Modeling relationships to solve complex problems efficiently
Associate Professor Julian Shun develops high-performance algorithms and frameworks for large-scale graph processing.
MIT Schwarzman College of Computing
How AI is improving simulations with smarter sampling techniques
MIT CSAIL researchers created an AI-powered method for low-discrepancy sampling, which uniformly distributes data points to boost simulation accuracy.
Q&A: A new initiative to help strengthen democracy
David Singer, head of the MIT Department of Political Science, discusses the Strengthening Democracy Initiative, focused on the rigorous study of elections, public opinion, and political participation.
AI pareidolia: Can machines spot faces in inanimate objects?
New dataset of “illusory” faces reveals differences between human and algorithmic face detection, links to animal face recognition, and a formula predicting where people most often perceive faces.
Helping robots zero in on the objects that matter
A new method called Clio enables robots to quickly map a scene and identify the items they need to complete a given set of tasks.
MIT launches new Music Technology and Computation Graduate Program
The program will invite students to investigate new vistas at the intersection of music, computing, and technology.
New security protocol shields data from attackers during cloud-based computation
The technique leverages quantum properties of light to guarantee security while preserving the accuracy of a deep-learning model.
3 Questions: Should we label AI systems like we do prescription drugs?
Researchers argue that in health care settings, “responsible use” labels could ensure AI systems are deployed appropriately.
Study: AI could lead to inconsistent outcomes in home surveillance
Researchers find large language models make inconsistent decisions about whether to call the police when analyzing surveillance videos.
Enhancing LLM collaboration for smarter, more efficient solutions
“Co-LLM” algorithm helps a general-purpose AI model collaborate with an expert large language model by combining the best parts of both answers, leading to more factual responses.