---
title: "Open Source AI Gap Map: A Global Partnership Building a Public Option for AI"
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","Open Source","Open Source AI Gap Map"]
---

# Open Source AI Gap Map: A Global Partnership Building a Public Option for AI

## At a glance

Current AI is a non-profit founded at the AI Action Summit in Paris in February 2025, backed by $400 million in committed capital. Its Gap Map v0.1 deeply indexes 421 open-source AI products: 266 software tools and libraries, 85 models, 50 datasets, and 20 hardware projects from 228 organizations. Products are organized into 14 categories across three stack layers (model components, product/UX, and infrastructure). The remaining 24,400 artifacts form the uncategorized long tail. The underlying data is MIT-licensed on GitHub, including 1,184 YAML files and scripts, explorable via Datasette Lite.

## Key points

- Gap Map v0.1 catalogs 421 open-source AI products including models, tools, datasets, and hardware.
- Operated by non-profit Current AI with $400M committed capital.
- Underlying data open-sourced under MIT license with 1,184 YAML files, explorable via Datasette Lite.
- Remaining 24,400 unstudied artifacts carry no score until researched and cited.

## Full text

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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