SGU Episode 961

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SGU Episode 961
December 9th 2023
961 Cerebyte.jpg

"In contrast to data usually stored on the best hard drives and the best SSDs of today, Cerabyte wants to use ceramic material, combined with glass, to hold mountains of data. For instance, it wants to build palm-sized cartridges that can store 10,000TB of data." [1]

SGU 960                      SGU 962

Skeptical Rogues
S: Steven Novella

B: Bob Novella

C: Cara Santa Maria

J: Jay Novella

Quote of the Week

People can be extremely intelligent, have taken a critical thinking course, and know logic inside and out. Yet they may just become clever debaters, not critical thinkers, because they are unwilling to look at their own biases.

Carole Wade, American cognitive psychologist


Links
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Show Notes
Forum Discussion

Introduction, Steve's coyote sighting, Rogues’ dogs[edit]

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, December 6th, 2023, and this is your host, Steven Novella. Joining me this week are Bob Novella...

B: Hey, everybody!

S: Cara Santa Maria...

C: Howdy.

S: ...and Jay Novella.

E: Hey, guys.

S: Evan is out this week. As we said, Evan just had his surgery yesterday, and apparently everything went well. He is recovering.

B: I can't wait to find out if he gets stronger.

S: You think he got stronger?

J: Right, Bob? That kind of blew my mind when he said that after they do the surgery, because of mechanically what's changed, that he actually might be a little stronger. Like that's-

S: No, it's not that he's going to be physically stronger. It's that the connection of the ligament to the bone would be stronger.

B: The mechanical advantage, right? He'll have a more mechanical advantage.

S: No, I just think it's going to be a tighter connection between the ligament and the bone.

C: It's going to be less likely to snap like it did this time, which is a good thing.

J: Well, we've got to ask him because I'm not 100% sure.

S: Don't listen to me. What do I know? (Cara laughs)

J: Well, he's not a freaking surgeon, you know?

S: I know, but how's it going to make his muscles stronger? It's just going to the connection-

B: Yeah, but the muscle, the pure muscle itself wouldn't be stronger. But if you-

C: He'll be weaker. He's going to need rehab.

B: Yeah, but I'm just talking about, I'm just saying that muscle strength isn't purely dependent on the muscle. The attachment point also can confer a mechanical advantage, lower-

S: You don't think that it's an evolved or optimal mechanical advantage already?

C: And you don't think that muscle strength is not a significant difference, that muscle strength overrides that, if that makes sense? Even if somebody else had that mechanical advantage, would you even know?

S: I just think it's the connection that's going to be stronger. That's it.

C: It's like saying, I got a fake knee. My knee is stronger because it's made of metal.

S: Yeah, it's titanium.

C: Like, of course it's stronger.

B: I would think that if you moved it, it could potentially be stronger. If you go up the arm a little bit, you'll have a better mechanical advantage. Maybe it's only five pounds stronger, but the mechanical advantage could be attained.

S: Yeah, but I don't think that's what everyone was saying.

B: All right. Well, that's what I'm saying.

S: You're just wishful thinking, Bob. You just want to-

C: So basically, Evan is a cyborg now. Is that what we're saying?

S: Evan is a cyborg. He is absolutely a cyborg. No question.

C: That's cool.

S: So guys, I had another nature encounter in my yard today.

J: Oh, boy.

S: It was just this morning. So my wife and I were basically eating breakfast downstairs in our kitchen, and right in our backyard, in broad daylight, this is the first time we saw a coyote.

C: Oh, really? It's your first coyote?

S: No, not my first coyote. First broad daylight coyote.

C: That's interesting, because they're all broad daylight here in LA.

S: Now, usually they're very nocturnal.

C: Sometimes crepuscular. Sometimes you'll see them at night when you're walking, but in LA they have adapted to be out during the day. They do not care.

S: It's interesting.

J: So what did he want, Steve?

S: Well, he was definitely looking for food. I mean, he was sniffing all up and down our yard. So it's definitely the closest encounter I've had with a coyote. And again, first broad daylight one. Our dog was inside at the time. And then I got like a crappy picture of him through the window, then I tried to sneak onto the deck to get a closer picture, and he ran off into the woods. And then we let our dog out, and he went our dog, who's an Australian Shepherd, just went crazy. He was sniffing up and down everywhere that the coyote was, like totally on patrol, like completely patrolling the edge of our property.

B: Nice.

S: Definitely, I mean, all dogs I've had do that, I'm sure that that's just a common trait of dogs. But this dog, and I think my assumption is because he's a sheepherder, is that, I mean, he goes crazy when any predator comes anywhere near our property. You know what I mean? He definitely, I think, has an instinct to keep predators away from the area that he is protecting. Just like this is a level of behavior that's beyond any dog I've personally had before.

J: How cool is that?

S: Yeah, it's cool. Very cool.

B: Yeah. He's awesome.

J: I mean, just the achievement of selective breeding, being able to breed straight up protection behavior herding behavior like that, that's remarkable.

S: Yeah, he definitely has the herding behavior that no other dog I've had before has. He's growing out of it a little bit, but like when he was younger, he would herd everything, you know? He would try to herd the car. You know, he would herd the vacuum. You know what I mean? Like anything that moved, his instincts would kick in and he would like, you could see that he's herding it. It's just amazing. He still does it to me. Like when I'm getting the food, his food for dinner, and he's hungry, he'll like nip at my heels. Like he's trying to control where I'm going to get his food.

B: Wow. Awesome.

J: And he can't help himself.

B: When he nips my butt, what does that mean?

S: I don't know.

C: He nips your butt?

B: Just a love bite.

C: Yeah, he's probably trying to get you to go in a certain direction. A lot of herding dogs don't like it when the pack is separated. So if like two people are in one room and one's in the other room, and they're kind of wandering, they'll try and get you to go be with the other people because they're used to herding sheep.

S: Right.

C: Or cows.

J: Well, they're not. But they're not used to herding sheep.

C: Well, genetically they are. That's the interesting part.

J: That's what I mean. That's the interesting part. Like, it's not like he's ever even seen a sheep, but he's genetically imprinted to do all of these behaviors. That's why like, it's funny, but like most dogs, they have a purpose. The breed has a purpose.

C: Yeah. Yeah. Yeah. Most breeds.

J: I don't know how many animals are out there that are bred to hang out in your house. Most dogs are work dogs.

C: Yeah. And it's interesting because all domesticates are like that, really. They're bred for a specific purpose. Some of them are behavioral. Some of them are more like just their body they're bred for food or something. So Steve, is this your first herding dog?

S: Yeah. Yes.

C: So I have friends who have, like I have a lot of friends who have herding dogs, and a lot of their dogs are really, really intelligent, but also really, really neurotic.

S: That's him.

C: Does your dog have any neuroses?

S: Totally. Absolutely. He's very smart and also very stubborn and just has these weird neurotic behaviors that we are trying to figure out. Over time, he's getting better, but at the, in the evening when we were calling him in for the last time, because we're going to go to bed and he knows, he always knows exactly what's happening. And he's like, he's sitting out in the front yard and I call him in. He just looks at me, just sits there and looks at me. And you know, it's getting better, but to some extent, like I have to go out at least a little bit and then he'll come in. He won't just answer the call. We've read online that that's the breed. The breed absolutely does that.

J: Except when my dog is over, Steve.

S: When your dog is over, yeah.

J: Because you call my dog in and then he follows.

S: Exactly right. It's a little bit easier because yeah, I just call Lando in and then Sagan will follow.

B: So Steve, if you call Sagan in like mid-afternoon, he'll just come in?

S: Yeah.

B: No problem?

S: Yeah. I mean dogs, remember, they're partly self-domesticated and a lot of their domestication is just being socially attuned to humans. And of course we get attuned to him. And I remember at one point, like my wife is telling me all the things that she does to get him to come inside. I'm like, you realize that he's training you more than you're training him. Like he's totally, she's jumping through all these hoops to get him to do exactly what she wants him to do.

B: And he's giggling inside.

S: But like if we're going to take him for a walk, we just start getting ready to go for the walk. And he could be very subtle. He knows exactly what's happening. He knows we're about to take him on a walk. Even if I'm just like changing my shoes or whatever, like he knows that's what's happening. And then he gets all excited and everything.

C: Yeah, I have a friend whose, his dog, her dog is especially smart. Like probably one of the smartest dogs I've ever seen, but has so many weird things and learns associations really quickly. So like one time the dog was in bed and a firecracker went off. So now bed is danger and like will not get in bed again. And like now has to sleep in different places. So like really easy to associate things and really hard to disassociate them. So she just has to do a lot of training with this dog, but it's one of the best dogs I've ever seen. My dog was staying at her house and she put down food for my dog and her dog went up to eat it. And she was like, not for you. One time. Dog never came back to my dog's bowl. And I was like, I could never teach my dog to do that. He'd be like, that is food on the floor. It is for me. Clearly.

S: No, he's, he's well-disciplined in that way too. We had our previous dog, yeah, my previous dog was a golden retriever. He's very sweet, but a total goofball and pretty much untrainable. I mean, not I was trained and everything, but like in terms of like inhibiting his own behavior, forget about it. There's this wonderful video we saw on YouTube where they show, it's like a dog contest. And one of the things was the dog walking down the long aisle of distractions, right? And like there's food and a toy and whatever, and they have to ignore all of that and go from one end to the other. And then they show like a golden retriever doing it. And he went for every single distraction, was completely undisciplined, just a total goofball. I'm like, that's, that's my dog. That is completely my dog.

C: But the funny thing is a lot of labs and golden retrievers are very trained, like they're often used for, for helping dogs, like service dogs.

