April 2026
Intermediate
348 pages
8h 22m
Korean
Content preview from 그림으로 배우는 생성형 AI
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322
그림으로 배우는 생성형 AI
6.5 LLM옵스
이 책에서 저는
LLM
의 응답이 비결정론적이고 환각
과 부정확성이 흔히 발생한다는 점을 거듭 경고했습
니다
.
또한 지연시간
,
편향
,
개인정보보호
,
기밀성
,
보안 등 생성형
AI
기반 애플리케이션과 관련된 난제
들도 논의했고요
.
이러한 난제들 때문에
,
책임 있는
생성형
AI
를 보장하기 위해서는 프로덕션에 배포할
애플리케이션을 개발할 때 그저 기능
feature
구현에만
집중해서는 안 됩니다
.
[
그림
6
-
12
]
에서 보듯이 애
플리케이션의 전체 수명 주기를 관리하기 위한 도구
,
관행
,
작업흐름도 개발해야 합니다
.
그러한 활동과
노력을 통틀어
LLM
옵스
LLMOps
라고 부릅니다
.
개발과
운영의 조합인
‘
데브옵스
DevOps
’
에서 착안한
LLM
옵스
는 프로덕션 환경에서
LLM
기반 애플리케이션을 효
율적으로 관리하고 운영하는 데 사용하는 관행
practice
,
도구
,
기술을 아우르는 용어입니다
.
LLM
옵스는 더 넓은 개념인
ML
옵스
machine
learning
operations
(
MLOps
)
를
LLM
에 특화한 버전입니다
.
ML
옵
스는 프로덕션 환경에서 종단간 머신러닝 시스템의
개발 및 운영을 위한 도구
,
프로세스
,
모범관행을 아
우르는 개념입니다
.
ML
옵스는 프로덕션 환경에서 머
신러닝 모델의 복잡성을 관리하고 모델이 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.