One of the most promising new cancer therapies involves engineering cells from the body's own immune system to attack tumors, but tuning those attackers to spare healthy tissues has been challenging.
A small drone takes a test flight through a space filled with randomly placed cardboard cylinders acting as stand-ins for trees, people or structures. The algorithm controlling the drone has been trained on a thousand simulated obstacle-laden courses, but it’s never seen one like this. Still, nine times out of 10, the pint-sized plane dodges...
With the launch of the Gaia satellite in 2013, scientists have been receiving an unprecedented quantity and quality of data on a billion stars in the Milky Way. But the data sets are incomplete. Gaia does not currently provide the complete position and velocity coordinates for all billion stars.
It is common for researchers to conduct field studies to study mass social behavior in online networks, such as Facebook or Reddit. These studies lead to qualitative-based conclusions. However, until recently, replicating these interactions in the lab and at scale has been hard to do.
Over the last several years, researchers have developed advanced machine learning tools to provide captions for still images and video. Applications for advanced image caption tools could include an assistant robot for the visually impaired or a robot that performs reconnaissance missions in environments inhospitable to humans...
Neural networks can study and model complex conditions at the macro scale, such as weather patterns or the movement of heavenly bodies, but researchers at Princeton University have also been applying this tool to ever smaller objects, yielding potentially valuable contributions for chemistry, physics and quantum computing.
Tabitha Belshee, 22, Class of 2020
Prateek Mittal, associate professor of electrical engineering at Princeton University, is here to discuss his team's research into how hackers can use adversarial tactics toward artificial intelligence to take advantage of us and our data.
Researchers at Princeton University have developed a tool that flags potential biases in sets of images used to train artificial intelligence (AI) systems. The work is part of a larger effort to remedy and prevent the biases that have crept into AI systems that influence everything from credit services to courtroom sentencing programs.