S: Yeah. Oh yeah. He was very smart. And so we could, we could train him, but, but inhibiting his behavior in that way, no, but my, my Australian Shepherd dog, my current dog is very disciplined. You know, once you get him to do what you want to do, like we have an invisible fence to it. Like almost instantly trained him. Like he just one time we had to tell him, this is the limit, like, don't go beyond this limit. I don't think he even ever had to get shocked and he like completely knows how to, to stay within the limit. In fact when we take him for walks, like again, he has this weird behavior and we have to figure out what's going on in his head. Like why is he doing what he's doing? And one of the things we figured out is that if he gets to any barrier that reminds him of the edge of our property, he won't go near it. He won't go near it. But, but it's weird, like which barriers trigger that for him and which ones don't. Cause we live at a cul-de-sac. So every time we get to a cul-de-sac, like he gets scared and won't go any beyond a certain point.

B: Yeah, I can relate to that. Jay and I talk about it a lot. It's like, we're, we're like what's happening in Steve's head? What is he, why is he doing what he's doing? You know, it's like, come on.

S: It's unfathomable.

C: Ooh, you should, I'd be curious. So my friend who has this super smart dog, she, and she's really interested in dog training and stuff. So they have a lot of fun together. She taught him, he knows about, gosh, I'm probably misspeaking here, 10 of his toys by name. So she can say, go get the axolotl or like go get the whale and he'll run into the other room and retrieve the correct toy.

J: That's awesome.

C: It's really cool. Like you could probably do some pretty cool experiments with your dog.

B: I've seen the champ at that test and he actually was able, his record was something crazy, like 150.

C: Yeah, it was a lot.

B: It was crazy.

C: It was that research dog, I remember.

B: Oh my God.

C: Uh huh. It was very cool.

S: Yeah, they have a high neuronal density.

J: My dog is by far the best dog I've ever met in my life.

B: He's a gem. He is a gem.

S: Yeah, he's a sweetheart. Totally desperate for attention.

C: I say the same thing about Killer.

S: Yeah. Although Jay, your dog, man, we still haven't been able to train him to go for a walk properly. He constantly wants to pull on the leash and haven't been able to break him of that. But again, we only get him for a few days at a time, you know what I mean? We haven't been able to do it consistently.

J: Yeah, but we have a hike with him and I can get him, like he needs like 10 minutes to be excited and then he chills out and he slacks on the leash. But yeah, I know exactly what you're saying. And he's super strong. Like he's got a very powerful body, you know?

S: Yeah. It's a totally different workout when you're walking with him. All right, guys, let's go on with the show.

Quickie with Bob: Ceramic Storage (12:19)[edit]

S: Bob, you're going to start us off with a quickie.

B: Sure. Thank you, Steve. This is your quickie with Bob. Ceramics in the news this week. But this ceramic is laser etched with data that the startup company Cerabyte claims is ideal for long-term cold storage. It's fast and dense and inexpensive and rugged all at the same time, which is saying something. Guys, they say this tech could make 10,000 terabyte palm sized cartridges that last for 5,000 years.

S: Is that all?

B: 5,000. They even launched a demo of a fully operational prototype system. The tech is cool. The cartridge contains a layer of tough glass similar to Gorilla Glass and thin layers of ceramic 50 to 100 atoms thick. The data is then etched. Get this, 2 million femtosecond laser beamlets that creates patterns in the ceramic, not unlike a QR code. Their initial product in 2024, I mean, just a month or so from now, should have a 10 petabyte capacity followed by the next gen, which would be 100 petabytes. And then they say in the next decade, they plan on using particle beams to etch the data, potentially reaching a terabyte or more per square millimetre. Incredible density there. Similarly, their transfer speeds are expected to improve from the gigabit per second range to terabit per second range using that particle beam. So amazing archival storage if this really, really does pan out. And we all know that data stored on tapes, hard drives, disks, et cetera, they're at serious risk. Once you get to, what, five years, 10 years? By then, if you haven't looked at it in 10 years, you're pretty much guaranteed there's going to be some serious data dropout. Longer than that, I mean, you got to be, you got to be redoing your storage on archive. I mean, you should be doing it sooner than five years. So if this is true, 5,000 years, I mean, ceramic is amazing. They were inspired by ceramic artefacts that have retained micro scale marks on them like fingerprints for thousands of years. So it is an amazing medium. So we'll see if anything pans out. This has been your quickie with Bob. Back to you, Steve.

S: So, Bob, these are not rewritable, right? This is just, they etch it once and that's it.

B: Yeah. Yeah.

S: So this would be for archiving or backup or-

B: Exactly. Archival, long-term, cold storage of data. I mean, it's they say 5,000 years, which is pretty ridiculous. I mean, if it lasts, just imagine just a generation, 20, 30, 40 years, which it should. I mean, the ceramic is designed to last. So I hope it pans out.

J: Bob, like how do you actually read it though? Like you have to have a special reader or, you know?

B: Yeah. It's got these micro optical readers to read it, but they can apparently do it pretty fast as well. That's what they're claiming. So their prototype, their fully operational prototype, like I said, it was supposedly fully operational, but it didn't have the maximum density that they say their first generation of the 10 petabyte first gen will have in 2024 sometime. Cerabyte, keep an eye on the company, C-E-R-A-B-Y-T-E.

S: All right. Thanks, Bob.

News Items[edit]

Quantum Gravity (15:35)[edit]

S: So Bob, I was a little surprised you didn't choose to do this news item this week.

B: Oh man. Almost. I came so close. I was going to do it next week.

S: But I'm sure you'll have some stuff to add. So you guys are familiar with probably the biggest scientific question, at least in the world of physics, which is how do we unite quantum mechanics and general relativity, right? So we have quantum mechanics, which deals with the world of the very tiny, atomic, subatomic. And essentially, it tells us that the world at that scale is quantized, like there are quanta of energy, there are things that you can't get smaller than, and that the universe is probabilistic at that level, right? There aren't particles, there are waves, and there are probability waves, et cetera. That's the world of quantum mechanics.

B: That's what Einstein hated, his famous quote, God doesn't throw dice. He hated that. And he was wrong.

S: And then there's general relativity, which deals with the super big scale of the universe, and that deals with space time. And essentially, the big concept there is that gravity is a function of curved space time, right? I can't remember who said this, but I might remember that matter tells space time how to curve, and space time tells matter how to move. So if the Earth is going around the sun, the Earth is actually traveling in a straight line, but it's going in a straight line through curved space. And that curved space takes it, is a path that is the orbit of the Earth around the sun, right?

B: Right. So Steve, one of the ways to distinguish quantum mechanics from general relativity is that the wave equations in quantum mechanics are defined on a fixed space time, whereas general relativity says that space time is dynamics. That's one of these head-butting areas that why it's so hard to join these two together.

S: That's right. And just mathematically, the equations don't match. And so what that means is that if we ever have a situation where relativistic effects and quantum effects are both significant, we can't resolve that. So for example within a black hole, for example, where you might have both relativistic and quantum effects at the same time, we don't know how to deal with that because we need a theory of quantum gravity, and we don't have one. Jay, do you know offhand what the two leading theories of how to unite quantum mechanics and gravity, general relativity are?

J: Yeah. I mean, someone just needs to take them to a bar and let them talk it out, you know?

S: How about you, Cara? So have you heard of string theory?

J: Of course.

S: Yep. So that's one, right? So string theory on one level is an attempt at uniting quantum mechanics and general relativity. And string theory says that at its most fundamental level, particles are actually little vibrating strings and that those vibrating strings are what are like the most fundamental building block of stuff.

J: But Steve, is that a way to visualize it? Or is that like what they're really saying?

S: It's a mathematical construct, right? It's just it's a mathematical, it's math. And as, and we've had this discussion, I think, with Brian and other physicists on the show, saying, does string theory, is it testable, does it say anything about the way the universe actually works? It's like, well, it has some utility. As a theory, it does help you do the math to work out some things about reality. That's not the same thing as testing it to see whether or not it's actually a true description of reality. The other competing theory, which I don't think gets as much play in the press, in the popular media, is loop quantum gravity. And loop quantum gravity says, it basically treats spacetime at the quantum scale as tiny loops, right? Well, string theory deals with point particles as if they were strings. So is reality loopy or stringy? That's what it comes down to.

B: It's fieldy.

S: So now for the first time, since I can remember, right, the first time we have a third competitor in this field, trying to unite these two. And this is called post quantum theory of classical gravity. There were two papers recently published going over this idea. And the idea here is that in trying to unite spacetime and quantum mechanics, that spacetime, we can actually treat spacetime and gravity as if they are classical, meaning that they're not quantized as they would need to be in order to mesh with quantum mechanics. But rather than trying to quantize gravity, this theory, the post quantum theory of classical gravity, states it tries to unite the two by modifying quantum mechanics. And here's a quote now. The theory "Modifies quantum theory and predicts an intrinsic breakdown in predictability that is mediated by spacetime itself." So what this deals with is the fact that at the quantum level, there is a certain unpredictability to reality. You guys are familiar with that concept. And that there's like this boiling ocean of quantum foam of unpredictability that exists to reality itself, to the fact that if you tried to measure a mass, if you had an unchanging mass, it actually would be variable, it would be fluctuating at the quantum level. But you would need to measure that mass really precisely. Orders of magnitude more precisely than we currently can in order to detect that the quantum fluctuations in the mass of that object, right? Now what this new theory, this post quantum theory states is that that variability is increased, right? It's greater than it would be with either loop quantum gravity or string theory. And so what that means, something very important, that means that this theory is testable, right? It's possible to conduct an experiment that rules it out. And that experiment there's two experiments that they present in the papers. One experiment is the fluctuation experiment, basically measuring just more precisely than we ever currently have the fluctuation in a physical property, like the mass of a fixed object. If they are smaller than a certain size, if the fluctuations are small, that rules out the post quantum theory. If they're bigger than a certain amount, they argue that rules out both loop quantum gravity and string theory. And so if we can see a way to conduct this experiment, we actually won't give us what the answer is, but at least it enables us to rule out some of these theories. The other way to test the theory is to determine how long particles can be in a superposition. So you know how a particle could be both a wave and a particle at the same time, right? Or it could be in a superposition of multiple states. And the bigger the object, the smaller the amount of time it could remain in the superposition. So one way to think about quantum mechanics is that it exists at every scale, like quantum effects exist. We are quantum creatures. It's just that the quantum effects at macroscopic scales are unmeasurable. They're just, they're like way down, you're getting close to the Planck length, you know. They're very, very, very tiny. So what they're saying here is that if you measure the sort of quantum effects of particles, this basically superposition, this post-quantum theory predicts that a large particle, I say large, I'm not talking macroscopic, I'm talking about like a large molecule versus just an atom or a subatomic particle, a large molecule would be able to remain in superposition for longer than under loop quantum gravity or string theory. Is that your understanding of it as well, Bob? Because again, we're trying to decipher pretty technical paper.

