Welcome to another episode of Impact Quantum, the

podcast that brings quantum computing down to Earth.

No PhD required, just an insatiable curiosity

and a fondness for mind bending tech. Today we're

thrilled to welcome David Isaac, co founder of Abacus. Yes,

that's Abacus with a Q. Because it wouldn't be a proper

quantum startup without one. David joins us to

explore the intersection of quantum computing and finance.

From portfolio optimization and anomaly detection

to the thrilling prospect of quantum AI. This

conversation dives deep into how quantum tech is reshaping

fintech and why the future might just arrive with a

qubit in hand. So whether you're a quantum

enthusiast, a fintech professional, or just someone who

wants to hear how D Wave Shear's algorithm and fish

and chips all fit into one conversation, you're in the right place.

Let's get quantum curious.

Well, hello. Let me shut that over. Well, hello

and welcome back to Impact Quantum, the podcast. We explore the emerging

future field of quantum computing where you don't need to be a

PhD in physics or advanced mathematics. You just need to be

curious. And with that in mind is my most. The

most quantum curious person I know.

The sneeze. I might leave that blooper in just to show that we were real.

So. Candace is quantum

curious. Welcome to the show, Candace. Thank you, Frank. I'm

really excited. I. I've been enjoying this so much

and today we have a great gu guest. We're going to be

talking to David. But hold off, hold off. Let's talk about her Instagram.

Oh, you're right. Go ahead, go ahead. Yeah, so we are

now on the gram, as the kids call it. Impact Quantum Podcast

is our id. So. Yeah. But without

further ado, because we do have an awesome guest and. Go ahead, Candace. I didn't

mean to steal your thunder. No, never. No worries. It's David Isaac.

He's the co founder of Abacus and we're just really excited

to speak with him today. David, thank you so much for joining us.

Hey, thanks so much for having me on. Really, really happy to be here and

happy to be on your really good podcast. Thank you.

Well, thank you, thank you. And you did say into virtual green moon. You've been

listening to us and I really appreciate that. That's awesome. We're at the point

now where we have some 25 episodes

that have been published for this season and we're like, wow, we're actually getting a

catalog now. Get the word up.

Yeah, yeah, thanks. So you work for a company called Abacus with a

Q because you Know, quantum companies have to have a Q in it,

but probably, probably the domain name probably has something to do with it

too. But what does abacus do?

Yeah, so it's, it's a, it's a great question.

So basically we are take, we are trying to apply

this current quantum computers to mostly

financial problems. So

we're doing a few different projects right now, but

mainly we're working with optimization. So

optimizing things like portfolios or

improving trading models and also something called anomaly

detection, which is a potential quantum advantage for

detecting things that are outside the

norm, which could be

important for things like fraud or

hacking banks and whatnot. So that's what we're currently working on.

And so the main thing is that we're trying to figure out ways that

we can give at least an on ramp for

what we believe is going to be a huge revolution

in technology and in finance in the future and

then try to provide advantage now to companies. And then as

the hardware becomes more powerful and scales up and also the

algorithms become more powerful, then we'll,

you know, we'll, we'll grow with those, with the technology.

That's kind of like pitch at the moment. Interesting. So

you more on the financial side. So I wouldn't kind of

call you, you're kind of a fintech company but you're really more of like financial

quant computing, right? Is that. Yeah, I think technically

when people ask this question, I think it does sort of fall under a fintech.

Yeah, but it's not like we're not helping people

save money or anything like that. It's.

You're not, you're not like letting people venmo money or whatever. Like. No, no,

no. Fintech is an interesting category. Right. Because you have everything.

So for those who don't know, fintech is short for financial tech. It's kind of

like a branch of startups. It really kind of came

to the fore as a term. I don't know like I always

think of Fintech has a bit of that, I don't want to say stain

but stench association with

crypto just a little I think as, as, as the crypto bro

kind of phase is part of, becomes

faded from memory. Like it's not as much but when you know, if you, you

know, if you were, if you. Somebody said FinTech maybe like five, six

years ago I'd been like oh, crypto bro. But like now it's, it's not

quite that. Right. I mean, yeah, I have

nothing against crypto or yeah, but I do. It's

just so broad, right? Like yeah, it really is. Like people don't realize like yeah,

it's almost like it's a category that's so broad it really going to need its

own kind of sub parts of it too. But yeah, I

only mentioned that because I just wonder like has the

fintech community in general, like what do they think of

quantum? Well, I

can say one, I can't comment so much on that. I

can say that we do are working

with a crypto analytics company right now

to enhance their classical trading

models. So you can actually gain

an advantage by training a classical prediction

model but using quantum to decide which.

It's called feature selection. So using a quantum computer to decide which

features are most relevant and then you can shrink down the size of

the training model and train it faster and maybe just

as accurately or approximately as accurately. And one would expect

that in the future that this will become more

powerful as hardware gets better. But so I, if you're asking me

about the adoption of quantum computing in the fintech industry, I think it's

like it, it's the, you know, fintechs tend to be, if they're startups, they tend

to be a little more adventurous and more curious. But, but

so far I haven't encountered too many that are into it, but that

seems to be slowly changing. That makes sense.

