“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.
“Co-LLM” algorithm helps a general-purpose AI model collaborate with an expert large language model by combining the best parts of both answers, leading to more factual responses.
Yiming Chen ’24, Wilhem Hector, Anushka Nair, and David Oluigbo will start postgraduate studies at Oxford next fall.
New algorithm helps robots practice skills like sweeping and placing objects, potentially helping them improve at important tasks in houses, hospitals, and factories.
Multiple CSAIL researchers past and present were highlighted in a recent Business Insider story spotlighting 'the most important people in robotics.'
Among the individuals profiled:
-Rodney Brooks, former director of CSAIL and founder of Rethink Robotics.
-Marc Raibert, former director of the AI Lab's Leg Lab and founder/president of Boston Dynamics.
An MIT/IBM system could help artists and designers make quick tweaks to visuals while also helping researchers identify “fake” images.
This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development.
Researchers use synthetic data to improve a model’s ability to grasp conceptual information, which could enhance automatic captioning and question-answering systems.
MIT CSAIL researchers innovate with synthetic imagery to train AI, paving the way for more efficient and bias-reduced machine learning.
A new technique that can automatically classify phases of physical systems could help scientists investigate novel materials.