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Scientific American

In a forthcoming book, photographer Jessica Wynne spotlights the chalkboards of mathematicians, including Professor Alexei Borodin’s and Associate Professor Ankur Moitra’s, reports Clara Moskowitz for Scientific American

Wired

Wired reporter Will Knight spotlights how MIT researchers have showed that “an AI program trained to verify that code will run safely can be deceived by making a few careful changes, like substituting certain variables, to create a harmful program.”

Quartz

MIT researchers are applying machine learning algorithms typically used for natural language processing to identify coronavirus variants, reports Brian Browdie for Quartz. “Besides being able to quantify the potential for mutations to escape, the research may pave the way for vaccines that broaden the body’s defenses against variants or that protect recipients against more than one virus, such as flu and the novel coronavirus, in a single shot,” writes Browdie. 

Mashable

CSAIL researchers have developed a new material with embedded sensors that can track a person’s movement, reports Mashable. The clothing could “track things like posture or give feedback on how you’re walking.”

Fast Company

Fast Company reporter Elizabeth Segran spotlights how CSAIL researchers have crafted a new smart fabric embedded with sensors that can sense pressure from the person wearing it. “Sensors in this new material can be used to gather data about people’s posture and body movements,” writes Segran. “This could be useful in a variety of settings, including athletic training, monitoring the health of elderly patients, and identifying whether someone has fallen over.”

Wired

Wired reporter Will Knight writes that MIT researchers have found that many of the key AI data sets used to train algorithms could contain many errors. “What this work is telling the world is that you need to clean the errors out,” says graduate student Curtis Northcutt. “Otherwise the models that you think are the best for your real-world business problem could actually be wrong.”

Boston.com

Boston.com reporter Mark Gartsbeyn spotlights “Coded Bias,” a new documentary that chronicles graduate student Joy Buolamwini’s work uncovering bias in AI systems. Gartsbeyn writes that in 2018, Buolamwini “co-authored an influential study showing that commercially available facial recognition programs had serious algorithmic bias against women and people of color.”

The Economist

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.”

Wired

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.

The Guardian

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.

New York Times

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.”

New Scientist

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.

The Wall Street Journal

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

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

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.”