WEBVTT

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there's the man hey jackson how you doing buddy

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i'm doing great james lang i'm excited to meet

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you yeah likewise i really like uh what you do

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you know taking uh actionable insights and real

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stories and kind of passing them on to those

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following in our footsteps right the bromance

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is strong where are you based out of james uh

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so i'm in denver yeah but i previously i was

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in scottsdale then la before that so but denver

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today scottsdale la denver today very good was

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that just a trip or did you mean you were you

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were stationed or or i i'm from yeah no i was

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based in la then scottsdale and now denver so

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um yeah just move around a bunch but you know

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you follow the dollars follow the opportunity

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and uh Certainly tax -wise, moving from LA to

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Scottsdale was nice. No, I love visiting LA.

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I love visiting. It's fun. Yeah. I love getting

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to LA almost as much as I like leaving. Yes.

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That's right. I'm down in Ecuador, actually.

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Oh, you're the smart guy on this call because

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you're doing the expat life where you're saving

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a ton of money. Well, that too. That's also for

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sure a big part of it. If you're okay with it,

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I'll share my vision real quick. Yeah, of course.

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We'll switch gears and dive into yours. I'm excited

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to talk about AI. Also, by the way, since we've

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already no hold bars, like started the conversation,

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if we want to, we can use this entire thing as

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an episode because it just turned out organically

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to be awesome. And if we decide we want to cut

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it, then we can cut too. So either way. Yeah,

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it's your show, man. Whatever you think your

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audience appreciates the most. I love that. It's

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my show, but it's your vision. And so we also

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always share that with the visionaries that we

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have. It's not my vision, it's yours. So we always

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want to honor that. But yeah, James, so my vision

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is to bridge the economic gap between North America,

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South America, and the rest of the world. That's

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what I live for every day. So I'm down here in

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the southern part of Americas and doing what

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I can to help people and bring that dream to

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reality. If I make even one small impact on it,

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fantastic. But every day I get to just be my

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best and show up and try to commit to helping

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with that. So what does that look like? Help

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me unpack that. It's a great question. In 10,

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15, 20 years, it might be lobbying to governments

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worldwide. As of right now, it's a first -class

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business. We help entrepreneurs with sustainable

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revenue growth. And then we have a program called

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Operaciones de Trabajo para Latinos. That's opportunities

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for work for Latinos. We've got a Spanish show.

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I actually just got off the Spanish show as well,

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but I have a couple of counterparts who are from

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Colombia and Peru and their co -hosts with me

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of the Spanish show. And we interview Latinos

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about how did they find their first job or how

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did they find their current opportunity? What

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work did they put in for that? What programs

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did they train in? And then we promote those

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episodes to help other Latinos jump into the

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program. And we give those services away for

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free, helping Latinos learn leadership skills

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and develop. Oh, there's my. My bell that says

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it's time to take my antibiotics. Cause, uh,

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even though I enjoy being here, my stomach doesn't

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always enjoy me. Oh, I've, I've had Montezuma's

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revenge before I've been there. That was terrible.

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You know it. Yeah. I live with Montezuma, um,

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often. So, um, yeah, I got laid up in Cabo for

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about three days straight, uh, past the time

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that I was going to fly home. Um, yeah, that

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was an experience. You know it, you know it then.

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So James, yes, AI. I'm not going to steal the

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show from you, but my audience knows a little

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bit about what we do and how we do it. So I just

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want to say congrats on what you're building

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because I saw the playground. And I was like,

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oh, cool. This guy, this guy gets it. And, you

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know, the AI craze, I love how you point out

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too, that, you know, there's a way for AI that

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you can ride, you can get crushed by. And that

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was really smart. And then I went to the playground

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and I wanted to move forward, but I'd saw the

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little memo that you don't have to like log in.

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And then that one still has like the login thing,

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but we're building something similar at first

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class business. And I called it Alfred. um you

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know meet alfred the butler of we're we're into

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heroes and all that so the butler superman and

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then we built mr fox as well uh we built both

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those characters and we still haven't released

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it though so you're ahead of me praise to you

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like good job on on moving it forward and getting

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things out there um but i mean if you want to

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we can just dive right in and start talking about

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vision but is there do you have any other questions

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for me before we do no it seems like you're super

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kind and generous so i appreciate it it's a great

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space for a conversation Yeah, man. Well, good.

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Then tell me about, tell me about your AI vision

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for now. Let's start there and then we can expand

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into other visions. Yeah. Well, let me tell you

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how we got here on the AI side of things. So

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about, and there's a whole bunch more to the

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story we can unpack later, but just kind of the

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condensed version from somebody who likes to

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talk too much. About six months ago, one of my

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buddies that I grew up with in Virginia beach

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in Virginia, his name's Jeff. After I moved to

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Denver, I realized Jeff lives out here too. So

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we had gone our own paths, our own ways after

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high school. But I was doing the e -commerce,

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operational consulting, med tech world, highly

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regulated, pain in the butt stuff in the men's

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wellness space. And then that same time, he was

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doing the AI and big data thing. back in like

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2014 like before it was cool so um he now works

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for one of the largest um data solutions for

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all the insurance companies here in the united

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states because you're fortunate you don't have

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to you have to deal with uh some stomach illnesses

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it sounds like dealing with uh you know the local

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water there in ecuador but uh you know we have

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to deal with just don't deal with the local water

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Yeah, you have the option of not drinking the

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local water. See, we don't have the option of

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not engaging with the insurance industry here.

