Music.
Hello and welcome everybody. This is Joe from StartupRate.io,
your startup podcast, YouTube blog and internet radio station from Germany bringing
you news and interviews from the German startup scene.
Today, I'm delighted to kick off again our fourth cooperation with the German
Startup Association where we interview the winners of the German Startup Awards.
Today, I would like to welcome the Newcomer of the Year, German Startup Awards
2024, Isch. Hello and congratulations.
Thanks so much. It's my pleasure to be here. It's awesome that you are here.
We already had a lot of fun before this interview started.
Maybe we can give you a sneak peek into what we've been talking about.
But first, as always, we'll be talking a little bit about you.
You are joining me from lovely Ulm, but you have not always been there.
When I've been looking in your LinkedIn profile, by the way,
as always linked in our blog post, you studied in Canada, University of Calgary,
India, India Institute of Technology in, how is it pronounced, Canpur?
Canpur, yes. Canpur. And in Germany, University of Ulm.
And as all Germans, we always have the tongue twister in mind in Ulm, Ulm, Ulm, and Ulm, Ulm.
Can you take us a little bit through this journey, including,
I've seen you have been awarded the National Child Award for Exceptional Achievement
by the Prime Minister of India in 2006. Thank you.
You must have done something outstanding. Can you tell us a little bit about
this before we dig a little bit deeper in what you've been doing?
Plus, did you have a lot of warm socks in Calgary?
Let's start with the last question. Yes, warm socks. Absolutely.
The best warm socks are what you get in Calgary.
Yeah, talking a little bit about how it was like growing up in India.
I think I'm really grateful for a lot of effort put in, for example,
in finding young talent.
And giving them opportunities that are otherwise hard to come across.
So there were a couple of opportunities for me as in, let's say,
ninth grade or tenth grade, where we had the possibility to be challenged in science creativity.
So lots and lots of top scientists would come together with these young kids
from the age of 10 to 20 or so.
And then they would basically challenge these kids to do something creative,
which means from everyday objects
that you find around the house can you make something that's
truly new not just reproducing textbook experiments
but make something truly new and this was the national
Palshri award and here the
award was given by the president of India back then
this was APJ Abdul Kalam who is one of
the top rocket scientists in the world and spent a
lot of time in NASA and then also set up the
rocket program in India or really took it forward quite a bit
and following from that there was the
national child award for exceptional achievement by the prime minister of india
where it was really a similar situation from every province in india they chose
one kid for basically going above and beyond and exports expose them to opportunities
which otherwise quite hard to get so those were really formative experiences
for me growing up in India.
I see. And how did you end up in Calgary?
Because being from India or from Germany, you don't think about studying in Calgary.
You have other universities, especially in the US and the UK or even in Australia in mind.
How did you end up in Calgary and how did you like it? Interesting.
So I did my undergrad, as you mentioned, in IIT Kanpur.
This was an amazing place. I focused as an undergrad on doing computer science. That was my major.
And it was basically one of the top programs in the world. And also,
I was very interested in physics.
And Kanpur gave me this possibility of being at the frontier of both computer science and physics.
During my time there, I learned something very cool about quantum computing,
which is that if any civilization anywhere in the world is building the ultimate
computing machine, team.
Then this computing machine is basically a universal quantum computer.
So I was very interested in quantum computing during my time in my undergrad at IIT Kanpur.
So starting out from computer science, then the next stop was to basically look
for a physics master's or PhD and try to explore this new field of quantum computing.
I applied, of course, to top universities in the US, lots of good universities
in Canada. And basically, I got rejected from every single U.S. university.
I think from their perspective, I really understand what is this computer science
guy trying to do here in the physics department.
But then in Calgary, there is a strong core of quantum computing researchers,
including my Ph.D. supervisor, Barry Sanders.
And Barry really saw the potential in working at the interface.
And then Barry took me on as a master's student very quickly switched to a PhD
program in three years or so finished the PhD did some really incredible work
with Barry at that time I was really happy with what came out of the PhD and
yeah that's that's how Calgary happened.
I see so they're very good in quantum computing uh-huh we may add that the India
Institute of Technology IIT is one of the premier institutions of educations in India.
And now we have this piece. Then it doesn't take a much longer way to understand
how you ended up in a quantum computing unicorn.
But first, let us take a little break for our sponsor. our sponsor,
StartupRaven.com, the best way to find investors and cooperation partners for early stage startups.
You can sign up for early access at StartupRaven.com. And we may tease that
we've covered the German Startup Awards since 2021.
