University of Maryland

18 Posts

AI Jobs Grow Beyond Established Hubs: AI careers spread across the U.S., outgrowing traditional tech hubs.
University of Maryland

AI Jobs Grow Beyond Established Hubs: AI careers spread across the U.S., outgrowing traditional tech hubs.

An analysis of United States job listings shows AI jobs are growing rapidly outside traditional tech hubs. Researchers at University of Maryland analyzed the distribution of AI jobs among U.S. job postings. California hosts the largest concentration...

January 31, 20242 min read
AI Jobs Grow Beyond Established Hubs: AI careers spread across the U.S., outgrowing traditional tech hubs.
University of Maryland

AI Jobs Grow Beyond Established Hubs: AI careers spread across the U.S., outgrowing traditional tech hubs.

An analysis of United States job listings shows AI jobs are growing rapidly outside traditional tech hubs. Researchers at University of Maryland analyzed the distribution of AI jobs among U.S. job postings. California hosts the largest concentration...

January 31, 20242 min read
Image Generators Copy Training Data: Spotting similarities between generated images and data
University of Maryland

Image Generators Copy Training Data: Spotting similarities between generated images and data

We know that image generators create wonderful original works, but do they sometimes replicate their training data? Recent work found that replication does occur.

April 26, 20232 min read
Image Generators Copy Training Data: Spotting similarities between generated images and data
University of Maryland

Image Generators Copy Training Data: Spotting similarities between generated images and data

We know that image generators create wonderful original works, but do they sometimes replicate their training data? Recent work found that replication does occur.

April 26, 20232 min read
Three Methods for Detecting Generated Text: Techniques to tell when you're reading AI-generated text
University of Maryland

Three Methods for Detecting Generated Text: Techniques to tell when you're reading AI-generated text

How can you tell when you’re reading machine-generated text? Three recent papers proposed solutions: Watermarking, classification, and a statistical method.

April 12, 20233 min read
Three Methods for Detecting Generated Text: Techniques to tell when you're reading AI-generated text
University of Maryland

Three Methods for Detecting Generated Text: Techniques to tell when you're reading AI-generated text

How can you tell when you’re reading machine-generated text? Three recent papers proposed solutions: Watermarking, classification, and a statistical method.

April 12, 20233 min read
Managing Medical Uncertainty: How Hospitals Use AI to Protect Patients
University of Maryland

Managing Medical Uncertainty: How Hospitals Use AI to Protect Patients

Hospitals across the United States are relying on AI to keep patients safe. Doctors are using a variety of machine learning systems to assess the risk that a given patient will suffer complications.

May 4, 20222 min read
Managing Medical Uncertainty: How Hospitals Use AI to Protect Patients
University of Maryland

Managing Medical Uncertainty: How Hospitals Use AI to Protect Patients

Hospitals across the United States are relying on AI to keep patients safe. Doctors are using a variety of machine learning systems to assess the risk that a given patient will suffer complications.

May 4, 20222 min read
More Thinking Solves Harder Problems: AI Can Learn From Simple Tasks to Solve Hard Problems
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.

September 29, 20212 min read
More Thinking Solves Harder Problems: AI Can Learn From Simple Tasks to Solve Hard Problems
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.

September 29, 20212 min read
Fighting Fakes: Six algorithms that help news sites spot deepfakes
University of Maryland

Fighting Fakes: Six algorithms that help news sites spot deepfakes

A supergroup of machine learning models flags manipulated photos. Jigsaw, a tech incubator owned by Alphabet, released a system that detects digitally altered images.

February 12, 20211 min read
Fighting Fakes: Six algorithms that help news sites spot deepfakes
University of Maryland

Fighting Fakes: Six algorithms that help news sites spot deepfakes

A supergroup of machine learning models flags manipulated photos. Jigsaw, a tech incubator owned by Alphabet, released a system that detects digitally altered images.

February 12, 20211 min read
Adversarial Helper: Adversarial learning can improve vision and NLP.
University of Maryland

Adversarial Helper: Adversarial learning can improve vision and NLP.

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.

January 20, 20212 min read
Adversarial Helper: Adversarial learning can improve vision and NLP.
University of Maryland

Adversarial Helper: Adversarial learning can improve vision and NLP.

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.

January 20, 20212 min read
Making GANs More Inclusive: A technique to help GANs represent their datasets fairly
University of Maryland

Making GANs More Inclusive: A technique to help GANs represent their datasets fairly

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.

September 30, 20202 min read

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