Changes Still, disinformation and propaganda are nothing magic. They can change things, but supposedly only if those things/meanings/opinions are not fixed completely. Galileo Galilee was not capable of changing people's opinion about the world being flat until some persons got suspicious that this long-believed-in truth was a mistake. The propaganda of his experiments which made him famous was not enough. On the other hand later all the propaganda of his enemies could not turn back the wheel of enlightenment, as people thought it was more logic to believe in a round world than in a flat one. It is never just a single idea that changes. Society is following the changes. Thinking about disinformation brings us to the word truth, of course, and to the doubt that there is no definite truth. And truth can easily be manipulated to another truth. Just present some facts that seem to be logic and there you've got a new truth. And if the facts can supposedly be proved by empirical studies then the quality of the truth definitely rises. That's what ideologies do all the time. And the media like to do the same thing - as a game with power or mere presentation of power? But of course there also exist bits of disinformation which are more amusing than evil or dangerous: - the theory of the celestro-centric world/"Hohlwelttheorie" - the story of the German philosopher who invented an Italian philosopher, wrote books about him, even reprinted "his" texts, which had gone lost pretendedly 100 years ago - and finally lost his job and all his career when other scientists found out that everything had been made up.

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Neural network A bottom-up artificial intelligence approach, a neural network is a network of many very simple processors ("units" or "neurons"), each possibly having a (small amount of) local memory. The units are connected by unidirectional communication channels ("connections"), which carry numeric data. The units operate only on their local data and on the inputs they receive via the connections. A neural network is a processing device, either an algorithm, or actual hardware, whose design was inspired by the design and functioning of animal brains and components thereof. Most neural networks have some sort of "training" rule whereby the weights of connections are adjusted on the basis of presented patterns. In other words, neural networks "learn" from examples and exhibit some structural capability for generalization.

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