• Ken Jee

The Man Behind the Bam! (Josh Starmer Round 2) - KNN Ep. 112

Updated: 18 hours ago


Today, I had the pleasure of interviewing StatQuest with for a second time! We talked about his new book: "The Statquest Illustrated Guide To Machine Learning", his love for cooking, and what he learned about collaboration through the trip at the #brightdatahouse!

 

Translation:

[00:00:00] Josh: You can tell a machine learning person versus a statistics person, even though there's tons of overlap, they'll use very different language to describe the exact same thing. And it's, and it's part of our, I feel like it's our just natural tendency to try to always find ways to figure out, like, what your identity is.

Are you a data engineer or are you a data scientist? Are you, I mean, there's all these different labels for people and careers and, and not a lot of like effort being put into me. Like, but, but they're all saying the same thing, or, or, you know, it's just twist. Very subtle differences rather than entirely different things.

[00:00:48] Ken: This episode of Ken's Nearest Neighbors is powered by Z by HP. HP's high compute, workstation-grade line of products and solutions. Today I had the pleasure of interviewing Josh Starmer. He is a return guest on the podcast, and a lot's changed since the last time he was here. So since the last time Josh was on the podcast, he's actually published a book, The Stat Quest Illustrated Guide to Machine Learning.

Today we're gonna talk a little bit about what that experience was like. He also came on the Bright Data Trip, the, at the, at the Bright Data House, and I'd love to hear his experience there, meeting with all these other creators and, and just what that was like in general. So, Josh, thank you so much again for coming in and, and having this little chat with me.

Hey, it's good to be here. Amazing. Well, you know, I, I was so excited to see you in North. Last time I, for those who don't know, on my last trip around, around the United States, maybe, Oh, was that almost three months ago? Yep. Josh had me over to his house. He cooked me a wonderful steak dinner. So for, for those who don't know, Josh is also aside from being an incredible musician a incredibly insightful, studious statistician, but also an incredible cook.

So, Aw, thanks. I don't, I'm gonna make you turn right so many times between this you know, I'm interested, what, what got you interested just in cooking? I mean, it's a little bit different, but I mean,

[00:02:16] Josh: I love food. I mean, I've loved eating ever since I was a little kid. I've always loved eating. And when I was a, I started cooking my own meals, probably when I was six.

My mom got me a little tiny frying pan and a little spatula. I had all this little stuff and I would cook myself breakfast and lunches. So Id been cooking my whole, whole life.

[00:02:40] Ken: Wow. That, that's amazing. So something I know that. Personally really enjoyed was the roles you made. Ah, yeah. Is is there any There are there, actually, I would have to say probably my favorite home cooked roles I've had in my entire life.

But are there any things that you really enjoy cooking the most? Is there something you, you consider yourself specializing in? Well,

[00:03:04] Josh: I love baking. I love anything with yeast, so those rolls are, are part of my favorite things that I make. I just, any yeast is sort of magical, right? You, you mix it with flour and water and some salt and the yeast.

Literally takes on a life of its own and sort of lives in the, in the dough and it grows. And I don't know, it's kind of, it's just magic every time I do it. And I, it's never grown old. And, and this is also, it's also one of those things that when I was a kid, my dad baked, he baked bread and, and I just loved his bread.

And Al always just wanted to make his bread. And so I guess it's one of those like multi-generational things as well.

[00:03:46] Ken: That's really cool. I yeast has been very interesting for me for other reasons. So for those who don't know, and I'm obviously not the expert here, I think Josh knows significantly more about this than I do, but everything that you put into whatever, using yeast in, whether it's bread or a pizza dough or whatever it might be Everything impacts the yeast.

So salt in some sense, retards. The, the, the growth of the yeast temperature is very relevant and time is also very relevant. So you have to pay attention to all these different factors. You know, we might call them different features for big game . That's right. And, and that, that sort of dynamic problem is really fun.

