Paradigm-Specific Intelligence Maps
How each AI paradigm becomes intelligence
Each map shows the emergence path for a specific paradigm: substrate, signal encoding, representation, learning, architecture, weak point, innovation zone, AGI contribution, and ASI pressure.
Electronic AI
Electronic AI turns digital scale, software tooling, memory, and datacenter economics into the current dominant path toward AGI.
Photonic / Light AI
Photonic AI uses light for bandwidth, low-latency communication, and fast linear operations, most plausibly as a hybrid accelerator.
Neuromorphic AI
Neuromorphic AI turns sparse spikes, locality, and event-driven computation into low-power adaptive intelligence.
Quantum AI
Quantum AI may matter where amplitude dynamics, sampling, chemistry, optimization, or quantum simulation give real advantage.
Evolutionary AI
Evolutionary AI becomes AGI-relevant when its substrate advantage strengthens representation, learning, agency, scalability, or safety better than the digital baseline.
Collective Intelligence
Collective Intelligence becomes AGI-relevant when its substrate advantage strengthens representation, learning, agency, scalability, or safety better than the digital baseline.
Embodied Robotics AI
Embodied Robotics AI grounds intelligence through perception, action, world models, affordances, and physical feedback.
Brain-Computer Interface AI
Brain-Computer Interface AI becomes AGI-relevant when its substrate advantage strengthens representation, learning, agency, scalability, or safety better than the digital baseline.
Analog Computing AI
Analog Computing AI becomes AGI-relevant when its substrate advantage strengthens representation, learning, agency, scalability, or safety better than the digital baseline.
Physics-Native Intelligence
Physics-Native Intelligence becomes AGI-relevant when its substrate advantage strengthens representation, learning, agency, scalability, or safety better than the digital baseline.
Synthetic Biological Intelligence
Synthetic Biological Intelligence becomes AGI-relevant when its substrate advantage strengthens representation, learning, agency, scalability, or safety better than the digital baseline.
Recursive Self-Improving AI
Recursive self-improving AI is the transition from static models to systems that improve their own tools, memory, code, evaluations, and architecture.
Multi-Agent Intelligence Systems
Multi-Agent Intelligence Systems becomes AGI-relevant when its substrate advantage strengthens representation, learning, agency, scalability, or safety better than the digital baseline.
Swarm Intelligence
Swarm Intelligence becomes AGI-relevant when its substrate advantage strengthens representation, learning, agency, scalability, or safety better than the digital baseline.
Hybrid Intelligence Systems
Hybrid Intelligence Systems are the likely practical AGI path: route tasks to the substrate, agent, human, or tool best suited to each bottleneck.
Maths AI
Maths AI emerges as a self-evolving local cognitive civilization: agents mutate reasoning strategies, but proof, code, simulation, and benchmark reality gates decide what survives.