System helps humans predict when self-driving cars will make mistakes
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.
The senior lecturer, already director of the degree program, will now oversee all aspects of the center’s activities and operations.
Read MoreThe Institute welcomes its first cohort of QMIT Fellows this fall to advance interdisciplinary quantum research.
Read MoreA new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
Read MoreThe “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.
Read MoreA new algorithm learns to anticipate the unprecedented scenarios that critical infrastructure and global supply chains are least prepared for.
Read MoreNew MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that’s essential to fertilizer and other products.
Read MoreA new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.
Read MoreIn his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
Read MoreIn his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
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