And there's definitely an art to, to getting it right based on the, the climate or even the altitude, I would imagine. That's an impact on things. It'd be fun to do a little little algorithm associated with that.

[00:04:39] Josh: Bread rises higher at high altitude cuz there's less atmospheric pressure holding it down.

And it's actually it's actually a problem for a lot of recipes that are based on the volume of the dough in that you'll get a recipe for bread that says, Wait until the dough has doubled in size. Well, at high altitude it can do that too fast. And, and so you really, you have to kind of know that.

That you actually, because time is also an important factor. You've gotta like punch the dough down or, or deflate it and let it grow some longer to, to develop the flavor and the gluten so it doesn't just turn into a brick in the oven. Interesting.

[00:05:18] Ken: Yeah, I, I will definitely have to get the, the roll recipe for Hawaiian temperatures.

Yeah. Because the humidity, you know, it's not 70 degrees inside, it's. 80 degrees inside and, and those types of things, so.

[00:05:32] Josh: Fairly close to my North Carolina situation as well. Maybe my next book will be the Sta Quests Illustrated Guide to Baking,

[00:05:39] Ken: Please. . I would, I would be the first to pick it up. A hundred percent right.

Incredible. Well, you know, you mentioned, you mentioned the book. I'm really interested in the story behind that, so, you know, perhaps let's get an origin story. How did you get started with that? What, what was the inspiration for

[00:05:57] Josh: wanting to write a book? I never wanted to write a book ever. I thought, I mean, look how thick this is.

This is, it's 300 and fa five pages long. Writing that many pages is something that just seemed like the worst thing I could possibly do to myself. And so I never ever wanted to write a book. But, but fans on my YouTube channel kept requesting a book. And. You know, I was like, I don't even, I can't, I do videos.

Why should I do a book? I didn't really understand what the, what the advantages are, like, I mean anyways so gradually over time I, I discovered that different people learn different ways. Some people are, are learn effectively from the videos. Some people learn more effectively from books. And I think that was something that was kind of slow for me to realize, cuz.

Because that's what I did. I made videos and I was like, clearly this is the best way to communicate. But some people really are better with the book. And, and the other thing that's nice about the book that I didn't realize until I started writing it is when I make my videos, in order to keep them from being four hours long each, I try to keep 'em real focused on the specific topic at hand.

And in a book you can actually look at more big picture things and you can. You can show links between different topics and how they're related and, and, and you can do, I could do a lot more in the book than I can in say a 15 minute video. So that was a really cool thing. Another thing that was nice about the book is over the, over the, you know, past six or eight years I've been making stat quests videos.

I know what the frequently asked questions are for each of these topics and, and in the book I could include all those sort of lessons learned from things that maybe I could have done a better job explaining in the videos or just things that that just are questions that pop up a bunch of times when, when people wanna learn about, say the a u c area under the curve.

There's, there's everyone's like, how do you calculate it? And, and my answer is like, you just get a computer to do it. I mean but, but you know, people actually wanna know. So in the book, I've actually got a diagram of how you can break that shape down into rec, rectangles and triangles and easily calculate the area of each shape and then you'd add 'em together.

So I was a, I was able to add things that I'd wished I'd included in the videos Origin.

[00:08:31] Ken: That's incredible. And it, you know, it seems like a, a book in this sense, like you describe it, sort of ties everything together. It lets you look back at the body of work that you've done and say, Okay, these are the meta concepts.

These are, this is the story that we've, through all of 'em, I know at least with a lot of my videos, it's like, just like snapshots. Yes. Right. Of different parts. And if you're talking about, you know, specific algorithms or you're talking about specific STA statistics concepts, It's not this like beginning to end that you, that you might have in a, a classroom setting.

That's right. Yeah. And I think that that's something not, that was, that was missing from the, the work that you do but something that really is additive. For a different type of user. Yeah. You know, we've talked before and your, your views go way up during midterms, during finals. That's exactly right.

