Wiggling toward bio-inspired machine intelligence
Inspired by jellyfish and octopuses, PhD candidate Juncal Arbelaiz investigates the theoretical underpinnings that will enable systems to more efficiently adapt to their environments.
Inspired by jellyfish and octopuses, PhD candidate Juncal Arbelaiz investigates the theoretical underpinnings that will enable systems to more efficiently adapt to their environments.
A machine-learning method finds patterns of health decline in ALS, informing future clinical trial designs and mechanism discovery. The technique also extends to Alzheimer’s and Parkinson’s.
The MIT-Pillar AI Collective will cultivate prospective entrepreneurs and drive innovation.
Aleksander Madry, Asu Ozdaglar, and Luis Videgaray, co-chairs of the AI Policy Forum, discuss key issues facing the AI policy landscape today.
Neuroscience PhD student Fernanda De La Torre uses complex algorithms to investigate philosophical questions about perception and reality.
By continuously monitoring a patient’s gait speed, the system can assess the condition’s severity between visits to the doctor’s office.
Mayor’s youth employment program brought local high schoolers to MIT this summer.
An interdisciplinary team is developing a mobile health platform that uses AI to detect infection in Cesarean section wounds.
The MIT Schwarzman College of Computing welcomes four new faculty members engaged in research and teaching that address climate risks and other environmental issues.
Researchers develop a new method that uses multiple models to create more complex images with better understanding.
Researchers increase the accuracy and efficiency of a machine-learning method that safeguards user data.
Study finds computer models that predict molecular interactions need improvement before they can help identify drug mechanisms of action.
A new model that maps developmental pathways to tumor cells may unlock the identity of cancers of unknown primary.
On its own, a new machine-learning model discovers linguistic rules that often match up with those created by human experts.
Lincoln Laboratory Supercomputing Center dataset aims to accelerate AI research into managing and optimizing high-performance computing systems.