So in the fourth year now, and down here in the show notes, we will give you
a link to a playlist of 21, 22, 23, and you're the first one of 24,
but hopefully not the last one.
So, as I was teasing, you ended up working in Toronto at the quantum computing unicorn Xanadu.
Was this a connection from the university? Not so much from the University of Calgary.
So, I think we moved to Xanadu.
But maybe one can talk a bit about from Calgary, I actually then moved to Germany.
And I think the German experience is actually then what led me to Xanadu.
So talking a bit about that, that is an interesting twist.
You came from India to Calgary to Germany, only to go back to Canada.
Absolutely. Quantum computing is an international is a very,
very international activity right now. We're all working at the frontier of human knowledge.
So geography, I think, doesn't stop people from basically working on cool things.
Okay, okay. So you came to Ulm here in Germany, right? Yes, absolutely.
I spent around three and a half years doing a postdoc with Martin Plenio,
who is now the co-founder of QC Design, actually, the startup along with me.
And so in those three and a half years, I think one of the things that happened
was we started to see quantum computing as a field go from something that happens
only in the lab to something which is actually of true potential and something
where actually humanity can start to use the fruits of quantum computing.
This was the time from 2016 to 2019.
I was fortunate enough to be able to work with Martin, more on that in a moment,
but also to be able to work with the top experimental groups in the world and
really see this technology coming out of the lab.
So it was only natural that basically by the end of my time there,
I wanted to do something useful, something that actually we can build,
you know, a real quantum computer that's useful.
And Xanadu was the best place for this.
I see. And there you actually headed a team, right?
Yes, I headed the architecture team, one of the three teams.
Very proud of the work that the team did there. So one of the things that we
worked on was to come up with the first true blueprint for building a useful
quantum computer with light.
And it was an amazing experience because in six to nine months,
basically, we put together a team of top researchers in that specific field in whatever capacity.
We were able to align this team towards working on one single goal,
which is, I think, quite non-trivial because often we are working with top researchers
who are very independent-minded.
And with that aligned team, we were able to work together and deliver something
which really pushes forward how humans think about quantum computing.
So that blueprint project is something I'm very proud of in terms of how well
the team accomplished it.
Before we get into that so quantum computing is based on quantum theory on the
works of Max Planck and the quants are little crazy pieces so small the smallest
we can investigate right now and.
I do believe you can only see those pieces. When you smash atoms,
we have very extremely fine instruments, only then it is even possible to investigate them.
And that is basically the level when the laws of physics that govern our world
are actually breaking down, as I understand, they have a randomness to them.
And that always reminds me of Heisenberg in Breaking Bad. And also,
I do remember quants, they do have, some of them have spin and taste and something like that.
Can you give us a very, very dumbed down introduction into quantum computing?
And then after we've done that, we'll talk about quantum computing with light. Okay.
Sounds good. Sounds good. Let's talk about quantum physics for a moment.
So there are two aspects here. There is what I would call quantum physics 1.0.
Where we start to look at the behavior of individual atoms or individual particles of light.
And this kind of physics actually underlies a lot of the technology that we use today.
So the laser in the supermarket or the silicon chip in the computer that you
and I are using, these all use quantum effects already.
But here we are just using the fact
that quantum states can be in superposition
which is just a big word for saying that it can be in the state 0 in the state
1 at the same time unlike a classical bit which can either be 0 or 1 but not both at the same time.
Sorry, one question. If you rely on those qubits, it sounds a little bit like
it's a bit with Alzheimer.
How can you work with that? This is actually a very deep question and interesting.
Working with these fragile, almost random bits, random qubits,
is one of the big challenges to building a large-scale, useful quantum computer.
And the way we work with it is in spirit.
It's very similar to how, for example, the Wi-Fi that we use,
the Wi-Fi connections that we
use, can still work despite there being some interference along the way.
The answer is called error correction. So you use many, many quantum bits to
act together as a single but very reliable logical qubit.
And this logical qubit is basically what one would use for useful quantum computing.
And still there are many quantum pieces there working together as a qubit.
They're still faster and smaller than
a normal bit would be yeah so a single
logical qubit could comprise somewhere between 10 and 10 000 physical pieces
physical qubits so there's a big overhead here and nevertheless there are some
problems for example if you want to study a molecule or study
a material or break encryption, for example, there are many problems where quantum
computers can do things which classical computers just cannot do.
And this is why there is great promise in a new way of computing,
basically with logical qubits.
