Researchers use large language models to help robots navigate
The method uses language-based inputs instead of costly visual data to direct a robot through a multistep navigation task.
New algorithm discovers language just by watching videos
DenseAV, developed at MIT, learns to parse and understand the meaning of language just by watching videos of people talking, with potential applications in multimedia search, language learning, and robotics.
New computer vision method helps speed up screening of electronic materials
The technique characterizes a material’s electronic properties 85 times faster than conventional methods.
Looking for a specific action in a video? This AI-based method can find it for you
A new approach could streamline virtual training processes or aid clinicians in reviewing diagnostic videos.
Controlled diffusion model can change material properties in images
“Alchemist” system adjusts the material attributes of specific objects within images to potentially modify video game models to fit different environments, fine-tune VFX, and diversify robotic training.
School of Engineering welcomes new faculty
Fifteen new faculty members join six of the school’s academic departments.
Creating bespoke programming languages for efficient visual AI systems
Associate Professor Jonathan Ragan-Kelley optimizes how computer graphics and images are processed for the hardware of today and tomorrow.
Natural language boosts LLM performance in coding, planning, and robotics
Three neurosymbolic methods help language models find better abstractions within natural language, then use those representations to execute complex tasks.
Advancing technology for aquaculture
MIT Sea Grant students apply machine learning to support local aquaculture hatcheries.
AI generates high-quality images 30 times faster in a single step
Novel method makes tools like Stable Diffusion and DALL-E-3 faster by simplifying the image-generating process to a single step while maintaining or enhancing image quality.
New algorithm unlocks high-resolution insights for computer vision
FeatUp, developed by MIT CSAIL researchers, boosts the resolution of any deep network or visual foundation for computer vision systems.
Researchers enhance peripheral vision in AI models
By enabling models to see the world more like humans do, the work could help improve driver safety and shed light on human behavior.
MIT researchers remotely map crops, field by field
The team used machine learning to analyze satellite and roadside images of areas where small farms predominate and agricultural data are sparse.
Study: Smart devices’ ambient light sensors pose imaging privacy risk
The ambient light sensors responsible for smart devices’ brightness adjustments can capture images of touch interactions like swiping and tapping for hackers.
Reasoning and reliability in AI
PhD students interning with the MIT-IBM Watson AI Lab look to improve natural language usage.