B: Yeah. For me, the biggest sticking point was this probabilistic mechanism and how that works. So let me just give a quick overview from another angle because as you know, Steve, there's a million different ways that this can be described. And sometimes you hit upon a description that makes it gel in your head. So for a quick, just a basic overview, the loop quantum gravity and string theory, they try to quantize gravity. This new idea, this new theory leaves gravity as a classical theory, does not quantize gravity and it couples it to quantum theory through this whole idea of this probabilistic mechanism. So what that means is that the evolution of space and time itself has these probabilistic elements embedded in it that you can't do anything about. They will always be probabilistic and you won't be able to make unique predictions about future states. That's what it means. And one of the challenges of this though is that some things change. We have a loss of quantum information in a black hole in this theory, which a lot of astrophysicists are going to be like, whoa, quantum information is lost? That's not supposed to be that way. So that's a challenge that they're going to have to deal with. But they did get rid of a lot of the problems that this approach had. And so that's an interesting thing. But as you said, Steve, the most important takeaway here is that we have serious tests which have been lacking for all these other theories. And hopefully soon, 10, 20 years, hopefully sooner, they'll be able to do a serious test, not to prove really one or the other, but to essentially rule out one or the other. So that would be an amazing step right there, even if it's just ruling out something.

S: The authors in an interview said they think it'll take 20 years to conduct these experiments. Which to me always means, I always just double it in my head. It's like, okay, that means 30, 40 years, we'll probably have the results of these experiments. But yeah, but it's decades. It's not going to be something that we're going to know in a year or two. It's going to take a long time to get to the point where we can test it. And you know, there are, we've spoken about, like with the Higgs boson, where somebody comes up with an idea, and then it's 50 years later before we do the definitive test to know if it exists or not. So that kind of thing would not surprise me. But this is this really is a very, very tough problem to hack. This is a generational physics problem, really. This idea of uniting quantum mechanics and general relativity. And it's important because it really is a sticking point in trying to go forward here. And there are, we come up with questions all the time, like, is artificial gravity possible? It's like, well, probably not, but we won't know for sure until we have a theory of quantum gravity. You know what I mean?

B: I've read the same in terms of addressing, can we travel into the past? The answer is typically, probably not, almost definitely not, but we won't know for sure until we develop quantum gravity. Like, okay.

S: Right. It leaves the door cracked open a little bit, depending on the-

B: A crack. Tiny crack.

S: A crack. Yeah, yeah, yeah. But how amazing would it be if the, when we do come up with a theory of quantum gravity, that door is cracked open?

J: If we develop anti-gravity, that means we can build the Millennium Falcon.

S: That's right.

B: Well-

S: Anti-gravity is a game changer. Right? When we wrote our futurism book, we basically had to say, like, there's one future with anti-gravity, and there's another future without anti-gravity. And they're very, very different in terms of super advanced technology. And most of science fiction behaves as if anti-gravity is possible, but in reality, it probably isn't, which means space travel is always going to suck, and it's always going to be difficult getting off of planets, like getting out of gravity wells, and there never will be anything like the Millennium Falcon. That's probably the actual future that will exist. You know, that's the reality. But yeah, it would be, certainly would be awfully nice if we could just float off into space.

B: Yeah. Well, I'll put my dime down right now. Anti-gravity is not going to happen.

S: Yeah, I agree.

B: Because gravity, by its very definition, is dynamic. Therefore, you won't be able to have an anti-gravity anything. It's just not going to happen. The only, the only tiniest hope we had was if that antimatter fell off. That didn't happen. So, I mean, it's just like, that's not, that's the biggest hand-wavium bit of sci-fi out there. It's a top, top five.

S: No, it's true. It's true. One thing completely changes almost every bit of science fiction about the future.

J: Yeah, you're totally right.

B: Yeah I'm okay. You know, throw your gravity plating in your ship, I guess, you know. But it's just don't, I'm not I'm not looking forward to it.

S: Right.

XPRIZE for Health Span (28:41)[edit]

S: All right, Jay, tell us about this new XPRIZE for Healthspan.

J: Yeah, like if this works out, Steve, then we might be around long enough to see anti-gravity. Yeah, you guys have heard about the XPRIZE. Bob and I are big fans of it. I keep referring back to the XPRIZE that they did where they, awarding really big money prizes to companies that develop some type of self-driving car this was the beginning of that whole, all of that technology. So the XPRIZE Foundation does a really good job at inspiring companies to try to reach technological goals by awarding them huge amounts of money if they can actually get to a certain bar. So in this instance, this is a pretty groundbreaking competition that they came up with. It's called XPRIZE Healthspan. So XPRIZE will be awarding $101 million US dollars. That's the total purse. To organizations whose researchers are working on drugs and other therapies and lifestyle strategies that would rejuvenate human biology. Specifically, they want methods that will extend how long a person can live in a biologically healthy state, something they're calling a person's healthspan. This is going to be a word that if you haven't heard of yet, you'll start hearing it. It's going to be used more and more. So the healthspan-

B: Nobody wants to be old and decrepit at 120. They want to make they want to make you be healthy from 80 to 90, 80 to 100 or whatever, where you're healthy and active, and then you have a very short period of decline and die and not have decades of decline and decrepitude.That's the goal.

J: Absolutely. Yeah. So at its core, it means a life free of disease and disability until the bitter end, right? So right at the end. So applicants have to show-

B: Until the heat death.

J: Applicants have to show research that targets restoring muscle and cognition and restores immune system function of elderly individuals to essentially a more youthful state. The competition is sponsored primarily by a guy called Chip Wilson. He's the founder of Lululemon and Athletica. These are two clothing brands, by the way. It's also sponsored by an organization called Hevolution Foundation, and this is pretty cool. I just found out about this foundation. The Hevolution Foundation is an organization that at its core, it funds research that specifically targets healthspan. They give money to companies to further their research and development on lots of different things, but they're all surrounded they're all about the concept of healthspan. So breakthroughs in this area could significantly improve the quality of life for ageing individuals, but also help prevent chronic diseases that are closely associated with ageing. Healthcare systems worldwide are facing a horribly important milestone, which is there's an older population, and the older population needs special care and more procedures and medicine and everything, and as those numbers go up, there aren't enough people in the healthcare industry to support the amount of old people that exist now and that will exist in the next 10, 20, and 30 years, and the numbers are going to keep going up from where they are today.

S: Won't this make the problem worse if people are living longer?

J: Well, I think from what Bob was saying, like people will live... It's not about life extension. It's about improving your healthspan, which is improving the quality of your life that you have.

S: But do they really distinguish those two things, or do they want both?

J: I mean, from my read, Steve, it's more about the quality of life that you have and not about increasing it.

S: What does the XPRIZE say? What does it actually say? Can you tell us?

J: So what the XPRIZE is saying is they're talking specifically about healthspan, right? And healthspan, if you read it, read the definition of it, at its core, it's improving quality of life while you're alive. It really isn't about like, hey, let's add 30 years to the human lifespan. Let's improve the quality of life in the last 20 to 30 years.

S: But then my question is, how are they going to quantify that?

C: Exactly.

J: Well, let me tell you. I have more information for you. So the competition right now is structured to award varying prize amounts, and those prize amounts depend on the achievements that the research teams get to. So the largest prize, $81 million. This will go to one of the research teams that can compensate for age-related declines in muscle use and cognitive abilities and immunity by 20 years. So to clarify, because it was a little unclear, saying that they want to be able to essentially make people like, let's say you give people these treatments and they're 60 years old, they want their physicality to be closer to a 40-year-old. And then it goes down from there. So if they can do a 15-year improvement, that'll be $71 million. If they could do a 10-year improvement, that'll be $61 million. So the XPRIZE Healthspan Initiative follows a series of ageing research competitions. Now, this includes the Methuselah Foundation's mPRIZE. This is for therapies extending the lifespan in mice. We also have the National Academy of Medicine, which was providing Catalyst Awards since 2019. And this totaled about $30 million globally for advances in health ageing research. So researchers entering the competition, the new competition, will need to submit information about their existing research, and this is going to include things like data from cell and animal and human studies. And those whose submissions meet the XPRIZE's criteria for safety, feasibility, and effectiveness, they will be selected as semifinalists and they will move on to the clinical trials that are going to start. They're saying now it'll start in 2026. There are some critics of this XPRIZE, and they're saying, and these are scientists, and they're saying that they've raised concerns about this one-year timeline for the clinical trials. And I agree with them. They're saying that the timeframe could be too short to prove a long-term effect necessary for like a drug approval, as an example, right?

C: Well, not just that. How do you know how it's going to affect ageing if you don't give people time to age?

J: Yeah, I agree. I mean, I think because they're going to be looking at it in multiple different ways that they can extrapolate, but I agree, Cara. It's not clear from what I read, what they're saying is not perfectly clear, but you got to keep in mind, I don't disagree with the critics and there's always critics and we should always be mindful of looking at it from the other side and trying to shoot holes in it. But at its core, the XPRIZE is trying to deliver money to companies and organizations and research facilities to help inspire new technology, make quicker advancements. That's the whole point. And that's what they're doing. It just happens to be a health-related one this time. So I'm all for it. I really hope that they fashion it in the best way that it can for the timeframes that they have. But I'm kind of excited about it too, because when this happens, companies jump in and other investors invest in those companies so they can get to the prize and it usually ends up creating new technologies that advance humanity. So I am all for the efforts of XPRIZE and I'll be definitely following this one.

