Ping pong bot returns shots with high-speed precision
In addition to training future players, the technology could expand the capabilities of other humanoid robots, such as for search and rescue.
In addition to training future players, the technology could expand the capabilities of other humanoid robots, such as for search and rescue.
The CausVid generative AI tool uses a diffusion model to teach an autoregressive (frame-by-frame) system to rapidly produce stable, high-resolution videos.
A new method helps convey uncertainty more precisely, which could give researchers and medical clinicians better information to make decisions.
A new approach could enable intuitive robotic helpers for household, workplace, and warehouse settings.
“InteRecon” enables users to capture items in a mobile app and reconstruct their interactive features in mixed reality. The tool could assist in education, medical environments, museums, and more.
Inaugural cohort of Tecnológico de Monterrey undergraduates participate in immersive practicum at MIT featuring desktop fiber-extrusion devices, or FrEDs.
Researchers fuse the best of two popular methods to create an image generator that uses less energy and can run locally on a laptop or smartphone.
Assistant Professor Sara Beery is using automation to improve monitoring of migrating salmon in the Pacific Northwest.
Associate Professor Luca Carlone is working to give robots a more human-like awareness of their environment.
Biodiversity researchers tested vision systems on how well they could retrieve relevant nature images. More advanced models performed well on simple queries but struggled with more research-specific prompts.
The “PRoC3S” method helps an LLM create a viable action plan by testing each step in a simulation. This strategy could eventually aid in-home robots to complete more ambiguous chore requests.
Researchers propose a simple fix to an existing technique that could help artists, designers, and engineers create better 3D models.
The method could help communities visualize and prepare for approaching storms.
MIT CSAIL researchers used AI-generated images to train a robot dog in parkour, without real-world data. Their LucidSim system demonstrates generative AI's potential for creating robotics training data.
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.