We Study Billionaires - The Investor’s Podcast Network - BTC188: Claude Shannon and Information Theory with Jimmy Soni (Bitcoin Podcast)

Episode Date: June 26, 2024

In this episode of the Bitcoin Fundamentals Podcast, Jimmy Soni, author of "A Mind at Play" and "The Founders," joins us to discuss the life and work of Claude Shannon. We explore Shannon's groundbreaking contributions to information theory, including the concept of entropy and its importance in data transmission. Jimmy explains how Shannon's work laid the foundation for many of the technologies we take for granted today, including Bitcoin and blockchain technology. We also touch on stories from "The Founders," highlighting the tech pioneers and their innovative contributions. Join us for an in-depth discussion on information theory, Bitcoin, and the history of technology. IN THIS EPISODE YOU’LL LEARN: 00:00 - Intro 02:06 - The life and work of Claude Shannon, the father of information theory. 07:10 - The foundational role of Shannon's work in modern technology. 20:31 - The relevance of information theory to Bitcoin and blockchain. 20:52 - Stories from Jimmy Soni's book "The Founders" about tech pioneers. 28:58 - How Shannon's concept of entropy relates to data transmission. 32:52 - Insights into the problem-solving approaches of early tech innovators. 40:42 - How Bitcoin investors can apply Shannon's principles to their strategies. 55:16 - The impact of Shannon's interdisciplinary approach on his innovations. Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences. BOOKS AND RESOURCES Jimmy’s book, A Mind at Play. Jimmy’s Book, The Founders. Jimmy's X (Twitter Account) Check out all the books mentioned and discussed in our podcast episodes here. Enjoy ad-free episodes when you subscribe to our Premium Feed. NEW TO THE SHOW? Join the exclusive TIP Mastermind Community to engage in meaningful stock investing discussions with Stig, Clay, Kyle, and the other community members. Follow our official social media accounts: X (Twitter) | LinkedIn | | Instagram | Facebook | TikTok. Check out our Bitcoin Fundamentals Starter Packs. Browse through all our episodes (complete with transcripts) here. Try our tool for picking stock winners and managing our portfolios: TIP Finance Tool. Enjoy exclusive perks from our favorite Apps and Services. Stay up-to-date on financial markets and investing strategies through our daily newsletter, We Study Markets. Learn how to better start, manage, and grow your business with the best business podcasts. SPONSORS Support our free podcast by supporting our sponsors: Bluehost Fintool PrizePicks Vanta Onramp SimpleMining Fundrise TurboTax Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm

You're listening to TIP. Hey everyone, welcome to this Wednesday's release of the Bitcoin Fundamentals podcast. On today's show, we have Mr. Jimmy Soni, the author of A Mind at Play, and also the author of the book The Founders. We'll dive deep into the life work of Claude Shannon, exploring his groundbreaking contributions to information theory and their relevance to Bitcoin. This was such a fascinating conversation for me. I deeply, deeply enjoyed this.

We'll also touch on some of the fascinating stories about the tech podcast. pioneers featured in the book, The Founders, some of the billionaires that Jimmy has interviewed. All right. So with all of that, let's go ahead and jump right into this interview with the thoughtful Mr. Jimmy Soni. Celebrating 10 years. You are listening to Bitcoin Fundamentals by the Investors Podcast Network. Now for your host, Preston Pish. Hey, everyone. Welcome to the show. I'm here with Jimmy Soni. And I'm thrilled to have this conversation. I read your book years ago. This is going to be a fun chat to have.

because I'm such a fan of your book and I'm a fan of Cloud Shannon. And this should be a really fun one. Well, I appreciate it. I mean, Shannon's having a moment and like he keeps having these little moments. So I'm excited to dive in. It'll be a lot of fun. I had a person asked me recently, like a family friend and they were like, who do you think is one of the most inspirational or impactful people of the last hundred years?

And so we were like, oh, I don't know. And I said, well, a person that's really impressed me that I think doesn't get a lot of credit is Cloud Shannon because of his information theory and what it's really led to in being able to just communicate. Starting off, I'm curious why you decided to write an entire book, an amazing book, the resources in this. Man, you did your homework. I can't even imagine how long this took. What fascinated you to the point where like, I'm going to write a book about this guy? It's a great question and I really appreciate the kind words. This was one of those projects. I am not an electrical engineer.

I am not a mathematician. I was in sort of foreign territory here, right? Like I was trying to figure this out and make sense of it for myself so that I could make sense of it for other people. Because I had the same instinct that this was this hugely interesting, complex, important person. And like nobody had written a biography of him that made me sense. But I'll rewind the clock a bit to tell you how it came about.

A friend of mine sent me a copy of a book called The Idea Fee. Factory by this author John Gertner. And the Idea Factory is a really close look at Bell Laboratories. So for your listeners, like, they might know the name Bell Labs. They probably know the name Alexander Graham Bell, and they know that Bell invented the telephone. Fast forward a few decades, like several decades, six, seven decades. And the Bell Systems Telephone Company is this massive enterprise. I mean, it is basically, I think, like the second largest employer in the country outside

of the Defense Department at one point. Because they run the phone system. And the phone system at that time is everything. Within the Bell system, they create this organization, sort of like what Google did with this Moonshot factory, where they created Bell Laboratory. So the idea was like, we have this Labs arm, right? They do all this kind of interesting research to advance the company.

And the idea factory is about Bell Labs. And the reason there should be a book about Bell Labs, frankly, more books about Bell Labs, is because Bell Labs was arguably like one of the highest concentrations of just pure innovation ever in history, of all time. They win six Nobel prizes. They invent the transistor. They invent touchtone dialing.

Make improvements on the bazooka. They invent communication networks. Like they invent satellites. So it's basically the entire underpinning of modern life. In that book, there's one section, a tiny section about this guy who worked there, whose name is Dr. Claude Shannon. And they talk about this guy

who's like unicycling in the hallways in chest in the cafeteria. He's kind of weird. He like sort of a loner, but like with really smart people, he becomes really good friends. And in 1948, while working at Bell Labs, he publishes this paper in the Bell Systems Technical Journal. And that paper really is one of the reasons why modern digital life exists the way it does. And he didn't collaborate with anybody on it. I call it the ultimate side hustle, because he like did it on the off hours, nights, weekends, et cetera. And this

paper will one person describe it. It sort of came like a bomb, right? Because all of a sudden, you have this new field information theory that's invented basically out of a whole cloth. And he does it. And he's super interesting. He like invents the world's first chess playing computer. All of these things. I'm reading in this book, The Idea Factory. So I go on Amazon.

