A smarter way to streamline drug discovery
The SPARROW algorithm automatically identifies the best molecules to test as potential new medicines, given the vast number of factors affecting each choice.
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The SPARROW algorithm automatically identifies the best molecules to test as potential new medicines, given the vast number of factors affecting each choice.
With generative AI models, researchers combined robotics data from different sources to help robots learn better.
Three neurosymbolic methods help language models find better abstractions within natural language, then use those representations to execute complex tasks.
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.
MIT researchers plan to search for proteins that could be used to measure electrical activity in the brain.
FeatUp, developed by MIT CSAIL researchers, boosts the resolution of any deep network or visual foundation for computer vision systems.
MIT engineers developed a tag that can reveal with near-perfect accuracy whether an item is real or fake. The key is in the glue on the back of the tag.
Researchers developed a simple yet effective solution for a puzzling problem that can worsen the performance of large language models such as ChatGPT.
MIT CSAIL researchers develop advanced machine-learning models that outperform current methods in detecting pancreatic ductal adenocarcinoma.