Generative Adversarial Networks Promise to Change Computing, and Us

Generative Adversarial Networks Promise to Change Computing, and Us

You have heard of machine learning, in which a computer gains “knowledge” and expertise as it tries and fails at a human-designed task until it learns the correct approach. That type of machine learning is still being used, but it could soon become very old-school. Some day, generative adversarial networks will take over, as two computers test each other, with little human intervention, to come up with a solution.

Of course, humans still must program the computers before they start on their task, but with generative adversarial networks, or GANs, the computers then test themselves to develop solutions that have minimal human input.

GANs are confined at the moment mostly to creating paintings and simulated photographs, but scientists say the technology could blaze the path to computers that think like humans – or come so close most of us won’t be able to tell the difference.

Positive or negative?
If you dread the singularity, when we become one with technology, this might be the time to start hoarding the freeze-dried food pellets at your mountain hideaway.

If you are more optimistic, you might see GANs as moving us closer to a world in which information technology is maximized to help us solve more of humanity’s problems.

In generative adversarial networks two computers teach each other to solve problems. With conventional machine learning, a human feeds labeled information to a computer until the machine learns a task.

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