Robots are becoming human - humanoid robots on the rise

00:00:04: Robots have become an indispensable part of our factories.

00:00:14: Without these steel assistants, many modern production methods wouldn't even be possible.

00:00:20: However, robots are still often heavy machines in confined spaces that repeat certain movements thousands of times with millimeter precision.

00:00:29: This means that these machines quickly reach their limits.

00:00:33: And these limits now need to be overcome.

00:00:36: Humanoid robots, that means robots that resemble humans in appearance, are expected to play an important role in this.

00:00:43: After all, the human body is a true marvel in terms of its potential applications.

00:00:49: But is all this really possible or is it just science fiction?

00:00:54: How close are developers to creating a C-IIIPO, the legendary humanoid robot character from the first Star Wars films?

00:01:02: And what advantages would there be if we really got humanoid robots up and running?

00:01:08: All these questions are addressed in today's episode of the VDMA Industry Podcast, which has the wonderful title, colleague robot becomes human, humanoid robots on the rise.

00:01:20: And to discuss this, I welcome Nikolai Anselm, CEO and founder of Synapticon, a manufacturer of motion control systems used in robots based in Schöneich, Svabia.

00:01:33: Welcome.

00:01:34: Hello, it's my pleasure to be here.

00:01:37: And I also welcome Dr.

00:01:39: Eric Meiser, head of VDMA Future Business, who deals with the many exciting future topics in mechanical engineering, including the future of robots in industry.

00:01:50: It's great to have you here too.

00:01:52: Hello, greetings.

00:01:54: Hello.

00:01:55: And my name is Steffi Burmeister.

00:01:57: So let's start the conversation with a little imaginary scene.

00:02:01: Suppose you were at an airport somewhere in the world, and got on a shuttle bus to the plane on the runway and there was a human robot at the wheel.

00:02:11: Would you feel safe or would you get off the bus right away?

00:02:16: Nikolai.

00:02:18: I think I would feel safe because I know what needs to happen with such a product before it's being released for such an application.

00:02:29: I probably need to ask back, okay, is this a future scenario or is it basically a prototype of any of the startups today who's riding this bus?

00:02:38: I would then reconsider my answer.

00:02:40: I was assuming it's a final and released product and then of course I would trust it.

00:02:46: Okay.

00:02:46: And what about you, Erik?

00:02:48: I would feel safe.

00:02:50: You always have to trust your taxi driver, right?

00:02:54: And yeah, but I would ask myself the question, is this the right use case, right?

00:03:01: Autonomous cars would do the job as well.

00:03:04: So why would you need a humanoid robot for this purpose, right?

00:03:08: And I think the use cases are then, when we talk now, one of the basic things we have to consider.

00:03:17: It's a great example, actually, because that is really often the question that is being asked when humanoids come up, okay.

00:03:24: cannot this be done with another form?

00:03:26: Do we really need the humanoid form for that given task?

00:03:29: Humanoid robots may sound like something out of science fiction for most of us.

00:03:35: What defines such a robot and how is it different from classic industrial robots?

00:03:43: There are two aspects to this.

00:03:44: Of course, the shape of the robot and related to this also the internal workings of the robot.

00:03:52: So you could say the physical part of the machine is different than existing robots, and of course the software part.

00:04:00: Let me elaborate on both a little bit.

00:04:02: So very obvious is the kinematics.

00:04:05: It means how many degrees of freedom this robot has, basically how then these two arms are aligned to the torso that there is a head with sensors inside.

00:04:19: that there are legs.

00:04:20: Obviously the humanoid form that is new.

00:04:23: And now you can say, okay, two arm robots do exist also on wheels.

00:04:28: We have to distinguish on legs and on wheels and so on.

00:04:31: But this, of course, is overall form.

00:04:33: But there is also a deeper difference in the types of, you know, the motion equipment that is being used.

00:04:40: So the actuators are quite a bit different in humanoids than they are in industrial robots.

00:04:45: when it comes to something we call back drive ability, so that means how flexible the structure of the robot is.

00:04:54: The motion structure, I'm not referring now to the material that is flexible necessarily, but the joints.

