Hi, welcome to our panel on robotics. For those of you who don't already know it, we do have an actual robot out there in the networking area. Its name is for anyone, and it talks. So, I would highly encourage you, after this discussion, to go out there and have a conversation with for anyone. Now, before we get started with our discussion with David and Kristen here, I do have a polling question for you. The question is, what industry do you believe robots will have the greatest employment impact in: logistics, health care, manufacturing, military, or housework? Answer No. And then we'll come back to your results at the end of this discussion. David, this summit is about trust. You're envisioning this world in which robots will work alongside human beings in offices and take up basic household chores. How are you going to convince people to trust your robots to work in their offices and inside of their own homes? Yeah, good question.

So, in my opinion, over time, I think trust is something we... it's not just... it's a gift. It's more something we have to reserve for. And this is also how I see it in the robotics field. First of all, robots are going to be helpers, in my opinion. If you're talking about trusting in humans and then talking about trusting in robots, I think it's two different kinds of things. Robots are not aiming for getting super rich. Robots are not aiming for, let's say, power and glory. And that's actually why I do see more... let's say they're more trustful. It depends a little bit which company they come from and what are they meant for. And this is, I think, the big topic we have just to work on and set rules for robots, educate people on exactly what your robots are designed to do. Now, Kristen, I want to bring you into this.

conversation because unlike David's robots, which are maybe designed to do everything from wash the dishes, you ironed your clothes for you. Your robot, your robotics or Dexter, you have a very specific task. What problem is Dextre trying to solve for? Yeah. So we're very much focused on the warehousing and logistics industry and closing that visibility gap on the data that currently exists and is missing. So our focus is not replacing what humans are doing, but adding to what already exists and creating a more complete picture of data so that we can better optimize the work that both the robots are doing, but also that all the teams are doing within the warehouses. This is hard for people to visualize. I mean, it looks like somebody just, you know, looking at a bunch of shelves and counting boxes. But tell me what this tell me what this Dextre robot looks like. So I think we have some images behind us.

It's much larger than you would think. So unfortunately, we couldn't bring it with us today because it would take up way, way above this ceiling. But what we're doing is in real time working in partnership. So working alongside it doesn't need to be happen in the dark at night when the warehouses are closed. But in real time, all day long, we're continuously scanning the warehouses. So we're using a mix of computer vision liners, all sorts of different technology to build up a constant and full picture of where inventory and stock is. But then using that to optimize the work that is happening and taking place with our digital technology that goes alongside. Now, Chris, you and I have talked about how that alleviates labor issues in the warehouses. It puts some responsibility and tasks to the robots as opposed to having to be put on human beings. David We have also talked about the labor issues in the global workforce.

I'd be interested in hearing your thoughts on what the global workforce looks like in ten years from now. So basically, I think everyone knows about the Silver Society, about the aging population, which we are in right now. So we see, especially in the Western world here in Europe, Germany is very much hit by that. If you're calculating, let's say, how many labors we are losing actually in the next ten years, it's tremendous. And it's the same happening also in all kinds of other parts of the world. So it means in the U.S., same also in Asia. If you're talking about China, for example, this is also why they're setting the rules of okay. Or a goal. That's a vision for China 2030, having, let's say, 5% of working labor. That's a like in in in robots are. So I'm just missing the right word. I don't want to replace. I don't want to say replace, but

actually, let's say at a labor of 5%, and this is how they get actually, let's say, pretty efficient also for the future. And I think that's also needed. If you're talking about Japan, I mean, this is why they're also the big lovers of robots, because simply they have this big need in the future. So I'm talking here about the next 5 to 10 years already, which is pretty strong. And for that, we are not in need of just robots as we have until today. So it means if you're looking in the robotics field, I mean, there is nothing new. There are already robots and 70 years. What changed was actually bringing robots together with artificial intelligence and giving them skills. So it means robots can be used as skilled workers in different kinds of tasks like welding, gluing, whatever. That's also what we are with our core, let's say, work we are doing right now.

So because everyone is telling you about our household thing, because we are showing these videos in households, but in reality, we do see, let's say, in the next five years already humanoids or all kinds of different kinds of shapes of robots in the industrial sectors, having skills, learning things, and taking action in skilled worker tasks. Now Chris and David mentioned I and what a game changer that is for the kind of robots that he's manufacturing. Tell us how AI is a game changer for Dexter. Yeah, I think there's a lot of talk about A.I. and we talk about it as a big generic piece. And I think for us, a big part of what we're doing is I keep mentioning the data that we are collecting to better optimize. So it is not just about how our robots work. And of course, advances in I have affected how our robots autonomously move and make really positive impacts there.

