Speaker 1: Welcome to tech Stuff, a production from I Heart Radio.
Speaker 1: Hey there, and welcome to tech Stuff. I'm your host
Speaker 1: job in Strickland. I'm an executive producer with I Heart Radio,
Speaker 1: and I love all things tech and it is time
Speaker 1: for a classic episode of tech Stuff. This episode originally
Speaker 1: published way back on October fifteenth, two thousand fourteen. It
Speaker 1: is titled do we need humanoid Robots? An interesting question
Speaker 1: because we often, at least I don't know, I can't
Speaker 1: say we. I often think of robots as sort of
Speaker 1: anthropomorphic robots, like I think of droids in the Star Wars,
Speaker 1: like C three b O that kind of droid. Not
Speaker 1: are two. He's clearly not humanoid. But you know, I
Speaker 1: think of humanoid robots more frequently than other types, despite
Speaker 1: the fact that the vast majority of robots I have have
Speaker 1: encountered have not been humanoid robots. So that does raise
Speaker 1: a question does a humanoid robot even makes sense? We
Speaker 1: try and answer that in this particular episode, Enjoy. I
Speaker 1: asked Josh what he would like to cover, because with
Speaker 1: the fact that I've got all these guests coming in
Speaker 1: to sit down with me, um, you know, some people
Speaker 1: like to come up with their own suggestions. Some people
Speaker 1: preferred if I pick a topic and then they research it.
Speaker 1: I asked Josh what he would like to talk about,
Speaker 1: and you were really interested in the idea of humanoid robots. Well,
Speaker 1: you have this awesome spreadsheet of um of listeners suggestions,
Speaker 1: and it might as well been a neon when it
Speaker 1: was going down the sheet. I'm like humanoid robots, of course,
Speaker 1: and this is a great topic. In order to really
Speaker 1: get into it, I was going to define a few terms,
Speaker 1: even though a lot of these are ones that I
Speaker 1: think most of us just kind of understand just from
Speaker 1: the fact that this is in our culture now. It's
Speaker 1: not just not just a reality as far as technology goes,
Speaker 1: but it plays a large part in fiction. In fact,
Speaker 1: that's where the term robot comes from, is from fiction. Uh.
Speaker 1: It was from Carrel Chopeck, a Czechoslovakian playwright. I did,
Speaker 1: in fact listen to it a couple of times. Carrel Chopec, Yeah,
Speaker 1: because it's his last name is spelled c A p
Speaker 1: e K. And it includes uh symbols that are not
Speaker 1: in the English alphabet, like squiggly lines and little UFOs
Speaker 1: and things he wrote. Are you are also known as
Speaker 1: Rossum's Universal robots, and the word robot comes from the
Speaker 1: check word robot to which means forced labor. Yeah, so
Speaker 1: a robot is a an entity, a synthetic construct that
Speaker 1: is forced to do work. Then we have humanoid, which
Speaker 1: just means resembling a human being. That's a term that
Speaker 1: is relatively young. It started showing up around the turn
Speaker 1: of the twentieth century. And uh, it started I think
Speaker 1: the first few times it was ever mentioned was around
Speaker 1: nineteen twelve, and it was mostly used then to describe fossils,
Speaker 1: saying these are humanoid fossils, like yeah. And then we
Speaker 1: have android, which is we're probably not gonna be using
Speaker 1: that word very often, but android is a robot that's
Speaker 1: in the form of a human. So all androids or robots,
Speaker 1: but not all robots are androids. And you know, I
Speaker 1: ran into I looked up android as well. Yeah, and
Speaker 1: apparently that's from like the early eighth century. It's a
Speaker 1: little odd that it actually predates robots. Yeah, but uh,
Speaker 1: when we look at myths and legends, there's so many
Speaker 1: stories that involve a human like entity that's not actually
Speaker 1: a person that you can see where it gets translated
Speaker 1: in there. This gets a little confusing too, because Star
Speaker 1: Wars they called all their robots droids, but there they
Speaker 1: aren't androids are two? T two is not an android
Speaker 1: because he's not um or it's not human shaped. You
Speaker 1: could even argue that C three Po is not a
Speaker 1: true android because some people say to be an android
Speaker 1: you have to appear, at least on casual glance to
Speaker 1: be human. He's way too shiny, way too shiny. Data
Speaker 1: from Star Trek Next Generation might be uh android, but
Speaker 1: he's an android who's had, you know, a long time
Speaker 1: in the man cave. He hasn't seen much sun, right, Yeah,
Speaker 1: because he's definitely got a weird complexion. Thing goes the
Speaker 1: kid in a I would be an android David, yes,
Speaker 1: which turns out to be a popular name for droids,
Speaker 1: because there was well there's David in AI, and there
Speaker 1: was also David and Prometheus. Oh you know, I never
Speaker 1: saw Prometheus. I don't know if your listeners are going
Speaker 1: to agree with me or not, because I could see
Speaker 1: um getting shouted down. But I thought Prometheus was a
Speaker 1: great movie. Even upon second viewing, I thought it was good.
Speaker 1: You know, I know that the from the artistic level,
Speaker 1: A lot of people really loved it, And then there
Speaker 1: were some people who said, how can you get lost
Speaker 1: if you have a three dimensional map with you at
Speaker 1: all time? But you know, plot versus artist, I don't know.
Speaker 1: Then you've got replicants from Blade Runner. These are more
Speaker 1: like cyborgs because they have some sort of organic material
Speaker 1: attached to them. They're not completely you know, synthetic material.
Speaker 1: So Terminator is another example. They have a fleshy over
Speaker 1: skin on top of their metallic bodies. But was that
Speaker 1: real skin that he had there was a synthetic skin,
Speaker 1: because that would make a difference. That's a good question.
Speaker 1: And I uh, you know, I know that they refer
Speaker 1: to them as cyborgs at least a few times in
Speaker 1: the movies, which would suggest that it's actual skin. Maybe
Speaker 1: it's lab grown human skin. So you know, there's some
Speaker 1: fuzzy lines around these definitions. I would think that cyborgs
Speaker 1: would be the hardest of all of the the um
Speaker 1: humanoid robots to make, because the flesh would just wrought
Speaker 1: like you have your normal looking humanoid robot your cyborg,
Speaker 1: and it's ear would just fall off. Yeah, and it's
Speaker 1: not as easy as you might think to wire together
Speaker 1: the wet wear that's in our heads, hardware that runs
Speaker 1: on circuits. We will often think of computers working in
Speaker 1: a way that's similar to our brains, but in fact
Speaker 1: the two work in very different ways. Well it seems
Speaker 1: like running into this though, Strickland um, the the more
Speaker 1: we got into humanoid robotics, the more we started to
Speaker 1: understand just how complex we are. Yeah, that's one of
Speaker 1: the things that I think is a benefit of study
Speaker 1: of humanoid robotics. The idea of pursuing the goal of
Speaker 1: creating a humanoid robot is not just that we learn
Speaker 1: more about all the different areas and robotics and they're
Speaker 1: a lot, and we'll talk about some of them, but
Speaker 1: we also learn more about ourselves. We're trying to figure out, Okay,
Speaker 1: if we're going to make something that is able to
Speaker 1: perform tasks the way human does, then we really got
Speaker 1: to take a close look at humans. That's that's the
Speaker 1: first place to start. So what makes a humanoid robot?
