A new study by York University researchers has found a potential striking flaw in artificial intelligence (AI) models.

Imagine a horse stumbling on a rock. It regains momentum, then hits bumpier terrain and slows to a walk. Back on steady ...

It might be futile to try making machines that are fully human. Our abilities have been refined through a lengthy evolution.

Artificial neural networks (ANNs) are increasingly being deployed to refine the estimation of evapotranspiration, a critical component in water resource management and agricultural planning. By ...

An improved model identifies power-reducing dust accumulation on photovoltaic modules, helping engineers know when the ...

Novel artificial neurons learn independently and are more strongly modeled on their biological counterparts. A team of researchers has programmed these infomorphic neurons and constructed artificial ...

Gamma-ray spectroscopy is a vital analytical technique employed in identifying and quantifying radioactive nuclides, while artificial neural networks (ANNs) have emerged as robust computational tools ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

In 1943, a pair of neuroscientists were trying to describe how the human nervous system works when they accidentally laid the foundation for artificial intelligence. In their mathematical framework ...

Listen to the first notes of an old, beloved song. Can you name that tune? If you can, congratulations — it’s a triumph of your associative memory, in which one piece of information (the first few ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.