April 15, 2025 • 37 mins
Quantum computing is no longer just a futuristic concept, it’s quickly becoming a practical reality. In this must-watch panel discussion, three quantum pioneers dive deep into the real progress being made and what’s coming in the next few years. From breakthroughs in drug discovery to tackling cybersecurity challenges, quantum's first impacts will be felt in unexpected ways. Get ready for an eye-opening conversation that cuts through the hype and gives you the insights you need to prepare for this technological revolution. Don't miss it!
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Hello everybody, I'm Alex, ceo and founder of Mars
Days.
Welcome to another episode ofLife on Mars, and in this
episode we bring you the secondpanel of the Corporate
Innovation Summit, incontinuation of the previous
episode.
In this case we discuss quantumcomputing, and this is
something that I had to preparea lot for, because I'm far from
being an expert, but luckily wecompensated with having three
(00:23):
real experts on quantumcomputing on the panel.
So, without further ado, let'sjump right into this episode.
Time to move to the next panel.
As I mentioned, we are a littlebit behind on time.
I'd like to welcome the nextset of speakers to the stage
(00:45):
Sergio, dorit and Victor.
Please come to the stage.
Big applause for them.
We got too many chairs, but wecan sit more spaced.
Let's leave distance betweenyou.
It should be distance or not,depends.
You came last year.
(01:05):
You decided to repeat this year.
I'm not sure why.
I'm not sure too.
Speaker 2 (01:09):
I'm still questioning , let's start One, two three.
Speaker 1 (01:13):
It works, thank you Well, thank you for being here,
sergio.
I wanted to start with youbecause I have the confidence,
and actually you say in Spanishwe say that confianza de Asco.
So we've seen that quantum issomething that people say every
year.
This is the year for quantum,right, obviously, 2025 is the
(01:34):
year for quantum, unless it was10 years ago.
But we have seen this demo byKusentroid.
We're seeing other examplesbeing shared at Mobile World
Congress, and yet we don't havethe hardware required to run the
real problems.
And we're sending stuff toquantum computers but they don't
solve real problems or problemswe could tackle with quantum
(01:54):
computing.
How far are we from that,especially taking into account
the big news from last week?
Is it on?
No, this one, then you use thisone.
Speaker 3 (02:03):
So this year.
Speaker 1 (02:03):
it is truly no, this one, Then you use this one.
Speaker 3 (02:05):
Oh yeah, so this year it is truly the year of quantum
.
The UN declared it last year.
Speaker 1 (02:10):
So it's the guy with the quantum newsletter, yeah.
Speaker 3 (02:12):
I do own a quantum newsletter.
We call it the quantum piratesnewsletter, if you're interested
in that.
I came to speak about my book,of course.
So this is the year of quantumofficially.
The UN and several otherorganizations have declared that
like that, and that's becausethe amount of development and
milestones achieved in the lastcouple of years or so have been
(02:34):
quintessential for what we areseeing today.
The past five years or a decadehave been already either solved
or are in the way of beingsolved in terms of scalability
of the devices or errorcorrection of them, of the
devices.
Moreover, we have a lot oftools, a lot of research, a lot
of government investment, andwe'll talk about cyber security
(02:57):
as well and the importance of,again, governments and companies
to tackle the challenge ofcybersecurity and the risk that
quantum computers put to that.
Now, the quantum computers thatwe have today we have them, they
exist, and Carlos showed howyou can send stuff to some of
these quantum devices.
They're still pretty small.
(03:19):
So if you take a productionworkload with the sizes that it
has, many of these devices willnot be big enough or robust
enough to run them.
If you take a productionworkload with the sizes that it
has.
Many of these devices will notbe big enough or robust enough
to run them.
But that doesn't mean that youdon't have to start today,
because finding the use casesand coding your data, finding
how to use them and learning andupskilling your team is quite
of a challenge.
(03:39):
So, yes, this is the year ofquantum, I would say.
Speaker 1 (03:43):
In fact, we could be nerding out about whether the
changes from physical to logicalqubits are going to affect the
industry and whatnot.
I don't think this is the righttime, especially given that
it's like beer o'clock, but I'dlike to get your vision on why
corporates have decided fromgoing like super private and
(04:05):
secretive about their strategywith new technologies because
back in the day, you know, oh,we don't want to share, we don't
want to share, we don't want toshare.
And I was like, yeah, here wehave, we have got everything is
open source right now.
So why did that change?
And uh, what?
What are you doing in terms ofquantum at modis and open source
as well?
Speaker 3 (04:22):
let me put put it this way how many people do you
guys think work in the privatesector full-time in quantum
computing?
Would you say a number, threepeople, that's really.
There are a hundred companies.
Speaker 1 (04:36):
You're part-time.
Speaker 2 (04:37):
I'm part-time, but there are a hundred companies,
at least, that have quantumgroups.
Speaker 3 (04:42):
So the best guess?
Obviously this is a guess, butthe survey that I've been making
with a lot of people fromdifferent companies, big and
small, is around 5,000 people,and there are a handful of
companies with a few hundredpeople, such as you guys in
Multiverse, IBM, AWS, Microsoft,have robust quantum teams on
different research, but that'sstill around 5,000 people.
(05:04):
Maybe I fall short.
It's 6,000.
Maybe 7,000.
Speaker 1 (05:07):
That's still peanuts, Unless you count quantum
enthusiasts on LinkedIn, whichis 5 million people.
Speaker 3 (05:13):
Well, yeah, yeah, it's almost as many as chat GPT
experts.
Exactly.
So, with that amount of peopleand with something that is still
getting into the maturationstage, sharing and building a
community is fundamental.
We all learn from each other,and it starts from academia,
from research, goes into theimplementations and something
(05:34):
that Greg mentioned before on AI.
That is absolutely true as well.
For quantum.
Fine, you have that.
What are you going to use itfor?
What are the use cases and howthese use cases actually touch
on the quantum device?
It's not just a high leveltextbook problem, but my data,
my way of solving it and thespecific use case that you're
(05:55):
solving, especially in finance.
Speaker 1 (05:57):
Dorit, welcome for the second year of thank you I
have before that.
Speaker 2 (06:01):
the first rule is to spell right the name.
Qubit is Q-B-E-A-T, but I'm ina superposition between cyber
checkpoint and qubit and quantum.
Speaker 1 (06:16):
My question is going to be so.
There's one news from last year.
Last year you were Onlycheckpoint, yeah, only
checkpoint.
I mean, besides all the otherthings you do, but no qubit
ventures.
So can you tell us about whatis that?
What is your investment thesis?
Because it's very difficultsometimes to understand the
investment thesis of VCs.
But now, in quantum, how do youbuild the thesis around that?
Speaker 2 (06:38):
Excellent.
So we start with the questionhow many years to an advantage?
So whether every year is thequantum year is because you have
to prep for it.
But I believe advantage is two,three years from now.
Two, three years is still good.
Advantage means that you couldnot this year.
You could still run it, butadvantage mean real advantage to
(06:59):
some application.
Second part is that not onewinner takes it all.
If you want to invest inquantum, you have to have a
portfolio.
So we're going to have aportfolio of multiple elements
of this to kind of facilitatethe industry to happen.
We also believe that it's stilla phase where early stage
(07:22):
solution has space to impact.
So we are going to invest inearly stage quantum focused only
, and we think that quantum isgoing to change the world and
that's exciting.
Speaker 1 (07:36):
How do you balance your investment thesis between
universal versus specializedquantum computing?
Speaker 2 (07:41):
What do you mean in that sense?
Speaker 1 (07:44):
In the sense that you know one of the fields that we
have seen in AI for instance is,at the very beginning,
everything was generalist right,and so people were trying to
tackle generic problems withgeneralist AI.
Then down the road we saw orlike the sector saw that
specialized LAMP, specializedmodels, specialized tools were
(08:08):
much more performant, less errorprone, and all of that in an
ever-changing landscape withquantum that's so unstable.
And then all of the sudden,microsoft comes and shakes the
entire industry.
How do you balance yourperformance with that?
Speaker 2 (08:18):
I think that at early stage in quantum there would be
very few generalists.
There is no way to begeneralist in quantum in early
stage.
