Computer vision enables contact-free 3D printing, letting engineers print with high-performance materials they couldn’t use before.

By blending 2D images with foundation models to build 3D feature fields, a new MIT method helps robots understand and manipulate nearby objects with open-ended language prompts.

AI models that prioritize similarity falter when asked to design something completely new.

Inspired by physics, a new generative model PFGM++ outperforms diffusion models in image generation.

The machine-learning method works on most mobile devices and could be expanded to assess other motor disorders outside of the doctor’s office.

Researchers use synthetic data to improve a model’s ability to grasp conceptual information, which could enhance automatic captioning and question-answering systems.

The system could improve image quality in video streaming or help autonomous vehicles identify road hazards in real-time.

The challenge involves than just a blurry JPEG. Fixing motion artifacts in medical imaging requires a more sophisticated approach.

“PhotoGuard,” developed by MIT CSAIL researchers, prevents unauthorized image manipulation, safeguarding authenticity in the era of advanced generative models.

The dataset, being collected as part of a US Coast Guard science mission, will be released open source to help advance naval mission planning and climate change studies.