Teaching physics to neural networks enables those networks to better adapt to chaos within their environment. The work has implications for improved artificial intelligence (AI) applications ranging ...

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

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

Suppose you have a thousand-page book, but each page has only a single line of text. You’re supposed to extract the information contained in the book using a scanner, only this particular scanner ...

Suppose you have a thousand-page book, but each page has only a single line of text. You’re supposed to extract the information contained in the book using a scanner, only this particular scanner ...

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

Artificial neural networks are a form of machine-learning algorithm with a structure roughly based on that of the human brain. Like other kinds of machine-­learning ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Nvidia Graphics Research said it has 19 research papers debuting at ...

We've been taught to distrust our inner worlds. Scientific rigor demands external measurement, controlled experiments, objective instruments. Introspection seems subjective, unreliable—the antithesis ...