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.
“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.
The new machine-learning system can generate a 3D scene from an image about 15,000 times faster than other methods.
Electrical engineer and Stanford University professor discusses how computer software can support advanced designs and new functionalities.
Senior Shardul Chiplunkar aims to be a translator between the tech world and the rest of society.
A new machine-learning model could enable robots to understand interactions in the world in the way humans do.
Houston discusses leading the company through the pandemic in a fireside chat hosted by the MIT Schwarzman College of Computing.
Mechanical engineers are using cutting-edge computing techniques to re-imagine how the products, systems, and infrastructures we use are designed.
Ruonan Han seeks to develop next-generation electronic devices by harnessing terahertz waves.
New work on linear-probing hash tables from MIT CSAIL could lead to more efficient data storage and retrieval in computers.
Reducing the complexity of a powerful machine-learning model may help level the playing field for automatic speech-recognition around the world.
The Common Ground for Computing Education is facilitating collaborations to develop new classes for students to pursue computational knowledge within the context of their fields of interest.
A new method forces a machine learning model to focus on more data when learning a task, which leads to more reliable predictions.
A National Science Foundation-funded team will use artificial intelligence to speed up discoveries in physics, astronomy, and neuroscience.
MIT researchers develop a new way to control and measure energy levels in a diamond crystal; could improve qubits in quantum computers.
Neuroscientists find the internal workings of next-word prediction models resemble those of language-processing centers in the brain.