at least for a period of time, I just want to sit down and properly

invest time and effort in asking questions and

patiently, with my own time, just looking at things

and, you know, be there a little

bit. Just be there with the problem

and with the challenging, with

excitement, with the unknown. That was

for me, the moment in which I realized, you know what, it's

worth it. Yes, it is true that there is a price, but it is

worth it. Welcome to Impact Quantum.

Quantum podcast, turn it up fast.

Candace and Frank blowing my mind at last. Quantum

podcast, they're breaking the mold. Science has got beats and bold. Hello and welcome back

to Impact Quantum, the podcast where we explore the emerging industry and field

of quantum computing. Computing, where it's not going to

require a PhD, although our guest today is a PhD

candidate, so PhDs are always going to be in fashion. But if

you are intimidated by the tech, don't be. I think this industry is going to

need a whole slew of people with different skills and talent.

All you need to do is bring a healthy sense of curiosity. And the most

healthy quantum curious person I know is Candice Cooley.

How's it going, Candice? It's great. Hi, Frank, how are you doing? You doing

good today? I'm doing right today. No snow. We were supposed— there

was a 36% chance of snow. It passed us, so

I was very happy. And we're supposed to get a

big storm this weekend. Big by Maryland standards, not Montreal standards.

Right. So we'll see how that goes.

And I

know we have someone interesting to talk to today. Yes, today we're going

to be speaking with Samuel Haag-Shinass. He is a

PhD student in theoretical physics in— at

Oxford. And how are you doing today, Samuel?

Hi, I'm great. Thank you very much. Wonderful, wonderful.

So tell us a little bit about what you're focusing on within

your PhD. Sure. So at the moment,

I'm doing my PhD in quantum information theory and quantum computation.

My main research at the moment is studying complex systems under the

lens of quantum information theory. I'm also interested in

biological systems and also in applying machine

learning techniques, as you know, artificial intelligence in general, in quantum

computation. So you mentioned quantum

biology, right? Well, I mentioned quantum information theory

applied to biology. Applied to biology. I'm personally fascinated by

quantum biology, so I always get really excited when I start hearing that because

Like I said, we're just, we're just trying to catch up with nature as it

is now. So I think that's incredibly exciting. Yeah. So what

made you, what made you interested in pursuing, in pursuing

theoretical physics? That's a great question.

Well, first of all, I've got to be honest, I'm not great with

experiments, so I'm a bit clumsy. So, you

know, for me, it's easier with pen and paper. Also, I

like to be a bit creative and, you know, explore different

directions. Of course, if you need to design

an experimental setup, you need to focus on that for a long period of

time, whereas I prefer to be more flexible about thinking about

stuff. So that's one of the reasons as well. And I

found myself quite comfortable in thinking for a long time about

abstract things, so that was actually my main reasons

to go to go into the field. Interesting.

Interesting. So what's the— you know, you're obviously currently in

academia. You're still training.

What's the mood inside academia today about quantum computing? Like,

what are the thinking, right? Because I would imagine that once upon a time,

it was largely always seen as a

theoretical type of field, right? Purely theoretical, right?

I would imagine now, is there— there's probably some excitement that

this theory, once wholly theoretical field, is, is

starting to have some real-world applications, not just in computing but biology

and all these things. Yeah, yeah, completely right.

Yes. Um, so of course in academia,

you know, there is a huge, um,

batch of people, so of course the point of views are a bit different.

And heterogeneous there. But to be

fair, I think there is excitement, which is something great. I think

we are really living in a very

particular period of time. The

change is really in the air. And also in academia, I

believe that people are starting to become more and more interested in building things.

Yeah. Which is, you know, of course, saying

something. As you said, Frank, I mean, quantum computing and

quantum information theory were mostly on the theoretical

side for many, many years. Now, now we have the chance to really

merge those two aspects, which is great. I believe it's very fun.

It's exciting. I was going to say, because it's got to be a shift, right?

I mean, even, even an exciting shift is there's going to be some people that

are going to be upset, you know, about it. But, but, but I think overall

and what's interesting Something you said kind

of triggered a memory. We talked to a lot of universities or people who are

affiliated with universities that they actually have like a

quantum incubator or like a startup incubator attached to the university.

I don't know if that's the case at Oxford, but I would imagine that if

they don't have one already, somebody's thinking one up.

You mean an incubator in general for startups, for instance? Right. So like,

for instance, again, I'm I live basically

between, I live in Maryland between Baltimore and DC and the University of Maryland

is, they have a big quantum research

lab and there's a quantum startup incubator there,

I believe, as well based out of, I guess they could put, they

find the MBA students and they match them up

with the quantum researchers. Well, I mean, buildings are there, right?

They're literally across the parking lot from each other.

