Learning on the edge
A new technique enables AI models to continually learn from new data on intelligent edge devices like smartphones and sensors, reducing energy costs and privacy risks.
MIT-IBM Watson AI Lab
Neurodegenerative disease can progress in newly identified patterns
A machine-learning method finds patterns of health decline in ALS, informing future clinical trial designs and mechanism discovery. The technique also extends to Alzheimer’s and Parkinson’s.
New hardware offers faster computation for artificial intelligence, with much less energy
Engineers working on “analog deep learning” have found a way to propel protons through solids at unprecedented speeds.
Student-powered machine learning
Recent MEng graduates reflect on their application-focused research as affiliates of the MIT-IBM Watson AI Lab.
Keeping web-browsing data safe from hackers
Studying a powerful type of cyberattack, researchers identified a flaw in how it’s been analyzed before, then developed new techniques that stop it in its tracks.
Hallucinating to better text translation
A machine-learning method imagines what a sentence visually looks like, to situate and ground its semantics in the real world, improving translation, like humans can.
Artificial intelligence system learns concepts shared across video, audio, and text
A machine-learning model can identify the action in a video clip and label it, without the help of humans.
A one-up on motion capture
A new neural network approach captures the characteristics of a physical system’s dynamic motion from video, regardless of rendering configuration or image differences.
How can we reduce the carbon footprint of global computing?
Workshop hosted by MIT’s Climate and Sustainability Consortium, MIT-IBM Watson AI Lab, and the MIT Schwarzman College of Computing highlights how new approaches to computing can save energy and help the planet.
Does this artificial intelligence think like a human?
A new technique compares the reasoning of a machine-learning model to that of a human, so the user can see patterns in the model’s behavior.
Generating new molecules with graph grammar
An efficient machine-learning method uses chemical knowledge to create a learnable grammar with production rules to build synthesizable monomers and polymers.
Unlocking new doors to artificial intelligence
MEng graduate students engage with IBM to develop their research skills and solutions to real-world problems.
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.
MIT community members elected to the National Academy of Engineering for 2022
John Cohn and Franz-Josef Ulm, along with 19 additional MIT alumni, are honored for significant contributions to engineering research, practice, and education.
A new language for quantum computing
Twist is an MIT-developed programming language that can describe and verify which pieces of data are entangled to prevent bugs in a quantum program.