Known for their energy efficiency, LEDs are also opening up completely new possibilities for applications beyond lighting. By using a neuron network of microscopic LEDs for the AI of tomorrow, a research group at Technische Universität Braunschweig (TU Braunschweig)’s Nitride Technology Centre (NTC) aims to make future computers more powerful and energy efficient. Miniaturization, scalability, and energy efficiency are crucial for the development of more powerful hardware for AI applications. The NTC research group at TU Braunschweig, along with collaborators from Ostfalia University of Applied Sciences and ams OSRAM, are taking a different approach to building computers using microLED technology. The researchers are miniaturizing and scaling the energy-efficient microLEDs in a way that makes a neuromorphic computer possible. “Our optical neuromorphic computing mimics the functioning of biological neural networks, such as those in the human brain, by using electronic circuits or photonic components,” said professor Andreas Waag from the Institute of Semiconductor Technology at TU Braunschweig. Professor Andreas Waag of TU Braunschweig and professor Christian Werner of Ostfalia University of Applied Sciences at the demonstrator for an LED-based neuromorphic computer. Courtesy of TU Braunschweig/Laurenz Kötter. “This avoids the weaknesses of conventional digital computer technology, which lead to immense energy demands in massively parallel information processing for AI applications,” said professor Christian Werner from Ostfalia University of Applied Sciences. It is expected that in 10 years, approximately a third of the world’s electrical energy will be used for supercomputers and their cooling. Gallium nitride (GaN) is the semiconductor of choice for microLED technology. This semiconductor is increasingly used in power electronics because it offers higher power density and better efficiency than traditional silicon semiconductors. However, unlike silicon, GaN is optically active, making it the basic building block for blue LEDs. The Nitride Technology Centre (NTC) at TU Braunschweig is driving the development of nitride semiconductor technology as the second pillar of microelectronics. The researchers are combining GaN components with conventional silicon microelectronics to open up completely new fields of application – such as highly integrated arrays with hundreds of thousands of microLEDs, which are also being used in the QuantumFrontiers cluster of excellence and in the Quantum Valley Lower Saxony. “The special properties of gallium nitride are ideal for microLEDs with dimensions of one micrometer and smaller,” said Waag. The research group also sees great potential in GaN-based microLED technology for reducing the power consumption caused by AI systems by a factor of 10,000. The microLEDs perform the task that would otherwise be performed by silicon transistors. Parallel in-memory processing combined with efficient photon production and detection creates a hardware that physically maps the different levels of neural networks and enables parallel information flow. Much research is needed before an “artificial brain” based on this technology can become a reality, but it promises enormous energy savings, the researchers said. The NTC research group has already developed a macroscopic optical microLED demonstrator with 1000 neurons. The demonstrator has already passed a standard AI pattern recognition test: it identifies numbers from zero to nine written in a jumbled fashion, some of which are difficult for a human to decipher. The research was published in the Journal of Physics Photonics (www.doi.org/10.1088/2515-7647/ad8615).