A neural network is a machine learning model originally inspired by how the human brain works (Courtesy: Shutterstock/Jackie Niam) Precision measurements of theoretical parameters are a core element ...

The application of neural network models to semiconductor device simulation has emerged as a transformative approach in the field of electronics. These models offer significant speed improvements over ...

Biology-inspired, silicon-based computing may boost AI efficiency; AMP2 instead uses AI to accelerate anaerobic biology.

The shift from slow, manual simulation to fast, automated optimisation using deep learning is unlocking better designs and faster time to market, says Jacomo Corbo, CEO and Co-Founder of PhysicsX.

As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...

Neural Concept aims to accelerate these timelines by integrating AI directly into CAD and physics-based simulation ...

Researchers propose a synergistic computational imaging framework that provides wide-field, subpixel resolution imaging without added optical complexity via a metalens-transformer design. They ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...