And what, for example, would they be able to do?
The first applications of quantum computing will be in simulations of materials
and molecules. But what does that mean?
If we want to study the properties of a drug on a computer before we ever start
to make it in the lab, this is something a quantum computer can help with.
If you want to come up with a new kind of a material for an electric vehicle
battery, this is something which can be done in simulations on a quantum computer
much, much faster than what a classical computer could do, even a supercomputer.
So these are the first applications. But only when we actually start to build
truly useful quantum computers will the next set of applications get unlocked.
I see. So we're now a little bit in quantum computing.
And now, can you tell us a little bit about the world of quantum computing and
what your company, QC Design, that he co-founded, is actually doing?
So we're now drilling down to the core of the matter here. Right.
So as I mentioned, to make a useful quantum computer, you need to put many physical
qubits together into a logical qubit. but this requires really sophisticated designs.
There are an infinite number of ways of putting qubits together,
of controlling them with, for example, microwave pulses or actually looking
at the qubits and using that information to figure out where an error happened.
So all of these designs together this is
called an architecture and there are
many hardware manufacturers in the
world right now who are working on their first
architectures for useful quantum computing on their first demonstrations of
useful quantum computing this is the endeavor that we at QC design support so
we provide very powerful design
software you can think of this design software as for example AutoCAD,
or if you come from the semiconductor industry,
then you can think about design software similar to what is provided by Cadence and Synopsys and Ansys.
But this design software gives our customers superpowers.
So it's researchers and architects within quantum hardware manufacturers that
use our software to come up with the most efficient ways of building I see.
So to put it in very, very simple terms, you're kind of the computer assisted
design that architectures would have for their houses, but you are this piece
of software for quantum computing. Absolutely.
I think now a lot of people understood here. And I'm going to ask you a question.
We skipped over a few pieces here, but in the preparation, we had a lot of text
here, and we went over some of them.
But going a little bit back to qubit and quantum computing,
according to your own website, you participated in a world record tomography of a 14 qubit computer.
Did you end up in the Guinness Book World of Records with that one?
Unfortunately not. It's not yet a category, but maybe one day it'll be.
I have to say, this was really a part of a big team effort. And there were many,
many people who were working much harder on this goal than I was.
But it was a very interesting experiment, which we performed with collaborators
in Innsbruck and along with basically my research group where I was working at Ulm.
We had come up with a way to solve an interesting and important problem in quantum computing.
So, as I mentioned, quantum computing can do things which classical computers
just cannot do, which is great.
But it also poses some challenges along with it. And the challenge is that it's
really hard to figure out whether the quantum computer is doing the right thing.
It sounds like AI.
Yes, perhaps even worse. Who knows?
Okay. And tomography here just means that given a quantum computer,
can you do something to it to figure out what actually it is doing?
And this was a very efficient algorithm developed in the research group where I was working.
And we worked with one of the top research groups making these quantum computers
to realize this tomography algorithm.
And yeah, it was a very positive result that the quantum computer was doing
more or less what we thought it should be doing. and this was on a 14 qubit
quantum computer back then.
I do think this was 2019 or so and then since then the field has moved on.
We have way more qubits out there in the wild today and many more powerful quantum computers.
Mm hmm. And going a little bit back on what you and QC design are doing.
How did you actually start this idea?
Because you've been working with quantum computers in the past? Yes, of course.
This question is still open how quantum computing would light would work that
we need to answer to our audience.
But first, can you take us through the steps that made you with the co-founders
start QC Design? Absolutely.
The founding story of QC Design is that we really wanted to push the envelope
with what one can do in terms of useful quantum computing.
Computing and this is something which
we are very proud of right
now that our software helps every quantum
hardware manufacturer on the planet potentially to come
up with the best designs and basically be
able to build useful quantum computers two three
four five years faster than without our software so i think that's the big vision
and i'm really very happy with the team that we've been fortunate to be able
to put together for the founding and as well as for the core team here in and around Ulm.
So the type of software that we build, this computer-aided design for quantum computers,
this type of software needs three kinds of expertise and one is this expertise in error correction.
So how do you make a perfect near-perfect logical qubit from many physical qubits,
it needs expertise in hardware.
So what are all the nasty things happening to these tiny particles of light or tiny atoms?
And you need basically.
Quantum software. How can one harness the properties of this hardware using software?
So in the team we've been able to from the very early days have this combination of expertise,
and we started to build this software and realized that it's something which
many many hardware manufacturers care very deeply about and so we really went
all in on providing this software to so many of these hardware manufacturers.
