Researchers use AI to identify similar materials in images
This machine-learning method could assist with robotic scene understanding, image editing, or online recommendation systems.
This machine-learning method could assist with robotic scene understanding, image editing, or online recommendation systems.
Senior Ananya Gurumurthy adds her musical talents to her math and computer science studies to advocate using data for social change.
With the artificial intelligence conversation now mainstream, the 2023 MIT-MGB AI Cures conference saw attendance double from previous years.
A new machine-learning model makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue.
In their new book, “Power and Progress,” Daron Acemoglu and Simon Johnson ask whether the benefits of AI will be shared widely or feed inequality.
Leo Anthony Celi invites industry to broaden its focus in gathering and analyzing clinical data for every population.
The CSAIL scientist describes natural language processing research through state-of-the-art machine-learning models and investigation of how language can enhance other types of artificial intelligence.
Models trained using common data-collection techniques judge rule violations more harshly than humans would, researchers report.
Citadel founder and CEO Ken Griffin visits MIT, discusses how technology will continue to transform trading and investing.
Matt Shoulders will lead an interdisciplinary team to improve RuBisCO — the photosynthesis enzyme thought to be the holy grail for improving agricultural yield.
A new computer vision system turns any shiny object into a camera of sorts, enabling an observer to see around corners or beyond obstructions.
Researchers identify a property that helps computer vision models learn to represent the visual world in a more stable, predictable way.
Jeff Wilke SM '93, former CEO of Amazon’s Worldwide Consumer business, brings his LGO playbook to his new mission of revitalizing manufacturing in the U.S.
The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.
A collaborative research team from the MIT-Takeda Program combined physics and machine learning to characterize rough particle surfaces in pharmaceutical pills and powders.