MIT scientists investigate memorization risk in the age of clinical AI
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
MIT community members made headlines with key research advances and their efforts to tackle pressing challenges.
CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.
MIT-IBM Watson AI Lab researchers developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
An AI-driven system lets users design and build simple, multicomponent objects by describing them with words.
The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.
The new certificate program will equip naval officers with skills needed to solve the military’s hardest problems.
The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.
By stacking multiple active components based on new materials on the back end of a computer chip, this new approach reduces the amount of energy wasted during computation.