Educational enterprise · Free & open source

Making the benefits of AI
broadly shared

ANTICARBON is an educational enterprise. We build free, open-source tools and open data so the benefits of artificial intelligence reach as many people as possible — through education.

🌍 Open knowledge  ·  MIT licensed  ·  Free forever

Intelligence is only worth building if everyone can share in it

Artificial intelligence is reshaping how we understand the world — but its benefits are far from evenly distributed. We exist to close that gap. By making powerful tools and trustworthy data free, open, and easy to learn from, we help the widest possible community put AI to work for themselves.

Open by default

Every tool we make is open source and openly licensed. No lock-in, no black boxes — inspect it, fork it, improve it, make it yours.

Education first

We build to teach. Clear tools and honest data help people learn how AI works and how to use it well — not just consume its outputs.

Free forever

Access should never be gated by ability to pay. Our public tools are free to use, free to study, and free to build upon.

What we're building

Small, sharp, open tools — each one designed to make something that was once expensive or opaque into something anyone can learn from.

● Live MIT · Open source
ManticView
Prediction markets, in your spreadsheet

ManticView brings live Manifold prediction-market data straight into Google Sheets. Custom =MANIFOLD functions pull probabilities, market searches, answer tables, portfolios and price history — no account or API key required — plus an Android home-screen widget for at-a-glance markets. Wholly free and open source.

In development MIT fork
Sirius
Open data on AI & education

A fork of the last MIT-licensed release of Our World in Data's Grapher, curated down to the visualizations that matter most for understanding artificial intelligence and education. Open data, open code, forever free — a small window onto the numbers behind our mission.

The data that matters, openly

A first, curated selection from Sirius: the long rise of human education, and the sudden acceleration of artificial intelligence. Together they frame the question we exist to answer — how do the benefits of AI reach everyone? Hover any point for detail.

Education

The long rise of world literacy

Share of the world's population able to read and write, 1820–2020

0% 25% 50% 75% 100% 12% 87% 1820 1900 1950 1990 2020
Source: Our World in Data — literacy (UNESCO; van Zanden et al.). Selected years; figures approximate.
Education

A century of schooling

Mean years of schooling, world average, 1870–2020

0 2 4 6 8 10 0.5 1.0 2.9 4.8 7.2 8.7 1870 1900 1950 1980 2000 2020
Source: Our World in Data — mean years of schooling (Lee & Lee; Barro & Lee; UNDP). Selected years; figures approximate.
Artificial intelligence

Compute behind notable AI

Estimated training compute of landmark AI systems (FLOP, log scale)

10¹⁶ 10¹⁸ 10²⁰ 10²² 10²⁴ 10²⁶ AlexNet GPT-2 GPT-3 PaLM GPT-4 2012 2020 2023
Source: Our World in Data & Epoch AI — training compute of notable systems. Log scale; landmark models; estimates approximate.
Artificial intelligence

Who builds the frontier

Industry's share of notable AI systems, 2010–2022

0% 25% 50% 75% 100% 38% 90% academia / industry parity 2010 2014 2018 2022
Source: Our World in Data & Epoch AI; AI Index — notable AI systems by sector. Selected years; shares approximate.
Open the Sirius explorer
Data drawn from Our World in Data and Epoch AI, used under a Creative Commons BY licence. Sirius is a fork of the last MIT-licensed release of the Our World in Data Grapher (commit 0f4f86b, before it moved to a proprietary licence on 12 May 2026). Charts above show selected landmark years and are simplified for clarity — always cite the original sources for research.

Everything we make is free and open

Openness is not a feature we add at the end — it is the point. When tools and data are free to inspect, copy, and improve, knowledge compounds and reaches people no paywall ever would. That is how the benefits of AI become broadly shared.

"If it can't be studied, forked, and taught, it can't truly belong to everyone."

  • Permissively licensed — MIT, free to use and build upon
  • Source public on GitHub, open to contribution
  • No accounts, paywalls, or lock-in on public tools
  • Data openly attributed to its original creators
  • Built to be read and learned from, not just run
  • Forks and remixes actively encouraged