This is market research for authors. And I'm like, all right, let me buy eye book about this guy. And I type in his name. And I can't find anything. And my friend had actually suggested the friend who sent me to books and, hey, you should really look at this Claude Shannon guy. He might be a good subject for you to write about. And I realized, I was like, there's just like a space on the bookshelf where his story should

be. And he's more than just some scientists. He's like a wildly interesting person in the way he lived his life. And so I was like, so those are like a key ingredients for a biography. One, is the person interesting to read about because otherwise it's just like watching Patriot or doing your homework or something. And the other is, did they do something important? And I kind of had both of them in this subject.

And I also got the sense that like Richard Feynman became famous and became a personality. Albert Einstein became famous, became personality. This is someone with the same IQ points, the same contribution scientifically, at the same level, we should say. But Claude Shannon actively avoided becoming famous. And so it made his story in some ways more interesting, but it was the reason that no one had done a biography. And so that's the kind of story that led me to writing the book. I was just like, I mean, really, if you bail boil it down, I went on Amazon to try to buy it. I couldn't find it.

So I decided to do it. And obviously there's a lot of steps from there. but I found him curious and inventive and interesting and super important and it was kind of like somebody should do this. And then I just sort of dubbed myself with somebody. Well, no, to your point, I know I forget how I became interested in him. And that was exactly what I did. I immediately went to Amazon and was like, all right, I'm going to deep dive on him.

This is like I said, a couple years ago. And your book is really kind of one of the only books out there. And obviously it had great reviews. and then I read it and it's amazing. And maybe that's why you're not going to have any competition is because you've covered it so well. But you're right. I mean, there's not many people that have written about them.

That's right. I would add two disclaimers for your audience because it's sort of important to get some of this stuff. Like people are listening and like, why should we keep listening to this? The other thing that Claude Shannon has is an incredible IRA as an investor. People don't know this. But he was actually like a very gifted investor and got super obsessed with the stock market, wrote a bunch of papers and ideas and concepts in this.

space. He was friends with Henry Singleton, who Warren Buffett admires. Warren Buffett, I think, once called Singleton, like the single best capital allocator in history. Shannon served on the board of Teledyne, the Teledyne Corporation. And there were all of these things in the investment world, too, that Shannon did that, again, nobody knew about. And I only discovered them later in my research. I would say the other interesting thing about Shannon's life is he wasn't a tortured genius, right? Does that make sense? We have this vision of like, if you're going to do something great in the world, then you need to have like deep scars. Like, you didn't hate yourself.

And there were definitely times in Shannon's life that were hard. But on the whole, one of the remarkable things about Shannon's life is he's basically like a playful genius throughout his life. Right? And it's why I called the book of mine to play. And it's what people can take from him that's bigger than just like, hey, there's this scientist. It's really, if you read the book, I think the way that I intended, what does play?

have to do with serious work, like science or like investing or like building machines or anything else. Why is playfulness important? That's one kind of through line in the book. And the last thing I would say is like, for anybody listening who is like, hey, this sounds super interesting, but I have a lot going on and I don't want to read a book. There's a really good documentary called The Bit Player that you should be able to Google and find. And it's the only documentary about Claude Shannon. And to your point, I thought Shannon mattered. And what I didn't know is that there are actually a lot of people who agree with me. And so the book has become kind of a cult hit among, particularly like I would say, investment professionals, but many others because they actually want to know more about him.

And I didn't know that going in. Ironically, it's like the thing Shannon would have liked least, like being sort of pseudo famous now. Right. And so it's like he passed away many years ago. But like he actually particularly avoided this kind of fame and interest. and whatever, because he just wanted to do his own things all the time throughout his life. Let's take a quick break and hear from today's sponsors. All right.

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how he would not respond to letters and communications and was really kind of detached from any type of comms. And the irony of this is that he mathematically figured out how to conduct communications, but then in his own life and the only way he was conducting him, he wasn't communicating. And then to a second point in your book, if I remember this correctly, and correct me if I'm wrong, but I remember there being something in there about how his parents were investors and making him read maybe like the Wall Street Journal or something when he was a really young kid. So he kind of came very wired for understanding, investing at a young age. Am I remembering that correctly?

Yeah. So I'll do the first one first and then the second. Actually, let me tackle the investor because that one's easy. No, actually, he was the parent. Here's what happened. So in their later ages, like when I think they were around 50 or 60, Shannon leaves Bell laboratories for MIT. And the family settles in a town called Winchester, Massachusetts.

It's one of his bedroom communities outside of MIT. and they start to get interested in the stock market. So this is like in the 70s and 80s. So they buy a stock ticker. They start reading the quotes. They start buying copies of the Wall Street Journal. And I interviewed Peggy Shannon and Andrew Shannon. Peggy and Andrew were son and daughter of Claude and Betty Shannon.

And they told me about how like we grew up with a lot of weird stuff happening around the house because our dad was Claude Shannon. I said, well, give me some examples. And they were like, well, not everybody's dad like juggles. Yes. Not everybody's dad has like a two-story workshop that's filled with like toys and robots and chess playing computers and stuff. And they said, and the other thing is our parents were very seriously interested in the

stock market. And they would tell you like we had the Walser Journal's table. We were all talking about it. They had people over. They were talking about investments. So it was sort of in the air in that way. And that was interesting. I don't know that it shaped those kids profoundly in any way.