00:05:02: They are also more human-like.

00:05:04: We also call this transparency or back drive ability.

00:05:08: The mechatronics are also more built to be human-like, not only the shape.

00:05:14: of the robot and the kinematic configuration.

00:05:18: And then, of course, the AI controls.

00:05:21: So in a humanoid robot, only a full stack AI control software makes sense.

00:05:28: And the classical robot program that we would have for an industrial robot who is repeatedly or repetitively doing the same task in a factory, it's very different.

00:05:40: So in a humanoid shape, With a very high probability only AI makes sense and traditional robot controls, a traditional robot programming language would not make so much sense.

00:05:50: That's how I would summarize the differences.

00:05:54: Until now, robots in human form have been more of a fantasy.

00:05:58: Why is there now so much talk and research about humanoid robots and why could they soon become reality?

00:06:06: Yeah, you know, it's have always triggered human fantasy.

00:06:11: Everybody finds that interesting.

00:06:13: And I love those movies that have the topic.

00:06:18: And you probably remember artificial intelligence, AI, this kids David.

00:06:26: It's like a modern Pinocchio story, right?

00:06:30: this kid looking for his mom and this movie is from from two thousand one.

00:06:37: and AI is is one of the catch words here right?

00:06:41: so several breakthroughs have been here for artificial intelligence since two thousand fifteen.

00:06:51: and yeah nowadays we have generative AI.

00:06:57: And now Generative AI gets a body, right?

00:07:00: And so the catchphrase here is physical AI.

00:07:04: And so the point is that the progress in AI has, of course, fueled robots.

00:07:15: But that's also true vice versa, right?

00:07:18: If you think about a humanoid robot, As a very challenging use case for a i also.

00:07:28: It's true that this this a i will grow with humanoid robots and will push its developments.

00:07:38: and of course the second development is interaction of a i with hardware so all the sensors that that have become possible.

00:07:50: hardware capabilities, computing power, and then this whole thing enabled movement and then also skills.

00:08:02: And this is why it happens now.

00:08:05: All these things have happened and now is the time.

00:08:08: You already mentioned that a humanoid robot on the wheel might be not the perfect match.

00:08:16: Where do you see the first and biggest areas of application for humanoid robots?

00:08:20: at home in the garden or in the factory, Nikolai?

00:08:27: Everybody is thinking of factory automation first, maybe because Elon Musk proposed the Tesla Optimus robot for the Tesla factories in the beginning.

00:08:40: Hyundai was acquiring Boston Dynamics and the car manufacturer as well.

00:08:45: I think this led into a trajectory for the car industry being particularly interested in these types of robots if they would allow to close the final gap of automation, if you will, in car factories.

00:08:58: But that's a comparably small field of application in my point of view.

00:09:04: I believe the big potential for humanoids in AI-controlled robots in general is outside of factories, where... humans perform physical labor.

00:09:15: so i see the greatest potential of application actually where we have least robots today.

00:09:20: so you could even say that's kind of directly counter proportional so to say so.

00:09:25: where we have a lot of automation today discrete automation you know that needs to be precise has high throughput and good repeatability.

00:09:34: these are all.

00:09:34: the qualities of humanoids and AI-controlled robots.

00:09:38: They are flexible, they're adaptive, they're autonomous.

00:09:41: And that is what you need in unstructured environments everywhere, where so far little automation was possible.

00:09:46: And that's also where we have the big challenge, right?

00:09:48: Ultimately, it's about closing ever-growing labor gap that our economies are experiencing.

00:09:55: So actually, it's devastating to see that if the world economy is only growing with two percent per year, On average, we will be lacking basically half of the workforce in simple physical labor that we need to sustain this growth and to sustain our economies.

00:10:17: And that's where I see the big potential of humanoids.

00:10:22: when you ask the first application is of course research.

00:10:26: So not every researcher can afford to design his own humanoid robot.

00:10:32: So everybody who wants to test, I mean, like Nicolai probably does, a humanoid robot has to buy one, right?

00:10:39: And so these companies building humanoid robots today probably have their first applications also in research.

00:10:48: And later on, of course, then households medical technology, whatever.

