News and Blogs

Event-Driven E-Skins Protect Both Robots and Humans
EE Times Current, 10 July 2025
Professor Gordon Cheng builds humanoid robots that can feel their environment using artificial skin. In this episode of Brains and Machines, he talks to Dr. Sunny Bains of University College London about how the skin was designed, how it improves safety, and why neuromorphic engineering will be important for machine autonomy. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University. Gordon Cheng in the lab at the Technical University of Munich with humanoid robot H1. Gordon Cheng in the lab at the Technical University of Munich with humanoid robot H1 (Source: Andreas Heddergott/Technical University of Munich)…

Memristors go mainstream: brain-inspired hardware could cut AI’s energy costs
ingenia, 12 July 2025
Professor Themis Prodromakis designs neuromorphic AI hardware that takes cues from the brain. Aside from slashing AI’s energy use, it could also make for smarter spacecraft and brain-computer interfaces. AI’s energy costs are skyrocketing. In April 2025, the International Energy Agency (IEA), which monitors the world’s energy use, forecasted that electricity demand from datacentres will double to…

Neuromorphic Now 2025: From Vision to Impact
University of Groningen, 2 July 2025
The Neuromorphic Now conference returned for its second edition on 13 June 2025, bringing together 110 researchers, innovators, and policymakers in Delft. Organised by TNO, CWI, TU Delft, and CogniGron, the event aimed to accelerate the neuromorphic computing innovation agenda. Building on the success of the inaugural 2024 meeting (co-organised by IMEC), this year’s edition focused…

How can AI be more energy efficient? UB researchers look to human brain for inspiration
EurekAlert!, 1 July 2025
BUFFALO, N.Y. — It’s estimated it can take an AI model over 6,000 joules of energy to generate a single text response. By comparison, your brain needs just 20 joules every second to keep you alive and cognitive. That’s why University at Buffalo researchers are taking inspiration from the human brain to develop computing architecture that can support the growing energy demands of artificial intelligence….

1,000x AI Efficiency? The Neuromorphic Chips That Could Slash Data Center Energy
Medium, 23 June 2025
Neuromorphic computing stands at the threshold of what could become one of the most transformative shifts in processing architecture since the birth of personal computing. By emulating the brain’s remarkable efficiency, neuromorphic systems offer a vision of AI processing that consumes vastly less power while unlocking new capabilities in real-time, adaptive decision-making….

Low-energy robot navigation mimics neural processes
THE ENGINEER, 23 June 2025
Developed at Queensland University of Technology (QUT), LENS (Locational Encoding with Neuromorphic Systems) uses brain-inspired computing to set a new, low-energy benchmark for robotic place recognition. The breakthrough is detailed in Science Robotics. The research, conducted by first author neuroscientist Dr Adam Hines along with Professor Michael Milford and Dr Tobias Fischer, all from the QUT Centre of Robotics and the QUT School of Electrical Engineering and Robotics, uses neuromorphic computing…

The Future of Neuromorphic Computing
Medium, 20 June 2025
Neuromorphic computing, a revolutionary approach to designing computer architectures inspired by the human brain’s neural structures, stands on the brink of transforming modern computing as we know it. By mimicking the brain’s massively parallel, event-driven, and energy-efficient processes, neuromorphic systems promise to break the limitations of traditional von Neumann architectures — particularly in an era where Moore’s Law is slowing down and the demand for smarte…

Seeing through a new LENS allows brain-like navigation in robots
EurekAlert!, 18 June 2025
QUT robotics researchers have developed a new robot navigation system that mimics neural processes of the human brain and uses less than 10 per cent of the energy required by traditional systems. In a study published in the journal Science Robotics, the researchers detail a new system which they call LENS – Locational Encoding with Neuromorphic Systems. LENS uses brain-inspired computing to set a new, low-energy benchmark for robotic place recognition. The research, conducted by first…

Low-power memristor for neuromorphic computing: From materials to applications
EurekAlert!, 11 June 2025
As the demand for artificial intelligence continues to grow, the limitations of traditional von Neumann architecture in terms of energy efficiency and processing speed become more pronounced. Now, researchers from the School of Integrated Circuits at Shandong University, led by Professor Jialin Meng and Professor Tianyu Wang, have presented a comprehensive review on low-power memristors…

Digital Prototypes May Enable Analog Neuromorphic Chips
EE Times Current, 7 June 2025
Dr. Charlotte Frenkel from the Technical University of Delft set records with a low-power neuromorphic chip she designed as part of her Ph.D. In this episode of Brains and Machines, she talks to Dr. Sunny Bains of University College London about what she has learned about building simplicity…

Ultrafast Neuromorphic Computing Driven by Polariton Nonlinearities
newswise, 6 June 2025
Newswise — Neuromorphic computing, inspired by the human brain, is considered as the next-generation paradigm for artificial intelligence (AI), offering dramatically increased speed and lower energy consumption. While software-based artificial neural networks (ANNs) have made remarkable strides, unlocking their full potential calls for physical platforms that combine ultrafast operation…