University of Maryland

5 Posts

Animated charts showing how AI can learn from simple tasks to harder versions of the same task
University of Maryland

More Thinking Solves Harder Problems: AI Can Learn From Simple Tasks to Solve Hard Problems

In machine learning, an easy task and a more difficult version of the same task — say, a maze that covers a smaller or larger area — often are learned separately.
2 min read
Detection of a digitally altered image of a frog holding a violin
University of Maryland

Fighting Fakes

A supergroup of machine learning models flags manipulated photos. Jigsaw, a tech incubator owned by Alphabet, released a system that detects digitally altered images.
1 min read
Data related to adversarial learning
University of Maryland

Adversarial Helper

Models that learn relationships between images and words are gaining a higher profile. New research shows that adversarial learning, usually a way to make models robust to deliberately misleading inputs, can boost vision-and-language performance.
2 min read
Data and examples related to IMLE-GAN
University of Maryland

Making GANs More Inclusive

A typical GAN’s output doesn’t necessarily reflect the data distribution of its training set. Instead, GANs are prone to modeling the majority of the training distribution, sometimes ignoring rare attributes — say, faces that represent minority populations.
2 min read
Original vs Deepfake example
University of Maryland

Facing Down Deepfakes

Deepfakes threaten to undermine law and order, perhaps democracy itself. A coalition of tech companies, nonprofits, and academics joined forces to counter potential adverse impacts.
1 min read

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