/sci/ - Science & Math » Thread #11943896

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Anonymous Mon 27 Jul 20:43:13 2020 No.11943896 View Reply Original Report

Quoted By: >>11944012 >>11944351 >>11944429

Scientifically speaking, what is the best way to predict the future?

I'm writing a short story, where Strong AI goes rogue and has only one task: predict future as close to 100% reliability as possible.

A computer, powered by black holes? Dark matter? If we go to the end of Kardashev scale - what is the best way?

thanks

Anonymous

Anonymous Mon 27 Jul 2020 21:20:25 No.11944012 Report

Quoted By:

>>11943896
brainlet question to assume so much

Anonymous

Anonymous Mon 27 Jul 2020 21:23:29 No.11944024 Report

Quoted By: >>11944423

>Strong AI goes rogue
>predict future as close to 100% reliability as possible

Please, you want me to write this story for you?
There is only 1 way to 100% reliability predict the future, that is to shape the future to your will. This is the AI's solution to the task it is given, and how/why the AI goes rogue in the 1st place.

Anonymous

Anonymous Mon 27 Jul 2020 22:51:08 No.11944333 Report

Quoted By:

The ai can perfectly predict everything but itself anon, that better be the central plot device or your story is SciFi mostly Fi, bullshit.

Anonymous

Anonymous Mon 27 Jul 2020 22:57:08 No.11944351 Report

Quoted By:

>>11943896
>Scientifically speaking, what is the best way to predict the future?
go down the /x/ route and explore project looking glass

Anonymous

Anonymous Mon 27 Jul 2020 23:26:38 No.11944423 Report

Quoted By:

>>11944024
Retard

Anonymous

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Anonymous Mon 27 Jul 2020 23:27:34 No.11944429 Report

Quoted By: >>11944436

>>11943896
>Even if we make the wildly improbable assumption that the behavior of our society could be predicted through the manipulation of, say, a million trillion simultaneous equations and that sufficient computing power to conduct such manipulation were available, collection of the data necessary for insertion of the appropriate numbers into the equations would be impracticable, especially since the data would have to meet impossibly high standards of precision if the predictions were expected to remain valid over any considerable interval of time. Edward Lorenz, a meteorologist, was the first to call widespread attention to the fact that even the most minute inaccuracy in the data provided can totally invalidate a prediction about the behavior of a complex system. This fact came to be called the "butterfly effect" because in 1972, at a meeting of the American Association for the Advancement of Science, Lorenz gave a talk that he titled "Predictability: Does the Flap of a Butterfly's Wings in Brazil Set Off a Tornado in Texas?" Lorenz's work is said to have been the inspiration for the development of what is called "chaos theory" -the butterfly effect being an example of "chaotic" behavior.

Anonymous

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Anonymous Mon 27 Jul 2020 23:28:37 No.11944436 Report

Quoted By:

>>11944429
>Chaotic behavior is not limited to complex systems; in fact, some surprisingly simple systems can behave chaotically. The Encyclopaedia Britannica illustrates this with a purely mathematical example. Let A and $\ X_{0}$ be any two given numbers with 0<A<4 and $\ 0 > X_{0} < 1$ <1, and let a sequence of numbers be generated according to the formula $x_{n+1} = Ax_{n}(1-x_{n})$ For certain values of A, e.g., A=3.7, the sequence behaves chaotically: In order to bring about a linear increase in the number of terms of the sequence that one can predict to a reasonable approximation, one needs to achieve an exponential improvement in the accuracy of one's estimate of $\ X_{0}$ In other words, in order to predict the nth term of the sequence, one needs to know the value of x0n with an error not exceeding $10^{-k}$ , k a constant. This is characteristic of chaotic systems generally: Any small extension of the range of prediction requires an exponential improvement in the accuracy of the data.

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