Unmasking Shadows with Chuck Palahniuk | Fight Clubs, Killer Families, and Deep Reflections

Transcript

This isn't your average business podcast, and he's not your average host. This is the James Altiger Show on the choose yourself network. Today on the James Altiger Show. Now more than ever, are we put in the place where we need to stand up for what we believe in. We have these powerful, engaging tools to influence others. But I mean, keep the balance. You believe something, share it. What's cool about the hacker culture is information should be free. So then everybody's sharing this stuff. Before, to go up against an institution, I'd have to almost be an institution. Now, I could go viral. It reminds me though of this trend from humans to data. You gotta be smart with your own data because look at the history. Look at the pattern of history. It's either you trust the government or you need to be the person policing that. Yeah. I sort of think data is the government. Right. You may actually, you probably have heard of cryptocurrencies like Bitcoin and Ethereum. I call them choose yourself currencies because they don't depend on any institutions to function, and they're simply exploding in price right now. Some have jumped as high as 3000%, 21,000%, and even a rare 81,000%. If you're missing out on this boom, don't worry. You're not alone. Most people are not investing in crypto simply because they don't even know how to get started. So I decided to do something about that. I wanna help listeners like you get started in this booming market. So I'm offering a free 6 video series masterclass on cryptocurrencies, all for free. I'll walk you step by step through the entire process. If you're interested in claiming this free masterclass, please go to altiture.i0. That's altature dotio slash masterclass where you'll find all of the details. So this is an odd podcast for me, and I'll explain why. Normally, at this point, I will introduce my guest. We'll have some nice chatter. I'll kind of explain his background a little bit more. I do have a guest right in front of me. I'm going to be calling him mister x. Or if that sounds kinda funny, maybe I'll just start calling just start calling him x or something like that. And his voice is going to be slightly distorted for reasons that will become clear as you listen to this podcast. So, do you prefer mister x or master x? I prefer mister x would be fine. Right? As long as you don't call me DMX, I'm okay. Well, DMX might if you were if you were DMX, it might be okay. That's true. So when we met, the first story I heard was, of course, this really fascinating story, about this kid in a military academy where something happens. I wanna get I wanna start off with that story just to kind of set the setting of where we're going with this. But why don't you start off with that story, and I'll ask questions along the way. Yes. You're at a military academy, and we're actually, I'm I'm not even gonna let you talk. I'm gonna ask some questions. Were you, like, the geekiest guy at the mill military academy? No. I wasn't. I actually wasn't the geekiest guy. I, like I mean I mean, it just depends who you ask. Right? I thought I was the man back then. Right? But I wasn't the geekiest guy. It was an interesting collective of, kids who went there. Right? And, you know, you had, like so there's a lot of big donors. Right? A lot of, like, big names, current president, all that went to that school. Right? So then they had a good endowment, so they had high speed Internet. Right? So everybody was kinda geeky because that's what I mean, that's what you did in your free time. Right? So you had access to all this compute were you had been previously been interested in computers, or now you suddenly had access to all this computing equipment and Wi Fi? And this is in the nineties, so it was when the Internet was, like, booming. So things were happening. Did that kind of, like, draw you into the computer room instead of the athletic field? I mean, well, look at it this way. Right? I mean, like, to communicate to the outside world. Right? The only medium we had at that point was the Internet. Right? And then so, like, if I wanted to talk to people at home, right, if I wanted to talk to what I can like girls, you know what I mean? Like, I had to, like, find them up, like, find them online and, like, so that was our that was, like, how we like like, we're so secluded. I mean, not jail, but we were heavily, I don't know, confined in a space. So that that's how we got our that's how we got out. I mean, I know the school. You were you were far away from every place. Right. Right. Right. Right. Right. Right. Right. So But we didn't go off campus. Oh, you weren't allowed? No. I mean, during the week, you weren't it's not like you go in, go out, man. Everything was regimented, and it was great. I loved it. But everything's regimented from, like, you wake up, 1st mess, salute the flag, go to class, 2nd mess, right, back to cla*s. Then change 15 minutes, go to sports. Right? After sports, 3rd mess. After 3rd mess, you have 2 hours of study hall, 1 hour free time, go to sleep, do it all over again. And so so you have some free time though which you used in a very interesting way that I can relate to. I kind of we we have, I think, at least back then, we had a similar knowledge base. You went in a specific direction with yours that almost got you into major trouble, but ended up changing the course of your life. Yeah. Absolutely. And so what what's the describe the actual event the actual event that took place. The event. Mister x. So how old were you at this point? About 13 years old. Right? 13, 14 years old. Right? So, I mean, what do we have to do? Right? So we're just tinkering around, and what what I was interested in, it's, like, there there are websites that they didn't let us go to. Like like, even MTV.com was censored. I mean, there's a ton of stuff that they had censored. So, like, the first thing we wanna do is, like, man, how do we how do we how do we how do I see that? Right? So then, I mean, I was pretty good in school. Right? So I didn't like the 2 hours of study hall. Right? I just spent, like, trying to figure out, like, oh, hey, man. How do we do this? Right? So, like, I mean and you there were sites back then that you were allowed to go to. Right? Like, I remember, there's a few. There's Soldier X. Right? There's Port Wolfe. There's a few where you could learn on, like, hey, man. How do you crack, you know, these firewalls? How do you how do you do this? How do you do that? Right? So then I gained a big interest in that. Right? And and back then, by the way, you mentioned MTV dotcom, and and I I apologize if I interrupt too much. I'm a serial interrupter. Go. But, like, mtv.com, you mentioned specifically, it reminds me that back and you also mentioned firewalls. It reminds me that all these companies and sites, particularly in the late nineties, they had no clue what security or firewalls were. Most companies were kind of disconnected in a weird way from the business of the Internet. Absolutely. So mtv.com, they didn't realize I and I know this from my own personal experience. They didn't realize that their email was completely open to outside invaders. So just as a joke, I would email like, at the time, I was working at HBO. I would I would get into the MTV email using ways which which you'll describe in a in a second, And I would email my boss, like, job offers from MTV and, you know, wait a day or 2 before I told them. We were doing that. I was just making a a a joke. But all these things were were were I don't wanna say they were easily hackable. You still had to know the language to speak. Like, what people don't understand is that every service you use on the Internet, like email, web, you know, mobile type services, they all speak their own specific language to each other across the network that's that's different than English, and it's different than a programming language, but that's how they communicate. Hey. Are you okay? I'm okay. Let's start exchanging messages. And so MTV just if you all all you had to do was know how to speak that email language, the SMTP protocol, and you were in. Yeah. You could you could be CEO of Coca Cola. Right. Exact well, I would I would do that. Right. Yeah. No. I know. CEO of MTV. Yep. Yep. So so so okay. So tell us what you did and roughly with who. Alright. So check this out. So then, like, one of the things, like, I mean, there's an ISP that a lot of people used back then, right, and had a great jingle. And then, so I was just, like, hacking around. ISP is like an Internet service provider. So so millions of people were signed up to the Internet probably for the first time ever Correct. Through this company. Absolutely. They were. They were. Their commercials and everything were large. And then so, like, I'm I'm like, okay. Cool. How's this work? How's this going on? Maybe there's a way I can get to mtv.com if I, like, can manipulate who I am. Right? Which at that point, like, wasn't the case. Right? The firewall is basically, like, you know, our IP and whatnot. Right? But I'm messing around trying to say, oh, cool. Maybe from someone else, I can go see it. Right? So so go ahead. And then, like, they had these files back then, like, they stored their like, think of it this way. There's a there's a piece, like, you said in that transfer protocol, right, that says who I am. Right? There's a hashed out password. Right? And then they to go to the to the ISP, and I get a response. Right? So then my response was, like, you know, like, my handle, my email address back then, and then, you know, hash. So I'm like, alright. Cool. I mean, what happens if we change a string around? Right? So what I was able to do, right, there's a certain method in which you could ping a response and get a lot of responses. Right? So then What do you mean? So you would, What think of it as, like, if you if for all database geeks out there, right, and they'll kinda know it's like a hash string where, like, if you think select star, Right? It was something to that accord. Right? Where, like, where I I see. So it'll let me try to explain because I think I understand now what you're saying. K. So you you basically, instead of giving a specific name or or requesting instead of requesting, does a certain name exist that I could start communicating with, you requested everybody's name. Right. I I went ahead and took the full response. Right? That the stuff. Knowingly. Not knowingly. Right? I was just, like, messing around with stuff I was learning. Right? And you did that because you wanted to get some accessible names that you could use? Like, was that the No. I wanted to get in c mtv.com. So I thought if I went in as someone else, maybe I could see it. Right? Elementary, the dumbest thing. Right? And then so then I went ahead and did that. Right? And I started looking at so, like, the the first thing that you would see, like, for just you, you would see your basic information because they disclose some of that. Right? So let's say let's say mister x. Right? And then here's some personal information, and there's some hash string. Yeah. And some of the hash string. Right? So then I did that, and then I started seeing, like, the that text file, like, that black terminal, like, grow and grow and grow and grow and grow. And I'm starting to get a lot of people's names. Right? They're not mine. I don't know these people. A lot of information. Right? So then I'm like at first, like, you're like, woah. This is kinda cool. Right? Woah. What is this? Right? And then you then you and then you kinda like and then the file still keeps growing and populating. A few minutes later, you're like, woah. I'm gonna get in some serious trouble, man. So so what other information other than names and then addresses was it giving? I can't really disclose that, right, per, like, I mean, and I'll tell you why in a second. But it gave personal information, right, that wasn't normally that should have been or wasn't supposed to be or they didn't how's this they intended to be disclosed. So so so I'm not gonna ask you to confirm it. The only thing I could possibly guess is financial related information, but don't don't say anything. You got out you're getting all this information on on a screen That I could've done a lot with. But then, like I said, my intent purpose, right, was to look at stuff that I was censored. So, like, censorship drove me to this pretty much. Right? So so then I I emailed it to him. I emailed the ISP. Right? I found, like, support, you know what I mean, help here. So you're 14 years old, and you just simply emailed customer service the file essentially of Yeah. All their customers This is what I found. And this quote unquote information you have on them. This is how I did it. Right? And then part of it is I had to hack a file that was local, right, on my machine. Right? I sent that that thing, and I get brief description of how I did it and whatnot. I'm sorry to interrupt you. You had to hack a local thing because That's what talked and generated. You had to change the right. So you had to change the way you were, querying their communicating with their Correct. Ancherer Correct. If that's the way to describe it. And you and the idea is if you were to do that, they can say, oh, if we it's very simple. If we see this kind of query, we don't