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.
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.”
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.
Researchers from the MIT-IBM Watson AI Lab and the Harvard Natural Language Processing Group developed the Giant Language model Test Room (GLTR), an algorithm that attempts to detect if text was written by a bot, reports Megan Morrone for Fast Company. “Using the ‘it takes one to know one’ method, if the GLTR algorithm can predict the next word in a sentence, then it will assume that sentence has been written by a bot,” explains Morrone.
MIT spinout Gaia A is developing a forest management building tool aimed at providing foresters with the resources to make data-driven decisions, reports Haje Jan Kamps and Brian Heater for TechCrunch. “The company is currently using lidar and computer vision tech to gather data but is ultimately building a data platform to tackle some of the big questions in forestry,” writes Kamps and Heater.
Rosina Samadani ’89, MS ’92 co-developed EyeBox, an algorithm-based non-invasive diagnostic test for concussions, reports Geri Stengel for Forbes. “Patients watch a video, and the device watches their eyes for 220 seconds with a very high-quality, high-frequency infrared camera that measures eye movements and provides a score based on those eye movements,” explains Stengel. “The score is correlated with the absence or presence of a concussion.”
Research affiliate Ramin Hasani speaks with Kimberly Adams of Marketplace about how he and his CSAIL colleagues solved a differential equation dating back to the early 1900s, enabling researchers to create an AI algorithm that can learn on the spot and adapt to evolving patterns. The new algorithm “will enable larger-scale brain simulations,” Hasani explains.
Popular Science reporter Charlotte Hu writes that MIT researchers have developed a new machine learning model that can depict how the sound around a listener changes as they move through a certain space. “We’re mostly modeling the spatial acoustics, so the [focus is on] reverberations,” explains graduate student Yilun Du. “Maybe if you’re in a concert hall, there are a lot of reverberations, maybe if you’re in a cathedral, there are many echoes versus if you’re in a small room, there isn’t really any echo.”
Scientists at MIT have developed “a machine learning model that can capture how sounds in a room will propagate through space,” report Kyle Wiggers and Devin Coldewey for TechCrunch. “By modeling the acoustics, the system can learn a room’s geometry from sound recordings, which can then be used to build a visual rendering of a room,” write Wiggers and Coldewey.
Writing for The Wall Street Journal, MIT Prof. Katherine Kellogg and Stanford Prof. Melissa Valentine explore the challenges of introducing AI technologies in the workplace, focusing on the fashion industry. "Getting workers to actually use the technologies will turn out to be just as important as making sure the systems work in the first place," they write.
Prof. Peter Shor has been named one of the winners of the 2023 Breakthrough Prize in Fundamental Physics, reports Nature. “Shor’s most renowned contribution is the development of quantum algorithms for prime number factorization,” writes Nature.
Researchers at MIT are working on a system that can track the development of Parkinson’s disease by monitoring a person’s gait speed, reports Kyle Wiggers and Devin Coldewey for TechCrunch. “The MIT Parkinson’s-tracking effort aims to help clinicians overcome challenges in treating the estimated 10 million people afflicted by the disease globally,” writes Wiggers and Coldewey.
MIT’s mini cheetah robot was taught how to goal keep using simulation, reports Emmett Smith for Mashable. “The robot was able to block 87.5 percent of the shots taken, which is just slightly above the best professional goalies in the English Premiere League,” writes Smith.
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.