Welcome back to Impact Quantum, the podcast that

explores the brave new world of quantum computing without requiring you

to earn a PhD first. In this

episode, your Quantum Curious hosts, Frank Lavine

and Candice Gilhooly sit down with the man who proudly holds the

title of the second least qualified person in

Quantum, Brian Ziegelwax. Broadcasting from the

Philippines, Brian brings a refreshing mix of humility,

humor and hard earned insight as he recounts his

accidental tumble down the quantum rabbit hole. From running

his first quantum experiment after watching a YouTube video

to offering candid thoughts on benchmarks, roadmaps,

and the software hardware tug of war in quantum tech,

Brian reminds us that sometimes the best way to navigate complex

topics is with a bit of curiosity and a lot of fun.

Along the way, he champions everything from assembly

language to the mysterious powers of quantum dragons, and

even makes the case for Kubble in quantum computing. Yes,

really. So whether you're a software engineer wondering what

skills to sharpen, a business leader eyeing the 2030

Horizon, or just quantum Curious like Candice, this

episode will make you laugh, think, and maybe even

question reality just a little bit. Strap in.

This isn't your average quantum chat.

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

the emerging market and field of quantum computing

and all. You don't need to be a PhD. You don't have to have a

PhD in physics. Don't let the technology scare you. Just got to be curious.

And with that in mind, I had the most quantum curious person I know with

me, Candace Gouley. How's it going, Candace? It's going great. Thank

you so much, Frank. I'm really excited about our conversation today.

Today we're going to be speaking with Brian Siegelwax, who

calls himself the second least qualified person

person in Quantum, which I very

much appreciate being quantum curious. And

so. Hello. Hi, Brian. Thank you so much for joining us today.

Thank you for having me. Pleasure to be here. Awesome. The

second most qualified person. Second least qualified

person in Quantum. Sounds like a DOS Equi commercial. If you

remember the most interesting man in the world

commercials. Yeah,

maybe I can work with that. There you go. Get a picture of you.

Like maybe Photoshop your face. Actually, you don't even need Photoshop anymore. Just use AI.

No, it would be the Dragon. It would be the Quantum Dragon that I use.

So maybe I could. The AIs are getting pretty good. I

might be able to use that and put the

most interesting dragon in the world. Oh no, I'll work on.

Takes time to come up with these things. How do how did you get into

quantum? Because it seems like you've been in the quantum space for a while. Is

that a fair statement? It was, it was an accident.

The story of my career actually. But I, I did it

backwards. So a lot of people, they've come into quantum and

they've stumbled into AI and

machine learning. What would. Kind of redundant, it's a subset of AI, but.

And then some of them have gone off

more towards AI while waiting for quantum to mature. So I did

it the opposite. I was doing machine learning and then

I accidentally discovered quantum. And

it's addictive. So that was,

I'd like to say around seven years ago. I have to look up when I

ran my first experiment. It would have been a little bit before that,

but yeah. YouTube video by IQT

IQT IBM research from

Dr. Doug McClure. I still remember it and saying

I could use a quantum computer for free via the cloud. And I thought, well,

you kind of have to just for conversation. But then it's, it's just

really addictive. You run the first one and then, and then you're

kind of like if, if you're not, let's

say a physicist or a mathematician or somebody

who's been studying quantum science. So it's your first exposure to

it. And what the heck did I really just do?

Superposition, entanglement. What is all that? I. I

kind of read up on that first, but now I've done it.

Let me see what the second experiment is and let me see what the third

experiment is and then might as well read a book and eventually you start

reading papers, then you start talking to people and then all these years

later I finally got promoted to the second least qualified

person in Quantum and it's my greatest

achievement to date. That's awesome.

I like what you said in the virtual Green Room. If you can't be serious,

be silly. Is that the thing? Something like

that. I'll have to work on that as a quote. There you go.

Put that in my email signature. What, what made

you like what you mentioned you, you know, you

started playing with it. Like what in particular made you hooked on Quantum?

That's a good question.

It's hard to say. You know, you try things in life and something sticks

and other things don't. And even from

like cell phone games that you download and you, you don't like this game and

you uninstall it and you don't like this game and you unins. Here's the game

that you play until four in the morning and you wish you hadn't. So

I'm not sure. Maybe the mystery of it,

like going back to the. What, what did I just do?

I, I read, I read the tutorial. I, I,

there was a course that

I audited, so I paid attention to that, watch that,

listened to that and kind of had an

idea. But then still you do it and you run it on a real

quantum computer and you wonder what did I really just do?

What did the hardware really just do? And where does

it go from here? And I

guess that's the mystery of it. Whereas classical

computing, you learn how to code and you're trying to create something new,

but then it doesn't have the

same, the same

mystique to it. Like with, like if you have, if you have

a problem with classical computing, you start

thinking, okay, how am I going to do that? And then with

quantum it's different. Can I do that?