we'll change the way we respond to it. It would be a very simple fix on their part. Yeah. Super simple. Right? And it was probably an oversight. It was a bug. Right? I mean I don't believe it. This is also one of the biggest companies in the world at the time. Right. And I think just people just didn't think about these things. Probably. You know what I mean? And there's still lots of things people don't think about all they think about that one. Crazy. But, it's crazy what people don't think about. But, yeah, they didn't think about it. But you know how much software not gonna get back to what you just said. You know but do you know how much software goes out that's bugs? Right? You know what I mean? Like, I I almost look at some of the software companies that are out there, all great, all innovative. Right? But, like, think of, like, if they were the ones in charge of the elevators. Right? How often when's the last time you went on your computer? Right? And it's like, oh, man. This thing doesn't work right. Like, Matt, what was that the elevator, dude? You know what I mean? So, like And all the elevators I forget if you were telling me this or someone else. All the elevators are, like, networked together right now. Like, all the Otus elevators I don't know. That wasn't me, but I would not be surprised. Yeah. I'm pretty sure someone was telling me that that they're all kind of centralized network together. So one person could monitor how they're all doing. Yeah. Probably certain aspects. I would hope it wouldn't be all aspects, but probably certain aspects of, like because then they get safety information. That's how they find things, like these loopholes now. Right. You know what I mean? So back to that. Right? So then, sent that out. I'm like, alright. Cool. Nothing happened, like, a week or two passed. Alright. So so you you send them a message to them of this critical breach in their entire company. In fact, it was such a critical breach that now if a company had a breach like that, they're required by law to instantly disclose. Yep. But I but the SEC wasn't sort of aware of these breaches back then, so so they weren't required. Correct. Correct. So then and then so then I'm like, alright. Cool. I'm chilling, dude. Like I said, I'm a kid. Right? What am I worried about? Right? I'm worried about, like, hanging out, getting girls, all that type of stuff. Right? So then, did that. And then one day, right, I I like, so, you know, we had a chain of command. Kids ran kids at that school. Right? It's a great institution. I think it's one of the best schools you could ever send your kid to. And then so then, I get called to the general's office. Now this guy, now, like, just let let me tell you. Right? So we had, like, a corps of cadets of, like, 600 kids. When this guy would walk into the mess hall, everybody's loud, everybody's going. You know, kids are from city. We're, you know, we're kids. Like, young kid, like, eating. Right? Think of, like, a lunchroom. Right? When this guy would walk in, it would get quiet. Silent. Pure silence. So so this guy old army, like, you know, like, 2 star general. Right? And, I keep I keep trying to say the I I immediately wanna say his name. Right? But, great guy. But he had, like, you know, he had, like, a boot that he jumped off helicopters with with the Vietnam mud still on it on his desk. This type of guy he was. Right? So then he I get called to his office, and, like, no one gets called the superintendent's office. Were you were you in a classroom and, like, somebody No. I was right outside. It was it was right sorry. It was I was outside right before second mess. So what happened was everybody's marching into the mess hall, and then I get called out. You know what I mean? Mister x, the general wants to see you. I'm like, what is going on? So I'm thinking, like, what happened? I'm like, alright. Dude, I made out with that girl last week behind the mess hall. Maybe that's it. I don't know. Like, I don't know. Like, what's going on? I'm like, it doesn't like, you never got called. Right? Then I'm standing out there, and there's this position called parade rest where you put your hands, interlock your thumbs. Right? And then, like and you're standing after some stand and wait there for, like, 15, 20 minutes. Right? And I'm just sweating bulls. Like, what I do? What's going on, man? Am I getting I don't know what I did, because, you know, fear is really from the unknown, and I really didn't know what I did wrong. Right? So I'm just like, oh. So then I get in. Right? There's a police. Is this a good like, like, making you wait for 15 minutes, does that increase the fear? Is this, like, almost like an interrogation tactic? I I I don't think it was an interrogation tactic, but, man, did it feel like one. Like, I was sweating bolts. Like, the first, like, alright. Cool. 15 minutes later, man, I'm like I'm like, I'm ready I'm ready to cut a deal, you know. Whatever it is. Yeah. I did it. Just give me you know what I mean? So then I walk in the, the general's office. Right? And then I see to my right a police officer. I'm like, woah. That's the first thing I saw. Like, because I mean, like so, like, before I went to military school, I grew up in a a city. Right? And, you know, like, cops, like, I don't know. We just kinda I'm scared of them. Right? So then, and then I look, I'm like, oh, man. Even though there's nothing to be scared of cops now. Right? But I I'm like, woah, what is going on? There's a cop. And I see 2 suits on my left right, and the general is sitting at his desk. And then, like, dude, I'm still feeling the heart pump now. Right? I'm like, oh, man. What's going on? Is the general looking angry at you? The guy always looked angry. He looked angry probably at his wife. You know what I mean? No knock to hurt. The guy would I mean, like, he saw real stuff. Right? So then, and then he and he's looking concerned. Right? And he had these, like, window glasses. Like, these you know, these huge glasses with the 2 frames that connected both lenses, like, he's sitting there wearing them. And then he puts his hand up right on his desk, and he looks over to me. Right? And he goes, that's him. And then one of the suits is like, I remember, if if I say the handle, it's a lot funnier. Right? Because it was an interesting handle. But they they they I'm gonna say the handle was, let's just say Looney Toon. Right? They're like, are you the Looney Toon? And I was like, yeah. Yeah. Yeah. What what's what's going on right now? I thought they had maybe, like, tracked I thought, like, maybe they tracked my Internet history, and, like, I would like, all they saw was just going to mtv.com or something like that. I'm, like, oh, man, dude. I don't know what happened. Right? So then, and then they went ahead, and they told me. They said, like, hey, They went through this process, like, hey. Do you know you broke these types of laws? Right? Do you know these are, felonies? Do you know what you did was, critical? What you could have done and all that type of stuff. So these were suits and a police officer? Suits and a police officer. How many suits? 2. And one police officer. Why was some 2 people in suits? Just what they wore. Okay. They were, like, detectives? No. They worked for a government agency. Can you say what government agency? I have a 3 letter agency. Right? Yeah. A 3 letter agency. Right. Not as high up as one as you think. Right? Let's just say that. Right? So and then so because, you know, it was more on a localized level. Yeah. Right? And then so they're there. I'm like, okay. Cool. They asked me these questions. They said, you know, you broke these laws, this type of stuff. One thing they really started harping on was, you know, like, how did I do it and and stuff like that. And I just told them, like, dude, it's in the email, man. Like, like, it's there. I'm sorry. And I, like, immediately as a kid, I'm like, I'm sorry. I'm sorry. I'm sorry. And then and then, like Were were you crying? I was tearing up a little bit behind. Right? But I was just like, I you know you know what the first thing that happened that goes to your head? Right? It's like the first thing that went through my head is like, oh, man, I don't wanna go to jail. Right? All that that's why I was just thinking, like, like, I don't wanna meet the toss the salad guy. You know what I mean? Like, I don't wanna do any of that stuff. Right? So and then, and then the general now this guy, well, like I said, Vietnam general, like, had money boots, seen some real stuff. He was cool. He was like so they said, you broke all these laws. You know what I mean? This is what you could face. Here's your senses. Like, yeah, like, you know, really blame on hard. And then he looks over at them. Right? So he has his hand still on his on his desk, and he turns his elbow and looks over at them. He's like, gentlemen, the way I see it is he saved you a lot of money. I should be sending you an invoice for this, and we're done here. And he looked over the copy, like, kinda nodded. Right? I don't know if you knew the cop or something like that maybe. And then, and, you know, and that was and then he dismissed me, and that was pretty much the the end of it, except we have this thing called tours. So during that hour of free time and on the weekend, if you had a tour, you get them for doing something wrong, being late to class, something like that. You have to march 1 hour. So one tour is 1 hour with a rifle. Right? Like, a 20 pound rifle. I got a 140 of them. Oh my gosh. Right. So forever, basically. Not forever. Right? You can knock them out. And luckily, I worked the system a little bit. So, like, I people knocked the extra off. Like, I did 1 for 2, that type of stuff. But yeah. So that's the trouble I got into. Right? And then I was banned from the ISP for life. So so so still banned to this day? Still banned to this day. And As far as my knowledge. So but this kind of began a chain of events that led to you getting a call much later on. Is it is it directly related? Directly related. So one of those guys so what happens is it's like when you're on you're not really on official parole, but in and I don't know. Maybe this is the case just me. I think it was probably the case standard operating procedure. Right? But, I had it like a like a handler. Right? It wasn't like a parole off. You didn't even know about it though? No. No. No. No. Right? But, like, no. But they would check-in. Right? So, like, what's weird about the school, like, my power of attorney was, like, to, a retired Vietnam army colonel. Right? So it's not like I really had parental. So, like, I had a a so and every once in a while, I remember I had to do a meeting one time and just ask he just asked a bunch of questions about, another ISP and that type of stuff. Right? And then What would they ask? Like, how how could you get information on other people? Right? Like, how like, if you were to go to this ISP, how would you do it? I remember I had a follow-up meeting, that type of stuff. Right? And they never asked me to do it because I wasn't allowed to. Right? But they said, like, how what are some of the things? They asked, like, it's pretty much proctale exam, like, what I did, and could it be done other places to pull information? And and how detailed did you get with them? I mean, I told them, like, what I would do. Right? But, yeah. So so, yeah, that's how that's And that was and that was basically someone from the government asking about US companies, how to get into them? I would say but really from, like, the threat perspective was really, like, could this happen here? Do you think this could happen here? Do you think this could happen here? Are you putting your own judgment on it that it was from a threat perspective, or do you think maybe the government just wanted a a a door in? Well, after so after that, right, I, you know, I'd end up being contracted by the government. So, like, from that, like, knowing that So so describe that. So how did it happen? So you you graduate high school or something. Yeah. What happened? So I graduated high school, you know, and I kinda, like, lollygagged in college for, like, a month or 2. Right? And then I got a call, right, to work for the government. Right? For in a in a cryptography program. Right? Can you can you so cryptography program describes a lot It did. It was like like a data nerd crunching a ton of analysis for pattern recognition. Can you say which agency? No. Okay. I can't. Right? But, it it started out the same one, and then I went to a different one. Right? But I, you know, is that I was an independent contract. If you were to have said the agency, would we say, okay, I I know what that is? Yeah. Okay. Yeah. Absolutely. I would say, yeah, aren't too many of them. Yeah. So then worked on them. That was really cool. Right? Because they pay a buttload. Right? I mean, for my from For a 19 year old. Right. Right. And then, and then, like, you know, like, we got to look at stuff and look at data and look at things and What sort of data were you looking at? Bunch of different ways. I mean, so we're just looking. A lot of times, I didn't necessarily know. Right? So what I was really doing is pattern recognition. Right? So, I can give the example of, like, burn phones. I I mean, a burn phone is a phone, like, when someone gets a Walmart and they drop. Right? And then, like, because