And, and just for the. So before I get the hate mail, I want to

say I'm not, I'm not a crypto hater. I'm just a crypto. I know I'm

crypto confused really is what it is, right. I'm to make of it like I

can, I understand the arguments for it but also

I don't understand how we get from, from where we are now to this

crypto utopia that has been promised. So

I don't want to go down that rabbit hole, but I just wanted to preempt

the hate mail. Well, David, let me ask

you this. What initially inspired you to apply quantum

technologies to the financial sector?

Yeah, so basically I shouldn't like,

I shouldn't say it this way maybe, but I was looking, you

know, there's this interesting technology like, which is quantum,

which is becoming, growing rapidly and becoming more

powerful rapidly. So I was looking for something to apply it

to and as they, you know, that's, you

know, in finance is interesting because

they are looking for a better solution. It doesn't

always have to be a perfect solution. So if you

can make say a hedge fund

1% more effective or something pretty soon

like 1% on. However much money they're trading that can add

up to really large amounts of money when you're trading

billions and billions of dollars every week or day

or whatever it is. So I feel like the leverage

in, in, in finance is, is

interesting to those people that work in that field.

Also. The other thing is like finance, quant finance typically is

really very much dominated by physicists.

Maybe not quantum computing physicists or maybe not quantum physicists. But

it attracts like the stem, you know, stem people

like mathematicians, physicists. And so it's a little easier

to get their attention, but also it's a little harder to sell them on it

because, you know, they want to know, like, all right, it's not working

right now. So it's not working. It's not

outperforming classical. Classical computers right

now. So. So that's. Yeah.

So which financial problems are best suited for quantum solutions

today? Risk trading? Fraud detection.

Yeah, I mean, I'll just say the, the killer

app for quantum, like quantum annealers right now

anyway, is portfolio optimization. Like, it's the one that every.

Yeah. So go ahead.

Yeah, because it's a. It's like one of these NP hard problems that isn't

essentially an optimization problem. So

it's just that it maps on perfectly onto the. It's called a.

I don't know if Jordy Rose talked about it, but it's called a cubo Q

U, B, O, which is sort of the. The

type of problem that the D wave quantum melar solve.

Mostly it's quadratic unconstrained binary

optimization. And the problem kind of maps on really well portfolio optimization.

So this is something that a lot of banks have a lot of interest in

because selecting an optimal portfolio under. With

many different securities, whatever you're, whatever

you're trading, is actually like fantastically

complex problem which is not really solvable

efficiently with a classical computer. So this is like the

big one that everyone, I'm sure everybody that you talk to is also talking about

this problem. But that's like, you know, it's also. When I say

that it's also the one that's.

It's more research has been done into that problem too. So there's one

really cool thing about quantum, which I think is going to get your listeners really

interested in me and everybody, is that there's all this uncharted

territory. There's all these, like, there's

probably all sorts of things out there are just waiting to

be discovered that a quantum will be. A quantum computer

will be able to probably handle a lot more easily than a

classical computer. And we don't know that. And we don't know it yet.

Like, you know, for example, just, like,

if I'm going on too much, just tell me. No, please. We do. You should

hear. You should hear Candice and I talk when we're like. Like,

yeah, like, this is nothing, man.

Good. I'll just keep going then. Tell me to shut up.

So, like, you know, everyone talks about Shor's algorithm. Shor.

Your guess, like, Shor's algorithm, which breaks the RSA

encryption. That's what's got a lot of people freaked out, honestly.

Yeah. And that's something that we should definitely talk about because it's, like, the thing

that gets, I would say, the most attention about

with quantum computers. So. And.

But, you know, Shores is just one. It's definitely the most. Probably

most interesting algorithm, but it's just one type

of quantum algorithm, and there's really not that many that are

known yet. There's. There's variations on some or, you know, I can't

even. I can't name them all, but there's really not that many. And

so there's a very. I mean, I can't prove it. There's a very

good chance that there's all sorts of other ones lying around somewhere that

are waiting to be discovered. And, like, it's not. That's not a sure thing.

But. Well, that's the exciting thing, Right. I mean, it's also new

that they're still naming algorithms after people, right? Yeah.

Like, you know, you go back to, like, you know, traditional computer science. Right.

There's this bubble sort, there's binary sort, there's this sort. They're not named after

people anymore. Right. Like, it's. I'm sure. I

mean, there's called. Shore's algorithm, the Grover's algorithm. They even name gates

after people. Right. The polygates. Right? Polygates, yeah.

Right. I mean, it's just kind of like. I mean, that's how new this is.

Like, this really is like, the frontier. Right. Like,

and a lot of people. I'm sorry, go ahead. I'm sorry.

I just wanted to get a. Like, the guy that I follow most, who

I admire, like, the most in this field is David Deutsch,

who. I don't know if you. I don't know if you've talked to him or

read a podcast, but I. Would love to have him on the show. Yeah. He

is, like. He is, like, considered to be the. At least the

theoretical father of quantum computing. And

I would just really recommend to your listeners not, not to take them away from

your podcast, but like, just watch a couple of his.

He's mind blowingly smart. He absolutely. Every time he

talks, I'm like, I never thought about that before. And

so he's, to me, he's someone I greatly admire. I think he's

the smartest person in the world. Probably one of them anyway. He's definitely

one of them. Yeah. Yeah. I think this is like, so

I get a lot of pushback from people like, oh, you know, it's only good.

