Everything is data

Happy Wednesday! So I think it was a week or two ago (what is time? A topic for another newsletter) that Apple held their WorldWide Developers Conference. In it, they introduced a few interesting software things, but the one that caught my attention as a music lover was the addition of lossless audio to the Apple Music subscription at no extra cost.

I’m no expert, but I’m fairly confident that I understand the basics of compression due to a few years of writing about audio. But I wanted to dig deeper and really understand the math of how compression works. Spoiler alert: I still don’t. Turns out, when you dive deep into audio compression you end up at the corner of physiology and information theory. That said, I do feel like I have a better understanding of basic Information theory and data compression now thanks to these resources.

In this issue

📖 A book.

📺 A visualization.

➕ The math.

The Information: A History, a Theory, a Flood

This was a book that I first came across while listening to a Bitcoin podcast during the ‘demic (the most 2021 statement). The Information: A History, a Theory, a Flood is a book by James Gleick that goes way back and tells the story of data and information. It reads almost like a novel with a large cast of main characters. It tells the stories of the many people whose work in mathematics helped lay the groundwork for cryptography, data transmission, and compression.

I read this book months before WWDC and I would highly recommend it if you’re at all interested in data but have never taken a course on the subject. I’m sure a basic college-level 101 course would go into way more detail, but as someone who was coming into this with a strong 4% knowledge of how data works, this book acted as an easy-to-read guide to the names, concepts, and math that I should be familiar with.

Information Theory

One of the people discussed in the book I just recommended is some dude named Claude Shannon. He was basically a mathematical genius and worked for Bell Labs during World War II on top secret work for the US government. Back in the day, Bell Labs would’ve been the equivalent of working at Google or Microsoft today. All of the top minds were there on defense contracts and instead of building bombs or new guns, they were trying to gain a deeper understanding of things.

Clause Shannon in particular worked on everything from signal processing to efficient data transmission, but his main work during the war was on high level cryptography and code-breaking. Eventually, a few years after the war he published a paper called “A Mathematical Theory of Communication” that is now the foundation for how we understand and use information. It is a TON of math trying to understand this but I found this YouTube video that’s a perfect visual analogy for what information is.

A Short Introduction to Entropy

This is a short lecture I found on YouTube where some basic math is used instead of scrabble letters. A basic understanding of how information transmission works felt like it was just a word on the tip of my tongue until I saw this video. I won’t say that it all clicked immediately but it was definitely my first “ohhh” moment.

Replacing letters with actual numbers and watching the math work out in a practical way left me feeling like all my research wasn’t in vain. I find all of this fascinating and I’m not entirely sure how it’s useful in my everyday life, but I think it’s cool as hell.