people were tracking the unique identifier. Like, hey, I know this is James because of his phone number, so I can track his calling pattern or his calling, you know, patterns. Right? Who he calls, whatnot. Right? But then when James loses phone, these these things like, oh, okay. Cool. That's it. Well, we we lost them. Like, you know what I mean? I lost the send of the government or whoever. Right? Just to let you know, like, they know the only person you'd ever try to fool with that is maybe your significant other, right, with a burn phone. I mean, like, it's useless because what happens is Or or or if you're a criminal, like a drug dealer or whatever. No. No? No. Because, I mean, like, at at that level, right, what you do is you reverse engineer the calling pattern. Right? So what happens is it's like, let's say, James, you you call 4 people within a certain delimited amount of frequency. Right? Certain pattern, you create a calling pattern. Those 4 people call, like, 3 more, and then there's a calling pattern there and so on and so forth. So then once you can reverse engineer and understand the calling pattern, doesn't matter if James changes his phone number. I know it's still James just with the new number. So it's almost like a fingerprint. Like, you're not identifying people by the phone number because they might be getting rid of phone numbers frequently. They are. Yeah. Yeah. They were. So and and these are are criminals that that someone's trying to track for whatever reason. And you're saying this tree of calls is like a fingerprint. Because what what if I don't know. I'm just asking as a question. What if you and I were to call the same three people? How would your tree be different than my tree? If you were assuming we call because then it's indicative upon frequency, right, as one layer in the waiting, and then who those three people call and so on and so forth. Because my call to those 3 Maybe at a certain time of day. Maybe it would trigger different different frequencies of their next layer and the next layer after that. Correct. So, like like, if we're involved, let's say, let me I mean, think of it. Right? Let's think, any any husband and wife, right, trying to get to soccer practice or pick up the kids on time. Right? You know what I mean? Maybe, like, my wife I call my wife or something. Cool. Alright. Cool. And my next my wife's next call is maybe to our babysitter. Right? And then so, you know, hey, that call before probably I mean, I'm making this simple. Right? That call before probably came from Eddie because that happens a lot versus when my wife's, mother calls her. Right? She may call me. Right? Or someone you know, she's not calling the babysitter with a good amount of frequency after that. Right? So so okay. So so, you developed for this agency this adult I was one of there was a team. There was okay. So there was a team of people. You were on it Yep. Where you developed, this ability to kind of identify people not by what what number they were using because they were getting rid of their numbers by using burn phones, but by building these trees for essentially every but how would you would you do it for what's an example where you did it where something happened? Like, where because because you didn't do it for everybody in the country. You would do it if you were on a a specific case, I imagine. The that is correct. But you, that is correct. Can you say, can you give a specific, case and what happened? No. Okay. I can't. But, but, like, there were, like I mean, there were many cases in in which, you know, threats were neutralized, right, because of things like this. What I can tell you, right, is, you know, somewhat of the same properties, right, that went into that also went into catching meth labs early on. Right? So all it was is we just used, power consumption at that point. Right? So someone's, like, I get like, more than peak so, like, there's an average benchmark for a town for for that house and then for the town and whatnot. And if you see statistically significant moves and power, right, they're leaving a pattern. Right? And we correlated that with, you know, other busts that they had with Catching Methyl Labs. Right? I see. So you had you had a statistic you had a sampling of successful busts Yep. And it was and you matched And that makes the model tighter. You you you matched energy patterns in a town to those successful busts. Now if you got a new energy sampling, you'd run it through that database and see, oh, is there a potential does it match something that did lead to a successful bust? And then you know you probably have an active meth lab in the region. To just go check it out. So The guys on the ground would go check it out. In in the case of these burner phones, though, how does that match with the like, let's say you were looking let's say somebody was on the loose and was changing burner phones every day, and there was some high profile criminal. Just saying hypothetically. And, how would that what would be the equivalent thing that you would do here? So one more time. So so so so there's a high profile criminal Yeah. On the loose Okay. And he's throwing away a burner phone every day. That's all. Alright. So Magneto's on the loose using a burner phone. Yeah. And and every and every, police agency in that area is looking for this guy because he's a a well known criminal, and they finally call in your agency and your team and you to figure out what do we do here. So they so these guys had access to those feeds, so that way the guys on the ground could kinda use it for intel. But it almost it you predict with the propensity of, like, hey. This is who the person is. Right? And this is when he's calling, and this is who he's calling from. Right? How how would you predict? So, like, you would you would build a tree for, let's say, everybody in the area. Okay. Like, let's say But I I would so I'll so here's the thing. A lot of these times, right, the intelligence on the ground and thankfully to the those men and women who serve on the ground, right, can give you a good snapshot. Right? They'll say, like, hey, look, I know we called from here at this time, and we get that once. Right? You got a good tight signal. So then you know then you know then you can look at the trees of everybody who called from that area or spot Right. And start looking. And then you can weed out the ones. And then I would know look. So and once I got him once, then I know his calling pattern. I got a picture of it right there, snapshot in time, who he'd call next, whatnot until that phone died out, or who he called. And then who he called, I may have a snapshot on them. And then now I have, like so trying to find me, you know I called you, James. Right? So then I have James' pattern. Right? So then I got a snapshot of where mine where my my mind's coming from. Right? So then if there's, like, some random anonymous that keeps calling, right, then you can predict that that's me. Right. So the and and the reason it's anonymous because the number is changing all the time. Yeah. Yeah. Yeah. So so once so so then how does that narrow down into an actual capture? And and I and I do wanna say, we are taught we're we're all we're inadvertently talking about a high profile case that everybody knows about, but we're not saying what the exact case is. So this is a case you were on. Right. So what I would say is is that, like, there's a few factors that went involved. Right? And then one is understanding, hey, who's calling when. I mean, this person, we had family members. We had you know what I mean? Like, there there are some things we had. Right? Yeah. And then you can look for standard deviations within what like, if you called your mom every night at, like, 4. Right? And that's changing. Right? And then it's changing with so what what caused that event? Right? So what what's the next correlation we can call we can or the next phone number we can wrap to that? Then it's about understanding, like, we had some information as to, like, you know, with the call, right, especially with cellular call, like, what tower went over, what time, and to come up with a triangulation of who, where, and what. And then what happened, and if let's say, if someone gets camped out for a little bit, that's when that's when you got them. And is that what happened? Like, you you you identified a tree. They started making, you you noticed a similar tree while they were doing a doing a, you know, camping out somewhere or hiding somewhere, and you were able to essentially GPS in on them and find out where they were? Correct. Give the give the guys on the ground the intel they needed to make the move. Because, ultimately, it's their decision at that point. Let's stop to take a quick break. We'll be right back. When we use our GPS now, is the is it significantly weaker than the actual GPS that, let's say, the government is able to use? What do you mean by weaker? Like like I mean, at least now it seems pretty accurate. Like, you could know within a few feet, but it wasn't always so accurate. It feels like at some point, there might have been a a a a separation between the power, you know, the the abilities of the government and the data that the government was getting from satellites and the data that individuals using like GPS or whatever. Because I mean, a lot of times we're running a we ran off those same it's just triangulation. Right? So the stronger intents oh, not the intent. Stronger signal you have between those three points, right, it's it it'll make it tighter. So But what we are doing is pairing other data, right, that with that. Like this tree data up up from the calling phones. Or what and whatnot. Right? That's really when you try to get get understand someone's behavior and intent. So so you were kind of doing this sort of activity, saving lives, but using your kind of, you know, kind of also elevating all the time your your hacking or I don't wanna say the word hacking, but your your programming skills in this way. Like, how would you say you were improving? Like, when you weren't kind of actively working on a case, what would you do to just improve your your skills? I mean, from it for me, what was cool is, like, it was all the same. Right? What do you mean? Like, the the same joy that I got out of hacking, right, for a purpose. Right? Because I didn't start out as a joy, but then I ended up liking a lot. Right? Like, I like the whole idea of this intermediating systems. Right? The same same way I got him, like, alright, cool. We'll put this to a different use. Right? And, like, I'm like detecting patterns. Then that's when it really hit me, like, detecting patterns. Right? So what I did was is, like, I just bought books. Like, back then, people read books a little more. Right? So I remember What are books? I know. But I remember going to man, what was the name? It was, like, Walden Books or something like that. It was, like, a bookstore that's not around. I didn't even know that was the name of being able to w, like, Walden Books. It wasn't Barnes and Noble. I go there and I just buy a ton of books. Right? By the way, Barnes and Noble did buy Walden Books. Did did they? Oh, so it was Walden Books. Alright. Great. So then I I went to Walden Books, and I I remember buying, like, big books in Pearl and all these different types of languages, not really knowing. But I would read online, and they would say, like, hey, you need to know this, this, this, this is this is what this is what this Trojan was written in. And all I'm like, alright. Cool. So I gotta learn this stuff. Right? And then, and then there's some great so what's cool about the I I'm gonna use the word hacker. Right? Because what's cool about the hacker culture, right, is it's, you know, information should be free. Right? Information dissemination. Like, it should should just be free. Right? So then, like, everybody's sharing this stuff. You know what I mean? Like, use it. Like, this is how you do this. This is how you do this. This is how you do this. Read this. And back then, it was all text based. Right? So these, and these boards would just put text based, and they put tutorials and, like, how and, like, now now that's, like, YouTube. Right? Now YouTube's how to. But back then, it was, like, reading all these text based files and these websites on, on how to do certain things. And then you play with it too. Right? Well, because what was cool is it's, like, you could test. Alright. Cool. Here's the thing. I'm gonna create this show. Is it doing like the same is is the script running the same as intended? Oh, no. It's not. Oh, I wonder why. Oh, I gotta learn this. You know what I mean? I I feel like a lot of these have having read some of the literature, like, let's say, in the magazine 26100 Love it. I got it. A lot of these Yeah. Sort of techniques. It seems like you get a technique and maybe 80 let let's be even fair to them. Eighty or 90% of companies or people, have already blocked, you know, the ability of those scripts to work. But you could try a lot and test to see which 10 to 20% still have these doors open. Even better is is do you like, with code. Right? You iterate off someone else's start. Right? That's why the open source movement's great. So what does that mean? So, like, someone puts out a script, an idea, like, that, like, to your point, right, that may have worked, but 