I mean, maybe it did. It wasn't anything I got into because I was actually writing the story of Claude Shannon. But I found it interesting that all these things became a part of their. family life too, right? It wasn't like work was separated from life. There was this, just to give a story on that, there's this great moment where they're hosting some dinner party or something and Peggy Shannon is carrying toothpicks, like a box of toothpicks from one place to another. I think it was toothpicks or pins or something. And she's walking. Something happens. The box of toothpicks drops on the ground. And she looks up, her dad's there. She thought her dad was going to get mad or something,

like a parent might get upset that she's like made this mess. And her dad looks at it and says something along the lines, it's been a while since I looked at this, but her dad basically looks at the and says, did you know there's like a mathematical equation that can predict the pattern that would be created by you dropping those teachings on the ground, right? Another story in this vein, when they would decide how to do dishes, instead of just assigning the roles to people, like, hey, Andrew, it's your night to wash. Or, hey, Claude, it's your night to wash. They had a multi-sided die, like a 16-sided die or something. And they would roll this dice, and every person had a series of numbers. Like, that was the

game of chance that they would play to see who had to do the dishes that night, right? So there are things like that that were in the ether in their home. It wasn't the case that he was the parent. You asked him, your first question was about fame and like his relationship with both fame and a claim, like just like being acclaimed for this information theory. Here's what happened. It's actually kind of a great story. This paper is published in 1948 in two parts.

And almost right away, his world of electrical engineering and mathematics and communication technology notices. And everybody's like, oh, this is a big deal. Like, you're like, Claude Shannon has done something significant here. So he's put on all his lists of like the most promising scientists. He's given a profile in Vogue magazine or this famous photographer comes and shoots photos of him. And he has this moment where he's like a scientific celebrity for like a hot second. He doesn't enjoy it.

What he wants to be doing is he wants to be in his workshop tinkering. He wants to be building machines. He wants to be thinking. He wants to be writing. And he kind of just like turns out like he just doesn't embrace the fame that's coming to him. People would send him letters. And he had literally a folder that was like letters I've waited too long to respond to, right? He would just like tuck it in there. He wouldn't give talks. He didn't say yes

to invitations that he got to give talks unless his wife wanted to travel to the location that they were going to go. So he gets invited to give prestigious talks around the world. And it's only on the urging of his wife, Betty, that he's like, all right, fine. I'll like go give the talks so he can travel to Japan. But he wanted to keep to himself and do his own work. The other thing that happens that is in some ways more interesting. And I think it's more relevant for an age of like TikTok and Twitter and meme stocks and everything. All of these people, look at information theory and they're like, oh, man, I could use information theory to explain everything. I can use you to explain birdsong. I've used this, that, and the other.

So you've all these people jumping on the bandwagon. And Claude Shannon actually publishes this very short piece. I think it was like 340, 350 words called the bandwagon. And it's to his people in his field. It's to other electrical engineers. And what he basically says, I'm paraphrasing, is he says, listen, I know there's a lot of enthusiasm about information theory. but we have a lot of research left to do to take the work I've done and turn it into practical technologies for people and to write new proofs and to design new technologies and everything

else. So basically it's effective. It's like everybody's slow your role. This is cool. It's not the theory of everything, right? And he actually does what so many people don't do. Like if you have a successful paper or a successful book or a successful anything in modern life, most people just like ramp that up. They need 25 versions of that. Right. It's like, oh, fast and that. the period is successful, we should make 12 of them. It's like, let's do that. Everybody got on the bandwagon. And you have this temptation, and he rejects it wholesale.

He says, no, this is like information theory. It needs to be further developed. There needs to be more research, more work. I understand that work is valuable. But he says, let's keep our house in order is what he says. Right. To me, it was like, it was super counterintuitive. It's not what you would want to, like,

it's not what a lot of modern people would do, right? You have one viral song hit about finance pros. And now you're like, you're like signing a deal in Columbia. And Shannon has his viral scientific hit. And instead of doing what everyone else might have done, he leaves Bell Labs, goes to MIT, builds a workshop, and starts the next phase of his life, which is like this interesting tinkering game playing machine part of his life. Wow.

It's funny you made the comment about everybody just basically saying information theory is this or that and everything else. I found it really interesting. And I know this is a huge tangent. David Sinclair, I don't know if you're familiar with his work out of Harvard and his information theory of aging. That's right. Which is talking about how the epigenetics in your cells are losing data and losing information and then they can't communicate in order to keep you healthy is a huge pool on some of these ideas that Shannon has put forth. I would say, by the way, he takes it very seriously. Dr. Sinclair, we've actually corresponded about Shannon.

He's a huge fan. And I wrote him when his book came out because he had mentioned Shannon a couple of us and said, hey, he might. and he had already read a mind of play. Yeah. We created some really nice notes. Now, what's interesting is he is carefully and rigorously applying the principles that are in information theory to talk, to discuss his field. And so there is this, like, I think what Shannon was saying was like, let's electrical

engineers, it's not trying to puff this up too much in our domain, but the metaphor or some of the principles that are in information theory apply very well in other domains. I'll give you another example that's probably more relevant to your audience and actually have some crossover with some of the other work I've done. One of the things that people have mentioned is that there's a fair amount of overlap in the world of Bitcoin and cryptocurrency and the work of information theory. Yeah. And one of the reasons is because what those systems do is reduce noise in financial transactions, right? They reduce latency. And well, noise is not latency, but they reduce latency. And for a separate project when I was interviewing

Elon for the founder's book, which is about PayPal, and we were talking about the role of my, what is money? He has this view. He said, money is just an information system. It's a way for us to avoid having to barter. That's almost an exact quote from something he said to me. It's like a way that we don't have to barter. It's an information system. And he says, because it's an information system, you could see how a universe of digital currencies is actually a much more efficient information system by Shannon terms than something like handing you pressing a dollar, right? Because there's a lot of friction involved there. And so, there are some interesting applications of information theory around the world and useful ones

in the case of Sinclair information being coded into our genes. Shannon actually did work on genetics before he published the information theory paper. And so there are some useful applications. I think what was happening is that people were not treating the work with sufficient seriousness in 1949 and 1950 and 1951. And a lot of those people were within Shannon's field. And that's why he had to kind of throw the brushback pitch of that bandwagon paper. Wow.

