New model offers a way to speed up drug discovery
Huge libraries of drug compounds may hold potential treatments for a variety of diseases, such as cancer or heart disease. Ideally, scientists would like to experimentally test each of these...
Bringing the social and ethical responsibilities of computing to the forefront
There has been a remarkable surge in the use of algorithms and artificial intelligence to address a wide range of problems and challenges. While their adoption, particularly with the rise...
Q&A: Gabriela Sá Pessoa on Brazilian politics, human rights in the Amazon, and AI
Gabriela Sá Pessoa is a journalist passionate about the intersection of human rights and climate change. She came to MIT from The Washington Post, where she worked from her home...
Scaling audio-visual learning without labels
Researchers from MIT, the MIT-IBM Watson AI Lab, IBM Research, and elsewhere have developed a new technique for analyzing unlabeled audio and visual data that could improve the performance of...
Driven to driverless
When Cindy Heredia was choosing an MBA program, she knew she wanted to be at the forefront of the autonomous driving industry. While doing research, she discovered that MIT had...
A more effective way to train machines for uncertain, real-world situations
Someone learning to play tennis might hire a teacher to help them learn faster. Because this teacher is (hopefully) a great tennis player, there are times when trying to exactly...
New tool helps people choose the right method for evaluating AI models
When machine-learning models are deployed in real-world situations, perhaps to flag potential disease in X-rays for a radiologist to review, human users need to know when to trust the model’s...
Celebrating the impact of IDSS
The “interdisciplinary approach” is something that has been lauded for decades for its ability to break down silos and create new integrated approaches to research. For Munther Dahleh, founding director...
Probabilistic AI that knows how well it’s working
Despite their enormous size and power, today’s artificial intelligence systems routinely fail to distinguish between hallucination and reality. Autonomous driving systems can fail to perceive pedestrians and emergency vehicles right...