90% of people have already blocked it. Cool. But what if I added another layer to it, another line, another string to it? Then how could I change it? Because I'm close. Right? I'm now, like, I'm now, like, like, 90% of people blocked, so this is something. Right? So and I you know, the code base is open. Right? So is there a way to hack this? Literally, like, you use the word, right, hack this to do something else to for my benefit or to to fit or to intrude so then that way, now it's back open to then now, like, only 2% of the people can block it. So so, like, what's an example? I mean, there's there's, like, there's many examples on, like, how you can do this with different types of, of software, but I'm gonna take I'm I'm not gonna talk about those specific ones, but I'm gonna talk about, like, just think of the open source movement. Right? How people are iterating off each other's, like, Bitcoin. You know what I mean? The Bitcoin source is open. Right? It's just people are using it different, and they're changing it around differently, putting more secure elements, and then, like, it really iterating off other people's work. You know, and it's interesting. I I don't wanna spend too much time on on Bitcoin. I think it's a fascinating topic, and there's and there's almost, like, you could spend too much time diving into straight. Yeah. But it does seem like other than big there's there's 871 cryptocurrencies out there Right. And 0 and they're all getting traded every single day, all 871 of them. Bitcoin being obviously the most popular, and probably in some ways the most secure because it's been around the the the longest and people trust it. But most of those 871 are being traded by people who haven't read the code. And it seems like in the code, there's a lot of just from what I've seen, there's a lot of backdoors that most of these cryptocurrencies are scams. Yeah. I I would say that yeah. I would I would Like 98% of them. I would say a lot of them were unsecure. Right? And the goal of them isn't necessarily to make greater good. It's just to make a quick buck. Yeah. Because there's there's so many ways to manipulate how to hide transactions, how to hide how many coins are being printed, who has what coin, and and so on. Absolutely. And as well as to see actually the names or the email addresses or or IP addresses of who's making transactions. So there's a lot of privacy issues. Just like my ISP example, early days. Early days again in a different place. Yeah. Because a a cryptocurrency could be thought of now as sort of the ISP of currency. Exchange. So so it's it's interesting. So so I I throw that out as a as a warning sign that the same issues and almost the same techniques exist, but they kinda modify themselves according to how the world modifies. And some of those old techniques that were blocked, right, for, like you said, 90% may be applicable to this new wild west. Right. Right. So so because because, again Those same attacking. The fundamental structure is the same. The Internet, the idea behind this this sharing of data the whole idea of the Internet initially from, like, the sixties initial white papers is that we should freely share data with each other. Right. Mostly academics wanted to freely share, you know, scientific research. And there weren't really the protections put into place that a correctly, that a closed system might put into place. And once everybody got on to this decentralized approach, kind of, it's just gonna be natural that that these sort of holes would be open. Absolutely. So so you basically spent years kind of if if not studying every hole, because, eventually, all of those get covered up, but kind of the ways of studying them. You you sort of meta studied it. Yeah. Because once you learn something and the like, I mean, it's education. Right? Once you learn something, you know how it applies to something else, and then you kinda innovate. Like, oh, man, maybe I oh, you know what I could do this for? I could use this for this. I could use this for why, instead of, like, kinda like taking one idea. And, it's like theoretical physics. Right? Or let's take Nash. Right? It's the Nash equilibrium. Right? I mean, the guy wasn't trying to solve economics. Right? But he did. Right? And I mean, like He just wanted to meet girls. Yeah. Right. Right. Right. I mean, a little more than I think he wanted a Fields medal or something like that. Right? But, like, he he didn't know that's what he'd get the Nobel Prize for. So, like, it's and what's cool about that is it's, like, when everything's logic and formulaic based, right, the variables change. Right? But the fundamental elements that make them work and pull those variables together, right, could be applicable to, other types of, you know, like, industries or to solve other types of problems. So there's 2 issues I wanna ask about. Yeah. There there's 2 whole areas of your career I wanna ask about. One is you've somehow transformed from, this agency hacking life and to military. Right. And then from that, you transformed and you you had some amazing experiences. And from that, you transformed into being an extremely successful entrepreneur, and you sold several companies. And and and they were kinda connected to what you were just talking about in terms of the pattern recognition except on maybe customer behavior and and so on. But I wanna actually, just for a a few minutes, skip ahead to right now. Sure. I mean, it seems like, my theory is is that everybody's so concerned about missiles and bullets and guns and warfare. But it seems like and we we saw this in this current election or at least we started thinking about it. It seems like all the wars are actually ongoing right now, but they're being fought with data. Absolutely. So, like, I mean, think of it I mean, look, when you look at your Bank of America account. Right? What are you really looking at? Yeah. Just just so a computer is telling me is look at opening up some ones and zeros and and spitting it out into some form I understand. And I call that my net worth now. Yeah. Your entire worth. Your worth as a human is how people equate it usually. Right. Right. My net worth is now in data. Right? I literally yeah. Cool. I have a house or maybe some assets I have. Cool. I have that. But, like, you know, for the quote, unquote what used to be cash portion is now in data. Right? So then Right. Because, you know, it's not like if you made let's say you, hypothetically making out. Let's say you made $10,000,000 selling a company. It's not like you're ever gonna see $10,000,000 in cash in your garden shed. Right. Right. It's only a number in a computer. Correct. Right? That's data. I mean, that I mean, we we come down to it. So then and, like, capitalism and whatnot in our society, that's data. Right? I mean, that's what we're basing currency off of. Right? So then when you're thinking about this, it's like, what more efficient way to let's just say like, let's not even say war. Let's say, what more efficient way to screw somebody than to alter or augment their data profile? Right? Like, let's say I could hack your credit report, right, or, hack your bank account. Right? Or, like, it's seen prevalently, I turned the power off to your house. Right? Some you know what I mean? Those are forms of hacks and data that that are controlling how we live. You said you, you see this more prevalently turning the power off on my house. Is that true? Look. So especially as with the advent of smart grids and whatnot, you're gonna see a lot of those, are controlled by computer systems. Right. Right? So I mean, like, yeah. I mean, I think we're seeing this a lot in other countries that are, you know, like, going through some things right now. Because, like, let's say Like, in the Ukraine. Yeah. So let's say, like, in the US, a lot of power grids are built with the latest and greatest. So, presumably, they have you have to be pretty sophisticated to get into them. But the Ukraine is kind of I'm just guessing, and and I think also we're probably using a a name of a different country in place of another country. But, they're just hobbling together routers from the nineties probably to to to do the Internet connectivity to power the grid or or to connect the grid, and it's those routers themselves that still have open holes in them. Yeah. So, like, I mean and I'm gonna speak for a lot of other people. How much is it look, on your device at home right. I'm talking to everyone at home right now. Right? On your device at home, you have ton of security. You got all this stuff, your Mac, Windows, whatever you have, your phone, you're all secured. You may even pay extra for a virus scan or whatnot, like, to in under the perception that you're secure. Right? I wanna ask everyone, right, when's the last time you updated the firmware on your router? Yeah. It's interesting. So so every home, by the way, has a router because that's how they get Wi Fi. So Wi Fi is, like, spreading out through the air. Right. The router kinda pulls it down and then spreads it out for your own private Internet use. Right. But nobody like, I've never once updated let's say I had a router for years. Okay. I'm I'm a weird story because I move around a lot. Right. But, like, if I had a house and I had a a a router from from some phone company for the past 5 years, I've probably never updated it. Right. And if it was built if the router was built, let's say, more than a few years ago, it probably doesn't update on its own. You probably have to manually do it. A lot of times, you have to update the firmware. Right? There may be small updates that'll do it, right, with these new smarter routers. Right? But a lot of times, you gotta manually update the the firmware. And probably the first twenty versions of all that firmware were exposable at some point. So look. Because that's where I'm gonna go. Right? If I'm hacking you at home, I'm gonna hit your router. Lease secure, and guess what? All the packets of data go over it. Even encrypted encrypted and I mean, like, there's ways to break encryption. Right? If I just get the pack extreme, then I I I own the data. And then it's whether or not if I can make a signal out of it or not. Well well, also, there there's there's software packages for taking a bunch of packets and reassembling them into their most likely messages, like passwords Absolutely. Logins and things like that. And that's how, like, keystroke loggers and things like that work. Absolutely. Libraries. There's libraries and libraries of this stuff. Right? So if I'm gonna so, I mean, that that's a big if I'm going in, I'm going in through the router. Right? What's even scarier, in my opinion, and it's my opinion about this whole situation is it's if you think about who are, like, the Fortune 5 100 and all these large companies, the the majority of them use the same technology, right, for those routers, right, for those now now granted, they may be more secure. They have other layers. Right? But if everybody's using, I'm gonna I don't wanna let's say if everybody's using a a Bisco router, right, or a or a or a Nabisco router. Nabisco router. Nabisco router you can eat. Yeah. Nabisco router. Right? Or or a or a or a or an HD router. Right? Like, you know what I mean? Or like a you know, this it's all these big companies are using this because and they're on their premise. Right? These CTOs are kinda like, oh, man. No one ever got fired for using Bisco. You know what I mean? They're one of the largest companies in the world. No one ever got fired for using them, using their systems. Right? And granted, I'm messing the name up on purpose. Right? That's cool. But what it's like kinda like GMO food, right, in the sense that one virus can wipe a lot of it out. Right? So, like, if there's one missing proto one one whole, one protocol that's messed up, right, that's not randomized and whatnot. Right? If I can get in per se, theoretically, right, I mean, there's other layers that go into, like, getting into a load balancer and whatnot. Right? I mean, I'm I'm just making this simple so people can understand. Right? But if everybody's using the same thing and there's a there's a there's a, you know, like, there's a hole in one of them, right, Theoretically, right, I could I would just keep trying until I found the one that's like, if I found one hole, it might have been a small one. I found one way, one intrusion method. Right? I'll keep trying that at other large companies until, like, one guy may not be as secure as the other one, and then that hole's still open here. So so it's having this it's like anything you wanna get better on in in life. You build up this repertoire of, like, 100 or thousands of skills. Right. And you're given a situation, like, you know, oh, we have this kind of router with this kind of company with this number of people that probably has this sort of backup system. I'm gonna try this set of dozen or so strategies to see if I could break in because this is what has worked, you know, for me roughly. Exactly. Right. And you keep trying it until you hit. Exactly. So what about the other technique of, phishing? So I send an email to you and say, hey, mister x. I just, saw a video of you. You should check it out, and here's the link to the video. And then you click on it, and now it gives me all of your you know, allows me to put, like, a cookie on your computer or a bot