It's going to be crazy.
Even picking two of the 10modalities is not something that
multiple people will understand.
So every early stage is goingto focus on something, either on
(08:44):
a qubit modality or on acomponent or on software.
On aspects, very few would beattempting to be very generalist
and that's going to be amistake.
Now the bigger guys may betrying to be generalist, but our
thesis is that still there isroom for early stage
technologies to influence thespace because it's very much
(09:07):
evolving and you could seetechnologies that are new, that
are jumping over previousgeneration of technologies.
Speaker 1 (09:14):
Still, In AI.
Two and a half years ago moreor less, we saw the breakthrough
to the general audience withChaiGPT.
Chaigpt accelerated.
Chai GPT kind of likeaccelerated things because it
allowed the, it crossed thechasm in a manner of speaking
right.
How far are we from seeingsomething like this in quantum?
Speaker 2 (09:36):
So I think this is really the question of what the
advantage comes to be.
I said I think there would bean advantage in two, three years
.
It's not going to be theapplication that my mother will
use or everybody in the street,but they may use it because
their application will use it.
(09:56):
So this would be kind of aback-end problem solving for
some bigger problem.
But maybe If it would beoptimization of portfolio of
investment, maybe everybodywould use it if they are an
investor.
So you may be using it at theback of the scene more than AI,
which is kind of front-facingyou.
(10:16):
You talk to it, it becomes verypersonal.
In quantum the behavior would bedifferent.
And if the first thing would beto invent chemical material,
I'm not sure how many peoplewould be directly using it.
If the first would be finding adrug, it's different things,
(10:37):
but even then approving a drugwill take a long time.
So it really depends on what isthe first advantage.
That would start C-Solution.
But what's true is that we allhad technology, for I don't know
if you saw the graph ofordering food from home in the
US there was a lot of technologyto do this, but only when COVID
(10:58):
came.
All of a sudden, everybodyordered food from home.
So there are sometimes momentsthat are triggered not just by
your technology readiness but bythe combination of your
technology readiness withsomething that is really looking
for this technology to happen.
Speaker 1 (11:15):
In fact, one of the differences between AI and
quantum is AI is kind of fancyin the sense that anybody can
use it, and it's moreB2C-oriented because, as you
mentioned, anybody can use chat,gpt to generate bedtime stories
for their children.
But I don't think I'm going tocreate proteins using quantum on
my phone in the next five years.
I don't know.
Speaker 2 (11:33):
But maybe you'd use a drug that was invented this way
.
Speaker 1 (11:35):
But then it depends if you'd feel that quantum
solves your problem really orit's too far, like along the
road, yeah, but it's kind oflike we have to wait for a
moment where an industry caninvest something in a real use
case, because quantum is veryback-end more than front-end In
this sense.
Maybe we've done or I'm not inquantum field, but you are,
(11:57):
you've done benefit from thishype that actually generates the
flywheel of more users spendingmore money than more investment
being made, more viralitythrough marketing.
There is more virality.
Speaker 2 (12:09):
but in business cases , If one financial company will
start to use quantum to do someoptimizations of their portfolio
, you would see all the banksand all the financial companies
using it.
So it won't be the effect ofviral in the consumer sense, but
it could be as important effectof viral in the business sense.
(12:33):
If you'd see somebodyoptimizing material with quantum
, you'll see many, manycompanies that are optimizing
material with quantum.
It won't be my mother, but itwill be many companies.
Speaker 1 (12:47):
It won't be me either , yet.
Speaker 2 (12:48):
Yeah.
Speaker 1 (12:49):
Thank you for that, victor.
Let's move over to you.
You got some big news thismorning that were announced Not
you personally, but your company.
So congratulations on getting alot of taxpayer money.
You're welcome.
No, actually you got somethinglike 65 million investment, 67.
Okay, 67.
Okay, 67.
You can break down, if you canexplain a little bit what the
(13:12):
company does, because a lot ofpeople from the audience might
not be familiar with that?
Obviously, they're familiarwith what Dirk does because
she's been here last year.
She's explained.
Sergio is already veryfrequently at Startup Prime.
How about you?
Speaker 4 (13:26):
Okay, first of all, regarding this investment from
the ministry you raised thepoint, it's part of our CDSB
that we are raising 150 millionclosing this quarter, so this
month, basically and it's partof the commitment from the
government of Spain to deeptechnology companies like ours.
So I think it's a support thatit's welcome to the Stata world.
(13:51):
In terms of materials computing, we are a software company.
We develop software for quantumcomputers and also
quantum-inspired computing.
I think I mentioned a littlebit what does it mean?
We call them basically to setthe stage.
We call them quantum computersbecause calling them science
experiments don't raisevaluations, because really they
(14:12):
are science experiments rightnow.
They are super noisy, they havea lot of errors.
Of course, there is a path tosolve all those problems.
It's an engineering problem.
The mathematicals and thephysics behind that are all
solid, but still an engineeringproblem that we are not capable
to solve.
I don't know the time frame.
I'm in sales and I want to dosales every three months.
(14:34):
I don't want to wait six yearsand there is this clear path to
developing a quantum computer.
There are many alternatives and, as a company that does
software for these quantumcomputers, it's clear that we
cannot make a sustainablebusiness only based on quantum
(14:55):
computers.
So we had this idea a few yearsback that we could use some
algorithms that are inspired onhow quantum mechanics work, but
they run on classical CPUs andGPUs, fpgas and using those
techniques for example, tensornetworks or simulated annealing
we could have this transitionfrom the quantum world, from the
(15:15):
real quantum world, from thereal quantum computer, into a
problem that we can solve today,into a problem that we can
bring value to the customerstoday.
Speaker 2 (15:26):
I want to say something about value today.
So this is our path Go ahead.
Value today we met a few tensof companies that do things with
quantum.
One of them is a company in theUS that is looking for small
molecules for specific drugs andthe founder said that they are
using today annealers and theyget to a result within three
(15:50):
months that they would otherwiseget to three years.
So I think we should just puton the table that there are
advantages.
I don't hear it often.
Most of the people that do usequantum today use it in order to
experiment, prep and kind ofset the stage for when the
quantum computer would be bigger.
But there are some advantagesalready today.
Speaker 1 (16:13):
It's just not yet the wow advantage that we want to
see like exponential advantagesno, but that's a good point,
because usually one of sometechnologies have experienced a
breakthrough moment when acertain industry that was not
expected, like maybe medicinefor, for instance, right.
Or the case of cloud, sostreaming, for instance, or
online gaming they create a newuse case and therefore more of
(16:36):
this technology was consumed,therefore lowering the cost of
it, creating the GIFs paradoxand whatnot, right.
So in the case of, I wanted toask maybe that's a question for
the three of you, I usuallydon't do these kind of generic
questions but like which fielddo you think, what sector do you
think is going to win the raceof quantum, or which one is not,
maybe not going to win, but iswinning right now?
Speaker 4 (16:58):
I only know.
Speaker 2 (16:59):
I only know one company that actually trying to
use it in a in an advantageousway.
The others are an experimentalway and in proof of concept.
I think that the chase isbetween material, drugs,
financials.
There is a couple of differenttypes of subjects.
(17:21):
There are simulations and thereare optimizations, mainly in
terms of the algorithms beingused.
Speaker 1 (17:28):
Sergio, obviously finance, right, obviously
finance.
Speaker 3 (17:32):
Or the next thing you create.
So I really believe that pharmais one of the key contendants,
because quantum devices areextremely good at dealing with
quantum data and molecules, drugdesign and all that is
effectively quantum data.
So anything that makes quantuminformation work better, whether
(17:53):
it's simulating atoms,simulating particles and so on
can be really good.
However, obviously in financethere could be a lot of haptic.
So if you there it wasmentioned in portfolio
optimization If I tell you Ihave a thing that can give you
1% more returns on yourportfolio, how much would you
pay for that 0.9% of yourreturns?
(18:16):
And on top of that, theavailability of those devices is
actually limited, or theability to connect your data and
your systems to those devicesis limited, or the ability to
connect your data and yoursystems to those devices is
limited, and there is a bigcompetitive advantage for those
companies that have startedworking on that already.
