Graduate student James Clark speaks with Boston Globe reporter Andres Picon about his study that provides evidence laser technology could be used to attract aliens. “A laser produces all of its power in one wavelength,” explains Clark, “so the way that it’s detectable is not that it’s more powerful than the sun, but that it’s very distinct from the sun.”
Writing for Popular Mechanics, David Grossman highlights a feasibility study by MIT researchers that provides evidence that lasers could be used to try to locate aliens. Grossman explains that the light would be targeted toward “areas like Proxima Centauri, the closest star to Earth, and TRAPPIST-1, a star around 40 light-years away with seven exoplanets in orbit.”
MIT researchers examined why a third of Wikipedia deliberations go unresolved and developed a new tool that could be used to help resolve more discussions, reports Samantha Cole for Motherboard. Cole explains that “the tool uses the data they found and analyzed in this research, to summarize threads and predict when they’re at risk of going stale.”
UPI reporter Tauren Dyson writes that a new feasibility study by MIT researchers shows that existing laser technology could be used to create a beacon light that could attract attention from as far as 20,000 light years away.
MIT researchers have found that laser technology could be used to attract attention from alien astronomers, reports Becky Ferreira for Motherboard. The researchers found that amplifying an infrared laser could “produce a signal that would outshine the Sun’s infrared emissions tenfold, an anomaly that would stand out to a smart species observing our solar system from a distant exoplanet.”
Writing for The Conversation, Prof. Tauhid Zaman discusses his research showing how a small number of very active social media bots can have a significant impact on public opinion. Zaman notes that his findings are “a reminder to be careful about what you read – and what you believe – on social media.”
Smithsonian reporter Randy Rieland writes that MIT researchers have developed a machine learning model that can detect speech and language patterns associated with depression. The researchers note that the system is intended to assist, not replace clinicians. “We’re hopeful we can provide a complementary form of analysis,” explains Senior Research Scientist James Glass.
Boston Globe reporter Katie Johnston speaks with several MIT researchers about their work developing technology that is aimed at improving collaboration between humans and robots. Prof. Julie Shah notes that offloading easier decisions onto a machine “would allow people to focus on the parts of job that truly require human judgment and experience.”
Boston Herald reporter Jordan Graham writes that MIT researchers have developed an autonomous system that allows fleets of drones to navigate without GPS and could be used to help find missing hikers. “What we’re trying to do is automate the search part of the search-and-rescue problem with a fleet of drones,” explains graduate student Yulun Tian.
Science reporter Tania Rabesandratana examines how MIT researchers are gathering and identifying gut bacteria from people around the world. The effort is aimed at preserving the human gut’s microbial biodiversity and developing new treatments for diseases. “I'm 100% confident that there are relevant medical applications for hundreds of strains we've screened and characterized,” explains Prof. Eric Alm.
Motherboard reporter Daniel Oberhaus writes that MIT researchers have developed an AI system that can generate theories about the physical laws of imaginary universes. Oberhaus writes that in the future the system could be used to help understand “massively complex datasets, such as those used in climate modeling or economics.”
Katharine Schwab of Fast Company writes about the Media Lab’s Moral Machine project, which surveyed people about their feelings on the ethical dilemmas posed by driverless vehicles. Because the results vary based on region and economic inequality, the researchers believe “self-driving car makers and politicians will need to take all of these variations into account when formulating decision-making systems and building regulations,” Schwab notes.
Technology developed by researchers from MIT Lincoln Lab could be used to help detect public shooters before they fire, writes Elizabeth MacBride for Forbes. “The technology uses radar energy to detect weapons and explosives through clothing, backpacks and hand baggage in real time,” MacBride explains.
MIT researchers have developed a language translation model that operates without human annotations and guidance, reports Liangyu for Xinhua news agency. The system, which may enable computer-based translations of the thousands of languages spoken worldwide, is “a step toward one of the major goals of machine translation, which is fully unsupervised word alignment,” Liangyu explains.
Graduate students Ziv Epstein and Matt Groh have developed an AI system that adds spooky figures to photos, reports Mark Wilson for Fast Company. Wilson writes that the system “works so well because it places ghostly figures exactly where your brain naturally thinks they could be–on a path in the middle of a forest, rather than, say, floating randomly through the air.”