on your computer or whatever. You know, comparing the two types of strategies, what do you see more? I hear more, right, on a on a individual basis of, of fishing. Right? I mean I mean, I think that that hits a lot of people. And, I mean, that's kinda I mean, that one is I mean, like, it's tough in one aspect. It look. It's tough in one aspect to say to to clear that out because there's a big human element. Right? There's a decision factor that goes into it. Right? Now there may be algorithms, one that, where we can highly detect, hey, this is a phishing scam using these types of words sent from this IP. And, you know, a lot of that works. Right? But, I mean, every once in a while, they're gonna fall through. Someone's gonna try something that worked. And and, like, and look, what's the marginal cost of a phishing scam? Yeah. Nothing. Nothing. You can send out thousands of emails. Yeah. I mean, email's free. Right? So I mean, like I mean, like, on a certain scale, an email's free. So then, you just keep they keep trying and trying and trying and trying and trying and trying. They get smart about it. They find a demo that works, and then they just hit that demo. Right? And they hit one message. It's really, like, evil email marketing is what phishing is. Even worse really because, yes, it's email in the sent marketing in the sense that you're sending out lots of emails. But then, specifically, you have this, malicious link inside, clicked on it, something downloads onto your computer, which starts, you know, hides itself and then starts uploading everything you do. Well, like, the most important thing you do is just be aware. Right? I mean, look, if all of your net worth, right, and growing these days, a lot of your personal, like, information is you're trusting it in the cloud or, like, in data in essence. Right? I'm trusting all my, like, people in Instagram. Right? I'm trusting all that, my birth date across multiple sources, my money, right, my pictures of my children and whatnot. You you should with with giving up that much security, right, you need to just be a little responsible and, like, almost do some homework as to, like, techniques and not just, like, put your trust in the government or this big going corporation to, like, take care of your data. You may need to do some some homework and understand, like, hey, no matter what, I'm gonna get phished. I'm gonna get social engineered. Right? Someone's gonna call my home and say they're, like, the like, I don't know, they're the energy company. They need to know my MAC address off my router or something like that. You know what I mean? Like, you you make out those calls, like, so as as while we loosen up our information in the security, like, it needs to be accounted for somewhere, and that's with our own personal responsibility, I think. I mean, I was once in looking at investing in a company that deals with the issue of how to fight bot armies. So a bot army is when your entire company, every computer is basically infested with a silent let's call it an application Right. That, on a given signal is ready to do something. Like, let's say, shut down all the computers at the company or send all the emails to some other address or or do something. And and this company was basically saying that 400 of the Fortune 500, the top 500 biggest companies, are probably infested with these bot armies that were probably unleashed by these phishing attacks. And I asked them, well, can you protect these companies? And their response was interesting. First off, the company was all PhDs, but their company said, but but the the the guy I asked, said, no matter how smart we are, the guys who are attacking these companies are smarter. See and I would I so, like, maybe there's a little bias here. I would say no to that. Mhmm. I wouldn't say that they're necessarily smarter. I think, like anything, man, people get caught up in bureaucracy. Right? And then people like, like, intentions change. And then, like, then I'm really about I'm not really about securing the company. I am. Right? It's my job. It's my livelihood, but I'm doing it so much just to keep my job versus there's someone out there who thinks they're gonna, like, gain all this power or gain all this monetary value from doing it. Right? I wouldn't say they're smarter. It's just probably just a different allocation of someone's time. So so I wanna I wanna get back to the present time in a second. But first Sure. How'd you go from, the, quote, unquote, agencies to, you know, military? Do you mean Or military usage of your abilities? I mean, so a lot of the times, right, if you were to swipe an ESN number off a phone and duplicate it and whatnot, you you had to you had to be there. So so so what's a what's a case where you had to do that? Where you specifically had to do it? I'm not gonna what I what I will say is is, like, there have been I mean, like, there's a lot of clandestine operations, and my hat goes off to a lot of those people who who even right now are on the ground helping those, operations out. But, yeah, it's just like sometimes you need someone who can do do the op, and sometimes it's better to have the person who knows how to do it in the event of variable change in a scenario, right, to figure it out. So, like, if you were to swipe, like, back I mean, the back of those Nokia green phones, the snake game. I I don't know that. You know, there's a phone, a green screen, a snake game on Nokia. Right? I mean, I I think everybody had one. Maybe you didn't, but, you know, those, you just swipe the ESN number on those things. Right? And then you could, like, duplicate that phone. Right? But, like On your own on your own Right. Right. Right. But a lot of times, the the phone companies, you know, you didn't I don't know. Like, you'd have to I'm probably speaking out of turn here. I'm saying, theoretically, maybe that's one instance, that that you would have to go on the ground for. What type of target? Something like, national security. Right? Something big. Like a terrorist? It could be. Yeah. Yeah. It could be. I mean So I'm sorry. I'm I'm drilling. I know I'm drilling for specifics. We're keeping you totally anonymous. You know, so so so you started doing these more clandestine operations. Did that involve, you know, you obviously were traveling to other countries where, you know, you I'm not gonna say I was traveling to other countries. Okay. You're not gonna say that. Alright. So so, given what you knew from your compatriots, what's a hypothetical scenario that you could've that could've happened? A hypothetical scenario that could've happened, right, is I mean, you you need to gain access to, let's say, a terminal, right, that is offline. Someone's, you know, responsible with their data, and they never put it online. Something like that. Right? You'd have to go in and try to crack it on the fly, but where you can't do it remote because there's no connection. Would that be would there be, like, a time thing? Like, are you I I picture this James Bond scenario. You only have, like, 15 seconds to, like, hack into a computer. No. No. No. They weren't, they weren't, like, look, theoretically, like, because I don't know. I wasn't involved in any of these, and I don't know anything about this stuff. I'm just talking we're we're just in play land right now. We're we're just in play land. We're just in play land. I I would say that, yeah, what would happen is it's you probably I mean, these guys are probably smart. You probably have open windows of time to go in and do it, and they do homework. Someone working at the like, who's a cleaner at the place whose access, right, is who's been there for 6 months. Right? Because that's a job that turns over a lot, right, with multiple different faces. I mean, you know, has time. I mean, like, at that at that time, you have all night. Right. Right. That's true. Yeah. So, I mean, it's not like, I mean, Hollywood hypes a lot of things, though. Right? But I'm not gonna say that those haven't happened. I don't I'm just saying I don't know. So so, first, I I I have to ask the question. Are you still involved in any, I I can't say that. I can't say that. Fair enough. So so you get you you're you're you're decided to get more entrepreneurial at one point. Of course. And what types of companies did you start? Ecommerce. Right? So a lot of the stuff was, started an ecommerce company, right, that sold car parts. Right? And then I got acquired by someone else who, I mean, what I was doing, right, is I just I like car parts. It was Fast and Furious rage. And I wanted these car parts, man. I'm like, alright. So I'm scouring the Internet on how to get them cheaper. I'm like, alright. Cool. So I'm like, alright. Cool. I mean, this part number seems to be a common denominator here. What if I just always scraped, right, these websites, right, to understand which to get the the parts. Right? So when I created something for myself to say, hey, where can I get this the cheapest? Right? A crawler. So so you basically create your own search engine for to search for the cheap you search all the properties. Start out as, like, I knew the websites to go to. Right. And then I would scrape them. Right? And then and then Colson, I know where the cheapest one was, versus me looking all the time. Right? Because there's a lot. Right. And then, I started thinking that was cool. My buddies I had buddies, like, dude, where did you get that so cheap? I'm, like, oh, here. I'm like, oh, my gosh. Get it for me, dude. I'm like, alright. Because then I saw, like, a business in it. I'm like, alright. Cool. Whereas most people would have, like, I don't know, just, like, waited to get a supplier deal and, like, applied for it and all this type of stuff. Right? I didn't. I just I I'm like, alright. Cool. If I can offer the cheapest price, there's some arb here. Right? There's arbitrage here, right, in pricing. So then I I consolidated, created a site that did that. And then, that and then that went ahead, scraped, found different prices. Right? And then I started pulling in what's cool about these manufacturers, I started pulling in other things like the manuals and stuff like that. Right? And long story short, someone else who sold more than just car parts, right, liked the technology and they purchased it. And they liked the technology for the car parts, or for did they try to just do it for everything else? For everything else. Wow. Right. So they were doing it for, like, like these, like all types of home parts, like a washing machine, microwave, plate, AC adapters, whatnot. Right? So what does it end up looking like? They it looks like you're going to the site, and it's it's almost like it's their product, but they're or or Well, no. They they actually had deals with suppliers. Like, they they went that so they was scanning their supplier deals with actually what was out there on the net. Because a lot of times, what they liked it the most for, to be honest with you, wasn't necessarily the pricing. It's good to keep competitive pricing, understand what other sites are doing. But they liked it because it pulled the manuals and all this stuff from the websites. Right? So that way, you knew how to install the part when you got home. It's early on before. Like, now everybody does that. Everybody's got YouTube videos on, like, how to install this part and whatnot on their products. Can't figure anything out. Right. I mean, but this is back when, like, you know, I had to look at these white PDFs and, like so they pulled in all that and, like and then just pulled in, like, the other information to append to, like, the descriptions. Right? And so and so that was company number 1. What was company number 2? Alright. So company number 2, right, was pretty much, like, me just trying to, like, take in as I worked at Wall Street for a little bit. Right? And then me trying to take When you say you worked at Wall Street, like, hedge funds, mutual funds, banks? I worked for, bank and hedge funds. Mhmm. Right? And then, you know, like like, that that was cool. Big dataset to play with. Okay. Yeah. So let let's get an example, like, data used by a hedge fund. How does it other than just straight pattern recognition, like, oh, when it There's arb when when, like, when Google goes up, Amazon goes up, that kind of stuff. Right? Other than that kind of basic pattern recognition, what what's the sort of most sophisticated thing you've seen on the hedge fund side for making money? For making for generating What is data that the average person can't use? I mean, they'll purchase, like, data from so, like, let's say there's companies, that aggregate data. Right? And they'll purchase and see if underlying company like, I mean, I'm taking for example, you ever been on one of these websites where, like, they they show you, like, your bank account and all your expenses for free and whatnot. Right? You know what I mean? Like like, I I I like If you sign up for it. Sign up for it, it'll show me, like, these cool charts. Right? So those guys resell your data. A lot of them. I'm not saying all of them do, but they do. Right? And they say they can see your Sprint bill. Let's, let's just say, like, your Sprint bill or some telecom bill. Right? Or why? And then they sell that data, right, to see if that goes down, up or down. Right? You know what I mean? Like, hey. This is the benchmark of how much