<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>机器学习工程 on AI内参</title>
    <link>https://www.neican.ai/tags/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%B7%A5%E7%A8%8B/</link>
    <description>Recent content in 机器学习工程 on AI内参</description>
    <generator>Hugo</generator>
    <language>zh-cn</language>
    <lastBuildDate>Thu, 11 Sep 2025 16:40:05 +0800</lastBuildDate>
    <atom:link href="https://www.neican.ai/tags/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%B7%A5%E7%A8%8B/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>告别“薛定谔的答案”：百亿独角兽重塑LLM推理确定性，开启AI研发新纪元</title>
      <link>https://www.neican.ai/insights/llmai-20250911164005634-1/</link>
      <pubDate>Thu, 11 Sep 2025 16:40:05 +0800</pubDate>
      <guid>https://www.neican.ai/insights/llmai-20250911164005634-1/</guid>
      <description>百亿美金独角兽Thinking Machines Lab解决了大语言模型推理中的非确定性难题，指出其根源在于“批次大小变化”而非浮点数非结合性。通过批处理不变性内核优化，他们实现了LLM输出的逐位一致性，这不仅将显著提升AI产品的商业可靠性，更将解锁“真正同策略强化学习”，为AI的科学可复现性与伦理治理奠定关键基石。</description>
    </item>
  </channel>
</rss>
