Welcome to Impact Quantum where we decode the quantum universe

one qubit at a time. In this episode, Frank and

Candice sit down with Anna White, president of Daikon,

and the innovative mind behind Hito Match. Forget

what you think you know about dating apps. This one's powered by quantum

algorithms and AI hybrids that predict human

behavior. Yes. Really. From matchmaking

to medical tech, Anna takes us on a journey into how

quantum computing isn't just for labs or physicists

anymore. It's here. It's real, and it's solving problems

in ways classical computing simply can't. If you've ever

wondered what happens when you combine a light bulb, a candle,

and a multiverse, you're in for a treat. Now here's some

dubstep.

Hello, and welcome back to Impact Quantum, the podcast where we explore the emergent

fields of quantum computing and talk about

the upcoming and burgeoning quantum ecosystem.

And really encourage those who are curious about quantum computing to really start

diving in now because this really is gonna be a major industry that will

rival, the semiconductor industry and the software

boom, that followed that. Candace, I still have to

work on that intro. But let me introduce my co host,

Candace Guhulle, who is probably the most quantum curious person I know.

I think she got into quantum computing because somehow we were talking about

factoring primes and security. And then she's like, you should

really restart that podcast you had. And I was like, I don't know.

And then she's very persistent, and here we are. Hi.

Thank you for I love the introduction. I'll take it. It's great.

It's great. No. Look. I'm really loving what we're doing and who we're talking

to. It's just it's so enlightening. And every

conversation we have, we find out that at least

I find out I don't know nearly enough, and I need to know more, and

there's so much more to find out. It's just so exciting. Oh, I love it.

I love it. Today, we're lucky enough to meet, with Anna

White. She is the president of

Daikon, and also, HidoMatch.

And we had a pre conversation with her, and what they are doing at

Hedo Match is oh my gosh. It is so

exciting that we keep on trying not to talk about it when we talk to

other people because, like, we feel like we're, like, in, like, the secret in, like,

in, like, the secret club. Like, it's really, really it's it's great. So,

Anna, so thank you so much for joining us today. Thank you.

Yes. I mean, I think, most of the time when we're

talking with people, nobody really understands the different

type of ways that you can utilize quantum. We just

decided to do it, a very, very different way than

everybody else. So the biggest

What's the difference? Sorry. I cut you off. But, like, what how how what's your

approach? So I think the biggest thing is there's a

few different companies that are working on building out algorithms

on quantum. The different approach we chose to take

was to deploy the application first and then

build out the algorithms. But since we already have that app built

out, we're able to input the data while we're building out the

algorithms, which nobody else is really doing it that way.

So we have a few different algorithms that we've already built out and

they are, quantum algorithms and currently running on

quantum hardware. And the first one is a

quantum and AI hybrid. And we use that

to be able to predict human behavior. And,

so we have a personality test on the app, and we use

that based on, the personality, the interest.

That's how we're offering the matches. So Interesting.

Yes. So that was the first one, and that is, using

different types of onsets and gates. So it's definitely, you

know, bridging both of those technologies of, quantum machine

learning. And that one still is able to operate

on its own compared to AI where you have to keep training

it. This model is is made to be able to train itself and

be able to give the right results every time. Interesting.

So you mentioned you mentioned you you said a lot of things, and I'm like,

I wanna unpack them all because that was a very Yeah.

So one, it sounds like you're a quantum software company.

Yes. That okay. I have a lot of questions about, like, what does quantum

software development look like? Right? Because obviously, there's different types of gates. There's a different

mentality in terms of so one, how do you recruit software engineers?

And if there's anyone in the audience that's like, hey. I'm already a software engineer

or AI engineer. I wanna get into this quantum

space. Those are these are two very small questions

with big answers. But, like, what what have you found has been the major

difference between, like, traditional, software engineering and

quantum based ones. And you you mentioned kind of the underlying gates of

stuff. Mhmm. And I don't even know if kids learn that in comp

sci anymore, honestly. Like, so I'm old enough

I'm old enough that my first computer was a Commodore sixty four. Right? And, when

I went to comp sci, one of the earlier classes was talking about the different

types of gates that are actually embedded in the electronics.

And when I was reading up on quantum

systems, like, there's a whole new families of gates that quantum computing kind of

opens up. So why don't we why don't we go into that? Like, how did

you what do you found has been the big difference between traditional

software engineering and quantum software engineering? Mhmm.

So I would say the biggest thing is, so our CEO,

she's, like, pretty much the main brains of the company.

It was really her initiative a couple years ago

where she wanted to be able to create an algorithm that was like she

wanted to pretty much dissect TikTok's algorithm and figure out how are

they running it that way. And so she was working with somebody that worked for

ByteDance, and that was the biggest thing. It seemed like they were using something

very similar to Quantum at that time. So, I mean, even though

Quantum is hitting now, it seems like they were already kind of somewhat

building out a quantum algorithm at that time. And so she wanted to be

able to build something similar. But I would say based on, like,

the the engineers we've recruited and have been

working with, I think you definitely have to have a balance of both.

You have to have, the background of machine learning,

of of of, software development, all of that.

But the biggest thing is you have to have a balance of science,

like somewhat. You have to really have a deep understanding of science

because the the the thing that made it difficult for people to be

able to use quantum right now or even understand the concept of

it is we went into, classical computing first

instead of, like, you know, which Albert Einstein back in the day was

like, seems like I have a theory here, you know, and and

was was going there, but it never developed,

until now. But because we went into classical,

quantum just seems so theory based, and people can't comprehend that

you can actually utilize it. So I think that was the biggest,

like, difference. Some people that are stuck in the classical and

and stuck on that, like, AI, focus, it's

very hard for them to wrap their brain around the concept of

quantum. And and we've had had that, like, kind of back and forth.

