SGU Episode 949: Difference between revisions
Hearmepurr (talk | contribs) (live from dragon con done) |
Hearmepurr (talk | contribs) (news items done) |
||
Line 401: | Line 401: | ||
== News Items == | == News Items == | ||
{{anchor|news#}} <!-- leave this news item anchor directly above the news item section that follows --> | {{anchor|news#}} <!-- leave this news item anchor directly above the news item section that follows --> | ||
Line 428: | Line 409: | ||
|publication = TS2 | |publication = TS2 | ||
}} | }} | ||
'''S:''' So we're going to power through some science news. We're going to start with Bob. | |||
'''B:''' Me? | |||
'''S:''' Yep. Telling us about, this is a follow on on our every now and then discussion of all that space junk that's up there in orbit. What are we going to do about it? | |||
'''B:''' Yeah, this was fascinating. Researchers have discovered a way to use batteries to help de-orbit satellites. Well, how does that work? First, though, what's the status of satellites in low Earth orbit? Currently, the latest numbers I have, we've got 22,000 objects that are being actively tracked by an agency called the Space Surveillance Network. I don't know much about them, but they're tracking 22,000 objects. But they also estimate that there's over 900,000 pieces greater than a centimeter in orbit around the Earth. That's a huge, 900,000. They're not doing anything. They're just like basically junk flying around at very, very fast velocities. And if you go less than a centimeter, it's in the millions. And remember, these are traveling at thousands of miles an hour. You do not want to be hit even by something really tiny. | |||
'''S:''' They're all bullets. | |||
'''B:''' They're basically bullets. So what's the big deal? Low Earth orbit's really big, right? Well, it's big, but this is a lot of objects. And there's always the fear of something that we've mentioned on the show, the {{w|Kessler syndrome}} or this Kessler effect, which is basically that at some point you're going to have a cascade of collisions that eventually becomes a situation where there's so much debris in orbit that you can't do anything in orbit. No satellites, no people are going, no astronauts, nothing. It's basically a dead zone for decades or centuries. That's the big fear. | |||
'''S:''' And interestingly, I was reading about that recently, and we were talking about this, that the Kessler cascade is not necessarily an event. It's just a mathematical probability that could play out over years or decades. In fact, it's possible it's happening right now, like we're at the beginning of this process. | |||
'''B:''' It's not only possible, I will say. I will say right now that it is happening. | |||
'''S:''' It is starting, yeah. | |||
'''B:''' And that's because I found this quote on the NASA site. NASA says, "Debris is now self-perpetuating in low Earth orbit due to the sheer number of objects." | |||
'''S:''' That's what it is. | |||
'''B:''' Worse than that, worse than that, debris in low Earth orbit are now projected to increase even without the addition of any new objects. So that means that the objects that are de-orbiting naturally is smaller compared to the collisions that are creating new pieces. So I would argue that the Kessler cascade has already started. The question now is, at this rate it would probably take years or many decades to get really bad. But the process has already started, and that's a really, really scary thing. | |||
'''J:''' How else can we screw the planet up, you know? | |||
'''B:''' Yeah, the surface, the ocean, the atmosphere, and then now, of course, low Earth orbit. | |||
'''J:''' This might actually be a good reason why we haven't been visited by aliens. They may come and they're like, no fucking way we go near that track. That's a test track! | |||
'''B:''' Those humans are a hot mess. | |||
'''J:''' All right, so how do we track them? | |||
'''B:''' There's been a lot of plans to deal with these satellites and how to de-orbit them. You put a thruster on satellites to de-orbit them, you have tethers. All are expensive, a lot of money, a lot of time. This new idea is called LIBDO. LIBDO stands for Lithium Ion Battery De-Orbiter. Now, how is that going to help de-orbit? All satellites have batteries, and most of those batteries are lithium ion batteries. Now, when you think of lithium ion batteries, in terms of danger, what do you think about? | |||
'''J:''' Fire. | |||
'''B:''' Fire, right? | |||
'''E:''' Explosion. | |||
'''B:''' And so some genius realized, well, maybe we can take this dangerous aspect of lithium ion batteries and turn it to our advantage. So they actually realized that if you start this thermal, this cascade leading to a thermal runaway on a lithium ion battery, it's actually a vacuum-capable solid rocket motor. It can actually be used. | |||
'''CH:''' Of course, I was going to guess that actually. | |||
'''B:''' So they did a test. They said, all right, let's take this battery, let's make it, let's start a thermal runaway. They measured it, and it created a force of 29 Newtons, a vacuum-equivalent force of 29 Newtons, which sounds, it's not a lot, but it might be enough. | |||
'''S:''' It's enough. | |||
'''B:''' It might actually be enough. And the great thing about this is that the batteries are already there. All you would need to do for all future satellites is to have a little nozzle. You add a little bit of a nozzle by the battery, and you need to be able to control the altitude of the satteliteso that when the battery goes off, you can control the orientation of the satellite so that it de-orbits. That's all you need. You're adding a miniscule amount of new weight. So when an astrophysicist or an engineer hears about, you don't really need to add any new weight to the satellite. They are very, very happy, because when you say to them, you've got to add 20 pounds, they're like, sorry, that's going to cost a million dollars, and it's going to take way too much time. So this is an amazing opportunity. And so here's an example of what you could achieve with this. If you've got a satellite that's 15, say 15 kilograms, it's in orbit, it takes 10 and a half years to de-orbit. It's life time. It's de-orbiting life time when all the work is done is 10 and a half years. If you use a battery like this, an optimized lithium ion battery, what you could do is you could do the explosion of the battery, the burn of the battery, and you could bring it from 500 kilometers to 400 kilometers. That would reduce its orbital decay time to, instead of 10 and a half years, 4.7 years, which is a 55% reduction. You're basically cutting the de-orbit time in half, which means that it's half the time that a cascade can start, where something could hit it and it could break up into a million pieces. So you're decreasing that time. I mean, it's not quickly de-orbiting, but if you're cutting the de-orbit time by half, that's great. That's a great start, and it's cheap. It won't cost hardly anything. So this is a great idea. I hope they really run away with this. | |||
'''S:''' But this is only for new satellites going up. They can't do this to existing satellites. | |||
'''B:''' Obviously. | |||
'''S:''' Yeah. So what are we going to do with existing satellites? | |||
'''B:''' We're screwed. | |||
'''E:''' Yeah, what's the solution. | |||
'''B:''' I mean, what are we going to do? It's going to cost money. It's going to be expensive. It's going to be time-consuming. But this is something, at least, that is all new. It should be a lot. All new satellites should have this set. | |||
'''S:''' It should be the standard. | |||
'''B:''' It's no panacea. | |||
'''J:''' But just like global warming, which is obviously on track to kill us, they wait too long and this gets more sloppy. | |||
'''S:''' It gets harder. | |||
'''J:''' We need to do it now. Right? Right now. | |||
'''S:''' We need to do it 20 years ago, but yeah, now it's better than later. So there are two companies that I'm aware of that are working on an alternate for satellites that are already up there. This is a really clunky way to do it, but they basically send this crab thing up another satellite to grab it and then de-orbit it. So this will only work for big satellites. This is not for the little nuts and bolts that are zipping around in orbit. It's going to be expensive and it's going to take time, but it's better than nothing. Every satellite we pull out of orbit is one fewer thing that could participate. Interestingly, the satellite that they were targeting for a test flight next year or in 2025 for this system, they were looking at it with a telescope, like it's already been hit by something and it's been broken up into multiple pieces. They still think they'll be able to grab it because it's kind of clustered together, but instead of being a solid object, it's now a pile of rubble. So ironically, it's already been hit by other debris. | |||
'''CH:''' And I've seen some of these things at the research proposal stage. You're seeing companies that are ready to go right now. What I see as a faculty member, they're soliciting ideas and NASA will put out proposals with very specific ideas of what to look for, and they were looking for things shortly after impact like what you're talking about, Steve. As part of the call for proposals, they showed this graphic of what it's like very shortly after a collision. And the idea was that if there's certain kinds of collisions, they will spread out if you let it go long enough. So if you get it intercepted early enough, everything will be still kind of in a cluster. And I was looking at it, I was like, oh, is this something that's doable? And I was looking at it, I was like, after five minutes, they were already many miles apart. I'm like, oh my goodness. It's like basically you have to intercept this thing from some other side of the planet and get there, seemingly in minutes, and I gave up on any possible ideas. It's just such a horrendous problem and it's going to be a tricky one. | |||
'''S:''' Any momentum that you're adding or subtracting is going to put it into a slightly different orbit. So it's going to just drift away and spread out. | |||
'''B:''' And don't forget, this whole crab idea where it's going to grab it and deorbit it, that's okay, but you're not going to be able to grab something and deorbit it and then go somewhere else and deorbit that and then go somewhere else. It's way too expensive in terms of fuel. | |||
'''S:''' You can't go to different orbits. | |||
'''B:''' You can't. | |||
'''S:''' It's like a one-shot deal. | |||
'''B:''' One-shot deal. So that's not a great solution. | |||
'''CH:''' Well, that cheered me up. | |||
'''S:''' Yeah. Well, this next news item will cheer you up there. | |||
=== Dark Stars <small>(58:10)</small> === | === Dark Stars <small>(58:10)</small> === | ||
Line 435: | Line 510: | ||
|publication = sa | |publication = sa | ||
}} | }} | ||
'''S:''' All right. So this is all theoretical, but it's super cool. Super cool. Has anyone here heard of dark stars? Dark stars, they're dark because they're made of dark matter, not because they're not light. In fact, they're extremely bright, theoretically, if they exist. In 2007, an astronomer named Elizabeth Freesc, F-R-E-E-S-C, I think that's Fries, she hypothesized that, hey in the very early universe, when there was clumps of dark matter, there were local regions of dense dark matter, it's possible that hydrogen and helium, because most of the universe, especially at the beginning, is all hydrogen and a little bit of helium, if, yeah, as that coalesced near a pocket of dark matter, the dark matter would have coalesced with it, and even 0.1% of dark matter in the mix would be enough, theoretically, to keep that hydrogen and helium into condensing into a star. And so it's possible, so we don't know what dark matter is. We're not 100% sure it exists. I think it probably does exist. So if it exists, but we don't know what it is, but if it is capable of annihilating itself, if two dark matter particles, if they collide with enough momentum, if that energy is enough for those particles to annihilate each other, then what will happen is those dark matter annihilations will release light and heat, and that heat would be enough to keep the hydrogen and helium from coalescing into a star. So you have basically a star fueled by dark matter annihilations rather than the fusion of hydrogen into helium and then into heavier elements. So what would this mean physically? What would be the physics of a dark star made of dark matter? So they would be capable of getting much more massive than a regular star, and they would be a lot bigger. So they could be as big as 10 AU in diameter, so that's 10 times the radius of the Earth. The biggest ones- | |||
'''E:''' The Earth's orbit. | |||
'''S:''' The Earth's orbit around the Sun, 10 times bigger than that. That's massive. And they could have millions of times more mass than our Sun, millions of solar masses, and billions of solar lumens, billions of times brighter than our Sun. | |||
'''J:''' So anything around it would get cooked. | |||
'''S:''' But it's cool, it's cool. It's not hot. | |||
'''J:''' What do you mean? It looks cool? | |||
'''S:''' Yes, it looks cool and it's temperature-wise cool relative to a star. | |||
'''B:''' I believe the surface temperature would be comparable to the Sun's. | |||
'''B:''' The surface temperature of the Sun's not that hot. There's no core temperature, there's no core where fusion's happening. | |||
'''J:''' So planets could be around it. | |||
'''S:''' They should be around it. Well, this would be in the early universe before there was any heavier elements. | |||
'''B:''' So no rocky worlds? | |||
'''S:''' Yeah, so no. | |||
'''J:''' So nobody played reruns of rocky over and over and over again? | |||
'''S:''' No, that's correct. These would be population 3-type stars, which ironically is not the first stars, it's the ones that are only hydrogen and helium. So anyway, this is her hypothesis. Maybe there are these dark matter stars that an individual star is as bright as a galaxy, because it's billions of times as bright as our Sun. So as bright as a galaxy, it's huge, it's massive, and it only existed in the very early universe. So if we're looking really far back in time towards the first few hundred million years of the universe, maybe we could see some of these dark matter stars. So enter the James Webb Space Telescope, JWST, which can look at these very, very distant, and then what you're seeing in the picture here, by the way, this is a galaxy field. Those are galaxies that you're looking at, and these are ancient galaxies. So what Freesc and colleagues did to follow up on her 2007 hypothesis was to pour through James Webb Space Telescope data and say, are there any of these ancient galaxies? So firstly, they picked out objects that were extremely redshifted. Redshifted means they're far away, they're old, they're early, early universe. They took those, they said, all right, which of these have the spectra? Spectra are the bright and dark lines when you analyze the light from an object. You can tell so much about the universe by looking at spectra. | |||
'''E:''' It's a fingerprint. | |||
'''S:''' Yeah, it's a fingerprint of all kinds of processes and elements and whatnot. So anyway, if you look at the spectra of these objects, they found four candidates that have the spectra that are consistent with the models of dark stars that she came up with in 2007. So basically, these four things, and there were three of them in particular, these three are, should be considered dark star candidates. It doesn't mean they're dark stars. We don't know that they are. | |||
'''B:''' But Steve, in my reading, it said that these stars, these candidate stars were, or objects, were very far away, which of course it would need to be. And secondly, they said it was more point-like and not fuzzy. | |||
'''S:''' Well, no, it's just that they couldn't tell the difference. It's not that they were more point-like. So if you're looking, the James Webb Space Telescope, because they're so far away, it's still just a point of light. They couldn't, so one way to tell the difference between a galaxy and a single object, as bright as a galaxy, is a galaxy would be fuzzy and a single object would be more of a point of light. They just couldn't tell the difference. So if they could, then that would confirm that it was not a galaxy. | |||
'''J:''' Well, we might need a better detection device. | |||
'''S:''' Yeah, but that's not going to happen. We're running out of time soon. The problem is we need a more detailed spectral analysis. So, because there are fingerprints of dark matter stars that we could absolutely see with a more higher resolution spectral analysis. And James Webb Space Telescope can do that. The problem is it would take months of observation in order to get that higher resolution. And they don't have the time on the James Webb Space Telescope. Because everybody wants time on the JWST, and this is one experiment. Like, hey, could we have access to this for several months and basically block every other experiment that people want to do so that we could answer this one question. Now, I don't know who makes these decisions or who gets time on the JWST, but let's say we were able to confirm that these were dark matter stars. How big a deal would that be? Like, is it worth time on the JWST? | |||