Quantum's only good for a few things, right. Like among the pushbacks. And I'm

like, it's only good for a few things so far. Right. Like,

yeah, it's kind of like. And I go back to, you know, it might have

been a previous guest said, you know, Nobody in the 60s at Bell Labs

when they were inventing the transistor. Right. Had

TikTok in mind. Exactly. So

we don't know what we don't know. Right. And who

knows what we'll discover when these things are more

widely available and have more, you know, qubits

available to them. Like, we really don't know. Yeah. And I think that,

I think one thing that I, I just want to bring it back to,

I don't. There's. It's not a good idea that like

quantum computers are going to require replace classical

computers because I don't, you know, I have my iPhone next to me. It's not

like I don't see any scenario. Maybe I'm wrong, but we're

a quantum computer where my iPhone is going to be running on a quantum computer

a. Hundred years from now, honestly, like, if. That'S even going to be a thing.

Even if that's going to be a thing. Right? Right. Like, I can easily

imagine though, like, you know, I have a, you know, I have a desktop computer,

right. Like I could go to the store and get a qpu, right. And just

pop that in. Right. Like, even then that's still some time away.

Right. But, but no, you're right. I don't think it's going to

replace classical computers. I seriously doubt that

somebody we were talking to, I don't remember this a show that's been published yet.

It's kind of like you think about cars, right? You know, there's multiple ways to

power cars, right? There's gasoline, there's diesel,

there's electric. There's

a few other ways too, right. Like so, so each one of them has

their strengths. Each one of them has Their drawbacks. And it'll probably

be the same way with, with computers. Right?

Yeah. I was talking to someone just recently who was

telling me that like, and this is another thing I haven't thought of too

deeply, but it could be that, like the, you know, there's different

architectures for quantum computers. You have like the ion traps and the

superconductors and maybe the topological qubits and

all this stuff. Okay. But it could be the different

architectures are better at solving. Yeah. Different

problems. That's not like you said, quantum computer.

No. It seems at the moment we don't really know which one is going to

be the, the dominant one. Right. Which is the first one.

The first one to come out. Or the first

one that'll be affordable. Right. We really don't know. Right. Like, you know, it'll probably.

I mean, I'm a big believer that history doesn't, if it doesn't outright repeat it

kind of rhymes. Right. And we're seeing kind of like when you.

Right. Like you kind of see one of the big drivers of quantum

computing. And again, I live in the D.C. baltimore area, so my

perspective is a little skewed towards kind of the Shor's algorithm national

security angle. Right. But if

you look at the development of computers, what really made them, quote

unquote, for real was code breaking during the Second

World War. Right. You know

what's making quantum computing a high priority for a lot of these

research institutions? Code breaking effectively. Right.

It's kind of the same, same flavor. Right. So I could

easily see there being like there's

different types of arc right now. Like, you know, at the end of the day,

every computer from your iPhone to my PC, I'm

recording this on to my, my MacBook. They all basically

work on getting electrons like mice in a maze and kind of

adjusting them around. Right. You know, you're bouncing electrons through. It's

called electronics. Right. I could, you know,

I could easily see that. You know, we'll have different

architectures. Right. There'll be photonics for this type of problem. There'll be ion traps

for this. And you know, there's no guarantee it has to

collapse into one. One type of

architecture. Right. I don't know. I mean, I mean,

classical sort of house. I mean, it has. Yeah. Vacuum

tubes anymore. Right. And you're right. I don't think Alan Turing had

tick tock in mind when he was breaking German

codes. Right, right, right. I don't know what he would have thought about

that. But. So

what are the biggest obstacles to adoption in fintech right now.

Is it like hardware, is it algorithms, is it

regulations? No,

I think that it

depends which fintech which angle you're

coming from. But I think that I'll like

say I don't really like hype too much but I like optimism.

But I think when you talk to these, when you're a

money manager you have to be a little more hard

nosed about things. And I think they have their classical

techniques for doing Monte Carlo

simulations or whatever and until you can actually

tell them oh this is going to work better right

now, like it's so it's more of a

get back to me when it actually works better. So I think

sometimes they're a little, they don't,

they're not thinking about, you know, they're thinking about next quarter

or you know, their investor report or something. They're not thinking about five years from

now. So there's, you know, it's like all, it's not just with

them, it's with all humans. Like we kind of think short term and

I think, I like, to me it's that sort of idea. If you're

talking about the cyber security side, which is like that one's

quite interesting because you know, you're right, Frank.

There's a panic starting to grow in

governments, most warm governments at the moment, but also in

financial institutions. I mean

I am just starting not working with them

but just I'm having a lot of conversations with Cybersecurity Forum

and they're not a quantum company but

they're starting to get requests from really large clients that they

have that like what's going on with this? Is our

data safe? And I think governments are starting to take it

seriously too because one thing that was pointed out to me which I found really

interesting, like this idea that say we're going to have

Q day, whatever happened seven years from today or whatever,

pick your number, 70 years, whatever.

There's this idea that you can just like flip a switch and oh,

we're safe now. Like we have, you know, they, they do have the code is

quantum cryptography. They have quantum resistant algorithms as far as

we know. And so

there's this idea you're just going to flip a switch and everything's going to be

okay. But it doesn't work that way and I'm not a cybersecurity expert

so I've been learning a lot. And even I, when I

started talking to this company I was like, well I'm not really that worried

about Q Day or Shor's algorithm or cracking the RSA

or any of that. But now I'm getting more worried about it

because it's what we don't know. We don't know, for

example, how many qubits it will take to say there's

like, you know, you need a million logical qubits, you need 300 logical cubits.

