The Gap
GPUs are extraordinary at training and high-throughput batch inference. They are structurally limited at three things: latency floors below one millisecond, deployment outside climate-controlled facilities, and physical-system workloads where the inference loop has to close in real time.
The next decade of machine learning deployment runs into all three.
The Approach
Pleco's processor uses photonic computation — light moving through configurable optical paths — to deliver inference latencies and deployment profiles that are physically unavailable to electronic accelerators.
The architecture is validated across the full target workload set in simulation. The first hardware prototype is in build.
State of Work
Roadmap
Contact
Interested in photonic compute for inference, edge deployment, or physical-system control? Get in touch.
Contact → hello@pleco.dev