'''B:''' It is. Nobel price. | |||
'''S:''' So, well, it would be huge. And everyone acknowledges. They say, listen the data we have so far, there's other possible explanations for this. There are stars that have the same kind of spectra. Again, it's just consistent. You could make a model that's consistent with the spectra that we're seeing. So we really, they're not confirmed. But if they were, that would mean several things. One, it means dark matter 100% exists, right? I think right now it's like 99%. But there are people serious astronomers who have good arguments about, the modified utonian dynamics. | |||
'''B:''' Are they good? Are they really good? | |||
'''S:''' I mean to listen to them say it, yes. But the majority of the opinion is, no, there's dark matter. But this would end the debate. This is one of the ways in which the debate would just be over. If there are dark matter stars, there's dark matter. So it would 100% end that debate. Two, it would tell us something very critical about dark matter. Dark matter is capable of annihilating itself. Not all models of what dark matter could be necessarily have that feature. So it would narrow the list of possible candidates for dark matter itself and would help us know where to look in the universe for dark matter and figure that out. Also, the third thing is that it could be a possible explanation for supermassive black holes. So galaxies that formed early in the universe, most of them like our galaxy, have a supermassive black hole at the beginning, at the center of the galaxy, and these are black holes that are millions to billions of solar masses. Again, they're massive. And astronomers aren't exactly sure how they formed in the early universe. Like, why did so many black holes coalesce into a supermassive black hole? | |||
'''B:''' They're too big. They're too big to be explained by modern theory. How do they get that big? | |||
'''S:''' We don't really know. This could be one solution because, if you think about it, you have a billion solar mass, I'm sorry, you have a million solar mass, it's a billion times as bright, a million times as massive, a million solar mass, dark matter star, and you have that 0.1% dark matter making light and heat and keeping it puffed up. When that dark matter runs out, all that hydrogen and helium collapses and forms a black hole because it's already too massive to hold itself up as a star. It would immediately collapse into a black hole. That could be why we have a lot of supermassive black holes. So it would potentially solve that mystery as well. So there's a lot riding on this. I don't know what's going to happen going forward. Right now we just have these candidates. The whole idea is fascinating. It may be completely wrong, but that's how science works, right? You have to make these hypotheses and, more importantly, figure out ways to test them. And that's what Freesc and her colleagues are doing. This is the possibility. It fits the models. This is how we can test it. Until you answer that last question, this is how we can test it, you're just chatting in the breeze. | |||
'''J:''' So what's the cool part? | |||
'''S:''' Yeah. I'll play it back for you later. ''(laughter)'' All right. | |||
=== AI Drone Racing <small>(1:08:15)</small> === | === AI Drone Racing <small>(1:08:15)</small> === | ||
Line 442: | Line 575: | ||
|publication = Nature | |publication = Nature | ||
}} | }} | ||
'''S:''' Christian, do you do this work with the drones? | |||
'''CH:''' I do some drone work. I don't do this drone work. | |||
'''S:''' Tell us about this drone work. | |||
'''CH:''' So researchers at the University of Zurichat the Robotic and Perception Group as well as Intel Labs have suddenly announced that they have an autonomous drone racing system which has achieved champion-level performance. They can beat human champions at racing through drone gates. People can see the image of basically the drone trails going through little squares doing time trials with drone gates. And this is really cool. It was actually published in the journal Nature just on Wednesday. And to get a robotics finding in nature, to my understanding, robots aren't natural, they don't know where to take their standard. But the big finding, and this is for a number of reasons, but we'll get into that. So what did they have? So basically what they created was an autonomous system they call it SWIFT. I don't know if it's an acronym for anything so it's a very clever one in order to make this drone racing controller work. And basically there are two key components of what it needs to do. One, and this is often undervalued in robots, it needs to know where it is. We take for granted that we know where we are in a room at a given time, and it's developed all kinds of cool algorithms including the best acronym in all of robotics the simultaneous localization and mapping called SLAM. I'm jealous of that, and that's good. Of course it's SLAM it. So part one is you have to know where it is. So it uses what we call visual inertial odometry. Have we covered this on the show in the past? | |||
'''B:''' Oh, many times. | |||
'''CH:''' We all know what odometry is. It's the odometer in your car, right? And how do you know how far you've gone? It counts how many times the wheels have turned, right? Well, we don't have wheels with these drones but you have vision. So you can do visual odometry. We have a camera on board the drone and you see how much the image flows past you and that gives you an estimate of how far that you've gone. That's the visual part of the visual inertial odometry. The inertial part is also really cool. It has an inertial measurement unit on board and that has two components in it. One is a gyroscope. We've heard of a gyroscope before, right? It detects rotation. You get a good enough one you can detect the rotation of the earth. Take that flat earthers, right? We had one of those in the lab and proved them wrong. | |||
'''S:''' They proved themselves wrong with one of them. | |||
'''CH:''' That's amazing. Have you covered that documentary behind the curve? That's amazing stuff. It was the ether that got in the way. That was the problem. One part is the gyroscope that senses rotation. The other part is the accelerometer. Who here has an accelerometer on them now? Anybody? We probably do if you have a cell phone, right? It's the thing that determines if you're in portrait or landscape mode because it determines the acceleration of gravity and which way it is down. It also senses all kinds of accelerations. If you were in a car and you fell asleep and you suddenly felt the car come to a stop like you've been parked, that's kind of what an accelerometer does. If that's acceleration, you can integrate that up to position using calculus, then you can know where you are. If you combine these two things together, the visual and inertial, you can get some pretty good estimates of where you are. That's half of it. The other part is deep reinforcement learning. I'm sure this has been covered many times on the podcast. Once you know where you are, what do you do? What they did is they trained this drone and they would try a hundred different drone races at a time. Reinforcement learning, you give it what's called a reward signal. What's good and what's bad, right? That's the art of reinforcement learning. Part of it is saying, hey, what's good and what's bad? It has to be a pretty clearly defined task. You might think, well, how fast do you finish the race? Sometimes that's a little too broad and you have to give it something more specific. What they gave it was a reward was time between gate one and gate two, time between gate three and gate four, trying to make sure you get to the next gate as fast as possible. When you get there, you're looking at the next gate. That's the way that they told it. That's the reward. They ran this thing and I always ask people when they do deep reinforcement learning, how long does it take to run on the computer? It turns out less than an hour. Less than an hour they got this thing to actually learn a policy. There were some tricky parts we can get to in a minute when maybe it's a little discussion about this because the simulations aren't perfect and they lead to real problems. When they put this all together, the headline was they had it race in time trials against champion drone racers. Three world champion level drone racers. One was the Swiss champion, one was the world champion. I don't know how they take the rankings of this all. I'm not going to get involved in that world. The autonomous SWIFT system got the fastest overall time and was the most consistent of them. When they broke down the actual performance of the drone, the thing they found was that it was most consistent getting from gate to gate and made tighter turns. Overall, the consistency between gate to gate helped to get it faster overall time whereas the drone racers themselves the human racers were able to get some faster segments. They were able to speed up and slow down at different points in order to beat them out in a partial time. Overall, the drone system was the fastest. The claim here, according to them, is that the first time an autonomous robot achieved champion level performance in a real world competitive sport. I don't know what the chess people feel about that. I wonder what they feel. | |||
'''S:''' Or the Go people. | |||
'''CH:''' Or the Go people, right? That's the headline. There's lots of nuance to it too. It's really interesting how they achieve this stuff. | |||
'''S:''' There's a lot of obvious applications. We're talking about as a travel option drones with people in them. Not hitting stuff is probably a good thing. | |||
'''CH:''' I'm in favor of not hitting stuff. This is the part we do in our own lab. We do drone avoidance. We'll have a drone and we'll throw a pendulum at it at 10 meters a second and we'll have to dodge it out of the way. That's the kind of thing we'll do. One thing that's underrated the understated robotics thing that I point out is that all of this computation and sensing was on board the drone. And that is hard to do. It's much easier to have a desktop computer off the side. This is what we'll do in our lab a lot of the time when we're debugging stuff. It will turn through all the calculations and tell the drone what to do. Also, a lot of labs will use motion capture systems to tell you where the drone is. That's easier than using SLAM. I just want to say SLAM again. I just want to say it. They had Onboard Camera doing all the calculations but all the calculations were done on board. That's really impressive. Some caveats in the paper that are different is that we talk about this inertial sense that the drone has. People don't have that in the drone. The human pilots don't have an inertial sense. They don't feel the bank of the turn. That's an advantage that the drone has structurally over the person. There are sometimes structural advantages in these human robot performance games. It happens all the time. They also pointed out that the camera refresh was only 30 frames per second. I'm not a biologist. They said that the human eye performance is more like 120. Humans had an advantage there. They said there's a little bit here and a little bit there. Bottom line, this is really impressive with not only what they can do with the drone but what they can shrink onto a tiny drone, computer and camera because they can't carry very much. | |||
'''J:''' You think if they can do that then what's up with autonomous cars? | |||
'''CH:''' When I saw this I was thinking about this, Jay. It's actually a great question. There were no other drones on them. They're not racing in and out with other drones. You don't have to worry about colliding. | |||
'''S:''' It's actually easier. | |||
'''CH:''' That's a big one, right? | |||
'''S:''' No pedestrians. | |||
'''CH:''' Some of those videos, man. Those can be pretty scary. There's nothing else on the course there. That's a next level thing that you don't want to do. What this really shows is that you can get a big enough neural network with enough data and it turns out a reasonable amount of data to do all kinds of stuff. We see this in robotics all the time. The neural network approaches can do really awesome stuff. The question is how reliable is it going to be? It's a race so you want to count your best time. You don't want to count your worst time. | |||
'''S:''' Getting back to my question at the beginning of the show, pretty soon. | |||
'''CH:''' What time is it? | |||
=== Settling Mars <small>(1:16:59)</small> === | === Settling Mars <small>(1:16:59)</small> === | ||
Line 449: | Line 622: | ||
|publication = ls | |publication = ls | ||
}} | }} | ||
'''S:''' Jay, we can't talk about everything to do with Mars, but tell us about if we're going to settle Mars, how many people do we have to put there? | |||
'''J:''' It's super complicated. Every study that's come out so far I think the consensus is maybe, you know what I mean? Because we know right now there's so many things that are dangerous and new about doing something like settling Mars. There's thousands and thousands of different technologies that need to be developed that don't exist today and they're working on it. We need to figure out every single thing that can go wrong before we start doing this. There's two studies that I read about. I'm going to focus on one of them but I'll give you a little bit of a comparison between the two. The first study is, and I'll tell you right out of the gate, they said 22 people. Think about that as we're going through this which I think personally is way too low sustained. | |||
'''S:''' Self-sustaining. | |||
'''J:''' Not really self-sustaining. Even in this one they were saying 22 they need some resources from Earth but even still it's a super low number, I don't see how it works. They asked a few questions. This is coming from the George Mason University Fairfax, Virginia. They wanted to know what conditions are needed to maintain a stable outpost on Mars. They wanted to know what combination of personality types would do best in this hostile environment and then they wanted to know how many resources are needed to get resupplies and assuming occasional accidents. They were saying that it takes about two years to get resupply from Earth which is a big deal because if you need something and you tell them hey we need it, they're like, okay, in two years you'll have it. That's no bueno. | |||
'''B:''' Can't they just call Amazon and get it? | |||
'''J:''' With the drone thing, you never know. | |||
'''CH:''' Amazon is probably working on it to be honest. | |||
'''J:''' I'm going to focus about their unique angle which was they were talking about personality types which I have not seen in any of the other studies that are done. They were saying at its core that people have to cooperate for there to be a successful ability to maintain a settlement. That seems really obvious but the scientists need to think about stuff like this because they're picking people that can handle stress and are really smart and are capable of doing different tasks and all that but of course you don't want to put narcisits up there, becasue they're going to have big problems. They're taking that into account in this study that they did. What they did was they created a computer model, they used several computer simulations to project out a 28-year span of people living on the planet just to see what would happen after the 28 years. Their approach that they had is they used something called agent-based modeling to really squelch it down. What it means in this case is that they are doing human interaction along with all the other things but this particular model includes human interaction. One thing that they said was that their model has to be pre-constructed before people arrived which again, that's a big deal because if we're going to pre-construct it then we have to have the technology to pre-construct it which means robots which is a big difference from the other study that I'll talk about in a minute. They also said that there has to be stores already in place of food, air, and water that all need to be created in situ on Mars. That's another huge thing, right? If you're going to say, yeah, we have to have food, water, and air already being created successfully to sustain well, how are you going to do that? Where's all the technology which we don't have today in order to pull that off? Another thing that they said was they were also saying that they would have constant power for seven years which is nice because solar panels don't work so great on Mars for lots of different reasons so they would have to use a nuclear generator. So getting into basically the personality types. I know most of you know studying people's personality types and taking tests all the different ones that are out there that's all nonsense and everything but they basically created four different groups. They said there's people who are agreeable, people who are sociable, people who are reactive and people who are neurotic. ''(laughter)'' | |||
'''S:''' That's an accepted personality profile. It's the {{w|Big Five personality traits|OCEAN}}. | |||
'''J:''' Yeah, I agree. | |||
'''S:''' So that's legit. | |||
