This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

Higher-order interactions underlie complex phenomena in systems such as biological and artificial neural networks, but their study is challenging due to the scarcity of tractable models. By leveraging ...

Processing spatiotemporal data sources with both high spatial dimension and rich temporal information is a ubiquitous need in machine intelligence. Recurrent neural networks in the machine learning ...

“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 ...

Artistic rendering of noncollinear sum-frequency generation (SFG): two infrared pulses mix in a χ² crystal to produce three output pulses (green), with the central SFG pulse being the primary output ...

Adrian de Wynter is an AI scientist at Microsoft and a researcher at the University of York. In addition to studying the ...

Forbes contributors publish independent expert analyses and insights. Philip Maymin, a professor of analytics and AI, covers finance and AI. Is this a deep learning neural network, with blue inputs, ...