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.
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.
Perfecting pitch perception
Computational modeling shows that both our ears and our environment influence how we hear.
Q&A: Cathy Wu on developing algorithms to safely integrate robots into our world
Assistant professor of civil engineering describes her career in robotics as well as challenges and promises of human-robot interactions.
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 speeds up vehicle routing
Strategy accelerates the best algorithmic solvers for large sets of cities.
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.
A tool to speed development of new solar cells
A new computational simulator can help predict whether changes to materials or design will improve performance in new photovoltaic cells.
Tiny machine learning design alleviates a bottleneck in memory usage on internet-of-things devices
New technique applied to small computer chips enables efficient vision and detection algorithms without internet connectivity.
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.
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.
Generating a realistic 3D world
A new AI-powered, virtual platform uses real-world physics to simulate a rich and interactive audio-visual environment, enabling human and robotic learning, training, and experimental studies.
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.