WEBVTT

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Music.

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Dot io your podcast and youtube

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blog covering the german startup scene with news

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interviews and live events hello

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and welcome everybody as you hear him laughing in the background today i'll

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bring you another startup interview today with caston carsten is an entrepreneur

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um co-founder of Casablanca.ai. We'll talk about it soon.

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He has been an entrepreneur since age 16 and also is the business angel of the year 2024.

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So-called the golden nose because you can sniff pretty good investments.

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But we'll get to this afterwards because this is part one of a two-part recording

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because usually we get through something like 20, 25 questions.

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And I was preparing for this interview, I was getting to almost 50 questions

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and I was like, that may be a little bit long.

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Let's cut this into two recordings. So, Karsten, welcome.

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Yes. Hello. Now from Zanzibar. I'm currently on holiday, but I'm very happy

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to do this interview with you.

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Oh, very nice. You're doing a sundowner at the Africa house?

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No, not the Africa. I'm somewhere on the south coast of Zanzibar.

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And I want to go diving tomorrow. So I'm going to do the sundowner.

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If we finish in time, I'm going to do the sundowner on the jetty here, which is also very nice.

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And tomorrow morning, I'm going to do some diving and hopefully also see some dolphins there.

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For everybody who's not been there, Sanzibar is strongly recommended.

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I spent a part of my honeymoon there with my wife. Wow.

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Yes. We also may tell that this interview is in association with the Business

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Angel event back in 2024 with the German Business Angel Association Band.

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Let's dive right into the interview. You built your first company with 16.

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What did that early experience teach you about entrepreneurship that still applies today? Okay.

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I think the most important lesson for entrepreneurs is let's do it.

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So don't get blocked by whatever rules, obstacles, something that you might

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not have and it would be better if you had it.

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Of course, it's always better if you have more, but if you don't start, you don't start.

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And so the most important thing is once you have a really good idea, you just do it.

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Not quoting an international apparel client here.

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Now, some people, because we do know, we're usually pretty popular,

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8.35 and up, some people will get nostalgic because you sold a company to Atari

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back in the days, very popular.

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And a lot of people will get, oh, yeah, I remember those games with the joystick and all that stuff.

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Oh, yes. Can you tell us a little bit the story of selling Omicron Basics to Atari?

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Because it was a major milestone in your life, right?

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Yes, it was, yes. So the key thing was we invented or I invented new architecture

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for programming languages.

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And so principally new structure, how to build a programming language interpreter,

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and built this together with two friends.

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They wrote most of the code and we were 70 times faster than what atari had at the time,

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for their atari st computer series so that was a new processor from motorola

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with a 68 000 processor very fast processor that was also used by unit packet

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and some other um high-end manufacturers,

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and atari and also the apple mac and atari launched a computer for about 1500

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at the time that was like one-tenth of the price of the unit packet and one-fifth of the Mac price.

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And we launched a new programming language which made it faster than all the

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other machines with the 6,000 to 8,000 processor.

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And we first sold it separately and then Atari offered to buy it from us and

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we had hard discussions and they negotiated very well.

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And in the end, they bought it from

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us and they bundled it with all their machines at the time. Thank you.

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And the processing capacity one computer had there at the time you now have

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on a smartwatch, I assume.

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No, smartphones are far beyond. So when you take a look at… No, smartwatches.

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Smartwatches, yes. So probably, yes. So my comparison actually is when you take

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a look at the computer that brought the Apollo 11 to the moon and you compare it.

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So many people have an iPhone. Now, don't compare it with the iPhone.

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Compare it with the charger of the iPhone.

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And the processor built into the charger that controls the voltage is about

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the compute power of the Apollo 11 computer.

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Okay, I see, I see. Getting to the next milestone in your life,

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FactFinder, scale to 2,000 plus online shops.

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What was the single smartest strategic move you made that led to this success?

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And can you tell us a little bit about what FactFinder is or was?

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Okay, so you mean an additional strategic move just outside,

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just building by far the best search technology at the time.

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Because that was also very important, I think, because else it's difficult to

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sell something if you're a small company and nobody knows you.

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So what did we do? We built a search technology in the year 2000.

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I actually built the prototype with an intern.

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So the intern coded I did the algorithms in six

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weeks and the prototype showed

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that we can solve this the question of

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how to find things that are misspelled better than

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anybody else it was the prototype was very

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slow and we had to make a lot of additional inventions which

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were made mostly by my best programmer armed at

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the time to have it fast enough but

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I could show that we have an

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understanding if that was also ai it was just not machine learning and understanding

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how humans perceive similarity and how we can represent this in the computer

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so that was the new thing in fact finally in the year 2000 two years before

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google launched its did you mean and did you mean from google.