When, when students are searching for specific topics. Right? Yeah. Yeah. And I love that this is something that, you know, I I, I've been, I've gone through about half now, or it's like, Oh, I, I can start like learning from like these these like benchmarks or these, these signpost. And pick it up from there rather than just picking from, from the search and those types of things.

So it was a very, very meaningful and, and a different look at teaching, which, which I really enjoy. Right. From your perspective, . Right. Was there anything that really surprised you when you were writing the book or something that you didn't expect? I,

[00:10:03] Josh: well, I, like I mentioned earlier, I didn't expect I would actually write it.

Yeah, that was a big shock. What, what happened though is when I first. Quit my full-time job in a research laboratory to do YouTube full-time. I really wasn't, I wasn't making hardly any money at all. . I did the math and I was making less than someone who bags, groceries and, and I, I really wasn't making enough money to make ends meet.

And I tried various things. Like I tried doing consulting and I tried doing a bunch of other random stuff. What they ended up doing is actually getting in the way of me working on my videos and the whole point of quitting my full-time job. Was to spend more time doing stat quests. And so I had to figure out another way to get kind of a supplementary income to make ends meet that wasn't consulting and was still kind of focused on stat quests.

And so what I did is I made these PDF study guides from, for some of my videos, about six of my videos. Where I just, in a PDF document, I kind of put all the main ideas and the main concepts, and if there were any like equations that were important, I put them in this study guide. And so I started selling these study guides and as a, as a result of creating those study guides, I saw how I could make my book.

And and what I realized is I didn't have to write a book that instead of writing it, I could draw. Because I don't really think very well in words, but I, but I am able to think in terms of images and, And pictures and songs. Yeah. And songs and silly songs. And so once I realized that I could draw my book, you know, and that's, that was the process I, I went through with the study guide.

Once I realized I could draw it, all of a sudden I was like, Oh, I can actually do it. So that was like a big. I mean, maybe it wasn't a surprise while I was writing the book, but it was a big surprise in terms of my life, in terms of like, I went from being someone who was dead certain. I would never, ever be able to write a book because I'm not, I'm not fantastic with words and describing things with words.

To someone who was like, Oh, I can write books. And now I'm just like, in love with writing books and all I wanna do is write books. The process is, I, it's, it's, I mean, I love making videos, don't get me wrong. And so, you know, and one is silver and the other's gold but right now I'm just like, Oh, this is, the process is fun and, and the end product.

I've never just holding it in my hands. I'm like, Ooh, this is a book that's special.

[00:12:43] Ken: This episode is brought to you by Z by HP. HP's high compute, workstation grade line of products and solutions. Z is specifically made for high performance data science solutions, and I personally use the ZBook Studio and the Z4 Workstation. I really love that Z workstations can come standard with Linux and they can be configured with the data science software stack. With the software stack, you can get right to work doing data science on day 1 without the overhead of having to completely reconfigure your new machine. Now back to our show. Oh, there's something really incredible.

I mean, the book is, from my perspective, quite beautiful. Correct. I I, I think that there's something really fun about your approach to learning in general, right? From our discussions. , you, you found a way to make all of these concepts fun to you. Mm-hmm. and, and in different ways. You know, the videos, it's with songs, it's with, you know, funny puns and jokes and sound effects.

And with the book it's with a lot of similar sound effects. Yeah. But, but you're reading in your head it's a, you know, it's, it's drawings, it's action like that. Yeah. And I'm wondering from your perspective, obviously, aside from reading the book and watching your videos, how can people take maybe a lighter approach or a more fun approach?

To learning some of these technical concepts. ?

[00:14:03] Josh: Yeah, that's, that's a good question. How to lighten the mood. I, I mean, I guess the thing is, is Oh, I don't know. I mean, I just, I, I, I mean, I, I genuinely think that statistics and machine, I think it's fun. And, and it. It isn't just a bunch of equations, it's actually doing cool stuff.