00:10:54: A lot of things are imaginable.

00:10:56: But let's take a closer look to the production.

00:11:00: How would it look like when humans and humanoid robots work there together?

00:11:05: Would they work side by side doing the same tasks?

00:11:08: Nikolaj?

00:11:09: This is certainly a scenario.

00:11:12: However, If we look into the critical paths for the development of humanoids, for them to get mature as products, one very critical path is actually the safety of the machines.

00:11:26: Now, there's already a big difference if the robot is standing on wheels or it's standing on legs in terms of how dangerous the robot is, because they can be quite heavy, similar to humans, but then they're not soft like a human, but they're made from hard metal and they can move.

00:11:41: quite fast and also should have ultimately high payloads, so they are strong to carry things.

00:11:50: So they're dangerous machines.

00:11:52: And with new challenges to functional safety, which is the stability as they are standing on legs, and which is their AI control.

00:12:00: So the robots, they basically do what they want, quote unquote, and not what they were programmed for.

00:12:06: Now, of course, the training is giving a certain, how to say, solution domain for what they will do based on the input, but we cannot really precisely predict what they will do.

00:12:16: And as you know that JetGPT can hallucinate, this is imaginable.

00:12:22: I mean that the AI controls inside of a humanoid robot do something unpredicted.

00:12:28: And we need safety systems for that.

00:12:31: And that is how to say a similar development that still needs to take place.

00:12:36: and especially needs to be brought to the application.

00:12:40: that means manufacturers.

00:12:41: they need to adopt new technologies in functional safety and new methods.

00:12:45: that by the way my company is strongly involved with in providing this to these manufacturers until they can sell robots that are considered safe to work besides humans or even in close interaction with humans until we have robots ready to be purchased and to be deployed.

00:13:05: that have a critical level of functional safety certification, this will be probably not viable, at least not in European factories.

00:13:13: So they will need to be separated in the meantime, but there are also a lot of use cases that are viable where the robots work alone and humans do not need to be close by, and these will be, of course, then the more obvious use cases in the beginning.

00:13:29: I think today, how do robots work today?

00:13:32: I mean, you basically have a fence around it.

00:13:35: And there are robots called co-bots today that work side by side with humans, but they are not on legs or wheels, right?

00:13:45: And then, of course, there's no safety issue as the one Nikolai.

00:13:50: just described.

00:13:51: but I think in the in the maybe further far future I think working side-by-side with humans is the one single thing that distinguishes humanoid robots from all the other robots that we already have right same tasks.

00:14:09: probably not right because You have a humanoid robot to relieve workers from their boring or too hard work or things like that.

00:14:20: So for the first question side by side, I would say yes, even for the future mandatory and for the same task, I would definitely say no.

00:14:31: It sounds like a really crazy picture for me to imagine that humanoid robots and humans side by side.

00:14:37: But yeah, let's see.

00:14:40: How it will be in a few years.

00:14:42: Today, what you can do today is to train humanoid robots by letting them watch humans do their work.

00:14:51: So that's already something that is done side by side.

00:14:56: Watching instead of programming.

00:14:59: And the first practical tests of humanoid robots and production are already underway.

00:15:04: How are people reacting to their new colleagues made of metal?

00:15:11: Yeah, to be honest, I mean, it's not so clear, I think, for the broad use because there is no broad use today.

00:15:19: So you have basically selected people working in test environments today.

00:15:26: And of course, those people are maybe researchers or engineers.

00:15:30: And of course, they are biased.

00:15:32: So I think they are surely fascinated, right?

00:15:36: But you don't really know how... acceptance in the workforce or even in society really is then later on.

00:15:45: And that probably is also different in different regions of the world.

00:15:50: If you look at China, for example, China really pushes the public perception already today.

00:15:59: So you have seen this ballet for Chinese New Year, a ballet of humanoid robots.

00:16:09: or a marathon that humanoid robots have participated in.

00:16:15: So I think for Chinese people, it becomes with those things probably more normal or normal earlier than for Europeans or for the US.

00:16:28: And then, of course, I mean, you can always have this question of German angst, right?

