Advancing technology for aquaculture
MIT Sea Grant students apply machine learning to support local aquaculture hatcheries.
MIT Sea Grant students apply machine learning to support local aquaculture hatcheries.
Lincoln Laboratory researchers are using AI to get a better picture of the atmospheric layer closest to Earth’s surface. Their techniques could improve weather and drought prediction.
MIT Center for Transportation and Logistics Director Matthias Winkenbach uses AI to make vehicle routing more efficient and adaptable for unexpected events.
Researchers create a curious machine-learning model that finds a wider variety of prompts for training a chatbot to avoid hateful or harmful output.
The 16 finalists — representing every school at MIT — will explore generative AI’s impact on privacy, art, drug discovery, aging, and more.
The new approach “nudges” existing climate simulations closer to future reality.
Researchers demonstrate a technique that can be used to probe a model to see what it knows about new subjects.
With help from a large language model, MIT engineers enabled robots to self-correct after missteps and carry on with their chores.
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.
FeatUp, developed by MIT CSAIL researchers, boosts the resolution of any deep network or visual foundation for computer vision systems.