第22章 · 2026 AI 技术全景

本章给出一张全栈地图。知道”有什么”比知道”怎么用”更优先 — 当你知道 vLLM 存在，自然会去查怎么部署；如果不知道，你可能以为只有 Ollama 一条路。

从应用层到训练层，七层架构逐层展开：全栈总览（22.1）-> 推理引擎（22.2）-> Agent 框架与互操作协议（22.3）-> 微调管线 SFT -> LoRA -> DPO（22.4）-> RAG 技术栈（22.5）-> 多模态模型（22.6）。每节包含概念讲解、教学方法、注意事项和关联指引，零基础读者可顺序阅读。

本章阅读指引：作为汇总章，大量工具和框架名密集出现。已在前面章节详细讲过的术语标注了”详见第X章”；全新的工具给出简短的一句话解释 — 知道它是干什么的即可，不需要在此展开。

生活比喻：AI 技术栈像一座城市的地图——应用层是街边的商店（用户直接用的产品），模型层是工厂（生产智能的地方），基础设施是水管电网（算力、存储、网络）。你不需要记住每条街的名字，但有了这张地图，你就知道去哪找什么，不会迷路。

本章目录

1. 22.1 全栈架构
2. 22.2 推理引擎：从云端到边缘
3. 22.3 Agent 框架：选型指南
4. 22.4 微调技术：SFT -> LoRA -> DPO 管线
5. 22.5 RAG 技术栈
6. 22.6 多模态模型一览

graph TD
    A[AI 技术全景] --> B[应用层]
    A --> C[模型层]
    A --> D[基础设施]
    B --> B1[Agent 框架选型]
    B --> B2[Agent 互操作协议]
    C --> C1[推理引擎]
    C --> C2[微调管线 SFT→LoRA→DPO]
    C --> C3[RAG 技术栈]
    C --> C4[多模态模型一览]
    D --> D1[全栈架构总览]

跨章节关联

• 第11章 · 模型微调 — 微调技术栈全景
• 第13章 · RAG 进化树 — RAG 技术栈全景
• 第14章 · Agent 是怎么工作的 — Agent 框架全景
• 第20章 · 模型推理部署 — 推理引擎全景
• 第21章 . MLOps 基础 — MLOps 工具链全景

来源

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