00:16:34: than probably hindering humanoid robots in Germany.

00:16:39: I don't know.

00:16:40: Yeah, so actually we see among our customers, our customers of our customers are kind of the public reaction to our customers in the humanoid field.

00:16:49: A lot of excitement and a lot of anticipation generally.

00:16:53: So once a robot is getting a humanoid form, people suddenly start imagining what this thing could do for them.

00:17:02: That's what industrial robots didn't unleash before, be it mobile robot, like just a mobile platform or a stationary robot arm.

00:17:12: Of course, you know, someone technically educated could imagine what this thing could do theoretically, but a normal human person not exposed to automation technology couldn't.

00:17:22: But now with the humanoid form, everybody has an imagination of what this thing could do and everybody, you know, has work that they don't like doing.

00:17:31: So we see across the bench, be it for their homes, be it for their companies.

00:17:37: So we hear it from some research partners and also these customers that they get a lot of inquiries from all across their customer bases or all across the different industries and kind of commercial domains, asking them about These humanoids if they can do this and that.

00:17:59: so some customers say they never got as many you know who did normal robots before so to say industrial robots and now they added humanoids.

00:18:07: they said never.

00:18:07: they got so many inquiries from all random sources asking them if that robot is available and if it can do this and that.

00:18:17: So besides that, I agree with what Eric said about this very big excitement in China, which is totally different than what we have here in Europe yet.

00:18:25: So I think here there is still one or the other question of what this will do to the labor market.

00:18:30: Some might be less concerned about that.

00:18:33: we're running out of workforces, but still are maybe a bit concerned about that the robots will take the jobs, which is probably a... pretty outdated fear, but some still have it probably.

00:18:44: And in some companies, there might be a certain backlash against the robots when people are fearing that their jobs are at stake for sure.

00:18:52: So Nikolai, what opportunities do humanoid robots offer companies, concrete?

00:18:58: I mentioned this general problem of finding the right people.

00:19:04: for given jobs.

00:19:05: And the simpler the job is that a company needs to fill the position, the harder it gets to find people, interestingly.

00:19:14: There is one example that I remember, strawberry fields in the south of Portugal,

00:19:19: where

00:19:20: my family used to go for vacations.

00:19:23: So it's a huge stretch of land where strawberries are being produced.

00:19:27: And traditionally, the Portuguese people there on the countryside, they simply worked on these fields.

00:19:33: and everything was happy.

00:19:35: But meantime, not a single Portuguese person wants to work there anymore.

00:19:38: They have better jobs and simply there is no workforce available for these berry fields anymore.

00:19:44: And they started importing people from other countries, so to say workers from abroad.

00:19:49: And now even these workers from abroad found better jobs in Portugal and they're lacking even these people.

00:19:57: So that is one of the examples that I keep telling to basically explain how.

00:20:02: not even, you know, that it's not an opportunity, but an urgent need that many companies already have, which is not served yet, and that more and more employers will have going forward.

00:20:16: Now, coming back to production, more in a German manufacturing context, maybe, it's obviously that... tasks can be automated that were not be possible to be automated before at an economic price point.

00:20:31: once these machines are available in certain volumes and AI has evolved as much that these robots can do all different kinds of tasks.

00:20:40: So I don't need to invest in automation anymore to automate something.

00:20:45: I can simply apply that robot, tell it what to do and it will do it.

00:20:48: That's the ultimate vision for any manufacturing task inside of a factory, for example.

00:20:54: Yeah, and that can be like, you know, machine loading or logistics or even measurement technology, things like that.

00:21:04: But yeah, as Nicola said, I mean, one thing is very important.

00:21:10: It's not clear if this is profitable or viable yet.

00:21:16: So it's all a big experiment.

00:21:20: And apart from the fact how workers would react to their colleague, it's not clear if it's profitable.

00:21:32: Maybe to add one more thing.

00:21:35: To model this a little bit, with the growing cost for labor, there is a higher pressure on automation, basically a very simple equation.

00:21:46: The labor cost is the more difficult it is to get people to higher the pressure on classical automation.

