Third-year student Casey Johnson speaks with Washington Post reporter Luz Lazo about his work exploring the feasibility of using GPS technology to determine when a scooter is on the sidewalk. Lazo explains that Johnson wrote a “surface categorization algorithm to detect the periodic cracks in a sidewalk. He then added an accelerator sensor — which costs less than $1 — to detect when the scooter is being used on an asphalt road versus a concrete sidewalk.”
Fox News reporter Chris Ciaccia writes that a team of astronomers, including MIT researchers, has found an exoplanet that has a 3.14-day orbit. “The ‘pi planet’ known as K2-315b is relatively close to Earth at 186 light-years away,” writes Ciaccia.
A new tool developed by MIT researchers sheds light on the operations of generative adversarial network models and allows users to edit these machine learning models to generate new images, reports Daphne Leprince-Ringuet for ZDNet. "The real challenge I'm trying to breach here," says graduate student David Bau, "is how to create models of the world based on people's imagination."
MIT researchers have developed an AI algorithm called MosAIc that “can spot connections between works from different cultures, artists and mediums,” writes Theresa Machemer for Smithsonian Magazine. “We hope this approach can be used as a tool to help art historians find new patterns in history and gather evidence to support their hypotheses,” says PhD student Mark Hamilton.
Forbes contributor Elizabeth Fernandez writes that a study co-authored by MIT researchers shows quantum entanglement could give blackjack players a slight edge. Fernandez adds that the research shows how, “entangled systems can show up in our macroscopic, everyday lives.”
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.