MIT researchers have identified a new kind of antibiotic using AI, according to BBC News. “A powerful algorithm was used to analyze more than one hundred million chemical compounds in a matter of days. The newly discovered compound was able to kill 35 types of potentially deadly bacteria.”
Newsweek reporter Rosie McCall writes that MIT researchers have developed a decision map to help determine the best course of action when faced with an asteroid headed towards Earth. The decision map “considers the asteroid's mass, momentum, trajectory and how much warning time scientists have before collision,” writes McCall.
In an article for The Washington Post, Prof. M. Taylor Fravel examines China’s approach to territorial disputes. Fravel notes that “by settling the majority of its other territorial disputes, China and its neighbors have reduced numerous opportunities for armed conflict.”
Writing for The Conversation, Sriram Chandrasekaran explores how MIT researchers used a deep-learning algorithm to identify an antibiotic that could be used to treat drug-resistant bacteria. Chandrasekaran writes that AI technologies “may soon give us a leg up in the never-ending battle against drug resistance.”
Alumna Mareena Robinson Snowden PhD '17 speaks with NBC’s Erin Delmore about what inspired her to pursue a career in nuclear engineering and the challenges women and minorities face in STEM fields. “I think it’s tremendously important to have this diversity of voices, not just from a cultural perspective or from a gender perspective, but just lived experience,” says Snowden.
Forbes contributor Vivienne Decker highlights Ten Little, a children’s shoe company co-founded by MIT alumna Fatma Collins MBA ’11 that is aimed at making it easier for parents to find shoes that fit properly and provide the necessary support. Collins explains she was motivated to start the company after searching for shoes for her daughter “left me thinking there must be a better way.”
Using a new algorithm, MIT researchers have discovered an antibiotic that can treat drug-resistant bacteria, reports Madhumita Murgia for the Financial Times. “There is still a question of whether machine-learning tools are really doing something intelligent in healthcare,” says Prof. Regina Barzilay. “This shows how far you can adapt this tool.”
Quanta Magazine reporter Dana Najjar writes that new findings from LIGO researchers challenge longstanding assumptions about neutron stars.
William McRaven, a retired four-star US Navy admiral, will deliver MIT’s 2020 Commencement address, writes Peter Bailey-Wells for The Boston Globe.
Boston Magazine reporter Kaylie Felsberg highlights an exhibit at the MIT List Visual Arts Center featuring the work of artist Rami George. Felsberg writes that the exhibit was inspired by how Rami George’s mother took her children to join a New Age cult called the Samaritan Foundation. George “reflects on their experience and shares research on the mysterious organization via two video essays.”
Jo Marchant writes for Nature that MIT researchers have developed a machine learning model that was used to discover an antibiotic that works against a wide range of bacteria. People keep finding the same molecules over and over,” says Prof. James Collins. “We need novel chemistries with novel mechanisms of action.”
HuffPost reporter Florence Breton spotlights the work of alumna Farah Alibay PhD '14, an aerospace engineer who is working on the Mars rover for the 2020 mission. “I want to show everyone that a diverse team can perform,” says Alibay. “I want to change the aerospace culture and the way we integrate young female engineers and celebrate differences.
MIT researchers have developed a new framework aimed at determining the best method to avoid a collision with an Earth-bound asteroid, reports Sophie Lewis for CBS News. “The method developed at MIT could give scientists a handy guide to determine the best course of action before launching a full-scale attack on a potential planet-killer,” Lewis explains.
MIT researchers used machine learning to identify an antibiotic capable of killing drug-resistant bacteria, reports Casey Ross for STAT. “I do think this platform will very directly reduce the cost involved in the discovery phase of antibiotic development,” says Prof. James Collins. “With these models, one can now get after novel chemistries in a shorter period of time involving less investment.”
Guardian reporter Ian Sample writes that MIT researchers have discovered a new antibiotic that kills drug-resistant bacteria using a deep-learning algorithm. “The drug works in a different way to existing antibacterials and is the first of its kind to be found by setting AI loose on vast digital libraries of pharmaceutical compounds,” Sample explains.