自蒸馏和模拟演练将真实任务中的经验沉淀至模型权重中。这种转变不仅打破了AI能力增长的瓶颈，也标志着AI从单纯的工具向具备自主进化能力的智能劳动力演进。</description>
    </item>
  </channel>
</rss>