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So you're one up on me on that one. But anyways,

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his background primarily is storing the petabytes

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of insurance information, processing claims,

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doing actuarial analysis, all that stuff, right?

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So we're catching up and swapping war stories.

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realizing that just like I knew back in high

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school, he's definitely smarter than me. But,

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you know, I was like unpacking like, okay, cool.

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Like you have this, you know, this AI and big

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data skillset, but, you know, coming at it from

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a marketer and an operations guy, you know, one

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of the most popular things is, you know, these,

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these quiz funnels. So if you're trying to sell

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a product online, You know, you ask the client

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or the customer four or five questions just to,

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you know, qualify them and get to know them and

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then get their email address. Now you have information,

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plus you can hit up their email without having

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to pay to reach them again. And I was like, you

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know, the problem is we have the goldfish attention

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span, which means that, you know, within five

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seconds, people are jumping. So we can't go really

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beyond five questions in a quiz funnel. But wouldn't

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it be cool if we had AI to be able to have conversations

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around the questions? So you're still doing.

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the five stage quiz. But if you have a question

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about the question or something totally random

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that you want to ask, you can do that all in

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the same place without having to leave and go

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search somewhere else. And anyways, that was

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kind of our brainchild moment. And he's like,

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yeah, we can totally build that. So we build

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out this, this kind of prototype. And the problem

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is, you know, we run through the first data set

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and just the compute to run that data set and

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the testing. it was eight hundred dollars in

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compute and that's what people aren't really

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talking about with ai right is it's so expensive

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to operate um you know most computers can't handle

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it like you can install an ai system or model

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and and you know with python and the infrastructure

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there um you can do it but uh good luck getting

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it to run unless you have like a really high

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-end graphics card and maybe even that's not

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enough in some cases so You know, the result

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is what we're asking all these cloud systems

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to do is so resource intensive that, you know,

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it's become expensive to be able to share that.

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And so, you know, as things get more expensive

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to operate, they become more expensive for the

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consumer. And so a lot of us, like if we're using

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ChatGPT or Claude or Gemini, you know, or Copilot,

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we're all kind of insulated from those costs.

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Like all we see is just, hey, this is kind of

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fun to play with. but we don't realize it's happening.

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Yeah, exactly. I got to pause real quick audience.

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We have like a guy who actually understands AI

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talking about AI for the first time. No, I shouldn't

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say the first time ever, but you're a different

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mode. Like you really get the behind the scenes

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stuff on AI and you know, everybody's claiming

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they're an AI guru these days. And so it's fun

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to talk to somebody who understands like the

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nuts and bolts behind it to a degree. So. Good

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on you, man. Keep going. Oh, well, you've pushed

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one of my biggest pet peeves, which is all of

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these guys on LinkedIn running around saying

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I'm an expert on AI. And last week, they were

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expert on blockchain. And the week before that,

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they were an expert on residential. I was trained

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by the coach of the coach of the coach of the

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coach of the coach of the coach of the coach.

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Like, you know, this should make me an expert,

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right? Exactly. I'll put a little pin in that.

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there's two sides to that that are, that are

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polarizing opposites. And there's a whole middle

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ground that I really appreciate too. But Matt

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cuts, the search director of Google was one of

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our first investors at the very first startup

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that I worked at on local. And I was first, the

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first sales rep hired. And you know, we were

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an SEO company. And so we, you know, he, but

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he immediately put a big, big pin in that. And

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he's like, guys, you cannot claim where the SEO

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gods, just because I work with you guys. I'm

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like, but here's what you can do. He said, the

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real sign of an expert is not somebody who knows

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it all. A true expert is a person who's willing

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to go get the right answer. That's it. Just that

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simple. And so I loved that because I had no

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degree and I had no background whatsoever in

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what we were doing. But I was like, I can be

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humble enough to admit I don't know and I can

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go get an answer. And that's what he taught was

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if you want to be an expert, that's what you

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do. You just go get the right answer. And so

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I don't hate on that. self -proclaimed. Okay.

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Maybe the guru is yes, but the ones who are trying,

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but I love that you understand the reality is

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reading about chat GBT this week and how they're

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not going to be, they have a very small chance

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of being profitable by 2035. But the amount of

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debt and the amount of money being dumped into

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this, you're right. As a consumer, we don't have

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to pay attention to that at all. We just get

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it. We just get to drink the Kool -Aid, you know,

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we just get to use what it is, but. And perhaps

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maybe this doesn't help all visionaries out there.

