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00:01And for all those who are joining us right now, here and behind their screens remotely, welcome to Vivitech.
00:07My name is Asha Sampet, I'm your host on Scaling Up Stage 2.
00:11We are live from Paris and this session is part of a series focused on major tech markets to follow.
00:18So this last discussion today will focus on deep tech.
00:22So I'm very glad to welcome my guests.
00:25I will welcome them in just a few seconds, but just some context.
00:29So we're going to look at how the complicated, hard to commercialize fundamental technologies move from the lab to the
00:38market.
00:38And what is the market's current attractiveness?
00:42So I'm really excited to talk about this with my guest here.
00:46With me, we have Manjari Chandran Ramesh, who is a partner at Amado's Capital.
00:52And on my left, Antoine Petit, the CEO and chairman of CNRS.
00:56So you're going to tell us what is CNRS, because we in France, we know what it is, probably internationally,
01:03not usually clear for everyone.
01:05So thank you to both for being with us here today at Vivitech.
01:08So Antoine, before we dive into deep tech, CNRS, tell us.
01:14So CNRS, CNRS, Centre National de la Recherche Scientifique, is probably the largest public European research institution.
01:24And we cover all fields of science, including humanities and social sciences.
01:29We are 34,000 employees with an annual budget of 3.6 billion euros.
01:36And our job is to do fundamental research.
01:39But nevertheless, our goal is to transfer this fundamental research in the economic and industrial worlds,
01:48in particular through startups and particular deep tech startups.
01:53And you said probably, but that's not true.
01:55You're being humble.
01:57It's the biggest.
01:58Yes, we do it.
01:59We create with our partners, universities and Grandes Écoles in France.
02:04We create between 80 and 100 startups every year.
02:10And one of them also entered in the CAC 40 last year.
02:16Probably you missed it.
02:17It's Eurofins Scientifique.
02:20Okay.
02:21Who entered in the CAC 40 last November, I think.
02:24And in fact, it has been created in 1985, so 37 years ago.
02:31But it comes really from a CNRS, a joint lab between CNRS and Université de Nantes.
02:38And probably if we were in the US, we were most better to emphasize on this story,
02:45to tell a right story about that.
02:46Since we're in France, in Europe, we don't speak from my point of view.
02:50But I think it's really a good story.
02:52Fantastic.
02:54So probably, I mean, we are going to talk about deep tech, obviously.
02:58And for people who know the topic, it might seem a little bit patronizing.
03:03But for many here, deep tech is something that can be very blurry.
03:09So what is deep tech concretely?
03:11And can you give us examples?
03:13Yes, I think the term of deep tech has been coined or invented
03:17to make a difference between Internet-based technologies.
03:23This last technology, of course, there is nothing wrong with them.
03:27But they are based mainly on the appropriate use of Internet with marketing digital.
03:34It is the example, for instance, of merchant seats or destination seats.
03:39On the contrary, deep tech is based on the fact that you have a potentially disruptive technology
03:47and you will construct a startup from this deep tech.
03:52And that's why a lot of them come from labs like CNRS Labs.
03:58And we present here in Viva Tech something like 30 startups
04:03and invite people to go on the CNRS 2s, where we present 10 of them in very different areas.
04:14To give you some examples, we have Alice and Bob, who are working on fault-tolerant quantum bits.
04:21We have, for instance, Cardiowave, who has invented a device which allowed to cure,
04:31thanks to ultrasounds, a herd disease, which can be a deadly herd disease.
04:41We have another startup which transformed the dioxide carbon, CO2, which is not interesting,
04:53in CO, so monoxide carbon and oxygen, which are very useful for industry.
05:01Just to give you some examples of what we do here at Viva Tech.
05:05That sounds exciting.
05:06Thank you, Antoine, for sharing.
05:08Manjari, so my question to you, what defines the commercial success of a deep tech solution?
05:16Hi, so I'm Manjari Chandran Ramesh.