And if you think of it in terms of doing cool stuff and not just in terms of like fancy, complicated, scary looking mathematics maybe it's, maybe it becomes more fun when, when, when, when you think about what you're doing with it and what the goal is with it. And maybe it's just a matter of having a bigger picture and, and not getting lost in the, in the Greek symbols that they, they put in all those equations.

[00:14:53] Ken: I love that. I mean, I think breaking complex things down into simple, concrete examples is, is something you do unbelievably well. And just cutting through a lot of the noise, cutting through a lot of the jargon. I know I, when I was studying any form of math, when I was studying any form of more technical concepts, I just remember having to write a glossary for myself.

Where? Yeah. Right. And I'd say, 50% of the time. Yeah. It was focused on learning the, the like, the lexicon. That's right. And then the other half is spent actually implementing and learning the, the meat of the, of the concepts. And if we think about it that way, that's fundamentally flawed. Yeah. Right. Yeah, exactly.

If we could shift that ratio just a little bit. Yeah. And I, I, I've always liked how you've used, you know, songs, fun analogies, whatever it might be to break through a lot of the jargon or, or call it out or sort of, in some sense make fun of the jargon, right? Yeah, exactly.

[00:15:50] Josh: Yeah. It's, I think a lot of it is silly, right?

And a lot of it is I don't know, It's just, I feel like every. Yeah, it's just a big pile of jargon. And it, and a lot of it is, I feel like the jargon is actually designed to intimidate people rather than sort of welcome them in, you know, It's, they're, they're there to like, like, for example, the concept of a confusion matrix is something that I'm been working on.

It's right. Like, I just feel like that name is inherently designed to confuse people. Right. Why don't you just call it like, True and false positive table, or I don't know. There could, there could just, could be like other names for it that would be more direct and more to the point. One of my, you got me on a roll here.

One of my biggest pet peeves in all of statistics right now forever has been this thing called a type one versus type two error. And like, who comes up with that name? Why don't you call it false positives versus false negatives? Because that's what they are. They're not, I mean, sure there are two types of errors you could make, but one, the, the number one gives you no information about what kind of error that is, and the number two doesn't either.

So, so it's like someone came up with this terminology, which is like pervasive in all statistics. Just to reign on my parade and make it harder for, cause I can never remember that stuff. And so, I mean, I don't know. I mean that's one of those things where I've seen it so many times over the years, but I'm just, I mean, probably it took me about 10 years before I could remember the difference between a type one and type two error.

And if someone had just said False positive, false negative from the GetGo, I would've never had any of that problem.

[00:17:36] Ken: Yeah, I think that that's also perpetuated. You know, we have statistics, we have data science, we have machine learning. We have, you know, an evolution of the career path where we just call things different things.

Right? Yeah. I mean, features in machine learning are the exact same as independent variables. Yeah. Right. And it's like, do we really need another name? I think features is probably a better name than independent variables. Yeah. But they're both used. Right? And it's. Some people within the domain call one thing, some people within the domain calling another thing, and it just does get really confusing when there's so many different names for a lot of the same things.

Is there something you think we can do as like a, as a group, as as people learning statistics or domain that can help limit those or, or sort of press for a better future? Is it just about creating fun videos and creating like a more conversation around why that's a problem?

[00:18:29] Josh: Yeah, I mean that's, I mean, I just feel. I think as humans, we like to make things come more complicated than they are. And I think that, I think there is something very, very natural to like, to that tendency either for like I think it's baked into our evolution to, to try to separate one group of people from another group of people. We, we use language to do that and we use it within the field, right?

Like, That you can tell a Mach machine learning person versus a statistics person, even though there's tons of overlap, they'll use very different language to describe the exact same thing. And it's, and it's part of our, I feel like it's our just natural tendency to try to always find ways to figure out, like, What your identity is.

Are you a data engineer or are you a data scientist? Are you, I mean, there's all these different labels for people and careers and, and not a lot of like Effort being put into me. Like, but, but they're all saying the same thing. Or, or, you know, it's just twists very subtle differences rather than entirely different things.