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Had a totally different approach they just asked millions and millions of users,

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did you mean this and then if they said yes they uh

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they they saved the synonym so they saved

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like this is in in fact that and this is in fact

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the other thing and they were very often wrong in the

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beginning but then they improved with all the users

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and that was a totally different approach and we solved it

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from the ground up we didn't have the resources we

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didn't have the millions of and billions of users um so

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we had to do it with ai and we did in the

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year 2000 and we solved the similarity problem with

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for misspelling things so um what was

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the most uh important strategic decision besides the

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very very good product um i think

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the most important thing was that i started uh not offering

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it for sale only but also for rent because we

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were a small company with seven people at the start i had

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some other products before but then i started fact finder and we put a lot of

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resources in that was almost killed us um and um and then people did not trust

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a small company so um if we said it costs up to 60 000 deutsche mark to buy this so that 30 000.

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Um many were still reluctant at the time because e-commerce

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was not as big as now and things were not so important as now and not so expensive

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as now and um so people were reluctant i said okay i can offer this for rent

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you can you can rent it instead of buy it and you pay only one and a half percent

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of this amount per month and um.

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So, of course, so four and a half percent per month, four and a half percent per month.

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So after 22 months, this pays off the full purchase price. So you should switch after a time.

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And we offer until half a year, we offer you to deduct 75% of the rent you have

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paid from the purchase price.

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And so people said, OK, I can decide this. I can risk that and we will test

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it. and we just throw it out and cancel it immediately if it doesn't run in

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practice, if it doesn't run well in practice.

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And so that reduced their threshold a lot and made us also trust us because

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they said, okay, if they are offering it for rent and not for purchase,

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that means that they believe that we will keep it.

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So it was in both directions. It was good for trust. And because it was so good, everybody kept it.

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And some purchased immediately after a month and some actually

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tended to not buy it because they

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were CEOs who did not own the company and so they said it's better for my bonus

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if this year I don't have the full purchase price on my expenses and just the

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rent and that's how I kind of invented ZAS but we didn't call it ZAS,

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we called it software rent at the time,

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that was quite new Because software as a service was not usual at the time.

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That was very, very uncommon.

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I see.

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You obviously do a lot with Omicron Basic and FactFinder.

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You had two huge successes early on. And you also do have 25 patents pending.

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I would be curious. Some pending, some still granted, yes. Ah, okay, okay.

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How do you get to all of them? And if you could just pick one that would change

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an entire industry, which one would it be?

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So actually, I have lots of ideas which just keep coming when I'm under the

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shower, going through the park, when I'm sleeping.

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I suddenly wake up at night, have to write something down, then fall asleep again.

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And sometimes I make a pattern out of it. not all of the ideas are worth a patent

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because some are just rubbish commercially,

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some are also not good ideas technically, and some have already,

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many have already been invented by other people and just not put into practice by them.

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So I have patents, for example, a granted patent for a new, for a new online,

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sorry, on-screen keyboard, which will make significantly,

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less miscorrections. So very often you type something, you mistype and you get

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a correction and the correction is actually worse than what you mistyped.

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And I have a granted patent to significantly improve this by some additional

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measurements which I do because I get more of the intent the user has rather

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than just the characters he types, he or she types.

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So that's a granted patent where I have not actually started developing yet

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because I don't have the time to build up a new company right now for that.

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I have other patents also for understanding if a picture is reality or if it

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has been manipulated, which also applies for pictures which are in printed magazines.

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So you can use this on printed pictures as well.

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And there are several other things where I have not built a company yet,

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but they also might do a lot of good for the world.

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So which is the one pattern that can change entire industries?

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I think most of my patterns don't go for one industry.

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So like when you look at Casablanca, it has the potential to disrupt video communication throughout the world.

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So in all industries, but of course, video communication is just a small part

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of the work, mostly of the work for internal meetings, sales, recruiting.

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But it's not for, for example, for production, not for fabrication.

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It's not for programming. It's not for all these things that produce the things.

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It's just for the communication. But of course, communication is also an important part of our lives.

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So Casablanca can disrupt video communication, but it will not be limited to one industry.

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Same goes for things like this better on-screen keyboard.

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It's also not for one industry, it's for many industries.

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I see. Given that you have so many ideas, built so many successful companies, when?

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When do you decide, now it's the time to implement one idea or step away from

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something and sell it or give it to another leadership team?

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That depends. So in some cases, I have an idea and suddenly I find somebody

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who would be the right person to implement that idea.

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And if I can get hold of her or him, then I start a new company with them.

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So that can be one point when I start.

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With Casablanca it was different, so I decided I sell FactFinder in order to start Casablanca.

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I wrote the patent, I registered the patent, I still had not sold a FactFinder yet.

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But I knew I needed to shift my attention to that project because it's a huge project.

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It's a huge work also to get it done. And I underestimated it,

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even though I thought it was a lot of work.

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I thought it would be like one year for five people. And it took us four years

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with five researchers plus me, so six people in total maybe.