'''J:''' It is legit to say we have these four basic personality types of course there's infinite shades of grey but let's put that aside for a second. So guess what personality type worked the best. | |||
'''B:''' People who have been on Survivor? | |||
'''S:''' Survivor of Mars. | |||
'''J:''' So between agreeable, sociable, reactive and neurotic, the agreeable people by far when they tested it. What they basically did was they started with tests at an equal amount of each and then they brought it through the simulation and they said well what happened, what went wrong who caused the problem and then whichever way success leaned they increased the number of those types of people and they kept doing it and kept doing it and then they basically said everybody's gotta be agreeable for this to work so we can't have any narcissists running around on Mars. They said, just to give you a definition of what agreeable means to them they said individuals with the lowest degree of competitiveness, low aggressiveness and not fixated on stringent routine. Which is interesting isn't it? | |||
'''S:''' Yeah, that's interesting because those are features that might be beneficial trying to run a settlement on Mars. Like you know, you're saying neurotic as if it's a bad thing but you know, being a little neurotic like worrying about things that can go wrong, obsessively checking stuff, you know? | |||
'''J:''' I took it as flexibility. You might be doing something different today than you did yesterday. | |||
'''S:''' Flexibility is good but there's gonna be a ton of routine if you're gonna be keeping the machines running up there. | |||
'''J:''' Well how about this, tons of routine, tons of routine for like 8 months you're doing the same thing holy shit but today you gotta do this and you gotta be okay with that. I mean I think that works. | |||
'''S:''' I would think intuitively I would say balanced would be better. | |||
'''J:''' Like I said, so over the many simulations they ran they had a varying degree of results from 170 people and they were able to get it down in their model to 22 people by using the people who were considered to be agreeable. So I'm gonna quote them the research team said "This demonstrates that team and individual psychological success in extreme environments can be broadly attributed to coping capacity which we define as the ability of people, organizations and systems using available skills and resources to manage adverse conditions, risks and disasters". This study is not peer reviewed yet. Now another study, very quickly another study who took a very mathematical approach to the whole thing and it wasn't just focused on Mars they were basically saying like what would it take to settle basically anything that's a hostile environment. And they came up with 110 people. So the big question here is why is there such a huge numbers difference. And again the minutia of the details of each study and what factors they took into account for and everything I'm sure are the major swing. I just ran out of the gate and I'm no expert, I know that but 22 just does not seem like it's enough to really pull it off. | |||
'''S:''' It sounds like they were looking at it mainly from the social perspective but it all depends on what you build into the model. First of all how many surgeons do you want up there and what if one of those surgeons dies, how many backups do you want? How much redundancy you're building in is a completely separate factor than what they were considering. Agreeable people will maybe help the society function better but if you don't have the other personality types does that have a negative thing to it they're not considering. You're not going to have the person who's going to check the fail safe or something obsessively or whatever. It's like an impossible to model thing. You're always just coming up with a construct and saying well if these are the factors that we take into consideration this is the output. And that's an interesting thing to answer, that's interesting information but it's not really simulating what would happen on Mars. | |||
'''J:''' Yeah and I think the real world studies you know that there are real people right now who are living in a Mars situation. | |||
'''S:''' Yes, yeah, but there's what? Six people with a four-six, something like that. It's very few. | |||
'''J:''' I mean, I think the data coming out of there is probably going to be much, much more accurate and useful than something else. | |||
'''S:''' That's why you got to do that. So, and I think that we would need to actually do a much bigger simulation. Put people in a self-contained environment for a year and see what happens. | |||
'''CH:''' I mean, all models are wrong, but some are useful. That's what it comes down to. I mean, and there are things you can do in a model. You can't do it in an experiment. You have to target the experiment appropriately. So that way you're validating the right thing or finding the new variables that you need. I mean, it is complicated. I mean, I kind of love these age-based models. I always view them like they're the sims anyway. So it's like, so it's pretty fun. | |||
'''S:''' It would be a fun sim game, like settlement Mars. And you have to decide all these variables and it affects what happens. | |||
'''J:''' Well, one day I thought about after reading all this was like the dynamic between people, like if you happen to like another person that's there and you want to get into a relationship, you're still living your life. You're working and you're on Mars, but you know, you still want to have relationships and stuff. And if there's any kind of, like there's a lot of options, it's like, oh, this person doesn't like me and then there's nobody else, you know. | |||
'''S:''' Well, do you send up pre-existing stable couples? Like that's a big decision. | |||
'''J:''' Yeah, that's a great question. | |||
'''B:''' My takeaway, though, is that I don't care about all this people stuff. I might take away, is like, wait, you got to send, we got to send all these robots to Mars to prep it for us? I mean, how long is that going to take before we can get anywhere near that level of sophistication? | |||
'''CH:''' I mean, again, what time is it? No, but it's, I mean, it's, they have to be more adaptable on the fly, is what it's going to come down to. | |||
'''B:''' My takeaway is that we are all going to be dead before any humans are on Mars. This is like, we're not going to see this. It says, way too complicated. I'm so disappointed in the press. That's all, my God. | |||
'''E:''' It doesn't happen in Bob's lifetime. | |||
'''J:''' Many experts are saying, like, within 30 years, we will have boots on the ground. | |||
'''B:''' Yeah, I'll be dead. | |||
'''S:''' That's different than self-sustaining settlement though. Oh, yeah, yeah, yeah, yeah. We will be dead, not all people, yeah. | |||
'''B:''' No, everyone in this room. Yeah, most of us will be dead. | |||
'''J:''' Let you blow your mind. Elon Musk actually said that, like, 2050, which has roughly 25 years from now, there'll be a million people living on Mars. ''(laughter)'' | |||
'''B:''' God. | |||
'''J:''' I'll be like, you've got to be kidding me. You've got to be kidding me. Send me $300,000 because of how stupid that is. | |||
'''S:''' All right. | |||
=== Stress Patches <small>(1:27:32)</small> === | === Stress Patches <small>(1:27:32)</small> === | ||
Line 456: | Line 715: | ||
|publication = Yahoo Life | |publication = Yahoo Life | ||
}} | }} | ||
'''S:''' Evan, what is Meghan Markle wearing on her wrist there? | |||
'''E:''' I want to know how many people know who Meghan Markle is. Raise your hand. Yeah, it's a lot. It's about 70% of the audience. 30% of you are very good and very proud of you. So anything when cost playing Meghan Markle here today, I got no one, no one, no one. OK, well, if you are, you see anyone out there. Their cost play is likely incomplete, because located on her left wrist is a little circular sticker. OK, you have to have that if you're cost playing Meghan Markle specifically. That is called a NUCALM. That's N-U-C-A-L-M, NUCALM, biosignal processing disc, also known as an anti-stress patch. So this was first picked up in an article recently by Vogue.com and the media jumped all over it after that. So what exactly is a biosignal processing disc? How does it work? Well, time for some science, right? According to its inventor, Dr. Blake Holloway, the patched lens of neuroscience, steved pay attention. Neuroscience and biochemistry to help regulate patients with post-traumatic stress disorder, right? | |||
'''S:''' Oh, they mentioned an actual disease by name? | |||
'''E:''' That's it. Yeah, according to the inventor, the disc enhances frequencies that relax the wearer. | |||
'''B:''' Frequencies. | |||
'''E:''' Yep. Right from the website, let me read this. This is hard science, folks. Pay attention. Traditional Chinese medicine. | |||
'''J:''' Stop right there. ''(laughter)'' Just stop. | |||
'''E:''' TCM explains that she flows through the body along particular pathways or meridians to maintain health. Everything in the world is we know it vibrates with a particular pattern. Science. ''(laughter)'' Thus living systems produce electromagnetic frequencies androgynously that differ depending on the level of health or disease direction their website, by the way. | |||
'''J:''' Wait, wait. What was that word you used? And they said androgynously? | |||
'''E:'' I'm sorry, I'm a typo here. Endogenously. | |||
'''J:''' All right, good. ''(laughter)'' Because I was like, they are going into areas now that I can't even comprehend. ''(laughter)'' | |||
'''E:''' It is hypothesized that if you restore the frequencies, the travel through the meridians, you can re-instate optimal physiology. These new condisks hold the EM frequency patterns of GABA, G-A-B-A, Steve. | |||
'''S:''' It's a neurotransmitter. | |||
'''E:''' And it's precursors to deliver a pure biological signal to your body. When placed on the inside on your left wrist, Megan Markle, at your pericardium six acupuncture point. The disc sens a signal to the pericardium of your heart to activate local parasymphatetic nerve fibers which then transmits the signal to your brain telling it to increase vagal nerve output and begin the process of slowing down the body. The disc stops your acute stress response. So the brain wave entrainment with new comm is always reliable and efficient in getting you into theta brain wave range, which—we're at right range—where restoration and relaxation can take place. | |||
'''S:''' Evan, that's like the trifecta of pseudoscience. It'a all there. | |||
'''J:''' Yeah, I mean, that is the officially the biggest load of bullshit I've ever heard in my life. In that sentence, what the f**k did we just do hear? ''(applause)'' I need you to take a goddamn bleach shower after hearing it, right? ''(laughter)'' | |||
'''E:''' I mean, you have to have some kind of advanced degree in order to be able to have the talent to coalesce so much junk into one gobbledy book paragraph. | |||
'''CH:''' So, but the thing is, they mentioned Z's at the beginning of this, is that what you said? | |||
'''S:''' Well, he mentioned PTSD, you're not supposed to like name specificity. | |||
'''CH:''' That's gonna say because now the realm of structure function claim, right? Under a regular term. | |||
'''S:''' They say relief stress or promotes a well-being, whatever, at least in the U.S. you can get away with that. But if once you say treats a disease, that's a no-no. | |||
'''B:''' But they're misinterpreting. I mean, that sticker, I mean, to me, it looks like she's got an active Wi-Fi signal. Maybe that's all that is. | |||
'''J:''' Did you find out how much it is? | |||
'''E:''' You have to buy from packs of $20, $80 for a pack of 24. | |||
'''S:''' For a little sticker. | |||
'''J:''' And how do you know where it runs out? | |||
'''E:''' It lasts up to four hours per sticker. Of course. You've got to be putting these- | |||
'''S:''' The frequencies wear out. | |||
'''CH:''' But you can recharge them. You can recharge them up. | |||
'''E:''' But you can buy packs. | |||
'''S:''' You hold the crystal next to them and it charges them up. ''(laughter)'' | |||
'''J:''' I imagine you walk into the place for the people that do it and you walk in and they're just always laughing.holy shit, we're making money. | |||
'''S:''' All right. You have to move on. | |||
'''E:''' Okay. | |||
'''S:''' Just enough time to find the picture. | |||
{{top}}{{anchor|sof}} | {{top}}{{anchor|sof}} | ||
{{anchor|theme}} <!-- leave anchor(s) directly above the corresponding section that follows --> | {{anchor|theme}} <!-- leave anchor(s) directly above the corresponding section that follows --> | ||
== Science or Fiction <small>(1:32:39)</small> == | == Science or Fiction <small>(1:32:39)</small> == | ||
<!-- | <!-- |
Revision as of 21:07, 26 October 2023
![]() |
This episode is in the middle of being transcribed by Hearmepurr (talk) as of 2023-10-25, 16:45 GMT. To help avoid duplication, please do not transcribe this episode while this message is displayed. |
![]() |
This episode needs: transcription, formatting, links, 'Today I Learned' list, categories, segment redirects. Please help out by contributing! |
How to Contribute |
You can use this outline to help structure the transcription. Click "Edit" above to begin.
SGU Episode 949 |
---|
September 16th 2023 |
Sci-fi futuristic robot |
Skeptical Rogues |
S: Steven Novella |
B: Bob Novella |
J: Jay Novella |
E: Evan Bernstein |
Guest |
CH: Christian Hubicki, |
Quote of the Week |
Individual science fiction stories may seem as trivial as ever to the blinder critics and philosophers of today – but the core of science fiction, its essence has become crucial to our salvation if we are to be saved at all. |
Isaac Asimov, American writer |
Links |
Download Podcast |
Show Notes |
Forum Discussion |
Introduction, Guest Rogue
Voice-over: You're listening to the Skeptics' Guide to the Universe, your escape to reality.
S: Hello and welcome to the Skeptics' Guide to the Universe. Today is Wednesday, September 13th, 2023, and this is your host, Steven Novella. Joining me this week are Bob Novella...
B: Hey, everybody!
S: Jay Novella...
J: Hey guys.
S: Evan Bernstein...
E: Hello, everyone.
S: And we have a special guest, Christian Hubecky. Christian, welcome to the SGU.
CH: Thank you so much for having me. It's great to be here.
S: This is actually in podcast time. This is your third time doing a show with them, although this is your first actual presence on the show. So this week's episode is mainly going to be a one-hour live show that we recorded with you as a guest at DragonCon. They only gave us an hour, and we figured we need more than that for a full show. So you agreed to give a virtual interview with us after the facts. Now it's like a week after DragonCon. This is the week that the show is going to come out. We're just going to have a little preamble discussion before we go to the live DragonCon show. For those who don't know, you'll hear again in a bit, but Christian, you are an alum of the Survivor TV show.
CH: That's right. That's right.
S: Yep. We talk a little bit about that on the show. And you are a professor of robotics at the Florida State University as well.
CH: That's right. That's right. And I got to say, as a professor, I'm not used to being cut off after an hour. The students stay until I'm done.
S: That's right. You leave when I say you leave.
CH: That's right.
J: It was fun. So when we got together with Christian at DragonCon, we had never met in person before. We emailed each other a few years ago, I think. But we had really good discussions over a couple of meals during DragonCon.
B: Oh, yeah.
J: Because we're all super into it. Of course, we're all super fans of robotics, and we like artificial intelligence, and we're really getting into it. I'm like, damn, these conversations were really good. We should have recorded them because we asked a lot of wacky questions, too. Because we'll ask anything when we're at dinner, we're like, so what are sex robots going to be like?
CH: That was not recorded, thankfully, for my tenure back, and I'm glad for that. But otherwise, it was fantastic. No, that was good stuff.
J: Christian's like, I've got 15 of them. They're awesome.
B: And don't forget, guys, guys, don't forget, Liz and Courtney, they watch Survivor every season. And they were very, they were very psyched.
S: Yeah, they were big fans.
CH: But I'd say what relevant to discuss that speaking of sex robots, Jay, then it was something that came up in casting interviews when you're interviewed before you go on the show. And so I was prepared that I was to be interviewed by like a Hollywood casting person. I tried to prepare myself. What are the stereotypical questions that people are going to ask you? And one of them, of course, would be about sex robots. So I had some pre-canned jokes. So I, of course, had, I didn't study sex robots in robot school. That was one of them that deployed.
S: It wasn't a course.
CH: No, I didn't know. It was capped out. I couldn't get in. But yeah, I would, though, recommend the reality casting process to anyone trying to go on a job interview, because there's probably no harder job interview than whatever curveballs they try to throw you in order to see how you'll react on a reality show. So highly recommended for at least the experience.
