research

In recent years, robots have gained artificial vision, touch, and even smell. “Researchers have been giving robots human-like perception,” says MIT Associate Professor Fadel Adib. In a new paper, Adib’s team is pushing the technology a step further. “We’re trying to give robots superhuman perception,” he says.

Smart speakers, such as Amazon Echo and Google Home, have proven adept at monitoring certain health care issues at home. For example, researchers at the University of Washington have shown that these devices can detect cardiac arrests or monitor babies breathing. But what about tracking something even smaller: the minute motion of individual heartbeats in a person sitting in front of a smart speaker?

A computer network closely modelled on part of the human brain is enabling new insights into the way our brains process moving images – and explains some perplexing optical illusions.

Engineers at the University of California San Diego have created a four-legged soft robot that doesn’t need any electronics to work. The robot only needs a constant source of pressurized air for all its functions, including its controls and locomotion systems.

Cold Spring Harbor Laboratory (CSHL) Assistant Professor Peter Koo and collaborator Matt Ploenzke reported a way to train machines to predict the function of DNA sequences. They used “neural nets”, a type of artificial intelligence (AI) typically used to classify images.

Soft robots may not be in touch with human feelings, but they are getting better at feeling human touch. Cornell University researchers have created a low-cost method for soft, deformable robots to detect a range of physical interactions, from pats to punches to hugs, without relying on touch at all. Instead, a USB camera located inside the robot captures the shadow movements of hand gestures on the robot’s skin and classifies them with machine-learning software.

Army-funded researchers discovered how to make materials capable of self-propulsion, allowing materials to move without motors or hands.

USC researchers have developed a new method to counter emergent mutations of the coronavirus and hasten vaccine development to stop the pathogen responsible for killing thousands of people and ruining the economy.

Using patient data, artificial intelligence can make a 90 percent accurate assessment of whether a person will die from COVID-19 or not, according to new research at the University of Copenhagen. Body mass index (BMI), gender and high blood pressure are among the most heavily weighted factors. The research can be used to predict the number of patients in hospitals, who will need a respirator and determine who ought to be first in line for a vaccination.