How generative AI can help scientists synthesize complex materials
MIT researchers’ DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.
MIT researchers’ DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.
The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.
The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.
With insect-like speed and agility, the tiny robot could someday aid in search-and-rescue missions.
Large language models can learn to mistakenly link certain sentence patterns with specific topics — and may then repeat these patterns instead of reasoning.
A new approach developed at MIT could help a search-and-rescue robot navigate an unpredictable environment by rapidly generating an accurate map of its surroundings.
MIT PhD student and CSAIL researcher Justin Kay describes his work combining AI and computer vision systems to monitor the ecosystems that support our planet.
Economics doctoral student Whitney Zhang investigates how technologies and organizational decisions shape labor markets.