The Skeptics Guide #1043 - Jul 5 2025

Quickie with Bob: Quantum Electronics; News Items: AI Research Collaborators, AI Carbon Footprint, Curing Deafness, Food Myths, AI Enzyme Engineering; Who's That Noisy; Why Didn't I Know This: The Great Attractor; Your Questions and E-mails: Why Scientists Fall for Woo; Science or Fiction

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

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• 0:33Speaker 01

  You're listening to The Skeptic's Guide to the Universe. Your escape to reality.

• 0:40Speaker 02

  Hello and welcome to The Skeptic's Guide to the Universe. Today is Wednesday, July 2nd, 2025, and this is your host, Stephen Novella. Joining me this week are Bob Novella.

• 0:49Bob Novella?

  Hey, everybody.

• 0:50Speaker 02

  Cara Santa Maria.

• 0:51Bob Novella?

  Howdy.

• 0:52Speaker 02

  Jay Novella. Hey, guys. And Evan Bernstein. Good evening, folks. Bob, an early happy birthday for you. Yeah, happy birthday, Bob.

• 1:00Bob Novella?

  Thank you very much.

• 1:01Speaker 02

  Bob was born on the 4th of July.

• 1:03Bob Novella?

  What a birthday. An awesome birthday. Never have to go to school on my birthday, never have to work on my birthday. It was good.

• 1:10Speaker 02

  And I think we've said this before, but Bob had a big, big family party with tons of friends every year, because that was like a big thing that we did every year. So it was awesome for Bob. It was quite the event.

• 1:22Bob Novella?

  Yeah, it was like the only second after like Halloween was, that was always a great day. Love that.

• 1:29Speaker 02

  So you guys want to hear about my tech hell, my tech help hell? Oh, is this the phone thing? Yeah. Oh, Christ, tell us all about it. Gather around, kids. Very quickly, I had to switch over my phone from work to my personal account. Right, it's both on Verizon. So it's Verizon to Verizon to switch it from my, give me the number from my business account to my personal account. The process should have taken 20 minutes. Guess how long it took? 20 days. 10 days. Took 10 days. What a cluster. To do this. I did the whole process, you know, like requesting that they release the number and making sure it was unlocked, which is a separate thing, apparently. And then I had, then I have to call Verizon and give them permission to switch the number to my account and do whatever things they need me to do. And they couldn't get it to work.

• 2:13Speaker 02

  It just wouldn't switch over. And they couldn't figure it out. And so this got bumped up multiple layers, like to hire and hire tech people, until I was on the phone with like my tech person from Yale and three people from Verizon at the same time on the same phone call, they still couldn't figure it out.

• 2:34Speaker 04

  Wow.

• 2:34Speaker 02

  So they basically said, well, we're gonna have to like get our software guru in there to try to figure out what's going on. So then like two days later, now we're like a week out. They say they think this is, they think they fixed it. So now, you know, again, it was some, whatever, something in the software. So go ahead and do it again. I did it and it didn't work. There was a separate problem, a completely separate problem that was also a hard stop that nobody can figure out. And cause now, so now, so first they couldn't get it off of Yale's account. Then they couldn't get it onto my account, which of course is the two things that would have to happen. And it was because, again, like some silly thing, the, we have insurance, like family insurance that covers three phones.

• 3:19Speaker 04

  Uh huh, yes.

• 3:20Speaker 02

  But it only covers three phones and now I'm trying to add a fourth phone.

• 3:24Speaker 04

  Oh, so that's a big to do.

• 3:26Speaker 02

  So the thing that kills me though, is that it creates an error, but it doesn't tell the person what the error is. Or, you know what I mean? So they don't know. It's just, no, this won't work, can't do it.

• 3:38Speaker 04

  Right.

• 3:39Speaker 02

  Yeah, seriously. It should have like a, a number next to it. Yeah, it should immediately say, you know, this is incompatible with this service. So that took them two more days to figure that out. And then finally, you know, I had to like remove that service, then transfer the number over. Uh, so then, so 10 days later, I finally own, you know, I have my phone number onto my personal account. So then I had to go get a new phone. And again, I've done this many times before with all my, all my family members. It's usually not a big deal, you know, you get a new phone. You activate your new phone and it takes the number from your old phone, right? So I did that and we went, we went to the Verizon sort of do it in person, right? You know, I mean, it's always better to do it, to do it in person. And we do that, there was two, something else happened too.

• 4:24Speaker 02

  For some reason, we, we got an Apple Watch in the mail from Verizon and they charged us like $900 for it. We never ordered it. We don't even own, none of us own an iPhone. What? So we don't know how that happened. It's still a mystery. We have no idea how. It's a mystery. This got ordered. So we, we, we, you know, we, we were told bring that in and to return it. So we returned that at the same time, right? So we had the person do two things for us. One, just take this, take back this iWatch and take the charge off of our account. Right. And two, get me a new phone, right? So I got the new, got the latest phone, get home, activate my new phone. Activate. They attached it to the wrong number. They attached it to my wife's number. So now I simultaneously.

• 5:09Speaker 02

  Oh, please. Deactivate her phone and activate my phone to the wrong number. So that was really hard to fix. That was just incredibly hard to fix. I went again, now I'm like hours, hours online, you know, trying to get this fixed. And they couldn't do it. They got to the point where you're supposed to activate. Like I was trying, I had to activate my wife's phone back to her old number and then I could activate my phone to my, to my number. And it would, the activation wouldn't happen. He didn't know why. He basically bailed on me. And so I called someone else and they basically said, you have to go to, I, we can't. So here's the other thing that happened. They said, okay, we need to send you a text to validate that you're the, that you have permission to do. That this is you, right?

• 5:55Speaker 02

  So like, cause I guess they, it was just fine. It's a security thing. They don't want somebody else stealing your number. Right. So at this point, the, what the other, what the previous person managed to do was make it so that my phone didn't work and my wife's phone didn't work. So neither of our phones work. So, and again, I'm doing this online. They say, okay, well, we have to send a text to a phone on your account, which is my daughter's phone who's home for the summer. But she's the phone that the Apple Watch was ordered for. It was on her line. So what the guy did was when he deleted the charge, he deactivated her phone. So they managed to deactivate every phone in my house.

• 6:40Speaker 02

  Oh my God. And there was absolutely no way to activate any of the phones.

• 6:47Speaker 04

  Oh my gosh.

• 6:48Speaker 02

  You know, remotely, I had to go to another store. We had to find a Verizon store that was open till nine, go there physically, and you know, so we could show them an ID. And that was a two-hour cluster, but it worked. We eventually got everything taken care of. Although, just to add one more wrinkle, in the middle of it, the guy we were dealing with deactivated my iPad by mistake, which is also on the same account.

• 7:15Bob Novella?

  Did you have any weapons on you?

• 7:18Speaker 02

  So, but at the end of the night, we got everything working and it's all good. But it was like a maximal cluster. It was just unbelievable.

• 7:27Bob Novella?

  You do realize that that's what hell is like?

• 7:30Speaker 02

  Just an endless loop of tech help.

• 7:33Jay Novella?

  Steve, were you there to keep it your cool? Or did you get pissed off at any point?

• 7:36Speaker 02

  No, I kept my cool. The thing is, like, the person I'm dealing with is never the person that screwed up. You know what I mean?

• 7:43Jay Novella?

  Right. Well, that one guy screwed up, though.

• 7:45Speaker 02

  He massively, massively, but their store was closed. We had to go to a different store to sort it out. I wouldn't go back to that guy anymore.

• 7:51Cara Santa Maria?

  Keeping your cool is not just the best, but kind of the only way to eventually get where you're trying to go.

• 7:56Speaker 04

  Steve, they're gonna send you a survey about your experience with Verizon.

• 8:01Speaker 02

  Oh my God. And the thing is, you know, I was talking to Jay about this. Part of the problem is, like, the software backbone that's running all of these is too complicated. Nobody knows how to really manage it. The person at the store I was dealing with had to call tech help. Like, he couldn't resolve it by himself. He had to get on with Verizon to, like, work the backend. And so now, listening to him, so, you know, the in-store tech guy talking to the tech person at Verizon, and, like, they're giving him a bunch of crappy advice of things, too. He's like, no, that's not gonna work. Like, he's telling them, rejecting most of their suggestions about how to solve the issue, until you get to the thing that actually worked, you know?

• 8:45Speaker 02

  It's just they don't understand their own software and they don't and I get the feeling like it's changing so frequently, there's so many moving parts and again like it's not very user friendly, like they get an error and it's a mystery as to what's causing the error, like now they have to go on this hunt to figure out what the problem is.

• 9:02Jay Novella?

  And Steve, it's not uncommon that, you know, these companies have legacy systems, you know, like, you know, they could be working on a codebase where there aren't many programmers on that codebase anymore.

• 9:13Speaker 04

  Cobal.

• 9:14Speaker 02

  Well, here's the other thing, here's another layer to this, so part of the problem, the reason why it took two hours to like undo all of this is they couldn't activate my wife's phone, they just couldn't do it, it wasn't, so again, we were never going to fix this online and eventually we figured out that the, her phone, which is only like a couple of models back, just wasn't supported anymore and they needed to give her a new physical SIM to do it, they couldn't do it on the SIM that was in her phone.

• 9:42Speaker 04

  Oh my god.

• 9:43Speaker 02

  And it wouldn't take the new eSIM, which is like an electronic SIM, so there was no way to fix it without physically swapping out her SIM card.

• 9:50Cara Santa Maria?

  And if there was a error code, they would have known that right away.

• 9:55Speaker 02

  But the thing is like, it's, this is, I think, a bit of planned obsolescence, like they just, they're constantly changing the models and then they sunset the older ones after a few years, it's like they don't really support it anymore.

• 10:09Speaker 04

  Yeah.

• 10:10Speaker 02

  Or it becomes incompatible.

• 10:11Speaker 04

  When a problem arises, it's impossible to fix.

• 10:13Speaker 02

  Like my daughter's phone, the one that they accidentally deactivated and we had to have reactivated, again, is a few models old and they're like, she better upgrade that soon or we won't be able to transfer the data to her new phone.

• 10:27Speaker 04

  Yikes.

• 10:28Speaker 02

  Right, it'll be so old, we can't even access it to transfer the data, it'll be incompatible, so you like have to update every few years to keep in the loop, like you know, otherwise you get, you're too old to even update it.

• 10:41Speaker 04

  You're rescusing everything.

• 10:42Speaker 02

  Yeah. It's crazy, it's frustrating, so that was my, that was, Steve, it sucked up a lot of time.

• 10:47Jay Novella?

  Steve, legit, like get off their network, man, I don't have any problems like this on AT&T.

• 10:52Speaker 02

  Well, I had never had problems like this before, that's, you know, I'm not going to overreact to one bad experience, it's, this is. Bad, that's how you describe it?

• 11:01Speaker 04

  Well, they are the most expensive too, I mean, that's part of the other frustration.

• 11:05Speaker 02

  And you can't tell me this never happens on other services, I don't believe that.

• 11:08Cara Santa Maria?

  Yeah, I think, it's like everybody has their reason that they stick with who they stick with.

• 11:12Speaker 02

  All right, let's move on. Bob, you're going to tell us about how quantum electronics is going to fix all these problems for us.

• 11:19Bob Novella?

  Oh, absolutely. Thank you, Steve. This is your Quickie with Bob, people. So here is yet another claim that we might be able to make electronics a thousand times faster. We've heard this so many times, but is this one it? You know, let's explore it and to see what the details are, at least. So researchers at Northeastern University published in the journal Nature Communications, and they claim a discovery that they say will allow them to change the electronic state of matter essentially at will, potentially making electronics a thousand times faster and more efficient. See? I told you. So this material was described as a quantum material. The name or the designation, I guess, 1T-TAS2, I don't know what the nickname might be. Call it TAS.

• 12:04Bob Novella?