Speaker 1: And generally speaking, we're talking about a robot that has
Speaker 1: basic features usually minimum a torso, arms and legs, and
Speaker 1: is walking up right. Uh, it may have a head
Speaker 1: or it might not. Early humanoid robots didn't, or at
Speaker 1: least their sensory uh. Instruments were all located within the
Speaker 1: top part of the torso there wasn't like a separate head.
Speaker 1: Did you see a picture of Minerva at the Smithsonian? No?
Speaker 1: I did not. It's a robot to her guide, but um,
Speaker 1: she came up in the humanoid robot research and I
Speaker 1: think she's stretching it a little bit. Yeah, she looks
Speaker 1: a bit like a washing machine with a couple of
Speaker 1: UM cameras on top. So just those alone, I guess
Speaker 1: makes her eligible for the humanoid robot realm. But that
Speaker 1: that seems like that's a bit of a you know,
Speaker 1: if it has an appendage, that doesn't necessarily make a humanoid.
Speaker 1: I mean, you could look at the Mars Curiosity rover,
Speaker 1: which has several appendages, but I don't think anyone would
Speaker 1: ever describe it as humanoid. Right, So, uh, ideally a
Speaker 1: humanoid robe lot would be able to interact with humans
Speaker 1: within a human environment. Because here's the thing about we,
Speaker 1: we people. We have defined our environments to a large extent,
Speaker 1: especially in developed nations, where the stuff that's around us
Speaker 1: we have shaped so that it works within our capabilities,
Speaker 1: right with our with our human environment thus far. If
Speaker 1: you look at technology though, on the whole, we've pretty
Speaker 1: much been forced to adapt to it. So, for example,
Speaker 1: like a keyboard, we don't normally naturally, you know, um
Speaker 1: express ideas through our fingers on a little a little board, right,
Speaker 1: we don't normally do that, So we had to adapt
Speaker 1: to the technology and learn to type and get good
Speaker 1: at it. With humanoid robots, it's basically going the exact opposite.
Speaker 1: It's saying we already have an environment, we already are um,
Speaker 1: you know, good at all this other stuff. If we're
Speaker 1: gonna make humanoid robots, one of the great benefits is
Speaker 1: they can adapt to us. Right. Yeah, we don't have
Speaker 1: to uh create a unitask or robe, but that's really
Speaker 1: good at one thing, um that may or may not
Speaker 1: be something that humans can do easily. We can make
Speaker 1: a robot that's good lots of things. Uh. I also
Speaker 1: think usually when I think of humanoid robots, when I
Speaker 1: think of robots in general, I normally think that they
Speaker 1: are at least semi autonomous. That's that's one of the
Speaker 1: things I usually think of. It doesn't necessarily have to be.
Speaker 1: You could have a tel operated robot, but I almost
Speaker 1: think of that closer to the realm of like a
Speaker 1: remote controlled car or a puppet even. Um So, I
Speaker 1: often one of the definitions I use is that it's
Speaker 1: an autonomous or semi autonomous machine in human form. It's
Speaker 1: mechanical and electronic, and it can thus do the sort
Speaker 1: of things humans do, but do it in a totally
Speaker 1: synthetic way. And you have to be careful when you
Speaker 1: say autonomous or semi autonomous, because the state of the
Speaker 1: art right now appears to be that robots display autonomy
Speaker 1: because they just kind of wander off in places they're
Speaker 1: not supposed But it's not because they want to. It's
Speaker 1: because their their program just ran a foul of program. Right.
Speaker 1: There's no determination there on the part of the robot.
Speaker 1: It's not exploring its environment on its own accord. It's
Speaker 1: someone made a mistake in the code somewhere and where
Speaker 1: the robot was supposed to take a left hand turn
Speaker 1: at this one you know, predetermined spot, and instead continued
Speaker 1: forward or something exactly. Um So, I wanted to talk
Speaker 1: a little bit about the history of humanoid robots, and
Speaker 1: if you wanna look way way way back, I mean
Speaker 1: we're talking about the first people to really kind of
Speaker 1: attempt to build a humanoid machine that could mimic or
Speaker 1: the movements at least of a person. You gotta go
Speaker 1: all the way back to Greece between the years ten
Speaker 1: and seventy Common era. That's when Hero of Alexandria started
Speaker 1: to create various machines. He's also the person who made
Speaker 1: the first working steam engine style tool, which is pretty impressive. Yeah.
Speaker 1: He he had come up with a lot of very
Speaker 1: clever designs. Whether they were built or not depends upon
Speaker 1: uh certain accounts and and if they're true. But the
Speaker 1: stuff he designed is completely build a bowl. So he
Speaker 1: didn't come up with any ideas where it was so
Speaker 1: you know, outlandish, that was impossible. He wasn't just like
Speaker 1: drawing in the margins of his diary or something. No, Yeah,
Speaker 1: he came up with specific plans that people today have recreated.
Speaker 1: They built their own versions. Yeah. So he created a
Speaker 1: lot of designs for automata. Although these are things that
Speaker 1: were controlled by pulleys and ropes and cogged wheels, and
Speaker 1: uh needed some form of outside influence to make them work,
Speaker 1: so they're not all fully self contained like the show
Speaker 1: biz pizza Rocke fire explosion day and yeah exactly, yeah, yeah,
Speaker 1: it was some one of those audio animatronic figures that
Speaker 1: that looks very robotic, but you realize it's really just
Speaker 1: one tiny piece of a giant system. Uh. In four,
Speaker 1: we get up to Leonardo da Vinci. He designed an
Speaker 1: automaton in the form of a mechanical night which uh
Speaker 1: again supposedly he built. There's no actual record of an
Speaker 1: existing one from history, but they have created ones based
Speaker 1: on the design since then, and it could do things
Speaker 1: like move its arms and raise its visor. Who's doing this?
Speaker 1: Who's doing this? Crazy engineers who are also uh, very
Speaker 1: excited about history and very wealthy too, I would imagine. Yeah,
Speaker 1: so in this case, you're talking about Mark Rossheim, who
Speaker 1: recreated this particular machine, and it it's a night, it's
Speaker 1: a night in German medieval armor. And it can sit down,
Speaker 1: it can stand up, it can move its arms, it
Speaker 1: can raise a visor, it can work its jaw ling,
Speaker 1: I imagine. So I tried to find video of ross
Speaker 1: Heims version working and I couldn't find it. He did, however,
Speaker 1: make another of Da Vinci's inventions, which was a self
Speaker 1: driving cart that used Yeah you you wound a spring,
Speaker 1: and it had cam stops that would allow it to
Speaker 1: steer a predetermined path. You would actually program the cart
Speaker 1: by putting cam stops in particular locations along the cam
Speaker 1: and that would tell it when to turn left or
Speaker 1: when to turn right, so it couldn't it couldn't navigate
Speaker 1: through uh an obstacle course unless you had already previously
Speaker 1: seen the obstacle course and you could figure out when
Speaker 1: it needed to turn ahead of time, so you're essentially
Speaker 1: programming the device. Um. There are lots of examples in
Speaker 1: the renaissance of automata and semi automata, things that are
Speaker 1: really more like puppets. You've heard about the Mechanical Turk
Speaker 1: have the chess playing robot uh So it looked like
Speaker 1: it was a robot that could play chess and was
Speaker 1: really really good at playing chess, and it turned out
Speaker 1: eventually to be a hoax. It was actually it was
Speaker 1: actually a puppet, and there was an actual chess master
Speaker 1: hidden in a cabinet beneath the Mechanical Turk who sat
Speaker 1: kind of Indian style with a chessboard in front of
Speaker 1: him and could move the pieces to where it needed
Speaker 1: to be. But it was all being guided by an
Speaker 1: actual chess master who was hidden under When was that
Speaker 1: that was late Renaissance early Enlightenment. That in and of
Speaker 1: itself is pretty impressive. Yeah, it was. It was neat
Speaker 1: that people were thinking about these sort of things. Uh.