00:21:52: Now the promise that humanoids are making or kind of this technology is generally making that once their capability grows over a certain threshold and the cost falls under a certain threshold, that this pressure to automate something with discrete automation, like build a machine for something or kind of build an automation system for something, this will go away to a degree because it will be simpler and cheaper to kind of let a humanoid take care of it.

00:22:19: This will not go into everything, of course, but as a general model, I think it's useful to understand the dynamics

00:22:28: long term.

00:22:28: Yeah, definitely.

00:22:30: But isn't it very expensive to program humanoid robots for production?

00:22:35: Very difficult.

00:22:37: No, not at all, actually.

00:22:39: That is the big disruption, if you will, or kind of the big revolution that comes in with physical AI, that we do not have to program the robots anymore.

00:22:49: We do not need to have specialists who understand kind of how this robot needs to be programmed.

00:22:53: We do not need to be specialists for the given application.

00:22:56: But we simply tell the robot what we want it to do.

00:23:00: And based on the pre-training of the AI, the robot can already understand quite well what we want from it.

00:23:06: In a similar way, like if you ask JetGPT something, it understands what you want from it.

00:23:11: That's kind of the one-to-one kind of counterpart in a physical embodiment.

00:23:18: And it can also understand based on what it perceives.

00:23:20: So like when you give JetGPT a picture and you ask it to do something with this picture, it can also do it.

00:23:25: So these capabilities come into the robot.

00:23:27: And then now the physical part, the action part is that you can show the robot what to do and it can learn from you.

00:23:36: And as Alec mentioned before, they actually are being trained by such methodologies, also tele-operation or imitation learning, watching humans, literally video data is being used, so kind of YouTube and Netflix is being used to train this AI and to teach it human capabilities.

00:23:57: So strong simplification in the use of such a complex machine, actually.

00:24:03: So it becomes easy.

00:24:04: That's part of the revolution.

00:24:06: And there's an exciting debate among developers.

00:24:09: Do humanoid robots need legs or don't they?

00:24:14: And isn't the real challenge actually the hands?

00:24:16: What do you think?

00:24:17: Yeah, absolutely.

00:24:18: So the big challenge is the hands.

00:24:21: No doubt about that.

00:24:23: The dexterity and capability of human hands is just incredible.

00:24:28: And until we have a machine equivalent of this, mechanically or electromechanically, mechatronically.

00:24:36: And until we have AI that can really make use out of a five-finger hand that is as dexterous and as robust as a human hand, this will be probably the longest part or kind of the biggest area of development that we have within this theme of humanoids.

00:24:53: You could say the body is fifty percent and the hands are the other fifty percent roundabout.

00:25:02: With legs, that's an interesting discussion.

00:25:04: Of course, in a factory, a robot doesn't need to have necessarily legs, especially if it doesn't move between levels.

00:25:12: And then if it needs to, there are probably elevators and so on.

00:25:14: So many say, in our factory, this robot won't need legs.

00:25:18: So you can make it safer and cheaper with a mobile basis.

00:25:22: But then I have to come again with my thesis that the even greater scope of applications is outside of the factories, where we do not have automation yet on the construction side, on the agricultural fields, cleaning facilities, inspecting industrial facilities, everything that is not automated yet so much, ultimately up into the homes.

00:25:47: And there you need to imagine a robot workforce on wheels.

00:25:53: is basically then as capable as a human workforce in wheelchairs.

00:25:57: You know, this is maybe a little bit a strong comparison, right?

00:26:01: But you get the idea, of course, these robots could still do something, but they would be quite limited.

00:26:09: So if we really want to have this universal worker for human physical labor, the legs are required.

00:26:15: But there will be many applications where we don't need the legs, obviously.

00:26:19: The VDMA is currently working on a study on the possibilities of humanoid robotics with a perspective on the year two thousand forty.

00:26:27: What findings are already available Eric?

00:26:31: Yeah, so two thousand forty, right?

00:26:34: That's fifteen years from now and that's pretty far away.

00:26:37: So what we won't do and you cannot do is to predict the future.

00:26:43: So what we try to find out with bright people like Nikolai in workshops is scenarios right.