But even more than that, it's about how the data that we're collecting. We then use A.I. to better optimize, to better support, to better focus the current teams that are working within the warehouses. I'm going to shoot our own horn a little bit. So recently, Bloomberg News broke the news that Tesla used humans to remotely operate some robots at a recent event. And I wondered, you know, Chris, and maybe we can start with you, like what challenges does that highlight that remain for robotics? What does that tell us about the state of robotics and how far we have to go and how hard the problem is? I think for me, what that really highlights is we're used to sci-fi. We're used to seeing things and expecting that we're not that far away from robots to be able to move in any environment in any way. But the reality is autonomously moving robots is a really difficult challenge.

to solve for and not just autonomously moving, but autonomously moving in conjunction with people. So how robots behave in spaces with other people. And that's an incredibly difficult problem to solve for an incredibly difficult to generalize for in different spaces. So we spend a huge amount of time on our autonomy and thinking about how our robots can be working alongside and in conjunction with people. But I think the fact that Tesla reverted back to their demo, having their remote-controlled, just shows how actually we're pretty far away from fully generalizable autonomous movement and things like cars. David, you are in the business of trying to manufacture robots that are fully autonomous. So how are you feeling about Chris saying this is it, her? Like, let's say I was actually impressed by Elon, like what he showed. I was impressed. Like, I mean, he had so many humanoid robots on stage. Only one fail of a really fail and fall was falling.

So I was impressed, like, but by because I mean just some, I think, two years ago, like you put like a human in a suit and let it dance on the stage. I mean, and where he got today, I was impressed. So the thing is about autonomy. It's like about it's the same about general artificial intelligence. Like if you're talking about I, I think there are steps to go there and for sure. So I will not doubt that. But the thing is, having his humanoid robots in his factories doing like all kind of little specific tasks, this is very close. So he is not far away from that. And this is already a huge achievement. And this is also what I see there. So it means that this exactly what we are doing as neuro, we call it, actually neural versus. We build a platform which we are not only depending on a humanoid robot, but actually using robot arms, which we built already and which we are

selling to the market, which we have already thousand pieces in the market and gaining their data, whatever they are doing, if they're welding, if there are penalties in whatever they do, and using that actually to train the human eyes of the future. So and what we see there is very big fast steps are happening. So we will show already much more next year in June where we show actually our brain in action. So it means the numerous platform in action by controlling like one brain controlling all kind of different robot types and getting tasks done which are specified or because if you are talking about, hey, just do something. Yes. Just walk around and do something. This is something what they can do. But if you tell them a specific task and this is actually what we need, we are humans. We should stay humans and let humans work for us. So it means you are telling them, Hey, clean my house. I'm sure the robots can do it already in two years.

Not and. And five or ten years. Why? Because simply scanning an environment, that's something we are doing every day already. Sitting like an idle state of this environment. Yes, it is everything. What's on the floor or on the table, but shouldn't be there. Pick it up and put it and back. Yes, it's possible. So it's not so complicated. But yes, it will be first specific task by task done. And this is what we need. We don't need another human, in my opinion. We need actually robots which can help us to so we get more human again. And this is what we are aiming for. Interesting. I do need a robot housecleaner, so I want to go back. To this scenario ten years from now that you're painting. It's a it's a pretty dire one. You're talking about like global workforce shortages. And you talked about Japan. You talked about China.

Well, you didn't talk about is like any of the countries in the Western world, the U.S. or the EU. And I just wonder if we are hurtling toward massive labor shortages, why isn't the world making millions of robots right now to plan for that future? So right now, there are no millions of robots made. Actually, that's the thing we are still building in Italy right now. If you're looking in the market of robotics, it's just 500,000 robots sold per year. All robot types together. So it's nothing. Even if we want to really reach the status of having, let's say, like the China goal of 35 million robots until 2030, it's not possible today. So there's even. So we have to start today to get it done. This is actually what we are doing. So the same also, if you're talking about robots, this right now, a lot of

complaints, and that's why I saw a lot of critics about e-learning. I think it has also something to do with his political statements. But in the end, but if you're seeing like, what would he move forward and where he goes, I think it's a drastic. He made a very good step, and it's a good step forward from a technology point of view. And I think like he will use his robots in his own production. That's also what he's saying and what he will. And he will gain a lot of knowledge in this production. And this is actually, I think, also what he's talking about, the brain behind which gets, let's say, all the skills, and this is what we are also doing, but not just limited to our automotive production, but actually going to different kinds of pillars and training our robots to gain skills like touching things, understanding things, how to grasp them, how to like assemble two parts in each other.

