A two-chip photonic neuromorphic system performs real time spiking reinforcement learning using only light, achieving GPU-class energy efficiency.

Innatera and Byte Lab partner to speed up the development and industrialisation of neuromorphic edge AI systems.

Innatera adopts Synopsys simulation technology to help design neuromorphic chips that enable low-power AI for wearables, smart home devices, and digital twin industrial sensors. K ...

Brain-inspired computing promises cheaper, faster, more energy efficient processing, according to experts at a Beijing conference, who discussed everything from reverse engineering insect brains to ...

Inspired by human brain, neuromorphic computing technologies have made important breakthroughs in recent years as alternatives to overcome the power and latency shortfalls of traditional digital ...

Scientists demonstrate neuromorphic computing utilizing perovskite microcavity exciton polaritons operating at room temperature. (Nanowerk News) Neuromorphic computing, inspired by the human brain, is ...

Innatera announced that it has selected Synopsys simulation technology to help design neuromorphic chips that enable low-power AI for wearables, smart home devices, and digital twin industrial sensors ...

Physicists and chemists at Heidelberg University have realized a photonic microchip that is driven by light just as easily as ...

Our latest and most advanced technologies — from AI to Industrial IoT, advanced robotics, and self-driving cars — share serious problems: massive energy consumption, limited on-edge capabilities, ...

An international team comprised of 23 researchers has published a review article on the future of neuromorphic computing that examines the state of neuromorphic technology and presents a strategy for ...

Covering developments in neuromorphic computing has been something of a piecemeal experience, as happens with all novel architectures. There are few companies with scalable devices and the research is ...

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