<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/">
  <channel>
    <title>Distributed Inference on AI Tech Blog</title>
    <link>https://jesamkim.github.io/ai-tech-blog/tags/distributed-inference/</link>
    <description>Recent content in Distributed Inference on AI Tech Blog</description>
    <generator>Hugo -- 0.147.6</generator>
    <language>ko</language>
    <lastBuildDate>Wed, 10 Jun 2026 10:00:00 +0900</lastBuildDate>
    <atom:link href="https://jesamkim.github.io/ai-tech-blog/tags/distributed-inference/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>내 데이터는 안 보내고 똑똑해지기: 연합학습부터 분산 추론까지</title>
      <link>https://jesamkim.github.io/ai-tech-blog/posts/2026-06-10-federated-learning-to-distributed-inference/</link>
      <pubDate>Wed, 10 Jun 2026 10:00:00 +0900</pubDate>
      <guid>https://jesamkim.github.io/ai-tech-blog/posts/2026-06-10-federated-learning-to-distributed-inference/</guid>
      <description>데이터를 한곳에 모으지 않고 모델을 학습시키는 연합학습의 원리부터, 학습된 거대 모델을 효율적으로 서비스하는 분산 추론까지 초보자 눈높이로 정리했습니다.</description>
    </item>
  </channel>
</rss>
