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INAIR, 28 January 2026
The relentless march of artificial intelligence is not just a story of algorithms and code; it is fundamentally a tale of silicon, electrons, and breathtakingly innovative hardware. Every breakthrough in machine learning, every generative AI model that captivates the world, and every autonomous system that navigates our reality is underpinned by physical computing power. Keeping pace with AI hardware news today is to witness the very foundation of our technological future being laid, brick by intricate brick. The developments are not merely…
Roboblog, 20 January 2026
2026 is the year neuromorphic chips go mainstream in robotics. Intel's Loihi 3, IBM's NorthPole, and BrainChip's Akida 2.0 deliver brain-inspired computing that consumes 1/1000th the power of GPUs while processing sensory data 100x faster. Robots with neuromorphic brains react in microseconds, learn continuously without forgetting, and run for weeks on battery power. The age of energy-efficient, real-time robot intelligence has arrived. Unlike traditional Von Neumann architectures that shuttle data between separate…
ScienceDaily, 3 January 2026
Scientists have developed molecular devices that can switch roles, behaving as memory, logic, or learning elements within the same structure. The breakthrough comes from precise chemical design that lets electrons and ions reorganize dynamically. Unlike conventional electronics, these devices do not just imitate intelligence but physically encode it. This approach could reshape how future AI hardware is built….
EDGEIR.com, 15 December 2025
BrainChip raised $25 million to fast track development and commercialization of its neuromorphic AI technology products, including Akida 2 and Akida GenAI. It will support the growth of BrainChip’s product offering and according to Grand View Research, the global neuromorphic computing market is expected to grow to more than $20 billion by 2030 globally. “Our capital raise positions BrainChip to furthe…
EE Times Current, 8 December 2025
Professor Chris Eliasmith is a computer scientist and philosopher who’s been modelling cognitive systems for almost three decades. In this episode of Brains and Machines, he talks to Dr. Sunny Bains of University College London about his neural engineering framework and the semantic pointer architecture his team have developed to implement it. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University….
newelectronics, 5 December 2025
Neuromorphic computing specialist Innatera has joined forces with UK-based innovation consultancy 42 Technology (42T) to accelerate the adoption of brain-inspired processors in industrial and consumer applications. The collaboration aims to deliver ultra-low-power artificial intelligence at the sensor edge, enabling smarter, more responsive products. The partnership will combine Innatera’s…
EE Times EUROPE, 26 November 2025
As quantum and analog neuromorphic systems move closer to commercialization, new architectures continue to expand the definition of what computing can be. “Usually, at CEA-Leti, research teams plan five years ahead, but in this case, it’s more like 10 years,” Éléonore Hardy, silicon photonics partnership manager at CEA-Leti, told EE Times Europe at the Silicon Photonics Workshop co-organized by CEA-Leti…
Electronic Engineering Journal, 20 November 2025
We live in exciting times with respect to AI and the devices used to implement inferencing at the edge, where the “internet rubber” meets the “real-world road,” as it were. It reminds me of those distant days in the 1970s when we were all “feeling our way” with 8-bit microprocessors. I’m thinking of devices like the Intel 8008 (1972), Intel 8080 (1974), Motorola 6800 (1974), MOS Technology 6502 (1975),…
EE Times Current, 7 November 2025
Dr. Claudia Lenk’s group creates brain-inspired hearing systems with micromechanical hair cells. In this episode of Brains and Machines, she talks to Dr. Sunny Bains of University College London about the advantages of the approach and how it could be applied to speech processing in AI. Discussion follows with Dr. Giulia D’Angelo from the Czech Technical University in Prague and Professor Ralph Etienne-Cummings of Johns Hopkins University….
SciTechDaily, 2 November 2025
A breakthrough in neuromorphic computing could lower the energy consumption of chips and accelerate progress toward artificial general intelligence (AGI). Researchers from the USC Viterbi School of Engineering and the School of Advanced Computing have created artificial neurons that closely mimic the complex electrochemical behavior of real brain cells. Their breakthrough,…
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