Blue Origin unveiled plans to send a spaceship to the moon, reports Seth Borenstein for the AP. Prof. Dava Newman explained that the newly designed rocket engine is what makes Blue Origin’s attempt to reach the moon unique. “It’s for real,” said Newman.
Researchers at MIT have found that adversarial examples, a kind of optical illusion for AI that makes the system incorrectly identify an image, may not actually impact AI in the ways computer scientists have previously thought. “When algorithms fall for an adversarial example, they’re not hallucinating—they’re seeing something that people don’t,” Louise Matsakis writes for Wired.
Writing for Nature, research affiliate Ashley Nunes cautions that the role of driverless cars in society must be closely investigated before they are integrated into mainstream modes of transportation. “Driverless-car technology might have the potential to improve public health and save lives,” Nunes writes, “but if those who most need it don’t have access, whose lives would we actually be saving?”
The Economist highlights a study co-authored by research affiliate Ashley Nunes that examines the economic feasibility of driverless taxis. The researchers found that riding in a driverless taxi is more expensive per mile than driving your own car.
Fast Company reporter Michael Grothaus writes that CSAIL researchers have developed a deep learning model that could predict whether a woman might develop breast cancer. The system “could accurately predict about 31% of all cancer patients in a high-risk category,” Grothaus explains, which is “significantly better than traditional ways of predicting breast cancer risks.”
A study by MIT researchers examining adversarial images finds that AI systems pick up on tiny details in images that are imperceptible to the human eye, which can lead to misidentification of objects, reports Louise Matsakis for Wired. “It’s not something that the model is doing weird, it’s just that you don’t see these things that are really predictive,” says graduate student Shibani Santurkar.
WCVB-TV’s Jennifer Eagan reports that researchers from MIT and MGH have developed a deep learning model that can predict a patient’s risk of developing breast cancer in the future from a mammogram image. Prof. Regina Barzilay explains that the model “can look at lots of pixels and variations of the pixels and capture very subtle patterns.”
Writing for The Wall Street Journal, Edward Glaeser spotlights a new book from Profs. Johnathan Gruber and Simon Johnson titled, “Jump-Starting America.” Glaeser writes that Gruber and Johnson have “produced a superbly argued case for public and private investment in education and research.”
Boston Globe reporter Laura Krantz visits MIT’s Haystack Observatory to learn more about the place where scientists played a key role in developing the first image of a black hole and created a supercomputer used to compile the image. Krantz notes that researchers at Haystack also study the Earth, not-far-away planets, and stars, and are creating devices to track the decay of icebergs.
Fast Company reporter Jared Lindzon spotlights how Ultra Testing, a company founded by two MIT graduates that employs over 60 workers remotely across 20 states, 75% of whom are on the autism spectrum. “Not only was the company open to hiring neurodiverse employees, but it actively sought them out,” notes Lindzon.
Popular Science reporter Nicole Wetsman writes that MIT researchers have found light pulses could potentially be used to help ease the symptoms of Alzheimer’s disease. The researchers found that “light pulses and gamma oscillations protect against neurodegeneration and change the expression of genes involved with inflammation and neuron health in the brains of mice.”
Scientific American reporter Jeremy Hsu highlights how CSAIL researchers have developed a robot that can automatically sort recycling. The robot “uses soft Teflon ‘fingers,’ which have fingertip sensors to detect object size and stiffness,” Hsu explains.
MIT researchers have identified a new method to engineer neural networks in a way that allows them to be a tenth of the size of current networks without losing any computational ability, reports Avery Thompson for Popular Mechanics. “The breakthrough could allow other researchers to build AI that are smaller, faster, and just as smart as those that exist today,” Thompson explains.
HealthDay News reporter Amy Norton writes that MIT researchers have developed an AI system that can help predict a woman’s risk of developing breast cancer and provide more personalized care. “If you know a woman is at high risk, maybe she can be screened more frequently, or be screened using MRI,” explains graduate student Adam Yala.
Researchers from MIT and the European Space Agency are developing a process to evaluate how operators deploy satellites to help reduce the amount of debris in space, reports Loren Grush for The Verge. “It’s actually encouraging companies to try to beat each other in how good they behave, so they can build their brand,” explains Prof. Danielle Wood.