I'm so impressed that you coordinated with David on the work he was doing there too. That's so cool. And if people are curious about that, oh my gosh, go read his book. What's the lifespan is the name of the book? He's got another one as well. Yeah. It's phenomenal. And he does such a great job kind of making it accessible for people that maybe aren't into biology. Okay. I would love for you to explain information theory for people that have no idea what it is. Like, if you were going to really kind of break it down into, like, the basics, explain what it is and why it's so groundbreaking and why it's actually this underpinning for all communications we see today. Yeah, this is one of those where I'm going to do my best. And I translated it and spent a lot of time thinking about that chapter of the book when we were writing it. If you feel like my explanation is inadequate, find me on Twitter, shoot me a DM or shoot me an email. And I'll just send you that chapter of the book because it'll do a much better job than I can in 30 seconds of it.

explaining it. But here's the visual that I would use that helps best explain what information theory actually does and why it matters. Right now, you and I are able to communicate over Zoom, or I can pick up my phone and download a YouTube video, right, and watch a YouTube video. And the reason that that process can happen is because of the transmission of information, but it's compressed information. And what information theory does is it provides a model for the compression and transmission of information without loss of meaning. So I'll give you a kind of example that emerges in the paper. There are a bunch of different ways to convey a piece of information without losing meaning. You can shout louder. You can repeat yourself. You can do many

things to communicate information better. But some of those ways of communicating information better will just add to the amount of time or the amount of bits that you need to communicate information. So the real trick in information theory is how do I tell Preston a sentence in this video and how is it communicated as efficiently as possible? There's a number of components to this, but one of the things that Shannon explains to people in information theory is there's a lot of redundancy in the English language, right? So he'll take a sentence, like the fox jumped over the something, and he'll show how even if you eliminated most of the vowels or other letters within that sentence, someone reading it could actually still make sense of it.

And that compression is one of the ways that you and I can have this exchange without it taking seven years. And the reason I'm doing that is because I want to connect the theory to the technology, which is this is effectively the theoretical plumbing for all of modern life. It affects everything from the phone calls we make to this exchange to a video or a song. if you're using Spotify, you were in some meaningful way using Claude Shannon's information theory. The idea is how do you most efficiently, and in the most compressed format possible, communicate information with high fidelity.

And what Shannon outlines is he outlines a theoretical limit for some of these. It's called the Shannon limit. And since he laid down that limit, engineers have basically been trying to get us technologies that communicate up to that limit. And that's why it was such an earthquake. Someone finally figured out that there was a model for this. And he lays it out in a little drawing. And if any of your listeners are curious, they can just Google information theory and they'll see a little drawing.

And he basically outlines that there is a sender, there's noise, there's a channel, and there's a recipient. And he shows you different ways to reduce noise in that channel. And so that's what we're trying. That's the basic guts of information theory is how do we communicate. Now, a number of surprising things emerge from this. One of the surprising things that emerges, Shannon posits that the actual value of information is not the meaning, it's the surprise. So, so that's a really interesting thing. What do you mean by that? Yeah. Yeah. So what he's saying is it's that all information can basically be abstracted

into a mathematical formula, that there's no difference between me saying the fox jumps over the dog, mathematically, there's no difference between me saying the fox jumps over the dog and the dog jumps over the fox. They're actually identical. So meaning doesn't matter. Like the actual bits mathematically, they're equivalent. He also points out that because, the English language has so much redundancy in it, it's surprised that is the thing you're trying to control for. Like if you have a word that's unexpected after another word, that's new, quote unquote, new information. So a good example of this. You, the letter you always follows the letter Q. So if you see a letter Q, I think it's like a 99.999% chance that the next letter after

Q is you. But if all of a sudden, let's say next year, Merriam Webster, there's some word that goes viral and it's Q and it doesn't have a you after it, that is actually, from an information theory perspective, that is more information, meaning this new word is surprising, and ergo is new information, because we have to do more to convey it. We have to do more to communicate it.

It's a little abstract, but I think people can get the idea. The basic idea is there's a ton of redundancy within the English language, and you can eliminate whole words and whole vowels, and people can still understand something. And so you can use that redundancy to your advantage. Because what you can do, and this is where Shannon applies the information theory,

you can encode messages with certain kinds of redundancy so that my message to you is conveyed, not perfectly, but almost perfectly. And by the way, I don't know people ever watch this show Silicon Valley, but when they're talking about lossless compression algorithms, the lossless compression algorithm idea traces directly back to this paper. And so for people who are working in modern communications, you stand in a 70-year legacy of something. that started with Claude Shannon, which is how do I get a text on my phone to be transmitted

from planet Earth to a satellite and over to Preston without losing any of the meaning. And that is the theoretical work that Claude Shannon did. This is mind-blowing stuff. Something that I've heard recently is with like chat GPT4 and because this is when we're talking about intelligence, we're talking about compression, right? We're talking about the compression of patterns. One of the things that I read is they took a, and I might be getting this way off, but generically speaking, I think this is accurately described. When you take a wave file and you compress it into an MP3, it has way smaller amounts of data that's being stored and also descend, I heard that they could take a wave file and they could run it through one of these AI models and it would give you better compression than the MP3 compression, meaning it's being stored and with the same level of quality.

is an MP3, but with less data required to store it. This all relates back to Shannon's, right? This is all interconnected with the math and the theory that he came up with and correct me. I'm probably saying this way wrong. But with more entropy, and I think this is what you were getting at there, is with more entropy, you allow for more data to be transmitted? Is that being stated correctly? Yeah, and people are going to have to forgive me since it's been a number of years since I wrote this work and since the book's been out. Yeah. And I think we have to be careful because data and entropy are really specific terms within

this field. So I want to be careful about not sort of going over my ice skis or getting things wrong. I'm way over mine. I'm way. I don't know. It's all right. But the basics of what you said are correct. Two things.

One is these compression algorithms have gotten better over time. And it doesn't surprise me that large language models, which are studying language broadly defined, that they have found ways to compress files further. and make the amount of data that is transmitted smaller. Because what they're probably doing is they probably have better ways of predicting what the next word or what the next bit or what the next thing will be. And when you can get that prediction improved, you don't need as much data transmitted.