00:26:54: so rather than predicting the future we have multiple futures and we try to figure out what kind of possibilities we have.

00:27:09: what can arise without looking at the probability.

00:27:15: So we don't ask for probabilities, we just ask for what is possible and imaginable.

00:27:21: So images of the future is our product here rather than a study.

00:27:27: We, to really capture that, we discuss that by influencing factors, right?

00:27:34: So what could be an influencing factor for humanoid robots in two thousand forty?

00:27:39: And what are projections for that?

00:27:41: And so there is no kind of wishful future or wish wishful thinking.

00:27:49: No market predictions, everything is allowed, right?

00:27:52: So I always say, as long as you don't reverse gravity, everything is allowed.

00:27:57: And we have for this study, sixteen influencing factors and those range from technology like AI or a sense of development to all kinds of other things like acceptance in society or economical questions or ecological questions or policy environments, so regulations would be one thing that is very important to get humanoids into the field.

00:28:28: And right now we have carved out four scenarios.

00:28:33: One is robots in everyday life where everybody uses them and they become common.

00:28:40: Then the second one is robots for the few, only those who can afford them.

00:28:46: Another one is government serving the public where governments invest into humanoids.

00:28:53: And fourth one is something we had in AI for a long time, so-called AI winters.

00:29:01: It could be possible that humanoids are just a hype and nobody cares in a couple of years.

00:29:07: But what do you think?

00:29:09: How big will the market be for humanoid robots in the future?

00:29:13: Yeah, so the market question is is hard right.

00:29:16: so you basically extrapolate from zero right now.

00:29:20: so and of course you.

00:29:23: You are in a classical hype cycle so we have anticipated the topic.

00:29:31: We are in a huge hype now over expectation and there will be in a hype cycle always the value of disillusionment before we go into a real market right.

00:29:41: so this is just normal for every new technology and this is the case here too.

00:29:47: so right now we have very bold predictions right.

00:29:49: so people talking about.

00:29:51: Yeah I've seen a study here at twenty three billion US dollars in twenty thirty five.

00:30:00: My best one is this one here, my colleague Patrick Schwarzkopf from VDMA Robotics.

00:30:06: He told me Elon Musk

00:30:08: said

00:30:08: that by two thousand forty we will have ten billion humanoid robots.

00:30:14: So if you remember how many humans, how many people are on the world right now, that's eight billion, right?

00:30:22: And I think prediction for people in the world in two thousand eighty is ten billion.

00:30:29: So you have to be a little bit careful with these very bold predictions.

00:30:34: And yeah, so to compare operational stock of industrial robots right now is if I'm right, Nikolai five million.

00:30:44: In twenty twenty four, it has been five hundred thousand on top.

00:30:51: And if you compare with cars, cars in the world today are one point five billion.

00:30:58: So if humanoid robots become like the car of a person, then we are there,

00:31:07: probably.

00:31:07: Yeah.

00:31:08: Let's venture a prediction.

00:31:10: How long, Nikolai, do you think will it take before humanoid robots?

00:31:14: become part of our everyday life, but also industrial life.

00:31:19: As my personal expectation is set in the next three years around about, we will see more and more impressive pilot applications, which are real.

00:31:33: So the technology is mature enough to be brought to application in certain use cases and the use cases will grow.

00:31:42: and the pilots will become more successful, and ultimately companies within this period also will pay for the robot hour or will buy robots, to which magnitude remains open.

00:31:53: So I would not call this really like a mass adoption yet, like a very established industry, but it will gain traction.

00:32:00: I'm quite sure about this.

00:32:01: I just see the technology getting there and the use.

00:32:05: for the companies be there, and also the cost coming down to a level that allows for return on investment.

00:32:11: Now, until this is, how to say, a commercially viable thing for a range of companies that will take another couple of years, so five to six years, we will consider this a relevant revenue turning industry.

00:32:28: And then until it's such a big thing, that Elon is outlining, for example.

00:32:35: I think the narrative that he has is that actually the population is shrinking, not growing.

00:32:41: So that's an alternative scenario that he's basically favoring.

00:32:45: and basically he says we need to have these robots to do the same work or even more than we had humans for before.