I don't know. I've heard all these different numbers. 10,000.

I don't know. I don't think anybody really knows. And so I think

it's like, what's out there right now? The same thing that I was talking about,

the optimism of the future and like all the

undiscovered ideas and code and

algorithms in the future. Well, now I'm like, well, there's

also the negative side of that too. There's like, how much.

What else do we not know? I mean,

that's a really good point. That's a really good point.

It is. No one really can

say for sure, right? There's just guesstimates, right? Like, what's

this going to look like? How's this going to affect the data? I mean,

and even then, right, we call it post quantum

cryptography. I don't really like that term. I like quantum resistant. Because

we really can't say for certain that maybe, you know,

Shor's algorithm, version two, or it'll. Maybe it'll be named after somebody, right?

Because they're still not new, right. Another way to factor primes or,

you know, that sort of thing that could break this, right?

What's interesting, if you remember, there was a

movie in the 90s called Sneakers. Robert

Redford, right? Yeah, Robert Redford. He passed away this week. So I,

it, I watched part of it again and was like the main plot line of

that wasn't about quantum computing. It was about this idea that there was a device

that could factor primes better and basically break all encryption, right?

Like if you watch it again, when I watched

at the time when it came out, I was like, ah, that's a cool movie.

But then, like, watch it again, it's like, yeah, I mean, there'd be a lot

of. There'd be a lot of drama around that, both above board

and below board, right. In terms of what that would mean for security.

But you're right, we don't know. And that's the

exciting thing about the future, right? And the terrifying thing about the future

is could go either way, right?

Yeah. I think one thing that I'm also really

interested in and I think is you talk

about things that are amazing, yet at the same time could be slightly frightening.

I was thinking, like, what is the effect of like, say,

AI running on quantum hardware?

And I don't think we really know that yet, but there's definitely research

that suggests there's like a great opportunity there.

But it also, like, AI is already scaring people with just

ChatGPT right now. Right. What

happens when you run it on some, like, much more

powerful, at least in that domain, technology?

I think that's like, so interesting, but at the same time,

like, kind of scary. What if you could, like, you know, what if

some really bad actor could, you know,

simulate molecules or simulate

protein folding very easily and very accurately and

build some horrible, monstrous virus?

Or like, pick your, pick your doomsday

scenario. Pick your doomsday scenario. Right. It's not just Skynet to be afraid of

anymore. Right? Yeah. Anyway, I don't want to be. I don't want to be that

guy. Talking about being scared and

all that we're learning. What do you think, and we ask this of

everyone. What do you think is the biggest

misconception about quantum technology?

I think that's a really interesting question. I

expected it. I expect you to ask that.

I think I kind of referenced it earlier.

I think the. It's the. There's a couple, but

it's the idea that it's going to replace classical

computers. And I strongly, although I

can't say for sure, I don't believe that it's going to replace it. I

think it will. They will act together. They will complement each other.

Also, I think, you know, there's ideas that they're completely

useless. Like, they're not.

They don't do anything. And I think that's. I mean, that's clearly not true. Now

there's at least, you know, what's called, I guess they're calling it quantum utility,

where there is some, like, you may not be outperforming classical

models, but you're using these really weak devices,

weak, noisy devices, and it's, you know, sometimes matching

extremely powerful classical computers. So

I think that's such a promising sign that we're still in this early

stages and we're already at that point. So, yeah, so that's,

that's like kind of two misconceptions. I think,

you know, the other ones too, that, you know, they're already

extremely, extremely powerful. It's obviously not true.

So, yeah, I think I named all three.

Right. Well, they're very powerful in certain domains.

Right. They may not, you know, I don't know that's kind of the impression I

get is that they are very powerful. Yes. But there's a catch

to it, right? There are going to be

specialized hardware for the foreseeable future. Right. It's not going to replace

classical computers if it does happen. It's not probably not going to be in our

lifetimes, realistically, who

knows? I mean, predicting the future is hard, especially when it's about the future.

That's a Niels Bohr. Right? Right.

People don't think these scientific geniuses aren't good at

communicating. But they have some killer quotes, man. I mean. Oh yeah,

Einstein was like so quotable.

Yeah. Yeah. So

I mean, I think it's just like some, some of

the problems they are really good at solving. Like you have like the Google

Willow or chip. Like I think they were doing some

very abstract, not very useful

mathematical problem. Just kind of like galaxy and

boson sampling problems which apparently will

take a classical computer like 10,000 years or the age of the

universe or pick whatever, pick your number and

it solved it in like a minute. That's really

interesting. But it's not useful yet. That's not like a problem that's going to

be Gaussian. Boson sampling is not like gonna help your

life too much if you're a quantum researcher. So.

But I mean, who knows next year, you know, as

if you look at the roadmaps of the various companies, they're talking

about, you know, like a thousand qubits

the next three to five years or something.

Is that you take what you. Is it true?

Can they do it? I don't know. I've heard some big claims out there

and it's really exciting. But like, how are you planning

to do that? Yeah, I do worry about the hype cycle

kind of taking over. Right. I do too,

as people start. Yeah, go ahead. I'm sorry. Well, you get these huge

funding rounds that are happening, which is amazing.

But it's, it's crazy. It's like $2 billion or something.