And so if you didn't need a specific word or bit and you cut it out, you've taken, let's say, 10 units of data and you've made it into eight units of data. And there was a time when we needed to convey every single bit. And now because of these predictive technologies, we can communicate with fewer bits. And by the way, we're at the 10,000 foot level on this. We're also at the limits of my understanding

about how LLMs actually do this. But these things are intimately tied together because the whole thing, the whole sort of genius insight for Shannon was we actually don't need most of the English language. And that applies across different. We actually don't need this, this, this, and this in order to communicate a message. And it allows for more efficient communication.

So it doesn't surprise me that the world of AI and LLMs has embraced this to make compression better. And I actually suspect that this is going to herald an era in which technologies like 6G are come to market more, much more quickly. Like, I think there's going to be a bunch of changes because of this. Because honestly, it's part of the magic of playing around with some of these tools is seeing exactly how they know what to do because they are predicting things that used to be done by us. Even on image creation, right? On image creation, they can predict that this shade of blue

should be based on statistical probabilities. Probabilistically speaking, this shade of blue should be next to this shade of blue on a picture of planet Earth. That's a probabilistic determination. They're making a best guess at what something could be. But it turns out the machines are pretty good of guessing. They've gotten better. Yeah. Well, I might go way over my ski tips here on this next one, but I want to ask it anyway. I'm curious if Shannon wrote about the increase in demand for energy for basically unwrapping the messages on the receive side because they're so deeply compressed.

So when we get into compression, we could compress a message down to, I mean, as an example, we could take one of these LLMs that are 600 gigabyte files. That's all the bigger that some of them are. and I mean, they're insanely powerful. They can answer almost any question, and they're only about half a terra. We could compress that using Shaw 256 encryption down to 64 characters, like all 600 gigabytes

down to 64 characters and transmit it very simply. But on the other side of that, to understand what was in that half a terra file, it would take, I did a little bit of math here before I did this with you, it would take 3.6 times 10 to the 49th years to decompress that file that is only 64 characters by taking a half a terra. So there's energy required on the receive side of a message that's been deeply compressed. And so you're putting the onus on the receiver. So I'm sending you this message right now as we're talking. You're receiving.

You're computing it inside your head. But if I was going to simplify and compress all of that message into two words and send it to you, you now have to do a whole bunch of work on your end in order to decompress those two words, assuming I could compress it into the two words, just getting dramatic here with the example. So I'm curious, did you study anything that Shannon ever talked about that? Because I think this is, and the reason I asked this question, I think in the coming 10 years, 15 years, the energy demands that we're going to have in order to deal with all of this compression, especially AI compression is going to be off the charts. And I don't think the world's prepared for it. I think

it's about to get crazy. It's a great question. And in some ways, there's a very simple answer, which is Shannon was in the following great position or privileged position. He pushed information theory, not the application of information theory. And so he had this great. So there's a bunch of great lines about this from other people in the field. And they basically said they were like, Shannon didn't identify what the error correcting codes were going to be or what the algorithms are actually going to be that did this. All he did, his genius insight, was identifying that this was a statistical possibility. It was actually possible for engineers to do this.

And what that did is it was like a starter gun. It basically sent the rest of that domain off on a search to find the codes that would most efficiently compress information that would reach the Shannon limit that would enable the technologies of today. Shannon didn't do that. He had a hugely groundbreaking insight in that this is possible, we can statistically do this, but he laid out the theoretical architecture for it. A good analogy or a good way to think about it is when Galileo was basically challenging

the church and saying, no, the earth revolves around the sun, the sun doesn't revolve around the earth. This is heliocentrism versus geocentrism. Galileo didn't have to do everything that came after the acceptance of geocentrism, meaning there's a bunch of stuff that we've discovered about the fact that the earth revolves around the sun after Galileo. He wasn't doing all of that, but it was important that the theory of geocentrism be broadly accepted as the truth so that we could do all of these other things.

In the same way, once Shannon identified that it was possible to do this, it sent the rest of his field off on the research that for the next 60, 70, and it's still going on today, would create the algorithms that we use to transmit information. So the short answer is not really, and he wasn't really thinking in practical terms about what energy demands would be required. Because remember, at the time he's doing this writing, 1948, computers are still like these room size things. You know, like computers are mechanical devices. They're not digital devices yet. The digital world is still super far off. And so he eventually becomes an enthusiast.

He always builds some of these things. He gets an Apple 2 that was delivered from Steve Jobs. He embraces all of that. But the technologies are very primitive in 1948. So it's a conversation that's a little bit, it's years away. But it is why, like why with the subtitle and with the way that the book kind of was embraced, it's like we really do live in Shannon's world. Everything that is going on today is Shannon's world.

And I agree with you, by the way, that I think the information, demands based on these technologies are going to be significant. Ironically, I also think there's a world in which these technologies help us figure out that problem. Yeah, true. There's a lot of promising stuff happening in this world. And I'm not at all an expert in that. But my sense is that ambitious, smart people are trying to figure that out.

And they're giving it a college try that seems pretty serious. Well, to your point, and you mentioned 6G earlier, that's exactly what you have. So when we're looking at the electromagnetic spectrum and all of the, this demand of people wanting to zap communications through the air, the bandwidth is extreme. I mean, it's limited. There's only so much bandwidth that you can shoot these messages through. But with AI and compression, now we can take the code that we're communicating in, run it through AI and figure out ways to compress it even further, which then allows more space to shoot

these messages through the electromagnetic spectrum. So perfect example of what you're saying. And well, you use the word code as did I, because there are codes. There are error correcting codes that are used to communicate digital messages. It's an interesting word, though. And the reason it's interesting is because the other cool part of Shannon's life is what happens right before the information theory paper. He is a codebreaker during World War II. And so part of what he's studying, like here's an example.

There was a phone system that Churchill used to communicate with FDR. It's called Sig SIG Sally. Sig Salli was designed to develop at Bell Laboratories. I think it was a pretty top secret project. A lot of information emerged about it after the fact. But Shannon was one of the engineers working on these code breaking devices. He was also somebody who like, that was an important job during the war, was figuring out how can President Franklin Delano Roosevelt send a message to Winston Churchill that cannot

be intercepted by the Nazis. And so part of what Shannon has to do is think about, well, we have to actually figure out way to do this so that we're not transmitting a ton of data so that they can avoid detection. You have to figure out little tips and tricks and tools to like take a certain word and turn it into something entirely different. Alan Turing was doing this work, obviously with like ciphers and other things in the UK, Turing and Shannon, funny enough, became friends. There's a part of this that is about encoding and a part of it that interestingly, like runs through a legacy of code breaking and code making, which I always found like one of the more interesting parts of this, like the idea of

secret codes, things that we were trying to hide, ultimately lead to a world in which we don't have to hide anything. You can give me anything about yourself, right? It's a kind of cool thing. It's a very interesting historical irony that it is information we were trying to conceal from people is what gives us the ability to conceal nothing from people. Let's take a quick break and hear from today's sponsors. No, it's not your imagination.