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Most of us aren't going to benefit from knowing

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the ins and outs of all the back end of AI. But

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it is really reassuring. Well, it's reassuring

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to talk to somebody who gets it. So go ahead,

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man. I'll let you hit on that for sure. Gosh,

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there's so many things that you just brought

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up that you're hitting all my main themes and

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points and things. So I love it. Okay, well,

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let's talk about why it matters. So going along

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with the example I gave, right, where it costs

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us $800 to run one computer. And then we talk

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about one, you know, the consumer being insulated,

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so they don't understand the cost. Well, for

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businesses, they're insulated too. There's AI

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startups all over the place. They're offering

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these off the shelf solutions that promise to

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do all these amazing things. And there's a whole

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bunch of things we can unpack there. But the

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biggest thing that's relevant to what you just

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said is, The problem is these startups, they

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have enough capital to get their plane going

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down the runway, but they probably don't have

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enough capital to keep their AWS bill paid as

00:12:10.039 --> 00:12:13.299
they scale unless they raise more money. So you

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as a business owner, if you're putting your information

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into this system, if you're relying on these

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tools, number one, where is the data stored?

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Do you own it? And number two, If suddenly a

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switch is flipped tomorrow and that company's

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out of business, how screwed are you? And a lot

00:12:31.429 --> 00:12:32.889
of people aren't thinking about that. And it's

00:12:32.889 --> 00:12:34.289
not going to be up to that other business. It's

00:12:34.289 --> 00:12:36.269
going to be when, you know, AWS or Microsoft

00:12:36.269 --> 00:12:38.909
or Google says, you know what, your bill's past

00:12:38.909 --> 00:12:41.389
due. It's, you know, we can't float you anymore.

00:12:41.669 --> 00:12:43.470
And they're not able to raise investor funding

00:12:43.470 --> 00:12:46.029
for whatever reason. So it's a real danger. It's

00:12:46.029 --> 00:12:47.929
a real liability that people aren't really talking

00:12:47.929 --> 00:12:52.320
about. And for us, that $800 compute bill. You

00:12:52.320 --> 00:12:54.019
know, that was what kind of shut us down for

00:12:54.019 --> 00:12:55.340
a second because it was like, yeah, we can go

00:12:55.340 --> 00:12:57.399
build this, but it's going to be too expensive

00:12:57.399 --> 00:13:00.960
to scale. So, you know, me being the dumb guy

00:13:00.960 --> 00:13:02.580
in the room, I'm just like, you know, hey, Jeff,

00:13:02.659 --> 00:13:03.860
I'm going to lock you in a room for a little

00:13:03.860 --> 00:13:07.320
bit. Go fix it. And so, you know, basically that's

00:13:07.320 --> 00:13:09.539
what we did. You know, we bounced ideas back

00:13:09.539 --> 00:13:11.519
and forth and, you know, he actually made it

00:13:11.519 --> 00:13:13.759
work. But, you know, I was able to bring kind

00:13:13.759 --> 00:13:16.480
of the user interface and the UX side of things.

00:13:17.820 --> 00:13:19.259
You know, it's really great working with someone

00:13:19.259 --> 00:13:21.659
who has such a deep level of knowledge in an

00:13:21.659 --> 00:13:24.940
area that you suck at. It's the best in the world.

00:13:25.059 --> 00:13:30.320
So, anyways, he was able to, it took us about

00:13:30.320 --> 00:13:32.539
six months, and primarily by us, I mean him,

00:13:32.620 --> 00:13:36.220
six months to really get something created that

00:13:36.220 --> 00:13:39.779
solved this problem. But what we did, and again,

00:13:39.899 --> 00:13:45.340
we is Jeff, but we built out this virtual cloud

00:13:45.340 --> 00:13:49.919
infrastructure. inside of AWS that has both the

00:13:49.919 --> 00:13:53.899
option to data vector in a way that AI can more

00:13:53.899 --> 00:13:58.340
easily ingest information, but also adjust. So

00:13:58.340 --> 00:14:01.779
you have in a system like this, you have an AI

00:14:01.779 --> 00:14:04.779
model, but that AI model is running in an engine.

00:14:05.039 --> 00:14:06.919
And so you have kind of what's called a wrapper

00:14:06.919 --> 00:14:09.340
around the engine, which is the thing that kind

00:14:09.340 --> 00:14:11.500
of filters it out. So when you're talking about,

00:14:11.559 --> 00:14:14.059
like when you're talking to chat GPT, the thing

00:14:14.059 --> 00:14:16.480
that keeps it from telling you, bad things or

00:14:16.480 --> 00:14:19.399
going outside of its guardrails part of that

00:14:19.399 --> 00:14:21.559
is in the wrapper that's around the engine so

00:14:21.559 --> 00:14:24.019
it's like a filter um which again the engine

00:14:24.019 --> 00:14:26.740
is being fueled by the ai model does that kind

00:14:26.740 --> 00:14:30.700
of make sense is that fair yeah okay so it makes

00:14:30.700 --> 00:14:32.879
sense for those of us who who understood the

00:14:32.879 --> 00:14:36.200
words uh that you put together um so but i i

00:14:36.200 --> 00:14:38.580
understand the the importance though of making

00:14:38.580 --> 00:14:41.309
sure that we're aware of the infrastructure.