B: Yeah, just from a purely money savings point of view, imagine if they're even partially successful. Imagine what they could save in healthcare costs, like in the billions or more. It's really-

S: But it's not organized specifically to accomplish that. You're just hoping that's going to be a side effect.

C: Yeah, that's the thing that bugs me about this kind of approach. I do like it when there's more incentivization for innovation like this, but it's not like people aren't already doing this. It's not like this is the first time people thought, oh, increase health years or whatever. Every biomedical approach is keeping that in mind.

J: Oh, well, Cara, let me clarify-

B: This is being incentivized though. I mean, you said that was good.

C: Yeah, exactly. It's an incentivization. Yeah.

J: These aren't new companies that are applying. All of the research facilities and companies and organizations that would apply for this, they have to have already... They're already in the research thing. They're already doing it. They're going to be submitting their research to the XPRIZE and then the XPRIZE is going to pick the ones that they feel that have the most possibility. But this isn't like new companies going, hey, we're going to all of a sudden start a company to do this.

C: Right. They've been doing this.

J: Yeah. They're just taking the best ones. They're running them through a series of tests to really figure out which are the best of the best here. Then they're essentially saying, we're going to give you money if you can get to these benchmarks, which is really, it is. It's just incentivizing them to get to those benchmarks faster than they may have normally done on their own.

B: It's funny, because even though we're talking millions of dollars, if they really did make a serious breakthrough, the money that they could potentially get from that would be far exceed even the millions that they would get from this.

S: That's the thing. There kind of already is an incentive structure built in here. In that, if you do have an innovation, especially if it's a drug, it could be a billion dollar drug. The $100 million is not a significant addition to that, and probably the research you'd have to fund in order to win the prize is going to be more than that.

C: That I agree with. The research you'd have to fund outstrips it, but I disagree that our incentive, you're right in the long term we have that incentivization structure, but we know that capitalism isn't built for the long term.

B: Short term.

C: It's short term. So having bragging rights and a little bit of extra, like, ooh, we are XPRIZE winners, maybe then a pharma company would say, okay, we can actually invest in this division that we've not really been investing in before.

S: Yeah, I see that. I mean, I'm always a little hesitant about things like this. I'm a fan of the XPRIZE in general, and I think they work best when they are basically incentivizing kickstarting a new technology, like they did that with self-driving cars. That probably accelerated the development of self-driving technology by a decade because of the XPRIZE. That kind of thing is great. In here, I'm just not sure that their goal is properly focused or optimally focused. I'm still left wondering, what exactly are they going to be researching? If the goal is to save healthcare dollars, you could frame the incentive or the research more of developing interventions that save healthcare dollars, right? That is the outcome measure you are using. You're going to replace a super expensive tech process or treatment or whatever with something that costs an order of magnitude less, which I think would be a great idea because right now, that's not how our research is incentivized. Our research is largely incentivized for expensive treatments with incremental improvements. The incremental improvements aren't great, and you do have to think of cost effectiveness. There is on grants and everything, they are looking at that more, but still, I think there are times where we could be doing research in order to develop a treatment that's no better than existing treatments in terms of outcomes, but that just costs a lot less. I don't really see a lot of that happening. I think we're underestimating how important that is because we already basically can't afford to pay for healthcare, and so if we give ourselves even more expensive healthcare that we can't afford, what are we really buying? I don't think we've balanced it well, our research priorities well enough to also emphasize cost effectiveness, and it's biting us in the ass, you know what I mean?

C: That's why something like this, I think, is a little bit... I don't want to call it fringe, but it's a little bit... It's like additive because it's sexy. They want something sexy, and what you're talking about isn't sexy.

S: No, I know it isn't. It's maximally not sexy, which is why it doesn't get done, but it is super, super important. I spoke about, previously, not too long ago, about the monoclonal antibodies, which are awesome. I prescribe them all the time, but they're, oh, great, so now we have a technology where we just have really expensive drugs. Yes, they're effective, but now it's like, no, I'm-

C: Does that really mean anything if nobody can use them?

S: Well, it is like, now, okay, oh, great, now I can prescribe a drug for migraine patients that cost $6,000 a year instead of the $100 a year drugs. That's great, and when you need it, you need it, and it's awesome, and it can be cost effective in very, in certain patients, like if they're winding up in the ER once a month, it's very cost effective, but believe me, a lot of people are getting it where it's not cost effective, but it is clinically effective. If we're not balancing those two things, we just basically end up with either you live in a country with nationalized healthcare, they're going to ration it, they're just not going to pay for it. You live in a country like the United States, insurance companies are going to totally clamp down on it and raise all kinds of barriers to prescribing it, and the healthcare costs go up as they have been.

C: Or you have a hybrid model where there's nationalized healthcare where, yes, some things have to be rationed, but then you have a free market, but that free market is competing with a national service which is keeping prices low.

S: That's complicated. It is all complicated. Again, I hope something good comes out of this. I hope if you, again, I'm still not clear on exactly what they're going to be doing. One of their outcomes is you'll get your immune system to function like a 40-year-old when you're 60. How exactly are you going to be measuring that? What's the clinical outcome of that? I think it's just for an XPRIZE, it's all a bit fuzzy to me, but we'll see how it goes.

ECT Heals the Brain (44:29)[edit]

S: All right, Cara.

C: Yes.

S: Tell us about electroconvulsive therapy.

C: You may or may not have heard of electroconvulsive therapy, also known as ECT. Historically, you probably heard the other name that people used, which was electroshock therapy. To be fair, electroshock therapy historically is relatively different from what we now call electroconvulsive therapy, but they are kind of based on the same principles. As somebody who works in psychology, I have patients who have had ECT. I have patients who have refused ECT and everything in between. Looking at the literature about ECT, it's really interesting. This is sort of to prime the story here. We know that ECT works. We know it's effective. We know that patients who undergo electroconvulsive therapy, most of them feel better. Their depression symptoms are lessened, and they're lessened significantly. We're talking somewhere in the area of like 80% of patients who undergo this treatment, and usually they get this for what we call treatment-resistant depression. They've tried a few different drugs, and they haven't had the relief that they are hoping for. We know that about 80% of patients who undergo this get up to 50% reduction in depressive symptoms. For anybody listening who has ever dealt with clinical depression, a 50% reduction in depressive symptoms could be the difference between suicidality and functionality. That's a lot. That's big.

S: That's huge.

C: It's huge.

J: I would even exaggerate that a little bit by saying a 50% improvement could be the difference between actually living a life that you do find enjoyment in. If the depression goes down that much, it sounds to me like you'd be having some good days in the mix.

S: It's also, Jay, it's basically, and this is how it's mainly used, it's the difference between functioning and not functioning.

C: 100%.

S: Being in bed, unfunctional, versus getting out there and going to work and raising your kids or whatever.

C: Yeah, absolutely. This is really, really significant for a lot of people, yet it's just not commonly utilized. The researchers in this new study were interested in a couple of things. They were interested first in discussing why it is that we don't utilize it much, even though we know it works, but B, getting past that, what actually happens in ECT? The question of why we don't utilize it much, it probably is deeply related to stigma. I think that there are a lot of media representations of ECT that-

S: One Flew Over the Cuckoo's Nest?

C: Yeah, One Flew Over the Cuckoo's Nest, where they make it look like a lobotomy. They really don't represent, and they show it as punitive, and they really don't represent it as a success story. I'm thinking of Requiem for a Dream, the Aronofsky film, when Ellen Bernstein's character gets ECT, and she's awake while she's getting it, which is not how it's done. Just the actual representation, I think, is quite stigmatizing. But beyond that, how does it work? It's so funny. Leading up to do this news item, I was talking to my friend on the phone. As I told you, I was listening to the article, and I was driving, and I was stuck in a lot of LA traffic today. She was like, what are you going to talk about? I was like, ECT. She was like, how does ECT work? I was like, well, it's interesting, because it sort of, imagine a seizure, which is a bunch of neural activity all at once, all happening at the same time, which is really, really dangerous. It can be damaging to your brain tissue, but when done in a controlled way, sort of resets these synapses, right? All these things are firing at the same time. They're not used to doing that, so it sort of resets. She's like, how? I'm like, I don't know. It was so funny, because I started thinking deeply about it, and I was like, I feel like I know this stuff, but I don't really know this stuff. I start reading into it more, and everybody's like, yeah, we don't really know how. We say it resets brain activity, but what does that actually mean? Often times, that leaves patients, and even physicians, wanting for more of an explanation. These researchers, who have a very specific interest in a certain type of brain activity, wanted to dig a little bit deeper. This takes a little bit of background, but I'm going to try and keep it simple. When we look at EEG, which is a readout of brain waves, which you get by putting electrodes on the scalp, so it's a non-invasive way to look at brain activity. It's an electroencephalogram. It's like what I did when I had my sleep study. I had all these wires on my head all night. It looks to see if I'm in REM sleep, or what different waves my brain is producing, so the electrical activity. When you look at an EEG, we see that there's a lot of different types of electrical activity, but we can broadly divide it into two types. We've got the brain waves that we're used to seeing, which are synchronized brain waves. They oscillate. There's a periodicity, a pattern to them. Then there's asynchronous, or aperiodic activity, which historically we've always thought of as noise. Most researchers, they see that on an EEG, or not even researchers, clinicians, and they just say, okay, throw away the noise. I'm looking for the signal. They focus on the oscillations. They focus on the reproducible, measurable patterns in brain activity, and say, okay, this is obviously a delta wave, or this is an alpha wave, or whatever. These researchers are actually fundamentally interested in asynchronous, or aperiodic activity. What often we thought of as noise, they're saying, maybe there's actually a signal there that's important. They started to look back at all of the historical data, and they did their own studies where they looked at recent patients who underwent both ECG, electroconvulsive therapy, and something called MCG, which is magnetic convulsive therapy, or sorry, MST. What does the S stand for? Because it's basically ECT.