So I like to to use, like, this analogy where, I

kinda consider quantum as, like, a light bulb where it

illuminates automatically. You just turn on the switch. But

AI is somewhat of a like a candle. You have to light it, but

then eventually it burns out, and it can't operate by itself. You

have to keep lighting it. So I think that was the biggest, like,

difference we were trying to explain, but we definitely try

to break through in the AI competitive battleground right now.

Interesting. And and That's gonna be an awesome clip, I just wanna say, like,

right now, I love I love the analogy. Thank you so much.

I'm I'm such a visual learner, that

I I know other people out there really appreciated that too. So I'm sorry. I'm

sorry, Frank. No. I think that's that's a great analogy because I think it also

encapsulate kinda like AI. Right? Like, AI always needs fresh data and to

pump into it for it to do anything, which would be analogous to air. Whereas

with traditional coding systems, you flip a switch. Like and also

traditional computers are, you know, the electricity flows or it doesn't flow. Right? There's

no ambiguity. Right? What's interesting about qubits is that it could be in

any state in between there. And, like, I

remember I like to fancy myself a smart guy.

But, you know, I remember when I first heard of when I first heard of

quantum computing, I'm like, yeah, yeah, that's cute and all. But then when I really

first, like, got it, like a light bulb moment, I remember I was

at an internal Microsoft conference. And I was

an AI conference of all things. And they were talking about hardware, and I'm like,

okay. I get it. Like, I need GPUs, more GPUs. And when those run

out, I just get more GPUs. But,

the presenter, she was like, you know, we could build and use all the GPUs

we want, but, you know, we are hitting a wall in

terms of how we design these, classical systems.

And, you know, quantum computing offers us an opportunity to kinda, like, really

exponentially boost this, because if Moore's law, you

know, will eventually kind of not be a thing.

And I was fascinated with it. And that night, I went back to the hotel,

and I installed the QDK quantum developer kit, like Q and

all that. And then I sat down in front of it. I'm like, okay. Now

what? Like and then I started looking at, like, well, wait. There's all these new

gates. And the last time I really thought deeply

about logic gates and the actual silicon, I mean, Kurt Cobain was still

alive. I think Tupac was still alive too. Right? Like, so,

that was a very, like, you know, jarring moment when I realized, like, you know,

again, I'm lifelong software engineer turned data

scientist. And I even I'm like, I had that, like,

okay. Now what moment? You know? Have you seen others

have that, or am I kind of, like, the special one in the

I think, like, everybody kind of hit that moment. Like, I

think, even for me, honestly, like, I'm a business

person. You know? And when I joined originally,

my, the CEO was just like, yeah. I'm creating a dating app.

I'm like, that's so cool. Like, I joined, you know,

to back her up as far as, like, the business aspect. But then,

like, there was moments where, you know, we were how to, you know, hit

because we originally started with Qiskit, and then we ended up going to

Penny Lane to write the language first, because we kept hitting

walls and there's so much limited information that you have to

try and puzzle together. And at one point, they gave

me an assignment to research colonels, and I'm like,

what am I supposed to do? Like military? Like,

yeah. Yeah. Popcorn kernels. Yeah. Popcorn kernels. Similar

to that. And, so I had to figure out,

you know, pretty much how to, turn the classical

data into, quantum state. And I remember,

like, I was like, how am I supposed to research this?

Instead, I ended up networking with millions of different people.

So I think, you know, the same situation you were in is the same

situation all of the quantum world is in. You know? Because everybody

is trying to figure out certain pieces of it. I just think, like, you know,

based on that, accomplishment we made with our first algorithm

and then our second one, the second one is the first of its kind. Nobody

has done it yet. You know? The we we know of one team that

was working on it in China, but they were working on,

working on it with 15 engineers. And we did it with

two. Interesting. And

No. That's fascinating. Like and and I think also one of the big

hypothesis hypothesis,

I need coffee today, like, really bad, Was

when we rebranded the show, we kinda rebooted the show. It was like to

you know, Candice and I had this conversation. I was like, you know, the quantum

world is gonna need marketers. It's gonna need business people. It's gonna need,

you know, it's gonna need not just quantum physicists. Because I think

one of the consistent theme we had when we started talking to people about restarting

the show was there's already enough quantum physicists in the field.

Yes. Right? What we need now are the

software developers, the marketers, the

PMs, the the, you know, the business line folks that, you

know, to really build it out as an industry. And I think,

that that is where I think for the majority of the population, you don't have

to study quantum physics if you don't want to. Don't be intimidated by the word

quantum. Right? Just get into it. Right? It's gonna be an

adjustment, but anything, you know, like, if you if

you go into a pool in the summer, right, like, you know, the first minute

or two, you're in the water, it's super cold, but then it's very enjoyable. And

I think any any endeavor is gonna be like that, whether it's,

you know, swimming or just even getting in the code and alone for a lot

of people has been was an adjustment. So, you know,

embrace that adjustment adjustment because it probably means you're onto something

that's gonna make you grow. Because it it's true. It's like how

does the business side, the marketing side, you know, we have to be able to

understand it so that we can sell it. We can communicate,

you know, what the unique, the the unique selling, you

know, points are about it, understanding,

you know, what companies need to be involved

and also to be understand what companies really don't need to be involved

because there are quite a few small, you

know, small type companies that don't have to bother.

And, you know, now, yes, do they have to bother in terms of, like, getting

involved with getting encryption from quantum so that their data is safe?