Or car park, I suppose, if you're in the UK. So,

like, why not, right? And they also know longer

term is that if all they need is 1 or 2

alums to make it real big, and then they get a shiny new building with

that company's name on it and all that sorts of things, right?

It's true, yeah. It's tactical. Tactical philanthropy, I

suppose. Yeah. And yes, the answer to this is

absolutely. In Oxford, there is a huge culture of startups

and by the way, is developing by the minute. Recently I've

been to the Said Business School here in Oxford for a

conference in entrepreneurship in general. It's called

Said, I think Oxford Said

Entrepreneurship Forum. And people really, you know, come together and

talk how to develop things. And there was a panel on quantum technology.

Technologies, and I was the moderator of that panel. Oh, nice. Yeah,

very cool. Really very cool. And I think that if

you want to be really on the line now, you can.

Now you can. People are coming together with different ideas

on the technical side of things, but also on the venture side

of things as well, for instance, or so artistic side of things, such

as, for instance, there is this startup. In San Francisco, I

think, in, uh, no, maybe in California. In California, it's called Quantum Light.

They are developing the first pigments using

quantum phenomena to use lights for arts but also

for technical other reasons. So

this is an example of being creative with what is

going on here now. I think it's very cool. It's really a nice period

to be doing research. Yeah. Yeah, well, because

it's one of those things where research is the

pathway from research and develop to product, path from

research to market is probably— it's never going to be a

smooth road, but it's definitely a much faster road than, than it's been, at least

in my lifetime. Yeah, surely.

Plus now we have also another one, which is artificial intelligence,

right? And I think this will really change. I mean, it would

be silly of us not saying this, but I think that artificial

intelligence is really changing the rules of the game, really. And if you

are able to merge maybe

insights that are mostly on the theoretical side of things in physics,

like for instance quantum information theory and quantum computation, with

a technical tool that will be able to, you know, make

computational tasks faster and more

efficient. Now we are talking about something really interesting, I believe.

Right, right, right. Yeah. So what other emerging areas

in quantum technology are you personally the most excited about?

Quantum computing, sensing, communication?

That's a great question. I know that lots of people are now working in

quantum internet, such as in a broad example,

quantum networks. I think that's very cool

on a personal level also, because as we know,

time in a day is not unlimited. So you need to choose at the end

of the day. Right. I personally believe that

merging automatic ways of

doing learning, for instance, with, you know, machine learning, for instance, which is a kind

of artificial intelligence method

with quantum data, which are intrinsically linked with

noise, because nature is noisy.

I think that's pretty cool. There are nice

people working in this area and I believe that is very

cool. Also working with quantum computers.

Last year I was doing research with the platform of IBM, IBM

Quantum, specifically Qiskit and Qiskit Pulse. I think that's very cool

as well because I was able to work on quantum computers at a

distance on the cloud. You see, this is very cool as

well. So I believe that to

properly answer this question, quantum algorithms, quantum

error correction,

quantum simulation, the merging of artificial intelligence and

quantum computers, quantum data, and because I'm

biased, but I want to say this, applying also the quantum theory

to biological systems as well. Yeah.

Okay. So what do you think is going to be the first most—

well, it's hard to guess, but what do you think is the most promising

application of quantum biology? Is it

medicine? Is it—

yeah. So I do believe that now is a bit too early.

Okay. I think it's very interesting and it's very exciting. But now,

now on the academic side of things,

We will still need time to look into that properly. I

know that some people are, you know, talking about understanding DNA

on a quantum level. Um, other

ones are talking about quantum in searching for new drugs and so on.

So, but now I believe that it's too early to say. Yeah,

so yeah, in the work that you've been doing so far—

I'm sorry, Frank. No, no, no, I was agreeing. In the

work that you've been doing so far, have you come across a

mentor that's really helped you,

or, you know, is that something that you would like to do in

the future? So

is that— this is a great question on, I would say,

several levels. Surely on a human level as well,

yes. I've been lucky enough to, you know, I've

met people that mentored me,

which by the way gave me confidence and a healthy dose of, you

know, believing in oneself. So I

was lucky to find people, you know, older than me, more mature.

I was lucky enough to find fellow students

kind enough to guide me as well. So absolutely, anything

that is one of the most important things for human beings in general, in

whichever field. I would love,

I would love to mentor

people in different ways though. I

also believe that mentorship can be surely the

standard kind, which is great, is super important,

but also, for instance, working and investing time and

effort in being able to express concepts that most of the times

are maybe a bit too technical and a bit

cloudy in a way, but also try to be as clear

and transparent as possible. I think that is a form of mentorship

which can work in both ways. And I think human beings,

as developed as they, as they did, most of the times because they were

able to express difficult concepts to other people.

Yeah. So yeah, that kind of leads into

my next question. So how do you explain what it is

that you do to a non-technical person?