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But the researchers are doing more of the new patents than I did.

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So in total, we are 20 now with Casablanca, so including people like marketing

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and administration people and so on.

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And besides the researchers we also have developers now because we wanted to

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implement the software and not only build the technology,

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so sometimes I have to dedicatedly start a new company and sometimes I can just

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pick the chance and do something so I just started the biggest German AI.

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What's the thing in English uh,

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I just started the biggest German AI directory called alles-ki.com.

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And I had this idea several months ago because I thought the ones I had seen

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in Germany were all so small and so difficult to find things.

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And also the American ones were not so easy to navigate and not so easy to find

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the solution you actually need.

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And with alles.ki with our german ai directory which is also usable in english actually,

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we have built everything on an ai stack and when i had the right people i started

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that was in october and i did some pre-tests before if my ideas work my ai ideas

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but but then i had the right people together.

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And we started with two people. Currently, there are three people in there.

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Besides me, I only put very little work into it. Mostly it's the other people who do it.

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So I mainly had the idea. But so sometimes it's this way. Sometimes it's the

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other way. It depends on the idea.

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Sorry for our audience. We have some very bad internet connections here.

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And actually, I can only understand all of the stuff Carson is saying after

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his file is uploaded. so not during the video.

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Really sorry about that. But my next question is, many startup founders focus on scaling fast.

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What's the biggest mistake they make when trying to scale quickly?

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So actually, I think there are some people who do it excellently.

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And I'm just a mediocre scaler, I would say.

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So I'm not the worst, but also by far not the best. There are people who really know how to do this.

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And so in terms of scaling, I would love to learn more.

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But some mistakes that people make at the very beginning is not being dedicated enough.

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Also, not starting quickly is often a mistake.

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If an idea is somewhere already somewhere in the air, and then you wait until

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you have more resources, more something, more something, then somebody else will just do it.

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So you can save the most time

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in the very beginning of an idea when you're when

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you're the first one to do it of course you will get people

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who copy you and that's there's

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you have to prepare for that and maybe the idea is

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just not working and somebody else does it much better but

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generally it's rather like start fast I

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think that's the that's a big mistake that people wait

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too long and until they start and then

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of course you have to be able to make mistakes and you have to

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understand that everything you do when you build when

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you scale a startup everything is an experiment and that

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means many many things will go wrong not just.

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Some things and it's not so error

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tolerant work in in german companies normally

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is seen as yes i accept that sometimes people also

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make mistakes this is not what we're talking about I'm

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talking about people do experiments every day

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and many of those experiments don't work so

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they don't just sometimes make mistakes they consequently make mistakes and

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you have to accept that many things go wrong so in marketing especially but

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also in lots of other things you just have to accept this what you don't have

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to accept and you shouldn't accept is mistakes out of negligence.

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Mistakes out of laziness and so on.

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But mistakes out of you think this is right, but you were wrong and thinking it's right.

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That's mistakes you have to learn to accept when scaling company,

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else you cannot scale it. So bottom line is do mistakes, but learn from them.

00:19:03.815 --> 00:19:08.195
Yes. But be prepared that many, many things go wrong when you start something.

00:19:09.915 --> 00:19:13.495
Aside from Casablanca if you

00:19:13.495 --> 00:19:17.495
were to launch a startup today what market or problem would you go after?

00:19:18.975 --> 00:19:20.095
So if I would,

00:19:21.331 --> 00:19:26.931
launch something just because I want to launch something, not because I have

00:19:26.931 --> 00:19:31.051
a specific idea, because if I have a specific idea, then I would do that.

00:19:31.591 --> 00:19:37.611
So, but generally I would build something on the basis of AI technology that

00:19:37.611 --> 00:19:43.791
is here and is going to be available easily for the next year. So like LLMs.

00:19:45.431 --> 00:19:48.591
And the problem is of course that everybody does this.

00:19:48.851 --> 00:19:52.931
So what you need to do, and I wrote this in an article also.

00:19:53.071 --> 00:19:56.691
What you need to do is you have to find some niche where you have more expertise

00:19:56.691 --> 00:20:01.891
or more knowledge, more data or something else that other people don't have

00:20:01.891 --> 00:20:05.211
or more market access where other people don't have this.

00:20:05.531 --> 00:20:09.471
So when you build something new on the basis of, let's say, a large bandwidth

00:20:09.471 --> 00:20:15.251
model or some other AI technology, it could also be like object identification or other things,

00:20:15.811 --> 00:20:20.771
but you build it on top of an AI technology that's easy to use and there are

00:20:20.771 --> 00:20:24.471
many AI technologies right now which are easy to use so they have APIs,

00:20:24.811 --> 00:20:28.551
it's easy access, you can use them without much difficulty,

00:20:30.131 --> 00:20:35.171
and then you just go for some niche where you have the better market access

00:20:35.171 --> 00:20:39.391
than anybody else or the better knowledge or some data which nobody else has

00:20:39.391 --> 00:20:43.851
and so on so what I yeah okay so this kind.