Yes. But do they have to have all their systems work, you know,

on a on a hybrid system? No. But, yeah,

like, how do you how do you explain, you know,

to the marketer to say, you know, this is what, like,

what you're doing with your dating app? And you're getting

people to try it out because you're gathering

additional data to to then go to the next step. So what's the next step

for you guys after you're gathering this information?

So as of right now, kinda where we are at is,

we were kinda holding off on marketing anything, you know, big,

up until we were able to somewhat get a lot of the,

underlining things that we were still developing done. I

think after we created the, last, well,

we're still working on the, very last algorithm,

but, the one that we just created was the facial

recognition on a cupel optimization model. And,

I think after we did that, that's when we started looking for funding.

And, we did, I will go

ahead and announce it because we're getting ready to make that announcement, but we did

hit that pre seed. And, I gotta I gotta say, like, it was

challenging. It was really challenging because, you

know, a lot of people hear of, AI

and a lot of the investors, they just can't comprehend

this, and it just seems like it's so far away. It's just the

fact that we're so small that we couldn't say otherwise, that you can

utilize it, and it is a useful technology. And it is right now.

It's not later. But, you know, there was so much misinformation in

the news that was stating that it's not gonna be ready for five, ten years,

and that's false. You know, it is. But, you know,

I think, the biggest thing for us is is our approach, why we

did it. We get the biggest question, like, well, you couldn't you

do that on a classical computer? You know? And they can't

understand why we used quantum to do it. But the thing is is,

it's the actual method of it that we were utilizing

and learning and building out. And that's the,

biggest discovery that we were able to make because we were able

and I was talking with Candace about that, is we were able to break up

that data into smaller pieces to be able to fit into

a, application. Most of the graph sizes,

you can't use on a classical computer. That's, like, the biggest thing that tells you

that it's a quantum algorithm because that graph can't be used. Because of

the size. It can't be used on a classical computer. So I think,

you know, now we're ready to start that marketing process and start

getting us out there. We also have a couple other things which we can't talk

about, but pretty big things. So are you running

on I'm sorry. I cut you off. No. You're fine. Are you running on

actual quantum hardware, or or is this a quantum inspired

algorithms? Because that's also another thing. So you're going straight to the metal.

Yeah. No. We are currently on quantum hardware. We,

currently are utilizing D Wave, but we're also looking

at other options as far as, like, you know, what can what else,

hardware companies can do pretty much. And that's

what makes, and that's a big difference between AI

writing and, quantum or classical and quantum.

Because when you write out that code for quantum, it's actually

easily trans trans transport, because, you know, D

Wave is on, an a link. IBM is gates. You know,

everybody has their different models. But because of the, the way

you write out the quantum coding, it's actually pretty easy to translate

that language into another system. So the

software layer is pretty agnostic to the underlying Yeah.

Like hardware mechanism because we were talking to somebody who's into photonics and then there's

different like, there's at least four different ways to

work to build a quantum computer system out, which I also think is a as

a major mental shift for a lot of people who grew who are in the

tech industry today. Right? Because it's it's literally in the name, electronics.

Right? You're basically you have, for lack of a better

term, like, little electrons running through a maze you built, like little mice.

And they either flow or they they're either moving or they're not moving. Right?

But with quantum systems, it's not just electrons. Right? There's

you mentioned annealing. There's, photonics. There was another one you

mentioned. And I mean, there's at least five different

contenders now, maybe more. But, and each one

of them has their strengths as it turns out, and each one of them has

their weaknesses. But I find it interesting, and I think that's actually a good news

for a lot of quantum software developers is

the software layer is pretty agnostic about it, it seems like.

Yeah. We were, actually surprised by that. That

was the biggest thing because we started you know, we're

we're small. And so for us to just try and, you know,

get partnerships, it's not as easy as a lot of the other companies that

are, you know, easily getting the partnerships. We have to fight for it.

And, you know, we have to kinda keep proving ourselves. And to be able to

do that, we had to keep rewriting the language to match their

system. So, you know, now I would say, you know, from two

years ago, there wasn't that many options. But I think a lot of the hardware

companies right now are being very diligent on

really getting this technology to be useful for all of

us. We just, you know, decided to use it in a mainstream

environment because that's where the people that don't believe in it,

that's where we need to hit. And so when those kind of people are starting

to use it and can see the type of results, like, for an example, there's

only a twelve percent success rate and a thirteen billion dollar industry in

dating. Wow. That's pretty bad.

That's pretty bad. Oh, and seventy nine percent of those users,

they're burnt out. They're ready to walk away because a lot of those are

using, you know, AI algorithms and that that, you

know, that pairing is not working. You know, that

algorithm is not giving them the best results that they could

potentially get. So, you know, once you you were able

to get into a mainstream area like this, I think you that's when

you get the people and they're that's what hypes that industry.

Absolutely. And there's plenty of plenty of upside for optimization if you're at

12%. Right? Even if you double it and it's

only 24% or 25%, that's you've doubled it.

Like, it's not seems like there could there's a a enormous

opportunity there. I would not have guessed that. Yeah. Well, that's

why we started with that. So our next projects are,

we're going into a traveling app. That's our next very next project.