05:19I'm a partner in Amadeus Capital Partners.
05:25Hopefully, I think they can hear us.
05:27Okay, great.
05:29So just before I answer that question,
05:31for those of you who don't know who Amadeus Capital Partners are,
05:34we're a global technology investor, and we invest in deep tech.
05:40So we've been around for 25 years.
05:42We've raised over a billion.
05:44We have backed 180 companies and had 90 exits from those.
05:49And as Antoine mentioned, we do everything from life sciences to novel materials,
05:58hardware, deep tech software, quantum.
06:01So we do the entire spectrum.
06:04And some of our success stories are Tobii, which are listed in the Stockholm Stock Exchange.
06:12ForScout, which listed on the London Stock Exchange.
06:15Sorry, the NASDAQ, not the London Stock Exchange.
06:19Cambridge Silicon Radio, which was a big, which revolutionized Bluetooth and got acquired.
06:25And VocalIQ, which was acquired by Apple.
06:28So what does commercialize, sorry, your question was...
06:34I mean, really, what really defines, you know, the commercial success of a deep tech solution?
06:39So when we get involved, it's very early stage.
06:43It's platform technology.
06:45And the place where we get involved is this is very differentiated.
06:50It is a novel idea, novel piece of research.
06:54But there is little else to go on.
06:57And so what really brings out successful commercialization is, I feel, two aspects.
07:03One is, can we identify a pain point in the business, in the market sectors that this particular technology is
07:15particularly suited to solve?
07:18Now, unless there is a really valuable pain point, even if the technology is fabulous, a business cannot be created.
07:26So that is a key aspect.
07:29The other aspect that we look at is the team itself.
07:32Now, it doesn't need to be a fully formed team.
07:35But I think team dynamics, the founders, quite often the founders are academics who, you know, will bring in a
07:43commercial person to join them on the journey.
07:47And sometimes that works brilliantly.
07:50There's, you know, great respect between, you know, the founding team.
07:54And sometimes, you know, there is absolutely no respect.
07:58And so it doesn't work unless the team works very cohesively.
08:03Thank you for sharing, Manjari.
08:05Did you manage to hear that, Antoine?
08:07Yeah.
08:07Yeah, okay, fantastic.
08:08Just checking because there were sound issues early on.
08:11So, Antoine, my question to you.
08:14What, according to you, what are the biggest challenges, you know, for a technology to evolve from research to commercialization?
08:24That's really an issue and not an easy issue.
08:30First of all, the most outstanding scientific result is probably the most disruptive the technology coming from these results can
08:43be.
08:43And so more of the chances of success are important.
08:47So that's why a center like CNRS, even if our job is to do fundamental research, we really try to
08:56do it at the better international level, better possible.
09:00And that's a chance of success.
09:02But it's not a guarantee.
09:04First of all, since it's deep tech, if you want to transfer a deep tech, you need the involvement of
09:10the scientific leader.
09:12That's clearly a key issue.
09:13If you have a leader who is not willing to do a startup, nobody can take his place or her
09:20place and to transform the startup.
09:23And so, and sometimes it's not easy because if you have decided to be a scientist, you don't necessarily want
09:28to be a startupper.
09:30And so you have to convince people sometimes that it is for them an issue.
09:36And that's why quite often it's PhD students who are the startuppers because they did not start already their career
09:44and they prefer to go there.
09:47The second one is even if an outstanding scientific result is needed, it's not sufficient.
09:53You need to have a product and you need to have a market and you need to understand the needs
09:59of the market.
10:00And sometimes it's complicated to say to a researcher, okay, you have a very interesting concept, outstanding, but where is
10:08the product?
10:08Where is the market?
10:11So the point is what was already mentioned is a team.
10:15And once again, it's sometimes complicated to say to a researcher, okay, you're at the origin of these startups.
10:23Without you, the startup would not exist, but you cannot be the CEO.
10:28And that's sometimes complicated.
