Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this prowess extend to other fields of biology as well? Contrary to expectations, a ...

Predicting observable traits from genetic variation remains difficult due to the complex interplay of multiple genes and environmental influences. Widely used statistical approaches are limited in ...

There is direct evidence of spatial learning in any butterfly or moth species. Melissa Breyer was Treehugger’s senior editorial director before moving to Martha Stewart. Her writing and photography ...

A sense of time is fundamental to how we understand, recall, and interact with the world. Tasks ranging from holding a conversation to driving a car require us to remember and perceive how long things ...

In a groundbreaking discovery, bumblebees have been shown to possess a previously unseen level of cognitive sophistication. A new study, published in Nature, reveals that these fuzzy pollinators can ...

A new publication from Opto-Electronic Advances, 10.29026/oea.2023.220157 discusses lensless complex amplitude demodulation based on deep learning in holographic data storage. In the era of big data, ...

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in research applications to explore potentially high-impact approaches in the development and use of ...

Transfer of math, physics, and communication skills into the entry-level photonics workforce, NSF Award 1432578, Sept 2014 – Aug 2019 Exploring factors that shape education & workplace training on ...

Reading these, one can be forgiven for thinking it's possible to become an AI master with little or no software development experience. But is that the case? Industry leaders suggest that there are ...