But then we're going into medical. That's when we wanna

hit the most important fields. I just don't think that,

and this is just the way that we decide to approach it. We don't think

that building out an algorithm and saying it's useful for meta

medicine. I think you need to be very careful about that. So

we chose to build out this algorithm, keep building it and make

it a very strong algorithm, do a different types of way,

building out different data, but then eventually mastering

that algorithm to be 100% certain that it

can help this field. I think, otherwise, I it's

dangerous to me. I just think it's dangerous. No. I I I

like your technique. I mean, I I understand how you're setting up your

strategy because once you dip your toe into something truly medical,

which ideally is there to help a lot of people, you wanna you wanna make

sure that you have everything buttoned up. You know? People's lives are

literally on the line. Like, it Right. Exactly. So that that

sounds legitimately that sounds totally legitimate to me. So that's

exciting. That's exciting. Yeah. And they say that, you know,

quantum does will will have that ability to be able

to unlock so much, benefits for people, things

that we couldn't solve on a classical computer, which, you know,

on our, on our, facial recognition, we

were actually running one test that, we we

ran the same test on a classical, and it took

twenty four hours for us to be able to complete. And then we ran it

on the quantum, and it took us point zero zero eight seconds to be able

to complete. Oh my gosh. So when you start doing that into

encryption, which we're working on our encryption, algorithm

now to to be able to secure the data on the app. That's our very

last one that we're working on. Well, we've got a few, but that's the one

we're working on for right now. Yeah. That's

where where it's gonna be a little bit tricky, and I think that's why a

lot of the, financial institutes are really going

after quantum right now. I don't know. Y'all saw the news about JPMorgan.

That was pretty huge. Yeah. So I wanna talk to you a little bit about

that. Right? I felt that that kinda came a lot of left field.

I did too. But I felt that they really wanted

to kind of state their their dominance early on. Right?

But, yeah, I felt that that was really out of left field, but vitally

important. So go ahead. I'm sorry, Frank. No. A

%. Like and and when one of

the one of the things that kind of, like, maybe I

also kind of saw it from left field, but I was also looking in that

direction because there was a number of, you know, Gartner or

whatever awards for, you know, most quantum ready companies,

blah blah blah blah blah. Right? Was all these

banks. And I just assumed is, you know,

for protection against, post quantum, you know,

quantum, you know, what they call it, y two q, right, where,

conventional encryption will be effectively useless. But, no,

like, there's other use cases. That was the thing that took me from the field.

Like, oh, I guess truly random number generation is a big deal. That's

Oh, yeah. Yeah. Yeah. We're utilizing,

a very specific method in our cryptography

algorithm, which is it's pretty brilliant.

I gotta I gotta say it's pretty brilliant. And, that I

I I think everybody kind of dealing with that is kind of

utilizing so many different methods. And, you know, only time will

tell who ends up having that superior, you know,

algorithm, but I think it it's it's so fun. It's

so, for me, it's fun to sell, but I think it's it's so fun to

be able to start now seeing people come out of the woodworks

and, you know, start getting into it because we started this industry

when nobody was talking about quantum at all. So we started

pitching these to, investors, like, really

early on, and they were like, no. I I don't I

don't I don't get it. You know? For for that

time frame, everybody just wanted to talk about AI, which, you know,

that's why our our actual business, Daikin, one of our,

options that we have is we are working with AI companies to be able to

help them translate that language into a quantum AI

algorithm. Because I think when quantum starts taking off,

it's gonna be a big problem for some of the AI companies to catch up

to. You know? So we did start working with a

couple. There's one robotic. It's it's a medical robotic company, and then there's

one company, and then there's one that,

is is in the medical field as well. But, you know, we just started working

with them as far as negotiating deals on, you know,

doing that. So Interesting. So I think

that really begs the question of, you know, you said you you enjoy doing the

sales in this quantum space. How did you get into the quantum space? Because I

think there's a lot of people, that really wanna get

into this space, but aren't really

sure where to get started. So what would be your advice to them? And

well, one, how'd you get into it? And then what would be your advice to

to to the quantum curious, if you will?

Well, to be honest, like, I'm I'm very close with the

CEO. And so back in the day when she was talking

about this, I just was pretty lost.

You know, the people that are really passionate about this and you

talk to them, that's when you start to learn this. That's when you start to

gain that passion behind it. That was the biggest thing I caught from

Candace when I first spoke with her. She's super passionate about

quantum. Those type of people are the people that will move

this field. And I think that was the biggest

thing I I noticed from her when I first started, you

know, talking with, the CEO of our

company. We like I said, we're very close. We're actually best

friends. Oh, that's cool. That's cool. And I I come from a

total different field, to be honest. I I work in a total

different field. I've worked in business for the last fifteen, twenty years,

and I'm actually, you know, pretty skilled at being able to see the opportunity in

businesses. But I I just recently, you know,

when she started this program, how to start learning about

quantum and start really comprehending how is

this operating. And it's so mind blowing when you

understand the concept. Before you understand it, then you're

just like, I mean, it's interesting, but you're not

passionate about it. But then when you start to

understand how these mechanism are working altogether,

you're mind blown. You're like, you you almost can't believe. You're

you're really actually making something impossible happen

and be possible for people. That's the mind blowing part of this.

So we're in our app, we're able to personalize things for

people that they won't even be able to comprehend because we also have a

shop on there, an ecommerce shop. So not even them will

be able to understand, like, why do I always find things I

love, you know, offer, you know, offer to me? Well, because we

built out that personalization to be able to match the right person.

Like, so we're not offering the red dress to the customer

that would prefer a black dress. So Interesting.

That's what I'm saying. Factors. There's so many different factors to

this. And now I'm sure you can't even imagine that you were

doing whatever it was that you were doing before when you're doing

this now. And it's just so exciting. Right? And it's just

it's fantastic. Right? Like, it's just it's exciting. It's new.