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slash income. This is a paid advertisement. All right. Back to the show. A little context of a comment you made earlier in the conversation where you said that his children said that they had the roll of dice and create entropy to do the dishes. now that they've got a little taste on what he did for the world with some of these theories, it makes more sense, I guess, to hear that that's the kind of thing he did with his kids.

The other piece of it, I'll tell you, is like a bunch of my favorite Shannon stories, ironically are not scientific stories, they're parenting stories. Maybe one more example. I think this made it into the book, but I don't know if it did. There was an oversized tree on his property at one point. I was like a big tree. They had a bill of the land. And the natural thing to do is like it was an aging tree and you got to take it down because it's

safe or whatever, or there was an eyesore. I don't even remember why they were going to cut it, but they needed to cut it. And Shannon had this thought, instead of cutting it down, what we should do is we should hire some people to basically file the tree down so that it's sort of like a flagpole that's growing in the ground. And then we should carve a skull at the very top of the tree and hoist a pirate flag up this carved tree with the skull on top. And that's exactly what they did.

So they built. They're like, they like fashion the file this tree down, like got a skull on top, hoist a Hoisted to Jolly Roger up the flagpole. And the whole reason they did it. There's no purpose. They just did it because Shannon thought it was funny and kind of interesting. I'll give you another example. One morning, I guess Andrew,

his son woke up, said he's got a performance at school, and I guess he was going to do a solo performance, and there was some kind of competition or something, and he was going to play the trumpet. And Shannon said, well, would it be interesting if your trumpet breathed fire? And his son was like, yeah, I would.

So Shannon constructed a flame-throwing, trumpet that Andrew used at school to perform. Again, with no practical purpose, just because he thought it would be funny and kind of clever and interesting. And this is, we talked a lot about information theory and about the details and the arcana of the science. It's worth appreciating that a lot of the fun of doing this project was just figuring out kind of the zaniness of Claude Shannon.

He was just like somebody who had an idea and did it. It was a part that's more endearing because we, especially adults, we take ourselves super seriously, right? We all take ourselves a little too seriously. Shannon never did. It was one of those things. I still remain inspired by it. A mind at play, right?

I mean, you nailed the title. And when you're saying all these stories that are just, they sound so loony. I go back to a statement that you said where you were describing the word, the sentence there that you kind of flipped. But you were like, it's the same amount of data, but it's the surprise in it that communicates or is, what was the word you used? The information is contained in the surprise. Meaning if I can predict it, it's actually not informative by Shannon's definition of information. It's not informative. Information is contained in the surprise.

That's one. It's like a little bit of a very simplified way to think about information. I'm just thinking of the flagpole with the small time. I mean, it's just so, it's such a surprise. All right. Unfortunately, I'm so sorry. I take great pride in reading any book of a person I bring on the show. I have not read the founders yet.

I need to read this. What? Gladly send a copy along. I would love to read this, especially because our show covers all these various billionaires and what they did. And to give people just a quick rundown on what the book was and what you were trying to accomplish and maybe your motivation on it. For sure. And I'm happy to come back on and chat about it.

Yeah. Yeah. A much longer conversation. Yeah. I suspect in some ways like your audience is more familiar with the people who are at the heart of that book than they are with Claude Shannon. Yeah. Maybe. PayPal.

is a company that has existed at this point for over 20 years. If you're listening, you've probably use one of their products because they own Venmo now. Obviously, the core PayPal ecosystem, everything else. And it also has given rise to a group known as the PayPal Mafia. That includes people like Elon Musk, Peter Thiel, Reid Hoffman, David Sachs, the founders of Yelp, YouTube, LinkedIn, Yammer, Palantir. I mean, every significant company to come out of Silicon Valley, arguably, for 20 years has some tie back to this ecosystem, whether they're an investor or something or whatever. Many years ago, I think at this point,

five or six years ago, maybe actually longer. I got this idea in my head. I was like, everyone's talking about these people, but how come no one's ever gone back and asked them like how they all ended up at the same company at the same time?

That seems kind of weird, right? Like, I was literally, the question was just like, wait, hold on. Elon and Peter and and and and and all these people worked at the same company. like, what was in the water? I mean, it was literally the question I was asking. It's one of my sentences in the introduction to the book,

what was in the water there? Because if you think about it, if it was a graduate school, literally every person on the planet would want to get in. Yeah, right? And I got the sense that there was a story there that hadn't been told because what happened is that these people became so larger than life,

that the focus of everyone's attention is kind of like, what are you doing today, not what did you do 20 years ago? So I, through Hook and Crook and a lot of intro, and everything else. I interviewed around 300 people. And I wrote the book. It's called The Founders. And it's about the story of PayPal from 1998 to 2002. So it is the story of creating this payments architecture and this startup during the dot-com bubble bursting and during all these other events happened. But basically, it's this crazy four-year sprint to build this company. And it has everything in it from like what you'd

expect, like kind of like, how did Elon get the idea to do this company? Why was it called? X.com at one point, all of those things. In addition to, like, there are a lot of things that were invented at PayPal that you probably use without knowing it. I'll give you one example. Capt a test. These tests where you have to identify that you are a human and not a robot. Those were commercialized at PayPal.

And the reason they were commercialized at PayPal is because when PayPal designed its system, a bunch of people started creating bots to create fake PayPal accounts so they could get the sign-on bonuses, the company needed to devise a way to separate Preston flesh and bud human user from like 10 robots Preston created to collect $10 bonuses, right? They did that with the first application of the CAPTC tool. Surprise. It was the first time they did it with surprise. It was right.