10:31It's like if you take a baby, okay, they consider their startup as their baby.
10:35And if you say, okay, you will not be in charge of the baby, that's complicated.
10:39So you have really to construct a team because clearly a startup is a collective initiative.
10:45So that's all the ingredients which are needed to go from the scientific result to a startup.
10:51And of course, you also need money, but that's not my specialty.
10:55So if I sort of add to that, so I've had these conversations and the way I characterize it is,
11:02you know, as parents, yes, you're the parent of the baby, but you would ideally leave the teachers in the
11:09school to teach your kids.
11:10As much as homeschooling happened in the pandemic, I think all parents realize the limitations of their teaching skills.
11:18It's very much the same, right?
11:20You will never stop being the parent.
11:22The prof will never stop being the parent of the company.
11:27They'll always be the founder.
11:28But sometimes there are certain skills that just, you know, other people have and will, you know, the business will
11:35benefit.
11:36And so that's usually my conversation.
11:38You are the parent, but let the teachers do their work.
11:41Absolutely.
11:42So, Manjari, where do you see deep tech?
11:45Where do you see the potential?
11:47Where do you think it has the most, it can make the most impact?
11:52So that's a really interesting question because, you know, deep tech itself, it's pretty long-term.
11:58It's not your consumer app, typically.
12:01It's not something that, you know, you flip in two, three, four years.
12:06So I characterize this as, you know, the deep tech short-term, medium-term, and longer-term.
12:13So I think, you know, we have had a lot of sessions on AI and machine learning and deep learning.
12:20And there are some really good solutions out there that, you know, are still what I call a bounded problem.
12:26There is a lot of markets that are still not data-driven.
12:29There are a lot of markets like, you know, construction tech.
12:32So we have a company called XYZ Reality that is revolutionizing the construction tech.
12:39There are other markets like, you know, the restaurant area that is just not data-driven.
12:45So I think in the, you know, sort of shorter term, we'll see a lot of stuff that comes about
12:51in these markets.
12:52Then, you know, if you sort of move to the medium term, I think, you know, generalized AI is still
12:57very elusive.
12:58There's a lot of research happening.
13:00I'm super excited about what the researchers are going to unveil in the years to come.
13:06But it's going to be, you know, really cool when they're able to solve the problem that the computer is
13:12as good or, if not better, than humans is able to understand as well as humans.
13:19And then in the really longer term, quantum.
13:21I think quantum technologies is really going to revolutionize the way our world works.
13:26But what can you say about the sectors?
13:28Do you see any sector, you know, attracting more investment there?
13:33So I think that there's always waves, right?
13:35I mean, right now, we are going through, especially in the U.S., we are going through a hype of
13:39quantum.
13:40A lot of investors do want to take their bets.
13:43And so as a consequence, you know, we do get these very top evaluations.
13:48As a deep tech investor, we try not to look at these waves beyond, you know, as macroeconomic factors.
13:55Because if you have really good tech, and if you have a really good team building out that business, the
14:03money will come.
14:03Because it is a really good business.
14:05And I think that's what matters.
14:07And Antoine, what about France?
14:08What do you see?
14:09Well, first of all, I think we have all to be humble.
14:12And we do not have any crystal ball who will say where will be the success.
14:17And I think for the investors in particular, if they knew what will be the successful startups, they will invest
14:25only in these startups.
14:26So I think you have to be very humble.
14:29You also have to consider that deep tech, in fact, is like research.
14:32I think it's a long-term process.
14:34So I do not think that we will see from nowhere a startup coming on a new subject.
14:41I think we know subjects already.
14:43So quantum is clearly a subject.
14:47And it's a fascinating subject because there are a lot of investments, even if there is no quantum computer.
14:53And nobody can really know when there will be.
14:57And even if there will be some quantum computer, there will be probably some quantum processors.
15:02But quantum computer, nevertheless, you have a lot of investments.
