New research from Rensselaer Polytechnic Institute (RPI) could help shape the future of artificial intelligence by making AI ...

We are being super paranoid about safety, so the date could shift,” Elon Musk tweeted on X, regarding Tesla’s June 22 ...

This important study demonstrates the significance of incorporating biological constraints in training neural networks to develop models that make accurate predictions under novel conditions. By ...

Deep convolutional neural networks (DCNN) are currently the most successful models for accurately recognizing ... 30 ms), suggesting that recurrent loops operate in our brain, too.

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions ...

But researchers at DeepMind claim neural networks can outperform neurosymbolic models under the right testing conditions. In a preprint paper, coauthors describe an architecture for spatiotemporal ...

Fast domain-aware neural network emulation of a planetary boundary layer parameterization in a numerical weather forecast model. Geoscientific Model Development , 2019; 12 (10): 4261 DOI: 10.5194 ...

New research from Rensselaer Polytechnic Institute (RPI) could help shape the future of artificial intelligence by making AI systems less resource-intensive, higher performing, and designed to emulate ...