A new study has used a type of machine learning called a neural network to reveal how different kinds of training can change how learning happens. As neural networks learn, they adopt patterns of activity that are strikingly similar to real-life neuron firing patterns. What’s more, the type of training affects both the activity pattern, and the ability to solve a task, in similar ways between neural networks and living brains.

University of Washington researchers gathered eight kids on campus to explore how they played with AI toys. The kids initially were curious, asking introductory questions, such as “What is your name?” But after communication breakdowns, the kids turned to antagonizing the toys, calling them “ugly” and “evil” and joking about throwing them in the ocean.

MUSC startup OncoBLAZE is developing a new imaging system that could help cancer researchers see experiments unfold in real time. Created by Hollings researcher Dieter Haemmerich, Ph.D., SphynxVision uses fluorescence imaging to track cancer cells, drugs and other biological processes under normal room lighting. Unlike conventional systems that require samples to be placed inside dark, closed chambers, its open design allows researchers to perform procedures while continuously capturing high-resolution images. The technology grew out of Haemmerich’s own need to track chemotherapy as it was delivered to tumors and could ultimately help scientists uncover biological changes that current imaging systems miss. OncoBLAZE is now preparing to place early versions of SphynxVision in research laboratories for testing ahead of a broader commercial launch.

A new, international, community-led scientific review warns that major gaps in knowledge along Antarctica’s coast are now one of the biggest obstacles to reliably predicting future global sea level rise.

A new software framework lets multiple artificial intelligence (AI) models plug directly into a fusion experiment’s control system, reading plasma measurements and issuing commands in about 20 milliseconds, far faster than any human operator. Researchers tested the framework in five experiments at the DIII-D National Fusion Facility, a Department of Energy user facility in San Diego. The framework predicted and prevented plasma instabilities and cut the time to deploy a new AI model from months to days.

Ying Zhang in URI's College of the Environment and Life Sciences is leading a collaboration funded by the National Science Foundation that will leverage existing collaborations and coastal research networks in Rhode Island and Louisiana. With nearly 40% of Americans living in coastal counties, this research is highly relevant to building community resilience and economic sustainability in both states.

Rice University has received a National Science Foundation award to develop artificial intelligence-powered cameras that could dramatically reduce the data, energy and cost needed to operate large-scale camera networks.