00:20:46.331 --> 00:20:50.831
Of company is not a world changing company in in all industries this is going

00:20:50.831 --> 00:20:52.631
to be something that changes a specific,

00:20:53.371 --> 00:20:57.451
industry or a specific topic probably because that's the thing where you have

00:20:57.451 --> 00:21:03.711
more knowledge so um if you are the best person for let's say um uh,

00:21:04.983 --> 00:21:08.363
spices or so then you build something built on

00:21:08.363 --> 00:21:11.223
your knowledge of spices that nobody else has and maybe

00:21:11.223 --> 00:21:15.883
your data on spices that nobody else has and your market access to spice suppliers

00:21:15.883 --> 00:21:22.523
and maybe spice users which nobody else has and spice could be a big market

00:21:22.523 --> 00:21:29.843
but it could also be something very specific like the pumps for fire sprinkling,

00:21:30.083 --> 00:21:36.643
for fire watering or something. So it could be something very specific.

00:21:37.423 --> 00:21:41.963
But you build it fast and you build it in your area where you have better market

00:21:41.963 --> 00:21:44.443
access, better knowledge than anybody else.

00:21:46.043 --> 00:21:49.563
And we just talked about mistakes, doing mistakes.

00:21:50.543 --> 00:21:58.123
And I was curious, looking back, what's the biggest bet you've made that didn't

00:21:58.123 --> 00:22:01.823
work out, and what did you learn from it? You're talking about learning from mistakes.

00:22:02.163 --> 00:22:05.763
Yeah, so there are probably thousands of small mistakes I made,

00:22:05.783 --> 00:22:08.803
and there are a few big ones.

00:22:09.063 --> 00:22:14.363
And I would say the one that cost me the most money, where I went in the wrong

00:22:14.363 --> 00:22:17.023
direction and stopped it completely.

00:22:17.023 --> 00:22:20.443
So not just did a turn or something is

00:22:20.443 --> 00:22:28.103
fact finder travel so the idea in the year 2011 was that we have sold fact finder

00:22:28.103 --> 00:22:32.903
at that time to i don't know like a thousand something e-commerce shops 53 of

00:22:32.903 --> 00:22:37.263
the top of the top 100 in germany and um,

00:22:37.959 --> 00:22:43.259
There were no travel sites on it.

00:22:43.999 --> 00:22:49.439
And the point is when you search for, let's say, an iPhone charger,

00:22:49.719 --> 00:22:54.639
you type in iPhone charger or maybe iPhone charger for iPhone at that time, 11 or something.

00:22:56.239 --> 00:23:05.039
And when you search for holiday and you type in Christmas holiday with my little daughter on the beach.

00:23:06.919 --> 00:23:09.779
Then what you

00:23:09.779 --> 00:23:15.859
would get with a standard keyword search is something where Christmas appears

00:23:15.859 --> 00:23:20.339
in the text daughter appears in the text also beach appears in the text and

00:23:20.339 --> 00:23:25.839
Christmas so the thing is keyword search brings you the wrong results because

00:23:25.839 --> 00:23:27.839
that also might be something like.

00:23:29.479 --> 00:23:32.979
Clothes on Christmas and the word Christmas is still in there,

00:23:33.619 --> 00:23:39.059
so you would not want that so what you need is you need understanding of the

00:23:39.059 --> 00:23:43.359
text and we produced the world first semantic search for the tourism industry

00:23:43.359 --> 00:23:47.879
which really worked so we could find those things so we thought okay so beach

00:23:47.879 --> 00:23:50.139
probably means swimming, swimming means warm,

00:23:50.359 --> 00:23:54.819
where is it warm over Christmas and we reasoned these things at the time so

00:23:54.819 --> 00:23:59.679
that was over 10 years ago and launched the product and the industry actually

00:23:59.679 --> 00:24:01.639
was enthusiastic about us So

00:24:01.639 --> 00:24:09.459
we got six customers within a few months who built it into their portals.

00:24:09.699 --> 00:24:12.959
And what happened was the end users did not use it.

00:24:13.679 --> 00:24:19.999
98% of the end users just typed in one word, one word like Mallorca or Caribbean or something.

00:24:20.879 --> 00:24:24.519
And they did not type in long sentence because at that time they had just been

00:24:24.519 --> 00:24:29.699
trained by Google that the best thing you can do for searching is type just one word.

00:24:30.979 --> 00:24:37.339
And so they didn't understand what it was about and none of our travel portals,

00:24:38.279 --> 00:24:41.079
really trained the users to change their behavior.

00:24:43.174 --> 00:24:49.354
So we were only participating in success, so things that were booked at a higher rate than normally.