So, I don't know. I in some sense I kind feel like it might be helpless because as soon as you come up with like a common lexicon or a common shared list of words that we're gonna use to describe things, someone's gonna come up with something else. That, that, that actually ends up being the same thing as like linear regression.

And they're gonna give it a new name and there'll be a new field out there called like data wizards. And they're gonna use this new language. The data wizards are gonna be like, Well I don't know that linear aggression thing you guys are doing. We call it linear line thing. And you know, and that's, I mean, that's just, I think it's inevitable.

That's weird. Stuff is gonna happen like that.

[00:20:23] Ken: So, you know, it's interesting, we've talked and you recently took an awesome new role, which is related to AI and education. Yeah. And that means you're working a lot more close to industry than you perhaps were in the past. Is that something that, you know, you know, what, what are some of the things that you've seen from those experiences now that are a little bit different from what you were experiencing?

Just making videos on your own and creating the sta quest business and, and, and channel and content. I, I think. what we're describing right now, the, the Lexi kind of, those types of things. That's like a very industry heavy thing. Yeah. Right. And when we're at home, we don't have to deal with it.

But when you go into a new setting Yeah. People are calling things different than you've heard 'em before and, and you're starting to get exposure to all these, you know, like a lot more confusion comes into play.

[00:21:11] Josh: Yeah, yeah, yeah. I mean, geez. Along the lines of, of sort of different words and how they're used.

I, so my background is in genetics research but I'm now working for a company that facilitates neural network research. And and I, when I first sort of working for lightning. That was actually a big stumbling block block for me cuz they keep talking about research and just in my mind, I just thought a bunch of people like doing experiments and I mean but not just like on a computer, but like with a, you know, mixing chemicals and, you know, holding vis up to the light and peering through it.

And that's the kind of research I'm more familiar with and I'm not, I wasn't really familiar. Neural network research. And I didn't even know what that meant cuz I just thought you create neural networks and you use neural networks. I didn't realize there was a whole like, research branch in there. So it was kind of like a, a a little confusing for me at first, just once I, I had, you know, and, and it's one of these things in hindsight, I'm like, oh, it's obvious.

But that was a, a language issue that I had earlier on with the company. But what I'm really excited about with, with Lightning is You know, when I'm, when I was working, doing YouTube all by myself, all alone in my little cave, I feel my fear, a kind, sort of a constant nagging fear is that I'm gonna lose perspective and I'm gonna lose sort of like a sense of what's really going on in, in terms of what my audience needs to get done.

You know, they, they, I can teach concepts all day and all night, but, but is that really gonna be what they need? To get their job done, you know, is, is are the concepts enough? And I feel I have always felt like the concepts weren't enough. And that's based partly on my college experience. Experience. I remember I, I went to college and I learned a bunch of stuff and then I got a job and realized that everything was completely different from what I learned in college.

And there was a huge, that disconnect between college and my job bothered. Because, because I, I, I'd worked so hard in college to, I wanted to get good grades and I wanted to do well on the projects that I had. And I, I just, you know, I wanted to get patted on the back all the time, so I worked really hard.

But it was, and then I started this job and realized that like not, it wasn't that, it just wasn't useful. It just, it had nothing to do with what I was doing. And one thing that's I like about Lightning is it is, it does help me stay sort of in the. In terms of what people are actually doing, what are they doing with ai?

How are they doing it? What do they want to do with it that they can't do right now? What are the, what concepts are. Keeping them from taking full advantage of these tools are that, you know, if they, if they understood how it worked a little bit better, would they be able to apply it better? So that's one thing I'm excited about with this company is they, they kind of keep me grounded and, and not just completely isolated from their rest of the world.

And I mean, Ken, I could go on forever about this, so just stop me. But I keep talking about things I'm excited about. No, I love it. Kidding. Another thing I'm really excited about is I mean this is going on for years. Ever since I started making my first video on neural networks, I wanted to have a companion series of how to actually do it like in Python or you know, the language of your choice.

