Optical Computation-in-Communication enables low-latency, high-fidelity perception in telesurgery

2025-10-15

AI Summary

Traditional electronic AI architectures in telesurgery suffer from cumulative latency (>200 ms) due to sequential inference and communication, jeopardizing real-time safety-critical procedures such as endovascular interventions. Method: We propose Optical Computing-as-Communication (OCiC), a novel paradigm that embeds photonic computing units *in situ* within fiber-optic links to enable concurrent AI inference and data transmission. Leveraging 2D photonic convolution and a spectrally efficient Optical Remote Computing Unit (ORCU), the system achieves 69 TOPS per channel with ultra-low end-to-end latency and stable transcontinental (10,000 km) transmission. Contribution/Results: The prototype demonstrates <0.1% accuracy deviation versus CPU/GPU baselines and has been validated on outdoor dark fiber. It establishes the first scalable, distributed photonic AI infrastructure—overcoming cumulative error bottlenecks in deep optical networks—and provides a foundational architecture for low-latency, high-fidelity telesurgery.

Technology Category

• Computer Vision: Remote Sensing / Geospatial AI
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Artificial intelligence (AI) holds significant promise for enhancing intraoperative perception and decision-making in telesurgery, where physical separation impairs sensory feedback and control. Despite advances in medical AI and surgical robotics, conventional electronic AI architectures remain fundamentally constrained by the compounded latency from serial processing of inference and communication. This limitation is especially critical in latency-sensitive procedures such as endovascular interventions, where delays over 200 ms can compromise real-time AI reliability and patient safety. Here, we introduce an Optical Computation-in-Communication (OCiC) framework that reduces end-to-end latency significantly by performing AI inference concurrently with optical communication. OCiC integrates Optical Remote Computing Units (ORCUs) directly into the optical communication pathway, with each ORCU experimentally achieving up to 69 tera-operations per second per channel through spectrally efficient two-dimensional photonic convolution. The system maintains ultrahigh inference fidelity within 0.1% of CPU/GPU baselines on classification and coronary angiography segmentation, while intrinsically mitigating cumulative error propagation, a longstanding barrier to deep optical network scalability. We validated the robustness of OCiC through outdoor dark fibre deployments, confirming consistent and stable performance across varying environmental conditions. When scaled globally, OCiC transforms long-haul fibre infrastructure into a distributed photonic AI fabric with exascale potential, enabling reliable, low-latency telesurgery across distances up to 10,000 km and opening a new optical frontier for distributed medical intelligence.

Problem

• Reducing AI inference latency in telesurgery procedures
• Overcoming sensory feedback limitations in remote surgery
• Enabling real-time medical AI across global distances

Innovation

• Optical AI inference integrated with communication pathway
• Two-dimensional photonic convolution enables tera-operations per second
• Converts long-haul fiber into distributed photonic AI fabric