S: Magnetic stimulation therapy.

C: Stimulation therapy. Thank you. But it still induces a convulsion. I guess they wanted to change the branding a little bit there. So MST-

S: But it is a completely different thing. It's so much gentler.

C: Yeah. It's using magnets. And actually, that translates in a minute to their outcomes, which is interesting. But magnetic stimulation therapy is using magnets instead of electricity to induce smaller, basically, less severe seizure activity, or convulsions. So they looked at one study with MST patients, two studies with ECT patients, small sample size, because there always are small sample sizes with this kind of intervention. And instead of looking at the oscillations, because historically, everybody was connecting the oscillations to the improvement or the reduction in depressive symptoms following ECT, they said, let's actually look at the aperiodic activity. Let's look at the brainwaves that we usually would just throw away as background noise. And part of the reason they did that is because nobody's really been satisfied with looking at the oscillations. They find that there's no real relationship, or no predictable, discernible relationship between a change in the oscillation patterns and a reduction in depressive symptoms. So people who are endorsing less depressive symptoms after ECT don't necessarily have higher or lower oscillations. It's kind of all over the map. So they're like, maybe there's something else going on here. So they dig into the aperiodic activity. They utilize a different approach, because sometimes it's really hard to distinguish the two. So they utilize a different approach to say, okay, we're pretty confident to say this is aperiodic activity. But it's not noise. It's telling us something. What is it telling us? They start looking at it, and they find something interesting. Aperiodic activity increases by more than 40% on average following electroconvulsive therapy. About 16% on average following magnetic stimulation therapy. And when they ran their calculations and utilized their statistical approaches, they actually found that the oscillations, the slow oscillations that are often pointed to as responsible for that change in depressive symptomatology, that they actually don't change much at all. But that most historical data was likely misidentifying aperiodic activity as slow oscillations. They said that actually some patients after ECT didn't even have any slow oscillations detected. So what historically was thought of as the noise, which most researchers were just throwing out and not even looking at, they think that's where the signal is. And when they start translating that from these sort of research terms into clinical terms, they are using a very particular theory. And that theory is a theory of depression that's based on brain inhibition. So we know that we have inhibitory neurotransmitters. We have specific cells that are GABAergic cells that induce inhibition in the brain. We also have excitatory neurotransmitters. There's a long standing theory of depression that people with severe depression don't have enough inhibition in their brain. The inhibitory cells aren't there or there aren't enough of them or they're not working well enough. And so because of that, you get this downstream effect where certain signals are amped up too much. They're not turned off or turned down enough. And that balance seems to be really, really important according to this theory. And there are a lot of different theories of depression. But according to this theory, that balance is really important of like inhibition to activity in order to maintain a sort of healthy behavioral response to mood. And so based on that theory, which is the theory that they're operating within to do these studies, they are positing that post-ECT changes in that aperiodic activity, what we used to think of as noise, is actually changing in inhibition in the brain. So that aperiodic activity might actually be restoring that balance and improving the patient's ability to inhibit certain downstream like neurotransmitter effects. And because of that, that reset function that we often talk about might be real. So an ECT or to a lower extent or less effective but also less invasive extent, MST, induces seizure-like activity. That seizure-like activity "resets" the brain. But the way it's resetting the brain is it's increasing aperiodic brainwaves, which downstream increases inhibitory neurotransmitters or inhibitory neurons, which release more inhibitor and neurotransmitter. And because of that, there's a better basically transmission, electrical transmission balance in the brain. So that's their theory. They're trying to test it. They're showing nibbles of improvements there, but it's going to take obviously a ton more research to look into it. But it's interesting to see because historically, we just don't have a good explanation of why this works. We just know it does, which for some patients just isn't enough for them to be willing to undergo the procedure. So it's interesting. Yeah. And I think it's really helpful. The more we know, the more armed with information we are, the better we can be our own health advocates and make decisions that are healthy and good for us. And so it's nice to know that at least we can see what's going on now. We can see a change. But why that's happening, we're still a little unclear about. And how that feeds into a larger theory of depression, it's still a pretty open question.

S: It's amazing how little that answer has moved. I learned about ECT 30 years ago.

C: Mm-hmm. It's an old treatment.

S: And it's older than that. But I remember when I was in medical school learning about it, the answer was, well, we don't really know. We think it resets the brain somehow.

C: Yeah, exactly. And it's-

S: That was 30 years ago. We're basically still there.

C: And I had this epiphany when I was talking to my friend today where I was like, well, it resets the brain. She's like, but how? And I'm like, because it's like a seizure. And she's like, yeah, but how does that read? What does that mean? And I'm like-

S: You don't know.

C: And I was like, I know, but I don't know because nobody really knows. But now maybe we know a little better. And that's kind of cool.

Building New Materials with AI and Robots (57:21)[edit]

S: Bob, tell us about building new materials with AI and robots. Those are three of my favorite things.

B: Yeah, right? AI, robots, and automating scientific research in the news this week with two related research papers that were published recently in Nature, which I think will be remembered for a long time. Their titles give you an idea what I'll be talking about. Scaling Deep Learning for Materials Discovery and an Autonomous Laboratory for the Accelerated Synthesis of Novel Materials. That kind of says it all right there. Many researchers were involved here, especially Ekin Dogus-Kubuck, who leads the Materials Discovery team at Google DeepMind in London, and he was involved in both of these studies. So what is the latest with automating science with new materials discovery? As we've said in our book and on the show many times, material science, it's really one of the key drivers of technological advancement. New functional materials can give us fundamental breakthroughs across countless technologies from clean energy, information processing, batteries, photovoltaics, and even samurai swords. Right, Steve?

S: Oh, yeah.

B: So yes, new classes of functional inorganic materials and even just minor tweaks to current materials could have amazing potential benefits to me, and I suppose you guys, too, and everybody else.

J: Thanks, Bob.

B: The problem is that literally billions of different materials probably exist. Studies have been done to point to, like, yeah, there's probably billions of these inorganic materials that are atomically different, that are distinct from each other, but only a smallish subset of them are probably functional and actually really have some utility for us. Finding those functional materials is basically, like, a major goal of the entirety of solid state chemistry, but the process is really expensive and it's really time-consuming. So automating this whole process is obviously the way to go here, right? And there have been successes in the past. I hadn't heard about this one, the Materials Project at Lawrence Berkeley National Laboratory in Berkeley, California, by computationally simulating new inorganic materials and then calculating what their properties could be, they've come up with 48,000 materials that they think will be stable, that they predict, that they calculate will be stable. So that's 48,000, amazing. The new process, though, is like that, but on smart steroids mixed with meth. What does that mean? I don't know, but it sounded good. This new process involves the creation of, it's a deep learning tool called Graph Networks for Materials Exploration, and the acronym is GNOME, G-N-O-M-E, Graph Networks for Materials Exploration. So quickly again, deep learning is a type of AI that trains neural networks with data to perform tasks without explicitly programming it in, and a graph network, I haven't heard that one before, but a graph network is a type of deep learning that can infer from data that's represented by graphs. So that's kind of what we're talking about. So the researchers trained GNOME on databases of materials information, like, for example, the Materials Project at Lawrence Berkeley Lab I just mentioned, and went through the entire database of 48,000 materials, and they went through other datasets as well. The key here is that GNOME, the GNOME algorithm used active learning. Now, active learning, it's fascinating. It essentially selects the most informative examples in a dataset, right? It goes through the dataset, and it determines which ones have the most information to teach the AI, and then it improves. It improves the algorithm a little each time, and it goes through and it does it over and over, slowly increasing the efficiency and the ability of the algorithm by using this active learning process. So using that process, GNOME was able to discover over 2 million stable structures, which then was able to add 381,000 new inorganic compounds for the Materials Project. 381,000, whoa, that's a good GNOME right there. They brought the number from 48,000 to, oh yeah, just to an extra 381,000 on top of that. Damn. So Emil Merchant, he's the lead researcher on the study and Google's AI resident, he said, at the beginning of this pipeline, we were getting about 10% of the materials that we were looking for were actually stable, so 10%. By the end of training and by the end of these rounds of active learning, this efficiency number was all the way to 80%. So their efficiency went from 10% to 80% in this study that they did. Wow. And that's just the first paper. That's just the first paper. Calculating, modeling, and predicting are great, obviously, but actually making these new materials, that's where the peanut butter hits the bread, right, Cara? Is that an expression?

C: I think so. It makes sense to me.

B: I think I just made that up. What is that called? A neologism?

C: Yeah.

B: I like it. Where the peanut butter hits the bread. Okay, so where was I? Okay, so creating the new material is the obvious next step, right? You predict it. Well, let's create it. That's where the autonomous A-Lab comes in. So this is a lab called A-Lab, interesting name, A-Lab. This was created in Berkeley. It cost $2 million. It took 18 months to build it with state-of-the-art robotics. And so what these robots would do is essentially they would mix – and they're like robot arms. They're not like bipedal robots walking around doing stuff. It's just like automated arms, robot arms. So they mix varied powdered solid ingredients and other components. They put them together. They heat them and then the robots do this without human intervention. But the real innovation here is again, it's the AI. The AI is the real achievement here because the AI directs this entire process. It's trained on 30,000 published synthesis procedures. So it memorized. It went through 30,000 different ways to synthesize materials, to mix them and cook them together. Then based on that, it determines the best way to synthesize the new material that was predicted to be potentially functional and helpful for us. So it would pick the best recipe. So then it would analyze it. It would synthesize it, heat it up. It would analyze the result and if there were problems with it or say like only – say it made a gram of this stuff but less than a half of it was the material that it was actually looking for, it would then go back to using active learning and it would create a better procedure, a better recipe and it would try it again. So it would be learning over time. One guy said that this is kind of reminding him of ChatGPT of just going back and learning more and more and more. So the A-Lab did this for 17 days all by itself doing 21 experiments a day with a 71% success rate, making these predicted new materials, making them a reality, right, chefing them up, cooking them, creating the recipe, making these materials. It was 71% successful. Now humans typically – what do you think a human – if these robots did 21 experiments a day, what do you think humans can do a day?