Speaker 1: By ninety six we get the first humanoid robot to
Speaker 1: appear on film, uh, Metropolis, the character of Maria, and
Speaker 1: at ninety nine at the World's Fair, Westinghouse Electric Corporation
Speaker 1: showed off a robot called Electro. Now have you ever
Speaker 1: seen this? So he kind of looks like the ten
Speaker 1: man from the Wizard of Oz film. Yes, he smokes.
Speaker 1: I have seen one of the things he can do
Speaker 1: get a little bellows in his head that allowed him
Speaker 1: to puff smoke. He could also kind of speak. He
Speaker 1: had a seventy eight revolution per minute UH record player
Speaker 1: essentially inside of him. I suppose if the if the
Speaker 1: needles skipp it would at least sound like it. Um.
Speaker 1: He repeat himself over. He called the audience twots. That
Speaker 1: was the name. Yeah, he's apparently the main reason he
Speaker 1: was retired from being shown off at exhibitions was because
Speaker 1: it was very dated kind of lingo. But he was
Speaker 1: used at the nineteen thirty nine World's Fair, which was
Speaker 1: It's funny because I'll be talking about that again in
Speaker 1: another episode very shortly. The World's Fair would have been
Speaker 1: an amazing thing to visit. Um, I'm more I can
Speaker 1: understand that. But if you're if you're going to get
Speaker 1: to the point where you're looking at full scale anthropomorphic robots,
Speaker 1: you gotta get up to about ninety three. That's when
Speaker 1: the Waybot one from the Waseda University came out. That
Speaker 1: was the first full scale anthropomorphic robot developed in the
Speaker 1: world which had limb control, a vision system, so I
Speaker 1: had an optical system that could recognize its environment and
Speaker 1: objects and measure distance, and it also had a conversation system. Uh.
Speaker 1: It was actually a collection of a bunch of very
Speaker 1: complex machinery. Like its hands had been previously developed independently
Speaker 1: of the robots, so had its legs. So it's like
Speaker 1: all these people coming up with these various pieces saying,
Speaker 1: all right, let's connect all this together and see what happens.
Speaker 1: So that was a huge, huge leap forward. Yeah, you know,
Speaker 1: if you'll notice, we went basically from um HOAXI chess
Speaker 1: playing turks to you know, a robot that could converse
Speaker 1: and interact with its environment. And then um, it seems
Speaker 1: like we we kind of went off course for a
Speaker 1: little bit and now we're coming full circle back to
Speaker 1: that where like you said, a lot of different disciplines
Speaker 1: are contributing these different pieces to what will eventually be
Speaker 1: all of the best practices from each little sub discipline
Speaker 1: put together in you know, the true humanoid robot. Well yeah,
Speaker 1: I mean, if we're talking about a humanoid robot that's
Speaker 1: capable of interacting with people as if they were, you know,
Speaker 1: their own person, even though maybe an odd person, not
Speaker 1: like the kind of person you would typically run into.
Speaker 1: There's it's a multi disciplinary approach. I mean, artificial intelligence
Speaker 1: by itself is multi disciplinary because you have sensing, you
Speaker 1: have so all the perception, there's all these different just
Speaker 1: that's multi disciplinary. Then you've got the processing, the cognition,
Speaker 1: things like planning, navigation. There are so many things that
Speaker 1: come together to make a humanoid robot a a possibility.
Speaker 1: And that's just the the mental side, right. Then you
Speaker 1: have all the physical side, the how do you make
Speaker 1: it walk, how do you make it keep its balanced?
Speaker 1: So lots of stuff to consider there. We're gonna take
Speaker 1: a quick break but when we come back, we will
Speaker 1: look more at the issue of humanoid robots. Wybot two
Speaker 1: came out in that was a specialist robot. It could
Speaker 1: play a keyboard, trying a keyboard. He could read sheet
Speaker 1: music and play music. Uh. It was because it was
Speaker 1: a specialist. It was not able to do the general
Speaker 1: functions that it's predecessor could do. And that's why the
Speaker 1: issues in robotics today is that it's very challenging to
Speaker 1: build a general purpose robot. It's much easier to take
Speaker 1: a specific task that you need to have done and
Speaker 1: designed a robot to do that. Yeah, because I mean
Speaker 1: we already have those rooms and rovers. I mean you know,
Speaker 1: there's there's also all the robots and manufacturing, all the
Speaker 1: welding robots things like that. Uh. Nine Pacific Northwest National
Speaker 1: Laboratory built a robot called Manny that was the first
Speaker 1: full scale android body and it had forty two degrees
Speaker 1: of freedom but no AI or autonomy. It was completely teleoperated.
Speaker 1: And um it took me a couple of times to
Speaker 1: figure out what degrees of freedom meant. Yeah, Um, I
Speaker 1: thought it meant like the it could move its arm
Speaker 1: forty two degrees basically, but a degree of freedom is say,
Speaker 1: like it can move its wrist, that's a degree of freedom.
Speaker 1: It can turn its head left and right, that's a
Speaker 1: degree of freedom right right. And if you look at
Speaker 1: the human hand, the human hand has about thirty degrees
Speaker 1: of freedom, meaning that you look at the way each
Speaker 1: finger and your thumb can move. You look at the
Speaker 1: way you can clench a fist, you can twist your
Speaker 1: hand with your wrist um, those are all different degrees
Speaker 1: of freedom. And uh. In fact, one of the cool
Speaker 1: things about robots is that as we get better and
Speaker 1: better at designing them, we can create robots that have
Speaker 1: far more degrees of freedom than the human body does.
Speaker 1: So I like the idea of a humanoid robot in
Speaker 1: the future that has sixty degree motion with its wrist
Speaker 1: and then just having it changed light bulbs. Is it
Speaker 1: just spin and not have to do the little twisty
Speaker 1: turning motion. How many robots does it take to change
Speaker 1: the light bulbs? Just just the one, just that one,
Speaker 1: just one billion dollar rob Yeah. Yeah, I'm not saying
Speaker 1: it's a fishing system. I'm just saying I'm in supremely
Speaker 1: lazy human being with tall ceilings. Uh. In nine Honda
Speaker 1: introduced the P two robot, which was a self contained
Speaker 1: robotic humanoid. It could walk and climb stairs. The P
Speaker 1: three followed in n and in two thousand two, Honda
Speaker 1: introduced My good buddy as Emo. As the first article
Speaker 1: I wrote for How Stuff Works. As Works have an
Speaker 1: episode on it. I have not done a full episode
Speaker 1: on Asimo. I even was offered the opportunity to meet
Speaker 1: as Amo when I first wrote the article, but it
Speaker 1: would have meant having to travel to Disneyland to do it,
Speaker 1: and at the time, How Stuff Works was not prepared
Speaker 1: to do such a I went to Disneyland by myself,
Speaker 1: uh well with my wife, and we went and saw
Speaker 1: the Asimo production. And at the end of it, I
Speaker 1: talked to of the Disney cast members and I said, yeah,
Speaker 1: I wrote the article about how Asthma works for How
Speaker 1: Stuff Works, and she said, hang on a minute. And
Speaker 1: I got to meet Asthmo. And it was a man
Speaker 1: in a suit, right. It was actually it was actually
Speaker 1: a collection of cats that the duct taped together and
Speaker 1: then plastic. No, it was a working robot. That's pretty
Speaker 1: near how blown away? I was very much blown away.
