Information loss

Our lack of perfect information about the world gives rise to all of probability theory, and its usefulness. We know now that the future is inherently unpredictable because not all variables can be known and even the smallest error imaginable in our data very quickly throws off our predictions. The best we can do is estimate the future by generating realistic, useful probabilities.

~ Shane Parrish from, https://fs.blog/2018/05/probabilistic-thinking/

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It’s a good article—of course, why would I link you to something I think you should not read?

To be fair, I skimmed it. But all I could think about was this one graduate course I took on Chaos Theory. It sounds like it should be a Star Trek episode. (Star Trek: The Next Generation was in its initial airing at the time.) But it was really an eye-opening class. Here’s this simple idea, called Chaos. And it explains a whole lot of how the universe works. Over-simplified, Chaos is when it is not possible to predict the future state of a system beyond some short timeframe. Somehow, information about the system is lost as time moves forward. (For example, this physical system of a pendulum, hanging from a pendulum… how hard could that be?)

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