So I sit down most of the time, or I walk in the park

and think about things. But my, my actual work, I'd

say, is, well, read a lot.

Try to know as much as possible in a very focused direction.

So try not to, um, lose track of things, but my

main work is look at the mathematical tools

that could merge very specific insight

in quantum information theory with

architecture that are already being studied in biological systems.

Which is my main research area at the moment. So I'm looking at that, for

instance, as proteins, the architectures of

proteins, the geometry of proteins, and so on, to understand how

to tackle those very specific patterns that present

themselves in nature with the framework of quantum information theory

on the mathematical sense of things, to, you know, maybe be

a bit more pragmatical on this.

I'm searching a model, mathematical model, to

make sense of how information can be transmitted

in your cells, for instance. Information is

not a trivial concept. We can see

on a very— maybe this is just a way of seeing information,

but information is what is needed to make a decision,

to follow a different path. And of course,

a multitude of different paths means

complexity, and complexity brings a lot of nice things.

So this is my way of expressing, as the best as I can, what I

do. Interesting. Well,

and bio— biology is inherently

a, um, a, um,

complicated field, right? You know, it's, it's kind of One of the best ways I

heard biology explained, I didn't come up with it, it was some

famous physicist said it's basically nature

coming up with a way to beat entropy, was kind of like the way,

which is true, right? Things kind of decay, and then about the same time

I heard that quote, there was one of the Doctor Who episodes

was, I think it was the Doctor,

I think it was David Tennant, that said something, and we're talking to someone in

the UK, right? So I think that's appropriate, right? He said something about

that life is just a way is nature's way of keeping meat fresh or something

like that. And I thought that was, you know, the fact that those

two memories have been fused in my brain, I think is kind of funny. But

you're right, I mean, these are complicated chemical

reactions that are, you know, by and large,

as far as we know, not very common, right? Like, so like what—

Yeah, actually quite rare, yeah. Right, and I mean, we don't know of any other

life outside of this planet. And, you know, although, you know,

life does find a way, right, quoting another movie. You know,

where, you know, we go to the ocean vent. I was in high school when

we were talking about, you know, in biology, and,

you know, literally that week or whatever, they discovered the life

forms around the volcanic vents on the ocean floor. It's like, you

know, like, there's no reason that we would have assumed this would have existed

a year ago. And, you know, like, she's like, you know, next year, we're going

to get all new textbooks, right? You know,

um, so it's interesting because biology can still always throw us a curveball like that.

Yeah, yeah, yeah. Sorry, I, I can go on a tangent, but

no, no, I, I completely agree with you. I think,

um, biology, um, is really— it really is a

manifestation of complexity, but not only

complexity, also order. Because we know

that if we have chaos, for instance, that can be very useful for us,

right? Also, maybe nothing will emerge from chaos, right?

So it's difficult to say I have something very complex and very

chaotic, but then something, you know, with order. And,

you know, um, I'm saying vision for, for lack of better wording, but with a

plan, which is, you know, the evolution of life. So I

believe that there is something really interesting to look at

in biological systems. And I believe that quantum information

theory, or on a broad, you know, in a general sense,

the transmission of information that could rely on

quantum phenomena, really is

a remarkable concept to apply to biological systems, which might be wrong,

but I don't think that's wrong.

And I think that really something interesting is going on there.

Yeah. Right. Could you share

more about the most interesting challenge you faced in your

research on multi-qubit

interaction? So you

mean my main project that I did on the IBM platform? I

see. Yeah. Well,

surely one challenge that I was not prepared for is really

going into something unknown, at least to you. In

university, in school, university, usually

people have the answer to your questions, right?

But in my research on the multi-qubit

interaction, on microwave interaction, and IBM platforms,

there was nobody with answers to my questions, really.

And I do remember one time that I really, you know, start,

you know, asking questions to people in my group and also my mentor.

And at some point, smiling, they said, I don't know, should figure it

out. And that was

challenging for sure, 100%, but also very

Very exciting, because I really understood in that moment

that I was doing something exciting, adventurous. I don't

really know where I'm going with this, but I was

navigating something that was not known.

So what open problem in quantum information

theory fascinates you the most right now?

I'd say quantum information theory applied to biological systems. Yeah.

Understand information transmission with quantum information theory.

Interesting. Very interesting.

How close— I'm sorry, go ahead. No, no, go ahead. How close do

you think you are to understanding the true limits of

quantum advantage across different algorithms?

Me personally? Yes.

I'd say pretty far, but that is the exciting part.

Yeah. Okay. Yeah.

So can you tell me a little bit more about the concept of quantum speedup?

You mean quantum speedup in a sense of advantage with

quantum? Yes. Yeah.

