Prof. Aleksander Mądry’s testimony before a House subcommittee was highlighted by Politico fellow Mohar Chatterjee in a recent newsletter exploring how large tech companies are dominating how generative AI technologies are developed and utilized. During his testimony, Mądry emphasized that “very few players will be able to compete, given the highly specialized skills and enormous capital investments the building of such systems requires.”
Using an artificial intelligence system, researchers at MIT and elsewhere have developed a new Covid-19 vaccine that could be effective against current and future strains, reports Gwen Egan for Boston.com. “The vaccine differs from others currently on the market due to the portion of the virus being targeted,” writes Egan.
Boston Globe reporter Hiawatha Bray writes that MIT researchers have used an AI system to identify a potential new Covid-19 vaccine that may be effective against both current and future variants of the virus. “The new vaccine targets a portion of the COVID virus that is much less prone to evolve,” writes Bray. “That could potentially make it effective against many different versions of the virus, eliminating the need for routine booster shots.”
MIT researchers have developed a new approach to vaccines that uses “a machine learning twist [that] could put an end to boosters and seasonal variant shots,” reports Devin Coldewey for TechCrunch.
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.