00:14:41.529 --> 00:14:43.710
We're aware of the liabilities that we have with

00:14:43.710 --> 00:14:46.509
basing AIs. And I'm really, really grateful that

00:14:46.509 --> 00:14:50.950
my business is not predominantly heavy on AI

00:14:50.950 --> 00:14:54.830
itself, because yeah, that would be a nasty disaster

00:14:54.830 --> 00:14:57.090
if one of the businesses, if you built in the

00:14:57.090 --> 00:14:59.429
backbone of it and then it went up in claims,

00:14:59.549 --> 00:15:01.549
it's like, oh, what do you do now? If that's

00:15:01.549 --> 00:15:03.470
where the diversification or that's where your

00:15:03.470 --> 00:15:05.970
income is coming from. So well said, James, keep

00:15:05.970 --> 00:15:09.309
going. Yeah. So I mentioned a moment ago that

00:15:09.710 --> 00:15:13.210
The challenge is, you know, the cost to scale,

00:15:13.230 --> 00:15:15.649
right? And I also talked about how you can install

00:15:15.649 --> 00:15:18.330
AI on your computer and try to run it or run

00:15:18.330 --> 00:15:19.950
a model. A lot of people don't realize that,

00:15:19.990 --> 00:15:23.049
that there's, you know, hundreds of AI models,

00:15:23.210 --> 00:15:25.909
LLMs out there floating around on the web that

00:15:25.909 --> 00:15:27.789
you can download. And if you're tech savvy enough,

00:15:27.850 --> 00:15:31.070
you can install them. So out of all those models

00:15:31.070 --> 00:15:34.529
floating on the web. we found 12 that we really,

00:15:34.590 --> 00:15:37.169
about a dozen, maybe a little more now, that

00:15:37.169 --> 00:15:39.690
we like for different tasks and different things.

00:15:39.950 --> 00:15:42.450
So the cool thing about the solution we built

00:15:42.450 --> 00:15:47.210
is we can plug and play those dozen models into

00:15:47.210 --> 00:15:51.929
the AI engine based on what task we're trying

00:15:51.929 --> 00:15:54.389
to accomplish. And the same goes for the data

00:15:54.389 --> 00:15:56.149
vectoring. We can change the formatting a little

00:15:56.149 --> 00:15:58.460
bit based on... the task we're trying to accomplish

00:15:58.460 --> 00:16:01.600
so the end result of that is that 800 compute

00:16:01.600 --> 00:16:05.559
bill uh goes down to about four dollars so it's

00:16:05.559 --> 00:16:08.419
a huge difference and you know this isn't something

00:16:08.419 --> 00:16:10.740
that's like you know nobody ever thought of how

00:16:10.740 --> 00:16:13.179
to do this before but the difference is small

00:16:13.179 --> 00:16:15.139
and medium -sized businesses have never had access

00:16:15.139 --> 00:16:17.940
to this before so that's what to my knowledge

00:16:17.940 --> 00:16:21.500
uh unless they're spending a lot of money uh

00:16:21.500 --> 00:16:24.289
because what all the fortune 500s are doing They

00:16:24.289 --> 00:16:25.950
have their own internal teams that are building

00:16:25.950 --> 00:16:27.750
out their own custom solutions from the ground

00:16:27.750 --> 00:16:30.730
up. And companies, the average company out there

00:16:30.730 --> 00:16:33.049
doesn't have access to that. No, we don't have

00:16:33.049 --> 00:16:34.769
access. We don't have knowledge. We don't have

00:16:34.769 --> 00:16:37.250
time as small business owners either. And it's,

00:16:37.250 --> 00:16:39.730
you know, it reminds me of in a very loose way

00:16:39.730 --> 00:16:43.330
of the podcasting world and how with the podcasting

00:16:43.330 --> 00:16:46.049
world, you know, we, a lot of businesses don't

00:16:46.049 --> 00:16:47.649
know like, okay, you can have your own studio

00:16:47.649 --> 00:16:51.529
in your. in your office now and control your

00:16:51.529 --> 00:16:53.970
own media output um you know and lebron james

00:16:53.970 --> 00:16:56.350
and jj reddick caught on to that just last you

00:16:56.350 --> 00:16:58.629
know what two years ago when they launched mind

00:16:58.629 --> 00:17:01.190
the game and it gave lebron the chance to finally

00:17:01.190 --> 00:17:03.830
talk about the narrative of how the game went

00:17:03.830 --> 00:17:07.130
outside of the controlled media's manipulative

00:17:07.130 --> 00:17:09.349
questions you know where they biased him into

00:17:09.349 --> 00:17:11.990
like oh you made this decision and you know it's

00:17:11.990 --> 00:17:14.190
like it's like the question when your kid asking

00:17:14.190 --> 00:17:15.670
your friend i'm going to be completely politically

00:17:15.670 --> 00:17:17.670
incorrect here but it's like when you say how

00:17:17.670 --> 00:17:20.500
long have you been gay for You know, it's like,

00:17:20.519 --> 00:17:24.119
how do you answer questions like that? That's

00:17:24.119 --> 00:17:26.180
not how that works. Or how long is a string,

00:17:26.339 --> 00:17:30.079
right? Yeah. And so those types of questions,

00:17:30.240 --> 00:17:32.359
if we can control our narratives from a PR media

00:17:32.359 --> 00:17:35.799
standpoint, now we have entire media outlets

00:17:35.799 --> 00:17:38.839
in our offices if we choose to build them out.

