Cognitive scientists develop new model explaining difficulty in language comprehension
Built on recent advances in machine learning, the model predicts how well individuals will produce and comprehend sentences.
Built on recent advances in machine learning, the model predicts how well individuals will produce and comprehend sentences.
But the harm from a discriminatory AI system can be minimized if the advice it delivers is properly framed, an MIT team has shown.
CAST Visiting Artist Andreas Refsgaard engages the MIT community in the ethics and play of creative coding.
This year's fellows will work across research areas including telemonitoring, human-computer interactions, operations research, AI-mediated socialization, and chemical transformations.
Professor Koroush Shirvan, who recently won a prestigious award from the American Nuclear Society, pursues avenues to lower the costs of nuclear energy.
Researchers used a powerful deep-learning model to extract important data from electronic health records that could assist with personalized medicine.
Dan Huttenlocher is a professor of electrical engineering and computer science and the inaugural dean at MIT Schwarzman College of Computing.
New technique significantly reduces training and inference time on extensive datasets to keep pace with fast-moving data in finance, social networks, and fraud detection in cryptocurrency.
New technique could diminish errors that hamper the performance of super-fast analog optical neural networks.
The MIT senior will pursue postgraduate studies in computer science in Ireland.
New research reveals a scalable technique that uses synthetic data to improve the accuracy of AI models that recognize images.
New system can teach a group of cooperative or competitive AI agents to find an optimal long-term solution.
MIT CSAIL researchers solve a differential equation behind the interaction of two neurons through synapses to unlock a new type of speedy and efficient AI algorithm.
Researchers make headway in solving a longstanding problem of balancing curious “exploration” versus “exploitation” of known pathways in reinforcement learning.
“I get the chance to not only watch the future happen, but I can actually be a part of it and create it,” says Ugandan entrepreneur Emmanuel Kasigazi.