And and no. Not not enough people understand it, but

enough people can learn about it that, and

that can, you know, make it approachable, give them an onboarding,

and say, you know, this is kind of what you need to kind of wrap

your mind around first, and then you can go from there. Like, how you

go to AI companies and you're explaining to them what kind of algorithm

that they're gonna need in order to do something.

And then so and excuse me for not

completely understanding, but, so then when you speak to an

AI company and you say to them, you know, this is this is kind of

what you need. Are you is it the is it the proprietary

algorithm that you guys have come up with that helps them do what they

need to do as well, or do you have to come up with something else

for them specifically? It it kinda

depends on the company. So I think, like, everybody

somewhat has that moment. And, you know, with some of the

AI, companies, they have started having that,

moment. And those were the first ones, but that's why we needed

that investment to be able to hire a couple more,

engineers, and kinda help us back up

that because, you know, if we're focusing on on our main

project, you know, we we do need other people to help with the

building of the algorithms for others if we start getting those AI

companies, and we need to build out separate algorithms for them.

That's why we needed that, investment, and that's why

we wanted to come still keep developing, not

just for the app, but keep developing as it is, this technology.

For an example, Tinder, they use about

$96,000,000 on, developers a

year. Our app, actually, we're running with one developer.

That's why we're able to have that extra time to be able to build

out other algorithms, you know, and and practice. Like

cryptography, like, you know, that came left left field. We were like, well, let's

just let's see what we can do because we saw everybody was kinda talking about

it. And the approach that they ended up going into

like, I don't know, like, technical too much, but the way it was

explained, I was mind blown. Completely mind blown.

I wanna sit in her office for, like, a week and just listen to

everything. I just wanna sit there and listen to everything that's going

on and just learn, learn, learn. I'm like, oh. I'm like,

Anna doesn't know how much how close friends we're gonna become. She doesn't know that

yet. Well, you know, just like Frank was saying

when he was, you know, reading and then, you know, he he was, like,

starting to get into everybody kinda goes through that moment. And

I even had to go through that moment when, you know, I was reading

it, learning it from them when I was given kernels to go

research, which I cheated. I will I will admit, I

I definitely cheated that. I reached out to a million

different physics of the quantum field,

IBM. Like, I reached out to so many people. That's

not cheating. That's networking. I'm so as a marketer, that's the first thing

I would have thought to do. Oh, good to say. Plus you're in sales. Right?

Like, that's just your job. Like You know? Yeah. But but it is originally, they

gave me books to read. I have Oh, yeah. Okay. Articles.

And I and so I read it, and I'm like, let me put this in

chat g p t. And then I was like, let me never let me

talk to people because I actually, like, I I got so much

feedback from a lot of different people. I had a filter before I gave it

to them what was, able to actually be

utilized and what wasn't. And and even coming

from a field where I I did not have that background, I was

at least able to figure that out. I mean, that's what I was saying. Like,

that's the biggest scale that I would say that I have. I'm I'm pretty good

at building that opportunity, figuring out what that opportunity is in a

business. So I had to figure out the same situation with those colonels. I

had to figure out what was the key and then hand over the

key. While they were building out all the most complicated

portions of it, I had to do, like, more of the easy parts.

I the name of the book escapes me. I was trying to look it up

in my Amazon order history, but I apparently actually bought it from Barnes and Noble.

So the

the thing that helped me the most was a book about the history of quantum

physics. Right? And it was, like, one of the things I read was when I

was going through, like, the different gates and stuff like that, and I was like,

you know, who there was a poly gate. There's poly x, y,

and z. I'm like, who is this poly guy? Like, why is why is this

such a big deal? Like, he claimed, like, three gates for himself. Like, how'd

that happen? And then when you read the book, it's pretty

obvious, like, he was a big deal. What was also cool about this book, and

it's a shame I can't remember the name, was it also got into the

personality conflicts between, like, these researchers in the early days and stuff like

that. Oh, yeah. So Paulie was quite I don't want to say Paulie was a

smart guy, but not exactly a role model. I'll just leave it there.

A colorful character. Okay. The biggest,

I would say the biggest skill that I've I've figured from our

CEO is she has a skill of put being

really good at putting the patterns together.

Right. That was, that was the biggest thing I noticed, from

when I had to actually work, you know, in the inside. Because usually I work

on the, you know, marketing's I work with our marketing team, which at the

time, we were kinda more so, you know, building out the ideas,

but not really, going full force on the marketing

campaign, you know, really getting the users. So we have about

5,712 users on the app, but

that was with, like, very minimal,

marketing campaigns. And that was just to be able to accumulate some of the data

until we went wide frame. But now that we're building out a lot

of the other algorithms, we're we're pretty confident that we could start

scaling. Interesting.

So given the current state of quantum

Mhmm. The ecosystem where we have, like you said,

you know, JPMorgan just made an announcement, and they seem to kind of

wanna own financial,

financial quantum, systems.

And everyone's make you know, we we talk to a lot of people. So given

the information that's coming out, that's come out, what do you find to be the

most exciting?

Well, that's a great question.

I would say, I saw that with the JP

Morgan, thing, I saw that there was

a teacher there at, UT PhD,

that helped them actually complete that. And for me, because,

you know, one of our engineers did graduate, my sister graduated from

UT, I thought that was pretty big because when we started it,

there was not a lot of, like, resources that we could go to

back then. You know? So now that there's resources that a lot of

people can start going into, that that is, I think, a a big thing.