And at first, the people who were on the product team were like horrified because they thought this would like nuke new signups. And it turned into an innovation that is literally all. all over the internet. I mean, you can't use most websites these days without having some kind of financial services website, certainly, without having some kind of gate like that. I could go on and on. That group created things in financial services that still affect our lives today.

And then I thought it was just interesting to know, like, before they flew private and ran the world, who were these people? Who were these people when they were in their early 20s? How did they figure life out? How did they get to Silicon Valley? What's a common thread you found in that question? is what they did early in their life. There's a lot of people at the heart of the story.

So there's a few common threads. But I don't want to paint with too broad a brush because it's like a little tough. I would say that a lot of them were building things on computers when it wasn't cool to do so. And when it wasn't lucrative to do so. So remember, the internet economy doesn't really become an economy until the mid to late 90s when Netscape goes public. Before then, the internet is like this thing that academics used and it's a thing that like nerds use. It's not a way to become a billionaire. In the 80s in particular,

if you wanted to become very, very wealthy, you went to financial services. You didn't go into technology. And if you went to technology, you did hardware, not software. You didn't do the internet. So all these people are kind of tinkering, they're playing with computers,

they're doing things, they all move out west. The boom starts. A lot of them study computer science, engineering. Not all of them. There are a bunch of people on the business side who are more traditional humanities tracks.

But I would say that one common theme is I noticed that many of them had built businesses before they ever joined PayPal. So for Max Lebedgen, who's one of the co-founders, one of the best known co-founders, he is now the CEO and founder of a firm. PayPal was his fifth business and we had four failures in college while he was like moonlighting as a student. He was also building businesses. It's his fifth or sixth company, right? Elon had a computer company he built in college. Then he had zip two. They had an arcade when he was living in South Africa. And then he had PayPal. So it was like

his fourth, maybe his fifth. And so you just have people who are serious. entrepreneurs, but minus the word entrepreneur, because that sounds, it makes sense fancier than it is. They were just building businesses and trying to figure it out along the way. And so I would say that's a common thread. I would say the other common thread is there's a lot of game playing, puzzle playing, chess playing.

There's a lot of like that in the air at PayPal. There's a bunch of stories in the book about that. But obviously Peter Thiel was a well-known chess player. But I would say a lot of a lot of chess titans within this group, a lot of poker players. There's a lot of that kind of puzzle-solving game playing in ether as well. But it's interesting. It's fascinating, to me, it's a fascinating story because it's like, who are these people before they become relentless objects of attention today? I find

the most interesting thing to me about writing biographies is figuring out who people are before they become rich, famous, or successful. Because to me, I want to know who they are when they're closer to me. I'm trying to solve these rubrics cues for myself. I don't actually find most of the contemporary coverage on these people all that interesting. Because the truth is, when you're at that level, it's not your life becomes a little bit more like boxed in. But when you're in your 20s and nobody knows who you are, the world is a blank page. You got to go upstream, right? Yeah. What is one of the stories, I mean, you've interviewed some just incredible people, 300 people for the second boy. Oh my God. What is a really unique, a surprising? Let me use

that word. What is a surprising story from one of these billionaires are very unique people that you had the opportunity to interview, that you just off the top of your head. It could be any one of them. Oh, I mean, there's so many. But let me pick a couple. One, one that people may know, but they should really think a little bit more about, which is there is this temptation these days that I think if Elon ate a piece of fruit, there would be a bunch of hate about that piece of fruit. I think if he suddenly got into like raspberries or do like an anti-rasbury coalition

or some nonsense like that. And I think one of the nice things about writing about a very specific and defined period of his life is that I wasn't asking him any questions about SpaceX, Tesla, Twitter, none of that. I was studying the years 1998 to 2002. And one way to think about the years 1998 to 2002 in his life is that it's during this period that he gets kicked out, he gets overthrown at PayPal as a CEO. He almost dies because he contracts malaria and meningitis while on a trip abroad.

And he loses a child. and people don't really know because he's not going to talk about it all the time but I went pretty deep on the history of that little moment and I wrote about it at the end and you think about

what someone's been through and it looks like these days his life is a glide path he can say whatever he wants, etc. There's this real profound four year period of difficulty in which he struggles

with the hardest thing that anyone I think could struggle with as a parent myself I can't fathom losing my kid and he has an influence in died, Sudden infant. SIDS, whatever the acronym is. Yeah.

And it's this really interesting thing. And I think at the end of Chowell 14 is when he leaves a story. Because he gets thrown out as CEO. But I think people would really benefit from reading that, especially people who kind of throw stones and don't realize that there was a period in which it wasn't a glide path. There wasn't a $56 million pay date. You need to have a little bit of, I think, humility about the people in our business life who become like business celebrities.

and to appreciate that there's a humanity there. There's some challenge there. There's some struggle there. So that's one story. It's a little surprising. The other thing I would say is the fact that this company, PayPal, it's created like as the dot-com bubble is just getting to its peak. And months after its creation, March of 2000, the bubble bursts.

And all of a sudden, like the NASDAQ loses 86% of its value that year, 86% of its value. People, like, Barron's is writing, like, they had this famous cover story. It's like, DOT.com, right? And it was about, oh, Amazon. Dot bomb. It was like Amazon. It was like Amazon's share price at the time is $9.

And everyone's like, oh, this is it. The internet's like a total hype machine. It's all nonsense, right? It's all foolishness. September 11th happens during the early creation years of PayPal, 9-11. And it massively changes things like K.C. rules, know your customer rules,

and financial regulation, because the government suddenly wants to crack down on Paris financing. There are all of these things that happen in this coming. They get sued. They get hacked. People are trying to defraud them. They're in this epic battle with eBay. They are in one of the worst markets for IPOs after 9-11.

It wasn't an IPO for three or four months because, I mean, 9-11 is like the financial services industry is in rubble, literal rubble. You have two competitors, X.com, which is Elon's company, and Confinity, which is Peter Thiel and Max Legend's company. they fight for three months, then have a merger that's basically organized within four or five weeks. And this is all just before the bubble burst. There's no financing left in venture for this kind of company. So I would just say that the surprising thing about PayPal is the mere fact that it survived.

