Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and IoT through spiking neural networks and next-gen processors. Pixabay, ...

A December 10–12 working group met to bring together researchers from two fields — neuromorphic computing and stochastic thermodynamics — to think about ways our built computers might replicate the ...

Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex mathematical problems that underpin scientific and engineering challenges.

• Overcoming CMOS Bottlenecks: As AI workloads surge, conventional architectures suffer from >100 pJ per MAC and millisecond latency due to sensor-memory-processor separation. MXene-Ti 3 C 2 T x ...

A new technical paper titled “Solving sparse finite element problems on neuromorphic hardware” was published by researchers at Sandia National Lab. Abstract “The finite element method (FEM) is one of ...

A human’s way of processing information can be used as a model to train next-generation artificial intelligence (AI) systems, according to research published Jan. 22 in Nature. Cory Merkel, an ...

Analysts project the global neuromorphic computing market to skyrocket – from roughly $7.5 billion in 2024 to nearly $59 billion by 2033. This explosive forecast set the stage for an unexpected ...

The field of computing is constantly evolving, providing numerous opportunities for startups to innovate and disrupt existing markets. This is more visible now than ever with Nvidia becoming the most ...

Comprehensive overview of high-entropy oxides (HEOs) in memristive devices, emphasizing their potential in neuromorphic computing and their ability to simulate synaptic plasticity and multilevel ...

BUFFALO, N.Y. — 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 ...