00:17:38.920 --> 00:17:41.180
And so you're talking about having the same type

00:17:41.180 --> 00:17:44.059
of access to knowledge where the knowledge can

00:17:44.059 --> 00:17:47.220
empower us to be able to have. better solutions

00:17:47.220 --> 00:17:49.019
for us and i'm glad you're building it out because

00:17:49.019 --> 00:17:50.779
most of us don't want to build it out we want

00:17:50.779 --> 00:17:52.859
to find the people like james who's you know

00:17:52.859 --> 00:17:54.779
you claim not to be the smart guy but you're

00:17:54.779 --> 00:17:56.960
like the perfect type of dumb guy um in that

00:17:56.960 --> 00:18:00.240
yes that's exactly it my my superpower is i'm

00:18:00.240 --> 00:18:02.440
this guy in the room and i ask the right questions

00:18:02.440 --> 00:18:03.900
and then i get out of the way while the smart

00:18:03.900 --> 00:18:06.339
people figure it out and you're genius enough

00:18:06.339 --> 00:18:08.819
to learn how to interpret it Right. So I got

00:18:08.819 --> 00:18:10.380
to give you the credit on that. I give you the

00:18:10.380 --> 00:18:12.859
flowers you don't want. But and it's you know,

00:18:12.859 --> 00:18:15.559
I've always been a big collaborator, James. And

00:18:15.559 --> 00:18:17.960
so in high school, they called this cheating.

00:18:18.460 --> 00:18:20.759
And I'm going to shamelessly say that, you know,

00:18:20.779 --> 00:18:22.859
I'm not quite repentant about it. I do feel a

00:18:22.859 --> 00:18:25.140
little bit awkward about it. No, like I was there

00:18:25.140 --> 00:18:27.819
in biology class and I got the top grade on the

00:18:27.819 --> 00:18:31.059
on the test. Right. And so my friends like what

00:18:31.059 --> 00:18:34.339
he cheated off of. So and, you know, and she's

00:18:34.339 --> 00:18:36.549
like, Paul, don't be jealous. And I go. Paul,

00:18:36.630 --> 00:18:38.769
don't be jealous. You know, what I was doing

00:18:38.769 --> 00:18:40.950
was I would ask Paul and then once they, once

00:18:40.950 --> 00:18:42.089
they figured out, I'd be like, what'd you guys

00:18:42.089 --> 00:18:44.069
get on this? And they gave me the answer. And

00:18:44.069 --> 00:18:45.730
then if they were confused, I went to the next

00:18:45.730 --> 00:18:47.089
group over and I was like, Hey, what about you

00:18:47.089 --> 00:18:49.049
guys? How are you guys? Oh, okay. So I just went

00:18:49.049 --> 00:18:53.569
back and forth collecting answers, you know,

00:18:53.569 --> 00:18:56.750
and it worked out well. So collaborating is something

00:18:56.750 --> 00:18:58.990
that in the world of entrepreneurship visionaries,

00:18:58.990 --> 00:19:02.230
we cherish. It's like pass notes back and forth,

00:19:02.250 --> 00:19:04.670
use people's formulas, let people use your formulas.

00:19:05.319 --> 00:19:07.960
grow together. So James, one of the things that

00:19:07.960 --> 00:19:12.079
you have on your site is it's about customer

00:19:12.079 --> 00:19:16.079
support. And that's obviously a huge area where

00:19:16.079 --> 00:19:19.660
Wells Fargo has brutally ruined their customer

00:19:19.660 --> 00:19:22.079
support, as has USAA. I'll call out my favorite.

00:19:22.079 --> 00:19:25.519
And Verizon. Just terrible, like their implementation.

00:19:25.720 --> 00:19:28.339
So it's one of those things where I think most

00:19:28.339 --> 00:19:31.559
of us are hesitant to even bother looking at

00:19:31.559 --> 00:19:34.029
until it's just like so stupid simple. that it

00:19:34.029 --> 00:19:38.230
gets developed. But what's one or two simple

00:19:38.230 --> 00:19:41.670
things that a small business can do in order

00:19:41.670 --> 00:19:45.390
to perhaps implement AI from a support standpoint

00:19:45.390 --> 00:19:49.549
or start looking at how do I even go about finding

00:19:49.549 --> 00:19:53.710
the right people to talk to about it? Well, the

00:19:53.710 --> 00:19:56.549
first thing... that's someone who's truly an

00:19:56.549 --> 00:19:59.470
expert in ai and i don't claim to be one i i

00:19:59.470 --> 00:20:03.509
claim to play one on podcasts but the uh the

00:20:03.509 --> 00:20:07.269
reality is if the person that's going to give

00:20:07.269 --> 00:20:09.490
you the solution is telling you that ai can do

00:20:09.490 --> 00:20:13.390
everything they're full of yeah uh in fact a

00:20:13.390 --> 00:20:16.470
real expert will tell you ai can't do this this

00:20:16.470 --> 00:20:19.930
and this but it can do this really well um you

00:20:19.930 --> 00:20:22.730
know the you use customer service examples in

00:20:22.730 --> 00:20:26.119
the legal field um this is becoming a thing as

00:20:26.119 --> 00:20:29.779
well you have so many uh people taking ai generated

