The AI businesses run today sits on computers built around a logic very different from the human brain’s. The brain stores and processes information in the same place, works in parallel and uses very little energy; a conventional processor keeps those functions apart and constantly shuttles data between them. Neuromorphic computing aims to close that gap with hardware that handles information more like neurons do. Research involving the Norwegian University of Science and Technology (NTNU) points to tiny magnetic structures called skyrmions as a possible foundation. This article explains how the idea works, what has actually been demonstrated so far, and what it means for your business.
Why computers don’t process information like the brain
What holds back AI running on conventional hardware?
Almost every computer today follows the von Neumann architecture, which separates memory from the processing unit. Every operation moves data between the two, and that back-and-forth costs time and energy. The human brain works differently: the connections between neurons store and process information at the same time, and millions of them operate in parallel. For a CTO, that means AI models needing ever more servers and electricity for tasks the brain handles with minimal power.
What neuromorphic computing is and where skyrmions fit in
Neuromorphic computing is a hardware design approach that imitates how the human brain combines memory and processing in the same physical structure.
A skyrmion is a nanoscale magnetic structure, shaped like a tiny whirl, that can store information in a stable way. According to the researchers, skyrmion-based devices could lead to computers that resemble biological brains, running on magnetism instead of transistors and needing hardly any electricity.
What exactly have the researchers demonstrated?
A team at Johannes Gutenberg University Mainz, working with NTNU’s QuSpin centre, filmed for the first time in real time how an ordered skyrmion lattice loses its structure, while changing the shape and size of individual skyrmions as it happened. The study, published in Nature Nanotechnology, helps explain how these structures behave and how to control them, a prerequisite for building any device. This is fundamental research, and no commercial chip exists yet.
What brain-inspired hardware could change for businesses
How would a factory detect equipment faults with neuromorphic chips?
Consider a plant with hundreds of machines fitted with vibration and temperature sensors. Today, those signals are usually analyzed on a central server. With neuromorphic hardware, each sensor could learn its machine’s normal pattern locally and raise an alert only when something deviates, much as the brain filters out routine stimuli and focuses on what is unusual. The result would be faster detection, less data in transit and far lower energy use. The same logic applies to power grids, smart street lighting in cities and in-store cameras in retail.
What a CTO can do today
Do you need to wait for these chips to run more efficient AI?
No. These chips are still years from the market, but their core principle already points to sound design decisions: process data close to where it is generated, choose the smallest model that solves the problem, and track energy per inference alongside accuracy and response time. Companies that design their architecture this way cut cost and risk today and will be better placed to adopt brain-inspired hardware once it becomes viable.
In summary
Neuromorphic computing is a hardware approach that imitates the human brain by combining memory and processing in the same structure. Today’s computers separate those functions, which forces constant data movement and consumes a lot of energy. Skyrmions are nanoscale magnetic whirls that could serve as the building blocks of brain-like chips. Researchers in Mainz and at NTNU filmed a skyrmion lattice losing its order in real time for the first time, a key step toward controlling them. The technology is still at the research stage and has no commercial application yet.
At Qaleon, we build applied AI and advanced analytics solutions tailored to each problem, and we follow neuromorphic computing closely so we can adopt it once it delivers real business value. If you want to explore how this applies to your business, let’s talk.