Scientists use generative AI to answer complex questions in physics
A new technique that can automatically classify phases of physical systems could help scientists investigate novel materials.
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A new technique that can automatically classify phases of physical systems could help scientists investigate novel materials.
A new “consensus game,” developed by MIT CSAIL researchers, elevates AI’s text comprehension and generation skills.
A new algorithm learns to squish, bend, or stretch a robot’s entire body to accomplish diverse tasks like avoiding obstacles or retrieving items.
Associate Professor Jonathan Ragan-Kelley optimizes how computer graphics and images are processed for the hardware of today and tomorrow.
Three neurosymbolic methods help language models find better abstractions within natural language, then use those representations to execute complex tasks.
For the first time, researchers use a combination of MEG and fMRI to map the spatio-temporal human brain dynamics of a visual image being recognized.
Researchers have developed a security solution for power-hungry AI models that offers protection against two common attacks.
A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals.
The MIT Schwarzman College of Computing building will form a new cluster of connectivity across a spectrum of disciplines in computing and artificial intelligence.
By providing plausible label maps for one medical image, the Tyche machine-learning model could help clinicians and researchers capture crucial information.