use this supplier. Is that going up or down? Right? Or is there a significant signal on that? Right? Or if So okay. So so I'm a hedge fund, and I I and let's say there's 30 of these companies. Right. I buy the data from 30 of these companies, and I could see in general, oh, for some reason, Sprint I'm just we're just making up Sprint. Right. Right. Sprint seems to be, making deals or cutting discounts to most of the customers. Or I'm starting to see less people show up in using Sprint in that in what aggregates that data. Then maybe they may be using other carrier. They may not give you the exact name of the carrier, but the other. So it's not quite insider trading, but it's data that most people don't have, and they could potentially make a trade. Yeah. I'm sure they could buy that data too. Right? There's that type of stuff. I mean, like, one of it, another one, right, that I'm just, like, that comes to mind is it's, like, when you're thinking about that type of data, right, so what are you getting? Right? I'm getting a third party data. Right? There's a lot of times you can do scrubs from, from, like, credit agencies, right, where you can come up with intense signals of finding out. And this is for, like, on a more macro level, right, of, like, understanding, like, is like, in a particular market. Let's say I had a company, and I let's say they're they're public or or even if they're not, I may I was gonna make a private investment, and they're heavily saturated in a few area codes. Right? Cool. Maybe pair some credit reporting data to see if, like, discretionary wallet sizes, right, are getting smaller or larger and that type of stuff. Right? Or, like, maybe a housing, right, they, like, kinda look and a lot of these research analysts, like, pull this data and they resell it to like, the buy side guys resell it. Right? But, or pulling data from, like, you know, this housing industry. Right? Like, Zillow probably has a great data set for that stuff. I'm pretty sure one of their APIs is open. Right? And maybe you can pull some data from that to understanding, hey, market prices and how they may affect, like and what's the company that makes the pink insulation? OC Corning or something like that. I don't know what I would predict like. So that's interesting because even search query data on Zillow might be interesting. If people if the average net price of a house that people are searching for on Zillow in a certain area, that totally affects all the companies involved in housing in that area. Right. And then which one, like, which one does it correlate with the most? Like, maybe new home building, right, correlates to the the guy who makes insulation. Right? You know what I mean? If that's a majority of his business. And then you just gotta do, like, read a real analysis, real homework, right, to figure out if there's it's really just trying to edge to get that alpha. Right? What about, is there anything what can I do now? Like, is there anything you know, like, everybody uses mobile phones for everything. Is there anything kinda mobile specific where headphones can get, like, a little bit of an edge? You know, it seems like the so many apps So, look, check this out. So, there's a lot of apps. Like, I always beware of anything free. Right? That's what your parents told you. Right? Beware of any it's not free. There's no free lunch, all that stuff. There's no free app. Right? Well, like, even the Flashlight app allows you the the flashlight app creator to open up your video without you knowing it. Right. Or yeah. Exactly. Or, like, allow access to my microphone. Right? I mean, there's this like, it's crazy. I I mean, I I met with this one company that were they were trying to allow access to microphone. Right? It's kinda like a Shazam, and then it would pick up inaudible signals. So that way, what they're trying to do is they were trying to trace, if you actually sat and saw and listened to a commercial. Right? So there'd be an inaudible signal, kinda like Shazam. Right? I mean, like, inaudible signal that goes out. That's like a message, like, you know, this McDonald's commercial aired at this time. You know, like one of those types of things. Right? And then your phone would pick it up because you you have some free app to allow access to microphone, and and and it would pick up that inaudible signal. Right? So the company try and do that. So when you do that, right, you offer a ton of access. Like now I know, like, hey, if I'm playing, I don't know, like some I'm trying to think of it, drums versus zombies or something like that. Right? I'm playing one of those games and it's free. There's certain access to my phone that I'm giving up. Right? It could be, like, location information, right, lat long. Right? They know where I am. Right? Which is which is crazy because back in the old censorship days, right, they were thinking no one would ever give up their location. But now people we volunteer. That location's on all the time. Oh, location's on all the time. I let Google know wherever the heck I'm going. Like, if I'm going to Google I like using the maps or any map app. Right? Or if I'm allowing location. Right? I know where these people are. Right? And then if they're check this. So if they're at a certain location for a certain period of time at a certain time, right? So if you're at a so if you're at a a lot long, right, from, like, 10 PM to, like, 5 AM majority of the time, I'm predicting that that very well may be what you call home. Right? And if you like, and and so on and so forth. Right? So now they could predict, like, okay, cool. Like, they're home. Like, they may be more apt to I mean, I don't know what you'd use that for. There's probably a lot of things. Right? But, like, in commercial applications. Right? But, like, oh, hey. A bunch of people in this demo are at home. Maybe they watch TV more at home. Right? Or or maybe they're they're sitting down spending more leisurely time. That's when we market those type of people. I mean, there's a ton of stuff that you give up with your phone when you give those free. I mean, like, I think it's worth the 90. If someone's giving you something for free, if they're like, think of that trade. Right? Like, how much do they spend in software development, all that stuff. Right? And if they're willing to give it to you for free, right, that is probably to them, that's worth that dev and capex and creating the app and then, like, what they could make for, like, the 299. Right? That's worth something to someone else. Right? I mean, there's even there's even kinda nefarious sort of applications I could think of just right away that would just be very dangerous if someone knew it across the board about everyone. Well, I mean, here that's another way to hack people's phones. Right? I guess that happens all the time. These apps are all over the place. Right. Be careful. I mean, like, be I mean, like, I mean, like, there's trusted I mean, like, you just you just gotta be responsible. So so company number 2, you sold company number 1. Did you have to stay at the company that bought your company? At company company number 2, no. I mean, that that was, like, more one off deals, right, and whatnot. Right? It's saying that, like, someone just saw, like, the technology, and they said that they purchased it. Right? And, you know, again, this is all anonymous. Did you make enough money to do well? Like, were you happy with it? Yeah. Yeah. Yeah. Each one I each each one of these things I made, like, the first one I was really young. Right? So I I made and I blew. Okay. Welcome to the club. Right. I made in blue. And then most recently, right, came coming off an acquisition. And, yeah, that one that one definitely teed up. I I could choose what I mean, it's awesome. That's great. Well well, so what was company number 2? So it's, artificial intelligence company. Right? And we went in, it was a one of the largest e commerce companies out there. Right? And really just tying it's look, it's the same thing we've been talking about the whole time. Right? It's pattern recognition in in an artificially intelligent scalable, right, using parallel computing way to detect who's most instead of detecting threats, right, using events in an ecosystem to detect threats, using events to find patterns in herds of people to give them the right product, right, at the right time, right, at the right price. And so so let's say you had a huge, amount of data. You would be able to say, oh, okay. This, lady in Iowa is not likely to buy a computer, a 2,000 dollar computer in February, but maybe she would buy 1 in November. Or Someone who came in on the site through a a Google keyword of, like, I don't know, cool pets just happened to click, and let's say I'm selling, like, computers in this scenario like you're giving me. Right? And they're on there's 2 ways to look at it. Right? They're on a they're on a brand new Mac, right, or the latest computer. Right? And they've updated to the latest, software or whatnot. Right? May not be in the market for a new computer. Right? Versus someone who's mid range is or or the the same would be said about the complete inverse. Right? Someone who's on, like, an Emachines, no offense. Right? It was a great company at the time of the Cal stuff. Right? I did like them, actually. I had one. Yeah. They're cool. I mean, a cool marketing concept. Right? Someone is on Emachines. Right? Who's on, like, I don't know, Netscape. Right? Browser or something like that. Right? I mean, I'm giving a crazy example. Also may not be in the market for a a computer because they obviously don't value it. Or someone in the mid range. Right? Maybe. Right? So it's understanding the patterns at those levels. Like, you'd be surprised at how statistically significant the patterns are by device type, by browser type, pairing those in probability trees. Right? Like, coming up with, like, this device type on this browser, right, coming in through this traffic source. So so, basically, let me try to, let me try to reverse engineer it. Yeah. So let's say someone does buy a new Apple computer. They buy a new laptop. Okay. Okay. Now I know 20 things about them. And and let's just say One of them is maybe their wallet size. Yeah. So I might know a lot of things about them. Apple might know a lot of things about them because they they just freely give the information. Right. But you give that information to every time it interacts with the site. I know your device type. Okay. So so so Apple now is able to say, well, these 10,000 people bought this laptop, and this is what they look like. They they look like they had each one of them has 20 factors that define them. Right. And, one factor might be where they live. One factor might be what they're upgrading from. One factor might be the time of year. One factor might be whether they're male or female, what their age is, where they went to school. Yep. What what they're willing to spend on extras and accessories. So that's the 20 factors. Now you get an unknown customer, an unknown potential customer. You get that data through a variety of ways. Maybe you have a cookie that has given you that data. Maybe you have an email list that's giving you that data. You found them on some other site where you bought that data or they visited and and deposit that data. You're able to match this new set of 20 variables to your database of successful Correct. Samples. The successful ones are the 20 are are the people with the 20 variables that match a purchase, of an Apple Computer. And you you could say, this person most closely matches the type of person who has bought an Apple laptop. And then you're able to, what, target them with an email? Or what do you do? So a couple of things. Right? So let's say I'm selling shoes. Right? And I have a a $50 shoe, $100 shoe, and a $300 shoe. Right? Different options. Right? Let's say you were coming in on a certain device and, like, I'm we'll just like, I'm just gonna make one up. Right? I'm gonna say you're coming in on, mister x computer. Right? Mister x computer costs, let's say, I don't know, it costs, like, $8. Right? You're coming in on mister x computer. Right? And you could see that right away in the server anyway. See it right away, and I also have a ballpark of location. Right? If you have location services on, I really do. But, I mean, even through what IP you're coming in on. Mhmm. And another pattern I have, right, is time of day, like, what time of day are they coming on. Each one's a different profile. Right? So, like, a guy who came in on mister x computer at noon at lunch may not be the same guy who comes on from mister x computer at, like, at 3 AM their time. They may be 2 totally different people. Right? Like, or 2 different types of people. But, anyway, surf with me here for a little bit. Right? They, on average, if when they interact with, you know, like, whatever I'm selling online or whatever product I'm selling, they may interact and purchase good like, the $300 shoe all the time. You have another person comes on, like, let's say, mid mid level, device. Right? And I'm just making this is uber simple. It's not just device. Device isn't know all. There's, like, a ton of end factors, but just to make a point. Mid level device. Right? Maybe they update their browser, so on so forth, and then, like, they interacted with e like, keywords like search cheap computers