So as a concept, there are some algorithms,

some remarkable ones and very well-known ones. One

is the Shor algorithm. They

theoretically proved that with quantum

phenomena, the two main ones are entanglement

and superposition.

You are able to devise algorithms that are able to do

some computational task faster than

the classical computer,

the, you know, a supercomputer, which is classical. Of course,

I'd say that most of— I don't really know, but I'd say that most of

the community now believes that with quantum There will be

advantages, right? But

the fact is that we still do not have a concrete

proof of this, at the best of my knowledge at the moment.

Yes, we know theoretically speaking that those algorithms are true and they

work, but still we do not have a device that is indeed able to

prove that those works. Even

though I'm not updated on this. I do believe that Google

did something nice recently, but I am

not fully aware of the dynamics there.

Right. I think it's fascinating to kind of see how

this is evolving, right? Because quantum

biology, I think not that long ago, was just thought of a weird

branch of biology, maybe a weird branch of

physics. But now you're seeing

startups being founded in that space. So people are willing to put—

now, has it been proven out yet? I think that's still up in the air,

but people are willing to put money down, money where their mouth is, as

the old saying goes.

One of the things that I kind of have in my head, because it's cool,

because we get to talk— doing this podcast is awesome because we get to talk

to experts. And every time we think we got something figured out, we talk to

somebody and it's like, well, There's more to it than that. But it's my

understanding that a big advantage of quantum computing

is that it's based on the same

principles which ultimately underlie every

or nearly every chemical

interaction, which a lot of things tend to hang off of

chemistry, biology, manufacturing,

right? Tend to rely— tend to hang off of

chemistry, which itself— chemistry kind of hangs off of physics, which itself

ultimately through a lineage does connect back to just raw

mathematics. Um, which I think— is that

one of the things? So anything that has some kind of chemical process is,

is very likely to see a speedup from

quantum computing?

Now, that's a good question.

So if I understand your question correctly, you're saying, given the

evolution of quantum computers, the development of quantum computers,

maybe since, you know, developing molecules or, you know,

chemical reaction is indeed following

quantum rules, maybe using devices that

rely on the same rules will allow us to

have better insights and a better

simulation of what's going on with chemistry and

molecules and so on. Was that the question? Yeah, I

believe so. Yeah, 100%. Not only that,

not only that, I also believe that

merging quantum data, which

is possible to obtain with quantum computers, right, is different

trying to obtain those data with molecules and

atoms and so on. And, you know, chemical reaction is

difficult because it sometimes is very difficult to probe those phenomena,

surely on a quantum level. But if you are indeed able to do

some simulation or computational task on

a device that will follow the same rule, this means that you also

can have a multitude of data, way,

way more than before. Now, if you find

intelligent ways of studying those data and

very efficient ways of studying those data, such as, for instance,

applying artificial intelligence methods— and machine learning, by the way, is,

you know, learning of something from those data

by the machine. The machine is able to do this. I think

this will be one of the main interesting parts of this

new development. Yeah.

Interesting. Yeah. What do you think

students who are entering quantum research today will need

that wasn't on your radar

when you initially started?

Oh, that's another great question. And I believe that

in a way my answer would be a bit

boring in the sense that expected,

like everything. No, you— I think you, you can— you kind of need

to have a plan, of course, in order to have a plan.

You need to have data, you need to know what's going on there, and you

need to know, maybe have some examples of other people

doing that and so on. So in my

case, I was able, I was lucky enough during my,

my master to

add courses on quantum computation and quantum information.

But those courses were mostly theoretical.

Chance to have examples from people.

So surely I'd say

try to understand what people are doing, trying to

understand at the best of your abilities, not only on the

technical side of things, but also on the business side of things.

Because in, in this time, I think it's also very

useful to see, to track down the development of

small companies or startups. Usually, if

there is investment, it means that there is potential, and

the presence of potential means that, scientifically speaking, something

interesting and potentially manifesting itself

in a short period of time is there. So I will— I would

first of all study the technical aspect of things, but also the business

side of things, and most importantly

maybe choosing 10 people and just ask

questions, people that are working in very specific fields in quantum

and just ask questions and as many as possible.

Yeah. Awesome.

So it all goes back to curiosity, right? Curiosity leads to

questions and then that leads hopefully to better wisdom.

Yeah, I think curiosity is well, very important,

always very important. But

also, in a way, be hungry as well,

because you can be curious, but in a way, you know, sit

down and just be

not lazy, but not being proactive. So I think

that being proactive and curious is something that is quite important

because you can Surely understand a lot, a lot in theory,

but also in this field, I'd say especially now,

understanding the pragmatic side of things is important as well.

