Sometimes it’s easy to forget how good we humans are at understanding our surroundings. Without much thinking, we can describe objects and how they interact with each other.
Sometimes it’s easy to forget how good we humans are at understanding our surroundings. Without much thinking, we can describe objects and how they interact with each other.
EECS faculty head of artificial intelligence and decision making honored for significant and extended contributions to the field of AI.
The event welcomed graduate students and postdocs of historically underrepresented genders. Panelists advised the Rising Stars on how to pursue academic careers in electrical engineering, computer science, and AI and decision-making.
Selecting the right method gives users a more accurate picture of how their model is behaving, so they are better equipped to correctly interpret its predictions.
The framework helps clinicians choose phrases that more accurately reflect the likelihood that certain conditions are present in X-rays.
A new “common-sense” approach to computer vision enables artificial intelligence that interprets scenes more accurately than other systems do.
A multimodal system uses models trained on language, vision, and action data to help robots develop and execute plans for household, construction, and manufacturing tasks.
Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
Joining three teams backed by a total of $75 million, MIT researchers will tackle some of cancer’s toughest challenges.