We investigate the potential of graph neural networks (GNNs) for transfer learning and improved molecular property prediction in the context of funnels or screening cascades characteristic of drug ...

Recent advances unveiled physical neural networks as promising machine learning platforms, offering faster and more energy-efficient information processing. Compared with extensively-studied optical ...

Giving AI a human-like memory limitation may actually help it learn language better. In their new proof-of-principle study, ...

For the past decade, AI researcher Chris Olah has been obsessed with artificial neural networks. One question in particular engaged him, and has been the center of his work, first at Google Brain, ...

From image captioning and neural networks to Tesla Autopilot and OpenAI, Andrej Karpathy has helped shape modern AI research. Here are seven major breakthroughs and contributions that influenced ...

Researchers build fleeting memory transformers with human-like memory decay, proving memory limits help AI learn grammar ...

“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 ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...

MCUs are opening the field for extreme edge development, unveiling a new age of possibilities and solutions — especially with ...

Autodesk's Mike Haley takes a closer look at what Autodesk is calling the next stage in 3D design "neural CAD" AI foundation ...