00:24:50.214 --> 00:24:53.794
So if it was just as good as normal, we would not get anything.

00:24:54.454 --> 00:24:59.594
And in the tests, we made tests in the usability studio. People were much happier

00:24:59.594 --> 00:25:01.934
about our search, but after we explained it.

00:25:03.674 --> 00:25:07.874
And so in Effect Final Travel, the end users didn't use it.

00:25:07.914 --> 00:25:12.414
We got a number of prizes for the software. So we won like the innovation prize

00:25:12.414 --> 00:25:16.754
of Deutsche Börse for the most promising startup,

00:25:16.934 --> 00:25:24.914
which is going to be an IPO soon and so on.

00:25:25.314 --> 00:25:29.574
So we got a number of prizes for it, for the innovation we made,

00:25:29.614 --> 00:25:31.654
because it was really disruptive innovation again.

00:25:32.314 --> 00:25:38.694
But we made €50,000 revenue and we invested about €1 million within three years

00:25:38.694 --> 00:25:41.154
and didn't get the market running.

00:25:41.514 --> 00:25:46.334
So we tried with some press releases and the press people just published the

00:25:46.334 --> 00:25:51.174
funny stories but never published like, this is a game changer for you.

00:25:51.614 --> 00:25:56.434
And we didn't have the money to really do TV advertising or so else we might have changed it.

00:25:58.294 --> 00:26:04.934
So that was hard. and I stopped it after spending roughly $1 million in three years.

00:26:05.994 --> 00:26:13.274
Okay. Talked about stopping that funding, talked about big decision management decisions.

00:26:14.434 --> 00:26:18.554
What is your go-to decision-making?

00:26:18.814 --> 00:26:24.594
Is it gut instinct? Is it data? Or do you have a certain rigid framework where

00:26:24.594 --> 00:26:25.454
you make your decisions?

00:26:25.834 --> 00:26:35.154
Yeah, all of them. So I do have two kinds of frameworks and one sentence to remember.

00:26:35.414 --> 00:26:40.714
So if you do a big decision and you have thought about it for a while,

00:26:41.074 --> 00:26:49.714
then the one sentence is never without your brains, never against your gut.

00:26:50.254 --> 00:26:53.574
Yep. So that sounds reasonable. if you

00:26:53.574 --> 00:26:56.634
cannot find a plausible reason so like when you calculate

00:26:56.634 --> 00:26:59.254
it so that you should do it you shouldn't do

00:26:59.254 --> 00:27:02.454
it so you have to have some reasoning why it

00:27:02.454 --> 00:27:06.854
should be done and if it still feels bad even though you have the reason then

00:27:06.854 --> 00:27:13.914
don't do it because your the gut feeling takes and takes in a lot more um factors

00:27:13.914 --> 00:27:19.314
and you take the factors uh which you you can't you cannot reason over 20 factors,

00:27:19.614 --> 00:27:25.454
but you can actually take your gut feeling for 20 or 50 factors because it will

00:27:25.454 --> 00:27:26.754
take all this into account.

00:27:27.014 --> 00:27:32.234
We'll be back after a short ad break and then we'll talk about Casablanca AI

00:27:32.234 --> 00:27:36.154
technology, AI differentiation and your future vision.

00:27:41.686 --> 00:27:46.606
Okay, guys, thanks for sticking around. Welcome back. Now we are talking with

00:27:46.606 --> 00:27:48.466
the Business Angel of the Year 2024,

00:27:48.746 --> 00:27:56.046
Carsten Krauss, currently in the first of two interviews about his most exciting

00:27:56.046 --> 00:27:58.686
startup right now that he does himself.

00:27:58.686 --> 00:28:05.986
It's called Casablanca.ai and it claims to be 20 times more efficient than Microsoft or Nvidia.

00:28:06.306 --> 00:28:08.446
What does it do and what's the secret?

00:28:09.806 --> 00:28:14.166
Okay so what does it do is simple so when

00:28:14.166 --> 00:28:17.046
you do a video call normally don't look at each other you

00:28:17.046 --> 00:28:19.786
normally look somewhere down on the side and so

00:28:19.786 --> 00:28:22.706
on because you look at the other person on screen

00:28:22.706 --> 00:28:25.906
you want to see their reactions but the camera is

00:28:25.906 --> 00:28:30.746
somewhere else it's not behind their eyes their eyes where it should be so what

00:28:30.746 --> 00:28:34.826
we do is we put a virtual camera behind the eyes no hardware it's just software

00:28:34.826 --> 00:28:38.846
we put a virtual camera behind the eyes of the person you're talking to and

00:28:38.846 --> 00:28:45.506
our software produces the picture in a way as if the camera would look from that perspective.

