boring stuff

aw, I think I’m seeing why my friends like Applejack so much. Well idk why they like her tbh, but I know why I like her.

Pinkie was my favourite of the mane six especially when I was going through depression last year. I guess it’s because Pinkie was crazily happy all the time, even if it caused her to be annoying she’d still smile and I loved that about her. I guess that’s what a lot of people miss about her especially from someone who’s depressed and wants that joy again.

But now that I’m NOT depressed and actually very happy in my life, I’m starting to look at AJ and how much of a hard worker she is. (I consider myself a hard worker when it comes to drawing, especially now that I’m trying to get these commissions done) So I can relate to that on a different level. Plus I really like her colourscheme >w>

So don’t even ask me who my favourite mane six is because I’ll never fully know


Harness randomness to succeed at life
THE American mathematician Claude Shannon was renowned as the father of information theory. But his colleagues at Bell Labs also knew him as a unicyclist, a juggler and the designer of an electromechanical mind-reading machine. In the early 1950s it was a big attraction at Bell, consistently predicting people’s behaviour in a guessing game by detecting patterns in their guesses. Only Shannon could beat it. As William Poundstone explains in How to Predict the Unpredictable, the machine’s power wasn’t down to its clever design but the fact it exploited a universal human weakness, “our inability to recognize or produce randomness”. Poundstone’s book takes up where the mind-reading machine left off, with the aim of helping everyone achieve Shannon’s guessing savvy. In other words, this book is a guide to outguessing people and computers by detecting their decision-making patterns. It’s also a tutorial in how to prevent others from anticipating your own behaviour. One realm in which readers can readily benefit by outguessing is standardised testing, since the pattern of correct answers is rarely truly random. Whether the tests are true/false or multiple-choice, and whether they are algebra quizzes or professional exams, examiners tend to make the same distribution errors. (via Harness randomness to succeed at life - physics-math - 09 September 2014 - New Scientist)