Speaker 1: It was cool seeing it up close. I mean, it
Speaker 1: looks like a little tiny astronaut right because he's got
Speaker 1: like the face plate especially. I love the people call
Speaker 1: it he people give And I do this all the
Speaker 1: time too. With robots, I'll sign a gender even though
Speaker 1: technically many of them are specifically genderless. As amo is
Speaker 1: is supposed to be genderless, but I often refer to
Speaker 1: Asmo as a he as well. Well, you know why.
Speaker 1: It's the shoulders, I would guess. Yeah, they go straight
Speaker 1: across and and and far out. That's very masculine no
Speaker 1: matter what. Yeah, and you need that, I would guess
Speaker 1: you need shoulders in a humanoid robot with flexible arms. Well,
Speaker 1: and also, I'm sure every single element of Asimo is
Speaker 1: built with the balance in mind, because is the first
Speaker 1: robot that can run. Yes, I've seen him run. It's gawky. Yeah,
Speaker 1: it kind of look like someone who really needs to
Speaker 1: get to the bathroom as a little bit of a
Speaker 1: hoppy kind of run. But the the definition of run
Speaker 1: here is that there are moments where both feet are
Speaker 1: off the ground. So walking you always have one ft
Speaker 1: in contact with the ground, and running both feet at
Speaker 1: some point are out of contact. And that's a huge
Speaker 1: deal for robotics, right. I mean, you have a machine
Speaker 1: that completely separates itself from contact on the ground. It
Speaker 1: has no propulsion to keep it upright, you know, it
Speaker 1: doesn't have like propellers or jets or anything like that.
Speaker 1: So you have to design it so it can it
Speaker 1: can propel itself off the ground and then catch itself
Speaker 1: when it comes back down without falling over. And that
Speaker 1: is a non trivial challenge. No, it's an enormous challenge
Speaker 1: that robots UM really kind of started to tackle lately. UM.
Speaker 1: One of the ways that they've overcome it is with
Speaker 1: rounded feet, which are very helpful in keeping balanced and
Speaker 1: allowing it to run UM. But there's drawbacks to it
Speaker 1: as well, Like the robot can't start itself, it also
Speaker 1: can't stop, so it can't stop moving, which is not
Speaker 1: something you want. Like, there's still some challenges there. Ahead
Speaker 1: of the robotists who are learning to teach a robot
Speaker 1: to walk, and even the ones that have taught robots
Speaker 1: to walk UM, they typically can just walk over flat
Speaker 1: surfaces with no obstacles. When they encounter stairs, there in trouble.
Speaker 1: But then you have robots that know how to go upstairs,
Speaker 1: but they can't walk on a flat surface. Eventually, all
Speaker 1: this information, all this knowledge will be brought together and
Speaker 1: you'll have a robot that can walk no problem. Right.
Speaker 1: In fact, this kind of transitions nicely into those challenges
Speaker 1: that face designers of humanoid robots and and locomotion is
Speaker 1: the probably one of the top ones, at least from
Speaker 1: the physical engineering side. For example, you know, as Amo
Speaker 1: can can go up and downstairs, but that is a
Speaker 1: little deceptive because as Amo has to be programmed to
Speaker 1: go up or down the staircase and know exactly how
Speaker 1: many stairs are involved. It's not so much it's not
Speaker 1: a case of Asimo detecting a staircase and then uh,
Speaker 1: and then navigating through oh up or down it. It's
Speaker 1: the fact that all right now we're initiating your stair
Speaker 1: climbing program. Yeah exactly. It's kind of like smoke and
Speaker 1: mirrors robotics. Basically, it's at But that's you know, those
Speaker 1: are the little no no pun intended, Those are the
Speaker 1: little steps you have to take in order to get
Speaker 1: to the destination. What do you mean, no pun intended.
Speaker 1: I don't buy that at all. I started saying it
Speaker 1: without thinking about it, and then I mean, but then
Speaker 1: I did follow through with it, so I guess there
Speaker 1: was some intention there at the end. But uh yeah.
Speaker 1: They're also not very good at going across any kind
Speaker 1: of uneven terrain, right, So, humanoid robots in particular find
Speaker 1: it very difficult to maintain balance over anything that's not
Speaker 1: either a flat surface or in the case some robots
Speaker 1: that can go up or downstairs and stairs. So if
Speaker 1: you're talking about like a sidewalk that is not completely even,
Speaker 1: that would be enough to give a robot trouble because
Speaker 1: it's going to try and put its foot down to
Speaker 1: where it would believe the ground to be, and if
Speaker 1: the ground is not exactly level, then that's yeah, because
Speaker 1: they can't really catch their balance very well. There are
Speaker 1: robots that can, but they are four legged. Yeah, you've
Speaker 1: you've seen the Big Dog video, No, I saw the Army,
Speaker 1: though it's very similar. Big Dog is essentially a robo
Speaker 1: mule type development. It is a four legged robot that
Speaker 1: is able to maintain its balance even when pushed. And
Speaker 1: the famous video shows the robot dog the Big Dog
Speaker 1: kind of jogging and then a guy just casually lifts
Speaker 1: his leg up and kicks the robot dog like he
Speaker 1: puts essentially puts the bomb of his foot against the
Speaker 1: side of it and pushes really hard, tipping and you
Speaker 1: see the big dog stumble. It actually stumbles and then
Speaker 1: catches itself and then rights itself and continues on. And
Speaker 1: almost everyone has an emotional reaction to this, like how
Speaker 1: dare that evil man kick that poor defenseless robot. The
Speaker 1: robot can't feel anything, but that robot is um gasoline powered.
Speaker 1: So oh yeah, that's right. That's one of the big
Speaker 1: dis keeping it inside you. Yeah, you wouldn't want to
Speaker 1: have one of these indoors. No, you don't bring your
Speaker 1: lam indoors. No, and uh. And the the pistons that
Speaker 1: allow it to do this are quite loud, you know.
Speaker 1: It's not not a subtle system at all. So a
Speaker 1: lot of work has to go into creating better systems
Speaker 1: for robots to maintain their balance in order for the
Speaker 1: locomotion problem to really be solved. And again, I mean,
Speaker 1: like anybody who's seen short Circuit knows that you can
Speaker 1: build a robot like Johnny five with arms in the
Speaker 1: head and a torso and then like traction um wed
Speaker 1: shreds uh and it can go anywhere over terrain, it
Speaker 1: can go up steps. Probably. The thing is is again
Speaker 1: you have to remember when it comes to humanoid robots,
Speaker 1: you're trying to make the robot that can adapt to
Speaker 1: the human world. So if you had somebody like Johnny
Speaker 1: five as your house butler or something, you you couldn't
Speaker 1: You couldn't have an island in your kitchen, and who
Speaker 1: doesn't love an island in their kitchen. Johnny five couldn't
Speaker 1: maneuver around it because he's too wide. Yeah, you wouldn't
Speaker 1: have You wouldn't be able to have any any space
Speaker 1: that would be narrower than the robot's body exactly. That's
Speaker 1: not what you want. Yeah, with humanoid robots, it wouldn't
Speaker 1: work well. In my house. I've got a I've got
Speaker 1: a a flat style house where there's three floors. Yeah,
Speaker 1: it's like flat, like European flat. Uh, not flat as
Speaker 1: in there's only one level. They're actually three of them,
Speaker 1: four if you count the rooftop denck, so that counts.