From my understanding, it's actually essential for the survival of those hardware
manufacturers to be able to really,
do that, to be an early adopter when quantum computing shows up because otherwise
they'll they'll be left in the dust, right?
100%. I think quantum computing is a part of the future of computing,
a very big part, if not the future of computing.
And we really need to focus on this task of putting together noisy physical
qubits into these near-perfect logical qubits, which makes the whole device useful.
I see. And you said you can be helpful to all hardware manufacturers out there.
In terms of markets, how many companies were you talking about there?
In terms of quantum computing manufacturers, there are about 60 or so quantum
hardware teams right now that are working on building full quantum computers.
But this is the early days. This is basically the transistor era of quantum computing right now.
The moment we switch to the pocket calculator era, basically have useful quantum
computers that solve one commercially valuable problem, then there will be many
more companies coming up.
I expect that in the next five to 10 years, this number will go from 60 to way
more than 100 and including potentially very big companies that are solving
very important problems for massive industries.
What comes to mind are the usual
hardware producers of the pieces that I have here in my new computer.
How many clients are already using your software?
So we know that our software is being used in a handful of hardware companies right now.
Let's say half a dozen or so companies are using it. and this number is something
that we're working hard on improving in the coming days so we're still a very
young startup started about two years or so ago and.
Converted our first customers recently and really now working hard on finding.
More and more utility for the software more and more people using the software
do i understand it right that right now talking about old computers here that right now teams who are,
trying to figure out how a quantum computing cpu could work are now using this
and over time could Could your software also be used for the companies producing the hard drives,
the graphics cards, and so on and so forth?
Whatever is needed in those future configurations of quantum computers?
100%. That's really the vision. So we want to be able to help our customers,
these hardware manufacturers, go from end to end.
Basically, before having to step foot inside the lab, can you design all parts
of the quantum computer?
Right now, it is unclear what these different parts are.
It's still an open research problem. So we have mostly the processor part of
it where there's a lot of iteration going on.
But over time, there will also be the memory part of it or the part of it which
would connect with other quantum computers and do all of this in an error-corrected manner.
And we hope that one day our customers can use our software to design all of this.
I see. And one question about.
As you said, it's not yet clear, but one question about interoperability of those systems.
Do you believe if there is at one point an economically viable CPU,
a commercially viable CPU built by a quantum computer company,
do you believe it would be simply able to be plugged in existing hardware,
abstracting from the fact that you would need to completely rewrite all the software on it?
In order for quantum computing to succeed, this is the only way.
We want to have a world where billions of people can directly program a quantum
chip like they can a classical chip.
And I don't know, maybe five to 10 years down the line, do this programming
without having to learn a programming language, but directly through voice and via AI tools.
This is the world that should be,
I also think that there are many smart people working very hard on this.
There are several top companies, many startups, many bigger companies all working on making this happen.
How do we make sure that a smart programmer who can code for a CPU today,
for a classical semiconductor chip today,
can also learn very quickly how to code for a quantum computer and basically
make this power of quantum computing available to everyone.
We've been talking now a lot about your company and quantum computing,
which actually is, I would say, a deep, if not deep, deep tech startup here.
Do you think it's possible to build something like this really lean?
100%. This is something we care a lot about. out.
Traditionally, people think of lean startups as being kind of opposite to deep
tech startups. So what's a lean startup?
This is the standard playbook for, for example, software startups to succeed.
You build a product, put it in the hands of the customers early on,
even if it embarrasses you, you learn from this and then build again.
So the build, measure, iteration loop is at the core of a lean startup.
And deep tech startups, to put quite simply, they are taking ideas that existed
so far in a research group in a lab and putting it in the hands of the customers.
And I think that these two ideas are actually much more compatible than we've thought so far. Why?
Firstly, because most of the people working in deep tech startups,
especially the core team, the first 10, 20 people, they often come from science
and engineering and are so used to the scientific method where you make a hypothesis,
You go to the lab, test the hypothesis,
come back, change the hypothesis if the experiment was not successful.
I think a lean startup is nothing but applying the scientific methods to building a great company.
So once this kind of mindset is established in a deep tech startup,
then I think it's very easy to have everyone on the same page about building something lean.
I can say that for us, this is an experiment that we've been working towards.
Words. We don't know whether it's successful yet, only time will tell.
But we focused from the very early days in building things in a matter of days,
even if it was slow, even if it was,
90% of the way there, not 100% perfect as a product, and showing it to customers.