00:32:52: So kind of fully fueling this narrative.

00:32:55: So let's say that it's imaginable that there will be more humanoids on Earth at some point than than cars.

00:33:04: that just make sense because we can use more of them as workforce and in factories and so on than we have space on the streets, so to say for cars.

00:33:14: And that is a development that I would anticipate.

00:33:17: still takes at least fifteen years to be fully kind of exploited or reaching close to there.

00:33:27: Why?

00:33:28: Because if you look into other industries like the internet or the mobile phone, industry that basically the time it took from anticipation high, the hype basically until this was a huge industry that is kind of world changing.

00:33:44: It was around about fifteen years kind of from hype to significant economic impact.

00:33:52: And I would say there are enough arguments to expect that physical AI is on a similar.

00:33:58: trajectories.

00:33:59: That's why my expectation until this is a very significant industry is fifteen years around

00:34:04: the bond.

00:34:04: Yeah, for me the same.

00:34:06: So if you consider like twenty twenty eight for mass production, something like three years more for industrial robustness, right?

00:34:15: So you ask for industrial purposes here.

00:34:18: Industrial robots have to run like eight hour shifts.

00:34:24: ten years in a row.

00:34:25: So that needs a certain robustness for these machines.

00:34:30: And then first uses another five years and you are at least ten years.

00:34:37: So let's conclude our podcast with a second prediction.

00:34:42: The cell phone had its famous iPhone moments.

00:34:45: Do you think there will be something similar with humanoid robotics?

00:34:49: And will we even recognize this special moment?

00:34:52: Nikolai?

00:34:53: I believe so, yes, one hand side, there will be a moment where it really gets to everybody that this technology can do amazing things.

00:35:04: I'm a little bit skeptical, though, if this will be such a sudden moment like we experienced with the iPhone or JetGPT, because we can already anticipate how this will come into the world.

00:35:19: So I think it is kind of a more... how to say, a quieter process at some point, less suddenly.

00:35:27: So I need to say suddenly, for the lack of other words, we will realize, oh, these things, they're doing a lot of useful things, right?

00:35:34: So I'm not seeing this sudden moment when it happens.

00:35:40: I more see a certain development, but definitely at some point, we will realize a similar technological leap like we basically... realized when the GPT or the iPhone came to the world.

00:35:55: Yeah, it's hard to imagine for that the broad usability of the humanoid robots.

00:36:02: This one iconic moment where everybody is waiting in front of the store to get the iPhone.

00:36:12: So I think so too.

00:36:14: So there will be After this probably this hype cycle disillusionment, there will be a market.

00:36:24: And yeah, so I think we will come into the situation probably in the same way we anticipated the laser.

00:36:37: Laser today is a universal tool, right?

00:36:40: And in the nineteen nineties, for example, this was just a very costly tool you only use for very special purposes.

00:36:50: And if the humanoid robot has become the universal machine, like the laser is the universal tool today, then we have this moment.

00:37:02: And then we can talk about something like a new machine breed.

00:37:07: This is probably the iconic moment we're waiting for.

00:37:10: It's a very nice comparison actually.

00:37:12: I like it.

00:37:13: And that brings us to the end of today's episode of the VDMA industry podcast.

00:37:19: A big thank you to our guests, Nikolaj Enslen, CEO and founder of Synapticon.

00:37:25: Thank you.

00:37:26: Thank you for having me.

00:37:27: And Dr.

00:37:28: Erik Meisser, head of VDMA Future Business.

00:37:31: Thanks a lot.

00:37:33: Thank you for sharing your insights, expertise and visions for the future of humanoid robotics.

00:37:38: It's fascinating to see how quickly this field is evolving from science fiction to potential everyday reality and factories and also in our daily lives.

00:37:50: You can also find more information on this topic at vdma.eu.

00:37:55: And if you enjoyed this conversation, don't forget to follow the VDMA industry podcast on your favorite platform so you never miss an episode.

00:38:04: Our podcast is available on Spotify, Apple Podcasts, Google Podcasts, and Potty G. And of course, we'd love it if you'd share the podcast and leave us a review.