  It's called a quantum material because it's essentially governed electronically, magnetically, everything by quantum mechanics, so it doesn't behave like ordinary silicon or copper at all.

• 12:14Speaker 02

  That's right, copper.

• 12:15Bob Novella?

  That's right, copper. They found a way to make this material switch its phase to behave like an insulator or as a metal. And these phases could act like transistors essentially, switching between allowing current to flow and blocking the flow, which could then, of course, represent the fundamental ones and zeros of today's binary computers. Now, if this works, and that's a big if, it would have tremendous benefits over silicon. It would really be so superior in so many ways. These phase states could exist in just a few atomic layers, so that would, of course, would allow ultra-dense packing, which could cram in far more components than silicon ever would. The switching itself could happen not in billions of a second, but trillions of a second, picoseconds. Incredibly fast, obviously.

• 12:59Bob Novella?

  Also, the energy usage could be far less than conventional transistors. So it's such a win-win-win on those, just these three basic characteristics would be so dramatic. This could potentially be just what we need as silicon, you know, every day gets closer and closer to that hard wall of physics limitations. It's really, it's getting, it's, everything's getting, the components are getting so small that you Having electron leakage that is going to basically just make it unusable. And we'll reach a point where you just can't really make it that much smaller and faster. As usual, there's lots of hurdles left for this guy. There's like, there's control, integration, stability problems, and all of these, any one of those, it seems to me, could be this technology's undoing.

• 13:42Bob Novella?

  But like many of these, these papers that we read about these huge advances in electronics, we just basically just have to wait and see, you know, which one takes off and when this is going to happen. So fingers crossed essentially. This has been your Quantum Quickie with Bob. Back to you, Steve.

• 13:55Speaker 02

  Thanks, Bob. So remember that I think it was a science or fiction from a few weeks ago, or a couple of weeks ago, where one of the items which was true was looking at two dimensional

• 14:03Bob Novella?

  Yeah.

• 14:04Speaker 02

  transistors, basically, because that doesn't have the same limit of scalability. So like with the silicon, again, below a certain, as you shrink it down, the physical properties change and you get to a point where it just wouldn't function anymore. But with the 2D material, it doesn't, it retains its physical properties even at the smallest possible molecular size. And so that also would be another potential pathway to solving that limitation.

• 14:29Bob Novella?

  I mean, there just, yeah, there seems to be lots of avenues they're going down. And really just if one hits big, I mean, it could be a dramatic change for the computing industry. So hopefully, you know, we just have just pure numbers into our advantage and possibilities. You keep, it seems like we read, you know, we read, you know, it's like battery technology. You see, oh, look at this breakthrough that they have in the lab. Well, yeah, they, of course, 99.9% don't pan out, but I mean, just gotta see what happens.

• 14:57Speaker 02

  All right, Jay.

• 14:59Jay Novella?

  Yeah.

• 15:00Speaker 02

  Yeah, we actually have a somewhat of an AI dense show this week. You're going to start us off talking about using artificial intelligence as research collaborators.

• 15:11Jay Novella?

  Yeah, I've been wanting to learn more about this, you know, I think about AI and all the uses that are spinning out, out in the world, you know, and this was one, a big one, you know, like what's it helping science do? And of course, there's tons of examples of it, but this is a, a, a pretty strong thing that they've come up with, pretty, pretty interesting and potentially for the future, could be very helpful. So there are multiple research teams who are currently developing artificial intelligence systems that are designed. They're not just there to assist a scientist, but they're to simulate a scientific collaboration. Let me tell you how they're doing this.

• 15:51Jay Novella?

  So the systems are using teams of AI agents and each assigned, you know, like a role, like a specific role, like one of them is going to act as a neuroscientist, the other one's going to be a pharmacologist. There's another one that's going to be a critic whose job is to, you know, ask a lot of questions and literally criticize what they're doing to poke holes in it. And they have to interact with each other, kind of like people do, right? They're talking to each other. They debate hypotheses, they propose research directions, and there's a conversation that's going on between all of them. And the goal is to mimic the structure and the reasoning of a real lab team using AI to accelerate the idea generation, you know, problem solving and scientific research.

• 16:35Jay Novella?

  It's seems like pretty obvious, right? Yeah, we do this. We're going to have, you know, these specific bots who we've given characteristics to, and we're going to have them talk and see what happens. So the research right now is actually happening in several labs. We have one in Stanford, we got one over at Google DeepMind, there's several of these that are happening in China, and the researchers are experimenting with what they're calling now, it's called AI coscientist systems. So how do these systems actually function? They're similar, they're very, very similar. Stanford set up, they called the virtual lab, and they used GPT-4 based agents and they configured them to play different roles, like I said earlier, in a simulated scientific meeting.

• 17:17Jay Novella?

  So for example, you provide a goal, you assign roles, so you could be like, okay, we're going to try to find a drug for this specific illness. What they do is they run several discussion rounds, and then, you know, the chat GPT or whatever model that they're using, it'll search all the current literature, it'll generate proposals, it'll evaluate a lot of potential answers that have come up with, and Google is testing something similar, and they're using their Gemini 2.0 system. So their their coscientist model assigns each agent, again, a specialized task. They have to come up with a certain number of ideas and they're supposed to come up with ideas. That's a big part of this. They have to do a literature review. They need a criticism

• 18:00Jay Novella?

  phase, synthesis, you know, then they run the group through multiple review cycles. Typically, they say that ends up with a written summary at the end. The appeal is that these systems can generate faster ideation, broader coverage of existing research. You know, it is a structured internal debate, which they have control over and they can see what's happening. And in the early tests, these multi-agent systems definitely outperformed single chatbots on scientific reasoning benchmarks, right? So they're saying, let's take a bunch of chatbots and how much more, you know, money and time does it take to spin up a bunch of them in these roles versus having one chatbot do it? It really isn't

• 18:40Jay Novella?

  crazy time consuming. It isn't. It's not that that much work to set all this up and then you just flick the marble and see what happens. It works remarkably better than a single a single chatbot doing it on its own. And this includes graduate level scientific questions. So what I also found even more interesting is that they're capable of proposing new ideas that human researchers might not reach as quickly in some cases at all. That's the important part of it. So let me give you a real world example that they had here. So this comes from liver fibrosis research. So Stanford pharmacologist, a guy named Gary Pelz, used Google's AI coscientist to propose a potential drug targeting epigenetic regulators.

• 19:25Jay Novella?

  Of these three drugs, the system identified two of them promised anti-fibrotic effects in human organoid models. Steve, you understand all of that.

• 19:35Speaker 02

  You should too. So you know what organoids are?

• 19:37Jay Novella?

  I know. I'm just I'm just making a joke. I know. It's just it's very sciency. Oh, boy. So the results that they got exceeded the performance of drugs selected by by Pelz himself. And while of course, this doesn't mean the AI discovered a cure, it does demonstrate that the potential for these systems To have a legitimate contribution meaningfully to preclinical research. It's not insignificant. And again, you know, we say this all the time. We are in the absolute skin of the apple part of AI. You know, it's, it's not a super progressed technology. It's, it's essentially, it's brand new. And it's already able to do things like this.

• 20:17Jay Novella?

  There are limitations, you know, I have to say, some researchers point out some really good points that we have to keep in mind. So out of the AI's suggestions, some of the researchers were saying that humans would likely have gotten to these conclusions on their own, which is perfectly crumulent, right? You know, it's, you know, in that case, you could say, well, the AI got there faster, but humans would still get there. The other note, so other people said that the simulated team discussions between the AI agents are, they're logically consistent. They stay on topic, but they don't have the spark of the unpredictability of, of real conversations between people.

• 20:56Speaker 02

  They're not really creative.

• 20:57Jay Novella?

  Right, exactly.

• 20:58Speaker 02

  Totally new ideas because they couldn't be trained on a totally new idea, right?

• 21:02Jay Novella?

  No, and, and quite simply, and this isn't simple, but you know, they're, they're not wired or programmed to function like a human brain. I mean, human creativity is super complicated. They can't get these chatbots to, to behave like a real human. You know, they're, they're, not only are they on rails, but they just don't have the mental capacity. They don't have any of that stuff. So there's no intuition, there's no sudden flashes of insight, there's no eureka moments like that.

• 21:28Speaker 02

  But do they, they could be good in a couple of ways, it seems to me. You know, one is good at summarizing existing research. You know, like this is where we are, this is the questions that are still open, et cetera. And it may be good at generating. Inspiration for ideas. They won't come up with the brand new ideas, but they might inspire the researcher to.

• 21:52Jay Novella?

  That's a good point, Steve, right? Because, you know, they're primed, they could be priming the humans they're working with.

• 21:56Speaker 02

  Yeah, right.

• 21:57Jay Novella?

  You know, and I know, I know artists that use AI-generated content to spark their imagination. Oh, I never would have thought of that type of thing or whatever, you know?

• 22:06Speaker 02

  Yeah, yeah.

• 22:07Jay Novella?

  Which is good. I mean, it's, you know, anything that pushes the ball forward here, I think, is a good thing. We also have to keep in mind, though, guys, that these chatbots hallucinate.

• 22:15Speaker 02

  Mm-hmm.

• 22:15Jay Novella?

  And these systems can and did and do generate incorrect information, which means the output still requires expert vetting. So there, there is still that limitation, and I have not heard anything about hallucinations going away at this point.

• 22:29Cara Santa Maria?

  You know, one thing that I, I think about having recently done a dissertation is how, in some way, stuck we are academically in thinking about research the way we thought about it 10, 20, 30 years ago. I'm glad that you mentioned like literary or literature reviews, because that's a really important part of a scientific paper. It's summarizing the state of the literature right now and kind of pointing to some of the most important or salient findings. One of the things that I did when I wrote my dissertation is I picked a topic that just not a lot of people are writing about, because I was overwhelmed by the prospect of talking about something that had thousands of hits within the literature.

• 23:15Cara Santa Maria?

  And I felt like I did a pretty okay job of summarizing the state of the literature on my topic, because it's, it was somewhat new. I think that we talk to students today and academics today as if that task is doable, and it's not anymore, because there are so many journal articles out there.

• 23:33Jay Novella?

  Yeah.

• 23:34Cara Santa Maria?

  Like, just the, the sheer number of publications in existence today compared to

• 23:40Cara Santa Maria?

  Five, 10, 20, 50 years ago is astounding. And using just like standard library skills, you're gonna overlook stuff. So I see this being hugely helpful.

• 23:51Jay Novella?

  Oh, God, Karen, I know. You know, it's, this was something that we talked about earlier. I definitely remember talking about it on the show, but it was the idea that like, let's say it's a code base instead of literature. The, you know, the ChatGPT, for example, would be able to, to be more aware of the whole structure of all of the software, right? A future version, say, that, you know, when they, when they finally refine it and are able to expand on how much like it can have active memory and they, they can really get rid of hallucinations. You know, you imagine if it's able to have all of Amazon's global shipping and business management software, which it's a huge code base. Like it's bigger than any 100 people could ever fully comprehend, right?

• 24:34Jay Novella?

  It's just this massive code base with tons of avenues and everything. And that's the same thing with research. If you're talking about, you know, it has to process through 10,000 papers and be able to get rid of the bad stuff, flag the good stuff, and then fully understand what's going on with the good stuff. You know, this could be a game changer to keep up, you know, to let scientists keep up, like you were saying, like, okay, good, we can, we can process through all this. And, but we have to have systems that we can trust.

• 25:02Speaker 02

  Yeah, I mean, I think, again, it's a powerful tool. And if used properly, I think it could be a massive benefit, especially in areas where, again, there's an overwhelming amount of information that we have to deal with, like in research and medicine. But it also can be used poorly, right? And can, if it's like a substitute for thinking, like the lazy route out, then it could be a detriment. Or like if you don't, you know, again, I think the best recent example is RFK Jr. submitting a report that had like six fake non-existent studies in it. Some jackass in his. His department used, clearly used AI to generate a report and didn't check it out.

