10k nonexistent cats created by machine & Ai
A composition of 10,000 unique cat images generated by the artificial intelligence called GAN (generative adversarial network), no human was involved in the creation of these cats, a machine created them by machine learning and artificial intelligence algorithms.
“Cats choose us; we don’t own them.”
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A generative adversarial network (GAN) is a class of machine learning frameworks designed by Ian Goodfellow and his colleagues in 2014. Two neural networks contesting with each other in a game (in the form of a zero-sum game, where one agent’s gain is another agent’s loss). Given a training set, this technique learns to generate new data with the same statistics as the training set.
For example, a GAN trained on photographs can generate new photographs that look at least superficially authentic to human observers, having many realistic characteristics. Though originally proposed as a form of a generative model for unsupervised learning, GANs have also proven useful for semi-supervised learning, fully supervised learning, and reinforcement learning.