Last week. Yeah, I thought it was just,

it was come about. There was something. It was just a lot of money was,

was just flying around. It appeared last week, so.

Yeah, I know. So it's like you can say. And so that's probably

a good thing maybe in the longer term. But you know, where this goes

like, I'm sure you guys know better than I do where it goes like it's

like very exciting. Very exciting and everyone's

very disappointed. So they say about. I think I say about

AI that I think it applies to quantum as well. You know, in the,

in the short term it's overhyped and in the long term it's

underhyped. And I, I like to quote that. I

think it's true. Right. Like, and, and you know, of all the

excesses of the. Well, not all, but a lot of the excesses of the dot

com boom, you know, it wasn't really. The problem was

in the technology. It just really wasn't mature enough. Right. They were making mature

promises on the immature technology. Right. And we're kind of starting to see

the, the, again, history repeating itself

with, with, with AI. Right. You know, depending on, depending on what

study you believe. Right. These, these gen AI projects,

you know, they're not 85% of them don't get the ROI or

whatever. Just, it's just, I don't. But again, like, it might be one of those

things where a few years down the road, you know, we'll have

another kind of AI realization that this is how you actually use it. Right.

I think everybody's just throwing AI at the wall and hoping something sticks.

True. But I mean, how else can you do it? I don't know. Yeah, I

haven't found a better way. Because, you know, like

there was all these dot bomb companies in the

late 90s, but there was like some really, really great companies

that came out of that. Yeah, there was a pets.com, but there was Amazon

too. You know. For every

pets.com or furniture.com. Right. There was,

you know, an ebay. Right. There was everything we interact with today

from a commercial, you know, aspect, Amazon, ebay, you know,

Uber wasn't around, but Uber could not have existed. Overstock.

Right. You know, could not have, you know, it doesn't. I think you

get from, I think what happens is you get from irrational exuberance

to irrational pessimism and then that's. When you want to buy.

That's when you want to buy. Yeah, yeah. Pessimism, you

know, and all these, you know, pets.com was,

you know, there's chewy.com, now there's barkbox. Like all these things

existed. But I have dogs, so

I'm very familiar with. I have a dog as well. Cool.

I wanted to ask you. Oh, I'm sorry. Go ahead.

Okay. I want to talk a little bit more for a minute because, you know,

now we have the expert on

the financial sector. So in terms of industry adoption,

do you expect Quantum to first benefit large

global banks or will fintech startups

lead the way?

So our goal at Abacus, we wanted

to focus on sort of medium companies,

medium to small companies. Because there's advantages and

disadvantages to dealing with them. They tend to be a little more like

forward thinking and adventurous. It's

like crypto companies. Sorry to bring up crypto again,

but they're very like. I don't hate

crypto. I really don't. I just, I, I feel like it's one of those things

where you remember those things. Speaking of the 90s, right? This is kind of a

retro theme show, right? Speaking of the 90s, remember the, the magic dots things? You

would have to stare at them and then you would see. You stared at it

long enough, you would see like this 3D thing pop out. Yeah, yeah.

The stereoscopic or whatever, whatever those things were called. I, I feel

like that, like, I feel like. And I never. It took me a.

It wasn't until like maybe like 5 years ago I actually got it to work.

But like. So like I feel like that. I feel like I'm looking at this

name expecting to see something pop out, but I don't. That's kind of how I

feel about crypto. I'm, you know, so it's, it's not that I hate it, but.

Sorry again. See, we do it all the time. You're seeing it right

here. We are doing it right now. Went from talking about financial analysis

and all that to, you know, those

magic eye diagrams or whatever. I'm, I'm

really good at getting people off topic.

So. Okay, wait, wait. So we were talking about fintech startups, right?

So fintech startups versus the. Then you were saying, what is

the goal? The goal of your company is you said you were going

after medium to small. Yeah. With a sense

of, with a sense of adventure and

scientific spirit. But the thing about them is they don't have like the

resources that say a big bank would have. You know, like

some, you know, some of the banks, the bigger, the biggest ones, they

actually have their own quantum teams. Even so, I mean,

I would expect that big

advancements in finance will

either spin out from them or like maybe

be inside those companies. So like, I would say that probably

bigger companies will benefit first and then after

they, I mean, they'll be the. Just not. Because they are very

conservative, which is not always a good thing, but they are. So they also have

like a big budget. So that's what I'm

expecting. But I kind of hope I'm wrong about that because

my model, not my business model. Okay.

You said something earlier that piqued my curiosity and I wanted to make sure

I asked you about it. I never thought about using

quantum computing in anomaly detection

because in my simple, in my simple mind I've just like, can't you

just use regular old statistical tools?

You can, but. Well, obviously they do, but you know, I've actually

been just, I'm building like right now just like just

a toy problem, like a demo, like a toy model and

using something called a restricted Boltzmann machine RBM

to use the D Wave hybrid Annealer to train

the negative phase of the rbm. And then it's. And also.

So I've just. On my toy problem, I compared it against like the classical

method, the auto encoder, tried a

couple of things and it was like very

competitive with it. And I had, I haven't really done a lot with this project.