And our customers, being architects and researchers in quantum hardware manufacturers,
We were so lucky that everyone was extremely open about sharing what are their
pain points and what is it that is really exciting about such software.
So for example, a visualization tool that we hacked together over one weekend
to scratch our own itch ended up being one of the more interesting things for customers.
And this way of working has solved one very important problem for us.
So as a company, as a deep tech startup, we are taking ideas at the frontier
of human knowledge in error correction, in quantum computing.
We are taking that, whether it's research that we do or research that other
people do, and taking that and putting it into production level software.
Now, as you can imagine, the frontier of human knowledge is vast and which of
the ideas, which of the many cool and fascinating ideas are also useful to our customers.
This only a lean way of working can help. So everyone in the team is really
excited that now we know for sure that what we are building is actually being
used by somebody to build a useful quantum computer, which will push humanity forward.
So I think that the lean way of working is not only, it's definitely not.
Not antithetical to building a deep tech startup, but can actually help move
a deep tech startup forward.
You've been talking about building startups on the edge of human knowledge and technology.
You've been saying,
in India, in Canada, and here in Germany in academics, in different levels,
even as a postdoc here in Germany.
I was wondering, do you believe that Germany could do more to enable those spinoffs
out of universities, research institutions, and so on and so forth?
This is something I care very deeply about. I think that deep tech startups
truly have the potential to push humanity forward.
So whether it was the transistor or the microchip or the internet,
every time somebody took something from a lab and put it into the hands of customers,
a lot of things changed. Humanity really advanced.
Deep tech startups do precisely that. And so far, many of the deep tech startups
that have come up have been very concentrated, traded, for example,
in the Silicon Valley or a few other hubs across the world.
And I think this is really a pity because talent is everywhere.
And to some extent, money is liquid. It can be everywhere.
So it's not the lack of talent or money that is holding back Germany,
Europe, or many other parts of the world from basically having more and more deep tech startups.
It's something else i feel like there is a
lot of friction in the process of
taking something from the lab and actually
putting it into a company environment and trying
to take it to customers and i feel like friction if removed can actually 10x
the amount of deep tech startups coming from coming from research and academic
hubs in germany and in the rest of the world So friction can be in the form of,
you know, it's really tough for a PhD student to spend six to 12 months just
working on some crazy idea and a program,
for example, where there is a little bit of money and a lot of freedom that's
given to young researchers to just explore a startup idea.
Something like this could really reduce friction.
Friction also comes in the form of kind of tech transfer agreements between
universities and startups, and I have to say that the U.S. does this much better
than the rest of the world.
So, a simple agreement where.
The university takes a part of the company so that they are also aligned with
the success of the company and in return basically offers their full support
in terms of intellectual property.
I think a much simpler agreement like this, rather than, for example,
three different ways in which royalties are charged or things like that,
this would also reduce the friction a lot.
And many more people don't have to wait months, but instead in a matter of days
or weeks can basically spin out of a university.
I have to say we are very fortunate to be working with the University of Ulm,
but I think this is not the usual experience that people have.
And it's really, it can take months for IP agreements to be set up with universities.
And I think the final part of this friction is coming from the lack of role models.
So for me, this was Martin Plinyu, seeing this world-class researcher who is
one of the top cited researchers in quantum information, who has mentored hundreds
of PhD students, many of whom are professors or leaders in the industry now.
But also Martin wanted to do more than just academia and Martin set up Envision
Imaging, which is now a quantum imaging startup that's eight years and the product
is on the market. So this was really inspiring.
So the fact that it's possible to do it, that also cuts friction.
So I feel like we should talk more about people trying to build deep tech startups
or especially deep tech startups that are succeeding.
So such small things reduce the friction, make it possible for deep tech startups
to basically come out of everywhere, wherever there's talent and unlock this
latent potential that's hiding in the universities right now.
Amen. Actually, one of the many things we try to do here is really to show the
movers and shakers of the future, those people who found path-breaking startups.
And that's at the core of StartupRate.io. That's why we'd also love to show more spin-offs here.
Thank you. let's go we've already
drifted into our outlook but um i
would be curious about a few questions and then we can close this interview
um how do you envision quantum computing revolutionizing industries and what
real world problems do you believe we could solve with quantum computing that we cannot do now,
you've been talking about drug discovery.
And I've talked to a lot of people around here.
And most of them tell me with a classical computer right now,
NDAI, they laid the groundwork for the very fast development of the COVID vaccines here.