And then I think that, I saw a lot of the companies, IBM,

I believe D Wave too. There was a few that I saw that a lot

of the hardware companies are starting to work with universities. We

have a a few, very famous, universities

in Korea that I saw a few of them. And, like, that was pretty,

like, touching, like, you know, because, that was

that's a big thing for me, you know, and our our economy there in Korea

too. You know? I I would love to see, you know, quantum start growing

there. You know? It it's just now, you know, touching surface. A lot of

the, you know, government is getting into it. We had

a governor actually recently partner with a few American

companies here to invest in a lot of startups.

I think that that that building out the ecosystem of of

technology in general, I think it's it's a big move, and it's very,

you know, it means a lot. But I think, you know,

just partnering with certain countries even. You know, we

partnered with so many different, European,

companies that helped a lot along the way. So I think that's the

biggest thing for me. I would say, like, I think it's more so

the quantum community is pretty small, so it's pretty somewhat tight.

A lot of companies are open to helping, and I think that's the biggest

thing. JPMorgan, I see that, you know,

they're they're getting there, but I think even before JPMorgan, SoftBank,

chose to start, really putting into that's when I've really

started seeing people pay attention to it. When when SoftBank

first initially started making that investment

into the, the two hardware companies, I saw a big,

like, focus and people actually paying attention. That's how we're gonna

move it, but there's people with names. There's people that are pretty big

that could make a big, difference. But I think it it's also

important for them not to forget about those small

ecosystems that can become big. And that was a big challenge for

us. Even now, it's a huge challenge for us to get and overcome. And

I just think with other startups, we would love to be able to

partner and help once we're able to at that time frame that

we scale to a bigger company.

Yeah. I think that's brilliant. I I I've spoke we've spoken to other guests. We've

talked about how, you know, you know,

there are you know, we Frank had mentioned five or maybe there's seven

different kinds of qubits out there. Like, there's all these different

reasons to to use the quantum algorithms.

What's exciting is that there seems to not

just be one path. Mhmm. And that since

there are multiple paths, I feel personally

that it could be much more in the future, it could be much more of

a collaborative effort. Like you said, getting other like, if you got,

you know, a bunch of, you know, precedes together that they're all

kind of focusing on something that they would benefit from working

with each other, they'd probably get there faster, by

being more collaborative as opposed to saying, you know, I I have to win

the race. So Yeah. I'd like to hear kind of where your mentality is.

I I totally agree with that. What what do you think, Frank? I think that's

a great I mean, I I think it's really the future of the quantum industry.

I think there's the the I think quantum computing is in that weird

kind of embryonic state where it's kinda like

it's it's definitely out of the lab. We'd all agree

that. But I wouldn't call it a major industry yet.

For sure. So it's kind of in that, like, you know,

a lot of the feedback we've gotten when we talk to other

founders and whatnot is saying completely independent people said more or

less the same thing. Like, you go to these quantum conferences. It's always the

same people. They're all PhDs. Right? They're all quantum physicists.

And he's like, that's fine. You need them. But in order for this to

grow into an industry, you know, akin to the

semiconductor industry or whatever industry you wanna use,

right? It you need to get people who are

run the gamut. Right? Run the spectrum of business operations. From

marketing to, you know, operations to, I mean,

heck, even accounting. Right? Like, you know, like and obviously investors and all

that. Like, I mean and and another example that someone had said to me, it's

like, it's a bit like the automotive industry. Right? Like, now we don't question it

as an industry. Right? But at one point, it was just a bunch of geeks,

mechanical kind of Right. Your heads just tinkering in their garage.

Like, one of the one of the funniest anecdotes I've heard, I don't know if

it's true, but it was basically there's a famous book called Think and Grow Rich

by Napoleon Hill. And he was I love it. I love it. That's a great

book. So, like, there was one scene there was one scene where he describes meeting

Henry Ford for the first time. This is before, you know, the blue oval was

a thing. And he's like he was sent there by

Andrew Carnegie to interview this guy because he's he thought he had potential.

And, like, his first thought was this guy in greasy overalls,

like, you know, this guy? Really? Yes. And there

was, like, kind of this moment where you can infer, like, kinda like the internal

dialogue of Napoleon Hill where he's like, really?

Like, you're gonna come infer that, and then you can kind of also infer, like,

he's like, well, Carnegie spoke well of him. He can't just be

like this crazy guy hacking away in a it wasn't even

called the garage then. Right? It would have been like a a carriage house or

whatever. Right. So but, you

know, but but in order for that industry to become what it became, like, you

need everybody. You need people to work the assembly line. You know? Like, so,

like, it takes a I don't wanna use the cliche term it takes a village,

but, I mean, it takes a wide variety of skill sets and personalities to

build out an industry. And It does. I don't I think

that I think in the in in the software slash computer, you know,

big tech industry, I think they figured that out. But I don't

think I think there's a lot of hesitancy

to, like, well, no. I don't want I don't want the the great unwashed masses,

like, you know, doing this. Right? Like, there's a lot of gatekeeping. I think that's

really the word. Data science was the same way. Like, ten years ago, you

know, when I was curious in getting into it, they're like, yeah. You really should

get a PhD. You go back to school, got a PhD. Like like, really? Like,

I can just go, you know, with kids and the dogs and all that. Yeah.

Sure. I can do that. Now to this guy's

to many of their defense, this guy in particular, like, he went to MIT. He

went to Harvard. He has multiple PhDs. Like, to him, getting a getting a

new PhD is like walking down to Walmart and picking up a,

you know, a can of Diet Coke. Right? Like Mhmm. It's it's

not a deal for him. But, like, for for most people, that's a

significant financial and, logistical lift.