• 25:44Speaker 04

  And never went to the references? Holy moly.

• 25:47Cara Santa Maria?

  Yep.

• 25:47Speaker 04

  That is lazy.

• 25:49Speaker 02

  Yeah, but that's gonna happen more and more.

• 25:51Jay Novella?

  Of course it is.

• 25:52Cara Santa Maria?

  It's happening all the time across every school in America, in the world.

• 25:56Jay Novella?

  You know, the researchers themselves said the real value here lies in accelerating parts of the scientific process that are time consuming, but absolutely have to happen. And again, you know, I, I use ChatGPT, you know, it's helping me write a screenplay. It helps me with SGU work that I'm doing, you know, not just asking me, not me just asking, hey, help me like frame this email, you know, like you help me generate some copy for an email that I want to send that's complicated or whatever, but you know, I, I personally will give it multiple articles. And I'll say, reduce all this down to bullet points for me. And like, let me just see, you know, let me see all the important information in that format. That helps me so much with the work that I do for the SGU in lots of ways. It's, it's powerful stuff. It's very powerful and it's super useful.

• 26:41Jay Novella?

  But man, the doctors can't lean back, you know, researchers can't lean back and not give it expert supervision, supervision, careful validation, you know, they have to work with it. It's another tool and we can't let it, it's gotta remain a tool. It can't, it can't be the thing that does everything.

• 26:58Speaker 02

  Phil, let me ask you a question. Have you asked your chatbot to marry you yet?

• 27:01Jay Novella?

  No, oh my God, remember, so we had a live stream today, guys? Bob, Steve and I did a live stream and there was this guy, oh Christ.

• 27:09Speaker 02

  He fell in love with his chatbot.

• 27:10Jay Novella?

  He fell in love with his chatbot. And then what happened is it, he hit the max memory of that session and it got, and it had, and it got wiped.

• 27:19Speaker 02

  It got reset.

• 27:20Jay Novella?

  And he cried and the guy was crying. I'm not putting him down for crying.

• 27:24Speaker 04

  Like that movie 50 First Dates or whatever that movie was.

• 27:27Jay Novella?

  Yeah, like it was gone. So it got creepy though, guys, because, you know, his wife knows about it and she's not happy. And then the, of course, the interviewer like asked this really hard question, like goes to the husband, like, you know, if your wife wants you to not use this anymore, would you, would you do it to, to remain healthy in the marriage pretty much? And he's like, no, nope. And he's like, you know, it's, it's expanding my intelligence and it's, it's like, yeah, sure. The way I use ChatGPT, yeah, it, it's a great research tool and all that. But the fact is, you know, one thing that Ian noticed when we were looking at it, they, they had a picture of his phone on his desk. And he, and we could read the text that he was typing to the freaking chatbot?

• 28:11Speaker 02

  No, no, no.

• 28:12Jay Novella?

  Yes. And it was sketchy. It was like, oh, baby, like when you use your tongue and shit like what? The chatbot was saying this, Kara.

• 28:21Cara Santa Maria?

  The sad thing here is that he wasn't quote falling in love with a chatbot at all. He might think that's what was happening, but the, a chatbot's not a person, right? A chatbot is not, not an entity. He was falling in love with his, himself.

• 28:33Jay Novella?

  That's exactly what I said. I said it's a-

• 28:35Speaker 02

  It was falling in love with an illusion.

• 28:37Cara Santa Maria?

  And not just with an illusion though.

• 28:38Jay Novella?

  Yeah, exactly.

• 28:40Cara Santa Maria?

  Yes. It was like a, an illusion that is ostensibly a mirror. He was throwing out the right things to be able to receive the right things. He just needed utter and complete validation.

• 28:52Jay Novella?

  But we can't, we were, when we discussed it today, and I think this is worth repeating, like we were, we were pointing out this idea that, you know, chatbots are going to become more personable. They're going to be more capable of having, you know, real, honest conversations and, you know, people will be developing relationships more and more, like the people are, you know, it's happening now. I mean, people are like having, you know, they think they're having relationships with chatbots. And Steve pointed this out, and I thought it hit, hit this whole thing right on the head. You know, imagine the chatbot is giving the person what they need and it's basically them getting for themselves exactly what they need and what they want, which could make them very egocentric.

• 29:32Cara Santa Maria?

  Of course.

• 29:33Jay Novella?

  Which makes them enter their own little bubble, not, not a political bubble that they belong to, not, you know, it's, it's like they'll become kind of egoists.

• 29:40Cara Santa Maria?

  Well, and it's already happening to a lesser and, and I guess less sophisticated degree. When you see grown adults who, and you see this even, I'm not going to talk about a couple who's been married for 40 years, but let's say a, a new relationship, grown adults on their phones.

• 30:00Cara Santa Maria?

  Swiping through social media, but they're sitting right across from each other.

• 30:04Jay Novella?

  Yeah.

• 30:04Cara Santa Maria?

  They're not engaging with the real person that's right in front of them and enjoying and experiencing all of the beautiful things that come from socialization. But instead, they're bubbling themselves in because they're not actually engaging with social. Those aren't people, they're engaging with themselves.

• 30:21Jay Novella?

  So I find it very intimidating and scary to think that in the future, right now, ChatGPT is so cheery and so ra ra in your corner. I've told my ChatGPT to not do that. I want it to be hard, I want it to be skeptical, I don't want it to yes me anything. I want it to push back, right? And again, it's kind of weird to even say that because I'm not talking about a person.

• 30:46Speaker 02

  And it said, yes, great idea, Jay.

• 30:47Jay Novella?

  Yeah.

• 30:50Jay Novella?

  But you know, people will slip into these egotistical, self-serving quote unquote relationships.

• 30:56Speaker 02

  Well, it'll be Pygmalion, right? They will create for themselves the easiest, most positive, affirming sort of persona.

• 31:04Jay Novella?

  Sure.

• 31:05Speaker 02

  And but not a real person that has their own needs, you know, and their own biases and everything. It creates this illusion of a person who is of fantasy, who's completely unrealistic, and it could spoil them for real relationships.

• 31:21Jay Novella?

  Yeah.

• 31:21Speaker 02

  You know, they have to actually think of some other person's needs, you know?

• 31:25Jay Novella?

  Kara, I would imagine that there'll be therapists whose job it is to detune people out of these quote unquote relationships with.

• 31:31Cara Santa Maria?

  Absolutely. And I mean, I know that this is going to feel confronting a little bit, so I'm going to caveat this with that. But from a like feminist psychological perspective, I also worry about the gender component of this because I feel like we're finally in an era, we've still got a long way to go, but we're finally in an era where we're making real progress when it comes to relationship equity. Historically, a lot of relationships, that was the angle, right? That men provided the type of security that was required. For women to be able to exist in the world because they didn't have the rights to like have a mortgage or to use a credit card or even like long before that,

• 32:12Cara Santa Maria?

  women were really dependent upon their male partner for their existence in the world.

• 32:18Jay Novella?

  Yep.

• 32:18Cara Santa Maria?

  And so you did see this abuse of power in many relationships where men sought out partners that were subservient and docile and just reinforced what they wanted to hear and think. I wonder if this is going to set us back from a gendered perspective because unfortunately, the sad thing is, and I'm not saying it doesn't happen with women, but these stories often are centered around men.

• 32:42Jay Novella?

  Yeah.

• 32:43Cara Santa Maria?

  They often are centered around men finding chat, like falling in love with their chatbots, not women falling in love with their chatbots.

• 32:49Jay Novella?

  Yeah.

• 32:50Cara Santa Maria?

  Women haven't historically had to, uh, we've had to kind of overcome that experience of like the narcissist partner.

• 32:58Jay Novella?

  It would be interesting to see statistics. Uh, you know, I'm curi-, I'm really curious about this now, now that we, we saw this news item. There was a woman who was in charge of this subreddit.

• 33:10Cara Santa Maria?

  Mm-hmm.

• 33:10Jay Novella?

  Who is basically about people in relationships with chatbots.

• 33:13Cara Santa Maria?

  Mm-hmm.

• 33:14Jay Novella?

  And she's in it and all these other people are, you know, I think it's going to happen.

• 33:18Cara Santa Maria?

  It will happen to everybody, but I think similarly when we see people, this was a huge story 15 years ago, 10 years ago, when I was doing a lot of television at the kind of dawn of this AI stuff was like the, the sexbot story.

• 33:30Jay Novella?

  Mm-hmm.

• 33:30Cara Santa Maria?

  I remember covering it for multiple outlets, like what happens when sexbots also have large language model capabilities in them. And I mean, their end users overwhelmingly male.

• 33:41Jay Novella?

  You know, look, I, I could see a scenario in my future where I have a personal assistant who I could kind of be friendly with, like be friends with, right?

• 33:49Cara Santa Maria?

  Sure.

• 33:49Jay Novella?

  You could, you'll have a rapport, they'll know what you like, you'll assign it, you know, personality traits and all that stuff. And, you know, I never for a moment thought that I'd be entering, you know, that, I know I'm not capable of this because I am so people-centric, like to an absolute, it's the most important thing in my life is the people in my life.

• 34:07Cara Santa Maria?

  Mm-hmm.

• 34:07Jay Novella?

  That's why this is horrifying to me. I would never, I have no interest in becoming like into, getting involved in like a relationship with an artificial being. Uh-uh. There's some, there's nothing there for me. And I think we, we need to start teaching people about this. We need to talk about it.

• 34:23Cara Santa Maria?

  We do.

• 34:23Jay Novella?

  Kids need to hear about it.

• 34:24Cara Santa Maria?

  And we've talked about the other risk. I know Steve, we've talked about this on the show before where. Let's say, like Jay, you were saying, you know, having an assistant and I'm really friendly with it, but a lot of people won't be friendly with it. And the fear is that it'll reinforce dehumanizing behavior that then will translate into their daily lives.

• 34:41Jay Novella?

  I just said that today, Kara. Like, I had this thing. So I told the guys, you know, when I'm, when I'm doing, you know, I could be talking to ChatGPT about a bread recipe, right? And it always comes back with a long-winded response and they give you to... So I, at one point, I caught myself saying, "So I don't want to hear any of that." I said that to the chat, and I'm like, "Whoa." I'm like, "I can't let myself talk like that because that could be, I could be training myself to have those kinds of... Most, I was going there because it wasn't a person."

• 35:10Cara Santa Maria?

  Right, because you were allowed to be egocentric in that moment. This is all about you. This query, this help, it's all about you. But when you're engaging with a person, it's equivalently about both of you.

• 35:19Jay Novella?

  Well, look at what people do just with the barrier of, you know, like they have internet balls, right? They're online. They're not face-to-face. Look at what people, look at all the dehumanizing thing that, things that we've witnessed over the last 10 years that people have been doing online. It's only going to get worse with this.

• 35:34Cara Santa Maria?

  And none of us are not like this. I mean, I listen to myself when I'm driving my car. And people can't hear what I'm saying to them, you know, the drivers in front of me. Yeah, like, this is natural behavior.

• 35:47Speaker 02

  All right, well, Kara.

• 35:48Cara Santa Maria?

  Yes, I know. There were so many segues.

• 35:51Speaker 02

  While we're talking about the impact AI is going to have on us, you know, psychologically, socially, what is the carbon footprint of training all these AIs?

• 36:02Cara Santa Maria?

  A deceptively difficult question to answer, which I didn't really realize until I started to dig into some of the literature on that. And it's funny because part of the reason that we don't really know how much energy our AI prompts use is because most of the companies who are developing these large language models Don't share that information with us.

• 36:28Speaker 04

  On purpose.

• 36:29Cara Santa Maria?

  On purpose, yeah. We've got all these large companies that are not opening up about how much energy their L L Ms are actually consuming.

• 36:36Speaker 04

  Because they're afraid to get taxed?

