The sweet taste of a new idea
Sendhil Mullainathan brings a lifetime of unique perspectives to research in behavioral economics and machine learning.
Electrical engineering and computer science (EECS)
With AI, researchers predict the location of virtually any protein within a human cell
Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.
Study shows vision-language models can’t handle queries with negation words
Words like “no” and “not” can cause this popular class of AI models to fail unexpectedly in high-stakes settings, such as medical diagnosis.
Hybrid AI model crafts smooth, high-quality videos in seconds
The CausVid generative AI tool uses a diffusion model to teach an autoregressive (frame-by-frame) system to rapidly produce stable, high-resolution videos.
Novel AI model inspired by neural dynamics from the brain
New type of “state-space model” leverages principles of harmonic oscillators.
Making AI models more trustworthy for high-stakes settings
A new method helps convey uncertainty more precisely, which could give researchers and medical clinicians better information to make decisions.
The MIT-Portugal Program enters Phase 4
New phase will support continued exploration of ideas and solutions in fields ranging from AI to nanotech to climate — with emphasis on educational exchanges and entrepreneurship.
Merging design and computer science in creative ways
MAD Fellow Alexander Htet Kyaw connects humans, machines, and the physical world using AI and augmented reality.
Novel method detects microbial contamination in cell cultures
Ultraviolet light “fingerprints” on cell cultures and machine learning can provide a definitive yes/no contamination assessment within 30 minutes.
“Periodic table of machine learning” could fuel AI discovery
Researchers have created a unifying framework that can help scientists combine existing ideas to improve AI models or create new ones.