Re-imagining our theories of language
Department of Brain and Cognitive Sciences faculty members Ev Fedorenko, Ted Gibson, and Roger Levy believe they can answer a fundamental question: What is the purpose of language?
MIT researchers make language models scalable self-learners
The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.
3 Questions: Jacob Andreas on large language models
The CSAIL scientist describes natural language processing research through state-of-the-art machine-learning models and investigation of how language can enhance other types of artificial intelligence.
Jacob Andreas and Mingda Li honored with Junior Bose Award for Excellence in Teaching
Award is given each year by the School of Engineering to an outstanding educator up for promotion to associate professor without tenure.
New insights into training dynamics of deep classifiers
MIT researchers uncover the structural properties and dynamics of deep classifiers, offering novel explanations for optimization, generalization, and approximation in deep networks.
Large language models are biased. Can logic help save them?
MIT researchers trained logic-aware language models to reduce harmful stereotypes like gender and racial biases.
Engineering in harmony
AeroAstro major and accomplished tuba player Frederick Ajisafe relishes the community he has found in the MIT Wind Ensemble.
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.
This is your brain. This is your brain on code
MIT researchers are discovering which parts of the brain are engaged when a person evaluates a computer program.
Large language models help decipher clinical notes
Researchers used a powerful deep-learning model to extract important data from electronic health records that could assist with personalized medicine.
Ushering in a new era of computing
Dan Huttenlocher is a professor of electrical engineering and computer science and the inaugural dean at MIT Schwarzman College of Computing.
3 Questions: How AI image generators could help robots
Yilun Du, a PhD student and MIT CSAIL affiliate, discusses the potential applications of generative art beyond the explosion of images that put the web into creative hysterics.
AI system makes models like DALL-E 2 more creative
Researchers develop a new method that uses multiple models to create more complex images with better understanding.
Designing zeolites, porous materials made to trap molecules
MIT engineers are controlling pore openings for maximum molecule capture.
New leadership at MIT’s Center for Biomedical Innovation
Stacy Springs named executive director; Richard Braatz is associate faculty director.