and whatnot. Taking all those types of factors together, like, oh, okay. Cool. He's a mid range person. Like, let's offer, let's offer the second shoe to him. Right? Because I know based on, like, there's a correlation with the type of computer. He's a mid level computer. He's probably mid level shoe guy. But but it and think of it that way, but it could be differently. It's it's like we kinda parallel compute, taking all these different factors and dimensions and come up with which one which trees in the forest, right, are the most statistically significant, and then we personalize the products to the offering. I see. So they they come to the site, and they see, based on their data and your analysis of their data, they they you put up the the the products they are most statistically likely to buy based on who previously bought these products. Correct. Correct. And then as you get more data than those targets, right, those signals get stronger than stronger, and maybe then I maybe I'll find more clusters, more different groups. Right? I I I love this stuff so much. You know why? Because, this reminds me so much of how game programs evolved. Yeah. So it used to be, like, chess programs would just build a tree. Oh, they can move here, then they can move here, then they can move here. And they would analyze, you know, who who is potentially winning. But what ended up happening was games like Checkers, Beckham, and Othello, and even Go most recently, they would take, let's say, 10,000 successfully won games. They would take a middle a middle of the game position, and they would know that white is later going to win. And they would put that in the category, oh, white is going to later win this, and black is later gonna win this. And they would analyze the 20 features about this position that they could sort of quantify. And then given a new position, let's say I'm in a new game with you, who's better? You or me? Well, I can make this move, or I can make that move. It'll run it into the database of we'll statistically match each move against all of the winning positions, the positions that we know are winning, and we'll make the move that is statistically closest to a winning position. And that's the move we would make, and that's how all those games work now. Oh, absolutely. And then, like, with those gaming especially, it's really, like, for each move, it's accounting for that variable change. Right? So, like like, right now, white's gonna win. Black moved here. Right now, black's got an 80% chance of of winning. They totally flipped the board on them. Right? Because that move depending on how like, because there's only so many moves that white can now make. You know what I mean? And, like so, like, I was looking at a at a at a I was talking with a friend, and, you know, he's got a cool cool industry really with the professional sports. Right? And then, like, when we're just talking about the NFL. Right? Oh, my god. You could totally do this with, like, fantasy sports, everything. Totally. Totally. And then, like, think of I mean, like, a part of it. I mean, what else we were talking about, like, would be cool, like, to overlay stats. Right? Because, you know, in that, because, you know, they have trackers on the, shoulder pads. Right? And then understanding, like, hey, in this lineup. Right? So, like, let's say when the New York giant Giants, right, lineup in the dime and the Philadelphia Eagles. Right? My team, who were the best team in football, you know, lineup in the shotgun. Right? And then this certain formation because you know where the players are. Each players wearing one of these RFID trackers too. Right? When they line up like this and, you know, like the left tackle is leaning forward, right, then there's a statistically significant chance that, like, the the Giants are gonna win this play. Right? Or that, like, or 9 times out of 10, it should be like a like a a big play 20 yards or more. Right? So so it's it's it seems like that is a multibillion dollar company that could be bought right there in either fantasy sports or sports betting. Absolutely. Absolutely. But but even more Using the exact same technology. But but even just giving the viewer a better experience too. You know what I mean? Like, I because, like Yeah. But let's say I don't care about that. I just wanna build a $1,000,000,000 company. I can use the these exact same algorithms that are used to win Checkers or Go Right. Or analyze customers. You know, it's basically this this multifactor it's the same, by the way, it's the same techniques as speech recognition. That's how speech rec speech recognition works. I know what it sounds like when someone says hello because hello's got, you know, 20 different factors in the in the signal graph. And now when someone else says hello, I'm gonna match it against my database of words. Oh, it looks statistically likely that this person just said hello. And that's how that works. They're all using the same statistical techniques. Yeah. And statistical techniques and other mathematical equations, like, my hero, right, is this guy named, Pam Dirac. Paul Adrian Maurice Dirac, right, won the 1933 Nobel Prize in Quantum Physics. And, you know, he had the Dirac Delta function, and he we had a quote that said, you know, like, I I forgot. I'm gonna butcher it. Right? But what I took from it, I think about it every day is, like, you know, these methods of theoretical physics, right, should be applied to everyday use. It's something along the lines like that. Right? Like, someone can like, that's not his exact quote, but that was the gist of it. Right? Is what if we applied, like and then what I take from that is, like, what if we apply these methods of theoretical physics, right, to everyday problems? Like, so one one, like, one that I've used before, right, is there's a there's there's a algorithm, right, there's, like, there's a math formula, right, involved to detect at when wire when heat or electricity runs through wire, which at which point it predicts will get hot on the wire first. Right? And that same one, you can overlay with, using I mean, you gotta do some other math in in in the foreground to set it up to get those variables in that that formula. But, to predict what's gonna be popular, Like, literally what's hot. Like, not literally what's hot, but, like like, what's hot in pop culture. Right? Because imagine imagine I had data about how movie trailers were shared in the month before a movie was released. So let's say I know exactly there was this number of shares in email, this number of shares in Twitter, this number of shares in YouTube or views on YouTube. That's the kind of, speed of the heat entering the wire and the amount of heat entering the wire, the the width of the wire The available market. Right. Yeah. Yeah. Then I can see how hot this movie is gonna be at the box office. It's the same thing with what you're talking about, sports. It's all the same technique. The reason why it works in theoretical physics is because most particles are found not nobody could see the particles. They only noticed statistically that that something happened. Right. And what they what they predicted would happen with a particle of that mass would happen, happened. So so so, again, why don't you right now start a fantasy sports company? I'll invest in it. I'll write you a check right now Alright. For a fantasy sports company. That's awesome. That's awesome. I I look, I just love solving problems. Right? To me, a lot of this stuff is the same. Right? A lot of the I mean, it's just, like, taking the massive datasets and coming up with, understanding what the target is or what the optimal function is. Like, someone wants to make more money, increase viewership, increase retention, reduce customer churn. I mean, it reminds me though of, again, this kind of trend from which I I have has been brought up in this podcast a bunch of times. This trend from humans to data. So rather than humans predicting, oh, the Giants are gonna beat the Eagles or the Eagles gonna beat the Giants, It's much more accurate, like, a 1000 times more accurate to make use of the data based on thousands and thousands or millions of units of data you have upon previous games that they've played. Absolutely. So it seems like you can start applying these things to every type of decision making from health to, you know, box office predictions to the stock market. You know, and I feel like I feel like you they the the first wave of pattern recognition in this of the stock market has kind of been come and gone. Right. Right. Right. But I think the next wave hasn't even begun, and it just seems like sky's the limit. So I know your your time is a little bit limited. Your I wanna ask you 2 questions. Go for it. A, I know you have a theory, so we can talk about it. It's not a direct experience, but a theory maybe based on what what you know and what other people know, but it's still a theory. What do you think is the real story of Osama bin Laden? I know it's out of out of the loop here. So like I said, yeah, I don't know. Right? I don't know, you know, like, officially. Right? But Just your theory based on your varied experiences. Here's what I will say. Right? And, if you look at it, like, you know, look at a bird's eye view of the place. Right? You're in a you're in a town. I mean, let let let's just look. If I look. If if you, James, right, if I went over your house, right, and there were huge high walls, right, and guards patrolling all around, right, what's the or if you went if what do you think? What what does that look like? Does that look like a palace to you? But maybe I'm being if I'm okay. If I'm Osama bin Laden, maybe I just want, like, people protect guards protecting me so no one rush no one rushes or investigates or spies. I just want kinda people around to make sure nobody comes in. Sure. Sure. Maybe maybe maybe you're creating a a big wall and a moat, and you just don't want anyone to come in. Right? And what you're doing is you're drawing and let's say you're also probably the, like, the most hunted person out there. Right? Would you still do that? Would you still draw that attention to yourself? No. Probably not. I'd probably live in a hole somewhere. Right. Right. Right. Out not outside of town and and whatnot. And, you know, like, I mean and, like, there's a ton of people go back and forth on this. Right? I just I'm not saying, like, what happened happened, what or what, you know, or didn't happen. I'm just saying, you know, kinda like be responsible with the data that's out there. Right? And make, you know, like, your own decision. Like, there's a guy, Ralph Waldo Emerson. Right? I love the dude. Right? He created this thing called the American Scholar. And he said, like, don't ever become a reclusive thinker commenting from afar. If something looks a little interesting, right, and voice it. And and what I'm saying is it's, like, to me, taking all the all the facts out, right, of of, you know, what was said, that looks more like a jail. Right, that this guy was potentially in a jail. Right? Held by a government Held by a government. By a government. Right? And then maybe because he had a lot of data and in eradicating this person, look, they're so valuable. Like like, I mean, like, let's say you had, like, the the head of anything. Right? They know everything. For a lot of I mean, it was their op. Right? So maybe maybe there's some data you can get into. Maybe this person for exchange, right, is that desperation point where they're not drinking their own Kool Aid and they just wanna live. So so so let's just hypothetically say it was the Americans holding him in prison, interrogating him for years to get information, but they don't want him Or another government who were feeding the who were feeding the the, whoever was interested in tell about him. But but nobody wants him alive because he might have too much information, you know, for various reasons. Because he's been involved in every government for decades, decades long before now that neutralize that threat. Right? Mhmm. There's still a growing threat out there. So you wanna neutralize all that too. So what better way than to have the head tell you about how the operations ran, who's who, who's what, where they are, what's gonna happen next, you know what I mean? In exchange for that. Right? And why would he why would he agree to tell anybody? I mean, obviously, he made interrogations. Agreed. I'm I'm not saying this happened either. Right? I'm just saying, like, I'm looking it from a I'm just offering a different perspective. Right? You know, like, you make different decisions when you got a barrel, right, of a gun pointed at your face. And then that whole scene where, like, Obama and Hillary and everybody's, like, watching the the operation, do you think that's, like, somewhat staged or or some people knew and some people didn't? I think some people knew, some people didn't. I wasn't in the room. Right? So I I I didn't see your picture there. No. Right. So I I can't I can't say. I would just say that, like, I mean, you got 2 helicopter or 2 choppers coming in, right, at night. Right? Make noise. If you really were being, like if you're really spooked about that type of stuff, had armed guards everywhere. Right? Like, You'd have escape doors. Yeah. I mean, you you could have escape doors. You'd have alternate way