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16:05 IEEE ist was, was aus der Elektrotechnik kommt, Institute of Electric Electronic

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25:36 had different journeys with education. Our oldest started college. It 26:12 We have a son now who's in college and I 26:59 college when the pandemic hit, and I saw I saw

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54:00 of my business.

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21:21 both of them. 27:18 all kinds of people, all kinds of relationships, all kinds 48:20 Yeah, you know a lot of a lot of black

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02:57 of gener? 02:56 Yeah. There's a bunch of 38:09 Okay. Kind of works out fine. But

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1:22:15 Ja, ich auch. Speaking of. Was kommt denn noch? 1:25:39 Also einmal bei Apple natürlich ein Stück Serie von Masters of the Air, 38:21 Und da haben wir dann erstmal ein Making-of gedreht für ihr und Tichy.

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37:53 It it's also hard it's also building into verticals that, let's be honest, like, are see the value in spending a bit of money to help them save a bunch of time. Right? Because Yeah. Your college student idea, it's like I sometimes selling to maybe broke college students isn't your best idea. Maybe it is, maybe it isn't. 02:12 Yeah. So in college, I had an internship at Apple, which I would say solidified a lot of the philosophies I have now, running a company. Can 04:13 Yes. That that's a great question. I should go I should go back to that. So we were actually buddies from college. Oh, cool.

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02:14 And so, and candidly, I had a really funny experience. I did a summer abroad, one summer and I was talking to some, some other American students. We were at lunch one day and I remember saying, hey, you know, next summer is the, is kind of the last summer of college, and what are you guys gonna do in the summer? And they all said, well, we're gonna move to New York City and do investment banking. And I I had no idea what that meant. 21:22 lot of sense. So and you can correct me if I'm wrong here, is you guys have been using kind of AI and machine learning for years well before the chat GPTs of the world kind of popped up and became, you know, trendy, I guess, for lack of a better term for 18:36 You know, Apple calls it machine learning because AI is scary to a lot of people. It's arguably the same thing or, like so where where are we at and kind of what is the state of kind of Fintech and banking leveraging some of this technology, and then how are you helping with that? Yeah.

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03:30 Yeah. So at university, I took, information systems. So I I was I just wanted to continue college, I I I I discovered at college programming. Although I I've been a programmer since I was 12, I never actually knew it was a thing. And then I went into college, and I learned about databases, and it was it was an actual proper job. 00:51 Oh, yeah. Sure. I I grew up in Manchester, which is in, the north of England in the UK. Manchester is famous for music, arts, and football or or soccer, as the Americans would say. Sure. 01:04 It was in in the early years, I I lived quite a poor neighborhood, but I, you know, I didn't I didn't really know exactly. I played a lot of football with, with my brothers, and, was my mom and dad. They were tough, hardworking, working class Northerners, parents, worked a few jobs to provide everything they could for the children. We had, like, a caravan on a holiday camp in the, near near the coast of Wales. So so every weekend, we would we would go to this campsite.

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37:01 So all the industries are going to, I think, have this bottom up cannibalization where, like, you lose the the less experienced and less skilled people. And I think it's also gonna make it more difficult for people out of college to get to get that experience that they need to be in the top of the pyramid. So I think it's it's both a pruning of the current workforce, but also I think it's a barrier for the future workforce, which is probably a bigger concern for me. 38:04 So you have to find a mentor that you can work in the same office at and learn from them. But that's difficult because that time is something which those mentors only have so much of. So they're gonna try and pick the best and the brightest to to work with. So it's difficult. You know, it used to be kind of like, you know, you go to to any college in the United States, you get your 4 year degree in computer science and you're guaranteed a, you know, a near 6 figure salary, you know, graduating. 23:08 The whole speculative tool of market aspect of it is kind of, you know, really tainted it for many people out there. Like, I would even argue that the datagrams that we have inside of XBEL where you have a, you know, data with a hash and that's stored is in a weird sort of way an NFT. It's a non fungible piece of data. It's not very

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46:03 a good rest of your day. Cool. Thank you 05:31 And I sort of wanted to be free of that. I wanted to sort of properly innovate and do it at a faster clip. So that was, know, there was a sense that of unfinished business or I was frustrated from doing something I wanted to do. So that was definitely one of the things. And and sorry, I should just explain. 21:37 Sure. So is that leveraging kind of machine learning and AI to do some of that, or what's the strategy to implement that?

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12:29 ist stark dahinter, das Department of Justice, das Justizministerium ist dahinter. 11:26 die sind da jetzt interessiert und haben das Center of Excellence für Ethical AI und so.

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24:52 Sagen wir mal, wir nennen das einfach Big Ball of Mud.

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00:18 through the parts of life that can be difficult to 00:26 discussions of different perspectives and life experiences, or going on 00:07 out kind of cry. I'm Rade Devlukiah and on my podcast,