Yeah. So what would be— what are some of the biggest challenges

in experimentally verifying quantum information

flow inside of biological

systems? That's a,

that's a good question. So first of all, it's not easy

to observe quantum phenomena, which is

also kind of funny to say this because,

um, we know that in quantum mechanics there is a principle,

um, uh, Heisenberg principle, which is the uncertainty one

that states that you cannot observe something

like a particle, knowing with exact precision at the same

time its position and its energy.

This is something very specific of quantum mechanics.

So in a way, we could say that this means that

observing quantum phenomena is tricky in general,

more so if you're trying to observe those quantum phenomena in

biological systems, which are complex by

themselves. Also, you need to be careful

because in observing those kind of phenomena, maybe your

setup will possibly destroy the biological system as well.

No, no, I'm not saying that this will happen in any

setup. I'm sure that people are, you know, developing something

very, very precise and very refined as well. But this

can be a possibility as well. We know that biological systems possibly

are also fragile. So there are lots of challenges

there and from different sides.

And we also need to remember that the complexity in

biological systems is remarkable. It really is remarkable.

Also, one of the main

statements against quantum biology is that

biological systems use— most of the times work at the high temperature.

Surely compared to the classical experimental setup that will probe

quantumness. Also,

um, they are messy. They really are messy. There is a lot of things going

on there. There are a lot of things going on there. So it really

is challenging. There are a lot of things to be studied there.

How am I— oh, go ahead. No, no, go ahead.

How might quantum information theory help us distinguish

genuine quantum biological phenomena

from classical explanations that

might only appear to be quantum-like?

That is an amazing question. It really is an amazing

question. And of course, is a question

that I'm asking myself quite often now.

I need to think about this for a second, but surely—

well, surely there are some phenomena

that are indeed quantum. A good example of

this is superradiance. Superradiance

is a cascade effect,

which we know to be only quantum.

To give a maybe brief intuition of this, let's

say for instance we have 10 photons.

Something will happen, some sort of reaction will happen,

and at the end of the process we'll find ourselves with

15 photons, right? Which is weird.

Now, this is super-radiance. It's a cascade effect that

will produce an

interesting number of photons in a very specific

setup. This is due to quantum phenomena.

Um, for instance, if you— if we observe this in a

biological case, we know that this must be quantum.

So I believe that my, my point here, to be, to be maybe a

bit more general, is try to, at

the best of our abilities, to find

something that we, we are sure

that is quantum, and we search for this.

And we also try to develop mathematical tools

able to probe interactions that are due to

quantum phenomena. If I may, I don't want to be

maybe too technical, and if I am,

I apologize. But

one thing that can be done in quantum

information theory is to

propose boundaries, mathematical boundaries. Let's say, for instance,

I am driving and I have

10 gallons of gasoline. Now, I do not know how much

gasoline my car needs, but I know that at

some point it will stop if I, you know, I do not refuel

the tank. Refuel the tank.

Now, um, in quantum information

theory, it's possible to prove that quantum

phenomena can be used as energy. To do

some activity, such as, for instance, yes,

it is true that I have 10 gallons of gasoline,

but it is also true that if

my, my engine is working on quantum

processes, it can use

some other resources that I do not know, but it can.

So that if my engine is not quantum, is

classical, it will maybe cover a distance x.

But if it is quantum, it will cover a distance x

plus something else. Mathematically speaking,

this means that I'm breaking those boundaries. I'm actually going beyond those

boundaries. And if this is the case, now I have quantumness.

This can be a tool that can be used.

Interesting. Okay. It's just so much

to unpack in this space. I, I have to say I'm impressed that,

you know, with your academic background. And

I mean, what, what was the moment for you that made you say, I want

to get a PhD in physics? Like, what was that

moment? Because it's probably not a decision that anyone would take lightly,

but let alone, let alone stay through graduate and post-grad

and, you know, kind of at the higher level, right? Like

what, what was that aha moment? Like where I'm like, this is what I want

to study. I believe that it was the

16th of April, 2025. Something. Sorry, I

love that you know exactly when it happened. Exactly the day. Yeah, I'm not

joking actually. It's fun, but I'm not joking.

Surely in the middle of April

2025. Yes, it's not a choice that I think— well, for

me personally, I didn't take it lightly. I thought

about it a little bit, and of course I'm saying a little bit, but I

mean quite a bit.

And first of all, I believe that sometimes you just need to be brave. You

just need to be brave. But

also I understood that for me

personally, if in 10 years' time

I thought, okay, I'm working on something and I want to

go deeper into this task, I want to know more about

this, but then I imagine somebody telling me,

yes, but this was the, you know, concrete example

that I had in mind, we are not paying you for this, you just need

to do this, this, and this. And I think that's

completely fine, but for me as a

person, that was not sitting right with me. I was a bit uncomfortable,

and I wanted to have time, at least for a period in

my life— I don't know about the future, nobody knows really, but I

surely don't know about the future— but at least for a period of time, I

just want to sit down and properly invest time and effort

in asking questions, and patiently, with my

own time, just looking at things and, you

know, be there a little bit. Just be there with a little bit, with the

problem and with the challenging, with, with

the excitement, with the unknown. That

was for me the moment in which I realized, you know

what, it's worth it. Yes, it is true that there is a price,

but It is worth it.