Or, or also should I do that? So you have all these additional

questions to ask and then at some point it's, you know, how would I actually

do that? Like classical. But then there's additional questions like,

you know, should we even be looking at quantum for this? And

then, you know, quantum circuits don't work the same way

as classical code. So, so can we do this or how

would we do this? And how do we encode this? And, and, and

another level of interest I guess over

classical coding, which I probably should say I've done for

four plus decades. So that's kind of a natural thing.

So here's this mysterious new thing,

right? Interesting. You know, maybe not for you

because you're so immersed in, in the space, but

you know, I feel like the, the, the quantum

sector has just been exploding in the past year with,

with you know, all these incredible

potential applications and really just

everyone's kind of fighting to be number one for their qubit

and I think it's very, very exciting. So we have a lot of

people in our audience who have

either they have a technical background or they have non

technical or like a non technical business leader. So how should

a non technical business leader best interpret the current

quantum computing benchmarks and roadma that

we've been looking at over the past year.

That is a good question.

They're not standardized, so,

so when you look at the roadmaps, they all say something different. And I've actually

written about this and I, and I tried to compare them and I

created a table and most of the cells ended up being

blank. Because this company in this year

wants this and this. Then the Next company doesn't

mention those at all and wants this and this and then the next company

wants something different. So they all, at the time

that I, I wrote that,

what, how many logical qubits are they? Are

they talking about what are the error rates? Not everybody says anything about

that. So it's really an apples to

apples and oranges and a few other fruit.

It'd be easier if it was just apples and oranges really, but so you need

a whole produce stand and everybody's got different produce and they're

all different prices and what's

tasty. And there really is no

comparison. And we really still need

to wait a few more years to find out

who's going to be first. Because the original,

the early roadmaps were looking at

2030. That the general, if you ask me to

describe the general roadmap, it would be 100 logical qubits

of unknown quality by 2030.

And that was kind of everybody's goal. And then

this year they've been kind of nudging forward

that we are going to be the first default tolerant

quantum computing. But, but quite a few companies are going

to be the first. So who's going to be the first? And then we, we

don't know again. And then the, the roadmaps have gotten a lot more

ambitious. So then there's a question

of what's really feasible. And the

earlier ones looked kind of feasible and then the newer ones,

you have to put question marks on lots of them. So who will

achieve what when? There's still time

for a lot of those companies to hit walls

and not progress and kind of drop out or change

course. And we see that a little bit. A lot of these roadmaps are

actually changing throughout the year.

So it's very dynamic who's promising what when. And

there really is no great way

to compare them other than I'd still use the year 2030.

Hopefully by 2030 we have at least one interesting

thing.

Well, also too, I think a lot of people are freaking

out because, you know, 2030 is,

you know, we're actually, I think now closer to

2030 than we are 2020, which is kind of a

scary thought. But also it's less than five

years away now and

today's secrets could be very potentially embarrassing. Right. So if you have something that

could break traditional RSA encryption,

now's the time to start upgrading your encryption, I think. Granted. I

live in the D.C. baltimore area, so maybe like Infosec is a little more

top of mind around here. Hopefully it is.

But I also think too, like

beyond the first system with 100 logical qubits, there's going

to be a lot more things and problems that could be solved once you get

beyond 100. Right. Like it gets more interesting as you get more stable

qubits. Is that correct? So it

depends on the problem you're trying to solve. So if you ask the question, when

will quantum computers be useful? Right. They're useful today,

but for very limited purposes. So

it's more of a question of when will they be useful for what you're trying

to do. When will they be useful for causing

cryptography problems? That's going to be one of the last

things. So things, things should start happening before that

happens, that within the next five

years more things will become practical.

That maybe 10 years and maybe 20 years. So.

So as the quantum computers get larger

and their error rates come down, more things will be possible.

And then really cryptography will be,

will be doing exciting things before that happens. And we're

not quite there yet.

Interesting. And we also don't know when that will happen because

anybody could have a breakthrough or a company could

purchase another company. So now you have this synergy kind of

speeding things up a little bit and we're starting to see that.

So it's really a bunch of question marks of

what if this company switches to doing this

and. Or all kinds of, all kinds of

breakthroughs, all kinds of technologies that could go from a little bit to a

lot quickly. But

we have to wait and see.

Do you think the balance is shifting

between hardware centric and software centric innovation

in quantum computing?

Well, the focus is and should be on

hardware because without hardware you can't do

anything with the software, which is actually. Let's

back the software a little bit. So a lot of the critique, there's an

increasing critique about the software because

of this pending arrival of useful

hardware. So useful hardware

is not so useful without the software.