Like I just haven't tuned it really well or anything. So like

it's really looking promising. Mind you, that's for. That was more for

not really credit card fraud or anything. You could use it for that, but it's

more for the cybersecurity angle,

which I. Not really financial related so much, but

it's kind of worked. But that's interesting. I mean, I hadn't thought about that but

like, I mean it'd be interesting like if it was competitive and you didn't do

anything really with it, like you know, to tune it or, or to

iterate on it if it's competitive from the get go. That has

some interesting promise, doesn't it? Like really there's research

on it. Like it's, it's not my idea. There was like, I read

a few papers on it. I, I wish I could send them to you. I

don't remember. I'm sure I have them somewhere. But I said,

oh, that's really interesting and it is promising. I would just

caveat a little that I always

have to say this. I'm using like for this particular problem

using the D wave hybrid. Right, the D

wave hybrid system. So take from that

what you will. How much of it is quantum? How much of

it is classical? Classical.

So is it is this abstracted away like as some kind of cloud service

type thing? So you, that's why you can't really say which is which?

No, you, I mean, well, that's not really why.

Okay, but yeah, so for me, yes, that is why. I mean

somebody could figure it out. But I don't. I'm not going to go that deep

in trying to figure out what's going on. I just want like when you talk

to clients. Like they are very unconcerned what is

Quantum and what is not quantum. They're just like, oh, this is,

this is kind of working and shows promise and maybe in two years

from now it will, you know, work much better. Right. But

yeah, I would say like we use like your, it's all this cloud service.

Like this is the amazing thing about the world we live in right now that

like you can have a small group of people can access

this really, really powerful computational resources.

Like say we use Azure, like say

there's no way we would be able to do any of this stuff without, you

know, D wave. And maybe you're using AWS or something.

And I think it's really, really inspiring for

entrepreneurs now that you can just test ideas

very quickly. You don't have to go out there and like spend

tons and tons of money or

you know, hire tons and tons of people. You can build like

interesting use cases and demos and,

and also like, I think the coding tools are becoming

really interesting too. Not this is nothing to do with Quantum, but like you know,

just using say Chat GBT or Claw or something to

help with the coding. Like you're like, I don't feel like,

you know, dealing with where to put the comma or the bracket or

whatever. I'm just gonna, I know what I want to do and just get ChatGPT

to run, to write it and then run it on

cloud service. So yeah, I'm a big fan of vibe coding.

Right. You know. Yeah. Because I mean like I, I

haven't really done anything spec, you know, with front end development

the better part of 10 years or more. So I have all

these ideas in my head, right. And

I'm like, I have four kids, I have, I have three kids, four

dogs, right. I have a job, I have all these. I have a lot going

on, right. So I'm not going to pick up a book and like, you know,

learn, react. I'd love to. I've been wanting to for a couple of years, but

it just, you know, there's a lot of other things just keeping ahead in AI

alone for my day job is a full time job, right.

So the ability. So like, I'm sorry, go ahead.

Oh, I don't mean to interrupt you, but I would like to ask you guys

because I know you guys are really plugged into tech.

Like I always think about this, what does it mean to have

access, like to be able to just do something

in a day that you probably couldn't do it all? Like

what does that I can give. You a practical example. Right.

So Candace has been working on compiling all these reports in terms of

countries, right. And what they're up to

and like, you know, quantum and things like that. So I was like,

this is great, but we have what, 30, 40 reports, right?

Right. And I'm a data viz guy. Like, in my heart, I'm a data visual

guy. Right. I'm a visual learner. And like, one of the appeals that got me

into AI and data science was data visualization. Right. So,

like. And so I'm like, you know, I

would love to have this talent can. It's like, you know, remember War Games? And

like, you had the whole map of the world and you kind of see this

and, and all that. I'm like, wouldn't it be cool to do that? And at

that point, I'm like, let me see if I could do this in Claude. Right?

So then rather than learn Babylon JS or whatever the

3D framework is and all these things, I just basically described

it. Excuse me. I described what I

wanted to build, and after about what, 30, 40 back and forth, it took us

like 45 minutes to an hour. Yeah. Like, to get it, like, to what we

wanted to do. Right. And then maybe a little bit more in terms of

polish. It. Had to polish it off.

I mean, it maybe took maybe two hours. And we were able to get

that up into the site still up there now, obviously. Right. It became our Quantum

World report. So if you go onto this, you go onto our website, right.

Under country reports, there's this one. It's really

cool. Yeah. And it talks about quantum readiness.

Yeah, go for it. And because impact.

Quantum.com globalreport Sorry, Candice. No,

no. And it just kind of showed what is the state of

quantum around the world and what

countries are. Are really involved and have active, active

roles in it. What countries are just kind of initially just thinking about it,

you know, which countries are led solely by industry, which are led by

government, which countries, for example, are really focusing

on having their youth

educated in what Quantum can do. It's really

was very exciting to see it as this huge visualization

of the individual reports that I created.

And so. Right. So that was a perfect example of where we took

the reports that had been created and we vibe coded

into this beautiful visualization. Right.

And it does these fun little things, like spin the Earth faster, right.

I can stop it, I can pause the Earth. Like all these little things that,

you know, if you ever work with a UX or

information architecture team, I mean, it Would take forever to do. Right.

To get this done. But what was also exciting was that the AI

initially had come up with this idea of quantum readiness

based upon all the data that we had supplied

to it. And it really kind of made us look at it in a different

way. Yeah. And I was like. And it, you know, and I asked it like,

well, how did you come up with the Quantum Readiness Index? What were the formula?

