Emergent Computation

For six decades, the dominant model of computation has been fundamentally instructional — processors executing discrete, deterministic sequences of commands encoded into silicon transistors. While this paradigm has produced extraordinary technological progress, it now faces hard physical limits at the nanoscale and deep architectural mismatches with the complexity of problems modern civilization demands it solve. This paper introduces Emergent Computing — a paradigm founded on a simple but profound principle: computation from interaction. Rather than executing discrete instruction sequences, computation arises from the collective behavior of engineered nanorobotic particles governed by defined properties and interaction laws. We argue that this paradigm is not invented but recognized: physical reality itself has computed through emergence since the origin of the universe, producing galaxies, chemistry, life, and consciousness from nothing but particles following local rules. Drawing on a scientific lineage spanning cellular automata, swarm intelligence, particle dynamics, and biological self-organization, we characterize the nanorobotic compute particle as the fundamental unit of emergent computation, introduce the principle of Physics Processing — in which the computational substrate shares the physical character of the workload — and articulate the concept of directed emergence: the systematic design of particle properties and interaction laws to produce intentional, reproducible computational outcomes. We survey the implications of this paradigm across artificial intelligence, complex systems modeling, molecular simulation, climate science, astrophysics, robotics, drug discovery, cryptography, neuroscience, and distributed infrastructure.