Neuromorphic AI hardware encompasses brain-inspired computing systems that implement neural network primitives directly in physical substrates to achieve extreme energy efficiency and low latency. Architectures use devices such as memristors, magnetic tunnel junctions, electrochemical memories, photonic and microwave components, and organic or superconducting neurons to realize synapses, neurons, and compute-in-memory operations. These platforms support spiking and analog neural computation, on-chip learning, and specialized sensory and cognitive functions, targeting applications from edge intelligence and autonomous systems to large-scale AI acceleration and brain–computer interfaces.
Energy & Green Tech
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.
Jul 1, 2025
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114
Hardware
Artificial intelligence is considered to be computationally and energy-intensive—a challenge for the Internet of Things (IoT), where small, embedded sensors have to make do with limited computing power, little memory and ...
Jun 26, 2025
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51
Electronics & Semiconductors
In recent decades, computer scientists have been developing increasingly advanced machine learning techniques that can learn to predict specific patterns or effectively complete tasks by analyzing large amounts of data. Yet ...
Hardware
BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at the Institute of Science Tokyo, ...
Jun 23, 2025
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48
Hardware
A novel power supply technology for 3D-integrated chips has been developed by employing a three-dimensionally stacked computing architecture consisting of processing units placed directly above stacks of dynamic random access ...
Jun 20, 2025
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142
Robotics
Robots are increasingly becoming a part of our lives—from warehouse automation to robotic vacuum cleaners. And just like humans, robots need to know where they are to reliably navigate from A to B.
Jun 19, 2025
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27
Hardware
Researchers at the University of Massachusetts Amherst have pushed forward the development of computer vision with new, silicon-based hardware that can both capture and process visual data in the analog domain. Their work, ...
Jun 18, 2025
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107
Robotics
QUT robotics researchers have developed a new robot navigation system that mimics the neural processes of the human brain and uses less than 10% of the energy required by traditional systems.
Jun 18, 2025
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111
Hardware
The promise of a new type of computer chip that could reshape the future of artificial intelligence and be more environmentally friendly is explored in a technology review paper published by UC Riverside engineers in the ...
Jun 17, 2025
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93
Machine learning & AI
The ability to precisely predict movements is essential not only for humans and animals, but also for many AI applications—from autonomous driving to robotics. Researchers at the Technical University of Munich (TUM) have ...
Jun 12, 2025
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