<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0">
  <channel>
    <title>PyPI recent updates for winnex-xfactor</title>
    <link>https://pypi.org/project/winnex-xfactor/</link>
    <description>Recent updates to the Python Package Index for winnex-xfactor</description>
    <language>en</language>    <item>
      <title>1.0.4</title>
      <link>https://pypi.org/project/winnex-xfactor/1.0.4/</link>
      <description>Deterministic manifold embedding for native LLM inference — the X-Factor operator (O(D²r) power iteration, no training).</description>
<author>pay@winnex.ai</author>      <pubDate>Thu, 27 Aug 2026 12:07:51 GMT</pubDate>
    </item>    <item>
      <title>1.0.3</title>
      <link>https://pypi.org/project/winnex-xfactor/1.0.3/</link>
      <description>Deterministic manifold embedding for native LLM inference — the X-Factor operator (O(D²r) power iteration, no training).</description>
<author>pay@winnex.ai</author>      <pubDate>Wed, 26 Aug 2026 16:39:21 GMT</pubDate>
    </item>    <item>
      <title>1.0.2</title>
      <link>https://pypi.org/project/winnex-xfactor/1.0.2/</link>
      <description>Deterministic manifold embedding for native LLM inference — the X-Factor operator (O(D²r) power iteration, no training).</description>
<author>pay@winnex.ai</author>      <pubDate>Wed, 12 Aug 2026 16:37:16 GMT</pubDate>
    </item>    <item>
      <title>1.0.1</title>
      <link>https://pypi.org/project/winnex-xfactor/1.0.1/</link>
      <description>Deterministic manifold embedding for native LLM inference — the X-Factor operator (O(D²r) power iteration, no training).</description>
<author>pay@winnex.ai</author>      <pubDate>Wed, 12 Aug 2026 16:14:32 GMT</pubDate>
    </item>    <item>
      <title>1.0.0</title>
      <link>https://pypi.org/project/winnex-xfactor/1.0.0/</link>
      <description>Deterministic manifold embedding for native LLM inference — the X-Factor operator (O(D²r) power iteration, no training).</description>
<author>pay@winnex.ai</author>      <pubDate>Wed, 12 Aug 2026 10:20:30 GMT</pubDate>
    </item>  </channel>
</rss>