The Economist spotlights how MIT researchers created a virtual technique to decipher the contents of a letter that was sealed 300 years ago. The letter was originally sealed by its sender using the historical practice of securing correspondence called letterlocking. The new virtual technique “seems to hold plenty of promise for future research into a fascinating historical practice.”
A new imaging technique created by researchers from MIT and other institutions has been used to shed light on the contents of an unopened letter from 1697, writes Matt Simon for Wired. “With fancy letterlocking techniques, you will forcibly rip some part of the paper, and then that will become detectable,” says Prof. Erik Demaine, of the method used to seal the letter.
Guardian reporter Alison Flood explores the new technique created by MIT researchers to virtually unseal an unopened letter written in 1697. The researchers, “worked with X-ray microtomography scans of the letter, which use X-rays to see inside the document, slice by slice, and create a 3D image,” writes Flood.
Researchers from MIT and other institutions have developed a new virtual-reality technique that has allowed them to unearth the contents of letters written hundreds of years ago, without opening them, writes New York Times reporter William J. Broad. “The new technique could open a window into the long history of communications security,” writes Broad. “And by unlocking private intimacies, it could aid researchers studying stories concealed in fragile pages found in archives all over the world.”
Using X-ray imaging and algorithms, MIT researchers have been able to virtually open and read letters that been sealed for more than 300 years, writes Priti Parikh for New Scientist. “Studying folding and tucking patterns in historic letters allows us to understand technologies used to communicate,” says Jana Dambrogio, a conservator at the MIT Libraries.
Researchers from MIT and other institutions have used algorithms and an X-ray scanner to decipher the secrets inside a letter that has been sealed since 1697, reports Sara Castellanos for The Wall Street Journal. “This is a dream come true in the field of conservation,” said Jana Dambrogio, the Thomas F. Peterson Conservator at MIT Libraries.
Bloomberg reporter Ashlee Vancee spotlights the work of alumnus Youyang Gu SB ’15, MEng’19, who developed a forecasting model for Covid-19 last spring that was widely considered to be one of the most accurate models of the pandemic’s trajectory. “The novel, sophisticated twist of Gu’s model came from his use of machine learning algorithms to hone his figures,” writes Vancee.
TechCrunch reporter Darrell Etherington writes that MIT researchers have developed a new “liquid” machine learning system that can learn on the job. Etherington notes that the system has “the potential to greatly expand the flexibility of AI technology after the training phase, when they’re engaged in the actual practical inference work done in the field.”
Wired reporter Will Knight spotlights how MIT researchers built a machine learning system that can help predict which patients are most likely to develop breast cancer. “What the AI tools are doing is they're extracting information that my eye and my brain can't,” says Constance Lehman, a professor of radiology at Harvard Medical School and division chief of breast imaging at MGH.
TechCrunch reporter Darrell Etherington writes that MIT researchers have developed a new system that devises hardware architecture that can speed up a robot’s operations. Etherington notes that “this research could help unlock the sci-fi future of humans and robots living in integrated harmony.”
Writing for Wired, Will Knight spotlights how MIT researchers developed a new technique to squeeze an AI vision algorithm onto a low-power computer chip that can run for months on a battery. The advance “could help bring more advanced AI capabilities, like image and voice recognition, to home appliances and wearable devices, along with medical gadgets and industrial sensors.”
Prof. James Collins speaks with Boston 25 reporter Julianne Lima about the growing issue of antibiotic resistant bacteria and his work using AI to identify new antibiotics. Collins explains that a new platform he developed with Prof. Regina Barzilay uncovered “a host of new antibiotics including one that we call halicin that has remarkable activity against multi drug-resistant pathogens.”
Fast Company reporter KC Ifeanyi writes about “Coded Bias,” which explores how graduate student Joy Buolamwini’s “groundbreaking discovery and subsequent studies on the biases in facial recognition software against darker-skinned individuals and women led to some of the biggest companies including Amazon and IBM rethinking their practices.”
New York Times reporter Devika Girish reviews “Coded Bias,” a new documentary that chronicles graduate student Joy Buolamwini’s work uncovering how many AI systems can perpetuate race and gender-based inequities. “When you think of A.I., it’s forward-looking,” says Buolamwini. “But A.I. is based on data, and data is a reflection of our history.”
Fox News reporter Kayla Rivas features Prof. Richard Larson’s work developing a new algorithm that could be used to help more accurately pinpoint sources of Covid-19 infections in sewer systems. The algorithm could be used to help “toggle between normal testing to an emergency schedule to locate asymptomatic cases fast before they infect others.”