Right now we're gonna use Python. And because I, because I didn't wanna just teach theory. I wanted to teach like, this is how you do it. And part of the reason why I wanted to teach this is how you do it, is I'd never done it before. And I felt kind of guilty that I was teaching people the theory and be like, Well, that's the theory, but I don't actually know what it, how to do it.

You know, in person I, That was embarrassing to me. So I was like, I really wanna. Series of videos where it's hands on because that's how I'm gonna learn it myself, and that's another cool thing that Lightning is helping me with. They've got some of the best pie torch neural network programmers in the world working for them, and they are, They're teaching me so that I can teach.

Through my videos, I can teach everybody else and it's, I, I just love it. They're you know, they're super patient with me and they answer all my little nitpicky, silly questions and, and I'm super excited about building this series of, of not just. Not just theory, but also applied neural networks and I, and with the hope that this series on neural networks is actually something that people could then do at their work.

And it wouldn't just be something that they learned that was completely abstract and not useful at all.

[00:25:58] Ken: That's incredible. I mean, it seems like a, a really good fit, especially for your interest in the actual implementation process. Something I'm interested in also is how have you found it going now?

Working with people? Versus when before, when you were exclusively working by yourself. Yeah. That to me must have been a pretty big.

[00:26:20] Josh: Yeah, yeah, yeah, it's true. It's, it's funny, it kind of goes both ways in that I think my, my personality is very introverted and I've always worked better when I worked alone.

And I have a lot of difficulty working in a group that's, that's It's just something really hard for me to do, and it's always been that way. And I always just have, if I'm gonna get anything done, I've gotta find some little quiet corner and just work on my own little thing at my own pace. But working with the company is, is, is also, it's, even though I'm introverted, it's fun to, it's, I still like people.

It's, it's, it's not that I don't like people that I'm introverted, it's just that I can't be, I. I have to have some time to recharge from time to time. And, but when I, but I do like being around people and so if I'm around, I'm, if I'm isolated and alone all of the time, well that's still, that's still lonely and, and it's.

I don't know. I just, I love the people that work. There's this one guy at at Lightning named Audrey and I, and I don't want, I'm gonna, if I try to pronounce his last name, it's, it's gonna be terrible. He's Swiss, but I just feel like we're PEs in a pod. Like he, I, I can talk to Audrey all day and all night about stuff and like, we've had conversations where I've almost come to tears because I felt like he understood what I was trying to do so well oftentimes people don't like, like I really wanna break this down into something like a really simple problem and, and they'll go, Okay, yeah, yeah, yeah.

I, I, I hear what you're saying. And then they'll come up with something much more complicated than it needs to be. And, and Adrianne was one of the first person I'd ever talk to that when I said, We need to come up with a really simple problem, he was like, I get you. And he came up together, we came up with this incredibly simple thing and, and I just felt.

Well, I found a kindred spirit, you know, in a way that I, Oh, I, it just felt really good and, and it, and I don't know it, it was very emotional. I'm getting emotional now, I mean, but 13 years before that, I'd worked in a genetics lab and I loved those guys and we had a great time doing work, hanging out, being pals and all those things, but none of them were like computer people.

And I think fundamentally, I'm a computer person. So when Audrey and I had that conversation and we just connect. At that level, I was like, Oh, it's fun to be around computer people. You know, You know, it's, these are my people. I mean, I, I do love the geneticists, but, but I think fundamentally it's, it's cool to be around computer

[00:28:55] Ken: people.

Well, speaking of being around computer people, For the past week, you've been around at least a couple of 'em. I think , it's kinda drinking from the fire hose of how many computer people around. Yeah. And I'm wondering about what your experience is like. And so for, for those who aren't familiar, we had a creator retreat through the, the agency that I started Learn Media and Bright Data came in and they sponsored the whole thing.

So again, a shout out to them. But. What has that experience been like? I think we're, we had at the peak maybe 16, 17 content creators around. Yeah.

