Source-backed maps of the AI field
Eight interactive references — foundations, papers, manufacture, application, biology, terminology, and two learning systems. Designed to be audited and updated over time.
Foundations
AI Map
Five-layer taxonomy of AI techniques and concepts. The starting point: how the field decomposes into models, data, training, deployment, and applications.
AI Atlas
Interactive knowledge graph of the 50 most important AI / ML papers. Trace dependencies, follow guided learning paths, see how the modern stack accumulated.
Manufacture & application
Accelerated Computing Atlas
How AI is physically built — power, chips, TSMC, HBM, NVIDIA, cloud and data centres. 148 nodes across 11 layers, 73 companies, 79 source-backed Q&As.
Applied AI Atlas
Where AI enters the world. 52 domains across biology, medicine, finance, law, robotics, and science — with architectures, papers, bottlenecks, and 126 elite questions.
Biology & reference
Biological Intelligence Atlas
What biology teaches us about intelligence — swarms, stigmergy, slime moulds, immune systems, embodiment, basal cognition, evolutionary search. Eight deep dives, eight design patterns.
The AI Field Manual
Every important AI term, explained from first principles. A living reference layer organised by stack: hardware, models, inference, agents, safety, benchmarks, economics, society.
Learning systems
AI Questions Canon
A structured map of the questions that define artificial intelligence — from beginner foundations to frontier models, safety, jobs, geopolitics, and energy.
AI Knowledge Bank
Russell & Norvig structured into a living mastery system — 7 phases, 28 domains, 220+ questions, flashcards, quizzes, plus interview / founder / researcher modes.