out, tunnels. Like, you know what I mean? And like I said, I wasn't there either. I don't I don't know specifically what happened. Right? But I'm just thinking that maybe, I mean, maybe the guy is not as smart as the as we thought he was. Right? But there were probably other way I probably would had a safe say like, you know, like, ways out and all that stuff. Right? And I I don't don't quote me on this. I think we had approval, right, to go in there and do that from the government at, like, the very last second. Like, we told them, like, hey, we're doing this. Oh, we're already there. That type of stuff. Right? But, there's a relationship there. Right? You know what I mean? If you're going fully convert. So there's just interesting things to think about. Right? Some, and things to theorize on it. Right? I'm not saying, conspiracy theory, all the type of stuff. Right? But that news is also also came out in an inopportune time. Right? For the for, you know, the people incumbents of, what Well, what interesting things do you think about right now given today's current news events? I mean, there's so much talk now more than ever about cyber hacking because of the elections, because of the phishing scandals, because of election manipulation. Nobody knows anything. Everybody's meeting with everybody. What reclusive things are you skeptical about right now? I'm skeptical that this data is being aggregated at a large mass scale. More data is being created per second, right, than potentially the history, right, of data. Right? And it keeps growing. That growth rate keeps growing exponentially. And then now what do you do with that? Right? So if I can influence someone to buy something, they have already shown intent. Cool. Right? You're reading news. Right? I mean, you know, like, the I'm I'm not saying news isn't this anymore. Right? I I love journalism. I love news, all that type of stuff. But, like, that's a real responsibility to the public good that they hold. Right? And then when that gets intermingled, like anything, with profits and quarters, right, making, hey, I need to make the next quarter in sales. I need to I need to reach x amount of people. Right? But that's already happening. Like, there are new sites, and I'll just say them because I think they're pretty public about it, like Upworthy dotcom. I think that's the name of it. They will, thousands of times a second, switch headlines, switch photos, switch the way the first sentences are written, to see who And that Which which articles capture the eyeballs the most. And for them, that's smart. Mhmm. But the incentive what's scary about me is all this data, aggregation and falling in the hands or not being used properly, right, or without the right intention. Right? Because then what happens is it's, like, that's where the real hacks come in. Right? Like, cool. There was one hack where I, like, I get your bank account. Right? There's another hack where, like, oh, I can get your personal information. I open up your identity. But then there's a much larger hack where I influence people, right, where I I'm the person, right, who that influences, like, what people are seeing, what stories are going out. And then that's really changing behavior, right, on on on a much larger scale. Like, I'm I mean, yeah, you can use it to sell products. Right? But I can also use it to if if I'm in the a business of something wrong, right, I can use it for fear. Right? I can use it to to change larger things, institution things. Right? I mean, like, it's it's almost like the government. Right? You know, like, we're backed by gold. We're backed by data. Right? And it's it's I'm we just gotta keep a parent of of that. Right? Like, we just need to, like, understand, like, our data is valuable. Right? It's my digital footprint. Right? It's as valuable as my social security card. Right? It's a you know what I mean? That that that's my that's my footprint. Right? And, you know, we're human. Right? I'm human. Right? I get influenced by stories. Like, oh, man. And then, like, you know, I try to do my best to check both sides, but there's no real medium where I can go and check both sides. Maybe that's a $1,000,000,000 business. Right? But, like, if if people aren't using that for the public good, then, with that power and that data, then then I'm a little, that is concerning to me. I mean, I think what what is once reclusive always becomes eventually out in the open in the sense that everything you just said that might happen will happen, and there's no avoiding it. And it becomes a matter of how you personally guide yourself through it. Like, you're being aware of these biases that are gonna constantly pop up. Because look at the history. Look at the pattern of history. Right? I mean, you have these great sides that go up. Right? And then a lot of times, there's always one tyrant guy, right, that, like, wants a little too much. Right? Starts out with an idiom or an idea, right, and then wants a little too much, and then, like, and then, like, that's that's bad for the whole. Right? You know, in some cases, unfortunately, there were genocide. You know what I mean? It was still happening right now in a in a few parts of the of the Earth. Right? But what if they they they what if they got that information? What if they are the ones in in control of that data? Right? What if they're the ones who could turn the lights out tomorrow? Right? I mean, that's and, like, I mean, like, that's where we I mean, like, me, but I feel like I personally need to educate people. Like, hey, man. Like, this is something that's happening. You need to be more secure with your own data. And then the problem is it's like, there's always gonna be history says there's always gonna be one of those guys, James. Right? So then it's either you trust the government to be that guy policing that But they can't anymore. Right. Or or or or you know what you gotta do, man? You gotta be smart with your own data, or you need to be the person. Yeah. I I I sort of think data is the government. Right. So I don't think the government even really matters that much except for the laws, the legacy laws that we all live by, like, you know, health care and, you know, all all the things that we argue about every day. Right. But what you're talking about, I think that's this I don't wanna say shadow government because that's overused, but I think that is where the real government is starting to form, and we don't know who the players are. Right. And we don't know what's out there. And this is not even being conspiratorial. This party exists. No. Because look. Think of it. That's happening. Right? And in in in and this is probably the truth. It's happening to help people with their incentives for their quarter to quarter profits, get more data, make more money. And it's and it's being done in a novel effort. Give people the right product at the right price. That way, it's a win win. They get they get a deal, and then, you know, like, and then the company makes money. They continue to offer those deals. Right? But, like, I'm just saying from a point of, like, what if, I mean, like, just looking at history, right, if that gets placed in the wrong hands, gets used for for what's wrong. Right? I mean, so like This will happen. Well, which would so, like, but here but he now now on the flip side of this in this time, right, more so now than ever, right, has a lot of barriers of entry been broken, have a lot of, you know, a lot of things been democratized. Right? Before, right, I to go up against an institution. Right? I mean, I'd have to almost be an institution. Now I could go viral. Right? I mean, you could see a lot of these, these changes happening now. So, I mean, like, it's I think now more than ever, are we put in a place where we need this stand up for what we believe in. Right? We have these powerful, engaging tools, right, to influence others in data. Right? And it's great, and it's been a great medium to share them, to share my pictures with people. I'm using it for that. Right? But, I mean, keep the balance. Right? You believe something? Right? Share it. Given all this and given that I wanna be a responsible citizen and I wanna improve myself and I wanna understand this world we're moving towards, what books or websites or whatever should I read to become more aware? So I would so here's what I tell everybody for that type of stuff. 1st, like, look, I mean, like you heard my own story. I didn't really go to college. I graduated, like, when I was 29, 30 just to, you know, for my child. Right? So that way I could say, yeah, you need to go. Right? And that was I would not have done that. I know. I know. I know. I I know you were I knew you were gonna say that. Right? But, I would tell people, find but here's what I like, I found something I was interested in, and then that was the best education I've ever had. Right? The other thing was, like, a stamp. I don't even know where the the diploma is. Right? It's, like, buried somewhere. Right? So you found something you were interested in Found something. Which is hard for people to do. Yeah. But, you know, well, true. But start somewhere, man. Right? It's like Try enough things. Try enough things. Go out. Like, live a life. Like, don't don't be succumb to your phone. Right? Or if you that's what you're into, right, then get into that. Right? If you're into like, you know what I mean? Put it to, like, find something you're interested in and then learn everything about it. Right? Or you know what? Change your career. Right? You're doing something you don't wanna do, change your career. You found something you're interested in, go do that. Go do that. Because then what'll happen is is you'll learn you're you're passionate. You may be more passionate than the person running that business. And I'm gonna play devil's advocate. Go. I'm a divorced wife raising 3 kids, and I have to play pay the mortgage. And I'm listening to James and mister x, and they're saying change my career. Well, I'm really interested in fantasy sports in for for women, but I I have to, be a paralegal somewhere. How can I do it? Get less sleep. You know what I mean? Yeah. If you really wanna do it, look, I mean, I like I mean, this is we live in a great country. If you really wanna do something, right, what I'm kinda saying is it's, like, the opportunity is there. So get really interested in something, then read those books. Right? Get get to be an expert or gain gain that experience. Go work there. Right? Gain that experience or get really educated. Because what happens is it's like I mean, if we didn't have biases of opinion biases of educated opinion. Right? If we didn't have real and what I mean, educated opinion, someone who really knows their tact, knows this industry, knows this niche, knows knows the best about, fantasy football for women. Right? What happens is you you bring an equilibrium to the game. Right? I mean, or it was like, if that never happened, right, we'd be all still standing at the in the center of the earth at fear for falling off one of the edges. Right. Right? So get again involved. Even if it's a passion. Right? Like, you know what I mean? I coach or I I plan to coach my daughter's soccer league. Dude, that's why I think that's my next thing. I'm gonna be like a woman's soccer coach. Right? Maybe I'll I'll maybe in, like, 10 years, I'm team USA Soccer. That that that's my dream. Right? But anyway, find those things. Right? Then immerse yourselves in those books. Right? And then what you'll find is is what you learn there. Right? And just like when I train a machine learning model. Right? Like, I the more data I get in, the smarter it gets. Right? When you get more data, right, into your head about something, you're and you get educated opinions and understand how something that you love works, you're gonna make educated opinions about how other things work. Well, because you're gonna be able to make connections much faster. Synapses. And so the learning grows exponentially as you as you immerse. Absolutely. And then, like, I would I love the article, right, or the essay or whatever. It's the white paper. Right? The American Scholar by Ralph Waldo Emerson. Right? If you, take a take a read of that, I mean I will. I never read it. Yeah. Yeah. It's, it's, you know, it's like it's been so long. It's free. This is why you went to college. Right. Yes. Right? To read those things. I don't know. I I didn't I didn't read in college. But, great thing, and and and then, like, but the best thing is right to, like, just go ahead and and do something. Right? Just take a don't be a to quote him, don't be a recruit a reclusive thinker commenting from afar. Right? Take action. Whatever that is that you love. Well, mister x, there are actually so many other things we could talk about. You'll have to come on again at some point. For sure. But, thank you so much for coming on. Thanks for I know I I will say this. I know you've personally saved a lot of lives. Oh, I wouldn't say that, man. I'm gonna say I would not say that. I'm gonna say it anyway. Okay. So thank you, and, let's talk soon. Absolutely. Thank you very much. For more from James, check out the James Alticere Show on the choose yourself network at jamesalticere.com, and get yourself on the free insider's list today. Hey. Thanks for listening. Listen. 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