These are other problems down the road that we could also solve with introducing
like real world problems with the introduction of the more capable quantum computing?
Absolutely. So you already mentioned designing drugs, designing new vaccines.
I think these will be the first problems where actually we'll see a real impact,
but also starting to design materials.
One important material which we don't think enough about
is fertilizers and fertilizer production
consumes about 3% of all energy worldwide
but if you
see how plants do it it takes a fraction of the energy of
how we do it at an industrial scale so a quantum
computer could perhaps help us understand more deeply how
plants do it and come up with new ways of making fertilizers that could cut
the energy consumption of the fertilizer process by a factor of a 10 or 100
so this is just one of the materials would be cool if quantum computers could
help us design materials for carbon capture,
would be amazing if we can have new batteries that are designed by quantum computers.
All of these are things which inherently quantum computers are good at because
all of these problems involve simulating materials.
And it's something which classical computers are not very good at,
but quantum computers being good at being basically quantum can simulate quantum
materials very, very well.
So that's my hope for what quantum computers help us with. A lot of talk is right now about AI.
There's we've been also talking a lot about the increasing capabilities in quantum computing um,
do you have like any and please don't
get me wrong i know forecasts are always difficult especially concerning the
future um but can you do you have a few guesses a few ideas is how the development
and capabilities of AI could improve with being on quantum computers and not
the usual silicon-based computers?
I think right now, AI is growing very rapidly.
And this rapid part is where things get interesting.
Existing so the amount of money time energy spent training a new model has gone
from tens of millions to hundreds of millions to billions now in a matter of only two to four years.
There is no reason to believe that this acceleration
will not continue so we do expect tens of billions or so spent training the
next models and this will continue we can imagine Imagine companies like Microsoft
and Google and perhaps other entities spending this kind of money training their new models.
But what happens when we go to hundreds of billion?
This is really now pushing it. A trillion dollar model? This is not feasible anymore.
And there is definitely an upper barrier coming very, very fast.
So the question is, how do we move away from how things are done right now,
classical computing, to actually come up with new,
more intelligent models?
We need an alternative. So quantum computing is definitely an alternative which could help.
I think this is a very active area of research right now. Many smart people
are devoting their time and lives towards understanding how quantum computers
could actually help AI or actually vice versa,
and have AI help us build better quantum computers.
I understand. So they can help each other.
I see. So as soon as the first quantum computer starts working,
you can build an AI on it that helps you design better quantum computers.
That'll be interesting. Yeah, that's really interesting.
But before we get into that, let us get a tiny bit back to QC design.
The usual closing questions. Are you looking for capable employees?
And if yes, do they need a PhD in quantum theory?
Building software like we do needs all the
smart and kind people that we can have join
us on this mission so we are
definitely looking for people we're looking for people who can write pleasing
fast code we're looking for people who understand very deeply how qubits work
and how they talk to each other so I guess those are much more research kind
of positions I guess even Even a smart and ambitious master's student can definitely
get to this frontier in a matter of months. I don't think a PhD is needed.
And I also personally feel like for quantum computing to go from a niche industry
where there's a bunch of startups and two big companies building quantum computers
to basically it being a worldwide endeavor.
We need to be able to make sure that many, many smart people can come together
and build useful quantum computers. So don't let the lack of a PhD stop you
from applying to a quantum computing role.
And if you're interested in building software that helps humanity get to useful
quantum computing, do reach out to us at jobs at QC.design is the email ID.
And of course, you need to pay those people. Are you open to talk to new investors?
Yes, we are right now in the middle of a funding round.
This is to take us from first customer attraction to a true product market fit in a lean startup style.
We still have a very comfortable runway, so we're not really desperate for money.
But we think that there's a massive opportunity and really an undervalued opportunity
in making this EDA or electronic design automation like software for quantum computing.
So if this is something that is interesting to potential deep tech investors
or investors in basically B2B software companies, then we'd love to talk. So happy to talk.
Ish at QC.design is where you can reach out to me.
And of course, as always, we link down everything down here in the show notes.
So there will be your LinkedIn profile. People can reach out on LinkedIn.
We'll add your email in some crypto kind of way. Then you don't get a lot of spam, hopefully.
Or maybe we just stick to the LinkedIn profile.
It was a pleasure talking to you. Thank you very much. Congratulations again
to your German Startup Award Newcomer of the Year 2024. and best of luck in
building QCD Design further. Thanks so much. It's been a pleasure.
The pleasure was all mine. Have a good day. Bye-bye. Bye.
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