Now the challenge is and I'llchallenge you a little bit on
(18:37):
the advantage thing advantage iscompletely dependent on the
benchmark, and the benchmarkcomes not only with what can you
do classically today, but alsowhat your data is.
So in finance, for example, wesee many cases and many claims
of there's quantum advantage onportfolio optimization, for
(18:57):
example, but when it comes tousing the real data that
companies use in productiontoday, everything falls through
the cracks, at least now.
Right, it's not aboutoptimizing with 10 assets from
the S&P 500 on equities.
It's about how financialinstitutions actually do these
kind of processes and verycomplex ways of encoding the
(19:19):
data.
I am very optimistic, obviously,and that's why we work on this.
But maybe back a little bit toyour point where we work on this
.
But maybe back a little bit toyour point.
Comparing quantum with the NAIis not the right comparison.
Quantum devices are theequivalent to NVIDIA GPUs, if
(19:41):
you will, and you can use thoseGPUs for playing video games,
for mining Bitcoin or forsimulating things and training
LLMs, for mining Bitcoin or forsimulating things and training
LLMs.
Likewise, if your company has alot of data and knowledge on
how to analyze risk of a givencompany defaulting, for example,
and you run that classicallyand you can encode that
information in a quantum devicethat happens to run faster in
(20:04):
the same way that GPUs runfaster than CPUs for certain
types of problems then you get acompetitive advantage.
That's the whole flow.
Speaker 1 (20:13):
Victor, how about you ?
Because you're seeing many moreuse cases, perhaps across
industries.
Speaker 4 (20:19):
I agree with material simulation.
I really like this idea ofbeing able to simulate
properties of materials beforeeven designing them.
We have a specific case withthe German Space Agency, where
we partnered with this Delftcompany that are developing
superconductor nanowire singlephoton detectors.
They develop these sensors thatare one million times thinner
(20:44):
than a hair and they have this99.5 detection rate so they can
detect single photons.
And it's amazing, there's anamazing sensor.
You can detect single photons,um, by using these properties of
this, of this type of materials, um, and now the bodies can we
be the benchmark?
So now we're trying it with themis can we develop an algorithm
(21:07):
that can, before they build theproduct, the sensor?
Can we predict the opticalproperties of this sensor before
we build it?
And the race, the benchmark ispretty high.
It's 99.5 detection rate.
Can we do something with aquantum computer in three years'
time that can beat thisbenchmark?
It's hard.
So I mean, the problems that wehave in front of us is not toy
(21:30):
models, as Sergio explained,like optimizing 100 portfolio,
100 companies in a portfolio.
It's about developing somethingthat brings value, and 99.5 is
damn difficult.
Speaker 1 (21:48):
Victor or you wanted to.
Speaker 2 (21:50):
There is a difference , by the way, between sensors
and quantum computing.
Sensors have the advantagetoday.
So if you talk quantumtechnologies and not quantum
computing, then there areadvantages today and there are
sensors today that would be muchbetter than normal sensors.
So if you take quantum asquantum technologies and not
(22:10):
just as quantum computing, thereis plenty that is already being
done.
Speaker 1 (22:15):
Victor, the reason I brought up the investment news.
It's twofold.
One is obviously tocongratulate you on that.
The second is I take it as agesture from the Spanish
government towards innovation.
The EU has been dismissed.
Basically, america has beensaying a lot the EU is slow,
(22:40):
innovation doesn't happen inEurope at the plastic caps of
the bottles and all of that,whereas we here we send rockets
to Mars and all of that, whereaswe here we create, we send
rockets to Mars and stuff likethat.
But in the last few weeksthere's been a change of
narrative of like, hey, europe,that was a wake-up call.
Wake-up call with Franceleading.
At least France is leading theEuropean innovation, at least in
(23:02):
AI.
Some might say how about?
What do you see the regulationlike in Spain and in Europe in
general?
Speaker 4 (23:11):
in your case, you promise in the preparation
meeting not to ask nastyquestions.
Speaker 1 (23:17):
It's never a nasty question, there's only nasty
answers.
Speaker 4 (23:21):
Okay.
So regulations, I think there'smy feeling there are many
people talking bad aboutregulations, but I think it's a.
There are many people talkingbad about regulations, but I
think it's a way to know whichgame are you playing.
I mean, it's like a soccermatch.
Imagine a soccer match withoutregulations, without norms.
I think it makes a commonplaying field for everyone and
(23:42):
you know who to play in thisgame and you decide whether you
want to play in this game or youwant to go somewhere else to
play in this game, or you willgo somewhere else to to play,
right?
I think, from a user's point ofview, having some clarity on how
my data is used if I have somesaying about how this company is
going to build a specific modelwith this data, how this
(24:03):
company is going to use it it'sreally, really good for the
users.
I mean, and as a citizen, Iappreciate that as a company, of
course, sometimes when therules are too tough, I prefer
maybe to go somewhere else, butthis is a whole way that the
what is it specifically?
What are the balance betweentoo much or too few regulation,
right?
I think in general, it'spositive.
(24:25):
I think it should be better inEurope to have a common
regulation, so something moresimple that applies in all the
countries, instead of dealingwith 27 different regulations.
So some common sense there.
It would be appreciated from acompany point of view.
But in general, I would saythat regulation is right and we
(24:46):
are in the right direction.
Also, that's my feeling.
Speaker 1 (24:50):
Thank you.
Financial services or financialcompanies have been early
adopters of quantum right,because there is a use case
there.
That's pretty clear.
Yet what do you think of thefriction that you're
encountering when you're tryingto sell internally these kind of
projects and investments?
Because I don't think it willbe easy to go to your CEO and
say like, look, you have toinvest one billion in producing
(25:11):
these because maybe in a fewyears we'll have something.
How do you present theseinternally?
How do you sell it internally?
That's kind of what I did.
Speaker 3 (25:19):
I didn't ask for a billion, but I think it is
really important.
There has been two challengesin quantum.
One is, obviously, that isreally difficult to explain what
the value is, and two, forthose who may manage to do that,
that they created or generatedthe wrong expectations as saying
(25:40):
we're going to get ROI fromthis very soon.
And in fact, in the financialindustry, we have seen how some
companies created quantum teamsand disbanded them right after
two or three years, of theseteams producing nothing but a
few white papers, for example,and that is a big challenge
because it's indeed a long-termthing.
So the first point is howlong-term innovation, what is
(26:04):
the long-term innovationstrategy of your company?
And making sure that there isan overarching theme around that
.
And then, specifically onquantum, a lot of what we've
been talking about here is theoffensive how can I create
better portfolios with betterreturns, or discover drugs
faster, and so on.
But there is a defensivemechanism as well, which is what
(26:26):
I guess many people in the roomknow that quantum computers
create a big disruption in thecybersecurity world because one
of those niche mathematicalproblems happens to be breaking
the cryptography system that weknow today.
So the argument is twofold.
One is what if, in a few years,we can manage to get this type
(26:47):
of ROI by meeting marketexpectations, by getting new
customers, by being competitive?
But also imagine all our datagoes out in the wild and
everyone can use it.
You probably wouldn't want that,right.
What are the chances of thathappening in 10 years?
Is that 50% chances?
No, is that 10?
(27:07):
No, is that 1%?
What do you think?
So now there's a really bigsurvey that runs every year by a
company called EvolutionQ, andin the last edition they are
saying that 10% of the quantumexperts think that there's going
to be a cryptographicallyrelevant quantum device, meaning
a quantum computer that canbreak RSA cryptography, by 2030.
(27:31):
10%.
Before it used to be 3% andthen 1%.
But it doesn't matter.
If you go to a CEO and you tellthat person look, a quantum
team is going to cost you a fewmillion.
Tops, it's not going to be amulti-multi-million dollar
initiative.
Unless you want to build yourown quantum device, would you be
the CEO that risks yourcompany's data?
(27:54):
For 1% chances, that argumenttakes the win.
Speaker 1 (27:59):
Dorit, what's your view on this?
Because it seems like everyyear we're pushing back that
date.
It feels like we're buildingthe Sagrada Familia, which you
know every year is like no, it'sgoing to be complete by 1992.
Should have been completed bythe Olympics, then year 2000,.
