Shared November 12, 2018
Sometimes, numbers on sites like YouTube and Twitter jump up and down; subscriber counts lag, like-counts bounce all over the place. Why is it so hard for computers to count? To answer that, we need to talk about threading, eventual consistency, and caching.
Thanks to my proofreading team, and to Tomek on camera!
The Cambridge Centre for Computing History: http://www.computinghistory.org.uk/
I'm at http://tomscott.com
on Twitter at http://twitter.com/tomscott
on Facebook at http://facebook.com/tomscott
and on Instagram as tomscottgo
Why The Government Shouldn't Break WhatsApp
What's The Longest Word You Can Write With Seven-Segment Displays?
The Consequences of Your Code
A Brief History of Graphics
YouTube's Copyright System Isn't Broken. The World's Is.
Making metal crystals from Pepto-Bismol
Single Point of Failure: The (Fictional) Day Google Forgot To Check Passwords
Tom Scott vs Irving Finkel: The Royal Game of Ur | PLAYTHROUGH | International Tabletop Day 2017
Why You Can't Buy Dasani Water in Britain
You Successfully Stalked Us, Please Don't Do It Again.
How The Self-Retweeting Tweet Worked: Cross-Site Scripting (XSS) and Twitter
Making transparent wood
Seeing Other People's Steam Accounts: The Christmas Caching Catastrophe
FizzBuzz: One Simple Interview Question
The Two Generals’ Problem
That Time I Got In Trouble With The Government
Why My Teenage Code Was Terrible: Sorting Algorithms and Big O Notation
The Art of the Bodge: How I Made The Emoji Keyboard
58 and other Confusing Numbers - Numberphile