But the software doesn't really need to be useful if you can't

actually use it on anything yet. So.

So there's more emphasis on software than there used to be

because now we need that software to

be ready to be able to use with the hardware that

depending on the roadmaps, maybe

next year, as early as next. Well, that might be 10 logical

qubits. They keep changing. I think

quera's roadmap is 100 logical qubits,

maybe 20, 28. Wow. So it's

not me, but I mean it's like within 2030. Like it's within,

like you Know corporate planning milestones, right?

Like, well it depends what your

corporation needs to solve. So 100 qubits may

not do much for you, but you might have the type of company

might do something for you. But now if you want to do,

you know, larger problems, it may, it may still start becoming

interesting, but it also depends

on we have a hundred logical qubits. How good are they really?

And they may have better error rates than today's

machines, but they may still not be good enough. So we

still have to see because with fault tolerant computers we'll also

run much larger and much deeper algorithms.

So the more gates you have, the more errors

accumulate. So,

so it'll be interesting. What's

what like a consensus. What's the consensus that this

new machine with this software is doing something

useful for these tasks and everybody kind

of, kind of agrees that we've, we've hit that milestone

and then there's still more milestones to be had but we at

least achieved some

businesses, some, some more enterprises are

having some commercial.

Can't speak at this hour. Commercial usefulness.

Interesting. Where do

you like what so, so really kind of. I know this is an

odd question to ask but like where, what do you think that like the C

suite people or the CTOs or the CIOs in particular,

how, how should they look at quantum

computing, right? Should they see this is on their radar over the horizon?

Again, I guess it probably depends what industry you're in, right?

The industry, the types of problems you're trying to solve. So you may

have a problem that is not

realistically close. You, you,

you're maybe interested in it, but realistically

it's, it's more years off to have a quantum computers that

are quite that large that are capable of handling those tests

and other industries are paying attention

sooner. And then a lot of,

a lot of uncertainty too with different tricks like

maybe, maybe it's enough to solve parts

of problems more accurately. What depends on

error rates again, but maybe you can solve parts of problems and that's

useful. So different strategies of.

But you know, if you're, if you have a business then

is it worth researching that there, there are questions to ask

and, and maybe you're watching some of the bigger companies out

there and what they're doing. The big companies aren't looking into it.

So they have seen the value of devoting

human resources and financial resources and trying

to determine what,

well first what problems you want to address with

quantum computers. Then how would we actually

address those problems with quantum computers and then

what's the timeline? When do we think we'll actually have one of those quantum

computers? And all those things need to come together

and probably.

Yep, probably by 2030. I'll, I'll just keep saying

2030 is a. A good year on the more

conservative side. Do I want to call it that? But by.

By 2030, enough companies are promising 100 logical

qubits that more enterprises should

be finding them interesting. And then the more enterprises that find

them interesting, then the other ones who are waiting might start taking

more notice of, okay, we've achieved this level.

We just need them to get a little bit bigger. Well, or a lot bigger.

And then we can do interesting things also.

That's fair. That's fair.

What do you think that if you're a software engineer,

what do you think people should be focusing on? Well, now,

basically performance

and integration. But. So when

quantum computers have five qubits and you're not doing much with

them, they're written in Python and

meant to be relatively easy to use and

accessible to broader audiences.

And be careful what I say, because Python people

irritated Python people with my comments on it. But it's not

adjectives. Got to pick the right adjectives here. But. So

I'll put Python aside for a moment to talk more like C

level of. Now we're talking about,

we have enterprise applications. We will quantum

computing fit. We have to integrate that into our C

or whatever production environment we have.

We need the performance, the memory management,

and we need to start looking at how we'll actually plug it

in and plug it in with the same performance

that we expect of classical applications.

You don't want any. You know, if you're using quantum

computing for especially

acceleration, you don't want anything

unnecessarily slowing it down. So Python

is not the language for. I'm going to get in trouble. I'm going to get

your whole podcast. You know, as a Python developer.

Developer, I think it's Python.

Python's biggest strength is its flexibility, not its performance.

And I think anyone who's honest about that, who's a Python

developer, will accept that reality. Have there been

strides to optimize Python? Absolutely. It's way better

performant now than it was before. Are there still ways to

go? Absolutely. Maybe there'll be a race between, like,

Python optimization and quantum qubits.

For a little background. If I could, I would be using C

in assembly. So that's my mindset of where I

prefer to be programming. But Quantum is still Python,

so. But it's spread. It's spread. You can look at

GitHub and find your language of choice.

Julia is quite a bit. Well,

there's some in Julia. I've seen Julia, but I've seen

kind of a mix of what's your language. There's

probably something out there written for you. Might

not be using real quantum computers, but might be

simulating them. There's a lot,

hundreds of

repositories on GitHub alone to choose

from that you can find and experiment with different things.