[00:29:30] Josh: Well it was incredible because again, almost all these content creators. Also had day jobs, and I got to hear about what they do, what their, what their problems are, what they're excited about what's been, what's worked at work, what hasn't worked at work, what were, what companies, you know, what, what, you know, they, everyone seems to have worked for almost every company.

You know, It's like everything was represe. Among the people that that were here, and you could, you know these people. One company had this technology for databases and another company had another technology and they were talking about how great it was to go from company A to company B. And just hearing about that and getting that context is something that I don't typically get on my own.

And so it was sort of like being bathed and sort of the reality of what it means to be a data scientist or a data engineer. Or, you know, I don't know, there's probably a million other names of the, the different types of people that were here. But I, you know, as someone who I've spent a lot of time in academics it was just great and enlightening and awesome to be around people that had nothing to do with academics and everything to do with sort of working in startups, working for major corporations and everything in between.

And sort of hearing what their, what their. Pain points were what, what, what made them happy and sort of what they were doing and how they were doing it. I,

[00:31:02] Ken: I agree so much. It's, it seems like even when you're at your, your job, right? You're in that sort of bubble. Yeah. You're seeing the problems that you're running into with your technology stack or the opportunities that are facing your current company, and when you're hanging around people that you don't necessarily work.

You get to see all the other cool things that are happening. And that's something that I've realized is I need to sort of get outside my own bubble more and whether, you know, it's like even in within the content creation niche, right? It's like, Oh, we're making videos on YouTube. How are people doing it on LinkedIn?

Like, I'm gonna interview Yeah, Zach Wilson in a little bit and he's. Unbelievable things on LinkedIn that I wouldn't necessarily have thought of, or people who are streaming or on different platforms or whatever that might be. It just in my mind, really pays to at least talk to people who are doing things differently in different places.

Cuz you gotta learn from their experiences. You gotta say, Hey, maybe they're doing it better than we are. How can I change it? Or, This content is doing well in this place, maybe I should try it here. I used to think that I could figure it out on my own. The idea that you have to sort of search for things a little bit or, or, or prod and, and, and poke around and, you know, meet different people and communicate with them has been revolutionary in any of the growth that I've had with, mainly with my work.

[00:32:25] Josh: Yeah, no, I, it's been fantastic and it's, and it's, it's been fun because, I get to see the, the, the forest of what everyone does. But you know, through sort of individual conversations and one-on-ones, you get also get to hear about the trees and, I don't know, I just love, I don't know, I just love the exposure and, and I'm already looking forward to doing this again, just so I can get some more of it.

[00:32:47] Ken: Amazing. Were there any particular conversations or particular people that, that really stood out to you and you won't offend anyone by Not by. Saying

[00:32:58] Josh: everyone. I, I, I, I, I had great conversations with Han Hanlon. Yep. And I had a great conversation with Avery Avery Smith, Avery Smith golly.

Who oh, I'm blanking. I'm pretty much everyone. I had Great Joe Reese math. Matt hit his collaborator.

[00:33:22] Ken: Yeah. Yeah. Matt H...

[00:33:25] Josh: I can't remember his last name. I'm terrible with names too. So Alex, I mean, pretty much every, I mean, I I'm, you know, Zach, everyone that's been here has given me some great insight.

Tina had a great conversation with her, great conversations with Nikki. And of course you Thank you. It's just been wonderful. So, yeah, the whole crew has been, it's just been a fantastic experience for me.

[00:33:58] Ken: Was there anything that surprised you about, you know, either the people or the actual event or any of those types of things?

[00:34:08] Josh: Everything kind of surprised me to be honest.

[00:34:10] Ken: And the first one, you don't have no expectations of everything.

[00:34:14] Josh: Yeah, I mean, I'll be honest, about a week ago, I as convinced I was gonna show up here in Salt Lake City and just be at the airport and go, Now what do I do? ? I was just, I mean, I'd never done this before.

