3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities
MIT CSAIL Principal Research Scientist Una-May O’Reilly discusses how she develops agents that reveal AI models’ security weaknesses before hackers do.
MIT CSAIL Principal Research Scientist Una-May O’Reilly discusses how she develops agents that reveal AI models’ security weaknesses before hackers do.
Projects from MIT course 4.043/4.044 (Interaction Intelligence) were presented at NeurIPS, showing how AI transforms creativity, education, and interaction in unexpected ways.
Sometimes, it might be better to train a robot in an environment that’s different from the one where it will be deployed.
Associate Professor Luca Carlone is working to give robots a more human-like awareness of their environment.
Station A, founded by MIT alumni, makes the process of buying clean energy simple for property owners.
Starting with a single frame in a simulation, a new system uses generative AI to emulate the dynamics of molecules, connecting static molecular structures and developing blurry pictures into videos.
Providing electricity to power-hungry data centers is stressing grids, raising prices for consumers, and slowing the transition to clean energy.
Rapid development and deployment of powerful generative AI models comes with environmental consequences, including increased electricity demand and water consumption.
Assistant Professor Manish Raghavan wants computational techniques to help solve societal problems.
The startup NALA, which began as an MIT class project, directly matches art buyers with artists.
With their recently-developed neural network architecture, MIT researchers can wring more information out of electronic structure calculations.
Machine-learning models let neuroscientists study the impact of auditory processing on real-world hearing.
As the use of generative AI continues to grow, Lincoln Laboratory's Vijay Gadepally describes what researchers and consumers can do to help mitigate its environmental impact.
Inspired by the human vocal tract, a new AI model can produce and understand vocal imitations of everyday sounds. The method could help build new sonic interfaces for entertainment and education.
Using this model, researchers may be able to identify antibody drugs that can target a variety of infectious diseases.