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LLM 技术图谱(LLM Tech Map)

LLM 技术图谱(LLM Tech Map)是将 LLM 相关技术进行系统化和图形化的呈现,此图谱主要特点是“专注于技术人视角”,不求从 LLM 产业角度汇聚信息,而是希望让从事相关工作或是想了解 LLM 的技术人有一个快速感知。

LLM 技术图谱(LLM Tech Map)从基础设施、大模型、Agent、AI 编程、工具和平台,以及算力几个方面,为开发者整理了当前 LLM 中最为热门和硬核的技术领域以及相关的软件产品和开源项目。

核心价值:帮助技术人快速了解 LLM 的核心技术和关键方向。

基础设施

LLM 技术图谱(LLM Tech Map)的基础设施部分主要包括以下几个方面:

  • 向量数据库:向量数据库是专门用于存储和检索向量数据的数据库,它可以为 LLM 提供高效的存储和检索能力。
  • 数据库向量支持:传统数据库通常不支持向量数据的存储和检索,数据库向量支持可以为传统数据库添加向量数据的存储和检索能力。
  • 大模型框架、微调 (Fine Tuning):针对大模型的开发。
  • 大模型训练平台与工具

大模型

LLM 技术图谱(LLM Tech Map)的大模型部分主要包括以下几个方面:

  • 备案上线的中国大模型:有牌照提供服务的大模型,需要注意的是大模型和相应的产品多半名称不同。
  • 知名大模型:在全球范围内,已经发布了多款知名大模型,这些大模型在各个领域都取得了突破性的进展。
  • 知名大模型应用:LLM 已经在多种应用场景中得到了应用,包括文本生成、机器翻译、问答、自然语言推理等。

AI Agent(LLM Agent)

LLM Agent 是指基于 LLM 技术构建的智能代理,它可以用于各种任务,比如让机器与 ChatGPT 交互,一层一层挖掘信息,自动化完成任务;比如由机器人构成的虚拟小镇。

AI 编程

让 LLM 帮你编写代码。

工具和平台

LLM 技术图谱(LLM Tech Map)的工具和平台部分主要包括以下几个方面:

  • LLMOps:简单点说(大家当前在说的),就是“快速从大模型到应用”。
  • 大模型聚合平台:汇聚大模型能力,提供服务。
  • 开发工具:其它开发相关的 LLM 工具。

算力

LLM 模型的训练和部署需要大量的算力,算力是 LLM 技术发展的关键因素。


另外,图谱上这些方向都可以单独拉出相关的话题,比如(随便举几个不完整的例子):

- 算力现在的行情就是“一片难求”……
- 向量数据库原本是国外有屈指可数的几家公司在发展,但当前国内 Zilliz 的 Milvus 已经取得了非常不错的成绩……
- LLMOps 的能力真的就只是“快速从大模型到应用”?
- 用机器去搞机器,LLM Agent 真能探到真实世界的边际吗?

有相关观点输出的同志可以直接联系我,一起策划、传播,一起玩。

关联项目:https://gitee.com/oschina/awesome-llm

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