When it comes to AI, can we ditch the datasets?
A machine-learning model for image classification that’s trained using synthetic data can rival one trained on the real thing, a study shows.
A machine-learning model for image classification that’s trained using synthetic data can rival one trained on the real thing, a study shows.
Chemical engineers use neural networks to discover the properties of metal-organic frameworks, for catalysis and other applications.
MEng graduate students engage with IBM to develop their research skills and solutions to real-world problems.
A new MIT-wide effort launched by the Institute for Data, Systems, and Society uses social science and computation to address systemic racism.
The Social and Ethical Responsibilities of Computing publishes a collection of original pedagogical materials developed for instructional use on MIT OpenCourseWare.
Researchers find similarities between how some computer-vision systems process images and how humans see out of the corners of our eyes.
Researchers surveyed 100 high-performing companies to determine which of them are leading adopters of machine intelligence and data analytics, and how they succeed.
A new technique boosts models’ ability to reduce bias, even if the dataset used to train the model is unbalanced.
A new machine-learning technique could pinpoint potential power grid failures or cascading traffic bottlenecks in real time.
A new methodology simulates counterfactual, time-varying, and dynamic treatment strategies, allowing doctors to choose the best course of action.
Improvements in the material that converts X-rays into light, for medical or industrial images, could allow a tenfold signal enhancement.
A model’s ability to generalize is influenced by both the diversity of the data and the way the model is trained, researchers report.
Engineers build a lower-energy chip that can prevent hackers from extracting hidden information from a smart device.
A new deep-learning algorithm trained to optimize doses of propofol to maintain unconsciousness during general anesthesia could augment patient monitoring.
Heather Kulik embraces computer models as “the only way to make a dent” in the vast number of potential materials that could solve important problems.