• 36:38Cara Santa Maria?

  Who knows why? I mean, they're not telling us. It could be because they don't know. It could be because, you know, the numbers are all over the place. It could be because they, obviously, it's not good for P R. What's so interesting is that if you ask this question, I haven't asked it to an L L M, to it, to it. Okay, like, so here's like a full caveat. I don't think I've ever used Chat G P T ever. The thing that's strange is that if you do an internet search, or I guess if you query an L L M about how much energy or how much carbon emission, or, you know, there's different ways of slicing and dicing this, does an A I prompt use, you're going to get a wide range of answers and you're also going to get a wide range of perspectives.

• 37:22Cara Santa Maria?

  You're going to read articles that are like super fear mongering, like, oh, my God, it's horrible. It's going to ruin the environment. Like, don't use Chat G P T at all. And then you're going to get articles like the one that I am looking at right here called, What's the Carbon Footprint of Using Chat G P T? Very small compared to most of the other stuff you do. And like this writer says, and this was just a couple of months ago, I used to feel guilty about it. Now that I've really looked into it, I'm not worried about it at all, and you should stop worrying about it, too. So you really see two different ends of the spectrum, and you see a lot of different ways that people go through and do their own calculations.

• 38:03Cara Santa Maria?

  A recent article in Science News, How Much Energy Does Your A I Prompt Use? It Depends, written by Selena Zhao, talks about the, you know, why it's so difficult to answer this question. And, and really, it focuses on a recently published journal article in Frontiers in Communication called Energy Costs of Communicating with A I. This just came out in June of 2025. In this study, what researchers did is they focused specifically on large language models that are open source, because that's really the only way that they could do it.

• 38:44Cara Santa Maria?

  They knew that they wouldn't be able to get behind that curtain of, you know, the big players like OpenAI and Anthropic, who have said that they have the data, but they're not sharing it. And instead, they looked at open source LLMs. They looked at 14 different models. Apparently Meta and DeepSeek do publish some of that data. And they found that part of the reason this question is so incredibly difficult to answer is because there are so many different components that go into a single query. All queries are not equal. And so, first of all, you have to break it down into two

• 39:28Cara Santa Maria?

  components of the carbon footprint altogether. There's the carbon footprint that is produced during the training of the LLM, and then there's the carbon footprint that's produced during individual, or we can say cumulative, queries after, or kind of separated from the training. Apparently, when it comes to how much carbon is produced, what the emissions are from the training, it's it's still pretty much a black box. And most of the things you're reading online where these emissions are estimated are just based on queries. They're not based on that whole training kind of experience. The other thing that's

• 40:09Cara Santa Maria?

  so confusing is that there are so many different types of, I guess, parameters. Different LLMs have, or different AI models have different numbers of parameters that, you know, will result in different types of, or different intensities, I guess you could say, of querying. So the way that this article describes a parameter, they say they're kind of like the internal knobs and model, internal knobs that the model adjusts during training to improve its performance. So as they say, quote, "The more parameters, the more capacity the model has to learn patterns and relationships and data." GPT-4, for example, is estimated

• 40:49Cara Santa Maria?

  to have over a trillion parameters. So when they did their their analysis for this scientific publication, they basically looked at 14 open source AI models, like I mentioned, and they ranged from 7 billion to 72 billion parameters. They looked at them all on a GPU called the Nvidia A100. Apparently, we're not even using that anymore. So like even this data is out of date because we're using a much more powerful GPU now. I'm a little confused about some of the articles that I read because this article says that with a more powerful GPU, we're actually talking about more carbon emissions.

• 41:31Cara Santa Maria?

  And I've read other articles that say, no, no, moving up to, I think it's called the H100 instead of the A100 from Nvidia, actually is more efficient, so it's less carbon emission. I don't know if you guys have any insights on that, or if you've dug that deep into like the GPU of these, of these kind of chips.

• 41:51Speaker 02

  I mean, I do know that the newer, more powerful, better chips, you know, graphic cards, do calculations with less energy. That's partly why crypto miners use them. They use the latest and greatest GPUs. Yeah. Because it's all about how much money you're spending for the electricity to run the process versus how much you mine.

• 42:17Cara Santa Maria?

  Yeah, yeah, there's a purely like economic calculation going on with, with those crypto miners. I think the issue here is that in order to, to handle the load that's being put on it, they have to be upgraded, right? So even though they're more efficient, they're more efficient with a much larger load.

• 42:35Speaker 02

  Yeah.

• 42:35Cara Santa Maria?

  And so then the question is, you know, how is it netting out? Because the, the load is just getting bigger and bigger and bigger over time. More and more queries are happening every day. And they also talk about, you know, uh, you know, these different prompts that are used. Um, they think that over time, they call them inference, right? So they start with the training and then they inference is the, the life of the model where the prompts are being used. And they say over time, that's expected to account for the bulk of the model's emissions. Here's a quote by somebody who was interviewed for the article. You train a model once, then billions of users are using the model so many times. And they're saying it's hard to quantify the environmental impact because that impact can vary

• 43:20Cara Santa Maria?

  depending on which data center it's routed to, depending on which energy grid powers that data center, depending on the time of day, and that really only the companies that are running them have that information. So we're talking about not just how the actual query is routed physically, but we're also talking about the different parameters that are included within the model that's then going to handle those queries. So tokens is a word that's thrown around a lot. Can you guys define that? Those are, I mean, they define it as the bits of text a model processes to generate a response.

• 43:56Jay Novella?

  Yeah, they break, they break things down into the words, into these tokens that essentially allows them to quantify the words and then they can use those tokens to actually build sentences and things like that. It's like a way of breaking it all down into like, almost like a language in a sense. You know what I mean?

• 44:15Cara Santa Maria?

  Yeah. And so one thing that they mentioned is that we've talked about this idea before. We both talked about it when we had a, our guest Rogue on and also in previous stories that we've covered, this idea of reasoning models versus sort of traditional or standard models, where in a standard model, what the LLM is doing is a bit of a black box to us. But in a reasoning model, it sort of shows its work, right? And says, this is how I got from, from A to B to C. Reasoning models use a ton more energy use. They use a lot more tokens.

• 44:51Jay Novella?

  That would make sense.

• 44:52Cara Santa Maria?

  Yeah. So they say, on average, a reasoning model uses about, or in their study, used about 543.5 tokens per query.

• 45:01Jay Novella?

  Yeah.

• 45:02Cara Santa Maria?

  And a standard model only use 37.7.

• 45:05Jay Novella?

  Well, it has a, it has a, there's this, a cost to the processing speed. And the more tokens that you have essentially means you have a broader memory base, right? And, and there are token limits and if you hit the token limit, it just starts losing the earliest tokens in that, in, you know, in that memory space.

• 45:24Bob Novella?

  Yeah, I mean, it makes sense because, I mean, the tokens are the fundamental, like, units of text that the model processes, processes. So if you've got a lot, if you've got, you know, a lot of those tokens and you're dealing with a lot more things to manipulate and process.

• 45:37Cara Santa Maria?

  So here's a real number because you sometimes will hear things thrown around like one query, query is equivalent to using your oven for one second. Like, that's one that I, I've been seeing over and over and over, but the authors of this study are saying that that's like wildly misleading. You, you can never see a single number because it has to be a range because it totally depends on the complexity of the query, where you're making it, who you're making it to. But here is one place where the, uh, where the authors actually do use real numbers and compare it to a real life comparison. They said at scale, these queries add up and they're talking specifically about using reasoning models. They said using a 70 parameter reasoning model called DeepSeek R1, that's one of the

• 46:21Cara Santa Maria?

  ones that they used in the study, to answer 600,000 questions. Now, 600,000 questions for a single person sounds insane, but not if you look at any cross-section of time of all the people querying these, um, LLMs. That would emit as much CO2 as a round trip flight from London to New York. That's a lot.

• 46:38Jay Novella?

  Wow, that's a whole lot.

• 46:39Cara Santa Maria?

  That's a lot. And they're saying even still, none of this accounts for the emissions generated from manufacturing the hardware, from building the buildings that house it, uh, all these things that they call embodied carbon, like the carbon that's required just for producing the things that will then run. And so even in this one article where, uh, where the author is saying, don't worry about it, don't worry about it, a typical query, they say a typical query is sort of less than the energy cost in watt hours of running a 10 watt light bulb for five minutes or using your laptop for five minutes. They show that a long input query is more than that, but still less than using a microwave

• 47:21Cara Santa Maria?

  for thirty seconds or the average US household consumption per minute. But then their maximum input query, because again, they looked at it on a range, and these are numbers that were released by Epic AI. They're saying that a maximum input query is twice the average US household consumption per minute. That's, that's a lot. Seems like it. So, yes, simple, not very complex, high-efficiency queries that are routed to the right data center at the right time of day, you know, at night when the load on the grid isn't very high, could be very, very low, but incredibly complex, high parameter, token-rich queries could also be really taxing the system.

• 48:05Cara Santa Maria?

  And it's not just about the energy being used, but as we mentioned, it's then about the physical carbon that's being put out from it. So I guess my take here is, I think both extremes aren't really telling the story. I don't think it's a, don't worry about it, but I also don't think it's a, it's so dire, the planet's gonna burn tomorrow because of, you know, ChatGPT. I think we have to look at it in context of all of the other things that we do that produce large quantities of carbon, and we have to be more mindful about how we use these LLMs, right? Like, the energy supply just won't be able to sustain it as it grows and grows and grows.

• 48:48Cara Santa Maria?

  The researchers basically say, we can't have all of the, I guess, the pressure on us as individual users. We have to also think about these large energy companies and how they are externalizing these costs, these tech companies. They said, I go to conferences where grid operators are just freaking out, like, these tech companies cannot just keep doing this, things are gonna start going south. Because if your model's being used by, say, ten million users a day or more, it has to have a better energy score. It just has to. But things that we can do as individuals, if, if it's just as easy to look something up in a traditional way, do it, right? If it's just as easy to read a Google

• 49:32Cara Santa Maria?

  Query or to look something up in a way that you used to do it. Choose that. Also, they say it's very similar to AC. If the outside temperature is high, if it's the middle of a hot day and all the lights are on, like, that's not the best time to be using these L L Ms, because that means more energy to cool down the inside of the places where these servers are being housed. So think about the pressure on the grid and engage the same way you would engage with your air conditioning or with other energy-heavy appliances. You you try not to do laundry in the middle of the day at peak time. You try not to run your dishwasher in the middle of the day at peak time.

• 50:14Cara Santa Maria?

  Do that. Also, they said, literally, and I never even thought about this, any extra input takes more processing power.

• 50:21Speaker 04

  Yes.

• 50:21Cara Santa Maria?

  So.

• 50:22Speaker 04

  I was told never say please.

• 50:24Cara Santa Maria?

  That's what they say in the article. It costs millions of extra dollars because of thank you and please.

• 50:29Jay Novella?

  Oh, my God, really? That's like taking the olive out of the salad on an airline.

• 50:33Speaker 04

  No, seriously, though.

• 50:34Cara Santa Maria?

  Every unnecessary word has an influence on the runtime.

• 50:37Speaker 04

  And I am cognizant. Once I read that, I became very cognizant of it. And I did. I changed that habit in myself. Now I just keep it to as minimal

• 50:45Cara Santa Maria?

  Yeah.

• 50:45Speaker 04

  uh, amount of words as I possibly can to try to get something out of Chat G P T.

• 50:49Cara Santa Maria?

  So it's like if we want it to be more efficient, we need to learn how to use it more efficiently.

• 50:54Speaker 04

  Yeah.

• 50:55Cara Santa Maria?

  But this also, I I think personally, it it needs to be taught at in acad- in academic settings. It needs to be taught to children uh, very early in school. It needs to be taught at the university level for researchers who who actually do are are some of the most heavy users of these products. Just like we had to take library literacy classes when we were using card catalogs. And then when we were using, you know, online um, catalogs, we need to be learning how to utilize these tools in the most efficient way possible.

