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

Researchers at the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory have created a new, AI-powered system for designing more durable microstructured ...

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

Wolfram-like attention framing meets spiking networks: event-triggered, energy-thrifty AI that “wakes” to stimuli.

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, launched a hybrid quantum neural network structure (H-QNN) ...

Recurrent neural networks are a classification of artificial neural networks used in artificial intelligence (AI), natural language processing (NLP), deep learning, and machine learning. They process ...

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 ...

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...

Cornell engineers have built the first fully integrated “microwave brain” — a silicon microchip that can process ultrafast data and wireless signals at the same time, while using less than 200 ...