And I'm like, oh, that's really good, actually. So,

you know, and you can kind of see the total funding worldwide, how many countries

average index, you know, and we could potentially track this over time

as well, like adding another dimension to the visualization. It's. I

mean, for me, I mean, this is something that. And there were a couple other

things I have in the back of my mind where I'm like, oh, one day

I'm going to build that. Well, we have that, right. We have a tool.

We might sell this as an external thing, Right. We call it Bookie.

Right. Has nothing to do with sports betting or anything like that. It's just that

we wanted to increase our affiliate revenue. Right. So one

of the. One of the ways that it does that, one of the

way I want to do that is like, any time we see a book on,

you know, on Quantum or whatever, we want to be able to post that to

the site and have the affiliate link. Yes. I do know that I could.

You. Know, use the Amazon tools, but the Amazon tools are, quite frankly,

lackluster. So I basically vibe coded this tool called Bookie. We'll probably

rename it to something else if we do sell it and

not to get confused with sports betting and all that. Right. So. So you basically

put in it, you paste in the URL of a book and it already knows

your affiliate code, and it'll basically generate all the materials

you need, you know, a QR code and affiliate link.

I'm a big believer in transparency, so I want to have the ability to have

people, you know, give the choice of. In certain scenarios. I want to say, all

right, you know, here's the. Not affiliate one. Here's the affiliate one. Right. Like, so

that way it's not. I'm not, you know, I'm not.

I'm not being a, you know, pushy in terms of

that. Yeah. But that

was all vibrated in a day or two. My first thought is, go

ahead. Yeah. So like five years ago,

McKinsey makes these, some. Whatever, Gartner or whatever. They do

these reports and they charge like a million dollars for them or

something. Right. And you guys are doing something like, probably

almost, I don't know, maybe as good, or at least almost as good,

and you're doing it for, like, few dollars. Right. I

mean, it's just so interesting. Well, it was funny because I'm not going to say

the name of the company, but I was in my day job, I was contacted

by somebody from a big company like that, and

they were giving me the sales pitch for, like, what they do. And I'm like,

after the call, I'm like, candace, they're doing more or less what we

do. Right. You know,

they were just. They were showing me a report and I'm like, this looks. It

wasn't about quantum computer computing, right. So. But it looked an awful lot like one

of the industry reports that she's working on that. Well, maybe by the time you

listen to this, they'll be released, but.

Yeah, right. Like, if you're in that business, you have a serious.

You're. You're gonna have a reckoning moment, right? Like, what value do you actually

add? And, you know,

it. That's a very good point. Right. Like, you know, and

if anyone, you know, with a. I dare say

a modest amount of AI skill, right. I can do this. I could do this

in my spare time. Candace can do this kind of, you know, because she's a

marketer with a history and, you know, proficient in writing.

Like, you know, and there's really, you know, we're not as big as

McKinsey or any of the big firms, but, yeah, I mean,

they're going to have to reinvent themselves, Right. Because what they're

selling today is going to be easily, or rather relatively

easily replicatable by much smaller teams.

Yeah. And soon, it seems. It seems. And soon. Arguably

now. Arguably now. Like, I

listen to Eric Schmidt a lot. Like, I watch his talks on

YouTube. And he asked all these to me what I think are really interesting

questions about, like, what does it mean to have, like, the world's best

mathematician in your pocket or your world's best.

Whatever doctor. There's all these industries. Well, maybe not

mathematicians so much, but, like, say, the medical industry is just

ripe for disruption. For.

I, like, it seems to me that it's an AI. Could be a

far better doctor than. Sorry, if there's any doctors listening, I apologize.

But seems like AI can. Well, I think. I think it comes down to

availability, right? Like, you know, 24 7.

Availability. Right. Like, so I, you know, I. My youngest gets frequent ear

infections. Candace knows all the sort of details, right. I can't tell you how many

times we've been to urgent care, right. You call up the, you know, and all

of these things like. But if I had an AI that I trusted, you

know, that would have the ability to order prescriptions or do

this, I would much rather do that than drag him out in the middle of

the night to urgent care or a couple times to the emergency room.

Right. I'd much rather do that. Now obviously there are going to be times when

you can't, you can't avoid that. But I just think of like all the, of

all the inefficiencies in, at least in the US healthcare system, right.

AI well, AI has an enormous opportunity to make things way

worse. But it also does have the opportunity to

streamline this. Right. Like if I have a, you know, a type of injury, I'm

not sure should I go to, you know, urgent care or not? Well, one, if

I'm not sure if I should go, that's one indicator that it's not actually life

threatening. Right. But if I can work with an

AI to do that, I mean, it wouldn't solve everything. But

if we could take like 50% off the load, that's a

step in the right direction. Yeah, right now it will take maybe 50%.

But what about 10 years from now? Yeah, maybe, maybe 80, 99%.

Yeah. And then using quantum technology to go to sift

through all of that data of all of the 2 year olds that

have all these type of ear infections and how often they're going to get

them and that the use of this one prescription is

really 95% effective for

X, Y, Z. Right. That's where

quantum in medicine, in pharma will become

incredibly useful to everybody. Right. Because

that's a swath across the, across everyone's going to be affected by pharma.

Right. Or they could, or what they could do is they could take a culture

of the bacteria that he's getting this infection from and then have a

custom made for him, his DNA, his everything for that

infection. There would be an antibiotic for that and then boom, done.

Like that's the dream, right? Yeah, I mean now, right, exactly, exactly.