Speaker 1: It makes it. You know, any robot that would not
Speaker 1: be able to navigate stairs easily would definitely have an issue,
Speaker 1: which is the main reason why I don't have a rumba,
Speaker 1: because I don't want to hear the sound of a
Speaker 1: roomba going falling down a flight up stairs. Um, but
Speaker 1: at any rate, Uh, that's a great point. Moving on
Speaker 1: from locomotion, there's also dexterous manipulation. Yeah, I think we should.
Speaker 1: I think that point bears repeating. What we just talked
Speaker 1: about is locomotion. Yeah, and this is you and I
Speaker 1: a couple of non robot experts talking about the problem
Speaker 1: with locomotion. That's just one of myriad challenges facing humanoid
Speaker 1: robotics designers. Yeah, yeah, exactly. It's It's one that's easy
Speaker 1: to point to because it's something that we all, you know,
Speaker 1: end up at least observing or participating in all the time.
Speaker 1: Can we take it for granted? But then when you think, okay, well,
Speaker 1: how do I make a machine that does that? You
Speaker 1: start to realize this is you know, even if I
Speaker 1: have a leg that has lots of different degrees of
Speaker 1: freedom and points of articulation, I still have to design
Speaker 1: the upper part of the robots so that it does
Speaker 1: not unbalance the lower part, and if it does on balance,
Speaker 1: it's able to catch itself. You know, some people just
Speaker 1: describe walking as falling and catching yourself over and over again. Yeah, yeah,
Speaker 1: they're walking right now. No, I I described walking as
Speaker 1: something that other people do. I like to keep my
Speaker 1: walking to a minimum. I thought you walked alot, Actually
Speaker 1: I do. I just joke about being lazy. I think
Speaker 1: moving forward, falling down and catching your balance every time
Speaker 1: it's lurching. Yeah, that's well. As an Adams Family fan,
Speaker 1: I'm okay with that. Yeah, but uh, Dexter's manipulation would
Speaker 1: be the ability to pick up and manipulate objects. Now,
Speaker 1: we're really good at that, we humans, You know, we
Speaker 1: can we can feel an object and decide at that
Speaker 1: point how to handle it, even if we've never encountered
Speaker 1: that kind of object before. So if I encounter something
Speaker 1: I've never seen before and i've I've ascertained it's safe
Speaker 1: for me to touch it, I can touch it. I
Speaker 1: can feel like, I can get a feel for how
Speaker 1: heavy it is, I can get a feel for how
Speaker 1: eloquant it might be, and then I can adjust on
Speaker 1: the fly so that I can handle it appropriately. Well,
Speaker 1: I'm not gonna hurt myself. I'm not gonna hurt the object.
Speaker 1: Robots are not so good at that. Yeah, exactly, even
Speaker 1: if they don't mean to right, Yeah, if the robots.
Speaker 1: If the robots grip is too strong, it can break
Speaker 1: the object. If it's too weak, the object slips from
Speaker 1: its grip and it falls. Uh. And it may not
Speaker 1: be able to distinguish between different types. So getting those
Speaker 1: tactile sensors where a robot can tell how tightly it's
Speaker 1: gripping something and how much pressure a particular object can
Speaker 1: take before you've reached the failure point is a big deal. Now,
Speaker 1: this is also a big deal for just making robots
Speaker 1: safe for humans to be around. It is a big deal.
Speaker 1: You know that the first fatality by robot occurred um
Speaker 1: at the business end of a robotic arm in a
Speaker 1: flat rock, Michigan in nine a man named Robert Williams
Speaker 1: who's working on a forward line. Yeah, his robot arm
Speaker 1: was moving a little slow for his taste in getting
Speaker 1: supplies down, so he climbed up to where the supplies were.
Speaker 1: The robot arms suddenly sped up and hit him in
Speaker 1: the head and killed him instantly. Wow. Yeah, I've I've
Speaker 1: had a chance to see some of these industrial robots. Uh.
Speaker 1: And I would say up close, but you can't because
Speaker 1: because of instances like that. Industrial robots usually have lots
Speaker 1: of of safety barriers around them because it's not safe
Speaker 1: to be near those robots when they're in operation. They
Speaker 1: they can't react exactly, So you leave it up to
Speaker 1: the humans to stay away from the robots because the road.
Speaker 1: We haven't gotten to the point where the robots no,
Speaker 1: did not crush you or hit you in the head. Right, Yeah,
Speaker 1: I got the robots fall. I'm looking forward to that
Speaker 1: day when they figure out not to crush me. Yes,
Speaker 1: it's been pretty lousy days so far. Uh. Yeah, when
Speaker 1: I when I toured the Georgia Tech Robotics Lab, they
Speaker 1: talked specifically about this. This is a real challenge having
Speaker 1: robots recognize and react in a way that's going to
Speaker 1: be safe around humans. And uh, but dexterous manipulation is
Speaker 1: only that's only a part of dexterous manipulation. Obviously. The
Speaker 1: rest of it is again that object recognition and handling
Speaker 1: so that you're not destroying whatever it is you're trying
Speaker 1: to pick up. Um. Another big challenge in designing robots
Speaker 1: in general, not just humanoid robots, is just the the perception,
Speaker 1: the sensory perception of the robot. Yeah, so you know,
Speaker 1: whether it's optical systems like actual cameras in the place
Speaker 1: of eyes, or infrared so that you can see even
Speaker 1: in low light situations, radar, light ar, I mean, there's
Speaker 1: tons of different ways of sensing. Yep, there's uh, there's
Speaker 1: you know sensing obviously, it's not just site. Then you
Speaker 1: have to have the sound. That's a really tricky one
Speaker 1: actually because for us humans, we we can kind of
Speaker 1: zero in on what's important. Right, So if we're if
Speaker 1: you and I were at a party, which you know,
Speaker 1: someone made a mistake and invited me, Uh, we could
Speaker 1: have a conversation and be able to carry that conversation
Speaker 1: on even within the context of a big, bustling party
Speaker 1: because we can focus on what the other person is saying.
Speaker 1: It's called latent inhibition. Yeah. So when you don't have that,
Speaker 1: that schizophrenia, Yeah, you you can't separate the the signal
Speaker 1: from the noise, and everything either becomes noise or everything
Speaker 1: becomes signal. Um. So for a robot that might for example,
Speaker 1: require verbal commands, that's really tricky. What if you have
Speaker 1: the television on and someone's saying something on TV and uh,
Speaker 1: you are trying to get your robot to do something
Speaker 1: and it's not quite sure what to do because it's
Speaker 1: hearing these different commands and isn't sure who to obey. Yeah,
Speaker 1: you are the person pitching the bacon bowl right right exactly.
