On November 25, Technische Universität Braunschweig (TU Braunschweig) announced that a research team from the university’s Nitride Technology Center (NTC) is leveraging Micro LED technology to construct AI neural networks. The goal is to develop more powerful and energy-efficient computer systems for the future of artificial intelligence.
Miniaturization, Scalability, and Energy Efficiency as Key Factors for AI Development
The miniaturization, scalability, and energy efficiency of hardware are essential for developing more advanced AI applications. The NTC research team at TU Braunschweig is exploring a novel approach to building computing systems using Micro LED technology. By miniaturizing and expanding the applications of Micro LED, the team aims to create neural network-based computers.
Results Published in the Journal of Physics Photonics
The research findings, published in the Journal of Physics Photonics, are a collaboration between TU Braunschweig, Osnabrück University of Applied Sciences, and ams OSRAM. The paper explains how this innovative computing system could elevate AI applications to new levels.
Optical Neuromorphic Computing Mimicking the Human Brain
The team highlighted that optical neuromorphic computing mimics the functioning of biological neural networks, such as the human brain, using electronic circuits or photonic components. This method circumvents the massive energy demands of traditional computing technologies in AI applications. It is predicted that, as AI technology advances, approximately one-third of global electricity will be consumed by supercomputers and their cooling systems over the next decade.
GaN-Based Micro LEDs Reduce AI System Energy Consumption
By combining GaN-based components with traditional silicon microelectronics, the research team created a highly integrated array of Micro LEDs consisting of hundreds of thousands of individual units. GaN-based Micro LED technology has significant potential to reduce the enormous energy consumption associated with AI systems, with a potential energy savings of up to 10,000 times.
Parallel Memory Processing and Efficient Photonic Production
These Micro LEDs can perform tasks typically handled by silicon transistors, integrating parallel memory processing with efficient photon production and detection. This setup creates hardware capable of physically mapping the different layers of a neural network and facilitating parallel information flow.
Early Stages of Research and First Demonstration
While still in the early stages of research, the NTC team has already developed a macroscopic optical Micro LED demonstration device containing 1,000 neurons. The device has passed standard AI pattern recognition tests, successfully identifying digit content written in a disordered manner.
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