• 51:25Speaker 04

  Good A I hygiene.

• 51:27Cara Santa Maria?

  Yeah, yeah.

• 51:29Speaker 02

  Here's a couple of other things that I came across to Kara. So this is like an M I T study. They they found that the carbon intensity of electricity used by data centers was forty-eight percent higher than the U S average. I think because it needs on-demand energy, right? So it's going to be getting more of its energy from fossil fuel plants, right? Not going to be using wind.

• 51:50Cara Santa Maria?

  Yeah.

• 51:51Speaker 02

  But they also said so at in 2023, 4.4% of all energy in the US went to data centers. By 2028, it could be as high as 22%. And half of that will be AI.

• 52:05Cara Santa Maria?

  Yeah, they say that in this article as well.

• 52:07Speaker 02

  Yeah. So maybe maybe hard to nail down, but the broad brush stroke is is this is going to significantly increase our energy demand. And it's going to it has altered the projections of like, how much electricity will be needed in 2050? We've had to revise all those projections because of these large language models.

• 52:26Cara Santa Maria?

  Yeah, and I think I think one of the things that can is sort of the easiest for us as the end user is to just remember it's the same as, you know, that that mental shift that happens. We've talked about this a lot on the show. When you realize that throwing something, quote, away, doesn't actually make it go, quote, away.

• 52:46Speaker 04

  Only away from you. That's what that when you're the point of center point of that equation, yes, you're throwing it away from yourself.

• 52:54Cara Santa Maria?

  Exactly, but like it is going somewhere, right? Like your your trash can is not magic.

• 52:59Speaker 04

  Closer to a lot of other things.

• 53:00Cara Santa Maria?

  Yeah, and so think that way as well when we're using these digital tools that feel so ineffable, right? They don't feel like they would require a lot of energy, but they do. And so every time you sit down to use one of these tools, be mindful and say, do I need to do this right now? And yes, there are plenty of cases where we do need to do it, just like there are plenty of cases where we have to use plastic in our lives or we have to use fossil fuels, but we do not use them that way. We use them in all the cases where we don't actually, quote, need them. It's a convenience issue, and that, I think, is where we really got off track. We should start to see more regulation around this as well so that it can't be used, I guess, in a wasteful manner.

• 53:44Speaker 04

  Too frivolously, yep.

• 53:45Cara Santa Maria?

  Yeah, yeah.

• 53:47Speaker 02

  All right. Thanks, Cara. Guys, let's stop there. All right, guys. Any of you know what the protein otoferlin is?

• 53:55Jay Novella?

  No, I have no idea.

• 53:56Speaker 02

  What would your guess be? Otoferlin. What part of the body is that?

• 53:59Speaker 04

  Well, oto was Deep Space Nine.

• 54:01Cara Santa Maria?

  Oto or odo?

• 54:02Speaker 02

  O T O.

• 54:03Speaker 04

  Oh, O T O. That's different.

• 54:05Speaker 02

  Not odo from Deep Space Nine.

• 54:06Jay Novella?

  The word toe is in there. I think it has to do with your feet.

• 54:09Speaker 02

  No.

• 54:09Cara Santa Maria?

  Wait. Are you asking about the ferlin part? Is it something that opens something?

• 54:13Speaker 02

  So otoferlin is a protein.

• 54:16Cara Santa Maria?

  In your ear?

• 54:16Speaker 02

  That is necessary for the release of neurotransmitters from the inner hair cells, enabling transmission of the signal to the auditory nerve. So it's necessary to hear.

• 54:26Cara Santa Maria?

  Yeah.

• 54:27Speaker 04

  Need these proteins to hear. Okay.

• 54:29Speaker 02

  You need these proteins to hear because it releases the neurotransmitter. Basically, it makes the hair cells that detect the sound communicate neuroelectrically to the neurons and then transfer the signal to the brain, right?

• 54:42Cara Santa Maria?

  So it's transducing sound into...

• 54:44Speaker 04

  So if you're protein deficient in this area, you're not going to be able to hear.

• 54:48Speaker 02

  Exactly. So if you have a mutation of that protein, there's the otoferlin gene, O T O F. If you have a mutation in that gene so that you do not make the protein or you make an imperfect protein, that can cause deafness, right? So it's one of the forms of hereditary deafness. So where do you think this story is going?

• 55:10Cara Santa Maria?

  CRISPR.

• 55:11Speaker 04

  Ah, yeah. I'm going to edit this.

• 55:13Speaker 02

  So just, yeah, I just wanted to... I love these stories about another use for CRISPR to treat a genetic disorder, in this case, this one form of genetic deafness. It's autosomal recessive. They looked at just 10 patients aged 9 to 23. So these are, you know, older children to adults. They used an adeno-associated virus as the vector, right? So this is a viral vector. And they used, again, gene therapy to, you know, introduce the gene to produce the protein. This is mainly a safety study, right?

• 55:55Speaker 02

  This is a sort of a preliminary clinical trial, just making sure that this was safe and well tolerated. But they did, as a secondary measure, look to see, did it affect their hearing? So the side effects were, the adverse events were all minor, and it was well tolerated. It was safe. So there's, that was the primary reason for the, for the study. That's why, again, it was only a few people, only 10 people.

• 56:18Speaker 04

  Is this a mouse hearing?

• 56:19Speaker 02

  No, it was a human.

• 56:20Speaker 04

  This is human?

• 56:21Speaker 02

  This is in humans. Yes, it's in human trials, it's already past the earlier stage.

• 56:25Speaker 04

  Past the animal stage, okay.

• 56:26Speaker 02

  So the average level of threshold of hearing in the 10 subjects went from 106 decibels to 52 decibels. So lower is better, right? So the, yeah, they, they were able to hear softer sounds. 106 is loud, I mean, so.

• 56:45Speaker 04

  Yeah.

• 56:46Speaker 02

  That's why they were functionally deaf. So that's pretty impressive.

• 56:49Speaker 04

  Right, yeah.

• 56:50Speaker 02

  Yeah, so it basically worked and was safe. We have to see how sustainable it is. And there's a question of like, how old the, the subject can be and have it still work? Because these are still young adults, you know, at the high end, 23.9 years. And this was, they followed these participants for at least six months, which is a good follow-up. But, you know, we need to see what it's like when we follow them up for years. They did see an age-dependent therapeutic effect, so it was better outcomes in the younger kids than in the old, than in the young adults. So, you know, this is the kind of thing where if you like get diagnosed with this at a young age, you might be able to treat you, maybe even treat toddlers with this, who knows? You know, you have to get it approved for, for very young children.

• 57:32Speaker 02

  The key, I think the tricky bit is the, the viral vector. Again, for these CRISPR-based therapies, the vector is like the big thing, right? That is the, the main limiting factor. And viral vectors are, can be effective.

• 57:50Speaker 02

  But they could also be risky.

• 57:52Speaker 04

  Deadly.

• 57:53Speaker 02

  This is why, talk about the nanoparticles, lipid nanoparticles. When they're feasible, depending on where you need to get them in the body. They're much better. They carry bigger payloads and they don't cause infection.

• 58:06Speaker 04

  Those are the fat bubbles, right?

• 58:08Speaker 02

  Yeah, the fat bubbles.

• 58:09Cara Santa Maria?

  I'm digging in, Steve, to the incidence rate and it's really low. It looks like this qualifies, or at least is listed on a lot of like rare disease.

• 58:18Speaker 02

  It's a rare disease.

• 58:18Cara Santa Maria?

  Yeah. And so that's like such a great thing about, yeah, about using CRISPR or using different kind of gene therapies that are so targeted is we can actually target rare diseases where there wasn't a lot of, I don't know, I mean, there wasn't enough, I guess, money.

• 58:36Bob Novella?

  Not just rare, not just rare.

• 58:37Speaker 02

  They're all bespoke anyway.

• 58:39Cara Santa Maria?

  Yeah, yeah, yeah.

• 58:40Bob Novella?

  Yeah, I mean, Steve, you've mentioned recently a couple where they were just like, this is for one person.

• 58:45Speaker 02

  It was, yeah, it was for, it was that child that was born with its own specific mutation.

• 58:50Speaker 04

  Wow.

• 58:50Speaker 02

  That they were able to treat. Yeah, that's the thing. These are all, these are often all bespoke anyway.

• 58:56Bob Novella?

  So what was the, Steve, what was the decibel rating before? A hundred and what?

• 59:01Speaker 02

  Hundred and six.

• 59:03Bob Novella?

  Hundred and six. That's around a chainsaw or a handheld drill. And 50 decibels, I see listed here as a quiet office.

• 59:12Speaker 02

  Yes.

• 59:12Bob Novella?

  60 is normal conversation and like 45 is like light rain. So damn, man, that's, that's life changing.

• 59:19Speaker 02

  Yeah, brought that down into the range of conversation. Yeah.

• 59:23Cara Santa Maria?

  Wow.

• 59:24Speaker 02

  Exactly. Very encouraging.

• 59:26Speaker 04

  Effectively curing it.

• 59:27Speaker 02

  Yeah. But what can they do for us, Steve?

• 59:29Speaker 04

  Us old folks?

• 59:30Speaker 02

  Yeah, who knows?

• 59:31Speaker 04

  Yeah.

• 59:31Speaker 02

  This is a genetic disease. Like genetic fixes are great for genetic diseases.

• 59:37Speaker 04

  We need regenerative, you know, something to keep our cells and our hairs from, what? Diminishing.

• 59:45Cara Santa Maria?

  Yeah, but then you gotta toe that line between aging and cancer.

• 59:49Speaker 02

  Hmm. That's a, you know, if you're getting to the stem cells, sort of regenerative kind of approach. It would be great if we could just regrow those hairs.

• 59:55Speaker 04

  Wouldn't it?

• 59:56Bob Novella?

  Oh, my God.

• 59:57Speaker 02

  Once they break off, you basically lose those frequencies.

• 59:59Speaker 04

  Some monsterism.

• 1:00:03Speaker 02

  All right, Evan, tell us about persistent food myths.

• 1:00:07Speaker 04

  Yeah, food myths. So this was a neat little article that came out recently titled Grandma Was Wrong. Food myths debunked. And this caught my attention specifically because in my family, when I was born, my paternal grandmother was already dead. So I did have, you know, my maternal grandmother was alive, but not, you know, not for long. I didn't have, I didn't have much of a relationship with her growing up. A bit estranged and, you know, then she passed away. So there wasn't grandma's home cooking as part of my upbringing. But I think for you, do you guys have memories of your grandma's home cooking?

• 1:00:45Bob Novella?

  Both of them, man.

• 1:00:46Speaker 02

  Sure.

• 1:00:46Jay Novella?

  Oh, hell yeah, yep.

• 1:00:47Speaker 04

  And, and what, long lasting memories and, you know,

• 1:00:52Speaker 02

  Oh, my God.

• 1:00:53Speaker 04

  The big meals.

• 1:00:54Bob Novella?

  Two Italian grandmas, what do you think?

• 1:00:59Speaker 04

  Yeah, yeah, a little different for me. So again, I didn't, I didn't really have much of that experience in my life. According to this article, a recent survey found 42% of Americans prefer to cook meals traditionally like their elders. But they also, you know, as we learn more about food, food science and other things as time goes on, you know, grandma used to do maybe some things in her traditional food cooking that was maybe not the, the best advice or was outright, you know, just silly and had, you know, no impact, you know? And there were, this article lists a couple of examples of that. So I want to share those with you that they talked about here. These are the myths. Rinsing raw chicken before cooking.

• 1:01:44Speaker 04

  I'll tell you, again, I don't have the experience of, you know, having much of a, you know, grandparents and the cooking experience. I've never rinsed my, I never learned to rinse raw chicken before cooking. It never became a practice. It was never habitual in my, in my family. And do you guys know why that's, first of all, a myth and why it's not good?