Dragon Con reflections (3:25)
S: This is our first time back to DragonCon since the before time, right? The pre-pandemic. What did you guys think about it? Did you guys have a good time?
J: Well, I made an observation and I talked to several people at DragonCon. I did notice that the overall quality of the costuming was not at the level that it's always been at for all the DragonCons we've been to.
S: There were some standouts, but it was a little underwhelming this year.
J: And I thought about it and I talked to some people at DragonCon who made similar observations and they were saying that they noticed that this happened post-pandemic. This is a post-pandemic thing that's happening at DragonCon. And we were surmising it's probably because people are financially strapped and they don't have like the five grand it probably takes them to build some of these costumes, some of the more outrageous ones.
E: Or invest the one thousand hours it takes over the year to build the costume you're going to make.
S: I know for us, because we had some really good costume ideas percolating and we back burned them all. And then even though we went this year, we decided late and so you didn't have as much time to invest in it because it was up in the air. You didn't know what was going to be going on with the pandemic and everything. But it's bouncing back. The numbers haven't completely bounced back yet to pre-pandemic levels.
B: Christian, this was your first DragonCon. What's your take on it?
CH: Indeed it was. I'll tell you, I was overwhelmed. I actually showed up on Thursday because I was giving a talk at Morehouse College in Atlanta just for general robotics purposes. So I jumped over to the conference just to get my badge and everything. I was just swept away by just the wild amount of costumes. I had no baseline and I got to see the big Zelda Korok protest, the Korok rights protest, which is probably the best thing I've ever seen. So I got to say, I enjoyed it. And I guess I was also taking in the fact that I had to give two full hour long talks. So I think I was overwhelmed by that as well. But I had a great time. I know me and Emily had a wonderful time hanging out with you guys and also just running around the conference scene and what happened.
S: Yeah, I agree. I think a lot of the best costumes I saw this year were ones I've seen in previous years. And so they don't have the same impact. It's like, oh yeah, there's the guy from Lord of the Rings, yep, saw him. For you, it's the first time. It's like, oh my god, that's amazing.
CH: Yeah, there was a Mark Hamill, which I double take that was really close to a Mark Hamill. That was crazy.
E: I remember, yes. Last Jedi, Mark Hamill.
S: I saw him and it's a double take. Wait, is that really him? No, no, it's not him. But for a half a second, you think it's him. There are some people, there's a couple of people who lean into the fact that they look like a celebrity and then dress like them. There's also every year there's an older Scotty from Star Trek walking around, like the movie version of Scotty who's a dead ringer. Yeah, but that, the Mark Hamill.
B: Yeah, it was a double take for sure too. Christian, what about you? Did you see any stars, any celebrities?
CH: Honestly, I didn't. I missed the whole celebrity thing. The only times that I've met a real superstar celebrity, I remember almost nothing from the interaction. They could have been speaking the Charlie Brown adult voice as far as I was concerned. I just remember the experience that I was in their presence. I said things. Hopefully they weren't overly embarrassing and then they kicked me out of their house and we're done.
E: They slammed the door on me.
J: There is something about it. There is really something about charisma and that type of human interaction. When you're meeting someone that's famous, because we've met lots of famous people throughout the years and you realize everybody's just people, right? They're all people. But every once in a while, when I met Prince, I had the opportunity to meet Prince. And my God, wow. That was not a normal meeting of a famous person where you're like, oh cool, I'm seeing this famous person. That guy had charisma that was palpable. And it was surreal. Plus, he's so incredibly famous. When I met him, he was unbelievably famous. So it was just very strange. So it is a pretty interesting experience. There is something mammalian about it. It's hardwired into us.
Steve on the UFO panel (7:43)
S: Yeah, I was busy doing a bunch of panels. The most surprising panel to me was the UFO panel.
J: Yeah, I saw that. Bob and I saw that. Well, Christian and I were there too. Yeah, we saw that.
E: You were finally convinced, Steve, right?
S: Well, no, it's just that I saw all the panels I was going to be on. Really, UFOs? Isn't this like, didn't we beat this dead horse already? But it was one of the most popular panels that I did. It's very hard to predict what people are going to want.
J: It's because of how in the news it's been.
S: I know. And even among skeptics, there is something a little bit different, I think, about this, what's happening now with the UFOs. And I think because the UFO community has managed to really snooker the government into lending them credibility, that people are like, whoa, whoa, this is before Congress and this is the Pentagon. Something's got to be going on. Even though it's the same crap as we've been seeing over the last 30, 40 years.
E: They've got NASA tied into it too, Steve. Talk about legitimacy.
S: After the panel, the next day, somebody recognizes me on the street and wanted to talk to me about the panel. Meanwhile, I'm late for another panel that I'm going to.
CH: You have like six panels, Steve. It's ridiculous.
S: Well, it was always the whole, yeah, but did you see this video? You know that? So listen, I'm late for a panel, email it to me and I'll take a look at it. I gave them the info at email and I never got it. I don't know if I remember or whatever. But the one thing that really, I mean, I knew this, but like it was really central to the discussion was the fact that, because we are always trying to talk about like how silly the conspiracy theories are, et cetera. But one of the problems that we have is that the government does hide things and especially surrounding the UFO phenomenon. Like for example, there's a lot of UFO sightings around military bases. And it's we know from now historical records that a lot of them were, oh yeah, that was the, they were testing the spy plane whatever. Of course, the government's not going to come out and say explain the UFO sightings as secret military testing. And so there is a layer of secrecy that's built into the whole thing, you know what I mean? And so it makes our task very difficult because we have to say, yeah, the government is not telling you the whole story, but not in the way that you think. And that's a challenging sell, you know?
B: And they're happy to let the whole UFO phenomenon take take control.
S: Yeah, it's good cover.
E: Yeah, oh absolutely.
B: It's great cover.
E: That's the margin in which they exist almost entirely, frankly.
S: And also like, yeah, there, there, like, there is a deep state, you know what I mean? Like, of course there is. There's a bureaucracy. There are people, there are career people who like, they work for the government from administration to administration. And the oversight of these entities is complicated and imperfect, but that's still different than we've been breaking the law for 50 years, right? I mean, it's like an order of magnitude different than what the UFO people are claiming, but it's not a clean narrative on our side either, because it's like, yeah, there is that kind of stuff going on. It's just not at the level that you're claiming.
CH: n a way that makes it more of an important skeptical lesson that just because there's not a cleanliness of narrative, it still doesn't change the underlying state of the evidence and what you can support with the evidence, what you can believe. What bothers me slightly about the current phenomenon, and I actually got contacted through my work email.
B: By an alien?
E: First contact.
CH: We're not supposed to talk about that, Bob. It was a survey intended toward academics and it was, it is seeming to probe attitudes of academics toward UAP research and yes, it said UAP, not UFO, and I was like, okay, this is starting to send off my antenna a little bit, my little alien antenna, as to what's going on. So I took the survey and what it did is it presented me with a bunch of academic articles about UFOs and asked if this changed my opinion of the literature. My answer was no. You're not going to hand me three studies and expect me to change my opinion on this overall phenomenon, and I kind of might have left some flaming comments at the end of that survey. After it was done, I was like, wait, why didn't I save what those articles were? I went and found some of the articles and some were published by the editor-in-chief of the journal that they were published in, which is not necessarily a bad thing, but it's just like, this is like your gold standard of evidence, and it was like in a journal that had nothing to do nominally with aerodynamics, it was like in a journal on entropy, and I was like, okay, how much is this being pushed into the academic sphere? It's hard to tell. That's one thing that I would worry about is if enough academics get snookered, it becomes a little subfield. Now, I think like all of them, they'd probably eventually deflate over time like a flan in a cupboard, but that is one thing I thought was interesting. Then he mentioned NASA. I remember I saw a talk by the current NASA administrator, and in the talk he was giving to kids, he was talking about one of the big reasons NASA should go out into the space is so that we can meet aliens out there instead of down here, where we're seeing all these alien contacts, all these alien contacts, and it's the same talking point, Steve, where these airplanes are locking on with radar and getting a range and confirming, we know these things are happening, and then they're going off at an impossible speed, the same old same old, but I was like, wow, so this is high level, again, these are administrator-level people at NASA, not necessarily the rank-and-file scientists, but that's the thing I worry about, that basically, it's the next generation of, wow, there's really something to this UFO thing.
S: Yeah. Meanwhile, it's a giant nothing burger. I mean, literally, when you dig down.
B: There's not even any ketchup on it.
S: This is the same stories they've been shopping around for 30, 40 years, sometimes literally the same ones, and the quality of evidence is abysmal, and it's more blurry photos or dots of light or things that are indistinct.
B: And the fact that we keep going back to it, the fact that with the proliferation of high-quality cameras in everybody's hands, we're still not seeing those videos, those good videos, and there's no reason why you wouldn't have four or five different videos of the same event from different perspectives, which definitely lead credence to it, right? If you saw five videos, each from a subtly different angle, like, whoa, that would take some work to fake. The thing about-
B: Not one. I've never seen them come across anything like it.
S: As cameras and videos have become more common, we're seeing more blurry photos, but we're not seeing better quality data. We're not seeing, oh my god, that's really something. That's not a plane. You know what I mean? We're not seeing that. The other thing is-
B: They live in the blur.
S: The evidence is the blur. If you think about the government, and just one point that I think is important to emphasize is, remember what they're alleging? They're covering up the biggest story in human history of all time without even anything close to this story, and they've been doing it for decades, and it's an international conspiracy, and yet they've managed to keep any smoking gun from getting to the press. No way. That's impossible. Think about the Vietnam War. How long was it before the Pentagon Papers were released? Information like that where no one's denying that they're real, no one denied that the Pentagon Papers were legitimate. They were verified. They were released to the freaking New York Times. You know what I mean? Why isn't there a Pentagon Papers of the UFO movement, and no of the MJ-12 documents are not real, those that have been completely debunked? You know what I mean? There's the alien autopsy video, and that turns out to be crap. It always craps out.
CH: It's interesting you bring this up, Steve, because you're talking about the extreme end of the massive conspiracy, where you have the whole government in it. I remember in the past you've covered actual academic studies people have done on the numerics of how likely a conspiracy is to fall apart when it's so big. It's kind of funny, like on Survivor, I got to experience the extreme opposite of that. For those who don't know, the format of the show is Survivor. Basically you vote each other off the island. Basically, if you're going to get voted off, there's a tiny conspiracy that's launched against you that you have to uncover in order for you to find out, oh, they're coming for me. I've got to make sure that it's not me. It's only a handful of people. The conspiracy may last a few days or perhaps a few hours or even minutes. Literally, it was five people who got together in a conversation around camp when you weren't there and said, hey, let's vote out that person. Even there, there were times where we were going to make sure that we don't hatch the plan a few hours too early, because what's going to happen? It's going to leak. It was interesting, kind of from a skeptical perspective, to want to have to try to ferret out real conspiracies on a short timeline. It was also the other end of the spectrum of the massive, now to the tiny conspiracy, which was highly plausible.
S: Absolutely. There are conspiracies all the time. We don't deny that. People get confused. You don't think there are conspiracies?
CH: Of course.
S: No. We're talking about grand conspiracies. It's all about the size and the duration. How many people would have to be involved across how many institutions for how long? It just gets exponentially more difficult to maintain a conspiracy the larger and longer you have to maintain it. And again, the academics have showed this mathematically, that these things just implode at some point. There's just no way the biggest story in human history has been covered up for 50 years without one good photo getting out, especially now that everyone has access to digital information. Somebody would like the Snowden thing. He blew up that conspiracy pretty quickly. There's no way that they would be able to keep this under wraps for this long.
CH: And not to labor this issue for too long with you guys, but the one thing I noticed as a person who doesn't deal with this day in and day out like you all do, when I sort of checked in on this whole UAP thing, that's when I found Mick West. I know you know Mick West.
E: Oh, sure.
S: Yeah, we interviewed him.
CH: He would take some of the famous recent videos such as the Gimbal UFO and just break it down in such phenomenal detail to the point where it's just like, oh, what else could it be other than this? And you can't always do that, of course. Sometimes you're in that low information zone. You just have no information to know what it could be. But sometimes just seeing such a calm and academic breakdown of a thing without any sort of bombast is, at least to me, so convincing. Maybe not everybody, but to me who was catching up on this, I thought it was incredibly compelling.
S: His videos are very compelling and he basically deconstructs the narrative, right? Because he demonstrates like, no, these pilots actually did get their angle of attack wrong. They got the geometry wrong and he proves it. He really demonstrates how they got it wrong. So the appeal to the expertise of the military pilots is flawed. They make the same kind of mistakes everybody make. They make errors of thinking, errors of perception, etc.
Special Report: The Future of Robots (19:43)
S: All right, before we go to the live show, Christian, I did want to chat with you a little bit about robots. Again, we're going to be talking a little bit about them during the live show, but we didn't really talk about the future of robotics. And I'm interested in what you think about that. How quickly are we heading to any kind of real game change in terms of robots in our lives? Is there anything that you think like, yeah, this is going to be the next big thing?
E: The Roomba 2.
S: A slightly better Roomba.
