Posted by Edith Cohen and Uri Stemmer, Research Scientists, Google Research Differential privacy (DP) is a rigorous mathematical definition of privacy. DP algorithms are randomized to protect user data by ensuring that the probability of any particular output is nearly unchanged when a data point is added or removed. Therefore, the output of a DP…
Computing is at an inflection point. Moore’s Law, which predicts that the number of transistors on an electronic chip will double each year, is slowing down due to the physical limits of fitting more transistors on affordable microchips. These increases in computer power are slowing down as the demand grows for high-performance computers that can…
“As a child, I wished for a robot that would explain others’ emotions to me” says Sharifa Alghowinem, a research scientist in the Media Lab’s Personal Robots Group (PRG). Growing up in Saudi Arabia, Alghowinem says she dreamed of coming to MIT one day to develop Arabic-based technologies, and of creating a robot that could…
Smart thermostats have changed the way many people heat and cool their homes by using machine learning to respond to occupancy patterns and preferences, resulting in a lower energy draw. This technology — which can collect and synthesize data — generally focuses on single-dwelling use, but what if this type of artificial intelligence could dynamically…
After three years leading biking tours through U.S. National Parks, Jackson Jewett decided it was time for a change. “It was a lot of fun, but I realized I missed buildings,” says Jewett. “I really wanted to be a part of that industry, learn more about it, and reconnect with my roots in the built…
Posted by Shantanu Shahane, Software Engineer, and Matthias Ihme, Research Scientist, Athena Team Turbulence is ubiquitous in environmental and engineering fluid flows, and is encountered routinely in everyday life. A better understanding of these turbulent processes could provide valuable insights across a variety of research areas — improving the prediction of cloud formation by atmospheric…
Posted by Si-An Chen, Student Researcher, Cloud AI Team, and Chun-Liang Li, Research Scientist, Cloud AI Team Time series forecasting is critical to various real-world applications, from demand forecasting to pandemic spread prediction. In multivariate time series forecasting (forecasting multiple variants at the same time), one can split existing methods into two categories: univariate models…
This story first appeared in China Report, MIT Technology Review’s newsletter about technology developments in China. Sign up to receive it in your inbox every Tuesday. Chinese ChatGPT-like bots are having a moment right now. As I reported last week, Baidu became the first Chinese tech company to roll out its large language model—called Ernie Bot—to the…
In the past year, kids, teachers, and parents have had a crash course in artificial intelligence, thanks to the wildly popular AI chatbot ChatGPT. In a knee-jerk reaction, some schools, such as the New York City public schools, banned the technology—only to cancel the ban months later. Now that many adults have caught up with…
AI language models are not humans, and yet we evaluate them as if they were, using tests like the bar exam or the United States Medical Licensing Examination. The models tend to do really well in these exams, probably because examples of such exams are abundant in the models’ training data. Yet, as my colleague…