Algorithms

TechCrunch reporter Darrell Etherington writes that CSAIL researchers have built a new two-fingered robotic gripper. The researchers “equipped their robotic gripper with fingertips that are not only made out of a soft material, but that also have embedded sensors which help it continually detect the position of a cable between the grippers to better control holding and manipulating them while performing simple tasks like detangling.”

MIT researchers have developed an AI-enabled machine known as DeepRole that can beat human players in an online multiplayer game where each player’s true motives and roles are kept secret from one another. This “is the first gaming bot that can win online multiplayer games in which the participants' team allegiances are initially unclear,” reports Xinhua.

MIT researchers have developed a new way to optimize how soft robots perform certain tasks. It "shrinks drastically the amount of computational overhead required to get good movement results out of soft robots,” writes Darrell Etherington for TechCrunch, “which is a key ingredient in helping make them partial to actually use in real-life applications.”

MIT researchers have developed an AI system that can predict Alzheimer’s risk by forecasting how patients will perform on a test measuring cognitive decline up to two years in advance, reports Casey Ross for STAT. 

Verge reporter James Vincent writes that researchers at the MIT-IBM Watson AI Lab have developed an algorithm that can transform selfies into artistic portraits. The algorithm is “trained on 45,000 classical portraits to render your face in faux oil, watercolor, or ink, “Vincent explains.

Writing for The New York Times, research scientists Chelsea Barabas and Karthik Dinakar argue that risk assessment algorithms designed to help predict people’s future criminal behavior are “fundamentally flawed. They give judges recommendations that make future violence seem more predictable and more certain than it actually is. In the process, risk assessments may perpetuate the misconceptions and fears that drive mass incarceration.”

CSAIL’s RoboRaise robot can successfully execute the Bottle Cap Challenge, removing a bottle cap with a well-placed kick, reports Darrell Etherington for TechCrunch. Etherington explains that the robot, “can mirror the actions of a human just by watching their bicep. This has a number of practical applications, including potentially assisting a person to lift large or awkward objects.”

Researchers at MIT and Brown University created an interactive data system that “could give everyone AI superpowers,” writes Darrell Etherington for TechCrunch. Known as ‘Northstar,’ the system can instantly generate machine-learning models to use with existing data sets in order to generate useful predictions, explains Etherington.

Using a tactile sensor and web camera, MIT researchers developed an AI system that allows robots to predict what something feels like just by looking at it, reports David Williams for CNN. “This technology could be used to help robots figure out the best way to hold an object just by looking at it,” explains Williams.

Forbes contributor Charles Towers-Clark explores how CSAIL researchers have developed a database of tactile and visual information that could be used to allow robots to infer how different objects look and feel. “This breakthrough could lead to far more sensitive and practical robotic arms that could improve any number of delicate or mission-critical operations,” Towers-Clark writes.

MIT researchers have created a new system that enables robots to identify objects using tactile information, reports Darrell Etherington for TechCrunch. “This type of AI also could be used to help robots operate more efficiently and effectively in low-light environments without requiring advanced sensors,” Etherington explains.

Fast Company reporter Michael Grothaus writes that CSAIL researchers have developed a new system that allows robots to determine what objects look like by touching them. “The breakthrough could ultimately help robots become better at manipulating objects,” Grothaus explains.

TechCrunch reporter Darrell Etherington writes that MIT researchers have developed a system that can predict a perso's trajectory. The tool could allow “robots that typically freeze in the face of anything even vaguely resembling a person walking in their path to continue to operate and move around the flow of human foot traffic."

Bloomberg News spotlights how MIT researchers have developed a fleet of autonomous boats that can automatically latch onto one another. Bloomberg notes that the boats will be able to “transport goods and people, collect trash and assemble into floating stages and bridges.”

Boston Globe reporter Martin Finucane writes that MIT researchers have developed an automated latching system that could enable a fleet of autonomous boats to connect to docking stations and other boats. Finucane explains that in turbulent water, “after a missed first attempt, the system can autonomously adapt, repositioning the roboat and latching.”