• 1:02:05Speaker 02

  I mean, I would think because of salmonella, whatever, like something like that.

• 1:02:09Speaker 04

  Yes.

• 1:02:09Cara Santa Maria?

  Like it spreads it when you rinse it?

• 1:02:11Speaker 04

  It spreads it, that's right. It doesn't wash it away. You don't wash it away. It just splatters around, basically. It can only make things worse through its contamination. Has anyone here rinsed their raw chicken before cooking? No.

• 1:02:25Speaker 02

  No, but what you should do, though, is like really limit the surfaces that the chicken comes in contact with. And make sure that those are cleaned and sanitized very well. But the chicken itself, you've just got to cook it properly.

• 1:02:37Speaker 04

  165 degrees Fahrenheit is the correct internal temperature it should be to kill all that bacteria.

• 1:02:45Cara Santa Maria?

  I also have a cutting board that's just a chicken cutting board.

• 1:02:48Speaker 04

  Mm-hmm, yeah, I use the same.

• 1:02:49Cara Santa Maria?

  Don't use the vegetable one, yeah.

• 1:02:51Speaker 04

  I do, I have a specific.

• 1:02:53Speaker 02

  All right, is it glass, plastic, or wood?

• 1:02:56Speaker 04

  Wood.

• 1:02:57Cara Santa Maria?

  Ooh, my cutting board?

• 1:02:58Speaker 04

  Not wood.

• 1:02:59Cara Santa Maria?

  It's plastic.

• 1:03:01Speaker 02

  See, that's, it's, it's hard to know, which would, I've done a deep dive on this and there's no clear answer, really. Because, because when you get little scratches in the plastic, the bacteria can hide in there very well.

• 1:03:13Cara Santa Maria?

  Yeah, but I, but I can also then just put it in the dishwasher.

• 1:03:17Speaker 04

  Yes.

• 1:03:17Cara Santa Maria?

  And that's like, you know, basically decontaminating it.

• 1:03:20Bob Novella?

  Yeah, I don't put our wooden cutting board in the dishwasher. I do that. I clean that.

• 1:03:24Speaker 04

  Right, because you can't, it'll, it'll crack.

• 1:03:26Cara Santa Maria?

  I don't use wood for anything but vegetables. Or like charcuterie.

• 1:03:31Speaker 02

  But it's good to keep them separate.

• 1:03:33Speaker 04

  How about this myth? Bread stays fresher in the refrigerator.

• 1:03:37Cara Santa Maria?

  Ooh, I always put my bread in the fridge. Oh, no.

• 1:03:42Speaker 02

  Well, hold on a second, hold on, because if you put, if you buy store-bought bread and you put it in the refrigerator, it does have preservatives in it. It will slow down any mold happening on that bread by a lot if you just leave it on the shelf.

• 1:03:56Cara Santa Maria?

  Yeah, I mean, I feel like I've observed that. Am I wrong?

• 1:04:00Speaker 04

  Have you?

• 1:04:00Cara Santa Maria?

  I've never done a controlled study, but I definitely feel like when a loaf of bread is in the fridge, it lasts longer. That doesn't mean it tastes fresher, but it lasts longer.

• 1:04:08Speaker 04

  For freshness, it says here, "Sandwich bread, buttermilk biscuits and rolls should be stored on the counter in a bread box or frozen." You can freeze them.

• 1:04:17Bob Novella?

  Freezing is your friend with bread.

• 1:04:19Jay Novella?

  Definitely. I mean, there is a big difference between refrigerating it and freezing.

• 1:04:24Speaker 04

  Right.

• 1:04:24Jay Novella?

  Like, when I make bread, I usually make at least two loaves, and I always put one in the freezer. And I can get that bread back to about eighty to ninety percent of what it was like when I baked it fresh. I figured out how to do that. You can't get it back if it goes in standard refrigerator temperature.

• 1:04:42Speaker 04

  And that's what this article is citing as well, yep.

• 1:04:45Speaker 02

  Yeah, I think what you guys are perceiving in terms of like the better outcome is that you just need to have it sealed. So putting it in a bread box, and I always put bread, I make sure like they are sealed. You know what I mean? That it's in something completely airtight. It's fine. They do perfectly fine. Then refrigerating it adds, there's no added benefit if it's sealed.

• 1:05:09Cara Santa Maria?

  Yeah, but I also think you're talking about the difference, am I wrong here, Evan? You're talking about the difference between it tasting fresh?

• 1:05:16Speaker 04

  Mm-hmm.

• 1:05:17Cara Santa Maria?

  Like, the starches being the right consistency and all of that versus growing mold. A refrigerator is going to reduce how quickly mold grows on bread. But it might not be fresh bread. It'll be stale bread that has less mold.

• 1:05:30Speaker 04

  Yeah, and they did say there are some, you know, it depends on your environment. Some houses have air conditioning, some don't. So you may, yes, the refrigerator might be the better option in that case. But in a controlled temperature environment, they are saying use the bread box when you can. What happens if you put the bread into the refrigerator? The cold temperature will cause recrystallization of the starch, and that's moisture loss. And then your bread starts to lose its, you know, taste, consistency, and all the other features that make your bread enjoyable. What about storing your tomatoes in the refrigerator?

• 1:06:05Jay Novella?

  Um, I don't do that. I'd say no.

• 1:06:07Speaker 04

  I've never done that either, no. And in fact, I've known for quite some time that you shouldn't do that. They recommend that you not do that. Researchers, what, from the University of California Davis, explain that cold temperatures mess with the enzymes that flavor tomatoes, leaving them mealy and bland. Yuck. Keep them out on the counter. Keep them on the counter, but out of direct sunlight. Wait till they're ripe and enjoy. What about this? I've never heard this one. Let hot food cool to room temperature.

• 1:06:34Speaker 02

  Oh, yeah. I did a whole deep dive on this.

• 1:06:37Speaker 04

  Before putting it in the refrigerator?

• 1:06:39Speaker 02

  Yes. You're not supposed to do that. So that here's the bottom, the best way to think about this is how much time is your food spending at a temperature where bacteria can grow? That's the bottom line. So you always want to, you know, get it up to eating temperature and eat it fairly quickly. And then when you're done with it, you want to get it at refrigerator temperature as quickly as possible. You don't want it to spend hours and hours at bacterial growth temperature. And room temperature is that. You don't want it at room temperature. You don't want it warm.

• 1:07:13Cara Santa Maria?

  Yeah, it's like that fried rice disease thing.

• 1:07:15Speaker 02

  Yeah, you want to get it, you eat it. And I'm kind of obsessed with that. I hate when people leave food out after dinner. Like as soon as you're done eating.

• 1:07:22Speaker 04

  Right, three hours later.

• 1:07:22Speaker 02

  Put that, yeah, right away. Get it into Tupperware, get it into the refrigerator right away.

• 1:07:27Cara Santa Maria?

  I feel like this one comes from the, the tru, the, the reality that you can't put like boiling hot liquid that's in hot glass into a refrigerator.

• 1:07:37Speaker 02

  That's a separate issue and that's correct.

• 1:07:38Speaker 04

  Yeah, and that could.

• 1:07:39Cara Santa Maria?

  Cause you don't want to shatter the glass.

• 1:07:40Speaker 02

  Exactly.

• 1:07:41Speaker 04

  Yeah, right. You don't want to do that, you know, and that could be part of people's calculus as far as, you know, how they're thinking about this.

• 1:07:49Cara Santa Maria?

  I also usually like will vent the lid because if you put it straight in while it's still hot, then it's all full of condensation.

• 1:07:55Speaker 04

  Yeah, the condensation as well. Should you be washing your produce with soap?

• 1:08:01Speaker 02

  No.

• 1:08:02Speaker 04

  No, I never did that either. In fact, I've never even used, they do have vegetable wash sprays. Have you seen those?

• 1:08:07Cara Santa Maria?

  I've used, I've used vegetable wash.

• 1:08:08Speaker 02

  I use vinegar if I want to do that.

• 1:08:10Cara Santa Maria?

  You can also use vinegar, yeah. They make vegetable wash, but that's not soap.

• 1:08:14Speaker 04

  Yeah, it's not soap. I know, I don't, I've never, but that's why this is strange to me. I'm like, really? Did people's grandmothers wash their? Vegetables with soap? I'd never really heard of that.

• 1:08:23Bob Novella?

  Wow.

• 1:08:24Cara Santa Maria?

  Yikes.

• 1:08:24Speaker 04

  Apparently that's a thing.

• 1:08:25Speaker 02

  Water's fine. As long as you, if you want to make sure it's clean, you just gotta scrub it. Like just get your, whatever you're, you know, you wash stuff with, your towel or paper towels. And just, you know, you just want to scrub it a little bit. Just the physical, physically wash it. You don't, you don't want to use soap. You don't want to put soap on your food.

• 1:08:42Speaker 04

  Right.

• 1:08:42Cara Santa Maria?

  You don't want to eat soap, ever.

• 1:08:44Speaker 04

  No, right, you can't think of, is there a reason to eat soap?

• 1:08:48Cara Santa Maria?

  No.

• 1:08:49Bob Novella?

  If you say some nasty curses.

• 1:08:51Cara Santa Maria?

  You might have to eat some soap.

• 1:08:52Speaker 04

  There's more on the list.

• 1:08:53Cara Santa Maria?

  That's actually abusive, yeah. Watch somebody's mouth with soap.

• 1:08:56Speaker 04

  And let me throw out one more, I'll, because it's a longer list, but I'll just end with this one. Uh, because this one I had not heard before either. Watermelon seeds will sprout in your stomach.

• 1:09:05Speaker 02

  Oh, that's old.

• 1:09:07Speaker 04

  That's like chewing, like swallowing the gum kind of thing, right?

• 1:09:10Cara Santa Maria?

  Yeah.

• 1:09:10Jay Novella?

  I had a plant, the watermelon plant was coming up out of my throat with the vine.

• 1:09:17Speaker 04

  I mean, that's right out of mythology or something, you know, like some Jack and the Beanstalk kind of story. I don't know. And you, had you guys heard of that before as a myth?

• 1:09:26Cara Santa Maria?

  Yeah, but why did, I guess, where do these things come from? Why would grandma not want you to swallow the seeds? Because she's afraid. Yeah, no, I get that, like grandma didn't think they would sprout in your stomach.

• 1:09:37Speaker 04

  Yeah, why would they care?

• 1:09:38Cara Santa Maria?

  Grandma didn't, just didn't want you eating the seeds. Is that because she had diverticulitis and when she ate the seeds, she felt like sick all the time?

• 1:09:46Bob Novella?

  Well, I mean, apple seeds are, have little.

• 1:09:48Cara Santa Maria?

  Have arsenic.

• 1:09:49Bob Novella?

  arsenic in it, so maybe it stemmed from that?

• 1:09:52Cara Santa Maria?

  Maybe.

• 1:09:52Speaker 04

  Perhaps.

• 1:09:53Cara Santa Maria?

  But nobody eats apple seeds.

• 1:09:55Jay Novella?

  So, yeah.

• 1:09:56Speaker 04

  You shouldn't.

• 1:09:56Jay Novella?

  Somebody that we know, Kara, eats the entire apple.

• 1:09:59Cara Santa Maria?

  That is.

• 1:10:00Speaker 04

  Is it a horse?

• 1:10:01Cara Santa Maria?

  Bananas. They eat the core of the apple?

• 1:10:06Cara Santa Maria?

  What?

• 1:10:07Jay Novella?

  Lots of people do that.

• 1:10:07Speaker 04

  Bob, I got that.

• 1:10:08Cara Santa Maria?

  No.

• 1:10:10Jay Novella?

  You gotta believe me, because I don't lie to you.

• 1:10:12Cara Santa Maria?

  Whereas with watermelon, like there's seeds in every bite.

• 1:10:15Bob Novella?