Yeah. But do you really need it? Like, I don't I

mean, it depends on what you wanna do. But in order for this to build

out to an industry, requiring everybody in an industry to have some kind of

advanced degree is not sustainable because you can only make

quite so many per year. And you also have people who are very talented who

don't have a degree. Right? So, like, you know, that that that I'm just saying,

like, it becomes, like, this whole thing. And I think we're at that point where

the quantum space is growing now. It's growing at a point where they're gonna have

to let in kids, so to speak, who don't have the PhD card. Mhmm.

Right? And there's always been a bit of that, at least I'm more

experienced with data science. And I think I'm too young to experience how that

went with computer science. But I do have people who mentored

me kind of in the business that basically said it was kind of the same

thing. And, like, it's it's I it's I wouldn't say it's intentional gatekeeping,

but it's kind of gatekeeping. Yeah. None of us. Back to

what you were just saying about Henry Ford when he was first breaking into

the automotive, industry. That's why we

use the candle. Because when the candle was, when they were

building out the candle, there was a lot of people that said it was a

Satan. It was like satanic. Like, at that

time frame, they didn't you know, there's always that moment.

I I'm from Korea. I know because we went through a whole century

while everybody else was progressing of staying stuck in that mentality.

Right. You know? So so I I get I get that. You know? But at

the same time, it takes a lot of different people as you're saying,

and it takes people giving other people chances. You know?

They will be surprised because for me, for an example, when

I when I first entered the field that I'm in, I actually

was working with people that were more tender than me and more,

smarter than me, more qualified. They had they had the

degrees. They had all of that. But the biggest difference was I was still willing

to and able to outsmart them and outwork

them. You you can't just put labels on people and

say, well, that person can't do so much because they're only they're only,

their only certification says that they can do this. That's just not

true. That's where you miss that opportunity of hitting the the golden

goose. Absolutely. Oh, I mean, look at Korea now. Like, the audio manufacturing,

the phones. I mean, Samsung alone is, like, a

major player in multiple markets. And so, like, once you I think you're

right. Like, once you kinda plug in the whole community and, like, everybody can kind

of work towards building something bigger than themselves.

And you and you and you you you you've read the book, Think and Grow

Rich, which I highly recommend. Right? So you know the part where he's kind of

book. It really is a good book. It's very but, like, the whole part where

he meets Henry Ford. And, like, in my lifetime, Henry Ford was, like, this you

know, historical figure. But, like, to meet him, to have somebody talking about him, like

like, really? This is the guy? Are you sure? Yeah. Well, yeah, I can imagine

if they had cell phones back then, he would've, like, went around the back or

texted them and been like, hey. You sure this is the right address?

Yeah. We definitely got that so many times.

Right. Right. No. But I think I think I

think that, this has been a great conversation, and and, I think I

think it's a, I think it speaks

to kind of a a think a line of thinking that Candace Lehan is that,

like, you know, this is a stage now where it's always been it's like an

adolescent phase. Like, it's always kind of this awkward phase where it's it's definitely out

of the lab, but it's definitely not a full on industry yet. Mhmm.

And, I mean, it's awkward. It there's gonna be some strange

moments as you've experienced. But, also, I mean, this is where, you know,

fortunes are made. Right? I mean, when I got into when I

switched from from chemical engineering to computer science, it was a big controversy with my

parents. Right? Because it was not seen as a viable yeah. Can you and I

see that look you gave me. Like, what? Like, this was not seen as a

viable career path up until maybe the mid nineties. Well,

our engineer has the same one, computer science. Yeah.

Yeah. So Yeah. So I mean, but it was not really, like it was

not really seen as a valid career path. Like, you know, my fam my parents

are very old school in that sense where, you know, like, they were doctor, lawyer,

engineer, or, you know, get a military

career. Like, that was basically kinda like their worldview. And, you know, and

I get it. Now that I have the shoes on the other foot, and I'm

a parent now and I have kids, and I'm like, you know, they you know,

I don't know what the the the middle said kid. He said he wanted to

be a race car driver or something like that. And I'm like, no. You gotta

be a doctor or a lawyer. And I'm like, oh, I become my parents.

Yes. Yeah. Well, you know, I went into business,

which for, my mom, that was pretty

hard, you know, because of course it's it's usually the medical

and she was a nurse. So of course it was like the medical. I could

never see myself just going through a field like that. I'm too,

spontaneous, I guess you could say. I like to go with with the

challenges, and and that's why I love this part of it because, like,

quantum is the most challenging, I would say, right now, but just because

I'm in it. I would agree. Yeah. It it's super challenging, you know, but

I think it it's gonna take a a few different approaches.

And I think our approach, when you hit a mainstream, like, when

Tinder became big, when Airbnb became big,

when, Uber began none of these concepts people could

comprehend when it happened. But, you know, I was I was telling somebody,

like, he he asked me, well, why do you need a quantum,

traveling app? You can just book your stuff. But, you

know, Steve Jobs said a long time

ago, sometimes you have to tell people what they need for them to understand

it. And I think when when we start building

out these apps and once we're we're starting to scale it,

people will understand, oh, this is why I needed this

so bad because it makes it so easy. We can we can

tailor it specifically for the person as far as, like,

a travel traveling is a a trillion dollar, projected to be a,

11, $11,000,000,000,000

industry. So when we get into that field, that's when when

when it things will, you know, hit the ground running. But I

know you probably don't wanna talk too much about it, but, I mean, is this,

like, travel from a consumer point of view or logistics

from, like, the airline kind of logistics provider's point of view, or is

it somewhere in the middle or somewhere else entirely? Well, no.

