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."
During a Times Higher Ed summit, Prof. Shigeru Miyagawa, senior associate dean for open learning, emphasized the importance of integrating attention to ethical implications into AI education, reports Paul Baskin. “My plan is to educate a new generation of young people who will have intuition behind computational thinking,” says Miyagawa.
Mashable highlights how MIT researchers have developed a new system of computationally simple robots inspired by biological cells that can connect in large groups to move around, transport objects and complete tasks. Mashable explains that robots made up of simplistic components, “could enable more scalable, flexible and robust systems.”
Motherboard reporter Rob Dozier writes about Glitch, an MIT startup that uses machine learning to design clothing. “These tools are meant to empower human designers,” explains graduate student Emily Salvador. “What I think is really cool about these creative-focused AI tools is that there’s still this really compelling need for a human to intervene with the algorithm.”
Researchers from MIT and a number of other institutions have found that grammar-enriched deep learning models had a better understanding of key linguistic rules, reports Kyle Wiggers for VentureBeat. The researchers found that an AI system provided with knowledge of basic grammar, “consistently performed better than systems trained on little-to-no grammar using a fraction of the data, and that it could comprehend ‘fairly sophisticated’ rules.”
In this video, Mashable highlights how CSAIL researchers have developed a new system that can help lift heavy objects by mirroring human activity. The system uses sensors that monitor muscle activity and detect changes in the user’s arm.
In an article for Gizmodo, Dell Cameron writes that graduate student Joy Buolamwini testified before Congress about the inherent biases of facial recognition systems. Buolamwini’s research on face recognition tools “identified a 35-percent error rate for photos of darker skinned women, as opposed to database searches using photos of white men, which proved accurate 99 percent of the time.”
Wired reporter Lily Hay Newman highlights graduate student Joy Buolamwini’s Congressional testimony about the bias of facial recognition systems. “New research is showing bias in the use of facial analysis technology for health care purposes, and facial recognition is being sold to schools,” said Buolamwini. “Our faces may well be the final frontier of privacy.”
Popular Science reporter Rob Verger writes that MIT researchers have developed a new mechanical system that can help humans lift heavy objects. “Overall the system aims to make it easier for people and robots to work together as a team on physical tasks,” explains graduate student Joseph DelPreto.
MIT and the U.S. Air Force “are teaming up to launch a new accelerator focused on artificial intelligence applications,” writes Danny Crichton for TechCrunch. The goal is that projects developed in the MIT-Air Force AI Accelerator would be “addressing challenges that are important to both the Air Force and society more broadly.”
Will Knight writes for MIT Technology Review about the MIT-Air Force AI Accelerator, which “will focus on uses of AI for the public good, meaning applications relevant to the humanitarian work done by the Air Force.” “These are extraordinarily important problems,” says Prof. Daniela Rus. “All of these applications have a great deal of uncertainty and complexity.”
The new MIT-Air Force AI Accelerator “will look at improving Air Force operations and addressing larger societal needs, such as responses to disasters and medical readiness,” reports Breanne Kovatch for The Boston Globe. “The AI Accelerator provides us with an opportunity to develop technologies that will be vectors for positive change in the world,” says Prof. Daniela Rus.
WCVB-TV’s Mike Wankum visits the Media Lab to learn more about a new wearable device that allows users to communicate with a computer without speaking by measuring tiny electrical impulses sent by the brain to the jaw and face. Graduate student Arnav Kapur explains that the device is aimed at exploring, “how do we marry AI and human intelligence in a way that’s symbiotic.”
Fast Company reporter Eillie Anzilotti highlights how MIT researchers have developed an AI-enabled headset device that can translate silent thoughts into speech. Anzilotti explains that one of the factors that is motivating graduate student Arnav Kapur to develop the device is “to return control and ease of verbal communication to people who struggle with it.”