Oct 02, 2019

6 Posts

Map of the area analyzed in Cascadia and sketch of the subduction zone
Oct 02, 2019

Prelude to a Quake?

Geologists call them slow slips: deep, low-frequency earthquakes that can last a month but have little effect on the surface. A model trained to predict such events could help with forecasting potentially catastrophic quakes.
1 min read
 A quantum processor and one qubit’s energy-relaxation time “T1” plotted as a function of it’s operating frequency and time
Oct 02, 2019

Quantum Leap

A leaked paper from Google’s quantum computing lab claims “supremacy” over conventional computers. The U.S. space agency NASA, whose scientists are collaborating with Google on a quantum computer, accidentally published a paper describing the breakthrough.
2 min read
DeepPrivacy results on a diverse set of images
Oct 02, 2019

Anonymous Faces

A number of countries restrict commercial use of personal data without consent unless they’re fully anonymized. A new paper proposes a way to anonymize images of faces, purportedly without degrading their usefulness in applications that rely on face recognition.
2 min read
Animation showing how players on the opposing team likely would move in response to human-drafted plays
Oct 02, 2019

Nothing but (Neural) Net

Basketball coaches sketch plays on a whiteboard to help players get the ball through the net. A new AI model predicts how opponents would respond to these tactics. A team of researchers in Taiwan trained a conditional generative adversarial network on data from National Basketball Association games.
1 min read
Amazon Rekognition screen capture
Oct 02, 2019

Amazon Prepares for a Crackdown

Amazon is writing what it hopes will become U.S. law governing use of face recognition technology. At a press event, Jeff Bezos told that his company’s lawyers are drafting a statutory framework to guide what he views as an inevitable federal crackdown on face recognition.
1 min read
GPT-2 text generator
Oct 02, 2019

Putting Text Generators on a Leash

Despite dramatic recent progress, natural language generation remains an iffy proposition. Even users of the muscular GPT-2 text generator have to press the button a number of times to get sensible output. But researchers are figuring out how to exert greater control over generated text.
2 min read

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