Robots can now learn directly from videos of human-robot interactions and apply this information to new tasks thanks to a new learning method created by SCS researchers.
Nearly all areas of the planet have microplastics, which are dangerous to animals if consumed. But once they find their way into the cracks at the bottom of rivers, it is difficult to get rid of such tiny particles from the ecosystem.
When you live in the driest State in the driest country in the world, bushfires are an unfortunate, and all-too-regular part of life. Learning how to survive such emergencies is important for all people, but especially for our youngest citizens
Our face can unlock a smartphone, provide access to a secure building and speed up passport control at airports, verifying our identity for numerous purposes.
Robot-assisted system with Ensenso 3D camera for safe handling of nuclear waste
As about 30% of the UK raspberry crop lies rotting in the fields, the need for automating the delicate harvesting operation becomes more acute.
An increasing number of research publications describe the use of Artificial Intelligence (AI) for the Sustainable Development Goals, but very few studies discuss the usually hidden environmental costs of AI.
The U.S. Department of Energy’s (DOE) Argonne National Laboratory (ANL) will be involved in two interdisciplinary projects after receiving approximately $3 million in funding to further enhance machine learning technology and artificial intelligence (AI).
In 2018, when Jeff Rutherford, a graduate student from Stanford University, began his doctorate studies, the volume of methane entering the atmosphere from oil and gas extraction operations, majorly as a result of fracking, was raised as an important issue.
A collaboration between Monash University’s Grid Innovation Hub, Worley and Palisade Energy Ltd is using machine learning technology to accurately predict wind and solar power to securely integrate them into the national electricity grid.