Interesting. I find that fascinating. I think also too,

predicting the dominance of a computer language

is also very hard too. Right? Just because,

just because predicting the future of the industry in general is hard.

But you know, who knows, maybe there'll be some other language that'll do it. I

think Julia, maybe, maybe Julia will find its stride.

I swear I was just thinking that in my mind, you know, my background

working for technology book publisher. Is that

Julia? When we came out with a Julia book, I mean, it was

a really long time ago and it really didn't have

legs. But now when

we. I've heard several of our guests talk about Julia and

if Julia is something that is going to be helpful with

Quantum, then I think that it is going to find its, its, its,

its legs. Finally, when more and more

developers are trying to figure out what are, what are some

skills that they can pick up when they're trying to

enter into this new sector. And I would also encourage people who are

religiously fanatical about a particular language to give it up. Right.

Like it's about the problem, it's not about the language. I mean,

I say this as a former C Sharp developer

who was a former Java developer, who was a former Perl

developer. If you're going through your career, different

languages will come and go. And if

you want to optimize your career

for growth and monetary reward,

you're going to have to pick up more than one language. Right? I mean, that's

just the way it is. Well, it's really

backwards because it's your production environment that

it has to fit into, right? So right now when we

use Python, you know, maybe you have a standalone

Jupyter notebook and it's Python or it's

Julia. Excuse me, but then in your

enterprise, what are you actually using? So the

Quantum companies are really going to have to adapt because

you're not going to change your system. And for performance, whatever

you're using, it has to integrate into that just like any other

enterprise application you might be looking at. It's the same

thing of we've got this application and now

we're adapting something to use GPUs for whatever

tasks. Same thing really, in principle,

for QPUs, we're going to adapt to

that thing and that thing has to be whether it's on premises

and however that will look or otherwise by API

calls to something on the cloud, which now

you've got the latency of the network. But however, however,

probably however you access QPUs,

then QPUs, you'll integrate them and use

each for dying

prematurely, but using each one

for the optimal tasks. Right.

Including CPUs, still great for a lot of things.

Interesting. No, I think, I think that's an interesting take on

it. And

the problem is what. So, like you as a C Sharp,

former C Sharp developer, if you were still using C Sharp, then Q

Sharp would probably be a natural fit

Quantum Development Kit. So that'd be like a

natural fit. So you're already using.

For whatever that. That would just seem to be a natural fit. And if

you want to use something else, then you have to figure out how to integrate

that. But that might be a natural fit. Or

if you're using C, this might be a natural fit. Or if you're using

Rust or whatever, then that

might affect who you go with or may affect how

they'll develop something for you.

I mean, that makes a lot of sense. If you look at,

if you look at historically, right. Like, C was largely a

response to Department of Justice saying Microsoft can't touch

Java anymore and they had JARP at one point. Right. Like, so these languages,

people, I think, get too wrapped up and focused on the actual language,

not the problem that they're trying to solve. Right. And I've seen this time and

time again. So I encourage folks to expand

their. Particularly if you're a software engineer, it's not about the language

you write in, it's about the problems and how you solve them in any

language. Right. Like one of the most interesting things about. NET is

was it compiled basically to an

intermediate language? I'll get into compilers in a

second. You would see people

write code in Visual Basic or C. But there are other languages too.

But those are the two main ones. You look at them and they're

saying the same thing and they're talking to the same underlying APIs.

So it was kind of funny to see. Oh, you know, kind of

the problem is the thing, not the language. The other thing is that.

Correct me if I'm wrong, Candace. He is the second guest to point out Assembly

Language as being important. Right. That kind of low level

programming as a skill. And I think, I think

assembly language, I feel is like a lost art. Right. It's almost

like, you know, being able to read like this ancient script, so

to speak. Right People. I don't even know if kids study it today

anymore. In, in college. Clearly you're a fan

of assembly language. Yeah. You know,

if you, if you code assembly, nobody can

question you. Right. You know, like if gonna get in

trouble with the Python people again, gonna not use any adjectives,

but a few years ago. Yeah, yeah, I won't get

started there. But assembly, you can't

criticize. How can you say, how can you say

somebody who codes assembly is not a real

programmer? Like I don't give

examples. I'll get myself in trouble for that too. But, but yeah, even

we'll see. Also C is also,

you really can't question anybody if they're a C programmer.

I'd let C into the group also. But

then the lower level you are. The,

the more committed to the cause you are. I would say. Well, it's not doing

it for you. Like vibe

coding today. Right. So,

so if you're using AI to write code for you, are you.