  Unless you got the seeds.

• 1:10:15Speaker 04

  Seedless ones.

• 1:10:16Bob Novella?

  Seedless.

• 1:10:17Cara Santa Maria?

  They still have seeds. They're just white seeds. They're not big, glassy.

• 1:10:20Speaker 04

  Yeah, they're little, tiny seeds.

• 1:10:20Jay Novella?

  They're seedlings.

• 1:10:21Speaker 04

  There are seeds in a lot of your vegetables, think. And there's a whole other list here, but those are some of the, uh, fun ones. Fun ones to review.

• 1:10:28Speaker 02

  All right, thanks, Evan. Bob, another AI article, last one to finish up the news. AI is going to help us with our enzyme engineering.

• 1:10:36Bob Novella?

  Oh, boy, yeah, this was so much fun. Okay, so guys, what happens when you combine automated robotics, synthetic biology, and that ubiquitous two-letter initialism that we call AI?

• 1:10:48Bob Novella?

  You get not only a technology that's brimming with potential, I mean, really, wow, but it's also an exciting solution to a powerful but limited biological tool used in industry, the lowly enzyme. This is from journal Nature Communications. The name of the study is "A Generalized Platform for Artificial Intelligence Powered Autonomous Enzyme Engineering." Study was led by Hua Min Zhao, professor of chemical and biomolecular engineering at the University of Illinois. Okay, so what's going on here? So it starts with enzymes, got to do a little table setting with the enzymes. These are specialized proteins, right, like most of the human body is comprised of, essentially strings of hundreds of amino acids or more that fold up into a specific shape, and that

• 1:11:32Bob Novella?

  shape directly translates into a specific function. And that specific function for enzymes is absolutely critical for life. I mean, we're talking like eating, digesting, breathing, reproduction, moving, none of that would happen without enzymes. And that's the hallmark of them and what makes them invaluable. They speed up chemical reactions by offering a low-energy path, essentially a shortcut. And it's not just a little bit faster. I read somewhere that enzymes, that without enzymes, digestion could take years, something like years or months, whatever. I mean, you'd be long dead before you've got any benefit from it. So, yeah, pretty important stuff. But this is just the biological role of enzymes in our body. It's just one side of the coin. They have a powerful presence outside of our bodies that you might be less familiar

• 1:12:16Bob Novella?

  with, and that's for industrial use. So there's so many industrial applications of enzymes. We're talking food production, pharmaceuticals, biofuels, biomaterials, textiles, detergents, wastewater treatment, and that's just to name a few. It's kind of endless. So now, these enzymes are essentially amazing little machines in this capacity, but they're underutilized because using them often involves some very frustrating roadblocks when you dig deep into it. They can be inefficient in a lot of ways. They sometimes don't have the ability that you would like to single out a specific target, you know, in this ridiculously complex chemical environment that they find themselves in. So, all right. To sum this up so far, we've got these amazing biological tools.

• 1:13:01Bob Novella?

  These are the enzymes that are critical to life. But also for many industries, they're essentially straitjacketed by the inefficiencies and inaccuracies at times for these enzymes. And then this is where this new study comes in. The study had a goal to solve this problem by improving protein function. But as the lead author Zhao said, he said, improving protein function, particularly enzyme function, is challenging because we don't know exactly what kinds of mutations we should introduce. And it's usually not just a single mutation, it's a lot of synergistic mutations. So this is, it's tough to tweak these enzymes and make them better at what they do. So they describe in their paper their solution to this problem,

• 1:13:46Bob Novella?

  which brings three technologies together like never before. And these are, like I said, AI, automated robotics, and synthetic biology. So let's start with the AI leg of this tripod. So for AI, they use deep learning with its layered artificial neural networks, right? And these networks analyze data and learn complex patterns, right? We've talked about this on the show before. This deep learning, though, also uses a protein language model, not an LLM, but a PLM, which essentially is using the languages, the language of proteins. It's fluent not in English, but in the language of proteins. Now, the AI's job in this role is to look at the genetic code and optimize it for the desired functions.

• 1:14:31Bob Novella?

  Remember, guys, you can't just brute force this thing. You know, you can't just like change, make little tweaks and random tweaks, and see what happens, test it, and make more. I mean, there's more possible amino acid combinations than atoms in the universe. How many atoms are there in the universe?

• 1:14:47Speaker 04

  Ten to the power of eighty.

• 1:14:48Bob Novella?

  Ten to the eightieth, ten to the eightieth power. And of course, you know I looked this up, that's a hundred octillion sexticillion. Just saying. Oh, yeah. So their AI, so their AI instead, what it doesn't, it would determine a small amount of possible sequence changes. And that, those sequence changes is based on its training on enzyme function and structure, and also, of course, the fluency of its protein language model. So it says, alright, here's, here's these suggestions that we, the tweaks that we can make to these, to these enzymes. So that's what the AI leg of this enzyme upgrade solution does. That's the first part. So then next comes the other, the other two legs of this tripod. We've got the robotic automation component and synthetic biology.

• 1:15:33Bob Novella?

  So these, these AI suggestions would be sent to what the University of Illinois calls its iBio foundry. And this seems like it belongs on the goddamn enterprise. This thing is like, what? This is fascinating. So this iBio foundry uses robotic platforms and computational tools, and it actually builds the enzymes that the AI is suggesting from scratch, from scratch, not just, not going into an enzyme and making a tweak. It's just building it piece by piece from scratch, and then it tests them. So it doesn't, doesn't just build them, it actually tests them to see how well they, they perform based on, on what the, you know, what the desired new updated functionality of that enzyme is.

• 1:16:14Bob Novella?

  And then that, its performance is sent back to the AI, and, and then that makes new suggestions based on this new information, and the process repeats over and over and over. These are being called self-driving labs. They're, they're powerful automated AI-guided platforms for enzyme engineering. And once this process starts, as I've described it, it's essentially running on its own with minimal supervision, or essentially no supervision at all at this point. So that's why they're calling it self-driving labs. So of course, the proof of the pudding, as they say, is in the tasting. So what are the results? What, what did they achieve using this new methodology? So they used two key industrial enzymes here, and both of them came back with substantially

• 1:16:59Bob Novella?

  improved performance. It's kind of dramatic, I think. So one enzyme, they use it in industry, they, to add to animal feed, to, to improve the nutrition of the food. This process, this new process that they have here, increases its activity by 26 times after being tweaked. The second enzyme, which is used for just a generic industrial chemical synthesis, the paper says. It had 16 times greater activity and this enzyme also had 90 times greater substrate preference, which means that it was far less likely to target chemicals that it was not supposed to target. So that's substrate preference, 90 times greater. So these seem

• 1:17:39Bob Novella?

  pretty dramatic to me as basically a proof of concept for this new technique. So what are we talking about now in the near future? I mean, this is what they're basically doing now. And they've designed this to be generic for just proteins in general. It's not just for these two enzymes that they tested. They made this so that it can be used for enzymes and proteins just in general. So in the very near future, what they plan on doing is somewhat predictable, as you might imagine, continue improving their AI models. They want to upgrade the equipment, make it faster, higher throughput, faster testing, all that stuff. But they also have, and it seems like they've already gone a long ways in having this, they want to create an entirely new user interface that can use simple typed queries. Because

• 1:18:24Bob Novella?

  I believe now you need to be able to like code it in Python in order to really get this system to do what you want it to do. But the new interface they're talking about would kind of almost be like an LLM, just type in what you want. Maybe, I'm sure there's some structure to it, and make very easily for non-specialists to use this system so that they can work on improving the enzymes that they want to improve, or if they want to improve, you know, drug development times, or maybe they want to make new innovations in energy and technology, they can use these systems as well. What do you guys think?

• 1:18:58Speaker 02

  I mean, industrial enzymes are a huge industry, it's a huge part of industry. So yeah, anything that can automate or increase the ability to make more efficient, more targeted enzymes could have a wide-ranging impact on, across many different industries.

• 1:19:16Bob Novella?

  I mean, look at the results of, you know, 26 times, you know, the activity for one enzyme or this other enzyme had 90 times greater substrate preference. That's just dramatic. I mean, imagine starting, just applying this, you know, once they tweak and get it even more efficient and better AI, you know, better protein language models. I mean, it just seems like this has got nowhere to go, but just dramatically up. But we will see, who knows what can kill these things, but fascinating stuff.

• 1:19:46Jay Novella?

  All right, thanks Bob. Jay, it's Who's That Noisy time. All right, guys, last week I played This Noisy.

• 1:20:02Jay Novella?

  What do you think?

• 1:20:02Speaker 02

  Don't like it.

• 1:20:03Jay Novella?

  Don't like it?

• 1:20:05Speaker 04

  Not your fave.

• 1:20:06Jay Novella?

  Not a pleasant noise. I mean, it sounds mechanical, like something's grinding or spinning or whatever. But yeah, the noise up front, like the slapping noise, I don't know what that is. Well, Visto Tuti wrote in, and Visto said, "This one sounds like a chiringa or a bull roar. This is a carved wooden wing, and it's attached to a length of rope and spun around so that the wing produces a loud sound as it beats the air." Yeah, so these were used to signal over large distances, and you could find these used in Australia, I think even today.

• 1:20:39Speaker 02

  Didn't Crocodile Dundee use one in the movie?

• 1:20:41Jay Novella?

  Yes, that is correct, Steve. A listener named M O J C A.

• 1:20:46Speaker 04

  M O J C A?

• 1:20:48Jay Novella?

  Mojka?

• 1:20:49Speaker 04

  Moka?

• 1:20:50Jay Novella?

  Moja?

• 1:20:51Speaker 04

  Is it Moka? Is it? The Jay silent?

• 1:20:54Jay Novella?

  And last name is Kolesek. "Hi Jay, I'm gonna guess the noisy is a drill bit, but since this would be too boring, and also due to strange frequencies, I'm guessing it's one of those two or three-headed drills I've seen all over the internet lately." I have not seen that, I don't know what you're talking about. It's intriguing, I definitely would like to look that up. But you are not correct, but thanks for guessing. Hunter Richards wrote in and said, "Hi Jay, I'm not too late. Is this the mini steam-powered train, the kind that's big enough to ride on Not In and not a model train? Or it's Bendered?" Yeah, I don't, I'm not, I don't know what you're hearing there. I'm not hearing that, but thanks for the guess.

• 1:21:37Jay Novella?

  You know, everybody, we have different memories that influence what we think we hear. So I do have a winner this week. I had several winners this week. The person that guessed first was Shane Hamblin, and Shane says, "Hey skeptics, guiders, I was listening to this podcast with my dad and immediately knew what this was. The noisy from the June 28th podcast was when you put a bolt or a nut, not a peanut, in a balloon and put air in the balloon and spin it. You can hear the nut slow down at the end of the noisy until it drops to the bottom of the balloon. That's exactly what this sound is. Listen again."

• 1:22:20Jay Novella?

  I will warn you that if you do, if you do this and you use a heavier sized nut, it could rip through the balloon, so be careful. So, good guess, good job. Shane, I did have other people guess, I wanted to mention this. Nathan Drake wrote in and said, "Hey Jay, listening since before my son was born in 2010. Never had any idea, but this week to me sounded like a combustion engine, starting and revving slowly then dying. My son Wyatt, in the backseat of the car, said I was wrong and that it's a hex nut spinning in a balloon and that you could tell because of the thud at the end when it finishes." Very cool. So, he guessed it right, his dad was wrong, and I like that he, he heard the little detail at the end, right, about the nut like basically slowing down and bouncing around in the balloon

• 1:23:03Jay Novella?

  when it didn't have the momentum to be spinning like, like going around the circumference of the balloon. Very good guess Wyatt. So, I have a new noisy though for you guys this week, and I'm curious to know what Kara thinks of this.

• 1:23:27Speaker 02

  That's a Space Invaders.

• 1:23:30Jay Novella?

