Bots & Brains

Researchers of the Japan Advanced Institute of Science and Technology (JAIST) have developed low-cost artificial robotic skin with high-performance, vision-guided sensing, opening the doors to large-scale tactile sensing technology. They claim this artificial skin brings robots closer to ‘touching’ human lives’

A team of New Jersey researchers has demonstrated that high-dose therapy gait training using robotic exoskeletons may aid early rehabilitation for acute stroke.

Researchers of the SHIBAURA INSTITUTE OF TECHNOLOGY demonstrate automated drone landing using 2D camera-based symbol detection, with potential applications in rescue missions.

Researchers from the University of Copenhagen have developed a ground-breaking technique that can help us unravel some of the mysteries of the human intestinal bacteria, with the help of artificial intelligence mapping 500-1000 different species among 100 billion active bacteria.

New research led by researchers at the University of Toronto (U of T) and Northwestern University employs machine learning to craft the best building blocks in the assembly of framework materials for use in a targeted application.

To navigate built environments, robots must be able to sense and make decisions about how to interact with their locale. Researchers at the University of Texas have made progress in this field using AI and supercomputers.

Mount Sinai researchers have published one of the first studies using a machine learning technique called “federated learning” to examine electronic health records to better predict how COVID-19 patients will progress. The study was published in the Journal of Medical Internet Research – Medical Informatics on January 18.

Using theoretical calculations, an international team of researchers, including scientists from the Center for Humans and Machines at the Max Planck Institute for Human Development, shows that it would not be possible to control a superintelligent AI. The study was published in the Journal of Artificial Intelligence Research.

Columbia engineers create a robot that learns to visually predict how its partner robot will behave, displaying a glimmer of empathy. This “Robot Theory of Mind” could help robots get along with other robots–and humans–more intuitively, the researchers claim.

Compared to standard machine learning models, deep learning models are largely superior at discerning patterns and discriminative features in brain imaging, despite being more complex in their architecture, according to a new study in Nature Communications led by Georgia State University.