I'm going to get in trouble. There goes your show. I apologize. You know, are

you really doing the programming? If the AI is doing the programming

for you, which is different though than let's say you have AI write

some code for you, but you're still integrating it or troubleshooting

it or debugging it because AI is not quite up to that task

yet. But if you're coding

assembly, it's unforgiving in so

many ways. Not really,

not really practical for Quantum at the moment. Well, I guess, I guess

we could. I don't know. Anybody who's somebody's

probably looking into that. I would imagine that there's somebody, not

me, who is looking into how can I access a

quantum computer by, by using

everything. Somebody. Somebody. Well,

IBM's Qiskit has been adapted to

like Raspberry PI devices. I haven't seen

that in a while, but it was converted at that point. So a,

a svelte version of it that could fit on,

on a little device and then somebody

ported it to like a mainframe or something. And you're thinking

why would you use a mainframe to run quantum computing? Well,

because you can. Or like people Who Network

Commodore 64 together and, and

try and do something with that just to see if it can happen.

Doesn't mean it's the Best thing. But. But C. Well,

if you're talking C plus plus, and C has to be in the

conversation somewhere. But assembly would. Oh, you know, it'd be

funnier, actually. Cobol. I forgot about this. This was on my to do

list a few years ago. You take like something like COBOL and

use that for quantum computing just for.

Can I swear I won't swear. We can bleep it out. Just

for the conversational. The conversational

benefits of it. Why would you do something like that?

It's. It's fun, you know, why.

Why would, why would anybody do such a thing? But. But that would be fun.

Well, somebody wrote a browser for the Commodore 64. Right. Which I think is, you

know, it's kind of like taking like an Impala 60,

like a 64 Impala and drop it in a brand new Bluetooth stereo with

Android Auto and all that. An Apple car. Right. Like, it's kind

of fun. Yeah. I've seen a

house like that, a house that looked like on the outside and

it should be condemned, but then you go inside and you're like,

oh, they spent all their money on the inside of the house. The outside. You're

not going to rob the place. Probably shouldn't say that out loud either, but.

But you know, from the outside of the house, it doesn't look like

anything until you go inside and everything's all

nicely nicely built and nicely

decorated and spacious too, actually. Nice

tall ceilings and everything. Totally off topic, but.

Well, while we're off topic, I was sharing a story recently.

I'm sorry, that I was in a

trailer park once visiting a friend's relative, and it was

a dodgy place and

my friend was like, no, this guy's really into Amigas. And I'm looking around like,

okay, right. And then we go inside, it

looked like norad. He had monitors. Like, I mean, maybe

that was the original inspiration for this. We had monitors. He had like 17 or

20, like amigas all like banked together doing this

supercomputing of like array of like video processing. This was in the

late 90s, so like video processing was still very much. I was just

amazed. Like from the outside you would not. It did not look like there

was NORAD inside, which I think was an interesting, interesting

choice. But

Commodore Amigas, because they're from the 80s

and late 80s. Early 90s. A company called 80s, maybe late 80s.

Yeah. So I don't know, I just thought that was

interesting. You had this

whole thing. Yeah.

What. What would be your advice to,

like when people ask You, I'm sure when people see that

you're the second least qualified quantum computer,

what do people, what do people say? Like, what do they ask you? Like, what's

quantum computing? Or like, what should I be focusing on quantum computing? Like,

what's what, what's kind of the,

the thinking there? Like, what happens?

Well, actually more so

than when I was the least qualified as the second least qualified.

Everybody wants to be below that. Well, not everybody, but there are a lot

of people who are like, well, if I'm the second least, they must be

the least. One person in a call

who went after me introduced him as, introduced

himself as completely unqualified in quantum.

So I find that's actually the most interesting thing, how everybody,

not everybody, but lots of people will try and like jockey themselves at,

at some lower level. So I wasn't expecting that.

And then the questions are

usually more specific. I don't really get too many general

questions issues. I said humility is not something the tech industry is

known for. Right. I mean, for me as a marketer,

I come into, I come into it from

a very different perspective. And I want to be,

I want to be the person that's able to communicate and explain

what it is, why you need it, why you don't need it.

You know what's important to understand, what you really don't need

to bother with, because it is where

computing is going for certain

types of problems that,

you know, the, you know, the

computer systems that we have now are simply incapable of

answering. It's not about speed, it's about the

specific problem as I'm beginning to understand it better.

Which kind of brings me to, you know, beyond the technical

skills which we talked about, what is the

most underrated attribute for someone

entering the quantum industry today?

The underrated attribute? Yeah.

Fun.

