New AI method captures uncertainty in medical images
By providing plausible label maps for one medical image, the Tyche machine-learning model could help clinicians and researchers capture crucial information.
Computer Science and Artificial Intelligence Laboratory (CSAIL)
A faster, better way to prevent an AI chatbot from giving toxic responses
Researchers create a curious machine-learning model that finds a wider variety of prompts for training a chatbot to avoid hateful or harmful output.
A new computational technique could make it easier to engineer useful proteins
MIT researchers plan to search for proteins that could be used to measure electrical activity in the brain.
New software enables blind and low-vision users to create interactive, accessible charts
Screen-reader users can upload a dataset and create customized data representations that combine visualization, textual description, and sonification.
Q&A: How refusal can be an act of design
Doctoral student and recent MAD Design Fellow Jonathan Zong SM ’20 discusses a proposed framework to map how individuals can say “no” to technology misuses.
Engineering household robots to have a little common sense
With help from a large language model, MIT engineers enabled robots to self-correct after missteps and carry on with their chores.
Large language models use a surprisingly simple mechanism to retrieve some stored knowledge
Researchers demonstrate a technique that can be used to probe a model to see what it knows about new subjects.
Study: Movement disorder ALS and cognitive disorder FTLD show strong molecular overlaps
Single-cell gene expression patterns in the brain, and evidence from follow-up experiments, reveal many shared cellular and molecular similarities that could be targeted for potential treatment.
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.
3 Questions: What you need to know about audio deepfakes
MIT CSAIL postdoc Nauman Dawalatabad explores ethical considerations, challenges in spear-phishing defense, and the optimistic future of AI-created voices across various sectors.
Researchers help robots navigate efficiently in uncertain environments
A new algorithm reduces travel time by identifying shortcuts a robot could take on the way to its destination.
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.
Method rapidly verifies that a robot will avoid collisions
Faster and more accurate than some alternatives, this approach could be useful for robots that interact with humans or work in tight spaces.
Eight from MIT named 2024 Sloan Research Fellows
Fellows honored for creativity, innovation, and research accomplishments.