Research news on Neuromorphic AI hardware

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.

Machine learning & AI

How artificial neural networks build their own learning machinery

As artificial intelligence becomes more powerful, its ability to handle humanlike tasks is undeniable. Artificial neural networks can learn to recognize images, use language or write computer code. Like the brain's circuits, ...

Security

Anthropic warns of AI 'worms' spreading across smart gadgets

Small artificial intelligence models may be only months away from being able to behave like a computer worm, copying themselves from one internet-connected gadget to the next without human help, Anthropic said.

Hardware

Microsoft bets on homegrown AI chip to challenge Nvidia

Microsoft said Monday it will roll out its in-house Maia artificial intelligence chips on a massive scale starting in 2027, making them the main hardware for running AI across its products—a move that could reduce its reliance ...

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