(Frankfurt a. M., 01.11.2024) Due to increasing digitalization, energy requirements are increasing – with corresponding consequences for our climate. Generative artificial intelligence (AI) in particular is anything but green. This is because processing the huge amounts of data requires computing power that causes energy consumption to skyrocket, both when training AI models and during operation. Neuromorphic computing (NMC) is intended to provide a remedy here. The concept: computers that are based on the principles of biological neuronal systems and therefore function in a comparably energy-efficient manner. Although there are currently many research approaches, there is a lack of standardization. This hinders the transfer from research to practice. In order to change this, experts from academia and industry from various disciplines have developed a VDE SPEC. Their aim: to bring innovations and technologies from the field of electrical engineering and information technology to the market more quickly in times of rapid technical progress.
Overcoming boundaries: Computing power with brains
“From nature to theory to practice – and then onto the shop shelf as quickly as possible. This is our vision for neuromorphic computing,” says Dr. Damian Dudek, Managing Director of the VDE Information Technology Society (VDE ITG). He emphasizes: “Completely new technologies are needed, as today's computers are gradually reaching their limits, especially when it comes to applications of generative AI.”
The problem: in conventional computer systems, computing and storage units are separate (so-called von Neumann architecture). The resulting need to exchange data between processor and memory costs energy and time.
In order to change this and develop the next generation of computers, researchers are looking to the human brain, for example. The reason: neurons in the brain can process and store signals locally. Due to the parallelism of data processing that this enables, the brain manages with a tiny fraction of the energy that today's AI systems consume. Information processing in other biological neuronal systems in nature is similar.