Three students in the Statistics and Machine Learning minor have received special recognition for their research at the Center for Statistics and Machine Learning’s end-of-the-year celebration.
Center for Statistics and Machine Learning participating faculty Prateek Mittal has received an award from the University’s Intellectual Property (IP) Accelerator Fund to build a network monitoring framework to improve internet security.
On April 18, the Center for Statistics and Machine Learning and the Princeton Institute for Computational Science and Engineering hosted their annual joint research colloquium.
The Princeton AI Sandbox is a new tool from the Office of Information Technology in collaboration with research computing which aims to reduce the security risks posed by using LLMs. The sandbox provides a secure environment for Princeton University researchers to explore and use models for their projects.
“Thinking about scientific transparency in the age of AI is just absolutely crucial,” said Class of 1987 Professor of Politics at the Department of Politics at Princeton University Arthur Spirling.
“Dinner with a Professor serves as a special celebration of the strong connection between SML students and their faculty advisors and mentors.”
Rafael Pastrana, a Princeton University Ph.D candidate in architecture, is at work developing and exploring his own methods of computing structural shapes that are both functional and judicious in the use of materials. “One of the secret sauces powering the methods I work with to create good shapes is machine learning,” said Pastrana.
In the same way that a dog can be trained to roll over in exchange for treats, reinforcement learning algorithms can train AI systems to learn to maximize rewards via trial and error.
Reinforcement learning methods enable AI systems to find strategies that are better than those used by humans, as demonstrated by…
On Feb. 28, more than 80 researchers from the Princeton Plasma Physics Laboratory and Princeton University gathered together in the Lewis Science Library to test some of the latest artificial intelligence tools.
“By leveraging fundamentally different physics, we can better align with the computations AI is doing,” said Professor of Electrical and Computer Engineering Naveen Verma. “Our work goes all the way from building the circuits that leverage physics in large-scale chips, to building the software.”