<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>AI能效 on AI内参</title>
    <link>https://www.neican.ai/tags/ai%E8%83%BD%E6%95%88/</link>
    <description>Recent content in AI能效 on AI内参</description>
    <generator>Hugo</generator>
    <language>zh-cn</language>
    <lastBuildDate>Thu, 04 Sep 2025 09:40:05 +0800</lastBuildDate>
    <atom:link href="https://www.neican.ai/tags/ai%E8%83%BD%E6%95%88/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>打破硅基算力瓶颈：微软模拟光学计算机如何重塑AI与优化范式</title>
      <link>https://www.neican.ai/insights/article-20250904094005015-2/</link>
      <pubDate>Thu, 04 Sep 2025 09:40:05 +0800</pubDate>
      <guid>https://www.neican.ai/insights/article-20250904094005015-2/</guid>
      <description>微软的模拟光学计算机（AOC）通过结合模拟电子与三维光学技术，实现了无需数字转换即可同时高效执行AI推理和组合优化任务的突破。这项登上Nature的研究，承诺将AI推理能效提升百倍，挑战了现有硅基算力的能耗瓶颈，并预示着计算架构的深层变革，对AI的可持续发展、产业竞争格局及未来应用边界具有深远影响。</description>
    </item>
    <item>
      <title>大模型能耗迷思的解构与重塑：Google Gemini揭示“绿色AI”新范式</title>
      <link>https://www.neican.ai/insights/google-geminiai-20250822204005234-3/</link>
      <pubDate>Fri, 22 Aug 2025 20:40:05 +0800</pubDate>
      <guid>https://www.neican.ai/insights/google-geminiai-20250822204005234-3/</guid>
      <description>Google报告揭示Gemini大模型单次查询能耗远低于预期，并通过模型架构、定制TPU及高效数据中心的全栈式优化，将能耗和碳排放大幅降低。这不仅挑战了对AI“能耗巨兽”的普遍认知，更将能源效率推至产业竞争核心，预示着可持续性将成为评估未来AI系统和企业战略的关键维度。</description>
    </item>
  </channel>
</rss>
