From physics to generative AI: An AI model for advanced pattern generation
Inspired by physics, a new generative model PFGM++ outperforms diffusion models in image generation.
Inspired by physics, a new generative model PFGM++ outperforms diffusion models in image generation.
The 27 finalists — representing every school at MIT — will explore the technology’s impact on democracy, education, sustainability, communications, and much more.
MIT Plasma Science and Fusion Center will receive DoE support to improve access to fusion data and increase workforce diversity.
The MIT Schwarzman College of Computing awards seed grants to seven interdisciplinary projects exploring AI-augmented management.
A new study bridging neuroscience and machine learning offers insights into the potential role of astrocytes in the human brain.
Training artificial neural networks with data from real brains can make computer vision more robust.
MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single system.
MIT students share ideas, aspirations, and vision for how advances in computing stand to transform society in a competition hosted by the Social and Ethical Responsibilities of Computing.
Recipients Luis Antonio Benítez, Carolina Cuesta-Lazaro, and Fernando Romero López receive support for their scientific research.
The inaugural SERC Symposium convened experts from multiple disciplines to explore the challenges and opportunities that arise with the broad applicability of computing in many aspects of society.