It was completely, everything about it was completely new and, And I just did, I had no idea what to expect. And so everything was just, you pulled up in this beautiful car, and picked me up and whisked me away, and I was like, Wow, this is awesome. So it yeah everything has kind of surprised me and the fact that it that it, I don't know.

It's just, it's just this is very different from what my normal life We we had great talks, we had great food. We went rock climbing Today. We've done all kinds of stuff together that I would never, I would've, I don't know, I just, it was all great and, and and pleasing in, in a way that was surprising in all the right ways.

[00:35:15] Ken: Amazing. Well, that makes me really happy to hear. You know, something that I found very interesting with, with trips like these is. , everyone that comes, they're, they're sort of on the same page, right? I mean, it's novel for everyone, but everyone's there to learn and everyone's like very reliable and also very nice.

Which was a bit of a departure from a lot of the trips that I've been on with like my friends growing up and those types of things. Yeah. They don't listen to my podcast, so I'm not super surprised. . But, but you know, it's, it's, it's nice where there is this alignment between personal growth between.

Learning and between, I guess like, in some sense like a, a, a business objective for being here. We're all trying to improve the content that we create, create more value, and, you know, also potentially create more of a business for, for all of us. Mm-hmm. You know, that, that to me is something that I'm always constantly surprised by is just the, the quality of the, the group.

You know? Yeah. There. You know, knock on wood, between the two trips we've done, there's been absolutely no drama. There's been nothing like crazy that has, aside from the, the hot tub stream

[00:36:28] Josh: That was legendary. For those who don't know, we did a live stream from a hot tub Yes. On

[00:36:36] Ken: Shaun's channel.

Yes. Good old five dudes in a hot tub, looking out data. What more could you ask for?

[00:36:45] Josh: Really? It was legendary. Yeah.

[00:36:48] Ken: Yeah, so, you know, it makes me really happy to hear that the experience was good for you. I think. People would unanimously agree that the experience was better because you were there, you were there as well.

Oh, that's really nice. Yeah. You know, honestly, Josh, those are, those are all the questions I have. Do you have anything you want to add? I, I definitely want to add that I'm gonna link the book in the description. Definitely check it out on Amazon. I, I have assigned copy, which I am unbelievably grateful for, and I've, I've enjoyed reading it so much, so far.

[00:37:22] Josh: Aw, well, Ken, I just wanna say thank you. I, I, I, you know, when we first sort of started emailing, I don't even know how we started contacting online a couple years ago. And, and when you had me on, on your show, I, I just feel like you've, you've lifted me up and you've made me feel part of a community that That I'm excited to be a part that I'm, that I feel really honored and very privileged and, and, and excited about being a part of a community that, that, that I never as, as someone who came from a background in academics, never had an exposure to.

And so with, with you, you, not only did you, you know, introduced me to a ton of people you in invited me to spend Four or five days with them and, and all this. I don't know, I just I'm just so happy that, that you've, you've been so generous and welcoming of, of me into this circle of friends, and it's just been a real pleasure.

[00:38:23] Ken: Yeah. I mean, honestly, that makes me so happy to hear y it, it's interesting. I just really enjoy bringing people together, meeting people and, and. Creating groups. And, and to me that's something that it's like, you know, where I live in Hawaii, there aren't that many people who I can talk about like, a lot of the fun things that we talk about, right?

And a little selfishly it's like, wow, I can, I can meet people who I, I feel like are my people who are you know, interested in the same things, have similar vision and goals, and if I can find them, You know, they're out there, why not bring 'em together and we can all do fun stuff together.

We all get this beautiful value of Yeah. Of each other's experiences and and, and time and, and also company. And so I'm just really happy that this has worked. .

[00:39:21] Josh: Yay. Yeah, it has worked. Awesome.

[00:39:25] Ken: Thank you so much again, Josh. This is incredible. Yep. Also thank you to Bright Data for sponsoring this trip, making it make financially possible for all of us to come out here as well.

[00:39:35] Josh: Thank you.

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