C: Five tops?

B: This type of experiment, they're saying a human could do typically one or two experiments a day. They're doing 21, 21 a day. The researchers say that the efficiency of this process boosted – boosted the efficiency by 50 to 100 times. That's a hell of an increase. Martin Burke is a chemist at the University of Illinois in Urbana said, these two papers together represent a very important step forward in our ability to predict stable materials and then transform them into physical form in the laboratory and I think it's a powerful one-two punch which really moves the needle in that important space. So in the future, all right, what's going to happen in the future? I think it's going to be pretty amazing with this tech. It just seems so – there's so much that could happen here. In the future, I think we'll likely see researchers that will try to have the AI be even more accurate in their prediction about the physical and the chemical properties of these new materials, right? As of right now, the AI basically says, hey, here's 30,000 new inorganic materials that I predicted this week. These should be synthesized and tested. But the problem is that there's no automated lab that's going to be – or labs, plural, that's going to keep up. There's just too many. We've got tens – we've got hundreds of thousands of these new predicted materials and we do not have the labs. Even if we had dozens of automated labs, it still would be too slow because it's discovering – we're discovering so many potentially new inorganic materials that we – it's too much. So what they want to do in the future is they want the AI to say, yo, here's 30,000 new inorganic materials that I predicted this week. But these 10 right here, these are probably going to knock your socks off. I want you to – I want to synthesize these and test these 10 first. Oh, and tell Bob I said hi.

C: Right. So like a decision tree about order of operations.

B: Yeah. So what they need to do is they need to determine that. They need to be able to predict the characteristics and the properties of these predicted materials to such a degree that they could prioritize them and say, hey, here's a whole bunch of new materials that probably are functional. But here's 10 of them. Here's 20 of them or even here's 50 of them. These guys you really want to look at first because they look so promising. They really could be a real breakthrough here. So that's what they need to do because right now, a robot, an AI is saying, here's 300,000 new materials. That's great. But how do you prioritize that? It could still take us way too long. So that's where I think it needs to go. That's where they want to take it. If you haven't noticed, I think this is pretty promising. It's very exciting and I haven't said this in a while. But this automated discovery and creation process, I think it needs to have a shit ton of attention, have money thrown at it, XPRIZES, Jay. Now imagine with materials discovery, there's so much that could happen that would be gamechangers. Imagine photovoltaics and battery technology that's near the limit of what physics allows. Imagine what that could do for society. That's just two very, very easy examples. It's so promising, I think. Basically, you're automating scientific discovery. You're essentially doing years of research in a couple of weeks type of thing. With the material science, don't get me going because that's, Jay, Steve, right? We've talked about it so many times. You come up with a new fundamental class of materials, I mean, that's a game changer right there.

S: Yeah. The AI and robotic automated research is taking off. Again, the ability to do weeks, months of research in hours or days is amazing. We're already seeing it. All right. Thanks, Bob.

B: Sure, man.

From Tik Tok: Electric Car Without Charging (1:08:36)[edit]

S: I'm going to do a quick item. This is from TikTok series. As you know, every Wednesday at 1 o'clock, I record some TikTok videos and we live stream on TikTok and on Discord. There's a lot of interesting nonsense on TikTok. It's funny how each social media outlet has its own character. You know what I mean? Facebook is different than Twitter.

C: It's own brand of pseudoscience.

S: Yeah, it's different than YouTube. I'm getting a feel for the brand of nonsense on TikTok. It's bad. It's bad.

J: It's deep.

S: It's deep, yeah. Anyway, we were flagged in this one and I did record a response to it. This is a video of an African self-taught, self-made researcher called Maxwell Chikumbutso. He is claiming that he has developed an electric car that never has to be charged. So where's the energy coming from, you might be asking if you have any scientific literacy whatsoever.

C: Is it coming from braking? I know that wouldn't be enough, but.

S: No, it's not just regenerative braking, which just recovers a little bit of energy.

C: Right.

S: It can't be the energy that runs the car entirely.

C: It's not from the sun or the wind?

S: No, not solar. It's not a wind-powered car.

B: It's run by water.

S: Not burning water. It's electric car. It's running off of radio frequency waves.

J: Oh, wow.

C: No.

S: So this is a known technology. It's called energy harvesting. We've talked about it on the show [link needed]. You can harvest teeny, tiny bits of energy from the ambient radio frequencies that are all around us, and this technology is being developed to do things like operate remote tiny sensors, for example. And that's, of course, the reason why this technology fails, is not because we can't do this. The whole idea that there's energy in wireless technology and that you can convert that into electricity, this is decades old. This is nothing new. The problem is, I did a rough back-of-the-envelope calculation, so I may be off by an order of magnitude or whatever. But I said, all right, well, how much energy typically can you get from harvesting energy from electromagnetic radiation, and how much electricity is in a Tesla, in an electric car battery? And the difference is about one million times. You're dealing with, it says milli to micro watts, so let's even assume milliwatts. And you have kilowatt hours in a car battery, so milliwatts to kilowatts is a million times, right? So this thing would harvest about one millionth of the energy you would actually need to drive your car for a day.

C: Maybe he's driving a toy car.

S: No, the video shows him driving an electric car, though it's only moving at one mile an hour across the showroom floor. You know what I mean? Like he's not driving it on a road or anything. And presumably there's batteries in there, but the question is where would this energy be coming from? So when confronted with that, not that specifically, but just the idea of, well, isn't there just very small amounts of energy in radio frequency? He says, yes, but he invented something which magnifies the energy.

B: Oh, my God.

S: What does that mean? What is that? What do you mean you magnify the energy? That's no such thing. You're just adding more energy? Where's that energy coming from? So there's no answer for that. So this is pure pseudoscience. It's pure nonsense.

C: And is he asking for money?

S: Yeah, well, yes, for investors. But of course, it's all the usual conspiracy theory nonsense that then gets surrounding these claims. Because there is obvious pseudoscientific free energy type of nonsense that just the math does not work. The physics does not work. And so how do you respond to that? So one thing he says is that he tried to get a patent for the device, but you can't. They said he couldn't get a patent because the patent office, this is in the United States, does not patent free energy devices. That's right. They don't. Because they don't exist. They don't work. And then they correctly identified your gadget as a free energy device. But then he and his supporters say, well, this is just discrimination against African inventors. It's like, OK, I'm not saying that that doesn't exist or whatever. That there isn't racism in the world. It's not my point. But that's not why they're rejecting you. You're rejecting you because this device can't possibly work. And it's pseudoscience, no matter where you're from or what your background is.

C: And if anything, all you're going to do is sadly increase discrimination by trying to posit, by basically scamming people when other people who are doing legitimate work are vying for the same funding.

S: Now, I don't know if this guy's a con artist or just a crank. He smells like a crank to me. So apparently he's self-taught and he's one of these guys who taught himself engineering and everything. And so he's disconnected from reality, disconnected from the scientific community.

C: Yeah, but he's got to be, I mean, there's got to be some charlatanism in there if he's got a working prototype, because that means he's faking his prototype.

S: Yeah, no, absolutely.

C: Yeah, like he's scamming people.

S: And the comments in TikTok are like 90% credulous. They mostly are like some version of, oh, you better watch your back. They're going to try to kill you to suppress this technology and that kind of stuff. Few people are saying like, but doesn't this break the laws of physics? And you know, but yeah, it's very, the responses are very sad. A lot of scientific illiteracy going on in there. And people basically just have no idea of the physics. And so they just see the movie plot. In fact I was talking about this on TikTok also recently, the fact there's, you guys remember the movie, The Formula from the 1980s? Yeah, I know Jay, we talked about it with you, that the idea that the Nazis developed a formula for creating synthetic gasoline. And then the whole plot of the movie is the attempt of like oil executives to squash this formula because that would threaten their profits. It's like, yeah, that's complete nonsense. Because what formula could possibly exist? Like where would all the energy be coming from to create because gasoline has a lot of energy in it and that energy is stored. It's a source of energy.

B: It's very energy dense.

S: Yeah. But it's not only a storage medium, it's also a source of energy because it has the energy in the ground. The crude oil has the energy in it. But if you have synthetic gasoline, what's the process for making it? You either have to be starting with hydrogen or some high energy molecule to begin with or you need to be putting energy into it. And where's that energy coming from? You're going to be having multiple power plants producing the energy necessary to synthesize the artificial gas. And then then it is just an energy storage medium and it is zero threat to the oil industries. It's not playing in the same space. But anyway just people fail to ask that question, that basic question whenever you're confronted with anything like this is where is the energy coming from? And if you just think through that question, it washes away a lot of pseudoscience because there's no free lunch. When it comes to physics, the energy has to come from somewhere.

J: Of course.

S: You say, of course, but that's like the big hole in a lot of these pseudoscientific claims is that they're not thinking about that very basic thing. Oh, we're just I have a device which amplifies the energy. But what does that mean it amplifies the energy.

B: And Steve, don't remember. You also got to kind of know energy can be neither created nor destroyed, right? I mean, this transfers from one type of energy to another with a little bit with some loss in heat. That's kind of inevitable. That's kind of the way the universe works.

C: It doesn't come out of thin air.

S: Right. That's why that's where zero point energy comes from, which he's not going there, but maybe he will eventually. Who knows? But where it's like, oh, the energy is there just in the in the the quantum foam of the universe.

B: Oh, no.

C: Well, in a way, it's like a different iteration of that. It's basically saying the energy is there in the form of waves, which is true.

S: Just only a millionth of what you're talking.