00:28:46.526 --> 00:28:50.966
And what's interesting for me, it also enables you to do some eye tracking,

00:28:51.006 --> 00:28:56.386
which you can also do with other competitors always to what's the camera.

00:28:56.686 --> 00:29:01.866
So for recording, it's pretty interesting, but we have to admit it's made it

00:29:01.866 --> 00:29:04.346
a little bit more for saving.

00:29:05.466 --> 00:29:08.606
Bandwidth so therefore it's not for a

00:29:08.606 --> 00:29:12.386
high for for high resolution recordings

00:29:12.386 --> 00:29:20.706
like we're doing now it's not made for that yet okay yes so generally it's the

00:29:20.706 --> 00:29:26.266
the Casablanca model is a we need to keep the model small in order to make it

00:29:26.266 --> 00:29:32.346
fast enough that you can use it without an extra GPU on a normal current computer.

00:29:32.586 --> 00:29:40.526
So an Apple M1 or a Pentium starting from end of 2022, beginning of 2023 is enough.

00:29:41.526 --> 00:29:47.586
Or an AMD from that time also. So that's why we need to make it small.

00:29:47.986 --> 00:29:56.306
And that means the resolution is not good enough for a high-quality video.

00:29:56.566 --> 00:29:59.726
But in video calls, you always have bad resolution anyway.

00:29:59.746 --> 00:30:03.186
Way so you don't see the difference so when

00:30:03.186 --> 00:30:05.946
when you do a normal video call Casablanca is good

00:30:05.946 --> 00:30:09.286
enough and it's fast enough to run on a normal computer so

00:30:09.286 --> 00:30:12.566
why why are we so fast it's not only because

00:30:12.566 --> 00:30:20.406
we have we we save time on resolution so it's also because we built a very very

00:30:20.406 --> 00:30:25.886
efficient model and we could do that because and we build a much smaller model

00:30:25.886 --> 00:30:30.826
than others do and we could build a smaller model because our model understands the faces better.

00:30:31.703 --> 00:30:34.523
And when you have more understanding, you can compress better.

00:30:34.723 --> 00:30:39.883
So if you have no knowledge of a language,

00:30:40.623 --> 00:30:44.603
then you have just to listen and you have to record the audio and you have to

00:30:44.603 --> 00:30:48.423
remember the audio by heart if you want to repeat it.

00:30:49.043 --> 00:30:52.103
That's very hard. If you understand the language,

00:30:52.303 --> 00:30:57.323
you can compress the audio to words and that's much less information bits you

00:30:57.323 --> 00:31:04.523
have to put and you can just put much longer texts into the same kind of sequence.

00:31:04.663 --> 00:31:08.203
And our model understands faces better than any other model.

00:31:08.443 --> 00:31:15.983
And that's mainly because we have built a self-supervised approach and we have

00:31:15.983 --> 00:31:20.763
built a new way how to build face models.

00:31:21.383 --> 00:31:27.843
And thus we can make a very small model and this very small model also allows us to make it very fast.

00:31:28.763 --> 00:31:32.503
And we will also launch higher resolution models, which will also be faster

00:31:32.503 --> 00:31:33.943
than all other high resolution models.

00:31:34.103 --> 00:31:39.283
But they will probably require a GPU if you want to use them on your personal computer.

00:31:46.883 --> 00:31:53.883
Your AI technology also enables a realistic 3D phase reconstruction using minimal

00:31:53.883 --> 00:31:56.163
data. How does this work?

00:31:56.723 --> 00:32:00.203
So that's part of our small phase model. So it's a number of new inventions.

00:32:00.423 --> 00:32:04.663
So we also made a new GAN, which doesn't need perceptual loss,

00:32:04.743 --> 00:32:09.763
which makes it faster and at the same time better in quality, actually.

00:32:10.803 --> 00:32:14.283
And we made a lot of inventions and registered a number of patents.

00:32:14.463 --> 00:32:16.803
The first one has been granted. The others are still pending.

00:32:18.723 --> 00:32:25.223
However, so to sum this up, what we do is we can compress a video picture of

00:32:25.223 --> 00:32:32.503
a person. So all their expressions, everything they do in a vector of less than 300,000.

00:32:32.927 --> 00:32:41.047
Data points so 300 dimensions of the vector and so if we have 25 of these vectors per second.

