
A new photonic chip achieves image processing at 25 million frames per second with high energy efficiency, promising major advances in real-time imaging and AI applications.
Key Details
- 1Vertically integrated photonic chip ('Gezhi') processes 25 million frames per second.
- 2Uses a mutually incoherent VCSEL array and diffractive neural network (DNN) for computation.
- 3Achieved 98.6% accuracy on MNIST image classification benchmark.
- 4Consumes only 3.52 aJ/μm² of optical energy per frame, outperforming electronic accelerators.
- 5Capable of versatile tasks like edge extraction and denoising.
- 6Can be scaled to larger distributed optical computing with tens of thousands of units.
Why It Matters

Source
EurekAlert
Related News

Deep Learning AI Outperforms Clinic Prognostics for Colorectal Cancer Recurrence
A new deep learning model using histopathology images identifies recurrence risk in stage II colorectal cancer more effectively than standard clinical predictors.

AI Reveals Key Health System Levers for Cancer Outcomes Globally
AI-based analysis identifies the most impactful policy and resource factors for improving cancer survival across 185 countries.

Dual-Branch Graph Attention Network Predicts ECT Success in Teen Depression
Researchers developed a dual-branch graph attention network that uses structural and functional MRI data to accurately predict individual responses to electroconvulsive therapy in adolescents with major depressive disorder.