Yeah.

Interesting. Were you into math and science as a kid? I say this as

a parent of 3 boys. So how do I—

my oldest is already on the robotics kind of mechatronics path.

So yay me.

My youngest is 3, so it's a little too soon. To tell,

but like what, what encouraged you to get into STEM and

more importantly, stay in it? That's a

great question. And I believe that the

proper answer will not be short, will not be brief. So I'll

try to be as concise as possible and to sum it up.

So to answer your first question, I was

into math for sure. But I also

was a lot into philosophy.

I always loved to talk about philosophy, but

really ask questions and really try not

to be in a rush of answering those

questions. And if I didn't know something,

I, I just asked more questions to other people, read more books and so

on. Um, and I hope that this answers your question. Yes, also mathematics,

specifically numbers. I always liked numbers quite a

lot. Um, logic for sure, but mostly philosophy and numbers.

Yeah, interesting. Yeah, and they're not mutually exclusive. I think a lot of people think

that philosophy, um, and, and, and mathematics

are, are opposite ends of the same spectrum, but if you look at the great

names in mathematics, right, they were

also philosophers. Descartes comes to mind

immediately. I'm sure— Gödel is a good example of

that. Wittgenstein was not maybe mainly a mathematician, it

is true, but surely was working very closely with mathematics, of course. Right,

right, right. So that's for sure, that's for

sure. Even though on a broad sense, I do believe that things tend

to be more interconnected than expected on

a general sense. To answer your third, the second

question, hmm, so it was not easy. It was not easy,

and for me it was not a linear path. So surely in

high school I, I knew that I wanted to be a

scientist, right? At university I was a

bit tired. Also, to be

honest, I, I also kind of lost hope

because I, I saw some, some things as a career path that I didn't

like. Right. Because, you know, you want to also have kind of a nice

life for yourself. Sure. An exciting one. Right. And

I noticed that most of the times looking at people, I felt

that that's kind of boring. You know, it's expected.

It's— I know how your life will

unfold. So after my bachelor's degree in physics, I kind of said, you know what,

I want to go into something more exciting. I want to go into

robotics. Right. There is a very nice university, uh, in, uh,

for robotics in Italy. So I applied and,

you know, I, I was admitted the day. And I

was super, you know, stressed out about the admission

process. Uh, the day that I received the admission letter, the very

day when I received admission letter saying

congratulations, in that moment I understood that I, I wanted to do physics. Not

only I wanted to do physics But the very same day I met a

friend of mine and he was going to a very good university in theoretical physics

in Italy. And I didn't know about this university. The very same

day I talked to this person and I decided, okay, you know what, I will

do theoretical physics. And I went to Torino.

So my path has always been like, you know, maybe I will

do something else now. Well, maybe not. Then

after my graduation from my master's, I was really

unsure of doing a PhD or not. Then again, I said, you

know what, yes, let's do a PhD in theoretical physics.

So it's not really a linear answer, and I apologize for this, but no, no,

no. I mean, I think

people assume that success is a

linear journey. It's not. Like, and there's plenty of like self-improvement

gurus on LinkedIn that'll post like memes of like, you know, the how you think

it'll be and like how it actually is. It's true. I mean,

I— so the reason why I'm asking about the kid stuff, right, isn't just because

I'm a dad, but I, I recently— I didn't— I don't think I told Candace

this yet. So I found this, or I did tell you, that, that

there was this funky documentary

about— so first off, I was asked, I was asked for my day job to

come up with the— an abbreviated timeline of AI research and milestones,

right? And that got me thinking about when I was in high

school or even when I was younger. And then this memory came to my

fore of, it was a

TV special. And I always, I remember

it was only on once because this is before we had cable. Like this

was BC, before cable TV.

And this was, I don't even think we had a VCR at

that point. So like, it was back in the day, back in my day when

you watched something that was on TV, that was it. She missed it, you know.

So I only ever saw it once, but I remember some

of it so deeply. And it's called, it's a documentary, it's on YouTube, it's called

Computers Are People Too. It is filled

with retro kind of synthwave feel, 'cause it came out

in 1981, 1982, right? So it is definitely a product of its

time. But that was the first, that was the

first thing that sparked my interest in computers, because it showed

computers If you watch the whole thing, and it's an entertaining thing to watch, but

if you watch the whole thing, if you could get past the synth music and

kind of like the overdoing on the '80s and late disco era

thing, sit through that because after the first 5 minutes it gets better.