The, the fun, the, the interest, the awe, the wonder of

it all. Some people who have been doing it for a while, well, this isn't

entirely true. So you, you watch a webinar and

somebody published a paper and they're very serious and they've got

their slides and they're talking about it and you can throw

them off guard. And I've done this a couple of times, like, what's

the most interesting thing about this? Or what's the most interesting thing

about that? And when you, you get them off script, their faces

light up because it's interesting stuff.

You know, classical compute's been around for a while. We all,

we all kind of have something, we all have either laptops

or smartphones or something. So that mystique is kind of gone,

but that, that curiosity

of what is it doing.

And like, like I, I don't

work at all. It's, it's all games to me. I, I play, I,

I play with words, I play with images and I

play with machines and, and I mean I

play a lot, you know, long hours every day. But

for me it's the difference between

what's a hobby and what's not, is, is what gets paid,

quite frankly. But, but, but still, you know,

after, so it's already

almost a quarter to 11pm here, but after

this I'll still be looking at something quantum or

my messages will be quantum.

So, so, so people

coming in to have that, that

I guess, sense of adventure. Because here's the thing also,

and it's only going to happen, it's not only going to happen once, but

the first time is going to be really interesting. So looking at 20, 30

and some point before that, something exciting will hopefully

happen. And that,

that moment when you've got this classically hard

problem and you get this result that

looks like the promise of quantum

just arrived, somebody's going to

observe that first and presumably

start questioning it. You know, what just happened and

is this real? Do we have to run this again? But at

some point you're going to get that excitement of this is

the limit of what we've been able to do classically. And

now this quantum thing, it's not theoretical anymore,

it's not even experimental on a small scale. So

experimentally demonstrating that logical qubits can work,

experimentally demonstrating that this algorithm can

have an exponential speed up. But now

here's our problem and holy

blank, we've just, I don't think I've ever used that phrase before.

Oh well, holy blank, we just actually

did it and, and really just, you

know, within a few years something exciting will happen and then it'll just get

more exciting from there as bigger,

bigger problems. Then there's, you know, some new material and that was

legitimately discovered with quantum computers and here's some

new pharmaceutical and that was legitimately discovered with quantum

computers. And it's just going to get,

well, I mean there are going to be business people that I'm going to, I'm

sure we'll look at the business side of it, but then there should

also be that excitement of, of

it's real, it's happening and we're seeing it first.

So I'm excited for that. I think that's a good way to put it, right,

because like, you Know, I wasn't born when the

transistor was invented, right. I feel like I missed out on the whole. Like you

hear these stories about early days of Apple with Steve Jobs and

Steve Wozniak at the homebrew computer clubs and there was just this sheer

joy and wonder even as a kid with a Commodore 64, right. Like it was,

was just like, you know, like I can, you know,

there was somebody who was on a podcast

who had said how she was amazed that what she typed

or what she did was able to show up on a TV or something like

that. I was paraphrasing and I was like, people, kids today just don't

understand the sheer wonder of that, right? Like, you know, you can, you can hook

something up to a TV and it would show something custom, right? Where, I

don't know, there was a certain, there was a certain

fascination of doing that,

of being able to, being able to

just write something and have it do something.

Right? Like having a computer do something for you. Right. There's a certain magic to

that. You see some of that magic in like home automation stuff, although I think

people are so used to it now. But I, I, I think you're right.

There's a certain amount of wonder and curiosity that, that has driven the

computer industry, you know, for most of its life and, and

certainly the innovation. But you know, once it kind of becomes mundane, people are like,

eh, you know. Yes, seeing that

transition. So I had, I had a gap

between when I first saw what

year was that, early

2000s probably. I don't know if I should name the

software or not, but, but the

speech to tech software. And it was

really crude in the beginning

and I was at a company where the, the president of the company,

owner of the company was trying to use it and of course it wasn't working

that great. So then the profanity starts, but it doesn't understand

profanity. So now it gets funny and we're just

literally all hovering around his desk looking at his screen

as all this gibberish happens. And I think that was the

last we ever saw that. And then so, so

quantum today is, is error prone. But then at some

point you hit that, that mark where I just, you know,

I just spoke into a phone for God's sake. And

here it is searching the Internet. It correctly

interpreted what I just said. It searched for what I

wanted and brought me the result. And that gap of

which is coming of we can't really do

much right now. It's not nothing, but we can't do much right now to

at some point soon this is going to be interesting.

And then verifying did it actually work? And all

the skeptics of verifying, well actually if you have a company you're not going

to publish that. So that's also interesting.

You know, if I think if I had a company I would, I would probably

say I'm not using quantum and it doesn't work and all that kind of stuff

while secretly working on it and try and throw everybody off because

then you have intellectual property and competitive advantage.