15:05You have investments in several, there are several hardware technologies competing each other on CMOS, rapid atoms, and so on.
15:15So that's clearly a domain.
15:17But you have also startups on the middleware and software because it's good to have a quantum computer or quantum
15:24processor.
15:25But you have to program it and you will not use the usual languages.
15:30So clearly it's a domain, a hot domain.
15:33And also all domain is all about energy and energy based on hydrogen, for instance.
15:46So if you have a lot of research about batteries, membranes, captation.
15:50Renewables.
15:51Yeah.
15:52And this is a subject of startup.
15:55Another domain from where you see a lot of startup emerging is healthcare.
16:01With a specific problem for healthcare is that in Europe, it's quite easy to, easy, well not easy, but not
16:11too difficult to find money for the first stage.
16:14But for healthcare, very often it requires at some stage of development, hundreds of millions of euros.
16:22And we see our startup in this domain after some years, they have to find funds in Asia or in
16:29US.
16:30And so that's clearly an issue for France and Europe, I think.
16:35But somehow, how do you detect the ideas and the projects that actually have commercial potential and are most likely
16:44to succeed?
16:45How do you do that?
16:47Manjar?
16:48Okay.
16:50So, yeah, it's not an easy task, but we go back to, you know, a lot of research.
16:57So, you know, most of us do incredible amounts of calling up, you know, people from market sites to technical
17:06due diligence
17:06and actually working out whether the technical differentiation that the technology is, you know, sort of proving has a value
17:15proposition in the market.
17:17So, you know, you might start off with a computer vision algorithm and you may, you know, sort of work
17:24out that this is now applicable in security, privacy, etc., etc.
17:30And then you actually need to dig deep and work out what is differentiated about these particular algorithms
17:36and which is the particular market that it is going to add the most value.
17:41And that just comes from a lot of talking from professors to CEOs of the markets.
17:48And Antoine, what would you say?
17:50You said you don't have the crystal ball, so how do you do it?
17:52Yes, but for us, the problem is a bit different.
17:55In the sense that for Senerais, our goal is to put startup on the starting lane, if I want to
18:02say.
18:02And after that, it's not our race, it's their race.
18:05But of course, we have to put on the starting lane the most potentially talent to startup.
18:12So the first point is, as I said before, is to convince people to go to start the process.
18:19And in Senerais, we have something like 1,000 labs, but in fact, 27 of our startup come from only
18:2710 labs.
18:29So clearly, it means that there is, well, it depends also on the subject on which you work.
18:33If you work on sensors, you have more chance to create a startup than if you work on, I don't
18:39know, medieval philosophy.
18:41We create not a lot of startup on that.
18:43But nevertheless, it's clear that there is some snowball effect.
18:48And if you are in a lab where you know that your colleague, the year before, created a startup,
18:54then probably it will help you to create a startup.
18:57But of course, if startups or ideas of startups do not come to us, we have to come to them.
19:02And so we have also business developers, and their job is precisely to go in the labs
19:09and to try to discuss with the researchers what are the ideas, the scientific ideas, the scientific results,
19:16which can be transformed in startup.
19:19And so we have a process for that.
19:21And the idea is to detect the best scientific results
19:27and to try to help them to have a first proof of concept.
19:32And that's the first step in the TRL later.
19:35And so we found them with the CNRS money.
19:38And we have a committee who is in charge not to judge the scientific results.
19:43We did it before.
19:44But it's a committee with people from VC, people from business, start-upers,
19:50who say, is there an idea?
19:51Is there a potential product?
19:53We don't want, of course, any business plan.
19:56That's not the problem.
19:56But is there an idea to transform the scientific results into a product?
20:00Is there a market, as I said before?
20:02And that's not a deterministic process.
20:05But I think it's very important to help to have more candidates.
20:10Thank you, Antoine.
20:12So, Manjari, financial conditions have tightened.
20:16And tech investors are not as bullish, as you know,
20:19as they were in the past two years we've seen before,
20:22particularly as regards to unprofitable ventures.
