Researchers at MIT have predicted that without improvements in hardware efficiency, energy consumption and emissions from autonomous vehicles could be “comparable to that of data centers today,” reports Sarah Wells for Popular Mechanics. “In order to reduce the future carbon footprint of AVs, scientists will need to make the computing systems of AVs, including smart sensors, far more efficient,” writes Wells.
Researchers at MIT developed a system that uses artificial intelligence to help predict future risk of developing breast cancer, reports Poppy Harlow for CNN. What this work does “is identifies risk. It can tell a woman that you’re at high risk for developing breast cancer before you develop breast cancer,” says Larry Norton, medical director of the Lauder Breast Center at the Memorial Sloan Kettering Cancer Center.
Joy Buolamwini PhD ’22 has been named one of Diverse: Issues in Higher Education’s Top Women for 2023 for her work in developing “more equitable and accountable technology.” Buolamwini “uncovered racial and gender bias in AI services from high profile companies such as Microsoft, IBM and Amazon. Now a sought-after international speaker, Buolamwini continues to advocate for algorithmic justice,” writes Diverse: Issues in Higher Education.
Writing for The Wall Street Journal, Dean Daniel Huttenlocher, former Secretary of State Henry Kissinger and former Google CEO Eric Schmidt explore how generative artificial intelligence “presents a philosophical and practical challenge on a scale not experienced since the beginning of the Enlightenment.” Huttenlocher, Kissinger and Schmidt make the case that “parameters for AI’s responsible use need to be established, with variation based on the type of technology and the context of deployment.”
MIT researchers have constructed a mini city to test to safely test algorithms designed for autonomous vehicles, reports Mashable. “The idea of the mini city is that we have lots of cars going at the same time and we can actually test out new algorithms in a safe environment,” says graduate student Noam Buckman.
Boston Globe reporter Aaron Pressman spotlights several MIT startups that are using AI to generate 3-D environments. Common Sense Machines, an MIT startup, is “trying to enhance the creativity of its app by adding a bit of, well, common sense,” writes Pressman. “Human babies form an understanding of the world by developing abstract models. Common Sense Machines is trying to add similar models to its 3D world builder.”
Motherboard reporter Tatyana Woodall writes that a new study co-authored by MIT researchers finds that AI models that can learn to perform new tasks from just a few examples create smaller models inside themselves to achieve these new tasks. “Learning is entangled with [existing] knowledge,” graduate student Ekin Akyürek explains. “We show that it is possible for these models to learn from examples on the fly without any parameter update we apply to the model.”
Researchers at MIT and Massachusetts General Hospital have developed “Sybil” – an artificial intelligence tool that can predict the risk of a patient developing lung cancer within six years, reports Mallika Marshall for CBS Boston.
CSAIL researchers are developing a drone that could be used to assist humans in search and rescue operations, reports Mashable. “If you are trying to detect someone in an avalanche and you can maybe just send a drone, and if they can find them out and then fly towards them and send a help signal. It would be probably be something that would be beneficial to people as an immediate application.”
Prof. Daniela Rus, director of CSAIL, speaks with Popular Science reporter Charlotte Hu about the field of artificial intelligence, explaining the difference between AI, robotics and machine learning, and exploring the future of AI. “[AI algorithms] can do really extraordinary things much faster than we can. But the way to think about it is that they’re tools that are supposed to augment and enhance how we operate,” says Rus. “And like any other tools, these solutions are not inherently good or bad. They are what we choose to do with them.”
Researchers at MIT have developed an autonomous vehicle with “mini sensors to allow it to see the world and also with an artificially intelligent computer brain that can allow it to drive,” explains postdoctoral associate Alexander Amini in an interview with Mashable. “Our autonomous vehicles are able to learn directly from humans how to drive a car so they can be deployed and interact in brand new environments that they’ve never seen before,” Amini notes.
MIT researchers have developed a new AI tool called Sybil that could help predict whether a patient will get lung cancer up to six years in advance, reports Pranshu Verma for The Washington Post. “Much of the technology involves analyzing large troves of medical scans, data sets or images, then feeding them into complex artificial intelligence software,” Verma explains. “From there, computers are trained to spot images of tumors or other abnormalities.”
An MIT study has found that the wide spread adoption of self-driving cars could lead to increased carbon emissions, reports Rima Sabina Aouf for Dezeen. “The study found that with a mass global take up of autonomous vehicles, the powerful onboard computers needed to run them could generate as many greenhouse gas emissions as all the data centers in operation today,” writes Aouf.
Prof. Nick Montfort speaks with GBH All Things Considered host Arun Rath about ChatGPT, its potential impact on the future of academia and how instructors could adapt their courses in light of this new technology.
Research fellow Michael Schrage speaks with Fortune reporter Sheryl Estrada about how generative A.I. will impact finance. “I think, increasingly, we’re going to be seeing generative A.I. used for financial forecasts and scenario generation,” says Schrage.