00:20:29.779 --> 00:20:34.740
slop into court including lawyers uh filing things

00:20:34.740 --> 00:20:36.920
and getting censured by the courts because it's

00:20:36.920 --> 00:20:39.319
like really you know you didn't sit there and

00:20:39.319 --> 00:20:42.000
fact check any of this and uh i could talk for

00:20:42.000 --> 00:20:43.640
hours on that but i won't bore you so anyways

00:20:43.640 --> 00:20:46.660
the the place that companies need to go if you're

00:20:46.660 --> 00:20:49.940
looking for people think of ai and think of customer

00:20:49.940 --> 00:20:53.440
support yeah okay cool ai is no different than

00:20:53.440 --> 00:20:56.880
like just I think we should define AI a little

00:20:56.880 --> 00:20:58.460
bit better for the purpose of this conversation.

00:20:58.799 --> 00:21:04.680
So I think of AI more as something that reduces

00:21:04.680 --> 00:21:09.039
the distance between the average human being

00:21:09.039 --> 00:21:11.740
and the silicone running the software, right?

00:21:11.859 --> 00:21:15.319
So you don't need to go through design iterations

00:21:15.319 --> 00:21:17.400
with a designer and then get to have the designer

00:21:17.400 --> 00:21:19.559
go to the coders and then the coders go to the

00:21:19.559 --> 00:21:22.500
UX people and then build out this whole thing.

00:21:23.180 --> 00:21:26.099
you literally tell ai if you treat ai whatever

00:21:26.099 --> 00:21:29.400
flavor of ai you're dealing with as an ass kissing

00:21:29.400 --> 00:21:32.099
employee it's going to give you what you want

00:21:32.099 --> 00:21:34.839
right and so one little tidbit i'll give you

00:21:34.839 --> 00:21:37.960
when i do prompting and chat gpt or claude or

00:21:37.960 --> 00:21:41.200
whatever i always start out by telling the ai

00:21:41.200 --> 00:21:43.539
what it is because it's a blank slate right so

00:21:43.539 --> 00:21:46.599
for example my dad's website which is you know

00:21:46.599 --> 00:21:48.940
i'll plug it here if you'll let me but Um, you

00:21:48.940 --> 00:21:51.579
know, I, I help out his, uh, his law firm, which

00:21:51.579 --> 00:21:54.099
is waterfrontpropertylaw .com, which is a really

00:21:54.099 --> 00:21:58.200
interesting property law .com. There you go.

00:21:58.480 --> 00:22:01.660
So it's a, and it's an interesting area of the

00:22:01.660 --> 00:22:04.059
law because riparian rights in America go all

00:22:04.059 --> 00:22:05.920
the way back to colonial times, like the King

00:22:05.920 --> 00:22:08.440
granted land to people. And then where did the

00:22:08.440 --> 00:22:10.579
land go from there? And did the water move and

00:22:10.579 --> 00:22:12.799
all that stuff? It's really fascinating if you're

00:22:12.799 --> 00:22:16.160
a dork like me, but, uh, anyways, when I was

00:22:16.160 --> 00:22:20.490
producing content for his site, the AI would

00:22:20.490 --> 00:22:24.769
reference all these legal cases. Some of them

00:22:24.769 --> 00:22:29.490
were real and many of them weren't. And almost

00:22:29.490 --> 00:22:32.990
none of the descriptions were accurate of the

00:22:32.990 --> 00:22:35.750
cases. So thank God he reviews anything before

00:22:35.750 --> 00:22:37.450
I post anything on his site to help him out.

00:22:38.089 --> 00:22:41.509
And we caught it. But these are examples of where

00:22:41.509 --> 00:22:45.269
AI is failing constantly. But again, I go back

00:22:45.269 --> 00:22:49.779
to... It's simply democratizing technology. It's

00:22:49.779 --> 00:22:52.740
allowing people to code without having to learn

00:22:52.740 --> 00:22:55.720
how to code. And so if you can learn how to prompt,

00:22:55.799 --> 00:22:57.740
and sorry, I get going on tangents, but going

00:22:57.740 --> 00:23:00.839
back to my prompting. So in that legal example

00:23:00.839 --> 00:23:03.720
for the law firm site, I would say you're an

00:23:03.720 --> 00:23:05.900
expert on waterfront law in the state of Virginia,

00:23:06.000 --> 00:23:08.640
and you've worked as an attorney for 20 plus

00:23:08.640 --> 00:23:11.519
years. So I'm telling it what it is. And then

00:23:11.519 --> 00:23:14.200
I'm saying what I need from you is a blog article.

00:23:14.299 --> 00:23:17.089
It's about 500 words. That's keyword optimized

00:23:17.089 --> 00:23:19.250
based on this brief, based on this information

00:23:19.250 --> 00:23:22.150
that I've attached to the prompt. And then at

00:23:22.150 --> 00:23:24.109
the end, I'm saying the content should be about

00:23:24.109 --> 00:23:27.170
500 pages, should include a featured image, should

00:23:27.170 --> 00:23:29.210
be easily scannable. So when I'm reading it.

