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"Generalized adversarial networks, or GANs, are a conceptual advance that allow reinforcement learning problems to be solved automatically." -

"Generalized" :D Also the description is nonsense. This has nothing to do with reinforcement learning. Makes me wonder about the rest.

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Now, if a press release from a top univ is so wrong on something that is easily checkable, how accurate are other forms of news?

Think of "press release wrongness" with a probability distribution. Some press releases are really good, some are really bad. A sensible prior would be somewhere in the middle. If you start to see a lot of bad press releases, then you can update your posterior towards "I can't trust any of these."

Is that a good prior? I expect due to Dunning–Kruger that the willingness to produce an article on a topic would follow a pretty intense bimodal distribution.

The paper has it right, at least.

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