CH: I would accept a better Roomba 1 at this point. As an academic in this space, I had the luxury of not having to hype up a product I'm selling. I can sort of look at the state of where robotics is right now. I'm generally impressed with the rapid progress of what people can do with robots in a particular setting, such as you can get a drone to race really fast. You can get robots to actually run really fast now. But the question isn't about what can you get them to do one time for a camera. What can you get them to reliably do in our lives? This is something that we see a bit in the AI, the current "AI revolution" is that we are getting some of these tools that are really impressive what they can do sometimes. Auto-correct and voice recognition, they've been working on this for a long time and now they're really good. But I wouldn't trust my life on it. I wouldn't want this thing, if it gets the word wrong, my life is over. Wheras if you have a robot that's up in your grill and it falls on you, that could really hurt you. You have to be really reliable if you want it to get up in your space. The classic example is you see the Boston Dynamics robots doing back flips and dancing on YouTube videos. They're incredible and they're real and they're amazing. Everyone respects what they do in the field as far as I'm concerned. But even they would admit that they will show news organizations when news organizations come and interview them. They will show the robot going around and they'll show the robot falls down sometimes. They know it and they're trying to improve it. I think that I view robotics on a sliding scale of environmental control. We know that robots are in factories right now, many, many. There are millions of robots in factories and quietly doing the job of making our stuff. Those are highly "controlled environments". I talk about this a lot. I might talk about this later, who knows? The reason they're so good is because they know what to expect that's coming at them. When you step out of the factories, what is the next step of uncontrolled but still kind of controlled environment? To me, that's the road. That's cars on the road. There are rules to the road, but there's also unexpected things that happen. We have this whole autonomous car push and we are pushing forward, but I think a lot of people at this point are asking, hey, where's my self-driving car? Where is it? There are some cities where you can have them pick you up in a cab, but there are some questions as to how much oversight there is by a human pilot, and that's not always known. I think there's a little bit of coming to reality as to where we are with these systems. Those are sort of, let's say, semi-controlled environment because there are rules to the road. What rules are there to your home? I know you talk about this in your book. I know you talk about this. I find it funny that I came to a similar conclusion, but there is so little control for a robot in your home. The companies that want to do home robotics, like a robot that will make cook for you or maybe a robot that might help grandpa off the couch, they know these are not products that are going to be ready soon. What they are doing is they're starting research institutes to answer those basic scientific questions of how do you fold the laundry? What are the algorithms to fold the laundry? Dealing with these categories of objects that robots have to deal with that they don't have to do as much in factories. Soft cloth folding, that's an active field of research. How would you, if you're cooking a vegetable, how would you know how to slice the carrot? The carrot's a different size. There are institutes that try to come up with control policies to handle that. We all know it's still at the basic to applied research stage. That's a long way of saying, Steve, that I think we have to wait a bit for robots to be in our homes. I would not expect it, in fact, if I were an audience member, I would apply your skepticism to whenever you see a product, something that seems like a product that's going to be in your home that's a robot anytime soon. If you see an advertisement or you see a cool YouTube video and say, oh, the robots are coming, you've got to ask yourself how often does it work? Just to belabor this a little bit longer, there's a great example, there's a company that I have ties to, it's called Agility Robotics, they make humanoid robots. They want humanoid robots to go in factories. If you're asking where they're going to show up next, there are multiple companies popping up seemingly almost every day that for some reason there's an intended market for humanoid robots in factories. Now, you could have knocked me over with a feather when I heard that, but it seems like people are really investing a lot of money because they want to put robots with a human form factor to do human form factor tasks. That way you are in a factory where things are semi-controlled, but they're not bolted to the wall or you don't have to roll along the floor. People have done live demos and where a humanoid would go and pick up a box and go put down a box somewhere else, basically sort of like doing this box stacking task and they did it live in front of a major industry conference. This is a great test for how close we are and they had multiple robots running around. It was a very impressive demo, but occasionally the robot would just fail. Sometimes the robot would just collapse out of nowhere, it would just onto the floor. People will clip this and put this on YouTube and they would say, and people say, hey, look, the robot worked for five minutes and gave up on life as a metaphor for humanity, I guess. But when they tallied it all up, it was like 99% reliable, which that sounds good. I would take that as an academic, 99%, but in this case-
B: I'm not 99% reliable.
CH: But I bet those, Bob, if you had to pick up hundreds of boxes a day, my guess would be one out of a hundred of those, you wouldn't collapse on the floor and die. And so there's still some ways to go. And I think everyone, to my eye, I think the people I talk to in the industry believe that, too. But they're banking that they can sort of close that gap. So where are robots going to be? I think first they got to be doing more things in factories. Then we got to start seeing more reliable cars. And if we start seeing more reliable autonomous cars, then I think we start thinking about where are we going to see these other places in our lives?
J: Christian, what about the big advancements that we're having in artificial intelligence? So these robots are largely controlled by collections of algorithms, right?
CH: Correct.
J: So, OK, so I'm just following the trendy news here for a second. So we have, we're hearing lots of stuff about like chat GPT and BARD and all of these companies are investing billions of dollars into artificial intelligence. If we have an artificial intelligence breakthrough, would that have a direct impact on how quickly developing robotics? Would you find at some point, wow, like all of a sudden, the software is working way better than we thought it was that it was working a few years ago because of these recent advancements. Would that have an impact on how fast things move?
CH: That's a great question, Jay.
J: Thank you.
CH: And I think it's one of the questions I think to have the answer to is my answer is it could. It depends on the nature of the breakthrough. And these things like large language models, people are trying to incorporate them into how robots do tasks. Like there are researchers who want to take a task such as chop the carrot, use a large language model to develop the steps along the way that would chop the carrot, have the robot try to do those steps to break it down to digestible tasks. Also, another example is stable diffusion. And for those who don't know, that's the underlying technology behind those image generation AI software where you create a picture of a cat, Pokemon on the moon doing the Hokey Pokey or something, right? People are also using those methods to take different examples of robot tasks and stitching together the robot doing a somewhat different task. Like, for instance, if you wanted to spread Nutella of different viscosities, you could have a couple of example, it's very I actually have a friend who's working on this exact problem, spreading Nutella on bread and using the stable diffusion to take a couple of different examples of robot motions, just like something like DALL-E might take examples of images to generate instead of a new image, a new policy, a new task that it can do. And so people are you doing these things, but and they are helping. But the question is, what would be the next big thing that you would need to now say, aha, this is we now have the algorithm to put robots in our spaces and be much more reliable and more versatile and get things done without having to have an expert engineer program every single motion. That's not sustainable. And what you'd be looking for is some really good jump in the generality of what a robot can do based upon a reasonable set of data. You're also looking for something that's going to give you more confidence in safety. And often that isn't in the field of AI traditionally, it's in the field of controls. Controls is an old field. It's hundreds of years old. It's a mathematical field. But one thing that people like about controls is that given certain assumptions about your system say what you will about assumptions, but given certain assumptions, you can make some guarantees about performance. So there are some people who are really trying to mix sort of like the peanut butter and jelly of of AI and controls to blend those together to have the what's a virtuosity of AI to do cool new things with sort of the performance or stability guarantees that you get out of control.
S: Christian, so you're talking about like what spaces the robots are going to be going into. And I agree, it's going to be factory than semi controlled spaces. And the home is going to like the last space is going to get into. But there's also the question of are the robots, especially when you're talking about the home, the robot, because robots are already in the home. It's really more of a question of are the you know, how general purpose versus narrow purpose are they going to be? Because I'm pretty happy with my Roomba. I think it does exactly what I want it to do.
B: Meh.
S: Does it impress me? Well, I have a higher end one than you. I do. I agree. I think the crappy ones are crappy. And if you get it, if you get a high end one, though, it's I mean, I'm quite impressed with it and does it's fine.
CH: It's decades of engineering that went into that.
S: I think it would be a very long time before we have an all purpose humanoid robot in the home. But I think more Roomba like things might be in nearer future.
CH: Oh, for sure. I mean, like and just like you go from, let's say, controlled environments to more uncontrolled environments, you would go from specific tasks to more general tasks. So imagine this is just me coming up with a random pitch here, but a Roomba that maybe had a little arm on it that maybe can pick up some things and help move them around. Imagine you had a Roomba instead of just sweeping up the floor. You'll pick up the kids toys or something along the way or maybe put them in the box to put them in the toy box. Maybe that'd be a niche product, but maybe it's something that where the company start thinking it into something getting a little bit more general. But it'll be incremental, I would say. Now, I say that, but I also say to any funding agencies listening, I would say by the end of the next funding cycle, I think we have this problem cracked where it's fully general. But I mean, but that is the dream. And that's the kind of thing people like me are motivated by is that we know that with one humanoid presence like ourselves, we can do a lot of stuff. Does that mean it's the best way to do things? Of course not. Of course not. But we know that this kind of generality is possible. And is that generality always what you want? I mean, no, not necessarily. I don't need my car to be a plane and a spaceship. My car is a fine car. But there are times where it's nice to have some generalized, some generalized equipment. The fact that our computers think about all the things our computers can do. I mean they went from word processor and maybe email sender and maybe paint MS Paint thing to just anything you could do so much on a computer these days. And that versatility really shines. So I think we see that, like, what if there was a machine you could have in your home that is like, I need to fix the roof. Can you go fix the roof, please? And it can just do it. But that would be that would be awesome. Like, there are so many little things. And it's like, oh, my shower, like my the knob of my shower got broken. I wish I didn't have a handyman to do that. Robot can do that. That would be awesome as a somewhat recent homeowner I now understand the value of a handyman and not just calling the landlord. But there is value because there's so many tasks that need to be done for us to live. And so and some of them, so many of them, I just do not want to do. And so that's one of that's one of the potentials, I think, of a generalized robotics. And that that would be exciting. Exactly the avenue which way to go. It's hard to know if I knew that I'd be probably a lot richer. But I think that moving just finding the low hanging fruit and moving forward from that I think that that's a good way to go. Just kind of generalized piece by piece.
S: Yeah, totally. So I mean, the question of specific task versus generalized capability is an interesting one, because I think it's different for a lot of different things. I generally tend to like prefer that I have something that does one thing really well but sometimes the versatility is worth that. I remember when smartphones first came out and I'm talking pre iPhone, like the first real smartphones. And I was very resistant to them. It's like, you know what? I just want a good phone. I don't need to do anything else with my phone.
CH: Blackberry.
S: Well, I think they were, yeah, they were like the Blackberry. I never owned a Blackberry. I don't need to like do email and texting on my phone. I just want a good damn phone. And they were a bit clunky as a phone. I wasn't willing to sacrifice the phone app to get versatility. But then when the iPhone came out and that generation of smartphones came out, the versatility was so off the hook, it became worth it. Then it was like, OK, the camera is not as good as my camera, but it's in my phone, but I have it with me at all times.
B: [inaudible] UFO happens to appear.
S: Exactly. So, yeah, it's interesting the trade off and there are thresholds. So I maybe the same thing will happen with robotics that we have a bunch of specific task robots until somebody could make the iPhone of robots, basically where it's so versatile and good enough at so many different things that that becomes worth it.
CH: I totally agree. And particularly what the example with the phone on a camera is perfectly apt because if you had asked me in the year 2000, hey, Christian, do you want a camera on your phone? I'm like, what are you duct taping to my phone? Why would you like cameras were much more people didn't run around with cameras all the time. They were more like if you were, you were like a hobbyist or a tourist. And but and also what are you going to do with the camera? Are you going to go develop the film in the middle of the day? What's going on? But it ended up being this ubiquitous thing we now all have. We all take for take for granted we have a camera, even though it didn't seem obvious at the time that, of course, we'd want a camera at all times. Think of all the things you could do also because we didn't have high bandwidth Internet or social media to share things at the time. So the point being is it could be unexpected the avenues in which these things finally crack wide open. I think that that level of humility of knowing what it's going to be and the creativity to think of what it could be is important when we're trying to project the future on this.
B: Oh, absolutely. Hugely important underappreciated. You just can't just can't anticipate that that's that texting will basically supplant using the phone. I really saw that coming.
CH: For sure. And I'll say that in terms of robotics, one other angle we haven't really talked about is that we can get these robots to do a lot, but they're still kind of expensive. And I mean, that's the elf in the room. They're still pretty darn expensive. I mean, a humanoid robot like sort of an Asimo, that's sort of Honda's robot, which you could never buy. But there were competitors such as Hugo and similar ones that are like these sort of like they look like little spacemen walking around. They're made by Japanese and Korean companies. And it would cost half a half to a full million dollars to buy one of those things, probably 10 years ago there about. I mean, and now you can get one for about one hundred thousand. So that's order of magnitude. That's that's coming down, but it's still very expensive.
S: Yeah, you need a couple more to get down to the prosumer.
E: Runs on a lithium ion battery, right?
CH: Absolutely does. I mean, Elon Musk wants to have his Tesla box because he invested in that. He unveiled his Tesla bot in the last year and he wants it to be down to twenty thousand dollars, like the cost of a car. And it's like it's one of those things that I'm like, I'll believe that when I can buy one for my laboratory, because that's just it's just right now there's a long way to go to make things cheaper. We're getting better at this and in a number of ways like we're finding that we can get away with cheaper sensors. We can find ways to make actuators cheaper. We can we can be smarter with how we use them so that we can drive down the cost. But it's still a ways to go.
S: All right. Well if there's any big robot breakthrough, we'll get you back on.
CH: Thank you. Appreciate it.
S: Christian, thank you for being so generous with your time. It's been a pleasure having you on the show. And we're going to transition now to our live show from Dragon Con.
[commercial brake]
Live from Dragon Con 2023 (40:26)
S: Hello and welcome to the Skeptics Guide to the Universe. (applause) Today is Sunday, September 3rd, 2023, and we are live from DragonCon. (applause) Joining me this week are Bob Novella...
B: Hey, everybody. (applause)
S: Jay Novella...
J: Hey, guys. (applause)
S: Evan Bernstein...
E: Hello, Atlanta. (applause)
S: And we have a special guest this week, survivor Christian Hubicki. (applause) Christian, welcome to the SGU. Now, I understand you're a longtime listener of the show.
CH: I am. Yeah, I have a vintage t-shirt on and everything from the first NECSS in 2009 in New York City.
G: Wow.
CH:' So it's pretty close to OG. Yeah, yeah, I've been a long time fan.
S: So you sort of cross a lot of lines with us. You're a skeptic, you're a fan of the SGU, you're a proper nerd, as we like to say.
CH: Indeed.
S: You're an actual scientist, does robotics, and you're kind of a celebrity because it's the Survivor's.
CH: I forget what letter of the alphabet celebrity I'd be. Probably in the M to P range. But yeah, absolutely. Thank you. I'll take it. No, it's been a lot of fun. So like I said, my background's in robotics and I'm now a professor and I run a research lab. So that's my day job. And at night, they throw me on islands. So what could I want?
S: Yeah, I got this photo off of the, I think it was the Survivor Wiki. You look pretty fierce. Pretty fierce. You were in the David and the David versus Goliath group.
CH: That's right. Our season was themed after David versus Goliath. And I guess the idea that some people were big, strong favourites and us weakling underdogs. Naturally, I'm a big, strong favourite. No, that's not fair. So for some reason, they threw me on the David tribe. And but that was a lot of fun because I got to talk about algorithms on television, which I'm not sure they do much on Survivor normally, but in my case, they made an exception, which I appreciated of them.