Speaker 1: Let's say that you are, you know, trying to get
Speaker 1: some help in the kitchen, but it just keeps hearing U,
Speaker 1: C S I Miami and say kill Billy. And then
Speaker 1: next thing you know, you're like, you're just desperately trying
Speaker 1: to kill the robot. Please don't kill Billy. Um. Yeah,
Speaker 1: well that's a silly example. It's a real problem. Uh.
Speaker 1: And then there's the tactile the responses, the tactile sensors,
Speaker 1: like the making sure you don't crush something that's delicate,
Speaker 1: that that falls into perception. Smell can also fall into perception.
Speaker 1: You might want to have humanoid robots that work in
Speaker 1: areas where the humanoid robot can alert humans to the
Speaker 1: presence of things that might be toxic. You know, this
Speaker 1: isn't necessarily just the robot butler we're talking about. This
Speaker 1: could be robots that work in areas that might be
Speaker 1: dangerous for humans, and that would be an important element too.
Speaker 1: It's not a robot. But NASA already has a sensor
Speaker 1: that senses things like ammonia or smoke. It can actually
Speaker 1: sense smoke artificially smell smoke before the fires actually started ignited. Interesting, yeah,
Speaker 1: because you know it's such a dangerous proposition, right, yes,
Speaker 1: clearly for for anything NASA related. But they can also
Speaker 1: sense ammonia because you know a lot of the refrigeration
Speaker 1: systems run on ammonia and you can't have aneumonia leak
Speaker 1: on the space right right, And I mean the same
Speaker 1: thing is true for I mean I've heard of of
Speaker 1: robots that are used in in mining operations, which you know,
Speaker 1: if you come upon a pocket of natural gas that
Speaker 1: can be a real danger that sort of stuff. Then
Speaker 1: you've got the the back end of the sensory perception.
Speaker 1: That's where you have the actual interpretation of the data.
Speaker 1: Where that's a big one. It's huge because not only
Speaker 1: do you need to have a robot that can have
Speaker 1: that has binocular vision so it has a depth of field, right, um,
Speaker 1: it also has to know what it's doing, what what
Speaker 1: the information means, and how to apply it to adapted changes,
Speaker 1: right right. So So if I were to show you
Speaker 1: josh a series of pictures of various types of dogs.
Speaker 1: You would very quickly pick up on the the things
Speaker 1: that mean mean dog like, you would understand the concept
Speaker 1: of dog pretty quickly. Robots and various other computers machines,
Speaker 1: they have a lot harder problem with this. If whatever
Speaker 1: they're looking at doesn't exactly match the parameters of the example.
Speaker 1: It's very difficult for a machine to extrapolate and say, oh,
Speaker 1: this other thing I'm looking at relates to this thing
Speaker 1: I know, even though the two examples don't aren't identical.
Speaker 1: So the same thing could be true for any object.
Speaker 1: Let's let's just use a coffee mug, and let's say
Speaker 1: that you use a plain white coffee mug of average
Speaker 1: size as the example for the robot, and then the
Speaker 1: robot encounters a larger blue coffee mug and the handle
Speaker 1: has turned the other way. The robot might be completely
Speaker 1: befuddled by this. So this is a real problem in
Speaker 1: artificial intelligence. Is object identification, so that a robot knows
Speaker 1: what it's looking at and also understands the context that
Speaker 1: that object fills within the environment. So it's not just that, oh,
Speaker 1: that's a mug, it's oh, that's a mug. A mug
Speaker 1: is a container. I can put things into that mug.
Speaker 1: You are the things that can go in the mug.
Speaker 1: Here are the things that absolutely should not go in
Speaker 1: the mug, like Billy. Those are the kind of things
Speaker 1: that yeah, Billy, well you know we're gonna need another Billy. Um,
Speaker 1: we'll make a robot Billy. Yeah, which in which case
Speaker 1: you can just turn those suckers out right, mass production
Speaker 1: of Billy. But yeah, artificial intelligence an enormous problem. And that,
Speaker 1: of course is not just with robotics. That's that's a
Speaker 1: field unto itself, and robotics is just one branch that
Speaker 1: relies upon artificial intelligence. And it's from what I came across,
Speaker 1: it looked like just out of the gate, I guess
Speaker 1: that was said a university, they tried to build a
Speaker 1: robot that was just like high functioning, Yeah, and they realized, like,
Speaker 1: we have no idea what we're doing. Yeah, that that
Speaker 1: waybot one was able to converse at the level or
Speaker 1: was able to have a a a cognitive function equivalent
Speaker 1: to a one and a half year old person, which
Speaker 1: I have to say, when you're talking right out of
Speaker 1: the gate, Yeah, impressive, very impressive, because we're not that
Speaker 1: much further along now. But what they found from making
Speaker 1: waybot one was, Okay, this is way more difficult than
Speaker 1: we thought. You can't just program every kind of coffee
Speaker 1: cup in the world, and even if you could, then
Speaker 1: you also have to program every kind of table and
Speaker 1: every kind of light. And we need to come at
Speaker 1: this in a different way. And so they realized number one,
Speaker 1: humans are extraordinarily more complex than we thought before. And
Speaker 1: then number two, humans make a pretty good model for
Speaker 1: a humanoid robot in the realm of things like perception
Speaker 1: and UM information systems and uh learning. So they went
Speaker 1: to these different these different disciplines like neurobiology, neurology, um psychology,
Speaker 1: and they said, what can we learn from you guys
Speaker 1: about how humans do this that we can apply to robots.
Speaker 1: And since they started taking those steps, it seems like, uh,
Speaker 1: humanoid robotics has gotten it's it's footing a little more. Yeah,
Speaker 1: and we're seeing so many developments in other areas of
Speaker 1: AI that are really promising. I always bring up IBM
Speaker 1: S Watson because it's natural language recognition was phenomenal. The
Speaker 1: ability for it to parse clues in jeopardy and come
Speaker 1: up with the appropriate answer, knowing that Jeopardy those clues
Speaker 1: are not always straightforward. Uh. And it again illustrates the
Speaker 1: complexity that we humans navigate without much trouble because this
Speaker 1: is the world we've created. But then we realize if
Speaker 1: we make a machine that's mostly when you get down
Speaker 1: to it based on yes or no, a one or
Speaker 1: a zero, true or false, and you're trying to build
Speaker 1: complex behaviors off of something that is incredibly simple. When
Speaker 1: you boil it down to its basic element, that's where
Speaker 1: you're like, oh, this is this is gonna require a
Speaker 1: lot of work. I mean, IBMS Watson was an enormous
Speaker 1: machine with with thoul of microprocessors just so it could
Speaker 1: be able to play Jeopardy. That's a very specific function too.
Speaker 1: We'll be right back after this next break. So, creating
Speaker 1: a robot that is able to navigate and interact with
Speaker 1: a human environment and be able to interact with humans
Speaker 1: in a way that makes sense is a big challenge. Also,
Speaker 1: just the way that a robot would socialize with humans
Speaker 1: is a huge challenge. How do how do you make
Speaker 1: a robot that is able to respond to commands and
Speaker 1: cues in an appropriate way? Uh? An appropriate way is
Speaker 1: the key there, because there are humans are pretty complex
Speaker 1: and we can be very subtle in many ways. Yeah,
Speaker 1: we speak unplainly, we use sarcasm, um, we we uh yeah,
Speaker 1: we use a lot of gestures rather than just words. Yep.
