We encountered many beautiful examples of substrate-independent patterns in chapter 2, including waves, memories and computations. We saw how they we… - Max Tegmark

It’s easy for you to tell what it’s a photo of, but to program a function that inputs nothing but the colors of all the pixels of an image and outputs an accurate caption such as “A group of young people playing a game of frisbee” had eluded all the world’s AI researchers for decades. Yet a team at Google led by Ilya Sutskever did precisely that in 2014. Input a different set of pixel colors, and it replies “A herd of elephants walking across a dry grass field,” again correctly. How did they do it? Deep Blue–style, by programming handcrafted algorithms for detecting frisbees, faces and the like? No, by creating a relatively simple neural network with no knowledge whatsoever about the physical world or its contents, and then letting it learn by exposing it to massive amounts of data. AI visionary Jeff Hawkins wrote in 2004 that “no computer can…see as well as a mouse,” but those days are now long gone.

Life 1.0”: life where both the hardware and software are evolved rather than designed. You and I, on the other hand, are examples of “Life 2.0”: life whose hardware is evolved, but whose software is largely designed. By your software, I mean all the algorithms and knowledge that you use to process the information from your senses and decide what to do — everything from the ability to recognize your friends when you see them to your ability to walk, read, write, calculate, sing and tell jokes.

My favorite movie of all time is... Life of Brian. We really should try and reenact this epic skit, "What have the Romans ever done for us?" by saying "What has physics ever done for us? ...But ...besides ...the internet and transistors, what has physics ever done for us?"