But we talked to someone, Marvin

Weinstein, who you should definitely check out that episode.

You know, he is working on cancer research

at the intersection of quantum and the day that we

talked to him, he had just gotten back approval of one of his papers

by some government institution that it was

really so exciting where he was talking about

different types of, of tumors in the brain and

the trajectory that they would show amongst the 108, let's say,

patients that they had viewed to show that if you ended up at the

end, the worst one possible. Right. Most likely you

went through all the other ones before that to get to that point

of that particular kind of cancer. It was

fascinating. I was fascinating. And that is really.

That's really, like. That makes me

really optimistic and hopeful, and it's really, really interesting.

It just makes me think that, like, you know, cancer is a

math problem, apparently. And it makes me think, isn't

everything sort of a math problem? If everything's a math problem, then

should be able to bring computational resources to bear on it and

solve it. Not sure that's true, but

if not. Everything is, you can definitely make a lot of things

that way. And I think for me, the aha moment was when I learned about

game theory. Right. Because game theory, among other things, deals

with interpersonal interactions which you would think would be very

unpredictable. But anytime you use Instagram, anytime

you use YouTube or things on Amazon, turns out it's actually very

predictable. Oh, it's.

Correct me if I'm wrong. It's predictable. Over large numbers of people. Yes, over large

numbers is correct. Yeah. Like, any individual can deviate.

Yeah, any individual could deviate, but yeah, over a large

thing. So I think it's kind of a. It's an old saying, and it was

like, people are smart. No person is smart. People are dumb. I think

that was the. The thing where you kind of have that herd mentality.

But yeah, I mean, but it, it, it.

A lot of things I think can be abstracted away,

mostly mathematically. Sure, there are things that can't be,

but, you know, I think there's a lot. That's what I'm wondering about.

I think I'm one. I do wonder about that. Like, if everything is physics

in physics as described by mathematics, then everything is

mathematics and should be reduced

to. I'm not sure if any of that's true, but I don't want to get

started. I'm getting really. No, no, that's all. No, it's a good point. Plus, it

also brings up one of my favorite cartoons. It was, I think was from xkcd.

You know that cartoon? You have definitely seen it. Like, it's. It's become meme

worthy. But this guy draws stick figures. I think he used to work for NASA

or the jpl. And one of the cartoons is basically

about math and science jokes, right? And.

The. There was this one cartoon where it shows, like, you know, what's the

most pure form of science and it shows like, you know, well, biology is

just applied chemistry. Chemistry is just applied physics. Right.

And then it was like. And then all the way, like to the other side,

it was like, oh, I didn't see you all, you know. You know, it was

like, oh, yeah, but everything is ultimately applied math. It was, the

cartoon was really funny, but take my word for it, no

kind of dovetails, what you're saying. Yeah, I mean, it's something,

you know, like there's that paper, that famous paper by Vigner or something about

the unreasonable effectiveness of mathematics. Yes, that

it's like very, very. It's so strange that if

you really think really deeply about it,

it's strange that it works so well. Why should it, why should

it work so well to describe reality? And

anyway, I'm going to put that. Cartoon in the

chat. Yeah, thank you.

And here's the link. It's

xkcd.com435

so if you want to have the URL. So there's the

cartoon where it's basically like fields by purity. Right.

Actually I could share my screen. Yeah,

make it, make it, make it faster. Right. So it's kind of like

fields of range by purity. Right. And it was like sociology is applied

psychology. Psychology is applied biology. Biology is applied

chemistry, which is just applied physics. It's nice to be the. On top.

And then all the way over here it's like, oh, hey, I didn't see you

all the way over there. Mathematicians.

Right. You know, like it's, it's so

interesting that they call physics the bully science because

it, it encroaches onto everything. And what's so, like, I

find very fascinating is that like how finance uses physics

to like these ideas like say Brownian motion,

like, which I think Einstein discovered, like

to describe the behavior of molecules. Actually they use it in,

in financial, financial problems too. Like the interesting. It's

black. Black Scholes equations or options pricing, like,

these are like, to me it's just interesting how like the same concepts come up

over and over again and these very disparate

ideas and fields. Yeah, no,

that's, that's. No, that's cool. We want to be respectful of your time.

So this was an awesome conversation. We'd love to have you back

and you know, and

any final questions. Candace, I wanted you to tell us where people

could find out more about abacus. You can go

to our website. It's probably the best place. I'm not, I'm

going to try to do more promotion. It's just abacus.dev a b

a q u s.de.dev

Fantastic. Yeah. I like the animation.

Thank you. I didn't do it. Thank you. It was really nice to

talk to you guys. Thank you.

Enjoyed it. We really, absolutely would like to have you back. So that

was great. That was great. Thank you. And we'll let our AI

finish the show. And that's a wrap on another quantum conversation

here at Impact. Quantum. Huge thanks to David

Isaac for joining us and showing how quantum computing

isn't just for breaking encryption. It's also breaking into

finance, trading and fraud detection with style,

precision and naturally a cue in the company name.

If your brain's still buzzing from talk of portfolio optimization

and Shear's algorithm, don't worry, ours is too.

That just means you're doing it right. Don't forget to follow us

on Instagram @impactquantumpodcast. Yes,

we're now officially on the gram, proving once again that quantum

and cool aren't mutually exclusive. Until next

time, stay curious, stay quantum. And

remember, the future isn't just coming, it's already entangled.