Then shit happens.
Speaker 3 (28:14):
It's going to be before fusion nuclear fusion.
Speaker 2 (28:18):
I have a few things.
First, just to set the ground.
It's my 30th year at Checkpointand I'm doing cyber like 37
years, and I'm only doingquantum very few years, so for
me it's a rather familiar.
I'm new doing quantum very fewyears, so for me, Sagrada.
Speaker 1 (28:32):
Familia is like.
Speaker 2 (28:33):
Still I'm new to quantum, but in 2020, I was in
Davos and I heard a lectureabout quantum supremacy and I
thought, wow, this is very longfrom now.
This is very, very far.
The presentation was kind ofvery theoretical.
From now, this is very, veryfar.
The presentation was kind ofvery theoretical and outreach
(28:56):
and I think why I got to quantumin the last year is because I
really got excited that by manyindication it's becoming sooner.
But the cryptography part isactually the hardest part
because you have to be faulttolerant and with many qubits.
So I'm excited about theadvantage that is coming soon.
(29:18):
That doesn't mean thatcryptography problems are coming
soon.
Nevertheless, even ifcryptography is broken in 10
years, there are a few reasonswhy companies should be worried
about them now.
One is that if you have data atrest that maybe somebody copied
(29:38):
today and would be stillvaluable, you need to handle it
today because if they break itin 10 years, it's still valuable
.
The second reason is that insome areas, replacing the whole
cryptography after building onthis industry as a basic
assumption that it will alwayswork, is going to take a very
(30:01):
long time Just mapping it,replacing it, changing the
protocols, etc.
It should be easy, like a VPN.
Buy a VPN from a vendor that isdoing the VPN in an agile way
and will just give you a PQCnext month, and that's it.
Speaker 1 (30:20):
It must be hard first to fight off technical debt in
a way.
The second is like peopleworking in these long time
solutions, they usually don'twork in the company to see the
effect of the decisions they'vemade.
Right Now you've been 30 yearsin the same company.
In technology that reallydoesn't happen.
So if I'm working on a quantumcompany and given the volatility
(30:42):
of the market, chances are thatdevelopers working on that or
technical people working on that, they will move to another
company.
So therefore I don't know howskewed or how sound their
architectural decisions are ifthey know they're not going to
be in the company.
Speaker 2 (30:54):
So I actually think these are two things.
One is for companies to buildquantum teams for the advantage
that they could use If the issueis quantum cryptography.
This is not the same set ofpeople and not the same set of
problems, in my opinion.
Actually, most of the solutionsare pure software solutions
(31:17):
that have nothing to do withquantum, except that the
algorithm should be quantum safeand there is the fine line of
using QKD, which is quantumtechnology, to exchange key
exchanges.
This is very expensivetechnologies that is created by
few.
It doesn't solve like a browserto a company.
(31:39):
It should solve site to site orcompany to company.
So most of the solutions forthe cryptography side is
post-quantum cryptography.
That has somewhat littlerelation to being a quantum
expert In the sense that youassume NIST or some other
(32:02):
organization would set thestandard on cryptography.
You are not going to inventyour own standard, so it's a
software issue.
Speaker 1 (32:10):
Victor.
Last question before we canwrap up the panel.
If I'm not mistaken, you're atechnical background.
You've got a technicalbackground doing sales.
It must be really hard sellinga technology corporates don't
understand.
Like you're selling Quantum tocorporates, I'm selling
JavaScript to corporates, whichis also they don't understand.
But how important do you thinkit's is having this ability to
(32:32):
speak the language of thetechnology you're selling,
understanding what thecorporations need and all your
other you know the other personyou're talking to and being able
to sell it right?
I think you did it in person,right?
That's a good question.
Speaker 4 (32:48):
At the end of the day , it's similar to selling any
type of software project.
You need to build trust.
You need to build trust.
You need to build trust thatyou can deliver.
And to build trust inside anorganization, you need to
convince several stakeholders.
If you can, in those firstinitial meetings with the
different stakeholders, managethe language and make it in a
way that they understand themessage.
(33:09):
I think that's the way to go.
If you can speak the saleslanguage, like, what is the
value for this company ofapplying this solution?
Maybe not now, maybe in fiveyears time, whatever.
Uh, you need to transmit it tothis particular person.
But then you have technicalpeople that maybe have different
interests.
You need to understand what aretheir interests and and try to
transmit that in the languagethat they understand.
(33:30):
So I think right now, since wecannot have a product that is
perfectly defined and we canpackage it and say it has a
product that is more orientedtowards services, you still need
this type of people that hasmixed backgrounds, that they can
talk a little bit the businesslanguage and also the technical
(33:51):
language.
Speaker 1 (33:52):
And how can you qualify whether a lead Because I
assume you're not doing salesoutreach it's mostly inbound
companies reaching out andsaying, hey, we want to explore
something with you.
However, you know that a highpercentage of that they just
want to entertain the idea, justto learn the basics, the cost
implications, whatnot but theywill never get to sign the
project right.
(34:12):
How do you qualify that?
Speaker 4 (34:15):
I mean for quantum computing.
So if you talk only purequantum algorithms and quantum
computers, that is only in sales.
We call it ideal customerprofile and there are really few
people inside organizations andreally few organizations that
are willing to invest in themid-long term.
Okay, so identifying what is toinvest in the mid-long term, so
identifying what is the accountin the mid-long term is pretty
easy.
Just look for the ones withdeepest pockets, and these are
(34:39):
the ones typically.
Speaker 1 (34:41):
Like Sergio.
Speaker 4 (34:42):
I mean, these are the guys that want to invest in the
mid-long term like five, tenyears' time again, to understand
the technology.
And inside those organizationsthey are the more technically
versed, like innovationdepartments, research
departments.
These are typically the areaswhere you scout for quantum
computing projects and then youhave mechanisms like public
(35:06):
funding, for example RFPs andgrants, to try to support the
business case with thoseorganizations on how to build a
project with them.
Right, and that's it.
Speaker 1 (35:17):
How can people reach out to you and why should they?
Speaker 4 (35:21):
I have a guy that's called Victor Gaspar.
He's a Brazilian top model.
It's not me, okay, Because ifyou go to this guy, I mean my
God, he's good.
Speaker 1 (35:32):
Everybody has got a doppelganger.
What is?
Speaker 4 (35:34):
going on Too many people.
So LinkedIn.
My email is victorgaspar atmultiversecomputingcom.
Pretty easy, and I mean reachout if you want to talk about
quantum computing, quantuminspired, how to use quantum
inspired computing for AI, Idon't know.
Let's have a conversation.
Speaker 1 (35:55):
Thank you.
Speaker 3 (35:56):
How about you?
I'm pretty easy to find.
You can subscribe to mynewsletter, the Quantum Pirates
and Substack.
You can buy my book, the CTOToolbox.
All the proceeds go to a coupleof fantastic NGOs in Barcelona,
and you can pick me on LinkedInanywhere.
Why should they?
Speaker 1 (36:17):
Oh, why?
Speaker 3 (36:18):
Because I'm awesome, that's fantastic Dorit.
Speaker 1 (36:21):
how could they reach you?
Speaker 2 (36:22):
I'm Dorit Dorit at LinkedIn.
I think there is not muchcompetition to my name.
Speaker 1 (36:29):
There's a Ukrainian developer that got your profile
or your GitHub handle orsomething like that.
Speaker 2 (36:37):
I'm also Dorit at checkpointcom.
I'm also Dorit at qubitvc andyou could reach out to me for
cyber stuff.
That's on my side of the oneside of the head.
On Quantum, we are looking forpipeline investors and strategic
relationships, so happy to talkto you on any of them.
(36:59):
I'm also enthusiastic ontechnologies more generally, so
AI and other stuff.
Speaker 1 (37:06):
the world is just very exciting thank you very
much, ladies and gentlemen.
Applause, applause, big thankyou.
Very exciting.
That's it.
Thank you very much, ladies andgentlemen.
Big, big thank you to thepanelists, all of them.
Big thank you to the crew andthe organization and our
sponsors.
Again, cms and Moody's, thankyou very much for putting up
with me and my fuck-ups forseven plus years.
