A working mental model
See how intelligence, priors, induction, adaptation, search, and world models fit together.
An interactive web book
Trace the papers, ideas, solvers, benchmarks, and open questions shaping the search for general intelligence.
24key works
13 + 9chapters + appendices
3reading depths
2019–2026the ARC era
Alpha edition
Tell us what helps, what remains unclear, and what is missing.
ARC-AGI was designed to test whether a system can learn a new skill from only a few examples.
This book follows that question from the 2019 benchmark through ARC-AGI-2 and into the interactive worlds of ARC-AGI-3.
The question is not how much a system knows. It is how efficiently it can learn something new.
Every work is connected to the ideas it inherits, the methods it enables, and the benchmarks it changes.
See how intelligence, priors, induction, adaptation, search, and world models fit together.
Read the original works with scores, claims, limits, and canonical links close at hand.
See how each solver family works and where it breaks down.
Know what is settled, what is contested, and where the frontier is still genuinely open.
The complete book
Reference layer
Canonical indexes sit outside the numbered argument, but remain one click away from every chapter.
Get the central claim in one sentence.
Understand the method, result, and significance.
Follow the full argument, evidence, and limitations.