Speaker 1: There's a lot that goes into human communication that, if
Speaker 1: you are a human, is pretty much natural, especially I
Speaker 1: mean if you're a human within that particular culture and
Speaker 1: you're familiar with that culture, Because anyone who has traveled
Speaker 1: extensively knows there are cultures where things that would be
Speaker 1: commonplace at home are very different in the place where
Speaker 1: you happen to be, right then, and it may be
Speaker 1: that something that is completely innocent at home is an uh,
Speaker 1: offensive gesture in the place where you are. Now, we'll
Speaker 1: imagine a robot that is not programmed to handle these
Speaker 1: kind of subtle uh communication methods, and yeah, he doesn't know,
Speaker 1: he's just he's just doing as he was programmed. But
Speaker 1: even even beyond that, something that you brought up in
Speaker 1: our research when we were planning this was the Uncanny Valley. Yeah,
Speaker 1: that's it's a big one. Yeah, I've never read that
Speaker 1: paper before, and I'm glad I did. It's really interesting, right, Yeah.
Speaker 1: So the uncanny Valley, for those who are not familiar
Speaker 1: with the term, uh it's it describes when we start
Speaker 1: to appre coach artificial humans that look almost, but not
Speaker 1: quite like real humans. And and by look, I don't
Speaker 1: necessarily just mean the physical appearance. I also mean their behaviors,
Speaker 1: their movements. So if you are if you were to
Speaker 1: look out and see a figure that from the from
Speaker 1: a distance looked like it was a human figure, and
Speaker 1: you start walking towards it just thinking this is another person,
Speaker 1: and then they start moving in a very herky jerky motion,
Speaker 1: very mechanical motion, then you're likely going to have a
Speaker 1: negative emotional response. Um often revulsion is one of the
Speaker 1: words used us. Yeah, I mean I remember the C
Speaker 1: G I movies that would that were almost to the
Speaker 1: point of photo realism, where they look like people for
Speaker 1: the most part, but there's not something's just not quite
Speaker 1: right with the eyes. There's a good example, and Polar
Speaker 1: express polar expresses the way everyone very well because the
Speaker 1: uncanny Valley, that's what they blame it on. Yeah, and
Speaker 1: the same thing applies to robots. So in fact, I
Speaker 1: saw a robot that was really disturbing to me, it
Speaker 1: was really an art exhibit, an installation, and um it
Speaker 1: was a robot of Confucius in a cell filled with monkeys,
Speaker 1: and uh they're live monkeys, real monkeys, and the robot
Speaker 1: would just thrash around wildly. It was it was the
Speaker 1: stuff of nightmares that I'll show it to you after
Speaker 1: the show. Yeah. So these are all big challenges, and
Speaker 1: some of them are going to be harder for us
Speaker 1: than others. It may be that the engineering challenges of
Speaker 1: locomotion are solved well before we ever get a real
Speaker 1: grip on all the artificial intelligence problems. Or it could
Speaker 1: be the other way around. Uh we but it is multidisciplinary.
Speaker 1: It's a big, big issue. So there are some people
Speaker 1: who argue for humanoid robots, there are people who argue
Speaker 1: against humanoid robots. Where do you, um, I think. I
Speaker 1: think research and development with humanoid robots is important because
Speaker 1: by having the goal of creating a humanoid robot, you
Speaker 1: drive the research and development process. You have a specific
Speaker 1: goal in mind, and in order to achieve that goal,
Speaker 1: you know what sort of problems you have to solve.
Speaker 1: And even if we never enter a future where humanoid
Speaker 1: robots are a common thing, even if they are mostly
Speaker 1: used as something in an exhibition or uh for pr
Speaker 1: or whatever. Even if that's the only use for them,
Speaker 1: We're going to benefit from the research and development of
Speaker 1: making that possible in ways we can't anticipate. Well. Yeah,
Speaker 1: and then the more we get into humanoid robotics, the
Speaker 1: more we understand humans, which is pretty much the only
Speaker 1: argument I've seen that stands up in favor of doing
Speaker 1: humanoid robots. Yeah, because it's it's expensive, and it's hard.
Speaker 1: I mean, it's it's really a different cult problem, and
Speaker 1: it's and and to build a humanoid robot something that
Speaker 1: is capable of being a general purpose robot, it's you know,
Speaker 1: it's hard to anticipate all the things you're going to
Speaker 1: need to be able to do. If you're talking general
Speaker 1: purpose and adaptable, that's really tough. I mean, we didn't
Speaker 1: even talk about the adaptability problem very much. We talked
Speaker 1: a little bit about a robot capable of learning from
Speaker 1: other people, which I find fascinating. Um, you know, that's
Speaker 1: one way, just watching humans and then mimicking humans, that's
Speaker 1: one way of robot learning. There's also, um the way
Speaker 1: where it's controlled through virtual reality by a human and
Speaker 1: it just kind of logs the motions the humans making
Speaker 1: it do. Like there's a NASA has a robot not
Speaker 1: that learns like that. So I think I think there's
Speaker 1: a lot of benefit to investigating artificial intelligence. Like you
Speaker 1: want your nest at home to learn so you don't
Speaker 1: have to keep adjusting the thermostat that counts. That's the
Speaker 1: that's sheen learning to me. The big argument against having
Speaker 1: humanoid robots, and the quagmire that seems to begin, is sociability.
Speaker 1: That seems to be the whole reason anybody wants a
Speaker 1: humanoid robot, because you can make you know, you have
Speaker 1: a ruma vacuums. You can make a driverless car um
Speaker 1: as Olivia Solan wrote and wired a couple of years back. Um,
Speaker 1: you know, why why do you have to make a
Speaker 1: robot butler to park the car? Just make a car
Speaker 1: that parks itself. And it seems like that's where we're
Speaker 1: going right now. Um. So when you add this extra
Speaker 1: layer of humanoid, you add all of this additional problems
Speaker 1: and troubles and redundancies, like like, for example, if you're
Speaker 1: gonna make a humanoid robot that throws a ball, this
Speaker 1: this humanoid robot to appear real needs to have a
Speaker 1: little bit of follow through. But as far as the
Speaker 1: robot the machine is concerned, it can throw the ball
Speaker 1: and just stop where the releases. It doesn't need to
Speaker 1: go anymore. But it's gonna look weird and robotic if
Speaker 1: you want to get past that uncanny valley, which is
Speaker 1: another problem. Um, the thing has to have followed through.
Speaker 1: That's totally unnecessary. You can make a robot that can
Speaker 1: throw a ball and the goal is to throw the ball.
Speaker 1: You don't have to add the follow through, but you
Speaker 1: do when you're making it a sociable humanoid robots. So
Speaker 1: it seems like that's the path that will lead everyone
Speaker 1: is straight that I don't get. Yeah, I I like
Speaker 1: the idea of designing robots for specific tasks because you
Speaker 1: can really focus on getting the task done. So there
Speaker 1: I see this as two separate branches. I see the
Speaker 1: branch of developing the humanoid robot as pushing forward a
Speaker 1: lot of different areas of thought that could be applied
Speaker 1: in multiple disciplines, so that will benefit from that. I
Speaker 1: see the development of robots as unitaskers as being important
Speaker 1: to actually handle the jobs that are the three D S.