C: Yeah.

Who's That Noisy? (1:18:23)[edit]

Answer to previous Noisy:
Eurasian bittern booming call
(The Eurasian bittern or great bittern is a wading bird in the bittern subfamily of the heron family Ardeidae.)

S: All right, Jay, it's Who's That Noisy time.

J: All right, guys, last week I played this Noisy.

[Deep, airy pulses]

It might be one of the weirdest Who's That Noisy.

S: That's a weird noise. If I had to guess, I would guess that it's a critter.

J: Bob and Cara, what do you guys think?

C: No idea.

B: Yeah, I'm thinking critter now, too.

J: Ed Falcone writes in, this week's one is easy. It's the Id monster from Forbidden Planet.

B: Oh, my God. Oh, my God. That's it.

C: You're so funny.

J: I thought, I don't know.

B: That's it.

J: Totally.

B: That's funny.

J: I love that movie. And I always wanted to the monster does make it this huge roar and everything. We do get to hear it. It isn't that. You're not right. But I thought that was funny. Thank you.

B: Well, but it's that it's the technology, the noise from the crell that made that looping noise.

J: Yeah.

B: I think that's what he was talking about.

J: Yeah. Like the machine. Yeah. The machine, right. Darcy Stevens writes in and says, "Hey, Bob Jay, longtime listener, first time guesser, contacting you from Edmonton, Alberta, Canada. We just had our first November without snow in almost a hundred years."

B: Whoa.

J: Yep. More to come. "For this week's Noisy I think it sounds a lot like hydrogen or oxygen gas in a glass tube or jar being burnt. The flame travels up the tube and makes the thumb sound when it hits the opening at the end." This is a good guess. It's not correct, but there are some similar sounds in there. I've heard that and it's a cool sound, but thank you for trying. Listener named Keely Hill wrote in and said, "Hi Jay, I think it's a plastic hand pump being used to fill a very large balloon. The click after each pump reminds me of those cheap balloon animal pumps, but hey, maybe it's a mammal." You are not correct.

C: Is it a mammal?

J: Well, let's just be a little more patient.

C: You just said they weren't correct.

J: All right. This is a close guess. Not all the way there. Kyle Ledbetter. He says, "Hey Jay, I think the Noisy this week is the booming of some sort of male grouse. Love you folks and the show. Happy holidays." Okay. We've taken a step in the correct direction. So let me read the winner. Carl Berg said, "Hi, this week's Noisy is clearly a great bittern, a fairly common bird, sadly declining in Sweden and its song can be heard around many of the thousands of lakes here. The deepest parts of the song travels very long and can be pretty spooky. My neighbours were terrified by the sound before they knew what it is."

S: It was a critter.

J: So the person, Andrew Furmore, who wrote in said the bird, it's the Eurasian bittern, it's making a comeback, he says in the UK, it's mentioned and it's known as the UK's loudest bird, which I find to be interesting, but it's cool. It has a trombone kind of noise. This guys is a bird. Check it out. Listen to this again now.

[plays Noisy]

Right. Just totally weird, right? Just found that, that very interesting, very funny sound. Just sounds really silly, you know? So anyway, so thank you guys for your guesses.

New Noisy (1:21:46)[edit]

J: Okay guys, this noisy was sent in by a listener named Fred Sandoval.

[echo-y hissing, then whirring of a musical/mechanical nature]

And there it is. If you guys think you know what this week's Noisy is, or you heard something cool, you can email me at WTN@theskepticsguide.org.

Announcements (1:22:44)[edit]

J: Steve, not much to announce here. We have a couple of events coming up. One of them is, so we're going to Dallas, Texas, and we will be doing an extravaganza and we will be doing an SGU private show. This is all happening in April, April 6th and 7th. You can go to theskepticsguide.org to see the link there to get the information on the dates and the locations and everything. So if you're interested, please join us. A lot of people have been, have been signing up. It's really exciting. We're really excited to do these shows. I actually can't wait to do the extravaganza again.

S: Yeah. It'll be a lot of fun.

J: And guys 2023 is coming to an end. If you are a regular listener of this show and you appreciate the work that we do, we would really appreciate you giving us some support. You can become a patron by going to patreon.com/SkepticsGuide. You know, our patrons really are what keep the lights on for us. And we have a wonderful community got to meet so many patrons of ours at NOTACON, which we did in November. So, yeah, we have a ton of awesome people that you could become friends with and chat with on a daily basis on our discord. And on top of that, you could be supporting something that you believe in. So if you feel like we've, we've moved the needle at all, please do consider becoming a patron.

S: All right. Thanks, Jay. All right, guys, let's go on with science or fiction.

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Science or Fiction (1:24:06)[edit]

Item #1: A new study finds that the average volume of speech, called “sonority” is highest in the tropics and lowest in the northwest coast of North America.[7]
Item #2: A new comparative study finds that human newborn brain size is relatively smaller at birth than our primate relatives, representing a relatively shorter gestation and delay in brain development. [8]
Item #3: Researchers find that the electric organ discharge of an electric eel is capable of transferring DNA into zebrafish larvae.[9]

† The "What's the Word" segment in Episode 655 explores the word "altricial", which is found in the title for this article.

Answer Item
Fiction Human newborn brain size
Science Average volume of speech
Science
Electric eel DNA transfer
Host Result
Steve win
Rogue Guess
Cara
Average volume of speech
Jay
Human newborn brain size
Bob
Human newborn brain size

Voice-over: It's time for Science or Fiction.

S: Each week I come up with three science news items, two real and one fake. And I challenge my panelists got to tell me which one is the fake. Got three regular news items. You guys ready?

J: Yep.

S: All right. Item number one, a new study finds that the average volume of speech called sonority is highest in the tropics and lowest in the Northwest coast of North America. Item number two, a new comparative study finds that human newborn brain size is relatively smaller at birth than our primate relatives, representing a relatively shorter gestation and delay in brain development. And item number three, researchers find that the electric organ discharge of an electric eel is capable of transferring DNA into zebrafish larva. Cara, go first.

Cara's Response[edit]

C: The one that I'm most credulous about off the top is the electric eel. I don't know why, but if an eel, I think they make contact, I think they have to like close the circuit somehow. So like make contact with whatever it is that gets kind of that, that zap and maybe that organ is releasing some sort of special cells that obviously have DNA and it just says it's capable of doing it. It doesn't say it always does it and specifically into larva. So I guess if it's shocking zebrafish larva specifically that it could transfer some DNA into it. I mean, we see, I feel like we see horizontal transfer all the time with bacteria and stuff. So I don't know, that one just doesn't bother me that much. So really it's between the sonority one and the comparative study. Okay. So a new comparative study says that a human newborn brain size is relatively smaller at birth than primate relatives. So relative...

S: Yeah. So I have to explain the relative, relative, I can only put so much information in one sentence. It's relative to developmental stage, right? So it's, in other words, it's basically saying that human babies are at a earlier developmental stage relatively when they're born than our primate relatives with respect to brain development. The brain is smaller and less developed at birth than compared to the, the full range of development in humans compared to our primate relatives.

C: Yeah. That's interesting because I think about looking at humans by themselves and you think about like the bobblehead phenomenon, right? How human babies have like huge heads compared to their bodies and they can't even like touch their fingers up above their head. I was watching The Boy Who Harnessed the Wind last night, which is a phenomenal film, by the way, if you haven't seen it. And the dad in the film was saying our village elders like didn't ever, didn't always record our, our actual ages when we were born. So we didn't know when we were old enough to go to school. And so one of the tests we would do is if you could reach your hand over your head and touch your ear, you were old enough to go to school because little kids' heads are really big. And so there's something about that when you just look at humans. But maybe primate heads are even bigger. And so that one is like, I don't know. And then this idea of sonority. So the average volume of speech, you're saying like across, if you're yelling, if you're whispering, whatever, but the average loudness at which people speak is higher in the tropics and lower in the Northwest coast of North America. I have no idea why that would be the case. I think we still have a pretty decent gestation as, as human beings. Nine months is a long time, but there is probably a delay. You're saying representing a delay in brain development in humans, not in other primates, right?

S: Yeah.

C: The way it's worded. Okay. It does take us quite a while to wean and it takes us quite a while to grow up. So that part is what you probably put in intentionally to make me more credulous. Ooh, I got to put my penny down, my nickel down on this one. I think I'll say that the fiction is the sonority one, although I'm 50/50 about it.

S: Okay. Jay?

Jay's Response[edit]

J: I think the sonority one is science. Not because I'm remembering any firsthand interaction. And I find this fascinating the, the idea that, culturally we, we speak at different volumes. When I first read it, I read Northeast, not Northwest. And I'm like, we speak very loud over here. You know, New York, forget about it. You know, 68th street whatever, I'm thinking that that one is science. The second one here about the human newborn brain size being relatively smaller at birth than our primate relatives. I can't think of any reason why that would be. I don't know. I just don't think that that one is science. And the third one, researchers find that electric organ discharge of an electric eel is capable of transferring DNA into zebrafish larvae. I mean, that's kind of crazy, isn't it? That seems strange. Very strange to me. Not out of the realm of possibility, but just a very weird thing happening there. Right? Steve, can you say anything else about that?

S: No.

J: Are you basically saying that they make the sound and the sound that they make is actually transferring DNA into the larvae?

S: It's not a sound. It's an electric discharge.

J: It's electricity.

S: It's electricity.

J: Man, that sounds pretty serious. But Cara didn't pick that one. And that one seems so weird to me.

C: That doesn't mean anything. You know, when we go first, we suck.

J: I know, but I just trust you, Cara, you know?

C: No, don't do that.

J: I don't know. I just, there's something about the human thing. I don't think the second one here, the human, the newborn brain size one, I think that one's a fiction.

S: Okay, Bob.