S: And that actually made it to air.
CH: That actually made it to air. That's the other thing.
S: This is the other photo I pulled. This is like you're famous. You've had to stand on this pole. How long did you last on this pole?
CH: Five and a half hours. Yeah, it was a good time, to be honest.
J: I can't even sleep five and a half hours.
CH: Well, I mean, they put you in like this pain position, like you're being crucified or something and like, and you're designed to go numb. And I'm just trying to find ways to pass the time and not think about pain. The best thing I could do was try to recite my master's dissertation to the host of the show. And then he was the one in pain.
B: Yes.
S: That was psychological warfare.
CH: I wasn't trapped in there with him. He was trapped in there with me. (laughter) But he learned a lot about robotic exoskeleton control in the process. So I consider it a win.
B: And you won. You won that grueling challenge.
CH: Yeah, yeah, that was that was that was good. That was a fun time. And and I got to say all the things I wanted to say to the host of the show. And so I don't think there's when you're that level of celebrity like Jeff Probst, the host of the show is most people can't keep them held captive for one hour, one hour and five. So you got to hear my review of all the seasons. So I'm sure you really enjoyed that.
S: You have [inaudible].
CH: We're on speaking terms again, thankfully.
S: What was the most surprising aspect of your whole experience on Survivor?
CH: I mean, the one was how fun it was. It was I mean, yes, starving was was not what that part was not fun. But I honestly don't feel like you're starving after a while. It was honestly it was the the intellectual rigor of a game of deception and political intrigue that you're playing solid for a month. It's one of the most interesting things I've experienced in my life. There were times where I like people are trying to mount a vote. For those who don't know, the game is not just don't starve. That's a component of it. It's also about voting out your colleagues. So and we're not going to vote it out. And in a game for a million dollars, people get pretty competitive.
S: That was a pretty good experience for academia.
CH: Yeah I'd say departmental meetings have a different take to them as a result. But the and so like that experience of trying to like we've figure out what does this person think the plan is? What do they think I think the plan is? What do they think that I think that they think is the plan? That and all what you're not eating is it's a lot. But it was an incredible amount of fun.
Christian and Robotics (45:19)
S: Let's talk about robotics really quickly. We're going to be talking to you about an item in a bit, but just to give people a flavor of what you do for your day job. So when are the robots actually going to take over the world?
CH: What time is it? So my background is in legged robotics. That's what I was trained in. That's what I did my doctorate in. So walk basically bipedal humanoid walking robots. It's a fun time. Makes for a compelling survivor audition video as well. Just a note to anyone who's interested. But it's I particularly focus on the control algorithms. How do we make them faster? How do we make more agile? How do we make them better at not falling down and more efficient as they move along. And that's and there's a there's a little bit of math and coding and programming in it. But a lot of fun experimentation along the way as you're basically pushing robots over and hope they don't remember the experience of doing that. So yeah, so and so now I want to research lab down at the FAMU FSU College of Engineering. It's a joint program between Florida A&M and Florida State University. I run the lab there. My students do excellent work that to making robots walk better. We have a couple of humanoid human sized robots in the lab. One that looks like an ostrich called Cassie. It's about three and a half feet tall. The other one's a humanoid robot called Digit, which is about five or five and some odd feet tall. And we're trying to get it to do more stuff more autonomously because robots, you can make great YouTube videos of them doing cool stuff. And that YouTube video is very reliable. It runs every time. Unless it's on my computer. Whereas real world robots if you're going to put them out with other folks, with other real people doing real jobs, you've got to count on them. And that's a real long term academic effort between academia and industry to make that happen. That's partly what I'm doing for my career.
S: Yeah, we were chatting about this. You think that one of the biggest public misconceptions is how reliable robots are. Because they see the video, they go, that robot does that every time. You ask it, does it backflip? It could do a backflip. But really, that's like the video, how many trials was that?
CH: Right. And the short answer is, we don't even know how many trials there are. You have to really rigorously document that. And if you're a company, you're not interested in documenting your failures to the public. Although I will say, the companies that do, they've actually been quite open when they do interviews, say, hey, it doesn't do this every time. We have a lot of work yet to do. Yes, our Boston Dynamics videos look awesome, but there's a lot of work, they're honest about it. But we don't know how big is that gap. I honestly don't know because we don't have that kind of data. And that's something that we academics, given that we're in the publishing business, should be doing.
E: And the media wants to see the successes. They don't want to see the robot fail any time after time.
CH: It's funny the first once or twice. But yeah, it gets old after a while.
B: But what's the difference between it does a backflip successfully, the next three times it does it, it fails. What's the difference? Is it how subtle, it must be a nuanced difference that it can't replicate.
CH: Well, I mean, with a robot, so many things can go wrong. I mean, it could be the core algorithm that you're working with. It's just not robust enough yet to just tiny changes in how you start it and move it. I mean, it's supposed to be. It's supposed to be. That's what the other people shoot for. And companies like Boston Dynamics, they do excellent work. They're like the best at it. They're among the best. But it also could just be silly things like the hose in your robot hydraulic was loose that day. And that created a thing.
S: A little friction of the joints.
CH: A little friction of the joints. Friction is very hard to come up with a good model of that we can rely on for robots. And that's a major problem. Other things that are hard to predict are going to act. Collisions. Two things hitting each other. And it could act one way and almost, you have two situations that look almost identical. But they sort of bounce off into different directions. And legged robots are all about impacts. What are those feet doing to the ground? Impacting them, right? Over and over and over again, every step. And if your control algorithm is good, it should be able to handle that variation. But that's a long process and it's difficult. It's hard. So I really respect everyone in the field who's tackling it.
S: Yeah. All right.
News Items
Exploding Batteries to Deorbit Satellites (49:10)
S: So we're going to power through some science news. We're going to start with Bob.
B: Me?
S: Yep. Telling us about, this is a follow on on our every now and then discussion of all that space junk that's up there in orbit. What are we going to do about it?
B: Yeah, this was fascinating. Researchers have discovered a way to use batteries to help de-orbit satellites. Well, how does that work? First, though, what's the status of satellites in low Earth orbit? Currently, the latest numbers I have, we've got 22,000 objects that are being actively tracked by an agency called the Space Surveillance Network. I don't know much about them, but they're tracking 22,000 objects. But they also estimate that there's over 900,000 pieces greater than a centimeter in orbit around the Earth. That's a huge, 900,000. They're not doing anything. They're just like basically junk flying around at very, very fast velocities. And if you go less than a centimeter, it's in the millions. And remember, these are traveling at thousands of miles an hour. You do not want to be hit even by something really tiny.
S: They're all bullets.
B: They're basically bullets. So what's the big deal? Low Earth orbit's really big, right? Well, it's big, but this is a lot of objects. And there's always the fear of something that we've mentioned on the show, the Kessler syndrome or this Kessler effect, which is basically that at some point you're going to have a cascade of collisions that eventually becomes a situation where there's so much debris in orbit that you can't do anything in orbit. No satellites, no people are going, no astronauts, nothing. It's basically a dead zone for decades or centuries. That's the big fear.
S: And interestingly, I was reading about that recently, and we were talking about this, that the Kessler cascade is not necessarily an event. It's just a mathematical probability that could play out over years or decades. In fact, it's possible it's happening right now, like we're at the beginning of this process.
B: It's not only possible, I will say. I will say right now that it is happening.
S: It is starting, yeah.
B: And that's because I found this quote on the NASA site. NASA says, "Debris is now self-perpetuating in low Earth orbit due to the sheer number of objects."
S: That's what it is.
B: Worse than that, worse than that, debris in low Earth orbit are now projected to increase even without the addition of any new objects. So that means that the objects that are de-orbiting naturally is smaller compared to the collisions that are creating new pieces. So I would argue that the Kessler cascade has already started. The question now is, at this rate it would probably take years or many decades to get really bad. But the process has already started, and that's a really, really scary thing.
J: How else can we screw the planet up, you know?
B: Yeah, the surface, the ocean, the atmosphere, and then now, of course, low Earth orbit.
J: This might actually be a good reason why we haven't been visited by aliens. They may come and they're like, no fucking way we go near that track. That's a test track!
B: Those humans are a hot mess.
J: All right, so how do we track them?
B: There's been a lot of plans to deal with these satellites and how to de-orbit them. You put a thruster on satellites to de-orbit them, you have tethers. All are expensive, a lot of money, a lot of time. This new idea is called LIBDO. LIBDO stands for Lithium Ion Battery De-Orbiter. Now, how is that going to help de-orbit? All satellites have batteries, and most of those batteries are lithium ion batteries. Now, when you think of lithium ion batteries, in terms of danger, what do you think about?
J: Fire.
B: Fire, right?
E: Explosion.
B: And so some genius realized, well, maybe we can take this dangerous aspect of lithium ion batteries and turn it to our advantage. So they actually realized that if you start this thermal, this cascade leading to a thermal runaway on a lithium ion battery, it's actually a vacuum-capable solid rocket motor. It can actually be used.
CH: Of course, I was going to guess that actually.
B: So they did a test. They said, all right, let's take this battery, let's make it, let's start a thermal runaway. They measured it, and it created a force of 29 Newtons, a vacuum-equivalent force of 29 Newtons, which sounds, it's not a lot, but it might be enough.
S: It's enough.
B: It might actually be enough. And the great thing about this is that the batteries are already there. All you would need to do for all future satellites is to have a little nozzle. You add a little bit of a nozzle by the battery, and you need to be able to control the altitude of the satteliteso that when the battery goes off, you can control the orientation of the satellite so that it de-orbits. That's all you need. You're adding a miniscule amount of new weight. So when an astrophysicist or an engineer hears about, you don't really need to add any new weight to the satellite. They are very, very happy, because when you say to them, you've got to add 20 pounds, they're like, sorry, that's going to cost a million dollars, and it's going to take way too much time. So this is an amazing opportunity. And so here's an example of what you could achieve with this. If you've got a satellite that's 15, say 15 kilograms, it's in orbit, it takes 10 and a half years to de-orbit. It's life time. It's de-orbiting life time when all the work is done is 10 and a half years. If you use a battery like this, an optimized lithium ion battery, what you could do is you could do the explosion of the battery, the burn of the battery, and you could bring it from 500 kilometers to 400 kilometers. That would reduce its orbital decay time to, instead of 10 and a half years, 4.7 years, which is a 55% reduction. You're basically cutting the de-orbit time in half, which means that it's half the time that a cascade can start, where something could hit it and it could break up into a million pieces. So you're decreasing that time. I mean, it's not quickly de-orbiting, but if you're cutting the de-orbit time by half, that's great. That's a great start, and it's cheap. It won't cost hardly anything. So this is a great idea. I hope they really run away with this.
S: But this is only for new satellites going up. They can't do this to existing satellites.
B: Obviously.
S: Yeah. So what are we going to do with existing satellites?
B: We're screwed.
E: Yeah, what's the solution.
B: I mean, what are we going to do? It's going to cost money. It's going to be expensive. It's going to be time-consuming. But this is something, at least, that is all new. It should be a lot. All new satellites should have this set.
S: It should be the standard.
B: It's no panacea.
J: But just like global warming, which is obviously on track to kill us, they wait too long and this gets more sloppy.
S: It gets harder.
J: We need to do it now. Right? Right now.
S: We need to do it 20 years ago, but yeah, now it's better than later. So there are two companies that I'm aware of that are working on an alternate for satellites that are already up there. This is a really clunky way to do it, but they basically send this crab thing up another satellite to grab it and then de-orbit it. So this will only work for big satellites. This is not for the little nuts and bolts that are zipping around in orbit. It's going to be expensive and it's going to take time, but it's better than nothing. Every satellite we pull out of orbit is one fewer thing that could participate. Interestingly, the satellite that they were targeting for a test flight next year or in 2025 for this system, they were looking at it with a telescope, like it's already been hit by something and it's been broken up into multiple pieces. They still think they'll be able to grab it because it's kind of clustered together, but instead of being a solid object, it's now a pile of rubble. So ironically, it's already been hit by other debris.
CH: And I've seen some of these things at the research proposal stage. You're seeing companies that are ready to go right now. What I see as a faculty member, they're soliciting ideas and NASA will put out proposals with very specific ideas of what to look for, and they were looking for things shortly after impact like what you're talking about, Steve. As part of the call for proposals, they showed this graphic of what it's like very shortly after a collision. And the idea was that if there's certain kinds of collisions, they will spread out if you let it go long enough. So if you get it intercepted early enough, everything will be still kind of in a cluster. And I was looking at it, I was like, oh, is this something that's doable? And I was looking at it, I was like, after five minutes, they were already many miles apart. I'm like, oh my goodness. It's like basically you have to intercept this thing from some other side of the planet and get there, seemingly in minutes, and I gave up on any possible ideas. It's just such a horrendous problem and it's going to be a tricky one.
S: Any momentum that you're adding or subtracting is going to put it into a slightly different orbit. So it's going to just drift away and spread out.
B: And don't forget, this whole crab idea where it's going to grab it and deorbit it, that's okay, but you're not going to be able to grab something and deorbit it and then go somewhere else and deorbit that and then go somewhere else. It's way too expensive in terms of fuel.
S: You can't go to different orbits.
B: You can't.
S: It's like a one-shot deal.
B: One-shot deal. So that's not a great solution.
CH: Well, that cheered me up.
S: Yeah. Well, this next news item will cheer you up there.