The most surprising thing about PayPal is this company should have gone under. None of this should have happened. And it stayed alive. And that's the cool part of the story is how do you keep a company alive when you're under siege and the pressure is on and everything is like chaos. And there's not low interest rates and there's not easy money. And there's not $100 million rounds that are being thrown at people. To my mind, that's actually like one of the cool things about this.

And it's one of the things that this team walked away with is they built something successful, but it came during a period of real hardship. And it meant that every subsequent thing they did, YouTube, Yelp, Palantir, SpaceX, Tesla, LinkedIn, that they were accustomed to this difficulty. And that's probably a good way to preview that particular project for those who were interested. I like that point a lot. Well, an interesting tidbit, and you might have to correct me here on this, but when Elon left as the CEO and Peter Thiel, I believe, was the one that came in and replaced him. There was obviously bad blood there when that took place. But what's interesting is decades later,

Elon is really struggling with SpaceX. It's about to go bust. And Peter Thiel was the guy that showed up. I can't remember the number, but I believe it was over a billion dollars and gave him a lifeline that was somewhat of a repayment or karma or whatever you want to call it later. Because I did this homework. It's funny. You referenced something that is one of the final lines I have at the end of the chapter 14 of the book. Yeah.

And it was actually when SpaceX, not at a billion, it was I think it was 14 million or 20 million or something. Okay, sorry. And it comes from Founders Fund. And it is one of the parts of the story that people miss, which is they did have a feud. They did have a moment where Peter replaced Elon as CEO. There was a lot of bitterness on both sides. If you were to talk to Peter and Max, they thought they were doing the right thing. If you talked to Elon, they thought they were doing the wrong thing.

But it is the case that Peter invests in Elon and more than that, like invests in Elon and often he had said to be something And there's a reason I don't invest in other companies and industries that Elon is in because I know what it's like to compete against Elon and you're going to lose. Right. It's relentless. And so it's interesting because it isn't just that there is respect. There's a difference between respecting somebody and giving them a $15 million check for their rocket company. And so you're right on on the broad outline, which may have been some temporary misgivings about

how things happened. But over time, there's a partnership there that has actually. really was stood a lot. People underestimate Elon's proof of work from his early days, like the Zip 2, I remember reading that he slept underneath of his desk. And so when he buys Twitter and he goes in there and he's conducting the audit and then he fires 80% of everybody in the company and everybody's like, the place is going to fall apart. There's no way you can do that. It's because Elon went in there and was like, all right, let me see all the code contributes of every programmer in this company. And he's going through and he's auditing all. And he's like, okay, yeah, we can downsize this by 80

And we're not going to have any issues because I've written the code for this GPS navigation system three decades ago or whatever it was from that moment in time. So yeah, there's people that underestimate like what that guy has done in his life and how gritty he has gotten his own hands in writing code or whatever it might be from an engineering standpoint. And it's hard, right? Because he's one of the most covered subjects in the world right now. And by the way, Like my book is not, it doesn't praise, it doesn't like, it's not a book where I'm trying to praise him or trying to criticize him. I just went where the facts took me. So I interviewed a lot of people.

I had a bunch of email. I had about six gigabytes of email from that era that someone shared with me. So I had a day bite. So for people who were listening, maybe the reason to read the book is because you can read Elon's resignation note. You don't even have to take my word for it. Like, it's all there. It's all just facts. But I would say that one of the things that happens is that people underestimate his willing to,

to do whatever it takes, to have his companies be successful, and the way that that kind of focus inspires engineers to do their best work too. A lot of the people writing about Elon are not engineers. And so the problem is they're writing about things, but they don't have any kind of understanding of how those things work. And so it's easy to look at something like, I'm going to lay off 80% of Twitter and say, that's terrible. It's another thing for somebody who has been the CEO of at that, when we have two internet companies, Zip 2 and Pip, to look at a situation and say, well, here are the things that matter in this business, here are the things that don't matter, and I need to cut cost because that's part of the issue here is that it's just things are

deeply inefficient. I can't be, I don't know enough about that situation to know what was right and what was wrong and what was executed well and what was executed poorly. But I think that one caution I would give to listeners who are reading things about Elon is to remember that most of the people writing about him don't have an engineering background. And it's actually a real deficit when you're writing about things like rocket engineering or car design or anything like that. Love it. Jimmy, I am so thrilled with this conversation.

And your book is phenomenal for people that want to pick this up. A Mind at Play. And the other book is called The Founders. And is there anything else that you want to highlight or point people towards a website or I know you're active on Twitter or X? Yeah. I mean, I'm not that active on X. I mean, I'm as active as I need to. but I love hearing from readers.

And you can just find me, I have a website, jimmysoni.com, but just find me on X and DM. I love hearing from folks who are in this space. And I would just say, I really appreciate your enthusiasm for Shannon. It's actually one thing that unites the two worlds. The people I interviewed knew who Claude Shannon was.

Like Elon references Claude Shannon on X from time to time because these ideas still last decades later. And there is something really inspiring about that. I mean, like ultimately all of us want to do work that stands a test of time. And so it's interesting to me. that Shannon has had a kind of a second life. The only other thing I would say is I am quite curious

if Anthropics Claude is named after Claude Shannon and nobody's been able to pin that one down for me. And so I'd be really like, if any of your listeners or you or somebody put a signal into the universe and figure that one out, I would be really grateful. That'd be cool. Let us know, folks.

Yeah, we might get, I don't know, we get 100,000 listeners on a shit. There you know, maybe somebody, maybe somebody working on Anthropic notes and they're like, no, no, no. It's actually John Claude Van Dam. They just thought that was really cool. Awesome. Well, Jimmy, thank you so much for your time. This was a real pleasure. And hopefully we'll

get another chance to chat sometime in the future. That sounds great. Thank you, Preston. All right. See you. Thank you for listening to TIP. Make sure to follow Bitcoin Fundamentals on your favorite podcast app and never miss out on episodes. To access our show notes, transcripts or courses, go to theinvestorspodcast.com. This show is for entertainment purposes only, before making any decision consultant. This show is copyrighted by the Investors Podcast Network. Written permission must be granted before syndication or rebroadcasting.