Optoelectronic Intelligence

TL;DR

This paper proposes a design for optoelectronic hardware for general intelligence, combining photonics and electronics to enable scalable, efficient neural systems inspired by neuroscience and VLSI principles.

Contribution

It introduces a comprehensive concept for optoelectronic neural hardware integrating photonics and electronics at wafer scale for large-scale intelligent systems.

Findings

Photonics enables high fan-out and low-latency communication.

Josephson circuits provide nonlinear, high-speed, low-power computation.

Operation at 4K allows efficient single-photon detection and silicon light sources.

Abstract

To design and construct hardware for general intelligence, we must consider principles of both neuroscience and very-large-scale integration. For large neural systems capable of general intelligence, the attributes of photonics for communication and electronics for computation are complementary and interdependent. Using light for communication enables high fan-out as well as low-latency signaling across large systems with no traffic-dependent bottlenecks. For computation, the inherent nonlinearities, high speed, and low power consumption of Josephson circuits are conducive to complex neural functions. Operation at 4\,K enables the use of single-photon detectors and silicon light sources, two features that lead to efficiency and economical scalability. Here I sketch a concept for optoelectronic hardware, beginning with synaptic circuits, continuing through wafer-scale integration, and extending to systems interconnected with fiber-optic white matter, potentially at the scale of the human brain and beyond.