00:32:41.747 --> 00:32:45.687
That would be seven and a half thousand data points and that's

00:32:45.687 --> 00:32:48.427
fast enough for making a video call with this

00:32:48.427 --> 00:32:51.707
compressed data over an

00:32:51.707 --> 00:32:55.727
edge communication so there's a 2g communication that

00:32:55.727 --> 00:32:58.607
will be it will be fast enough for that if both

00:32:58.607 --> 00:33:01.627
sides have casablanca and it would be a direct

00:33:01.627 --> 00:33:04.567
communication so it's currently not integrated into

00:33:04.567 --> 00:33:07.427
this kind of communication into zoom or teams or anyone

00:33:07.427 --> 00:33:10.747
but if they would integrate it they could enable video

00:33:10.747 --> 00:33:15.587
calls also in areas like where I am now where the internet connection is not

00:33:15.587 --> 00:33:19.307
so good or Germany where the internet connection is also not very good outside

00:33:19.307 --> 00:33:24.867
the big cities so very often you only have edge connection and you always say

00:33:24.867 --> 00:33:28.147
oh I can't do anything on the internet but now with So Casablanca,

00:33:28.147 --> 00:33:32.947
if both sides had this technology and it would be built into video communication,

00:33:33.227 --> 00:33:36.907
you could do video calls even with only this batch connection.

00:33:37.127 --> 00:33:42.667
Every major tech company and non-tech company is investing in AI,

00:33:42.907 --> 00:33:46.107
especially talking about AI-driven video communications.

00:33:46.467 --> 00:33:48.907
What makes Casablanca stand out there?

00:33:49.427 --> 00:33:55.547
Well, the thing we are solving, we solve best in the world. So making authentic

00:33:55.547 --> 00:33:59.567
communication with a full face turning and eyes turning.

00:33:59.827 --> 00:34:04.927
So all the competitors currently can only correct the eyes, but Casablanca corrects

00:34:04.927 --> 00:34:10.207
the full face so that you have an authentic communication as if the camera would

00:34:10.207 --> 00:34:13.007
be behind the eyes of the person you're talking to on screen.

00:34:14.067 --> 00:34:19.647
So we're the only ones who can do this at the moment. That's what we do better.

00:34:19.647 --> 00:34:25.127
But then how do we do it better by a lot of inventions again some have been

00:34:25.127 --> 00:34:29.747
made by me but most have been done by my by my team of researchers and that's

00:34:29.747 --> 00:34:31.007
actually one of my talents,

00:34:31.527 --> 00:34:34.327
so i start with an idea and then i find

00:34:34.327 --> 00:34:37.107
people who understand the details even better

00:34:37.107 --> 00:34:39.827
than me and i can understand if they

00:34:39.827 --> 00:34:42.887
do or they can't because mostly the ceo

00:34:42.887 --> 00:34:48.807
does not understand enough technology to to realize if the person who claims

00:34:48.807 --> 00:34:55.907
to be an ai expert is just okay with ai or really good and i'm one of the few

00:34:55.907 --> 00:34:59.987
ceos who can do that and i've done this all my life so all i've,

00:35:00.727 --> 00:35:03.427
mostly i have made some part of the invention myself,

00:35:04.166 --> 00:35:10.366
uh where you needed a lot of things to come in together but for um that that

00:35:10.366 --> 00:35:15.866
does not complete the product so also in fact finder as i told you the um we

00:35:15.866 --> 00:35:17.726
started out with this very slow,

00:35:18.406 --> 00:35:24.186
um implementation which already showed that the idea of how to how to represent

00:35:24.186 --> 00:35:29.766
similarity in search is really understood well but in order to get the speed

00:35:29.766 --> 00:35:33.366
somebody else had to do it and there had to be a lot of additional inventions.

00:35:33.606 --> 00:35:39.446
And I find those people who make the details, who it's not a small detail,

00:35:39.606 --> 00:35:41.706
it's an important detail. Speed is essential.

00:35:42.506 --> 00:35:46.986
And I find those people and I can decide if they are really so good or not.

00:35:47.366 --> 00:35:51.166
And I bring them together and I make them work together and I make them work

00:35:51.166 --> 00:35:53.626
with me also, but also work together very well.

00:35:54.286 --> 00:35:56.866
So I think that's my secret sauce here.

00:35:57.866 --> 00:35:59.966
I've done this all my life in all my companies.

00:36:03.566 --> 00:36:10.526
Apple's FaceTime now offers an eye-powered gaze correction. Why is Casablanca a better solution here?

00:36:11.086 --> 00:36:14.666
As far as I know, Apple only corrects the eyes again.

00:36:15.126 --> 00:36:20.526
So that means it works well for a small angle, if you have a very small angle.

00:36:20.666 --> 00:36:24.426
So you're like on a smartphone, normally you're like this far away,

00:36:24.646 --> 00:36:32.586
and you talk, and then the angle between the eyes and the,

00:36:33.486 --> 00:36:39.426
And the camera is very small. And if you correct only by a small angle, just the eyes.

00:36:39.606 --> 00:36:41.886
So I'm trying to simulate this now.

00:36:42.286 --> 00:36:46.566
So if you do a small angle, it looks good. If you do a big angle,

00:36:46.726 --> 00:36:49.166
it looks crazy if you just correct the eyes.

00:36:49.526 --> 00:36:55.966
And so it looks like this is a different emotion you're showing. Yes, yeah.