00:23:29.329 --> 00:23:32.329
So in the end, that prompt has three parts to

00:23:32.329 --> 00:23:35.730
it. The first part is, who are you? The second

00:23:35.730 --> 00:23:38.750
part is, what are you producing? And the third

00:23:38.750 --> 00:23:42.059
part is. What does the final product look like?

00:23:42.160 --> 00:23:44.839
And if you give that three part formula and you're

00:23:44.839 --> 00:23:46.339
prompting, you're going to get a lot more out

00:23:46.339 --> 00:23:49.839
of AI than you would otherwise. But it's also

00:23:49.839 --> 00:23:53.059
kind of funny to me that this perfectly rhymes

00:23:53.059 --> 00:23:55.660
with what I did as a chief operating officer

00:23:55.660 --> 00:23:58.119
and dealing with a 60 person team and trying

00:23:58.119 --> 00:23:59.839
to get the most out of our team members and,

00:23:59.859 --> 00:24:02.119
you know, coordinating all of the back and forth

00:24:02.119 --> 00:24:04.059
between the different departments and making

00:24:04.059 --> 00:24:06.849
sure the trains ran on time, but also. the shareholder

00:24:06.849 --> 00:24:11.950
and the CEO's vision was executed properly. You

00:24:11.950 --> 00:24:15.630
know, if you set people up for success, they'll

00:24:15.630 --> 00:24:18.569
deliver what you want more easily, which helps

00:24:18.569 --> 00:24:21.430
you succeed. So all of this kind of comes full

00:24:21.430 --> 00:24:24.190
circle into AI as an ass -kissing employee. And

00:24:24.190 --> 00:24:26.430
if you treat it like one, you're going to get

00:24:26.430 --> 00:24:28.549
good results. It's a thought partner, not a thought

00:24:28.549 --> 00:24:31.529
leader. Oh, I love that. I love that you said

00:24:31.529 --> 00:24:33.950
that. And then way to mic drop it at the end

00:24:33.950 --> 00:24:37.650
there. the thought partner, not a thought leader.

00:24:37.769 --> 00:24:39.849
It's, it's huge. And I, I look at it kind of

00:24:39.849 --> 00:24:42.630
like a teenager, you know, who's, who's really,

00:24:42.670 --> 00:24:45.210
really like a prodigy, right? They've got all

00:24:45.210 --> 00:24:46.990
this wisdom that they can use for good and for

00:24:46.990 --> 00:24:49.690
bad, you know, and they can also manipulate and

00:24:49.690 --> 00:24:52.130
change wisdom to get creative on its own. And,

00:24:52.150 --> 00:24:56.250
and so we, we have this superpower at our disposal

00:24:56.250 --> 00:24:59.130
in our hands that we can utilize, but we've also

00:24:59.130 --> 00:25:01.230
got to have the comprehensive analysis skills.

00:25:01.759 --> 00:25:03.759
on our end you know of the old school journalist

00:25:03.759 --> 00:25:05.740
you know a journalist that's willing to fact

00:25:05.740 --> 00:25:07.259
check like you said a journalist that's willing

00:25:07.259 --> 00:25:09.759
to do the the nitty -gritty details to figure

00:25:09.759 --> 00:25:12.279
out what's there because it can it can royally

00:25:12.279 --> 00:25:16.539
hurt anybody very very fast and that that's going

00:25:16.539 --> 00:25:18.079
to get to a whole new level here in a couple

00:25:18.079 --> 00:25:20.900
years when tesla robots um you know are walking

00:25:20.900 --> 00:25:23.079
around everywhere and other robots out there

00:25:23.079 --> 00:25:25.819
are starting to implement this but i think i

00:25:25.819 --> 00:25:28.799
hope that the world uh gets ahead of the types

00:25:28.799 --> 00:25:30.880
of challenges. Like, you know, I, Oh, go quick.

00:25:30.980 --> 00:25:33.359
Give me, give me a hot chocolate at Starbucks

00:25:33.359 --> 00:25:35.700
as fast as you can. Boom. It runs through the

00:25:35.700 --> 00:25:38.279
wall and boom, it runs over and crushes the neighbor's

00:25:38.279 --> 00:25:40.200
dog in the process. It runs through the wall

00:25:40.200 --> 00:25:42.380
at Starbucks, grabs a coffee, steals it, brings

00:25:42.380 --> 00:25:44.240
it all the way back to me. You know, there's

00:25:44.240 --> 00:25:46.079
so many tragedies that could happen along the

00:25:46.079 --> 00:25:48.319
way where this, it doesn't have a conscious,

00:25:48.519 --> 00:25:51.339
um, you know, of like, Oh, there's, there's painful

00:25:51.339 --> 00:25:53.779
realities and threats that exist for human beings

00:25:53.779 --> 00:25:56.400
that don't exist for me. As a robot entity, they

00:25:56.400 --> 00:25:58.900
can't feel any of that. So anyway, I just took

00:25:58.900 --> 00:26:00.980
us down a whole another rabbit hole. No, you

00:26:00.980 --> 00:26:03.480
didn't actually. It wasn't a rabbit hole, actually.