(37:27):
I'll see you all.
In the next room there's acatering and the beers.
We're going to have one hourfor that.
Thanks for the mics and for themics.
Yeah, next year with NVIDIAmics.
Thanks, thanks, thanks.
Hello everybody, I'm Alex, ceo and founder of Mars
Days.
Welcome to another episode ofLife on Mars, and in this
episode we bring you the secondpanel of the Corporate
Innovation Summit, incontinuation of the previous
episode.
In this case we discuss quantumcomputing, and this is
something that I had to preparea lot for, because I'm far from
being an expert, but luckily wecompensated with having three
(00:23):
real experts on quantumcomputing on the panel.
So, without further ado, let'sjump right into this episode.
Time to move to the next panel.
As I mentioned, we are a littlebit behind on time.
I'd like to welcome the nextset of speakers to the stage
(00:45):
Sergio, dorit and Victor.
Please come to the stage.
Big applause for them.
We got too many chairs, but wecan sit more spaced.
Let's leave distance betweenyou.
It should be distance or not,depends.
You came last year.
(01:05):
You decided to repeat this year.
I'm not sure why.
I'm not sure too.
Speaker 2 (01:09):
I'm still questioning , let's start One, two three.
Speaker 1 (01:13):
It works, thank you Well, thank you for being here,
sergio.
I wanted to start with youbecause I have the confidence,
and actually you say in Spanishwe say that confianza de Asco.
So we've seen that quantum issomething that people say every
year.
This is the year for quantum,right, obviously, 2025 is the
(01:34):
year for quantum, unless it was10 years ago.
But we have seen this demo byKusentroid.
We're seeing other examplesbeing shared at Mobile World
Congress, and yet we don't havethe hardware required to run the
real problems.
And we're sending stuff toquantum computers but they don't
solve real problems or problemswe could tackle with quantum
(01:54):
computing.
How far are we from that,especially taking into account
the big news from last week?
Is it on?
No, this one, then you use thisone.
Speaker 3 (02:03):
So this year.
Speaker 1 (02:03):
it is truly no, this one, Then you use this one.
Speaker 3 (02:05):
Oh yeah, so this year it is truly the year of quantum
.
The UN declared it last year.
Speaker 1 (02:10):
So it's the guy with the quantum newsletter, yeah.
Speaker 3 (02:12):
I do own a quantum newsletter.
We call it the quantum piratesnewsletter, if you're interested
in that.
I came to speak about my book,of course.
So this is the year of quantumofficially.
The UN and several otherorganizations have declared that
like that, and that's becausethe amount of development and
milestones achieved in the lastcouple of years or so have been
(02:34):
quintessential for what we areseeing today.
The past five years or a decadehave been already either solved
or are in the way of beingsolved in terms of scalability
of the devices or errorcorrection of them, of the
devices.
Moreover, we have a lot oftools, a lot of research, a lot
of government investment, andwe'll talk about cyber security
(02:57):
as well and the importance of,again, governments and companies
to tackle the challenge ofcybersecurity and the risk that
quantum computers put to that.
Now, the quantum computers thatwe have today we have them, they
exist, and Carlos showed howyou can send stuff to some of
these quantum devices.
They're still pretty small.
(03:19):
So if you take a productionworkload with the sizes that it
has, many of these devices willnot be big enough or robust
enough to run them.
If you take a productionworkload with the sizes that it
has.
Many of these devices will notbe big enough or robust enough
to run them.
But that doesn't mean that youdon't have to start today,
because finding the use casesand coding your data, finding
how to use them and learning andupskilling your team is quite
of a challenge.
(03:39):
So, yes, this is the year ofquantum, I would say.
Speaker 1 (03:43):
In fact, we could be nerding out about whether the
changes from physical to logicalqubits are going to affect the
industry and whatnot.
I don't think this is the righttime, especially given that
it's like beer o'clock, but I'dlike to get your vision on why
corporates have decided fromgoing like super private and
(04:05):
secretive about their strategywith new technologies because
back in the day, you know, oh,we don't want to share, we don't
want to share, we don't want toshare.
And I was like, yeah, here wehave, we have got everything is
open source right now.
So why did that change?
And uh, what?
What are you doing in terms ofquantum at modis and open source
as well?
Speaker 3 (04:22):
let me put put it this way how many people do you
guys think work in the privatesector full-time in quantum
computing?
Would you say a number, threepeople, that's really.
There are a hundred companies.
Speaker 1 (04:36):
You're part-time.
Speaker 2 (04:37):
I'm part-time, but there are a hundred companies,
at least, that have quantumgroups.
Speaker 3 (04:42):
So the best guess?
Obviously this is a guess, butthe survey that I've been making
with a lot of people fromdifferent companies, big and
small, is around 5,000 people,and there are a handful of
companies with a few hundredpeople, such as you guys in
Multiverse, IBM, AWS, Microsoft,have robust quantum teams on
different research, but that'sstill around 5,000 people.
(05:04):
Maybe I fall short.
It's 6,000.
Maybe 7,000.
Speaker 1 (05:07):
That's still peanuts, Unless you count quantum
enthusiasts on LinkedIn, whichis 5 million people.
Speaker 3 (05:13):
Well, yeah, yeah, it's almost as many as chat GPT
experts.
Exactly.
So, with that amount of peopleand with something that is still
getting into the maturationstage, sharing and building a
community is fundamental.
We all learn from each other,and it starts from academia,
from research, goes into theimplementations and something
(05:34):
that Greg mentioned before on AI.
That is absolutely true as well.
For quantum.
Fine, you have that.
What are you going to use itfor?
What are the use cases and howthese use cases actually touch
on the quantum device?
It's not just a high leveltextbook problem, but my data,
my way of solving it and thespecific use case that you're
(05:55):
solving, especially in finance.
Speaker 1 (05:57):
Dorit, welcome for the second year of thank you I
have before that.
Speaker 2 (06:01):
the first rule is to spell right the name.
Qubit is Q-B-E-A-T, but I'm ina superposition between cyber
checkpoint and qubit and quantum.
Speaker 1 (06:16):
My question is going to be so.
There's one news from last year.
Last year you were Onlycheckpoint, yeah, only
checkpoint.
I mean, besides all the otherthings you do, but no qubit
ventures.
So can you tell us about whatis that?
What is your investment thesis?
Because it's very difficultsometimes to understand the
investment thesis of VCs.
But now, in quantum, how do youbuild the thesis around that?
Speaker 2 (06:38):
Excellent.
So we start with the questionhow many years to an advantage?
So whether every year is thequantum year is because you have
to prep for it.
But I believe advantage is two,three years from now.
Two, three years is still good.
Advantage means that you couldnot this year.
You could still run it, butadvantage mean real advantage to
(06:59):
some application.
Second part is that not onewinner takes it all.
If you want to invest inquantum, you have to have a
portfolio.
So we're going to have aportfolio of multiple elements
of this to kind of facilitatethe industry to happen.
We also believe that it's stilla phase where early stage
(07:22):
solution has space to impact.
So we are going to invest inearly stage quantum focused only
, and we think that quantum isgoing to change the world and
that's exciting.
Speaker 1 (07:36):
How do you balance your investment thesis between
universal versus specializedquantum computing?
Speaker 2 (07:41):
What do you mean in that sense?
Speaker 1 (07:44):
In the sense that you know one of the fields that we
have seen in AI for instance is,at the very beginning,
everything was generalist right,and so people were trying to
tackle generic problems withgeneralist AI.
Then down the road we saw orlike the sector saw that
specialized LAMP, specializedmodels, specialized tools were
(08:08):
much more performant, less errorprone, and all of that in an
ever-changing landscape withquantum that's so unstable.
And then all of the sudden,microsoft comes and shakes the
entire industry.
How do you balance yourperformance with that?
Speaker 2 (08:18):
I think that at early stage in quantum there would be
very few generalists.
There is no way to begeneralist in quantum in early
stage.
It's going to be crazy.
Even picking two of the 10modalities is not something that
multiple people will understand.
So every early stage is goingto focus on something, either on
(08:44):
a qubit modality or on acomponent or on software.
On aspects, very few would beattempting to be very generalist
and that's going to be amistake.