00:36:56.406 --> 00:36:59.486
Yeah, so yeah, maybe that. But even if they don't appear on your head,

00:36:59.626 --> 00:37:05.826
if they're just correct, But just looking at somebody from the side is like,

00:37:06.126 --> 00:37:11.966
oh, he's giving me a side-eye view, so what does he want to say? Is something wrong?

00:37:12.746 --> 00:37:18.766
Is he not believing me? That's also a mimical expression when you look from

00:37:18.766 --> 00:37:21.066
the side. And you don't want this.

00:37:22.246 --> 00:37:25.426
You want the true mimical expression. That's the essence of communication.

00:37:25.426 --> 00:37:31.266
We humans are so fine in reading all the small movements of the mouth, of the eyes.

00:37:31.506 --> 00:37:38.566
If you move the lower eyelid half a millimeter down, people say, oh, now he's skeptical.

00:37:39.566 --> 00:37:44.806
Or he's ironic when you move it further down. So there are some things which

00:37:44.806 --> 00:37:51.526
are very small mimic changes, making an expression.

00:37:51.846 --> 00:37:56.546
And you want to avoid this. And Casablanca changes or corrects the full face

00:37:56.546 --> 00:38:00.706
so that you don't have this involuntary eye expressions.

00:38:00.866 --> 00:38:04.826
And it works well when you just correct the eyes if the angle is really small

00:38:04.826 --> 00:38:08.626
and it does not work well when the angle is bigger, like when you have an additional

00:38:08.626 --> 00:38:10.826
screen or even just a big notebook screen.

00:38:12.746 --> 00:38:19.606
I was wondering, seeing that you put so much thought, so much energy and so

00:38:19.606 --> 00:38:24.646
much future potential in this company. What is your ultimate vision for Casablanca AI?

00:38:24.966 --> 00:38:28.226
Is it an IPO, an acquisition, or a long-term standalone company?

00:38:29.084 --> 00:38:34.084
So the first vision is like in five years, nobody will remember how video calls

00:38:34.084 --> 00:38:37.804
were before when you had no eye contact.

00:38:38.484 --> 00:38:43.704
So I want to improve the world here. So, I mean, people will probably remember,

00:38:43.744 --> 00:38:46.424
but they say, oh, yes, long ago it wasn't like this.

00:38:49.744 --> 00:38:56.684
And so that's my first vision. And then I think I will go with what is a good

00:38:56.684 --> 00:39:03.924
offer. So at a certain size of the company, I think other people can run it better than me.

00:39:06.104 --> 00:39:11.384
And so right now I'm open to everything, but we are currently in a seed phase.

00:39:11.404 --> 00:39:12.944
So we're taking up angel investors.

00:39:13.264 --> 00:39:16.064
So far, I invested about two and a half million euros myself.

00:39:17.224 --> 00:39:22.824
And now we're currently gathering one million for the seed phase,

00:39:22.904 --> 00:39:27.224
but we also want very good angels in there. so people who can also advise us

00:39:27.224 --> 00:39:30.144
and also open us some doors and so on.

00:39:31.184 --> 00:39:36.504
And then probably like around the end of the year or so, we will go into a VC phase.

00:39:36.604 --> 00:39:41.484
And then probably it's more the VC who decides where we are going because they

00:39:41.484 --> 00:39:45.764
know better how to make the most money-wise out of it. It could be all of them.

00:39:47.584 --> 00:39:53.464
Anybody who's now interested about working with Keterblanke.ai or investing

00:39:53.464 --> 00:39:56.944
into it, they can reach out to you on your LinkedIn profile,

00:39:57.164 --> 00:39:58.924
which we link down here in the show notes?

00:39:59.844 --> 00:40:03.164
Yes, please do. So we already have some people we're discussing with now,

00:40:03.204 --> 00:40:06.604
so it will not be endless the time we will have.

00:40:06.764 --> 00:40:11.944
But we are also very interested to have international people because internationalization

00:40:11.944 --> 00:40:17.444
is one of the topics I personally would love to have somebody who advises us

00:40:17.444 --> 00:40:19.984
on this much better than I know myself.

00:40:21.364 --> 00:40:25.284
I see. Awesome. Closing words to our audience.

00:40:25.564 --> 00:40:29.624
What questions do you think we missed? Let us know in the comments down here.

00:40:30.424 --> 00:40:34.004
Karsen, thank you very much for the first interview. For everybody,

00:40:34.324 --> 00:40:38.144
it will be one of the next interviews published.

00:40:38.464 --> 00:40:41.964
Your interview number two. And we only take like five minutes break.

00:40:47.384 --> 00:40:56.564
That's all, folks. Find more news, streams, events, and interviews at www.startuprad.io.

00:40:56.904 --> 00:40:59.064
Remember, sharing is caring.

00:40:59.760 --> 00:41:12.646
Music.

