Photonics-Electronics Co-Designed AI Computing Chips for Edge Intelligence
IntelligenceLight in. Intelligence out.
Photonics-Electronics Co-Designed AI Computing Chips for Edge Intelligence
IntelligenceLight in. Intelligence out.
IntelligenceLight in. Intelligence out.
IntelligenceLight in. Intelligence out.
At Nanon, we are pioneering the photonics-electronics co-design era for edge intelligence, where real-time computing is faster and more efficient, closer to the physical limits of speed and energy.
Our mission is to unlock new possibilities in how information is processed, and acted upon by seamlessly integrating the edges of both photonics and electronics. We aim to break through the traditional bottlenecks of conventional computing, creating systems that power the next generation of intelligent machines and connected environments.
At Nanon, we believe that rethinking the foundation of computing will drive the next leap in technology, industry, and society.
Accelerating the core AV/EV vision tasks like object detection, semantic segmentation, lane recognition, and motion tracking. This enables faster perception loops, supports higher-resolution models, and reduces compute strain across the vehicle’s autonomy stack.
Giving industrial robots faster visual perception for real-time tasks like defect detection, part localization, bin picking, and dynamic path planning. This enables quicker visual feedback loops, reduces cycle time, and improves safety and precision on the factory floor.
Enabling industrial drones to perform true real-time inspection, mapping, and monitoring with faster visual processing. This supports fast obstacle avoidance, dynamic path tracking, precision landing, swarm coordination, and stable navigation in GPS-denied environments—crucial for missions in complex, cluttered, or hazardous environments—all while reducing onboard power consumption for longer flight endurance.
Enhancing autonomous defense systems by enabling real-time visual processing for target recognition, threat detection, and navigation in contested or GPS-denied environments. This supports faster reaction times in edge-deployed drones, robots, and surveillance platforms—critical for low-latency decision-making in high-risk, dynamic missions.
Enabling AR/VR headsets to process visual data with ultra-low latency, significantly reducing motion delay and enabling faster hand and head tracking. This helps eliminate motion sickness, improves user immersion, and supports high-resolution rendering with lower power consumption, crucial for lightweight, untethered headsets.
Giving embodied intelligence systems—like autonomous robots, quadrupeds, and human-assistive machines—the ability to process visual input and react in real time. This enables fast perception-to-action loops for tasks like balance control, obstacle avoidance, object manipulation, and human interaction. This is critical for dynamic environments where delayed responses can lead to instability, failure, or safety risks.
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