Dark Stars (58:10)
S: All right. So this is all theoretical, but it's super cool. Super cool. Has anyone here heard of dark stars? Dark stars, they're dark because they're made of dark matter, not because they're not light. In fact, they're extremely bright, theoretically, if they exist. In 2007, an astronomer named Elizabeth Freesc, F-R-E-E-S-C, I think that's Fries, she hypothesized that, hey in the very early universe, when there was clumps of dark matter, there were local regions of dense dark matter, it's possible that hydrogen and helium, because most of the universe, especially at the beginning, is all hydrogen and a little bit of helium, if, yeah, as that coalesced near a pocket of dark matter, the dark matter would have coalesced with it, and even 0.1% of dark matter in the mix would be enough, theoretically, to keep that hydrogen and helium into condensing into a star. And so it's possible, so we don't know what dark matter is. We're not 100% sure it exists. I think it probably does exist. So if it exists, but we don't know what it is, but if it is capable of annihilating itself, if two dark matter particles, if they collide with enough momentum, if that energy is enough for those particles to annihilate each other, then what will happen is those dark matter annihilations will release light and heat, and that heat would be enough to keep the hydrogen and helium from coalescing into a star. So you have basically a star fueled by dark matter annihilations rather than the fusion of hydrogen into helium and then into heavier elements. So what would this mean physically? What would be the physics of a dark star made of dark matter? So they would be capable of getting much more massive than a regular star, and they would be a lot bigger. So they could be as big as 10 AU in diameter, so that's 10 times the radius of the Earth. The biggest ones-
E: The Earth's orbit.
S: The Earth's orbit around the Sun, 10 times bigger than that. That's massive. And they could have millions of times more mass than our Sun, millions of solar masses, and billions of solar lumens, billions of times brighter than our Sun.
J: So anything around it would get cooked.
S: But it's cool, it's cool. It's not hot.
J: What do you mean? It looks cool?
S: Yes, it looks cool and it's temperature-wise cool relative to a star.
B: I believe the surface temperature would be comparable to the Sun's.
B: The surface temperature of the Sun's not that hot. There's no core temperature, there's no core where fusion's happening.
J: So planets could be around it.
S: They should be around it. Well, this would be in the early universe before there was any heavier elements.
B: So no rocky worlds?
S: Yeah, so no.
J: So nobody played reruns of rocky over and over and over again?
S: No, that's correct. These would be population 3-type stars, which ironically is not the first stars, it's the ones that are only hydrogen and helium. So anyway, this is her hypothesis. Maybe there are these dark matter stars that an individual star is as bright as a galaxy, because it's billions of times as bright as our Sun. So as bright as a galaxy, it's huge, it's massive, and it only existed in the very early universe. So if we're looking really far back in time towards the first few hundred million years of the universe, maybe we could see some of these dark matter stars. So enter the James Webb Space Telescope, JWST, which can look at these very, very distant, and then what you're seeing in the picture here, by the way, this is a galaxy field. Those are galaxies that you're looking at, and these are ancient galaxies. So what Freesc and colleagues did to follow up on her 2007 hypothesis was to pour through James Webb Space Telescope data and say, are there any of these ancient galaxies? So firstly, they picked out objects that were extremely redshifted. Redshifted means they're far away, they're old, they're early, early universe. They took those, they said, all right, which of these have the spectra? Spectra are the bright and dark lines when you analyze the light from an object. You can tell so much about the universe by looking at spectra.
E: It's a fingerprint.
S: Yeah, it's a fingerprint of all kinds of processes and elements and whatnot. So anyway, if you look at the spectra of these objects, they found four candidates that have the spectra that are consistent with the models of dark stars that she came up with in 2007. So basically, these four things, and there were three of them in particular, these three are, should be considered dark star candidates. It doesn't mean they're dark stars. We don't know that they are.
B: But Steve, in my reading, it said that these stars, these candidate stars were, or objects, were very far away, which of course it would need to be. And secondly, they said it was more point-like and not fuzzy.
S: Well, no, it's just that they couldn't tell the difference. It's not that they were more point-like. So if you're looking, the James Webb Space Telescope, because they're so far away, it's still just a point of light. They couldn't, so one way to tell the difference between a galaxy and a single object, as bright as a galaxy, is a galaxy would be fuzzy and a single object would be more of a point of light. They just couldn't tell the difference. So if they could, then that would confirm that it was not a galaxy.
J: Well, we might need a better detection device.
S: Yeah, but that's not going to happen. We're running out of time soon. The problem is we need a more detailed spectral analysis. So, because there are fingerprints of dark matter stars that we could absolutely see with a more higher resolution spectral analysis. And James Webb Space Telescope can do that. The problem is it would take months of observation in order to get that higher resolution. And they don't have the time on the James Webb Space Telescope. Because everybody wants time on the JWST, and this is one experiment. Like, hey, could we have access to this for several months and basically block every other experiment that people want to do so that we could answer this one question. Now, I don't know who makes these decisions or who gets time on the JWST, but let's say we were able to confirm that these were dark matter stars. How big a deal would that be? Like, is it worth time on the JWST?
B: It is. Nobel price.
S: So, well, it would be huge. And everyone acknowledges. They say, listen the data we have so far, there's other possible explanations for this. There are stars that have the same kind of spectra. Again, it's just consistent. You could make a model that's consistent with the spectra that we're seeing. So we really, they're not confirmed. But if they were, that would mean several things. One, it means dark matter 100% exists, right? I think right now it's like 99%. But there are people serious astronomers who have good arguments about, the modified utonian dynamics.
B: Are they good? Are they really good?
S: I mean to listen to them say it, yes. But the majority of the opinion is, no, there's dark matter. But this would end the debate. This is one of the ways in which the debate would just be over. If there are dark matter stars, there's dark matter. So it would 100% end that debate. Two, it would tell us something very critical about dark matter. Dark matter is capable of annihilating itself. Not all models of what dark matter could be necessarily have that feature. So it would narrow the list of possible candidates for dark matter itself and would help us know where to look in the universe for dark matter and figure that out. Also, the third thing is that it could be a possible explanation for supermassive black holes. So galaxies that formed early in the universe, most of them like our galaxy, have a supermassive black hole at the beginning, at the center of the galaxy, and these are black holes that are millions to billions of solar masses. Again, they're massive. And astronomers aren't exactly sure how they formed in the early universe. Like, why did so many black holes coalesce into a supermassive black hole?
B: They're too big. They're too big to be explained by modern theory. How do they get that big?
S: We don't really know. This could be one solution because, if you think about it, you have a billion solar mass, I'm sorry, you have a million solar mass, it's a billion times as bright, a million times as massive, a million solar mass, dark matter star, and you have that 0.1% dark matter making light and heat and keeping it puffed up. When that dark matter runs out, all that hydrogen and helium collapses and forms a black hole because it's already too massive to hold itself up as a star. It would immediately collapse into a black hole. That could be why we have a lot of supermassive black holes. So it would potentially solve that mystery as well. So there's a lot riding on this. I don't know what's going to happen going forward. Right now we just have these candidates. The whole idea is fascinating. It may be completely wrong, but that's how science works, right? You have to make these hypotheses and, more importantly, figure out ways to test them. And that's what Freesc and her colleagues are doing. This is the possibility. It fits the models. This is how we can test it. Until you answer that last question, this is how we can test it, you're just chatting in the breeze.
J: So what's the cool part?
S: Yeah. I'll play it back for you later. (laughter) All right.
AI Drone Racing (1:08:15)
S: Christian, do you do this work with the drones?
CH: I do some drone work. I don't do this drone work.
S: Tell us about this drone work.
CH: So researchers at the University of Zurichat the Robotic and Perception Group as well as Intel Labs have suddenly announced that they have an autonomous drone racing system which has achieved champion-level performance. They can beat human champions at racing through drone gates. People can see the image of basically the drone trails going through little squares doing time trials with drone gates. And this is really cool. It was actually published in the journal Nature just on Wednesday. And to get a robotics finding in nature, to my understanding, robots aren't natural, they don't know where to take their standard. But the big finding, and this is for a number of reasons, but we'll get into that. So what did they have? So basically what they created was an autonomous system they call it SWIFT. I don't know if it's an acronym for anything so it's a very clever one in order to make this drone racing controller work. And basically there are two key components of what it needs to do. One, and this is often undervalued in robots, it needs to know where it is. We take for granted that we know where we are in a room at a given time, and it's developed all kinds of cool algorithms including the best acronym in all of robotics the simultaneous localization and mapping called SLAM. I'm jealous of that, and that's good. Of course it's SLAM it. So part one is you have to know where it is. So it uses what we call visual inertial odometry. Have we covered this on the show in the past?
B: Oh, many times.
CH: We all know what odometry is. It's the odometer in your car, right? And how do you know how far you've gone? It counts how many times the wheels have turned, right? Well, we don't have wheels with these drones but you have vision. So you can do visual odometry. We have a camera on board the drone and you see how much the image flows past you and that gives you an estimate of how far that you've gone. That's the visual part of the visual inertial odometry. The inertial part is also really cool. It has an inertial measurement unit on board and that has two components in it. One is a gyroscope. We've heard of a gyroscope before, right? It detects rotation. You get a good enough one you can detect the rotation of the earth. Take that flat earthers, right? We had one of those in the lab and proved them wrong.
S: They proved themselves wrong with one of them.
CH: That's amazing. Have you covered that documentary behind the curve? That's amazing stuff. It was the ether that got in the way. That was the problem. One part is the gyroscope that senses rotation. The other part is the accelerometer. Who here has an accelerometer on them now? Anybody? We probably do if you have a cell phone, right? It's the thing that determines if you're in portrait or landscape mode because it determines the acceleration of gravity and which way it is down. It also senses all kinds of accelerations. If you were in a car and you fell asleep and you suddenly felt the car come to a stop like you've been parked, that's kind of what an accelerometer does. If that's acceleration, you can integrate that up to position using calculus, then you can know where you are. If you combine these two things together, the visual and inertial, you can get some pretty good estimates of where you are. That's half of it. The other part is deep reinforcement learning. I'm sure this has been covered many times on the podcast. Once you know where you are, what do you do? What they did is they trained this drone and they would try a hundred different drone races at a time. Reinforcement learning, you give it what's called a reward signal. What's good and what's bad, right? That's the art of reinforcement learning. Part of it is saying, hey, what's good and what's bad? It has to be a pretty clearly defined task. You might think, well, how fast do you finish the race? Sometimes that's a little too broad and you have to give it something more specific. What they gave it was a reward was time between gate one and gate two, time between gate three and gate four, trying to make sure you get to the next gate as fast as possible. When you get there, you're looking at the next gate. That's the way that they told it. That's the reward. They ran this thing and I always ask people when they do deep reinforcement learning, how long does it take to run on the computer? It turns out less than an hour. Less than an hour they got this thing to actually learn a policy. There were some tricky parts we can get to in a minute when maybe it's a little discussion about this because the simulations aren't perfect and they lead to real problems. When they put this all together, the headline was they had it race in time trials against champion drone racers. Three world champion level drone racers. One was the Swiss champion, one was the world champion. I don't know how they take the rankings of this all. I'm not going to get involved in that world. The autonomous SWIFT system got the fastest overall time and was the most consistent of them. When they broke down the actual performance of the drone, the thing they found was that it was most consistent getting from gate to gate and made tighter turns. Overall, the consistency between gate to gate helped to get it faster overall time whereas the drone racers themselves the human racers were able to get some faster segments. They were able to speed up and slow down at different points in order to beat them out in a partial time. Overall, the drone system was the fastest. The claim here, according to them, is that the first time an autonomous robot achieved champion level performance in a real world competitive sport. I don't know what the chess people feel about that. I wonder what they feel.
S: Or the Go people.
CH: Or the Go people, right? That's the headline. There's lots of nuance to it too. It's really interesting how they achieve this stuff.
S: There's a lot of obvious applications. We're talking about as a travel option drones with people in them. Not hitting stuff is probably a good thing.
CH: I'm in favor of not hitting stuff. This is the part we do in our own lab. We do drone avoidance. We'll have a drone and we'll throw a pendulum at it at 10 meters a second and we'll have to dodge it out of the way. That's the kind of thing we'll do. One thing that's underrated the understated robotics thing that I point out is that all of this computation and sensing was on board the drone. And that is hard to do. It's much easier to have a desktop computer off the side. This is what we'll do in our lab a lot of the time when we're debugging stuff. It will turn through all the calculations and tell the drone what to do. Also, a lot of labs will use motion capture systems to tell you where the drone is. That's easier than using SLAM. I just want to say SLAM again. I just want to say it. They had Onboard Camera doing all the calculations but all the calculations were done on board. That's really impressive. Some caveats in the paper that are different is that we talk about this inertial sense that the drone has. People don't have that in the drone. The human pilots don't have an inertial sense. They don't feel the bank of the turn. That's an advantage that the drone has structurally over the person. There are sometimes structural advantages in these human robot performance games. It happens all the time. They also pointed out that the camera refresh was only 30 frames per second. I'm not a biologist. They said that the human eye performance is more like 120. Humans had an advantage there. They said there's a little bit here and a little bit there. Bottom line, this is really impressive with not only what they can do with the drone but what they can shrink onto a tiny drone, computer and camera because they can't carry very much.
J: You think if they can do that then what's up with autonomous cars?
CH: When I saw this I was thinking about this, Jay. It's actually a great question. There were no other drones on them. They're not racing in and out with other drones. You don't have to worry about colliding.
S: It's actually easier.
CH: That's a big one, right?
S: No pedestrians.
CH: Some of those videos, man. Those can be pretty scary. There's nothing else on the course there. That's a next level thing that you don't want to do. What this really shows is that you can get a big enough neural network with enough data and it turns out a reasonable amount of data to do all kinds of stuff. We see this in robotics all the time. The neural network approaches can do really awesome stuff. The question is how reliable is it going to be? It's a race so you want to count your best time. You don't want to count your worst time.
S: Getting back to my question at the beginning of the show, pretty soon.
CH: What time is it?
Settling Mars (1:16:59)
- Just 22 people are needed to colonize Mars — as long as they are the right personality type, study claims[4]
S: Jay, we can't talk about everything to do with Mars, but tell us about if we're going to settle Mars, how many people do we have to put there?
J: It's super complicated. Every study that's come out so far I think the consensus is maybe, you know what I mean? Because we know right now there's so many things that are dangerous and new about doing something like settling Mars. There's thousands and thousands of different technologies that need to be developed that don't exist today and they're working on it. We need to figure out every single thing that can go wrong before we start doing this. There's two studies that I read about. I'm going to focus on one of them but I'll give you a little bit of a comparison between the two. The first study is, and I'll tell you right out of the gate, they said 22 people. Think about that as we're going through this which I think personally is way too low sustained.
S: Self-sustaining.
