Making quantum circuits more robust
Researchers have developed a technique for making quantum computing more resilient to noise, which boosts performance.
3 Questions: How the MIT mini cheetah learns to run
CSAIL scientists came up with a learning pipeline for the four-legged robot that learns to run entirely by trial and error in simulation.
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.
An “oracle” for predicting the evolution of gene regulation
Researchers create a mathematical framework to examine the genome and detect signatures of natural selection, deciphering the evolutionary past and future of non-coding DNA.
A new resource for teaching responsible technology development
The Social and Ethical Responsibilities of Computing publishes a collection of original pedagogical materials developed for instructional use on MIT OpenCourseWare.
The benefits of peripheral vision for machines
Researchers find similarities between how some computer-vision systems process images and how humans see out of the corners of our eyes.
Study examines how machine learning boosts manufacturing
Researchers surveyed 100 high-performing companies to determine which of them are leading adopters of machine intelligence and data analytics, and how they succeed.
Injecting fairness into machine-learning models
A new technique boosts models’ ability to reduce bias, even if the dataset used to train the model is unbalanced.
Using artificial intelligence to find anomalies hiding in massive datasets
A new machine-learning technique could pinpoint potential power grid failures or cascading traffic bottlenecks in real time.
Deep-learning technique predicts clinical treatment outcomes
A new methodology simulates counterfactual, time-varying, and dynamic treatment strategies, allowing doctors to choose the best course of action.
More sensitive X-ray imaging
Improvements in the material that converts X-rays into light, for medical or industrial images, could allow a tenfold signal enhancement.
Can machine-learning models overcome biased datasets?
A model’s ability to generalize is influenced by both the diversity of the data and the way the model is trained, researchers report.
Using deep imaging for higher resolution
Akasha Imaging, an MIT Media Lab spinout, provides efficient and cost-effective imaging with higher-resolution feature detection, tracking, and pose orientation.
Fostering media literacy in the age of deepfakes
Online course from the MIT Center for Advanced Virtuality seeks to empower students and educators to critically engage with media.
Research advances technology of AI assistance for anesthesiologists
A new deep-learning algorithm trained to optimize doses of propofol to maintain unconsciousness during general anesthesia could augment patient monitoring.