Now the bigger guys may betrying to be generalist, but our
thesis is that still there isroom for early stage
technologies to influence thespace because it's very much
(09:07):
evolving and you could seetechnologies that are new, that
are jumping over previousgeneration of technologies.
Speaker 1 (09:14):
Still, In AI.
Two and a half years ago moreor less, we saw the breakthrough
to the general audience withChaiGPT.
Chaigpt accelerated.
Chai GPT kind of likeaccelerated things because it
allowed the, it crossed thechasm in a manner of speaking
right.
How far are we from seeingsomething like this in quantum?
Speaker 2 (09:36):
So I think this is really the question of what the
advantage comes to be.
I said I think there would bean advantage in two, three years
.
It's not going to be theapplication that my mother will
use or everybody in the street,but they may use it because
their application will use it.
(09:56):
So this would be kind of aback-end problem solving for
some bigger problem.
But maybe If it would beoptimization of portfolio of
investment, maybe everybodywould use it if they are an
investor.
So you may be using it at theback of the scene more than AI,
which is kind of front-facingyou.
(10:16):
You talk to it, it becomes verypersonal.
In quantum the behavior would bedifferent.
And if the first thing would beto invent chemical material,
I'm not sure how many peoplewould be directly using it.
If the first would be finding adrug, it's different things,
(10:37):
but even then approving a drugwill take a long time.
So it really depends on what isthe first advantage.
That would start C-Solution.
But what's true is that we allhad technology, for I don't know
if you saw the graph ofordering food from home in the
US there was a lot of technologyto do this, but only when COVID
(10:58):
came.
All of a sudden, everybodyordered food from home.
So there are sometimes momentsthat are triggered not just by
your technology readiness but bythe combination of your
technology readiness withsomething that is really looking
for this technology to happen.
Speaker 1 (11:15):
In fact, one of the differences between AI and
quantum is AI is kind of fancyin the sense that anybody can
use it, and it's moreB2C-oriented because, as you
mentioned, anybody can use chat,gpt to generate bedtime stories
for their children.
But I don't think I'm going tocreate proteins using quantum on
my phone in the next five years.
I don't know.
Speaker 2 (11:33):
But maybe you'd use a drug that was invented this way
.
Speaker 1 (11:35):
But then it depends if you'd feel that quantum
solves your problem really orit's too far, like along the
road, yeah, but it's kind oflike we have to wait for a
moment where an industry caninvest something in a real use
case, because quantum is veryback-end more than front-end In
this sense.
Maybe we've done or I'm not inquantum field, but you are,
(11:57):
you've done benefit from thishype that actually generates the
flywheel of more users spendingmore money than more investment
being made, more viralitythrough marketing.
There is more virality.
Speaker 2 (12:09):
but in business cases , If one financial company will
start to use quantum to do someoptimizations of their portfolio
, you would see all the banksand all the financial companies
using it.
So it won't be the effect ofviral in the consumer sense, but
it could be as important effectof viral in the business sense.
(12:33):
If you'd see somebodyoptimizing material with quantum
, you'll see many, manycompanies that are optimizing
material with quantum.
It won't be my mother, but itwill be many companies.
Speaker 1 (12:47):
It won't be me either , yet.
Speaker 2 (12:48):
Yeah.
Speaker 1 (12:49):
Thank you for that, victor.
Let's move over to you.
You got some big news thismorning that were announced Not
you personally, but your company.
So congratulations on getting alot of taxpayer money.
You're welcome.
No, actually you got somethinglike 65 million investment, 67.
Okay, 67.
Okay, 67.
You can break down, if you canexplain a little bit what the
(13:12):
company does, because a lot ofpeople from the audience might
not be familiar with that?
Obviously, they're familiarwith what Dirk does because
she's been here last year.
She's explained.
Sergio is already veryfrequently at Startup Prime.
How about you?
Speaker 4 (13:26):
Okay, first of all, regarding this investment from
the ministry you raised thepoint, it's part of our CDSB
that we are raising 150 millionclosing this quarter, so this
month, basically and it's partof the commitment from the
government of Spain to deeptechnology companies like ours.
So I think it's a support thatit's welcome to the Stata world.
(13:51):
In terms of materials computing, we are a software company.
We develop software for quantumcomputers and also
quantum-inspired computing.
I think I mentioned a littlebit what does it mean?
We call them basically to setthe stage.
We call them quantum computersbecause calling them science
experiments don't raisevaluations, because really they
(14:12):
are science experiments rightnow.
They are super noisy, they havea lot of errors.
Of course, there is a path tosolve all those problems.
It's an engineering problem.
The mathematicals and thephysics behind that are all
solid, but still an engineeringproblem that we are not capable
to solve.
I don't know the time frame.
I'm in sales and I want to dosales every three months.
(14:34):
I don't want to wait six yearsand there is this clear path to
developing a quantum computer.
There are many alternatives and, as a company that does
software for these quantumcomputers, it's clear that we
cannot make a sustainablebusiness only based on quantum
(14:55):
computers.
So we had this idea a few yearsback that we could use some
algorithms that are inspired onhow quantum mechanics work, but
they run on classical CPUs andGPUs, fpgas and using those
techniques for example, tensornetworks or simulated annealing
we could have this transitionfrom the quantum world, from the
(15:15):
real quantum world, from thereal quantum computer, into a
problem that we can solve today,into a problem that we can
bring value to the customerstoday.
Speaker 2 (15:26):
I want to say something about value today.
So this is our path Go ahead.
Value today we met a few tensof companies that do things with
quantum.
One of them is a company in theUS that is looking for small
molecules for specific drugs andthe founder said that they are
using today annealers and theyget to a result within three
(15:50):
months that they would otherwiseget to three years.
So I think we should just puton the table that there are
advantages.
I don't hear it often.
Most of the people that do usequantum today use it in order to
experiment, prep and kind ofset the stage for when the
quantum computer would be bigger.
But there are some advantagesalready today.
Speaker 1 (16:13):
It's just not yet the wow advantage that we want to
see like exponential advantagesno, but that's a good point,
because usually one of sometechnologies have experienced a
breakthrough moment when acertain industry that was not
expected, like maybe medicinefor, for instance, right.
Or the case of cloud, sostreaming, for instance, or
online gaming they create a newuse case and therefore more of
(16:36):
this technology was consumed,therefore lowering the cost of
it, creating the GIFs paradoxand whatnot, right.
So in the case of, I wanted toask maybe that's a question for
the three of you, I usuallydon't do these kind of generic
questions but like which fielddo you think, what sector do you
think is going to win the raceof quantum, or which one is not,
maybe not going to win, but iswinning right now?
Speaker 4 (16:58):
I only know.
Speaker 2 (16:59):
I only know one company that actually trying to
use it in a in an advantageousway.
The others are an experimentalway and in proof of concept.
I think that the chase isbetween material, drugs,
financials.
There is a couple of differenttypes of subjects.
(17:21):
There are simulations and thereare optimizations, mainly in
terms of the algorithms beingused.
Speaker 1 (17:28):
Sergio, obviously finance, right, obviously
finance.
Speaker 3 (17:32):
Or the next thing you create.
So I really believe that pharmais one of the key contendants,
because quantum devices areextremely good at dealing with
quantum data and molecules, drugdesign and all that is
effectively quantum data.
So anything that makes quantuminformation work better, whether
(17:53):
it's simulating atoms,simulating particles and so on
can be really good.
However, obviously in financethere could be a lot of haptic.
So if you there it wasmentioned in portfolio
optimization If I tell you Ihave a thing that can give you
1% more returns on yourportfolio, how much would you
pay for that 0.9% of yourreturns?
(18:16):
And on top of that, theavailability of those devices is
actually limited, or theability to connect your data and
your systems to those devicesis limited, or the ability to
connect your data and yoursystems to those devices is
limited, and there is a bigcompetitive advantage for those
companies that have startedworking on that already.
Now the challenge is and I'llchallenge you a little bit on
(18:37):
the advantage thing advantage iscompletely dependent on the
benchmark, and the benchmarkcomes not only with what can you
do classically today, but alsowhat your data is.
