---
title: "开源AI差距地图：全球合作构建AI公共选项"
source: "Simon Willison 博客（Atom）"
source_tier: "t2"
url: "https://simonwillison.net/2026/Jul/3/open-source-ai-gap-map/#atom-everything"
permalink: "https://feed.astralor.com/items/itm_4c8e751a878dcbfc29320add"
published: "2026-07-03T22:04:31.000Z"
score: 63
channel: "ai"
tags: ["Current AI","开源","开源AI差距地图"]
---

# 开源AI差距地图：全球合作构建AI公共选项

## 速览

Current AI 是一个非营利组织，于2025年2月在巴黎AI行动峰会上成立，已获4亿美元资本承诺。其发布的Gap Map v0.1深度索引了421个开源AI产品，包括266个软件工具与库、85个模型、50个数据集和20个硬件项目，由228个组织贡献。地图按组件层、产品/用户体验层和基础设施层分为14个类别，其余2.44万个未分类工件暂无评分。底层数据以MIT许可证开源在GitHub，包含1184个YAML文件及辅助脚本，可通过Datasette Lite探索。

## 关键点

- Gap Map v0.1 收录421个开源AI产品，覆盖模型、工具、数据集和硬件。
- 由非营利组织Current AI运营，初始获4亿美元承诺资金。
- 数据以MIT许可证开源，包含1184个YAML文件，可通过Datasette Lite探索。
- 其余2.44万个低知名度工件暂未评分，需后续研究和引用。

## 全文

Open Source AI Gap Map Current AI is "a global partnership building a public option for AI", founded as a non-profit at the AI Action Summit in Paris in February 2025 and backed by serious capital ($400m already committed). They launched their Gap Map a couple of days ago - an attempt at indexing the current state of open source AI: The Gap Map v0.1 details 421 products in depth: 266 software tools and libraries, 85 models, 50 datasets, and 20 hardware projects, produced by 228 organizations. These products are organized into 14 categories across 3 layers of the stack (model components, product / UX, and infrastructure). The remaining 24,400 artifacts constitute the uncategorized long tail of the open source AI ecosystem, and will carry no score until they are researched and cited. The map itself is interesting to explore, but I'm more excited about the underlying data - released under an MIT license in the currentai-org/os-ai-map GitHub account: 1,184 YAML files plus the notebooks, schemas and other scripts used to help gather them. Since the files are on GitHub you can use Datasette Lite to explore some of them - here are 16,185 GitHub repos the project is tracking as a CSV file loaded into Datasette Lite. Tags: open-source, ai, datasette-lite, generative-ai, local-llms, llms

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引用前请核对原文;本文由星际流动整理:https://feed.astralor.com/items/itm_4c8e751a878dcbfc29320add