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.
Prof. Daniela Rus, director of CSAIL, discusses the future of artificial intelligence, emphasizing the importance of balancing the development of new technologies with the need to ensure they are deployed in a way that benefits humanity. “We have to advance the science and engineering of autonomy and the science and engineering of intelligence to create the kinds of machines that will be friendly to people, that will be assistive and supportive for people and that will augment people with the tasks that they need help with,” Rus explains.
A new study by MIT researchers finds that “the energy required to run computers in a future global fleet of autonomous vehicles could produce as much greenhouse gas emissions as all the data centers in the world,” reports Sharon Udasin for The Hill. The researchers found that “1 billion such cars, each driving for an hour daily, would use enough energy to generate the same amount of emissions that data centers do today.”
NBC 1st Look host Chelsea Cabarcas visits MIT to learn more about how faculty, researchers and students are “pioneering the world of tomorrow.” Cabarcas meets the MIT Solar Electric Vehicle team and gets a peek at Nimbus, the single-occupant vehicle that team members raced in the American Solar Challenge from Kansas City to New Mexico. Cabarcas also sees the back-flipping MIT mini cheetah that could one day be used in disaster-relief operations.
Politico reporter Derek Robertson writes that a new study by MIT researchers finds the computing power required to replace the world’s auto fleet with AVs would produce about the same amount of greenhouse gas emissions as all the data centers currently operating. Robertson writes that the researchers view the experiment “as an important step in getting auto- and policymakers to pay closer attention to the unexpected ways in which the carbon footprint for new tech can increase.”
Researchers from MIT and Harvard have developed “a new type of electrically conductive hydrogel ‘scaffold’ that could eventually be used to create a soft brain-computer interface (or BCI) that translates neural signals from the brain into machine-readable instructions,” reports Adam Bluestein for Fast Company.
Graduate student Soumya Sudhakar speaks with BBC Digital Planet host Gareth Mitchell about her new study showing that hardware efficiency for self-driving cars will need to advance rapidly to avoid generating as many greenhouse gas emissions as all the data centers in the world.
Researchers from MIT and Mass General Hospital have developed “a deep learning model named ‘Sybil’ that can be used to predict lung cancer risk, using data from just a single CT scan,” writes Sai Balasubramanian for Forbes. “Sybil is able to predict a patient’s future lung cancer risk to a certain extent of accuracy, using the data from just one LDCT [low-dose computed tomography scan],” writes Balasubramanian.
Using statistical modeling, MIT researchers have found that the energy needed to power a fleet of fully autonomous EVs could generate as much carbon emissions as all the world’s data centers combined, reports Andrew Paul for Popular Science.
Washington Post reporter Pranshu Verma writes that a new study by MIT researchers finds the “future energy required to run just the computers on a global fleet of autonomous vehicles could generate as much greenhouse gas emissions as all the data centers in the world today.”
Kevin Hu SB ’13, SM ’15, PhD ’19 co-founded Metaplane, a startup aimed at providing users with data analytics-focused tools, reports Kyle Wiggers for TechCrunch. “Metaplane monitors data using anomaly detection models trained primarily on historical metadata. The monitors try to account for seasonality, trends and feedback from customers, Hu says, to minimize alert fatigue, “writes Wiggers.
A review led Prof. Marzyeh Ghassemi has found that a major issue in health-related machine learning models “is the relative scarcity of publicly available data sets in medicine,” reports Emily Sohn for Nature.
Research scientist Ryan Hamerly and his team are working to harness “the low power consumption of hybrid optical devices for smart speakers, lightweight drones and even self-driving cars,” reports The Economist.