Physics and the machine-learning “black box”
In 2.C01, George Barbastathis demonstrates how mechanical engineers can use their knowledge of physical systems to keep algorithms in check and develop more accurate predictions.
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Seeing the plasma edge of fusion experiments in new ways with artificial intelligence
MIT researchers are testing a simplified turbulence theory’s ability to model complex plasma phenomena using a novel machine-learning technique.
Meet the 2021-22 Accenture Fellows
The 2021-22 Accenture Fellows are bolstering research and igniting ideas to help transform global business.
MIT in the media: 2021 in review
MIT community members made headlines around the world for their innovative approaches to addressing problems local and global.
Perfecting pitch perception
Computational modeling shows that both our ears and our environment influence how we hear.
Characters for good, created by artificial intelligence
Researchers encourage positive use cases of AI-generated characters for education and well-being.
From counting blood cells to motion capture, sensors drive patient-centered research
SENSE.nano symposium highlights the importance of sensing technologies in medical studies.
Nonsense can make sense to machine-learning models
Deep-learning methods confidently recognize images that are nonsense, a potential problem for medical and autonomous-driving decisions.
Machine-learning system flags remedies that might do more harm than good
The system could help physicians select the least risky treatments in urgent situations, such as treating sepsis.
EECS graduate women’s research summit increases research visibility and strengthens community
Summit features the latest research of women and other underrepresented genders in MIT EECS, along with an opportunity to network, share experiences, and learn.
Machines that see the world more like humans do
A new “common-sense” approach to computer vision enables artificial intelligence that interprets scenes more accurately than other systems do.
Q&A: More-sustainable concrete with machine learning
MIT-IBM Watson AI Lab researchers aim to design concrete mixtures that use AI to shrink environmental footprint and cost, while recycling byproducts and increasing performance.
A system for designing and training intelligent soft robots
“Evolution Gym” is a large-scale benchmark for co-optimizing the design and control of soft robots that takes inspiration from nature and evolutionary processes.
Technique enables real-time rendering of scenes in 3D
The new machine-learning system can generate a 3D scene from an image about 15,000 times faster than other methods.
Taking some of the guesswork out of drug discovery
A deep learning model rapidly predicts the 3D shapes of drug-like molecules, which could accelerate the process of discovering new medicines.