00:26:03.539 --> 00:26:05.640
No, it's all it's all tied in. Right. So here's

00:26:05.640 --> 00:26:07.500
another mic drop for you based on what you just

00:26:07.500 --> 00:26:09.599
said. So I know we're out of time. So I want

00:26:09.599 --> 00:26:11.200
to make sure that you get the opportunity to

00:26:11.200 --> 00:26:13.619
do the power mic drop on this. So let's do that.

00:26:13.920 --> 00:26:16.099
And man, I'm just going to beg you right now.

00:26:16.119 --> 00:26:18.759
Will you come back, please? Absolutely. Yeah.

00:26:18.819 --> 00:26:20.519
I'm happy to stay on for a few extra minutes

00:26:20.519 --> 00:26:22.400
if that's helpful to you or whatever works for

00:26:22.400 --> 00:26:24.420
you. I got to wrap up a little sooner than I

00:26:24.420 --> 00:26:26.279
want to. No worries. No sweat. On that note,

00:26:26.400 --> 00:26:28.400
though, power mic drop. James, hit it. What you

00:26:28.400 --> 00:26:31.220
got? Well, you have to remember that AI does

00:26:31.220 --> 00:26:33.779
not know the difference between Hitler and Mickey

00:26:33.779 --> 00:26:36.099
Mouse. They're just different pieces of data.

00:26:36.700 --> 00:26:39.779
So that speaks to what you're talking about.

00:26:39.880 --> 00:26:43.180
You know, the robot going through the wall. It's

00:26:43.180 --> 00:26:46.480
narcissistic. I'm teasing a bit, but John Gottman

00:26:46.480 --> 00:26:48.099
Institute would tell me, no, Jackson, that's

00:26:48.099 --> 00:26:51.750
not how narcissism works. well said it doesn't

00:26:51.750 --> 00:26:53.509
it doesn't know and we have the opportunities

00:26:53.509 --> 00:26:56.210
right to figure out well how do we train it and

00:26:56.210 --> 00:26:57.829
then the things that we can't train it how do

00:26:57.829 --> 00:27:00.349
we accept that reality in fact from my favorite

00:27:00.349 --> 00:27:02.670
business book one of my favorite business books

00:27:02.670 --> 00:27:05.930
dr peter jackers the effective executive effective

00:27:05.930 --> 00:27:08.809
executives or strong tremendous leaders always

00:27:08.809 --> 00:27:12.160
come with tremendous weaknesses Always where

00:27:12.160 --> 00:27:14.099
there are peaks, there are valleys. And that

00:27:14.099 --> 00:27:17.279
still applies to the AI world as well. And so

00:27:17.279 --> 00:27:19.960
my friends, if you're looking for help with the

00:27:19.960 --> 00:27:23.299
AI revolution, I know we talked very deep level

00:27:23.299 --> 00:27:25.240
and very high level today. We didn't dive into

00:27:25.240 --> 00:27:28.500
specifics, but you can always go check out overlink

00:27:28.500 --> 00:27:30.940
.com and see what James is up to. I'm going to

00:27:30.940 --> 00:27:32.500
continue to do that. I can't wait to dive into

00:27:32.500 --> 00:27:34.039
the playground a little bit further and see what's

00:27:34.039 --> 00:27:36.140
there because it is important that we protect

00:27:36.140 --> 00:27:38.039
our brands, but it's also important that we recognize.

00:27:38.599 --> 00:27:41.119
There's a massive wave that we can ride right

00:27:41.119 --> 00:27:43.180
now. And I don't think there's been a better

00:27:43.180 --> 00:27:45.880
opportunity for people to step up in life all

00:27:45.880 --> 00:27:47.940
over the world and say, you know what, I'm going

00:27:47.940 --> 00:27:49.900
to take full control over my destiny here. And

00:27:49.900 --> 00:27:51.839
I'm going to change my life with this and doing

00:27:51.839 --> 00:27:55.000
this with the best type of leaders possible who

00:27:55.000 --> 00:27:56.839
can teach you how to surf the wave, you know,

00:27:56.839 --> 00:27:59.299
like Kelly Slater style. Yeah, man, let's go.

00:27:59.359 --> 00:28:00.920
So James, thanks for being here. Vision Pros,

00:28:01.119 --> 00:28:03.660
we'll see you guys all on the next episode. Take

00:28:03.660 --> 00:28:05.180
care, everybody. Thank you for being here today.

00:28:05.380 --> 00:28:07.099
I'm really happy that you tuned in to Vision

00:28:07.099 --> 00:28:09.759
Pros Live. I'm looking forward to seeing your

00:28:09.759 --> 00:28:12.559
reactions as these episodes continue to move

00:28:12.559 --> 00:28:14.500
forward. This is going to get more and more fun.

00:28:14.539 --> 00:28:16.400
We'll have more and more engagement as well.

00:28:16.420 --> 00:28:18.339
We'll invite people to participate in the show.

00:28:18.460 --> 00:28:20.519
And thank you for giving us your time and attention.

00:28:20.799 --> 00:28:23.440
Have an excellent time building out your vision

00:28:23.440 --> 00:28:24.759
and becoming a Vision Pro yourself.