J: Not really self-sustaining. Even in this one they were saying 22 they need some resources from Earth but even still it's a super low number, I don't see how it works. They asked a few questions. This is coming from the George Mason University Fairfax, Virginia. They wanted to know what conditions are needed to maintain a stable outpost on Mars. They wanted to know what combination of personality types would do best in this hostile environment and then they wanted to know how many resources are needed to get resupplies and assuming occasional accidents. They were saying that it takes about two years to get resupply from Earth which is a big deal because if you need something and you tell them hey we need it, they're like, okay, in two years you'll have it. That's no bueno.
B: Can't they just call Amazon and get it?
J: With the drone thing, you never know.
CH: Amazon is probably working on it to be honest.
J: I'm going to focus about their unique angle which was they were talking about personality types which I have not seen in any of the other studies that are done. They were saying at its core that people have to cooperate for there to be a successful ability to maintain a settlement. That seems really obvious but the scientists need to think about stuff like this because they're picking people that can handle stress and are really smart and are capable of doing different tasks and all that but of course you don't want to put narcisits up there, becasue they're going to have big problems. They're taking that into account in this study that they did. What they did was they created a computer model, they used several computer simulations to project out a 28-year span of people living on the planet just to see what would happen after the 28 years. Their approach that they had is they used something called agent-based modeling to really squelch it down. What it means in this case is that they are doing human interaction along with all the other things but this particular model includes human interaction. One thing that they said was that their model has to be pre-constructed before people arrived which again, that's a big deal because if we're going to pre-construct it then we have to have the technology to pre-construct it which means robots which is a big difference from the other study that I'll talk about in a minute. They also said that there has to be stores already in place of food, air, and water that all need to be created in situ on Mars. That's another huge thing, right? If you're going to say, yeah, we have to have food, water, and air already being created successfully to sustain well, how are you going to do that? Where's all the technology which we don't have today in order to pull that off? Another thing that they said was they were also saying that they would have constant power for seven years which is nice because solar panels don't work so great on Mars for lots of different reasons so they would have to use a nuclear generator. So getting into basically the personality types. I know most of you know studying people's personality types and taking tests all the different ones that are out there that's all nonsense and everything but they basically created four different groups. They said there's people who are agreeable, people who are sociable, people who are reactive and people who are neurotic. (laughter)
S: That's an accepted personality profile. It's the OCEAN.
J: Yeah, I agree.
S: So that's legit.
J: It is legit to say we have these four basic personality types of course there's infinite shades of grey but let's put that aside for a second. So guess what personality type worked the best.
B: People who have been on Survivor?
S: Survivor of Mars.
J: So between agreeable, sociable, reactive and neurotic, the agreeable people by far when they tested it. What they basically did was they started with tests at an equal amount of each and then they brought it through the simulation and they said well what happened, what went wrong who caused the problem and then whichever way success leaned they increased the number of those types of people and they kept doing it and kept doing it and then they basically said everybody's gotta be agreeable for this to work so we can't have any narcissists running around on Mars. They said, just to give you a definition of what agreeable means to them they said individuals with the lowest degree of competitiveness, low aggressiveness and not fixated on stringent routine. Which is interesting isn't it?
S: Yeah, that's interesting because those are features that might be beneficial trying to run a settlement on Mars. Like you know, you're saying neurotic as if it's a bad thing but you know, being a little neurotic like worrying about things that can go wrong, obsessively checking stuff, you know?
J: I took it as flexibility. You might be doing something different today than you did yesterday.
S: Flexibility is good but there's gonna be a ton of routine if you're gonna be keeping the machines running up there.
J: Well how about this, tons of routine, tons of routine for like 8 months you're doing the same thing holy shit but today you gotta do this and you gotta be okay with that. I mean I think that works.
S: I would think intuitively I would say balanced would be better.
J: Like I said, so over the many simulations they ran they had a varying degree of results from 170 people and they were able to get it down in their model to 22 people by using the people who were considered to be agreeable. So I'm gonna quote them the research team said "This demonstrates that team and individual psychological success in extreme environments can be broadly attributed to coping capacity which we define as the ability of people, organizations and systems using available skills and resources to manage adverse conditions, risks and disasters". This study is not peer reviewed yet. Now another study, very quickly another study who took a very mathematical approach to the whole thing and it wasn't just focused on Mars they were basically saying like what would it take to settle basically anything that's a hostile environment. And they came up with 110 people. So the big question here is why is there such a huge numbers difference. And again the minutia of the details of each study and what factors they took into account for and everything I'm sure are the major swing. I just ran out of the gate and I'm no expert, I know that but 22 just does not seem like it's enough to really pull it off.
S: It sounds like they were looking at it mainly from the social perspective but it all depends on what you build into the model. First of all how many surgeons do you want up there and what if one of those surgeons dies, how many backups do you want? How much redundancy you're building in is a completely separate factor than what they were considering. Agreeable people will maybe help the society function better but if you don't have the other personality types does that have a negative thing to it they're not considering. You're not going to have the person who's going to check the fail safe or something obsessively or whatever. It's like an impossible to model thing. You're always just coming up with a construct and saying well if these are the factors that we take into consideration this is the output. And that's an interesting thing to answer, that's interesting information but it's not really simulating what would happen on Mars.
J: Yeah and I think the real world studies you know that there are real people right now who are living in a Mars situation.
S: Yes, yeah, but there's what? Six people with a four-six, something like that. It's very few.
J: I mean, I think the data coming out of there is probably going to be much, much more accurate and useful than something else.
S: That's why you got to do that. So, and I think that we would need to actually do a much bigger simulation. Put people in a self-contained environment for a year and see what happens.
CH: I mean, all models are wrong, but some are useful. That's what it comes down to. I mean, and there are things you can do in a model. You can't do it in an experiment. You have to target the experiment appropriately. So that way you're validating the right thing or finding the new variables that you need. I mean, it is complicated. I mean, I kind of love these age-based models. I always view them like they're the sims anyway. So it's like, so it's pretty fun.
S: It would be a fun sim game, like settlement Mars. And you have to decide all these variables and it affects what happens.
J: Well, one day I thought about after reading all this was like the dynamic between people, like if you happen to like another person that's there and you want to get into a relationship, you're still living your life. You're working and you're on Mars, but you know, you still want to have relationships and stuff. And if there's any kind of, like there's a lot of options, it's like, oh, this person doesn't like me and then there's nobody else, you know.
S: Well, do you send up pre-existing stable couples? Like that's a big decision.
J: Yeah, that's a great question.
B: My takeaway, though, is that I don't care about all this people stuff. I might take away, is like, wait, you got to send, we got to send all these robots to Mars to prep it for us? I mean, how long is that going to take before we can get anywhere near that level of sophistication?
CH: I mean, again, what time is it? No, but it's, I mean, it's, they have to be more adaptable on the fly, is what it's going to come down to.
B: My takeaway is that we are all going to be dead before any humans are on Mars. This is like, we're not going to see this. It says, way too complicated. I'm so disappointed in the press. That's all, my God.
E: It doesn't happen in Bob's lifetime.
J: Many experts are saying, like, within 30 years, we will have boots on the ground.
B: Yeah, I'll be dead.
S: That's different than self-sustaining settlement though. Oh, yeah, yeah, yeah, yeah. We will be dead, not all people, yeah.
B: No, everyone in this room. Yeah, most of us will be dead.
J: Let you blow your mind. Elon Musk actually said that, like, 2050, which has roughly 25 years from now, there'll be a million people living on Mars. (laughter)
B: God.
J: I'll be like, you've got to be kidding me. You've got to be kidding me. Send me $300,000 because of how stupid that is.
S: All right.
Stress Patches (1:27:32)
S: Evan, what is Meghan Markle wearing on her wrist there?
E: I want to know how many people know who Meghan Markle is. Raise your hand. Yeah, it's a lot. It's about 70% of the audience. 30% of you are very good and very proud of you. So anything when cost playing Meghan Markle here today, I got no one, no one, no one. OK, well, if you are, you see anyone out there. Their cost play is likely incomplete, because located on her left wrist is a little circular sticker. OK, you have to have that if you're cost playing Meghan Markle specifically. That is called a NUCALM. That's N-U-C-A-L-M, NUCALM, biosignal processing disc, also known as an anti-stress patch. So this was first picked up in an article recently by Vogue.com and the media jumped all over it after that. So what exactly is a biosignal processing disc? How does it work? Well, time for some science, right? According to its inventor, Dr. Blake Holloway, the patched lens of neuroscience, steved pay attention. Neuroscience and biochemistry to help regulate patients with post-traumatic stress disorder, right?
S: Oh, they mentioned an actual disease by name?
E: That's it. Yeah, according to the inventor, the disc enhances frequencies that relax the wearer.
B: Frequencies.
E: Yep. Right from the website, let me read this. This is hard science, folks. Pay attention. Traditional Chinese medicine.
J: Stop right there. (laughter) Just stop.
E: TCM explains that she flows through the body along particular pathways or meridians to maintain health. Everything in the world is we know it vibrates with a particular pattern. Science. (laughter) Thus living systems produce electromagnetic frequencies androgynously that differ depending on the level of health or disease direction their website, by the way.
J: Wait, wait. What was that word you used? And they said androgynously?
'E: I'm sorry, I'm a typo here. Endogenously.
J: All right, good. (laughter) Because I was like, they are going into areas now that I can't even comprehend. (laughter)
E: It is hypothesized that if you restore the frequencies, the travel through the meridians, you can re-instate optimal physiology. These new condisks hold the EM frequency patterns of GABA, G-A-B-A, Steve.
S: It's a neurotransmitter.
E: And it's precursors to deliver a pure biological signal to your body. When placed on the inside on your left wrist, Megan Markle, at your pericardium six acupuncture point. The disc sens a signal to the pericardium of your heart to activate local parasymphatetic nerve fibers which then transmits the signal to your brain telling it to increase vagal nerve output and begin the process of slowing down the body. The disc stops your acute stress response. So the brain wave entrainment with new comm is always reliable and efficient in getting you into theta brain wave range, which—we're at right range—where restoration and relaxation can take place.
S: Evan, that's like the trifecta of pseudoscience. It'a all there.
J: Yeah, I mean, that is the officially the biggest load of bullshit I've ever heard in my life. In that sentence, what the f**k did we just do hear? (applause) I need you to take a goddamn bleach shower after hearing it, right? (laughter)
E: I mean, you have to have some kind of advanced degree in order to be able to have the talent to coalesce so much junk into one gobbledy book paragraph.
CH: So, but the thing is, they mentioned Z's at the beginning of this, is that what you said?
S: Well, he mentioned PTSD, you're not supposed to like name specificity.
CH: That's gonna say because now the realm of structure function claim, right? Under a regular term.
S: They say relief stress or promotes a well-being, whatever, at least in the U.S. you can get away with that. But if once you say treats a disease, that's a no-no.
B: But they're misinterpreting. I mean, that sticker, I mean, to me, it looks like she's got an active Wi-Fi signal. Maybe that's all that is.
J: Did you find out how much it is?
E: You have to buy from packs of $20, $80 for a pack of 24.
S: For a little sticker.
J: And how do you know where it runs out?
E: It lasts up to four hours per sticker. Of course. You've got to be putting these-
S: The frequencies wear out.
CH: But you can recharge them. You can recharge them up.
E: But you can buy packs.
S: You hold the crystal next to them and it charges them up. (laughter)
J: I imagine you walk into the place for the people that do it and you walk in and they're just always laughing.holy shit, we're making money.
S: All right. You have to move on.
E: Okay.
S: Just enough time to find the picture.
Science or Fiction (1:32:39)
Theme: Robotics Item #1: According to the International Federation of Robotics, in 2023 there are 35 million industrial robots, and 43 million service robots worldwide.* [6]
Item #2: The first robot-assisted surgery was in Vancouver in 1984, with the Arthrobot, which assisted in arthroscopic procedures.[7]
Item #3: Arguably the oldest robots include water-powered, clock-driven figurines dating from 3,000 BCE, and a steam-powered pigeon that could actually fly, dating from 400 BCE.[8]* The shownotes page for this episode on the SGU website did not have a link for any article to be referenced for this item.
Answer | Item |
---|---|
Fiction | 35/43M robots worldwide |
Science | Robot-assisted surgery |
Science | Oldest robots |
Host | Result |
---|---|
Steve | sweep |
Rogue | Guess |
---|---|
Evan | Robot-assisted surgery |
Jay | Robot-assisted surgery |
Bob | Oldest robots |
Christian | Robot-assisted surgery |
Voice-over: It's time for Science or Fiction.
Evan's Response
Jay's Response
Bob's Response
Christian's Response
Audience's Response
Steve Explains Item #1
Steve Explains Item #2
Steve Explains Item #3
Skeptical Quote of the Week (1:40:12)
Individual science fiction stories may seem as trivial as ever to the blinder critics and philosophers of today – but the core of science fiction, its essence has become crucial to our salvation if we are to be saved at all.
– Isaac Asimov (1920-1992), American writer and professor of biochemistry
Signoff
S: —and until next week, this is your Skeptics' Guide to the Universe.
(applause)
S: Skeptics' Guide to the Universe is produced by SGU Productions, dedicated to promoting science and critical thinking. For more information, visit us at theskepticsguide.org. Send your questions to info@theskepticsguide.org. And, if you would like to support the show and all the work that we do, go to patreon.com/SkepticsGuide and consider becoming a patron and becoming part of the SGU community. Our listeners and supporters are what make SGU possible.
Today I Learned
- Fact/Description, possibly with an article reference[9]
- Fact/Description
- Fact/Description
References
- ↑ TS2: Using Lithium-Ion Battery Explosions to Deorbit Satellites
- ↑ Scientific American: JWST Might Have Spotted the First Dark Matter Stars
- ↑ Nature: Champion-level drone racing using deep reinforcement learning
- ↑ Live Science: Just 22 people are needed to colonize Mars — as long as they are the right personality type, study claims
- ↑ Yahoo Life: Is Meghan Markle's stress patch legit? Here's what experts say.
- ↑ International Federation of Robotics (IFR): IFR Presents World Robotics Report 2022
- ↑ Surgrob Blog: World's First Surgical Robot
- ↑ Ancient Origins: The Steam-Powered Pigeon of Archytas – The Flying Machine of Antiquity
- ↑ [url_for_TIL publication: title]
![]() |
![]() |
![]() |