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 ...

Computers have come so far in terms of their power and potential, rivaling and even eclipsing human brains in their ability to store and crunch data, make predictions and communicate. But there is one ...

Rapid development of artificial intelligence requires the implementation of hardware systems with bioinspired parallel ...

A technical paper titled “3D Neuromorphic Hardware with Single Thin-Film Transistor Synapses Over Single Thin-Body Transistor Neurons by Monolithic Vertical Integration” was published by researchers ...

Neuromorphic computing, inspired by the brain, integrates memory and processing to drastically reduce power consumption compared to traditional CPUs and GPUs, making AI at the network edge more ...

Researchers demonstrate that a single transistor can mimic neural and synaptic behaviors, bringing brain-inspired computing closer to reality. (Nanowerk News) Researchers from the National University ...

(Nanowerk News) A research team consisting of NIMS and the Tokyo University of Science has developed the fastest electric double layer transistor using a highly ion conductive ceramic thin film and a ...

TL;DR: Scientists at the National University of Singapore have developed a silicon transistor that mimics biological neurons and synapses, offering a scalable and energy-efficient solution for ...

An integrated spiking artificial neuron, with rich neuron functionality, single-transistor footprints, and low energy consumption for neuromorphic computing systems, can be created by stacking one ...

The growing energy use of AI has gotten a lot of people working on ways to make it less power hungry. One option is to develop processors that are a better match to the sort of computational needs of ...

Although today’s computers can perform superhuman feats, even the best are no match for human brains at tasks like processing speech. But as Jessamyn Fairfield explains, a new generation of ...