So in finance, for example, wesee many cases and many claims
of there's quantum advantage onportfolio optimization, for
(18:57):
example, but when it comes tousing the real data that
companies use in productiontoday, everything falls through
the cracks, at least now.
Right, it's not aboutoptimizing with 10 assets from
the S&P 500 on equities.
It's about how financialinstitutions actually do these
kind of processes and verycomplex ways of encoding the
(19:19):
data.
I am very optimistic, obviously,and that's why we work on this.
But maybe back a little bit toyour point where we work on this
.
But maybe back a little bit toyour point.
Comparing quantum with the NAIis not the right comparison.
Quantum devices are theequivalent to NVIDIA GPUs, if
(19:41):
you will, and you can use thoseGPUs for playing video games,
for mining Bitcoin or forsimulating things and training
LLMs, for mining Bitcoin or forsimulating things and training
LLMs.
Likewise, if your company has alot of data and knowledge on
how to analyze risk of a givencompany defaulting, for example,
and you run that classicallyand you can encode that
information in a quantum devicethat happens to run faster in
(20:04):
the same way that GPUs runfaster than CPUs for certain
types of problems then you get acompetitive advantage.
That's the whole flow.
Speaker 1 (20:13):
Victor, how about you ?
Because you're seeing many moreuse cases, perhaps across
industries.
Speaker 4 (20:19):
I agree with material simulation.
I really like this idea ofbeing able to simulate
properties of materials beforeeven designing them.
We have a specific case withthe German Space Agency, where
we partnered with this Delftcompany that are developing
superconductor nanowire singlephoton detectors.
They develop these sensors thatare one million times thinner
(20:44):
than a hair and they have this99.5 detection rate so they can
detect single photons.
And it's amazing, there's anamazing sensor.
You can detect single photons,um, by using these properties of
this, of this type of materials, um, and now the bodies can we
be the benchmark?
So now we're trying it with themis can we develop an algorithm
(21:07):
that can, before they build theproduct, the sensor?
Can we predict the opticalproperties of this sensor before
we build it?
And the race, the benchmark ispretty high.
It's 99.5 detection rate.
Can we do something with aquantum computer in three years'
time that can beat thisbenchmark?
It's hard.
So I mean, the problems that wehave in front of us is not toy
(21:30):
models, as Sergio explained,like optimizing 100 portfolio,
100 companies in a portfolio.
It's about developing somethingthat brings value, and 99.5 is
damn difficult.
Speaker 1 (21:48):
Victor or you wanted to.
Speaker 2 (21:50):
There is a difference , by the way, between sensors
and quantum computing.
Sensors have the advantagetoday.
So if you talk quantumtechnologies and not quantum
computing, then there areadvantages today and there are
sensors today that would be muchbetter than normal sensors.
So if you take quantum asquantum technologies and not
(22:10):
just as quantum computing, thereis plenty that is already being
done.
Speaker 1 (22:15):
Victor, the reason I brought up the investment news.
It's twofold.
One is obviously tocongratulate you on that.
The second is I take it as agesture from the Spanish
government towards innovation.
The EU has been dismissed.
Basically, america has beensaying a lot the EU is slow,
(22:40):
innovation doesn't happen inEurope at the plastic caps of
the bottles and all of that,whereas we here we send rockets
to Mars and all of that, whereaswe here we create, we send
rockets to Mars and stuff likethat.
But in the last few weeksthere's been a change of
narrative of like, hey, europe,that was a wake-up call.
Wake-up call with Franceleading.
At least France is leading theEuropean innovation, at least in
(23:02):
AI.
Some might say how about?
What do you see the regulationlike in Spain and in Europe in
general?
Speaker 4 (23:11):
in your case, you promise in the preparation
meeting not to ask nastyquestions.
Speaker 1 (23:17):
It's never a nasty question, there's only nasty
answers.
Speaker 4 (23:21):
Okay.
So regulations, I think there'smy feeling there are many
people talking bad aboutregulations, but I think it's a.
There are many people talkingbad about regulations, but I
think it's a way to know whichgame are you playing.
I mean, it's like a soccermatch.
Imagine a soccer match withoutregulations, without norms.
I think it makes a commonplaying field for everyone and
(23:42):
you know who to play in thisgame and you decide whether you
want to play in this game or youwant to go somewhere else to
play in this game, or you willgo somewhere else to to play,
right?
I think, from a user's point ofview, having some clarity on how
my data is used if I have somesaying about how this company is
going to build a specific modelwith this data, how this
(24:03):
company is going to use it it'sreally, really good for the
users.
I mean, and as a citizen, Iappreciate that as a company, of
course, sometimes when therules are too tough, I prefer
maybe to go somewhere else, butthis is a whole way that the
what is it specifically?
What are the balance betweentoo much or too few regulation,
right?
I think in general, it'spositive.
(24:25):
I think it should be better inEurope to have a common
regulation, so something moresimple that applies in all the
countries, instead of dealingwith 27 different regulations.
So some common sense there.
It would be appreciated from acompany point of view.
But in general, I would saythat regulation is right and we
(24:46):
are in the right direction.
Also, that's my feeling.
Speaker 1 (24:50):
Thank you.
Financial services or financialcompanies have been early
adopters of quantum right,because there is a use case
there.
That's pretty clear.
Yet what do you think of thefriction that you're
encountering when you're tryingto sell internally these kind of
projects and investments?
Because I don't think it willbe easy to go to your CEO and
say like, look, you have toinvest one billion in producing
(25:11):
these because maybe in a fewyears we'll have something.
How do you present theseinternally?
How do you sell it internally?
That's kind of what I did.
Speaker 3 (25:19):
I didn't ask for a billion, but I think it is
really important.
There has been two challengesin quantum.
One is, obviously, that isreally difficult to explain what
the value is, and two, forthose who may manage to do that,
that they created or generatedthe wrong expectations as saying
(25:40):
we're going to get ROI fromthis very soon.
And in fact, in the financialindustry, we have seen how some
companies created quantum teamsand disbanded them right after
two or three years, of theseteams producing nothing but a
few white papers, for example,and that is a big challenge
because it's indeed a long-termthing.
So the first point is howlong-term innovation, what is
(26:04):
the long-term innovationstrategy of your company?
And making sure that there isan overarching theme around that
.
And then, specifically onquantum, a lot of what we've
been talking about here is theoffensive how can I create
better portfolios with betterreturns, or discover drugs
faster, and so on.
But there is a defensivemechanism as well, which is what
(26:26):
I guess many people in the roomknow that quantum computers
create a big disruption in thecybersecurity world because one
of those niche mathematicalproblems happens to be breaking
the cryptography system that weknow today.
So the argument is twofold.
One is what if, in a few years,we can manage to get this type
(26:47):
of ROI by meeting marketexpectations, by getting new
customers, by being competitive?
But also imagine all our datagoes out in the wild and
everyone can use it.
You probably wouldn't want that,right.
What are the chances of thathappening in 10 years?
Is that 50% chances?
No, is that 10?
(27:07):
No, is that 1%?
What do you think?
So now there's a really bigsurvey that runs every year by a
company called EvolutionQ, andin the last edition they are
saying that 10% of the quantumexperts think that there's going
to be a cryptographicallyrelevant quantum device, meaning
a quantum computer that canbreak RSA cryptography, by 2030.
(27:31):
10%.
Before it used to be 3% andthen 1%.
But it doesn't matter.
If you go to a CEO and you tellthat person look, a quantum
team is going to cost you a fewmillion.
Tops, it's not going to be amulti-multi-million dollar
initiative.
Unless you want to build yourown quantum device, would you be
the CEO that risks yourcompany's data?
(27:54):
For 1% chances, that argumenttakes the win.
Speaker 1 (27:59):
Dorit, what's your view on this?
Because it seems like everyyear we're pushing back that
date.
It feels like we're buildingthe Sagrada Familia, which you
know every year is like no, it'sgoing to be complete by 1992.
Should have been completed bythe Olympics, then year 2000,.
Then shit happens.
Speaker 3 (28:14):
It's going to be before fusion nuclear fusion.
Speaker 2 (28:18):
I have a few things.
First, just to set the ground.