But I look at that and I remember now as a kid

watching, like, because it showed how to use computers in

creative sense, right? So this was you know,

the dawn of computer graphics, the dawn of electronic music, right? And

like, I remember sitting there, like, I was watching it again. I'm

like, that's where I first saw it. Because I remember he has this thing where

he has a dog bark into a microphone.

Just bear with me. And he had it hooked up to a synthesizer, which to

us today, like, you know, I is like, you know, of course

I probably have 100 apps on my phone that could do that. But then

It was completely revolutionary. And you see the guy had to use computer setup and

things like that. So it's the weirdest things that'll inspire you. Because

I remember, I guess it would have been about 8 or 9 years later

when I first saw a real synthesizer on like

a Mac, you know, the little Macs. It was like the Mac Classic or

whatever. And I was just blown away. I'm like, oh, so this is now

like something you can actually get. And actually, a kid

down the, down the hall for me in my freshman year

dorm um, he had like a Mac hooked up to his thing with a MIDI

card and all that. And I was like, you know, wow, like not only is

this— was this real, but like, you know, it's actually kind

of affordable to build one yourself or get this together. Like, that was for

me. And I think from that moment on, I always approached

computers not so much as mathematical devices but as, as instruments

of creativity. Obviously, there's a lot of

math between point A and point B. And

also too, I think if I could go back in time and tell a younger

version of myself, because the way— I don't know where you grew up or

what your first introduction to math was, but when I was a kid, I despised

math. Seriously, I despised it. Part of that was me, but

part of it was the way it was taught, and part of it, quite frankly,

was the teachers. I just think

that I don't know what would be better, but I know that things could be

done. Things could be done better. And

thankfully, my two older kids don't have that math kind

of annoyance that I did. So I also don't say

it around them that I hated math at their age because that would give them

a nice little out to say, "I hate

math." Because I think

Again, like, again, it's multi, multifaceted, right? It's not a straight line, right? I found

I got into computer science because as a kid we had a Commodore 64

and I wrote video games for it, right? And I fell away

from it because I, my family gave me the choice of being a

doctor, lawyer, engineer. Software engineering was not yet a

term that had been made, can be coined

yet, right? So when I, when I, um, and I actually switched to computer science

because At the time, I had an ROTC scholarship,

and because of the scheduling of that, I couldn't take all the chemistry classes I

needed to take. So I took a computer class,

and that's when I realized— I was talking to the professor, even like, wait, you

could study this and you can have a good career at

this? No, really? And it sounds

funny, right? And to 2025, or I guess as we're airing this,

2026 years, that sounds absolutely absurd. But this was 1991. It

was a different era. So I encourage

anyone to watch that documentary, because

it's kind of funny. And it's also very relevant to like a big theme in

it is, you know, the idea that if you're an artist, computers are going to

put you out of work, which I think is oddly

relevant conversation in 2025, 2026, right?

Because, you know, if you watch any of our live streams, actually season 4's

intro song was actually AI-generated, right? So the intro song,

you've heard AI music, at least today. You've probably heard another

before and didn't know it yet. But I think it's an interesting

thing. And again, I did meander. So, you know, meandering is kind of what we

do here. But no, I mean, that's a fair answer, right? Because

like, and I want to encourage anyone who's listening, like, you know, oh, you know,

I didn't do this. I became an electrician or electrical engineer. And I can't get

into quantum. That's nonsense. I was going to use another word, but we like our

clean rating on iTunes. That's

nonsense because you're going to need someone that knows how

to— you're going to need the physicists, obviously, doing kind of

the physicist-y type things. But you're also going to need

people that will rack and stack these things, plug them

in, make sure if you're using a hypercooled, like down

to 0.5 Kelvin, you're going to need HVAC techs,

right? You're going to need people to sell the solutions, right? You're going to need

people to market the solutions. You're going to need a village. I hate

that term because it's so cliché, but you will need a quantum

village. Sorry, that was me. I've got to get off my soapbox

now. I do believe that is completely true, but also I think

that almost in

every arena of human development, and when I say human development, I

also mean development of tools by

humans, right? Um, you will

see that will be, uh, there is a

meeting, uh, merging of people from different

backgrounds, from different views

as well. Um, different skills. Of course, you can have the same background or

different backgrounds and having different skills, or the

same skill even if there are two different backgrounds.

So I, I think that

building meeting points inside of something on the technical side of

things as well is very important. So I think that, I

think maybe now more than ever, of course, we don't know about the future, nobody

does. But I think now more than ever is a

really good time to try to be

as different as possible, quote

unquote. Right. Yeah.

Right. I mean, that's a fair— that's a fair statement,

right? Like the ability to—

yeah. Also being flexible, being fluid. Is very important as

well. The ability to

adapt. This is something crucial. And at some point you

mentioned from, you know, talking about the past,

saying that, you know, I didn't really like math. Maybe it was me, maybe

it was the, you know, the teacher or, you know, the overall system.

