Hybrid AI model crafts smooth, high-quality videos in seconds
The CausVid generative AI tool uses a diffusion model to teach an autoregressive (frame-by-frame) system to rapidly produce stable, high-resolution videos.
The CausVid generative AI tool uses a diffusion model to teach an autoregressive (frame-by-frame) system to rapidly produce stable, high-resolution videos.
Ukrainian students and collaborators provide high-quality translations of MIT OpenCourseWare educational resources.
A new method can train a neural network to sort corrupted data while anticipating next steps. It can make flexible plans for robots, generate high-quality video, and help AI agents navigate digital environments.
Researchers find large language models make inconsistent decisions about whether to call the police when analyzing surveillance videos.
Films produced by MIT Video Productions and the Department of Mechanical Engineering highlight some of MIT’s global conversations about the environment and climate change.
Multimedia artist Jackson 2bears reimagines the Haudenosaunee longhouse and creation story.
A new approach could streamline virtual training processes or aid clinicians in reviewing diagnostic videos.
Associate Professor Jonathan Ragan-Kelley optimizes how computer graphics and images are processed for the hardware of today and tomorrow.
When it comes to shaping political beliefs, MIT postdoc Chloe Wittenberg PhD ’23 finds video captivates, but might not beat text.
By synchronizing media streams transmitted from the cloud to two devices, researchers could improve cloud gaming and AR/VR applications.
Cloud security and video forensics software have been transitioned to end users.
MIT professors collaborate at a whirlwind pace to create and stage a play inspired by advances in neurotechnology.
The popular YouTuber, engineer, and inventor works to engage young people in science and technology while encouraging curiosity and resilience.
MIT’s inaugural Bearing Witness, Seeking Justice conference explores video’s role in the struggle over truth and civil liberties.
Models trained on synthetic data can be more accurate than other models in some cases, which could eliminate some privacy, copyright, and ethical concerns from using real data.