Speaker 1: That's dirty, different called dangerous, all right, So those are
Speaker 1: the jobs that maybe they revolve a lot of repetition,
Speaker 1: which can cause injury over time, or it can lead
Speaker 1: to mistakes because you've done the same task so many
Speaker 1: times that you start to kind of zone out. Robots
Speaker 1: will never zone out. Um, if it's a dirty job
Speaker 1: where it's something that's undesirable by people, robots don't care,
Speaker 1: they'll do that. Or if it's dangerous, if it's bomb disposal,
Speaker 1: or if it's something like the Mars Curiosity rover. These
Speaker 1: are dangerous jobs that you wouldn't necessarily want to put
Speaker 1: a human into if you had the alternative. So all
Speaker 1: of these things, those that's where robots really makes sense
Speaker 1: to me um to to go to the places that
Speaker 1: are difficult for us to go to. Maybe that's you know,
Speaker 1: deep sea exploration, space exploration, that kind of thing, or
Speaker 1: to do jobs that might be dangerous having a first
Speaker 1: respond to robot to survey a scene to make sure
Speaker 1: that a structure is remaining solid while maybe there was
Speaker 1: a fire and it has to make sure that the
Speaker 1: it's not going to collapse in on rescue mission that
Speaker 1: kind of stuff. Um, But do you need those things
Speaker 1: to be to come out and be able to tell
Speaker 1: a joke or something. And most of them don't need
Speaker 1: to be any sort of humanoid form factor either, which
Speaker 1: greatly simplifies the actual development of the robot and thus
Speaker 1: cuts down on the cost, so you can you can
Speaker 1: achieve the task you're trying to achieve for less money
Speaker 1: than if you are trying to build this this general
Speaker 1: purpose machine. So then we come to this ultimate question,
Speaker 1: why what's the purpose of humanoid robot? Well, I think
Speaker 1: the I think the purposes too fold. One is again
Speaker 1: to have that specific goal in mind that allows you
Speaker 1: to define where your indpoint is. I believe that when
Speaker 1: you have that defined in goal, it makes it easier
Speaker 1: for you to build on the things you need to
Speaker 1: achieve it, as opposed to having an open goal where
Speaker 1: it's just I want to approve improve a I that's
Speaker 1: so open that it's hard to get direction from it.
Speaker 1: But if you think I need to have an artificial
Speaker 1: intelligence that will allow a robot to uh, here's a
Speaker 1: great example. Let's say that the challenge is to have
Speaker 1: a robot leave a room, go down a flight of stairs,
Speaker 1: leave a building, get into a vehicle, drive the vehicle
Speaker 1: to a different location, get out of the vehicle, go
Speaker 1: into another building, break through a wall and put out
Speaker 1: a fire. That's a real, actual robotics challenge challenge. Yeah.
Speaker 1: Dr Henrik Kristensen told me about this. Is I mean,
Speaker 1: it really is a challenge. It's not just a real challenge.
Speaker 1: It's a real challenge. It's like a DARPA challenge. So
Speaker 1: it's a uh he was telling me about this, and
Speaker 1: you start to think about all the things that have
Speaker 1: to fall in line for you to be able to
Speaker 1: achieve the skull That is a valuable thing. But I
Speaker 1: think the other thing is the social aspect. I think
Speaker 1: that there are people who would benefit from a robot
Speaker 1: that is able to give some form of social comfort.
Speaker 1: Let's say for the elderly who need to have some
Speaker 1: form of interaction. Um. You know, that could actually be
Speaker 1: a really valuable tool. And in fact, there's a lot
Speaker 1: of work that's going into robotics to help people like
Speaker 1: the elderly who may have real emotional and psychological problems, um,
Speaker 1: due to loneliness. Do you think that robots are the
Speaker 1: answer to that. I think that robots can help. I
Speaker 1: don't know, I would never go so far as to
Speaker 1: say answer, but couldn't you also make the argument that
Speaker 1: if you created robots that displaced human jobs and also
Speaker 1: simultaneously said, hey, this, this nursing home sector is about
Speaker 1: to explode because we've got a bunch of baby boomers,
Speaker 1: and ways the society of now decided that our elderly
Speaker 1: need human interaction more than we've more than we've carried
Speaker 1: it out before. So let's create this whole other industry.
Speaker 1: Or let's expand this industry of elderly caretakers and fill
Speaker 1: those jobs with people who have been displaced by worker robots.
Speaker 1: Wouldn't that be better? That might be, or you could again,
Speaker 1: looking at the way a lot of roboticists framed this,
Speaker 1: they say, all right, well, it is a reality that
Speaker 1: robots are taking over actual jobs. But the hope is
Speaker 1: that it also ends up creating new jobs that are
Speaker 1: better paying jobs, less dangerous jobs friendly, more old books friendly.
Speaker 1: But yeah, like um, the idea being that that it
Speaker 1: frees up people and encourages the pursuit of jobs and
Speaker 1: engineering in computer science. Now, we live in the real world,
Speaker 1: and we understand that it's a lot more complex than
Speaker 1: telling someone who's been working on a manufacturing line. Hey,
Speaker 1: I'm sorry your job's gone because there's a robot here.
Speaker 1: But guess what, we have an opening and engineering. So
Speaker 1: if you just go and pursue a four year degree
Speaker 1: and then some post graduate work, you'll be right back
Speaker 1: to work. That's that's obviously not uh something that's going
Speaker 1: to be easy, especially in the short term. But the
Speaker 1: long term hope is that more and more of these
Speaker 1: jobs that are are dangerous for people, are less desirable
Speaker 1: for people, will be taken up by robots, and then
Speaker 1: the will there will be the creation of better jobs
Speaker 1: that are higher up on the food chain. And I
Speaker 1: think that makes sense to me. It's just the once
Speaker 1: you enter the sociability, yeah, because without sociability, you there's
Speaker 1: no reason to create a humanoid robot. Everything else can
Speaker 1: look like a robot. Yeah. Um, so it's it's when
Speaker 1: you enter sociability that you lose me. Not only does
Speaker 1: it can it look like a robot, but we can
Speaker 1: still socialize with it even if it doesn't look like
Speaker 1: a human people. There. You know, there's the story Rumba
Speaker 1: owners named their rumba. Yeah, so you we we end
Speaker 1: up having these kind of emotional attachments and investments in
Speaker 1: things that don't look Not only do they not look human,
Speaker 1: they don't look like any other animal that we would
Speaker 1: interact with on a like owner or and pet or whatever.
Speaker 1: I mean, they they're They're just a robot. So I
Speaker 1: think at the end of the day, Josh, I think
Speaker 1: we're on the same page. We think humanoid robots are
Speaker 1: an interesting idea, but not necessarily the end goal. There's
Speaker 1: there's not a whole lot of of incentive to go
Speaker 1: after it for its own purposes. We can see the
Speaker 1: benefits of going after it in the sense of the
Speaker 1: developments that are made in that pursuit help us in
Speaker 1: other ways. And that wraps up this classic episode of
Speaker 1: tech Stuff. I hope you enjoyed it. If you have
Speaker 1: suggestions for topics I should cover in future episodes, please
Speaker 1: reach out to me on Twitter. The handle for the
Speaker 1: show is tech Stuff h SW and I'll tell to
Speaker 1: you again really soon. Text Stuff is an I Heart
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