20:25So, as an investor today focusing on early-stage deep tech startups,
20:31so do you see these companies' valuation coming down?
20:34Are they struggling to raise money?
20:36What are you seeing?
20:38So, yes.
20:39I mean, the macroeconomic conditions are going to affect.
20:44But I think if you look at deep tech,
20:47the Series B onwards we are seeing valuations come down,
20:52which is inevitable.
20:54You know, there were very top evaluations over the last two years or so.
20:58And so, this year there has been a correction.
21:00I think with the early stage, that's less likely.
21:03Because, first of all,
21:05I don't think the valuations became all that much higher than what they already were.
21:11And so, some correction, the delta is not all that much.
21:15But whichever stage, you know, the company is raising,
21:18I go back to if it has really great tech,
21:21if it's solving a very important problem and is a good business because of the team behind it,
21:27there's never been a problem raising money.
21:30Well, you feel a problem with money, finance, no?
21:35No, I think I can agree with the majority.
21:40For us, as I said, it's really a question of mind, of researchers.
21:47And now, if I compare with the situation 30 years ago,
21:52young researchers are more keen to create startups.
21:56And, of course, there are money and investors.
22:00And that's clearly for us the issue is to show them or to explain to them that it's –
22:05After a PhD, of course, you can have the ambition to become a prominent researcher.
22:10But, in fact, there are few positions if you compare to the number of PhDs.
22:15Of course, you can go in an existing companies.
22:18But if during your PhD, you have discovered or you get outstanding results,
22:26then the creation startup is a possible future for you.
22:30And that's what we try to convince them.
22:32And more or less, it works.
22:33And it's important to have a symposium like VivaTech
22:38to show that startups coming from the academic world
22:41are as good as the others and perhaps even better,
22:47potentially better, because they are based on outstanding research.
22:51And that's clearly for deep techs.
22:52That's clearly the key point.
22:54We're probably going to see researchers become startups
22:55and heading the companies themselves.
22:59Antoine, where's research making the most progress at the moment?
23:03And what deep tech will be showcased here at VivaTech in the next three years when you come back?
23:09Yes, yes.
23:09We will come back every year, of course.
23:11And what is fascinating, as I said,
23:14we cover all fields of science.
23:16And sometimes we see startups coming from very strange results.
23:22For instance, we have a joint lab with Thales working on circuit.
23:27And we had a startup coming from it which worked in luxury
23:31because they invented a new gold, a new white gold.
23:36and it was really absolutely incredible to see that a startup,
23:41you see the difference between an idea or reason and a product.
23:45And the product clearly was unexpected.
23:47And that's why it's good to discuss with investors
23:50and to share this in order to find the right market, the right product.
23:54Fantastic.
23:55So I'm really curious to see what you come up with next year and the coming years.
23:59Great.
23:59Thank you, Antoine.
24:00Maybe one final word, Manjari.
24:02What would you like to tell the startups and the entrepreneurs watching us today
24:07when it comes to investment, to deep tech, if you want to...
24:14Well, you know, come and speak to me if you're building a deep tech technology.
24:19We're always looking at good stuff and we invest worldwide.
24:23So, yeah, looking forward to meeting you.
24:25Fantastic.
24:25Thank you, Manjari.
24:27Thank you, Antoine.
24:27It was great to have you on the show.
24:28Big thank you to both for sharing your perspective here at Vivitech.
24:32And ladies and gentlemen, our scaling session, scaling up session has come to an end.
24:37Thank you very much to our audience who are here in this room
24:41and those watching us behind their screens.
24:43So we reconvene tomorrow for our last day here at Vivitech in Paris.
24:48And, of course, I'll see you tomorrow here at midday for the Female Founders Challenge
24:53and in 30 minutes on Vivitech News for the After Tech show.
24:59So don't miss it.
25:00See you.
25:00Thank you.
25:01Thank you.
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