<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>AI效率与扩展性 on AI内参</title>
    <link>https://www.neican.ai/main_topics/ai%E6%95%88%E7%8E%87%E4%B8%8E%E6%89%A9%E5%B1%95%E6%80%A7/</link>
    <description>Recent content in AI效率与扩展性 on AI内参</description>
    <generator>Hugo</generator>
    <language>zh-cn</language>
    <lastBuildDate>Wed, 18 Jun 2025 11:20:04 +0800</lastBuildDate>
    <atom:link href="https://www.neican.ai/main_topics/ai%E6%95%88%E7%8E%87%E4%B8%8E%E6%89%A9%E5%B1%95%E6%80%A7/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>化繁为简：ZPressor如何破解3D高斯泼溅的“多视图之困”</title>
      <link>https://www.neican.ai/insights/zpressor3d-20250618112004717-2/</link>
      <pubDate>Wed, 18 Jun 2025 11:20:04 +0800</pubDate>
      <guid>https://www.neican.ai/insights/zpressor3d-20250618112004717-2/</guid>
      <description>浙江大学研究人员提出ZPressor模块，通过引入信息瓶颈原理，彻底解决了3D高斯泼溅（3DGS）在处理密集多视图输入时的性能瓶颈。ZPressor能够将可输入视图量提升至500个，推理速度提高3倍，并显著降低80%的内存占用，预示着其在AR/VR和更广泛的AI领域中的深远应用潜力。</description>
    </item>
  </channel>
</rss>