If you're my competitor, why do I want you to know that it even works

at all? So that difference between industry

and academia of academia wants to publish everything

and this is what this can do and so forth versus now

I'm a Fortune 100 company. I don't want to tell you diddly

squad. I often wondered about that. Like

a couple of things, right? Well one hot on the heels

of Google's Willow announcement, right.

Jensen Huang was like ah, you know, this is, this is baloney.

I'm paraphrasing, right.

And then all the quantum stocks tanked,

right? And a lot of people kind of said wait a minute, like he's, he's

advanced, he is advantage to trash talk quantum.

And because that makes it easier for him to acquire stuff, it

also like you said, kind of keeps his keep, keeps his cards

close to his vest and all that. And that was interesting. I also think that

the first working quantum computer is probably going to be in some nation

state intelligence apparatus

that we're not going to know about.

To me, just kind of knowing human history, human nature and how

nations interact and that's just kind of how it's going to play out.

I could totally see that being a thing first.

But no, I think that's interesting. You have this tension between people who

want to, people who are incentivized and you know, publish or parish, right.

Like get stuff out there and kind of share the this but also other

people, whether those are corporations or whether those are nation

actors wanting to like not

publicize these advances. I think that's an interesting tension

I don't have. I don't think I've seen anything like that in my

lifetime. At least not that I'm aware of.

Well, I can imagine, I don't pay attention too closely, but I can

imagine AI would kind of be similar. What are

you using AI for? If I'm your competitor, why do

you want me to have any idea what you're

doing? That's, that's better.

So and, and everything else we don't

know. That's totally fair. Actually now you mentioned it.

Augmented reality maybe in this environment over here. And

that helps productivity activity maybe. I, I'm totally speaking out

of place on that. I have no idea. But just imagining that other

technologies, whatever my advantage is, I really

don't want my competitors to know anything.

Interesting. I don't know. Well, I haven't seen any companies

who actually. Well, I guess Nvidia would be the most famous one

with the whole. But that, that was really.

Boy, is that a whole story. Because the, even the whole 20 year thing. Well,

what application are you talking about? Right. So

some things are not going to be done in five years. Like

simulating large molecules.

100 qubits is definitely. I've heard,

I've heard relatively small logical qubit

counts. Mention is like a starting point with,

with a few hundred, we can start doing some interesting things.

But now that again, what company we're talking about what industry

and then a lot of what we're talking about,

including encryption, we're talking about much larger systems.

So when we talk about 2030, we're still not talking about everything,

but still more is coming. Well, again

there's, there's functionality now

and more coming and then more coming and more coming. So, so

I graduated introduction to

more use cases and things that'll turn out

to not work and, and

new things that we're not imagining now. New algorithms that we're not

imagining now because of the limitations of what we have. So

new things will be discovered. You know, when, when ENIAC was built,

nobody was thinking about TikTok, hopefully,

I pray nobody was thinking about it back then. But you know, too late, it's

here. It alarms me that people think about,

alarms me people think about TikTok now. But yeah, no, I mean that's a good

point. Right. And that's just it, right? When, when Vint Cerf and,

and, and everybody at DARPA was working on what became

the Internet. Right. I don't think that YouTube or Netflix streaming or

video streaming was even considered possible. Yeah, right. Or certainly

another. And I remember an early, early

magazine article was talking about, remember real networks,

real audio, progressive networks and like streaming audio over the Internet.

This is like 90s tech. And they were like, oh, this technology is

terrible. The Internet's not built for this. And here we are, I mean we're

having a real time conversation over the Internet across

three countries in two continents. Right. Like,

I just don't think that people don't know what they don't know.

And predicting the future is inherently hard.

And an interesting point about quantum is

that the difference in challenges that are physics and

engineering. So what we generally hear

is that there's no physics

prohibiting what we're trying to do. So it's usually

presented as an engineering challenge. Which means

looking back at Eniac, Commodore 64,

right. I had a 386 and looking at the

evolution of technology, all of this

quantum stuff is more of a question of when.

And then you've got this, these competing

roadmaps. I

question the dates, the years placed on some of these, but

not necessarily the eventual outcome, but

the, the level of ambition. And is it

really practical to go from where we are.

Well, you know, the first airplane

to landing on the moon, that was still a

pretty big leap right there. I don't know what my point was but you know,

it takes time to get from, from

even like the early Internet to what the Internet can do today and, and the

amount of bandwidth that we consume and

all of these things really being. And

then the technology will evolve and what looks possible now

and what maybe looks impractical now, but then the technology will evolve

and then that'll make new things look possible.

Like, like quantum tick tock.

Yeah, like a, a video card. And what did I, I

bought a video card. Yeah, like it. Well this was before,

before they were called GPUs. So just a video video

card for my 386 and you know, to get that little

extra capability. And

what was my point? To go from that to GPUs and

what they're doing today. Right. And it's really just a

matter of kind of like guessing when that'll happen.