Bob's Response[edit]

B: The sonority one, my first thought was, could it be air density? At those locations, potentially, I don't know. Let's jump to the electric organ discharge. Yeah, I mean, I remember a technique called electrophoresis, which basically organizes DNA and RNA using an electric charge. So that makes me think this could be feasible. So I know that I have read in the past that human babies have the highest brain to body weight ratio of anything alive. I don't know if that's absolutely 100% true now, but I specifically remember reading that. And relative to their size, babies have huge brains. But on the other hand, they are relatively immature because they wean for a long time, and they can't get too much bigger. Otherwise, human hips will be an impediment, and they won't be able to get out. So there's all that floating around. But I'll say that one, the brain size is fiction anyway.

Steve Explains Item #3[edit]

S: Okay, so you all have been in the third one. So we'll start there. Researchers find that the electric organ discharge of an electric eel is capable of transferring DNA into zebrafish larvae. You all agree that one is science, and that one is science. That one is science.

C: Yay.

S: That was the one I thought I was going to get you guys on.

J: Why?

S: Because it's weird.

C: It's weird, yeah.

B: I almost said no until I remembered about electrophoresis.

S: Yeah, and that's, I think, probably somewhat related to it, but more directly related why would they have even studied this is because we use electricity in order to do genetic engineering. This is how we get cells to take up DNA. So they said, oh, I wonder if electric eels have the same effect. And the reason why it's zebrafish larvae, because that's the study, right? They didn't show that this is happening in the wild. They were testing their hypothesis in the lab to see if this could even theoretically happen. So they used zebrafish larvae, and they had fluorescent genes in the water. And some tanks got shocked, and other tanks didn't get shocked. And the ones that did get shocked incorporated the bioluminescence genes in them. And the ones that didn't get shocked didn't. So it actually did have an effect on the uptake of these genes by the zebrafish larvae. So that means this is something that could potentially happen in the wild, but that wasn't the study, right? So that will be the next step to see if it's actually happening. That's why I had to say that it's capable of transferring DNA, not that it's actually happening. All right, should we go to one or two? What do you think?

J: One.

C: No idea. Which one did I pick? Sonority?

S: Yeah. All right, Jay said one.

Steve Explains Item #1[edit]

S: A new study finds that average volume of speech called sonority is highest in the tropics and lowest in the northwest coast of North America. Cara, you think this one is a fiction. Bob and Jay, you think this one is science. The interesting question here for me is, is that a variable that varies by culture or by language, right? And if so, what is the pattern? What is it varying with, right?

C: And if it was by culture or by language, why would it vary so much within a culture?

S: So this is what they found. Yeah, but is there an average, right? So the average.

C: Oh, right, right.

S: So obviously there's going to be a lot of variability on the individual level, and we all know loud talkers, right? But this one is science. This is science.

B: Yeah, baby.

S: Now what they found was that it varies by language groups, but there's some variability in individual languages. And how they interpret that is that evolutionarily, I mean culturally evolutionarily, it takes a long time for this feature to become solidified within a group, right? So it only correlates with basal languages, like more recently diverged languages don't necessarily correlate with each other. So there is some variability within a language group, but the language group is pretty consistent overall in its average volume. But it's one of those things that you don't think is varying culturally, right? You wouldn't notice it until you went to a different culture that had a different sonority, had a different average volume. Why is everybody shouting at me or why is everybody whispering? So I thought that was interesting.

Steve Explains Item #2[edit]

S: All of this means that a new comparative study finds that human newborn brain size is relatively smaller at birth than our primate relatives, representing a relatively shorter gestation and delay in brain development is the fiction. But this also, I thought, might have been a gotcha one because this is what people, prior to this study, this was conventional wisdom, not because there was data showing it, but because it makes sense. So again, I tried to clarify, I know this is a little complicated, but it's relative to their developmental potential, right? So in other words, when humans are born, their brains are not as far along their developmental pathway as, say, a chimpanzee or a gorilla baby is. And Bob, you hit upon the reason. The reason was, you think, well, because our brains are absolutely so big and pelvises only get so big, we had to speed up our gestation. We had to, like, shorten the gestation and basically slow down brain development up until birth and then have a spurt of brain development after birth because we've got to get this head through the pelvis, right? And so that's what they were expecting, and that's the conventional wisdom. But what they found was that, in fact, that's not true, that human babies are just as developed as primate babies in terms of their relative brain development their developmental stage neurologically. In fact, maybe even a little advanced. So essentially, we do get born relatively a little bit earlier, like a shorter gestation, but our neural development is still on track, and it's not relatively earlier in our developmental stage at birth than our primate relatives.

C: I think I also, like, sometimes these get me because I remember learning a long time ago, and I was just trying to look into it now as you were talking, brain-to-body weight is not a good indicator of much. We're up there on the scale, but we're not, like, the biggest. I'm pretty sure, like, the brain-to-body ratio is sort of not a good predictor of much. We're high-ish. Elephants are higher, whales are higher, hippopotamuses are higher.

S: You can't just use just brain size to body size, and the reason is that that is not linear along different sizes, like the mouse-to-elephant scale or the mouse-to-whale scale. You can't use that because bigger bodies need bigger brains because you need all of that surface area to control the bigger body, right?

C: And then there's also just, like, weird flukes of evolution, like chihuahuas have a super weird brain-to-body size ratio.

S: Yeah, or, like, dolphins have a bigger brain, but that's because they have a lot of white matter to process all of their sonar. So there's something called an encephalization quotient, which basically there's a curve, again, there's sort of the mouse-to-whale curve relating average brain size to body size for mammals. It's only relevant for mammals. And then you could say, are you above or below the curve for mammals of your size, right? You basically take your body size and where does it intersect the curve, and is your brain size above or below the curve for your size? That's the encephalization quotient. That does track not just raw brain size to body size, because it's not linear.

C: And I think that's sort of what I was thinking about when I was thinking about the relative size compared to primates.

S: Yeah, but what this is getting at is just, developmentally, are we born in a more undeveloped state than our primates? Neurologically speaking, the answer is no, even though we thought maybe we would be in order to get the head through the pelvis, but it turns out that's not the case. Remember, there's also neuronal density, which is not just brain size. It's the neurons per unit of volume of brain. And so you have to not only look at the encephalization quotient, you have to also look at neuronal density. Humans, of course, have a massive neuronal density, and we are the most encephalized species, even though we don't have the largest brain-to-body weight, because again, that's not a linear thing.

B: Steve, was it raccoons that had-

S: Raccoons are very high, bears are high, dogs are high. Yeah, raccoons have a very high neuronal density. Cats are very low. They're like average for mammals. But yeah, so animals, mammals that have high socialization, that seems to be really the biggest thing driving brain power and neuronal density, is socializing takes a lot of brain power. There's a lot of variables you got to think about and you have to calculate and be sensitive to and perceive and everything. And dogs got that way because they basically socialized to humans, as we were saying earlier in the show, whereas cats are kind of aloof, and they have the neuronal density to go with it. All right, well, good job, guys.

J: Thank you, Steve.

Skeptical Quote of the Week (1:40:15)[edit]

People can be extremely intelligent, have taken a critical thinking course, and know logic inside and out. Yet they may just become clever debaters, not critical thinkers, because they are unwilling to look at their own biases.

 – Carole Wade, American cognitive psychologist 

S: Evan is not here, so I have a quote. This quote comes from Carol Wade, who is a cognitive psychologist. She's a co-author with Carol Tavris on a couple of books on psychology. And Carol Wade wrote, "People can be extremely intelligent, have taken a critical thinking course, and no logic inside and out. Yet they may just become clever debaters, not critical thinkers, because they are unwilling to look at their own biases." Yeah, I like that quote. We talk about this all the time. When people first learn critical thinking, skeptical chops, they use it as a weapon against others, not as a way of examining their own thinking, beliefs, and arguments. And you really need to turn that light inward. That's the most important thing. So I completely agree with this quote. I think it's great.

C: They fall victim to that. What is that bias where it's like, when good things happen, it's because of something we did, and when bad things happen, it's because of something somebody else, like it happened to us?

S: That's the fundamental attribution error.

C: Yes, it's like, it's sort of like a flavor of the fundamental attribution error. It's like we first learn this stuff, and then we just apply it to everybody else.

S: Yes, exactly. It was funny, I was looking, I saw the quote, I'm like, oh, who was Carol Wade? So I put her name, when you put Carol Wade into Google with no qualifiers, the first thing you come up with is, Carol Wade is an actress known for Team Knight Rider from 1997. So I'm like, oh, cool. And it's one of those actresses turned academic, and we're like, nope, that was the wrong Carol Wade. It's Carol Wade, the cognitive psychologist, which makes a lot more sense.

C: A lot more sense. Yeah, that's true.

S: All right. Hey, guys, I want to point out that the show we're recording in two weeks, and it'll be the show that's coming up at the last show of the calendar year, is our year-in-review show. Always a lot of fun.

B: Again?

S: Ian will be joining us for that show. But what we need from you, the listener, is you need to email us at INFO@theskeptics.org, email us all of your fondest memories of SGU over 2023. So we want you to tell us what was your favorite news item, or science news of the year, best SGU segment, best interview, funniest moment, skeptical hero of the year, skeptical jackass of the year. And if there's any skeptic or scientist or thinker or philosopher or whatever who died in 2023 that you want to get mentioned in memoriam, send me that information as well. We'll add them to the list. This show's always a lot of fun. We're looking forward to it. But it's better the more information you send us.

B: Yes. Please remind us, because I'm getting old, and I don't remember this year.

S: I always have to look back over the episodes and remind myself of all the stuff we talked about and all the interviews we did. All right. Well, thank you guys again for joining me this week.

B: Sure man.

J: Thank you.

C: Thanks Steve.

Signoff/Announcements (1:41:59)[edit]

S: —and until next week, this is your Skeptics' Guide to the Universe.

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.

[top]                        

Today I Learned[edit]

  • Fact/Description, possibly with an article reference[10]
  • Fact/Description
  • Fact/Description

References[edit]

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