Michael Friesen generated these abominable pokemon sprites. Be sure to see a similar set hand-drawn by iguanamouth. [via Janelle Shane]

Here's a human illustrating some neural net-generated pokemon names and abilities. Humans earnestly engaging with AI bizarreness is one of my favorite things.https://t.co/bMxUoXSbGB pic.twitter.com/RarbkeJfGX

— Janelle Shane (@JanelleCShane) May 12, 2019

Uncurated samples: https://t.co/CEcXvViZXlPre-trained model: https://t.co/nuXdzwGQtS

— Michael Friesen (@MichaelFriese10) May 13, 2019

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Generative Adversarial Networks use a pair of machine-learning models to create things that seem very realistic: one of the models, the "generator," uses its training data to make new things; and the other, the "discerner," checks the generator's output to see if it conforms to the model. Read the rest

Researchers at NYU and U Michigan have published a paper explaining how they used a pair of machine-learning systems to develop a "universal fingerprint" that can fool the lowest-security fingerprint sensors 76% of the time (it is less effective against higher-security sensors). Read the rest