It's it's gonna be for the consumer. So that's why we're building out

that compatibility algorithm in a dating app

because that's what we'll end up utilizing and the optimization

into the traveling app so we can optimize these traveling,

itineraries for people that, like, gives them all like,

we we read something a long time ago where, you know, most

travelers, when they go places, either they regret where they go or they

miss out on the key places that most,

people that are from that area would never have recommended that they

missed. You know? So we're able to kinda build all of those things

in. But I think the biggest thing from my part is just building out

the partnerships with a lot of huge companies, and that's how we're gonna

start kinda building that out. But, yeah, it's just gonna be for consumers, but

it's meant to be, very easy for people to be

able to travel with. Very

cool. I'm looking forward to seeing that because I think it it it there's a

lot of variables in even just on the consumer level of travel. Right? Like, do

you what airports do you like? You know, it's more than just aisle or window.

Right? Oh, you know, I

think of hotels. Like, I I've had to do a lot of business travel of

late and, like, it's kinda like there's just I don't know

how they did it, but post pandemic, they actually made business travel worse. Like

and it's not the big things. It's just the little things. It's like, not this

again. Like, this so I think there's I think there's plenty of room to improve

the process. And then to your point, like, when it comes to online dating, like,

now that's, like, totally normal to meet people. Like, I met my wife,

online, and that was kind of, like, you know, like, really?

Like, you know, when I was like, done. The day. Yeah. And it

wasn't that long ago. Like, it was only, like, 02/2006. But, like, even before

then, you knew I knew people that had met through Usenet, if you even know

what that is. Wow. It's it's so before the web, there

was, basically news groups, on the Internet. So, like,

you know so there was, like, alt.personalsdot, like, whatever.

And, people met there, and it was, like, you know, some people we

know have been married, like, thirty, forty years. Like, that's where they met.

And but, like, you know, prior to when my wife and I met on

match.com. By that point, it was almost mainstream. But, like,

prior to that, it was just like, oh, no. You met online.

She's probably a match murderer. Someone's currently the people we

talk to. And even even some of the big companies that we

were pitching partnerships with, like, a lot of them actually all met on

dating app. Them and their wives met on on dating apps or,

Match. Match is a a huge one. And, you know, so I I do

think that, like, if somebody has, like, a resignation with

it, me, I just had headaches that my best friend was trying to solve, and

that's why some of these ideas came. That well, that's the

best reason, you know, solutions to real problems that you're having. I

mean, a %. That's why that's why most of the jobs

that we have now didn't even exist when we were in university.

You know, the world changes very quickly. I mean, I would never thought I

would be doing this when I was at Columbia and

getting my liberal arts education. You know, you never know

where it's gonna end up and and where the passion and when you're gonna meet

somebody who's gonna inspire you so much that they're

gonna help in changing your trajectory. So Technology

changes so fast in society along with it. Like, when we were talking about our

first computers the other day, right, and you

when you went off to college when I went off to college, the mat there

were no ColorMax. Right? Like, there were no, like, colorful back and

then when you were talking about, like, how when you went to school, like, all

the other cool kids had The color max, the orange or

yeah. They all had these Tangerine and all those colors. And I'm like, well, I

was out of college by time that happened. And we're not like that different in

age. Like, it was not like it's not like a generational thing. But, like, it's,

it's just fascinating. Because when I got the collars, like, a color Mac was, like,

the giant, like, thing you would get. And it was basically, you had to sell

a kidney to get one. Oh, yeah.

But, you know, a couple years later, you know, the the little iMacs came out

and stuff like that. And I and I think that there's the

unintended consequences for society. Like, you know, I met my wife. I don't think I

would have met her ordinarily because I was in a different city and stuff

like that. And we almost met just by chance based on,

like, shared connections and stuff like that in the nineties in New York because

she worked at a I, an early day ISP. And I was

trying to start set up another downstream ISP, like a consumer

brand. And I remember talking I was talking to one of the sales

reps who was at that company, and she would've if if we

had raised the funding, she would've shown up to that meeting, which is kinda funny.

That is very funny. Yeah. But but, I mean, they say your

soulmate, you know Yeah. Exactly. To to find you. But that's why

I think the coolest thing is we are literally using

parallel universes to make matches. Like, who can

say that? Right. Right. Great. That's

very romantic. And, and, and, oh, that's

just so exciting. Come on. Find your soulmate across the

multiverse. That should be your turn. Right.

Exactly. Exactly. Awesome. So we're, I'm sorry, Candace.

Go ahead. Okay. So I, I want to say to Anna that I want the

opportunity, to have you back on the show

again. I love what you're talking about. We'd

love to follow what is going on with Hedo Match

and, your work now, and then your work

into your next project, the travel. I wanna be part of it. I wanna hear

all about it. So hopefully you would like to come back

again. Of course. Oh, fabulous. That's exactly what I'm looking

for. So good. Good. This was so fascinating.

And, honestly, I have a bunch of people that, like, wanna talk to you,

that I've that I've spoken to, and then I'm like, she's got something real going

on right now. So, you know, business owner, bid you know,

president to presidents of these exciting quantum companies.

Again, the collaboration is really where the the most

fantastic stuff can happen. So I think that's great. I think that's

great. Thank you so much. Thanks for joining, and we'll let our

AI, who, far as I know, she's not Quantum, Bailey

finish the show. And that wraps up another entangled

episode of Impact Quantum. Huge thanks to Anna White

for showing us how quantum isn't just about Schrodinger's cat and

abstract physics. It's also about solving real world problems, like

love, travel, and the occasional cryptographic

crisis. If you enjoyed this mind bending conversation,

be sure to like, subscribe, and tell your AI

assistant to do the same. Until next time, stay

curious, stay quantum. And remember, in the

multiverse of possibilities, you're only one qubit away from

greatness.