In a new paper, MIT researchers detail the use of reinforcement learning to teach MIT’s mini cheetah robot to play goalie in a soccer match, reports Brian Heater for TechCrunch. “In this work, we focused solely on the goalkeeping task, but the proposed framework can be extended to other scenarios, such as multi-skill soccer ball kicking,” the researchers explain.
Researchers from MIT and the Amsterdam Institute for Advanced Metropolitan Solutions have been developing an electric autonomous trash boat, reports Sarah Holder for Bloomberg. The boats “could reduce noise, pollution, and congestion, thus improving the quality of Amsterdam’s historic cityscape.”
Institute Prof. Barbara Liskov discusses the importance of including ethics and foresight as a key parts of computer science education, reports Susan D'Agostino for Inside Higher Ed. “The days of being naïvely technical, which we were for many years, are over,” says Liskov. “We need to open students’ minds so they think about the harm that can come from what they’re doing and so they ask, ‘What could I add that could act as a safeguard?’ It’s more than ethics. They need to think from a different perspective.”
At MIT’s AI Policy Forum Summit, which was focused on exploring the challenges facing the implementation of AI technologies across a variety of sectors, SEC Chair Gary Gensler and MIT Schwarzman College of Computing Dean Daniel Huttenlocher discussed the impact of AI on the world of finance. “If someone is relying on open-AI, that's a concentrated risk and a lot of fintech companies can build on top of it,” Gensler said. “Then you have a node that's every bit as systemically relevant as maybe a stock exchange."
Prof. Cynthia Breazeal discusses her work exploring how artificial intelligence can help students impacted by Covid, including refugees or children with disabilities, reports Ryan Heath for Politico. “We want to be super clear on what the role is of the robot versus the community, of which this robot is a part of. That's part of the ethical design thinking,” says Breazeal. “We don't want to have the robot overstep its responsibilities. All of our data that we collect is protected and encrypted.”
MIT researchers have developed a new in-home device that can help monitor Parkinson’s patients by tracking their gait, reports Hiawatha Bray for The Boston Globe. “We know very little about the brain and its diseases,” says Professor Dina Katabi. “My goal is to develop non-invasive tools that provide new insights about the functioning of the brain and its diseases.”
Popular Science reporter Philip Kiefer writes that MIT researchers have developed an in-home device that could be used to track the progression of symptoms in Parkinson’s patients. “We can’t really ask patients to come to the clinic every day or every week,” explains graduate student Yingcheng Liu. “This technology gives us the possibility to continuously monitor patients, and provide more objective assessments.”
TechCrunch reporter Kyle Wiggers spotlights DynamoFl, a company founded by Christian Lau PhD ’20 and Vaikkunth Mugunthan PhD ’22 that is developing a federated learning platform, a technique for preserving data privacy in AI systems.
Research scientist Barmak Heshmat, CEO and founder of MIT spinout Brelyon, speaks with TechCrunch reporter Haje Jan Kamps about the company’s work in immersive digital monitors. “Our logic is pretty simple: If we can give you even half of the immersion of headsets with a device that doesn’t have to sit on your face and works with all existing content, then that would be a much more compelling progression of your computer experience and thus a better bridge to the emerging metaverse,” says Heshmat.
Lawrence A. Tabak, who is currently performing the duties of the NIH Director, spotlights a new study by Prof. James Collins and his colleagues aimed at exploring the potential of AI to streamline the process of selecting new antibiotics. “In future studies, the Collins lab will continue to incorporate and train the computers on even more biochemical and biophysical data to help with the predictive process," Tabak writes. "That’s why this study should be interpreted as an interim progress report on an area of science that will only get better with time.”
Researchers from MIT are working with the Staten Island Performing Provider System to develop an algorithm that can predict who in the system is at risk for an opioid overdose, reports Maddie Bender for the Daily Beast. “In preliminary testing, Conte’s team and MIT Sloan researchers found their model was highly accurate at predicting overdoses and fatal overdoses, even with delays in the data of up to 180 days,” writes Bender.
Washington Post reporter Pranshu Verma writes about how Prof. Dina Katabi and her colleagues developed a new AI tool that could be used to help detect early signs of Parkinson’s by analyzing a patient’s breathing patterns. For diseases like Parkinson’s “one of the biggest challenges is that we need to get to [it] very early on, before the damage has mostly happened in the brain,” said Katabi. “So being able to detect Parkinson’s early is essential.”
MIT researchers have developed a new hardware that offers faster computation for artificial intelligence with less energy, reports Kyle Wiggers for TechCrunch. “The researchers’ processor uses ‘protonic programmable resistors’ arranged in an array to ‘learn’ skills” explains Wiggers.
Forbes contributor Jennifer Kite-Powell spotlights how MIT researchers created a new AI system that analyzes radio waves bouncing off a person while they sleep to monitor breathing patterns and help identify Parkinson’s disease. “The device can also measure how bad the disease has become and could be used to track Parkinson's progression over time,” writes Kite-Powell.
A new tool for diagnosing Parkinson’s disease developed by MIT researchers uses an AI system to monitor a person’s breathing patterns during sleep, reports Hiawatha Bray for The Boston Globe. “The system is capable of detecting the chest movements of a sleeping person, even if they’re under a blanket or lying on their side,” writes Bray. “It uses software to filter out all other extraneous information, until only the breathing data remains. Using it for just one night provides enough data for a diagnosis.”