But you know, lots of companies working on it so. And then a

race to be first, you know, who gets to, who gets to

uncontroversially be first. That's, that's going to be the big thing.

Who's going to be first, who's going to claim what and who's not going

to believe it and who's, who's going to automatically believe

it, who's not going to believe it. But then at one point to be all

kind of have a consensus of saying wow,

that's, that's something so,

so that'll be exciting. The, at that moment

of we just, you know, we

went from the 386. Well, even worse, you know,

286, 386, 46 Pentium, Pentium this,

Pentium that. I can't keep track anymore. And they're going to keep

improving. Then maybe some mergers and

different capabilities forming there. Then

quantum networks mature and new capabilities there

and then quantum sensors get connected to those quantum networks

and wow, now we've got, you know, quantum stuff all over the

place and now we discover, hey, we can

do this. And we, it's not even

mentioned today, nobody has any idea. And then

suddenly here's this capability now we all, we

plug them. Well, I guess there's still things getting

plugged in, not necessarily satellite stuff

going on with satellite networks, but you know what I

mean, lots of things plugged in and, and we're going to

discover, hey we can do this, hey we can do that. And it's all,

it's all interesting times ahead. No, absolutely.

And a lot of false claims. Of course, you know, we've got hype now, right?

That might get continued to get amplified. You know, somebody's

claiming this, that and the other thing and no, not yet,

that's not it. But then somebody's,

somebody's going to do something really exciting.

Well, it's all exciting, but somebody's going to do something really,

really exciting possibly soon.

And then, and then more, then more people

around the world will get interested because now it's,

it's not quite quantum computers can't do much

is, you know, quantum computers actually can do something

like, like Commodore

64, you could plug the cartridge in the back or, or put

in a five and a quarter floppy. God, I feel old. Why am I doing

this to myself? But you know, you

could play like these games and things like that and do different things. So now

we can actually, you know, do these,

know maybe run these use cases and,

and then economies of scale. When does that kick in? And then

the systems get a little bit cheaper than what? Well you know, we're talking millions

of dollars right now. But the

laptop I'm using for this is

far more capable and far less expensive than the

386 I keep mentioning. That was

four to five times more expensive and far

less capable than this. Low end,

it's a low end laptop, I'm not ashamed to admit it. Much

cheaper, far more, far more capable. So economies of

scale, they'll come down and then we still have the

larger systems coming out. Or again, quantum

networking. How does that change the game? If we can start

plugging them in and then like distributed

computing today, now we have more total qubits available

over, over a quant network

and you know, when the, when will that, when will

that happen and when will be a demonstration of that and Then,

okay, how quickly will that scale up from two

computers doing it to five to 10 to 20? And,

and yeah, all, all. Exciting,

exciting times ahead. Awesome. Well, we're

at the top of the hour. The end of the hour. Top of the hour.

I never got that terminology right, but it's been great talking with you, Brian

Siegelwax, the second least qualified.

I'm telling you. Dosseki, they're looking for a new spokesman. I don't know.

I gotta write that out. I really, I'll put that out there. I really have

to write that down before I forget. Yeah. Thank you

so much again. This was absolutely fascinating. Really exciting,

really exciting. Great stuff. Yeah, you have to be careful. I

can talk for hours. I know, it's awesome.

On and on and on. So. Because it's fun. So this

isn't, this isn't just like, you know, block of time to set

aside. It's. It's a conversation. And,

and if I'm not talking about quantum, I'm reading about something quantum or

writing about something quantum or

badly joking about quantum or, or

that could have been better. That, that could have been a better self

deprecating boy, you know, when you, when you try

to use self deprecating humor and you're not even funny enough to get

it right, what do you call that irony? Like, like extra.

Extra factual.

Yeah. Epic fail. Epic fail. Yeah. Hashtag.

All right, well, with that, we'll let our AI finish the show. And that,

dear listeners, wraps up another mind bending voyage through the

quantum cosmos. On Impact Quantum Huge

thanks to Brian Ziegelwax for reminding us that you don't need to be the

most qualified to ask the best questions or to make the

rest of us feel slightly more qualified by comparison.

From the quantum curious to the quantum committed. We

hope today's episode gave you something to ponder, be it the

philosophical implications of error correction or just

how many monitors one person really needs. Remember,

the path to quantum enlightenment isn't about having all the answers. It's

about having fun exploring the questions. So

stay curious, keep questioning, and if all else fails,

blame it on superposition. Until next time, I'm

Candice. That's Frank. And we'll see you on the next

episode of Impact Quantum, where the future isn't just uncertain,

it's entangled. Don't forget to, like, subscribe

or collapse your waveform by observing us on your favorite podcast

platform.