Principal Research Scientist Leo Anthony Celi oversaw a study which found that people of color were given significantly less supplemental oxygen than white people because of inaccuracies in pulse oximeter readings, reports Nancy Lapid for Reuters. “Nurses and doctors make the wrong decisions and end up giving less oxygen to people of color because they are fooled [by incorrect readings from pulse oximeters],” says Celi.
Researchers at MIT have created a knit textile containing pressure sensors called 3DKnITS which can be used to predict a person’s movements, reports Charlotte Hu for Popular Science. “Smart textiles that can sense how users are moving could be useful in healthcare, for example, for monitoring gait or movement after an injury,” writes Hu.
A study co-authored by MIT researchers finds that algorithms based on clinical medical notes can predict the self-identified race of a patient, reports Katie Palmer for STAT. “We’re not ready for AI — no sector really is ready for AI — until they’ve figured out that the computers are learning things that they’re not supposed to learn,” says Principal Research Scientist Leo Anthony Celi.
Ken Knowlton PhD ’62 - a pioneer in the science and art of computer graphics and the creator of some of the first computer-generated pictures, portraits and movies - died June 16 at the age of 91, reports Cade Metz for The New York Times. “Knowlton was the only person to ever use the BEFLIX language – he and his colleagues quickly replaced it with other tools and techniques – the ideas behind this technology would eventually overhaul the movie business,” writes Metz.
CSAIL graduate student Yunzhu Li and his colleagues have trained a robot to use two metal grippers to mold letters out of play dough, reports Jeremy Hsu for New Scientist. "Li and his colleagues trained a robot to use two metal grippers to mould the approximate shapes of the letters B, R, T, X and A out of Play-Doh," explains Hsu. "The training involved just 10 minutes of randomly manipulating a block of the modelling clay beforehand, without requiring any human demonstrations."
Graduate student Anna Ivanova and University of Texas at Austin Professor Kyle Mahowald, along with Professors Evelina Fedorenko, Joshua Tenenbaum and Nancy Kanwisher, write for The Conversation that even though AI systems may be able to use language fluently, it does not mean they are sentient, conscious or intelligent. “Words can be misleading, and it is all too easy to mistake fluent speech for fluent thought,” they write.
TechCrunch reporter Brian Heater spotlights multiple MIT research projects, including MIT Space Exploration Initiative’s TESSERAE, CSAIL’s Robocraft and the recent development of miniature flying robotic drones.
Prof. Pattie Maes, and graduate students Valdemar Danry, Joanne Leong and Pat Pataranutaporn speak with Forbes reporter Stephen Ibaraki about their work in the MIT Media Lab Fluid Interfaces research group. “Their highly interdisciplinary work covering decades of MIT Lab pioneering inventions integrates human computer interaction (HCI), sensor technologies, AI / machine learning, nano-tech, brain computer interfaces, design and HCI, psychology, neuroscience and much more,” writes Ibaraki.
MIT researchers have developed a new computational model that could be used to help explain differences in how neurotypical adults and adults with autism recognize emotions via facial expressions, reports Tony Ho Tran for The Daily Beast. “For visual behaviors, the study suggests that [the IT cortex] pays a strong role,” says research scientist Kohitij Kar. “But it might not be the only region. Other regions like amygdala have been implicated strongly as well. But these studies illustrate how having good [AI models] of the brain will be key to identifying those regions as well.”
Scientists from MIT, Georgia Institute of Technology, Sun Yat-sen University and Beijing-based AI startup Galixir have developed a deep-learning toolkit that can predict biosynthetic pathways for natural products, which are a primary source of clinical drug discovery, reports Xinhua Net. “The researchers presented a toolkit called Bionavi-NP to propose NP biosynthetic pathways from simple building blocks in an oprtimal fashion, which requires no already-known biochemical rules,” writes Xinhua Net.
Popular Science reporter Charlotte Hu writes that MIT researchers have developed an “electronics chip design that allows for sensors and processors to be easily swapped out or added on, like bricks of LEGO.” Hu writes that “a reconfigurable, modular chip like this could be useful for upgrading smartphones, computers, or other devices without producing as much waste.”
MIT engineers have developed a wireless, reconfigurable chip that could easily be snapped onto existing devices like a LEGO brick, reports Miriam Fauzia for The Daily Beast. “Having the flexibility to customize and upgrade an old device is a modder’s dream,” writes Fauzia, “but the chip may also help reduce electronic waste, which is estimated at 50 million tons a year worldwide.”
Tom Davenport, a visiting scholar at the MIT Initiative on the Digital Economy, writes for Forbes about Telstra Ventures, a venture capitalist firm that invests in tech firms and its incorporation of data science into its investing criteria. “It seems inevitable that other venture capitalist firms will begin to make more data and analytics-driven decisions in the future,” writes Davenport.
TechCrunch reporters Kyle Wiggers and Devin Coldewey spotlight how MIT researchers developed a new technique for simulating an overall system of independent agents: self-driving cars. “The idea is that if you have a good amount of cars on the road, you can have them work together not just to avoid collisions but to prevent idling and unnecessary stops at lights,” write Wiggers and Coldewey.
Researchers at MIT and Harvard Medical School have created an artificial intelligence program that can accurately identify a patient’s race based off medical images, reports Tony Ho Tran for The Daily Beast. “The reason we decided to release this paper is to draw attention to the importance of evaluating, auditing, and regulating medical AI,” explains Principal Research Scientist Leo Anthony Celi.