USA Today reporter Barbara VanDenburgh spotlights Media Lab research specialist Kate Darling’s new book, “The New Breed: What Our History with Animals Reveals about Our Future with Robots.” VanDenburgh writes that in the book, “An MIT Media Lab researcher and technology policy expert argues that treating robots more like we treat animals, with a bit of humanity, will serve mankind well.”
Writing for Wired, Media Lab research specialist Kate Darling makes the case that robots are more like animals than people. “Despite the AI pioneers’ original goal of recreating human intelligence, our current robots are fundamentally different,” writes Darling. “They’re not less-developed versions of us that will eventually catch up as we increase their computing power; like animals, they have a different type of intelligence entirely.”
Rebellions Inc., a company founded by alumnus Park Sunghyun S.M. ’11, PhD ’14, is developing a microchip aimed at “running artificial intelligence more efficiently, which could cut precious millionths of a second off the reaction times of automatic-trading machines,” reports Hooyeon Kim and Whanwoong Choi for Bloomberg.
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.
MIT researchers have developed a new robot, dubbed RF Grasp, that can sense hidden objects using radio waves, reports Brian Heater for TechCrunch. “The tech allows RF Grasp to pick up things that are covered up or otherwise out of its line of vision,” writes Heater.
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.”
TechCrunch reporter Brian Heater spotlights how MIT researchers have devised a neural network to help optimize sensor placement on soft robots to help give them a better picture of their environment.
Boston Globe reporter Andy Rosen writes that the Broad Institute of MIT and Harvard has launched “a new, $300 million initiative that applies advanced computer science to some of the hardest problems in medicine — an endeavor it said could uncover new ways to fight cancer, infectious disease, and other illnesses.”
Graduate student Joy Buolamwini speaks with Molly Wood of Marketplace about her work uncovering bias in AI systems and her calls for greater oversight of facial recognition systems. “We need the laws, we need the regulations, we need an external pressure, and that’s when companies respond,” says Buolamwini. “But the change will not come from within alone because the incentives are not aligned.”
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.”
Writing for Forbes, research affiliate Tom Davenport spotlights how Stitch Fix “uses AI algorithms and human stylists working in combination to make recommendations to clients of items of clothing, shoes, or accessories.”
Research scientist Andreas Mershin speaks with Noam Hassenfeld of Vox about his work developing a new AI system that could be used to detect disease using smell.
A new AI-powered system developed by researchers from MIT and other institutions can detect prostate cancer in urine samples as accurately as dogs can, reports Tanya Lewis and Prachi Patel for Scientific American. “We found we could repeat the training you use for dogs on the machines until we can’t tell the difference between the two,” says research scientist Andreas Mershin.
Elisabeth Reynolds, executive director of the MIT Task Force on the Work of the Future, speaks with Soledad O’Brien about how to ensure workers aren’t left behind in the transition to a more digital workforce. “If we can find pathways to the middle where we do see growth and demand for workers - construction, healthcare, the trades, manufacturing, places where we are seeing opportunities - that move can really be a new lifeline for people,” says Reynolds.
ITV reporter Liz Summers spotlights how researchers from MIT and other institutions have developed a new system that could eventually be used to help detect diseases via smell. The researchers hope the results could “eventually result in the production of a ‘robotic nose’ perhaps in the form of a smartphone app.”