It's my 30th year at Checkpointand I'm doing cyber like 37
years, and I'm only doingquantum very few years, so for
me it's a rather familiar.
I'm new doing quantum very fewyears, so for me, Sagrada.
Speaker 1 (28:32):
Familia is like.
Speaker 2 (28:33):
Still I'm new to quantum, but in 2020, I was in
Davos and I heard a lectureabout quantum supremacy and I
thought, wow, this is very longfrom now.
This is very, very far.
The presentation was kind ofvery theoretical.
From now, this is very, veryfar.
The presentation was kind ofvery theoretical and outreach
(28:56):
and I think why I got to quantumin the last year is because I
really got excited that by manyindication it's becoming sooner.
But the cryptography part isactually the hardest part
because you have to be faulttolerant and with many qubits.
So I'm excited about theadvantage that is coming soon.
(29:18):
That doesn't mean thatcryptography problems are coming
soon.
Nevertheless, even ifcryptography is broken in 10
years, there are a few reasonswhy companies should be worried
about them now.
One is that if you have data atrest that maybe somebody copied
(29:38):
today and would be stillvaluable, you need to handle it
today because if they break itin 10 years, it's still valuable
.
The second reason is that insome areas, replacing the whole
cryptography after building onthis industry as a basic
assumption that it will alwayswork, is going to take a very
(30:01):
long time Just mapping it,replacing it, changing the
protocols, etc.
It should be easy, like a VPN.
Buy a VPN from a vendor that isdoing the VPN in an agile way
and will just give you a PQCnext month, and that's it.
Speaker 1 (30:20):
It must be hard first to fight off technical debt in
a way.
The second is like peopleworking in these long time
solutions, they usually don'twork in the company to see the
effect of the decisions they'vemade.
Right Now you've been 30 yearsin the same company.
In technology that reallydoesn't happen.
So if I'm working on a quantumcompany and given the volatility
(30:42):
of the market, chances are thatdevelopers working on that or
technical people working on that, they will move to another
company.
So therefore I don't know howskewed or how sound their
architectural decisions are ifthey know they're not going to
be in the company.
Speaker 2 (30:54):
So I actually think these are two things.
One is for companies to buildquantum teams for the advantage
that they could use If the issueis quantum cryptography.
This is not the same set ofpeople and not the same set of
problems, in my opinion.
Actually, most of the solutionsare pure software solutions
(31:17):
that have nothing to do withquantum, except that the
algorithm should be quantum safeand there is the fine line of
using QKD, which is quantumtechnology, to exchange key
exchanges.
This is very expensivetechnologies that is created by
few.
It doesn't solve like a browserto a company.
(31:39):
It should solve site to site orcompany to company.
So most of the solutions forthe cryptography side is
post-quantum cryptography.
That has somewhat littlerelation to being a quantum
expert In the sense that youassume NIST or some other
(32:02):
organization would set thestandard on cryptography.
You are not going to inventyour own standard, so it's a
software issue.
Speaker 1 (32:10):
Victor.
Last question before we canwrap up the panel.
If I'm not mistaken, you're atechnical background.
You've got a technicalbackground doing sales.
It must be really hard sellinga technology corporates don't
understand.
Like you're selling Quantum tocorporates, I'm selling
JavaScript to corporates, whichis also they don't understand.
But how important do you thinkit's is having this ability to
(32:32):
speak the language of thetechnology you're selling,
understanding what thecorporations need and all your
other you know the other personyou're talking to and being able
to sell it right?
I think you did it in person,right?
That's a good question.
Speaker 4 (32:48):
At the end of the day , it's similar to selling any
type of software project.
You need to build trust.
You need to build trust.
You need to build trust thatyou can deliver.
And to build trust inside anorganization, you need to
convince several stakeholders.
If you can, in those firstinitial meetings with the
different stakeholders, managethe language and make it in a
way that they understand themessage.
(33:09):
I think that's the way to go.
If you can speak the saleslanguage, like, what is the
value for this company ofapplying this solution?
Maybe not now, maybe in fiveyears time, whatever.
Uh, you need to transmit it tothis particular person.
But then you have technicalpeople that maybe have different
interests.
You need to understand what aretheir interests and and try to
transmit that in the languagethat they understand.
(33:30):
So I think right now, since wecannot have a product that is
perfectly defined and we canpackage it and say it has a
product that is more orientedtowards services, you still need
this type of people that hasmixed backgrounds, that they can
talk a little bit the businesslanguage and also the technical
(33:51):
language.
Speaker 1 (33:52):
And how can you qualify whether a lead Because I
assume you're not doing salesoutreach it's mostly inbound
companies reaching out andsaying, hey, we want to explore
something with you.
However, you know that a highpercentage of that they just
want to entertain the idea, justto learn the basics, the cost
implications, whatnot but theywill never get to sign the
project right.
(34:12):
How do you qualify that?
Speaker 4 (34:15):
I mean for quantum computing.
So if you talk only purequantum algorithms and quantum
computers, that is only in sales.
We call it ideal customerprofile and there are really few
people inside organizations andreally few organizations that
are willing to invest in themid-long term.
Okay, so identifying what is toinvest in the mid-long term, so
identifying what is the accountin the mid-long term is pretty
easy.
Just look for the ones withdeepest pockets, and these are
(34:39):
the ones typically.
Speaker 1 (34:41):
Like Sergio.
Speaker 4 (34:42):
I mean, these are the guys that want to invest in the
mid-long term like five, tenyears' time again, to understand
the technology.
And inside those organizationsthey are the more technically
versed, like innovationdepartments, research
departments.
These are typically the areaswhere you scout for quantum
computing projects and then youhave mechanisms like public
(35:06):
funding, for example RFPs andgrants, to try to support the
business case with thoseorganizations on how to build a
project with them.
Right, and that's it.
Speaker 1 (35:17):
How can people reach out to you and why should they?
Speaker 4 (35:21):
I have a guy that's called Victor Gaspar.
He's a Brazilian top model.
It's not me, okay, Because ifyou go to this guy, I mean my
God, he's good.
Speaker 1 (35:32):
Everybody has got a doppelganger.
What is?
Speaker 4 (35:34):
going on Too many people.
So LinkedIn.
My email is victorgaspar atmultiversecomputingcom.
Pretty easy, and I mean reachout if you want to talk about
quantum computing, quantuminspired, how to use quantum
inspired computing for AI, Idon't know.
Let's have a conversation.
Speaker 1 (35:55):
Thank you.
Speaker 3 (35:56):
How about you?
I'm pretty easy to find.
You can subscribe to mynewsletter, the Quantum Pirates
and Substack.
You can buy my book, the CTOToolbox.
All the proceeds go to a coupleof fantastic NGOs in Barcelona,
and you can pick me on LinkedInanywhere.
Why should they?
Speaker 1 (36:17):
Oh, why?
Speaker 3 (36:18):
Because I'm awesome, that's fantastic Dorit.
Speaker 1 (36:21):
how could they reach you?
Speaker 2 (36:22):
I'm Dorit Dorit at LinkedIn.
I think there is not muchcompetition to my name.
Speaker 1 (36:29):
There's a Ukrainian developer that got your profile
or your GitHub handle orsomething like that.
Speaker 2 (36:37):
I'm also Dorit at checkpointcom.
I'm also Dorit at qubitvc andyou could reach out to me for
cyber stuff.
That's on my side of the oneside of the head.
On Quantum, we are looking forpipeline investors and strategic
relationships, so happy to talkto you on any of them.
(36:59):
I'm also enthusiastic ontechnologies more generally, so
AI and other stuff.
Speaker 1 (37:06):
the world is just very exciting thank you very
much, ladies and gentlemen.
Applause, applause, big thankyou.
Very exciting.
That's it.
Thank you very much, ladies andgentlemen.
Big, big thank you to thepanelists, all of them.
Big thank you to the crew andthe organization and our
sponsors.
Again, cms and Moody's, thankyou very much for putting up
with me and my fuck-ups forseven plus years.
(37:27):
I'll see you all.
In the next room there's acatering and the beers.
We're going to have one hourfor that.
Thanks for the mics and for themics.
Yeah, next year with NVIDIAmics.
Thanks, thanks, thanks.
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