But I do believe, I do believe, and that is something

that I felt quite

recently, that each and every human being has their own way

of learning stuff. Yes. And I think

that schools and university are doing a good job with

a maybe a path which is

common. But I also believe that human beings also need

something else and different, very specific,

very tailored. And

parents can do this, um,

but on a general level, I think that we need to think a bit

more about how to mentor

people independently of age as well. So I

think that is a big deal as well, just to respect it.

Yeah, it is a good way. It's to respect the fact that we, that we

don't all think the same, we don't all learn the

same. And, you know, what might

be the predominant method right now of teaching

something, it might not be effective to the students that

are trying to absorb it because they just— yeah, they don't think

maybe conventionally. And more and more children are

not thinking conventionally as it stands.

So, yeah, education has to change.,

to meet the greater needs of, of, of, of the community that they're

trying to, you know, influence and educate. I totally agree. Well, I

also think too, there, there was a long, there's a long-winded

like TED Talk I saw where it was basically the

current educational system is basically a byproduct of the

industrial era, right? The guy goes through this whole flowery thing. You've probably seen

the video in the US. In the US for sure.

The US has got a lot of— anyway,

but the year you graduate is almost like a manufacturing stamp, like

the way he phrases that, like, and everyone's at the same level at the

grade and that sort of thing. That may not work in a

flexible career type, postmodern future, right?

I mean, when I was in university, there was one artificial intelligence class,

and that was Prolog, right? You probably never heard of Prolog. Most people

have not heard of Prolog, right? It was kind

of this, um, it was a language that's effectively dead. I'm sure I'll get hate

mail by saying that, but, um, but at the time it

was cutting edge, right? So the whole notion of having a career

in AI is, was very much, again, very similar to physics in that

way, right? Like, for, it was a research thing for

for decades. And realistically, with not a lot

of commercial applications. And, you

know, there's a video, if you search on Yann LeCun,

you know, the big, one of the big dogs of

AI today, was a humble grad student in NYU, and he had

worked on the MNIST problem and had it on a neural network,

right? Like, you know, and there was a video of him in a very kind

of early '90s haircut in front of an

old DOS x86 computer, showing off

his hand— the handwriting

recognition stuff, which at the time was very cutting edge. But now we kind

of look back at that and laugh a little,

right? But again, I probably think that as he was doing that research, he

wasn't thinking that he was going to be— certainly, I don't think he was

thinking about being the

joining Facebook/Meta, let alone leaving kind of Facebook/Meta, right?

Like, so the path is linear. Like, and if you look at the most successful

people in history, it generally does seem to

be linear. I'm not linear, a linear. Yeah, I understand what

you mean. Time for me to get some more coffee, apparently. I was gonna say

it's time for another caffeine, caffeine boost, right? But we are coming to

the end of the hour and we want to be respectful of your time. This

has been an awesome conversation. It's been great.

Where can folks find out about you? And how does it work with

a PhD program? Do you— because I've known a

few people that kind of take a decade or so

to do their dissertation. I don't think you're on

that path. But like, how does that work? You have to— you take your classes,

you do your research, and then you have to write your thesis and then go

through the process of presenting and defending it? Kind of, but not

really. So I'd say that there is actually a difference in between how people

do a PhD in the US and overall in Europe,

I'd say. Right. So at Oxford, the PhD

on average lasts between 3 to

4 years. You, on the first— in the first year, you also need to take

some classes, but just a few

of them. And mostly is research. It's conference, it's talking

to people and talking about ideas, which is, I believe,

amazing. It's great. Cool.

Yeah. That's great. That's great. So

is there anywhere that we can send people who want to know more

about you? Well, absolutely. What you're working on? For sure, there is my LinkedIn profile,

which at the moment is the platform that I

update the most. So, I'd

say LinkedIn now is best. Okay.

Yeah. Cool. Awesome. We will send folks your LinkedIn profile, make sure it's in the

show notes. And any parting thoughts, Candice, before we play the outro

music? Honestly, this was fascinating. I really appreciated your perspective. Thank

you so much. It's really helpful. We have so many people that want

to understand the journey and what excites them to

pursue more. And I think that you answered the questions brilliantly.

Thank you. Thank you, and it was amazing. My pleasure, really.

Awesome. Thanks. The multiverse is skanking, skanking in time. Black

holes are wailing in a horn line so fine. From Planck scales to

planets, they're connecting the dots. Candace and Frank, they're

the

cosmic hotshot. Quantum podcast, turn it up fast. Candace

and Frank blowing my mind at last. Quantum Podcast,

they're breaking the mold. Science and Scott Beats,

it's bold and it's gold.