And they have a lot of similarities to each other. And this is actually what we are gaining on skills. Just to follow up on that, like, you know what? What do governments need to do in order to take you from point A to point B? I think the governments should just, let's say, in my opinion, like I can talk for Germany. What we are missing in Germany is actually just the right mindset, you know? That's it. I do think we, like I can speak for Europe, I do think we have all these brilliant brains there. I do know that the market is there, is existing, and it's right now growing, and I do think it is the next big pillar for a big economy. Because if you're talking about just, like, let's say, the number which China wants to put up, it's about 1.4 trillion just until 2030 in revenue. So it's a good number, I

would say. And this is what I see: a huge potential which we could actually win if we start today. And because let's go also some steps back like the automotive industry, like why were we so good at it? Because we were focusing. So this is also to your question about what governments can do. They can actually focus. They can actually tell, We are having a vision. That's what China is doing and what they do pretty well, in my opinion. It's like they're having a vision for the next five years, for the next ten years, and then they are all aiming for that. They are focusing all their, let's say, power to actually get it done. And this is also what I hope also in our Western European world, that we actually have a goal, a vision for something, what we can aim for to reach in the next five years, ten years, because it's very close. Chris, speaking of focus, I mean, what would you love for the governments

to be doing to aid your industry? But also like what kind of focus are you seeing from venture capital in robotics? I think that's point I was just going to say investment. That's the other piece that we need to look at, like David's point about the number of robots that actually have been built up to this point, it's so small compared to where we need to go. And any hardware fields takes a level of investment that is not the same as the software fields. And I think we need to recognize that. And I think if we sincerely want to see continued investment advancements but also advancements at scale, then we need to think about how that investment works, both from the government encouraging investment and then also from the private sector investment. And I think we're very lucky. We've recently closed a funding round, thank you, which we're very pleased about. But I think the interest in deep tech investment is definitely on the up in

the kind of past year, year and a half, two years, but previously too, that it traditionally was a space that everyone shied away from. And I think the fact that now that we're seeing some of the biggest companies are also hardware companies and building the physical asset, not just the software on top shows us that there are huge gains to be made here for investors. But I think not just talking about it, but continuing to actually put capital into these spaces is going to be one of the key things for the private market, but also for governments. Get involved in. So in terms of investments on the government side, what do you want that to look like? Oh, good question. I was like, Is anyone here that I can ask her to check? I think there's one great thing about the UK is how much amazing brainpower we have in our universities here and how well some of that collaboration has worked previously in terms of universities spin out,

spinning out into new companies. I think governments invest in both there to help facilitate that, but also the UK does run quite a few different funding schemes where they're investing directly in startups, but also improving tax credits for people that are investing in that space. So I think the government, yes, of course capital going into it, but I think to David's point, like having a focus and a vision where we align our policy and our tax policy to that makes a big difference to where we can head. David, I just want to touch on the funding situation for you. What are you seeing in the investing landscape? Don't be shy. You're raising money. And I think it's still. Again, getting back to my first point, like it's all about mindset. Like if our country would have a vision, like going like, one way and we are aiming for and it's the biggest market in the future, let's go there. I think also the money will come here.

and that's and then we need some success stories because this is actually what we don't have here and in Europe a lot. It's like if you're looking the last hundred years, like which kind of where the big giants come from and the successful companies, they are not from Europe. So and this is why I do think we have to change. And I think the good thing is and I think that's a good news, but also bad news is that we are right now, especially like I talk again for Germany in a very bad situation. Why? Because we simply see that we have now we are facing an issue in the future, like in the automotive sector, which we can can solve right now. So it means that we are again starting to be open for innovations, because if you're looking in the past right now, it was simply made like like there was even a German politician saying, like, if you have visions, go see a doctor.

Everyone is like saying, Okay, what a dumb person. And I said, Like, but at his time when he was living, it was actually not that stupid because this was actually giving us this amazing, let's say, this how to say it's this good economics for the past future because we were simply the champs in automotive. And if you are looking back even 2008, the big crisis came. Everyone knew one day they will start buying cars again. But this time changed. So it means we have enough pressure and also the willingness of the governments, in my opinion, I hope soon to actually change something and aim for other visions than automotive and other markets and automotive, which I hope will be robotics because it's simply the biggest market in the future. I have a bit of a heavy question here for both of you. We live in a time of war, and while both of you are designing robotics, you wrote

us some very nice and kind. But, you know, there's a lot of conversation around autonomous drones and AI-powered targeting. Is there going to be a role for robotics in warfare in the future? AI It's very different from what we do. Our robots are not designed in any way to partake in that future. But I do think to me, one of the very big positives of robotics is doing jobs more safely that we wouldn't want people doing. So when I think of like work in clearing of landmines and other pieces, so some of the effect negative effects of war. I see robotics playing a really key role in helping and promoting the safety of people. Nora is for sure not going to build robots for any to take any weapons or against humans, let's say like that. But we do see right now that for sure robotics will be used for that heavily. That is what we are seeing right now in the works are like a lot of drones, But

in the same time, I think there will be a lot of other tools in the robotics space. But it's just very important for us because we started with a question of trust. We will never like our company will never do anything what's against humans, because there's a lot of other things to solve. And I think that's why our slogan is We serve humanity from the first day. And that's also what we are willing to do. We've run out of time here. I do want to share the poll results. It looks like the largest share of our audience expects that the manufacturing industry will see the greatest employment impact from robotics, which is too bad. I was hoping for housework, but thank you so much to our panelists and thank you to all of you for joining us.

The Robotic Revolution has Arrived #technologymind

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