  I suspect this week is gonna be very difficult, but I will give you no clues, because everybody like completely went crazy on the Space Invaders one, like I got so many emails and everyone saying, "Oh my gosh, too easy, too easy." A lot of people had fun, you know, writing in and saying, you know, getting one. Uh, the bottom line is, this one's hard, good luck. If you think you know this week's noisy, or you heard something cool, you can email me at [email protected]. Quickly, we have a show in Kansas, guys, on September 20th. We have two shows, a private show, which is a live podcast recording, and then at night we'll be doing our stage show, which is the Skeptical Extravaganza of special significance. If you're interested in seeing us live on these, you know, two different types of shows,

• 1:24:15Jay Novella?

  you could come to one or both, whatever you want to do, go to theskepticsguy.org, there's a button on there for each of these, and you know, we just would like it if you'd join us, because it's a, it's a fun day, uh, those who will spend the whole day with us, you know, we have a lot of people that do that. You know, then there's synergy between the two shows that only you will get if you, you know, at the second show, which is pretty, pretty cool.

• 1:24:38Speaker 02

  All right. Thanks, Jay. We're going to hit you guys with a new segment. I call this segment, Why Didn't I Know This?

• 1:24:45Speaker 04

  Yeah.

• 1:24:46Speaker 02

  Inspired by Evan.

• 1:24:48Speaker 04

  Yes.

• 1:24:49Speaker 02

  Does an email saying, Why Didn't I Know This? Talking about the Great Attractor. So yeah, let's talk about the Great Attractor. And we could see if this works out as a new segment where we just talk about something in the world of whatever science and reality. That we never, maybe, maybe you never heard of, but it's kind of cool.

• 1:25:08Speaker 04

  And I brought this up specifically, I was, you know, YouTube has shorts, right? They're basically little TikTok videos, vignettes of videos and whatnot. And I get, you know, like any person, I get stuck in down the rabbit hole sometimes. And one came up of Neil deGrasse Tyson talking about how we are, you know, how fast we're moving through space, you know? Everything relative to, you know, our entire

• 1:25:34Speaker 02

  Other stuff.

• 1:25:34Speaker 04

  Solar system that's moving right and everything else. We're basically going at what? 2.1 million kilometers per hour at one certain measure. So I was like, okay, yeah, we're going pretty fast. And then he mentioned the Great Attractor, because apparently that's the direction our entire Milky Way galaxy is generally heading, along with a bunch of other galaxies. Now, this is, this was new to me for, I'd not heard of this before. I spoke to Bob a little bit about it and asked Bob if we had brought this up on, if this had come up as a subject at all on the Skeptic's Guide before. And Bob, what? You said you didn't have any recollection of it either, right?

• 1:26:15Speaker 02

  Yeah, I don't know if we've ever spoken about it.

• 1:26:17Speaker 04

  Okay, so good. Then, then nobody, I'm not, I'm not misremembering, right?

• 1:26:22Speaker 02

  So here it is, but yeah, but we've read about this before, but you know, just getting myself updated on it. It's interesting. So in order to know what the Great Attractor is, you have to know a little bit about the structure of our part of the universe. So you guys know that our galaxy is the Milky Way?

• 1:26:38Speaker 04

  Yes.

• 1:26:39Speaker 02

  Right? Do you know that our galaxy is part of a local group? Yes.

• 1:26:44Bob Novella?

  Better, because I've only mentioned it about a dozen times.

• 1:26:46Speaker 02

  The Virgo, is it the Virgo group? No, you're two, you're two, you're two levels high. Oh, okay. So the local group includes the Milky Way, the Andromeda Galaxy, the Triangulum Galaxy, and a bunch of dwarf galaxies, right? That's our local group.

• 1:26:59Bob Novella?

  It's anywhere, I've heard numbers from anywhere from fifty to sixty to over a hundred galaxies.

• 1:27:04Speaker 02

  Yeah.

• 1:27:04Bob Novella?

  Yeah, many of them dwarf galaxies, many of them hidden, they think.

• 1:27:07Speaker 02

  Right.

• 1:27:07Bob Novella?

  So, that's why the number is kind of big.

• 1:27:10Speaker 02

  Ten million light years across, right? That's our local group. That's the next notch up above our galaxy.

• 1:27:16Bob Novella?

  And that's the group that we will all eventually merge with.

• 1:27:20Speaker 02

  Mm-hmm. Nice. Eventually. Now, the local group is part of the local sheet. The local sheet is a flattened structure containing several local groups.

• 1:27:32Bob Novella?

  No sheet.

• 1:27:33Speaker 02

  Yeah, the local sheet. So there's two other groups, like the M81 group and the Centauri Z group, combined with our local group that make up the local sheet, okay?

• 1:27:43Bob Novella?

  Okay, next step up?

• 1:27:43Speaker 02

  Next up is the Virgo supercluster. Okay. Right, this is the, that's what we think of. That's our local supercluster. This is about thirteen hundred galaxies, and it's about a hundred and ten million light years across. But that's not it. That's at the highest level. The Virgo supercluster is part of the Lani Akia supercluster.

• 1:28:04Bob Novella?

  Yes, which I talked about like eight, what, nine, ten years ago?

• 1:28:07Speaker 02

  Yeah, which is.

• 1:28:08Bob Novella?

  When we discovered that, that was a good.

• 1:28:09Speaker 02

  Five hundred and twenty million light years across. Oh, it's crazy. Now.

• 1:28:13Cara Santa Maria?

  I don't like this. Why are they both called superclusters?

• 1:28:16Speaker 02

  You know. Well, one's a super-dupercluster. It's a super, we'll call it a super-dupercluster.

• 1:28:20Cara Santa Maria?

  It should be an ubercluster.

• 1:28:22Speaker 02

  So there's about a hundred thousand galaxies in the Lani Akia supercluster. Now, at the very gravitational center of the Lani Akia supercluster is the Great Attractor. Whoa. And it's a, it's, it's more than a galaxy, it's a con, it's a concentration of mass that's ten to the sixteenth solar masses, that's massive. And so it's, basically, it's probably a supercluster, right? So there's a supercluster in the middle of the. The Lani Akia supercluster, and that is the center of gravity of the biggest, the bigger supercluster.

• 1:29:03Speaker 02

  And so, everything is moving towards it, including the Milky Way galaxy.

• 1:29:08Bob Novella?

  Right. It's hard to see, I mean, they see, they see something there, they call it the Norma cluster, but it's, that's only part of, you know, part of what's there, so it's kind of obscure, so they're not really sure, and that's why it was kind of mysterious. But my question, Steve, is, now, I've read over and over that the, that we will, all our, all the local galaxies, fifty to a hundred of our local galaxies in our local group, will merge eventually, but the question is, will, I mean, will the expansion of space win out over?

• 1:29:38Speaker 02

  I think so.

• 1:29:39Bob Novella?

  The Lani Akia, it's got, yeah.

• 1:29:40Speaker 02

  I think so, I think it's, it's too big, it's too big for

• 1:29:44Bob Novella?

  So big.

• 1:29:45Speaker 02

  gravitational binding, you know what I mean? So, yeah.

• 1:29:48Bob Novella?

  Yeah.

• 1:29:49Speaker 02

  The expansion will overcome the gravitational attraction of the Lani Akia supercluster, not our local group. I don't know about the Virgo supercluster, but definitely the, um, the Lani Akia.

• 1:29:58Bob Novella?

  Yeah, I think even the Virgo supercluster will eventually go bye-bye.

• 1:30:01Speaker 02

  Maybe, yeah, yeah.

• 1:30:02Cara Santa Maria?

  So, when you say it'll win out, you mean eventually, but right now, we're moving towards?

• 1:30:06Speaker 02

  We're moving towards it, but it's, but the expansion's greater. So, here's the thing, when we look at all, so we can't see it directly because it's in the quote-unquote "zone of avoidance," which basically is the

• 1:30:16Bob Novella?

  I love that.

• 1:30:17Speaker 04

  But don't let that scare you.

• 1:30:18Speaker 02

  No, it's, it's part of

• 1:30:19Speaker 04

  Part of a region.

• 1:30:20Speaker 02

  It's a part of the universe we can't see because the center of the galaxy's in our way, right? So, we

• 1:30:25Bob Novella?

  It's very annoying when that happens.

• 1:30:26Speaker 02

  The dust and, and stars and everything in our own galaxy keep us from, from seeing that, that strip. And that's where the great attractor is, happens to be obscured by this zone of avoidance. But, when we did a massive survey of the redshift of the galaxies in the Lani Akia supercluster,

• 1:30:51Speaker 02

  Right, they're all redshifted, they're all moving away from us. But, but they also have what they call peculiar velocities. They have, in addition to the redshift, there is some additional velocity. And all of these additional velocities are moving towards the same point. That's the great attractor.

• 1:31:09Speaker 04

  Ah.

• 1:31:10Speaker 02

  So, everything is moving towards the great attractor, but they're, but they're moving away from each other even faster because of the expansion of the universe.

• 1:31:17Speaker 04

  We'll never get there.

• 1:31:18Cara Santa Maria?

  Yeah, that's interesting. So, the movement towards it, though, not, not, not counting, like, let's calculate out the expansion of the universe. The movement towards it, is it collapse, a collapsing movement? Or is it a circular, like a spinning?

• 1:31:34Speaker 02

  No, we're moving, just, we're moving in that direction, just like as a straight line.

• 1:31:38Cara Santa Maria?

  I know we are, but I'm saying when you look at everything around.

• 1:31:40Speaker 02

  Everything's moving towards that point.

• 1:31:43Speaker 04

  Yeah.

• 1:31:43Cara Santa Maria?

  So, it's like a collapsing movement?

• 1:31:44Speaker 02

  Yeah, yeah.

• 1:31:46Cara Santa Maria?

  Not like a?

• 1:31:46Speaker 02

  Not complicated.

• 1:31:47Speaker 04

  But the expansion is?

• 1:31:49Bob Novella?

  Think of all the, think of all the different ways we are moving, around the sun, the sun around the galaxy, the galaxy, you know, within the local group. And then the local, I mean, there's so many different ways we're moving.

• 1:32:01Cara Santa Maria?

  I'm talking about space, like, is all the stuff in space, not, like, not from our perspective. But like, if you just look at the great attractor as the arbitrary center of this model. The things that are moving towards it are collapsing in towards it, like, linearly, or they're rotating around it, like most things do in space.

• 1:32:22Speaker 02

  Well, we don't have, I don't think we have enough long time of, of measurement to know.

• 1:32:26Cara Santa Maria?

  But then it's actually being pulled apart faster than it's?

• 1:32:29Speaker 02

  But yeah, they're, they're all, they're all still redshifted, which means they're all moving away from us and from each other.

• 1:32:35Cara Santa Maria?

  Yeah.

• 1:32:36Speaker 02

  But there's this additional velocity, the peculiar velocity, that's plus 700 to minus 700 kilometers per second, depending on where it is in relation to the great attractor and us as the viewer. Right, so something that's on the opposite side of the great attractor is moving away from us at 700 kilometers slower than it should be. Because it's also being drawn in by the great attractor.

• 1:32:58Bob Novella?

  You know, that's, that's where I want to live. I want to live in the great attractor. Think about it, though.

• 1:33:04Speaker 04

  There's a lot going on there.

• 1:33:06Bob Novella?

  For long-term, for super-long-term survivability of whatever's there, you want as much mass as possible in your vicinity so that you could use that mass, you know, the mass energy to survive long into the cold, you know, after it's really just like black holes and white dwarves left in the universe, that you want as much mass as you can. If you don't have a lot of mass and you're just like, not going to last as long as any civilizations, that might be, that might be.

• 1:33:31Speaker 04

  It's like the highest mountain peak of, during a flood.

• 1:33:34Bob Novella?

  Imagine, imagine astronomers in the great attractor looking around and eventually figuring out, "Hey, check this shit out. Everyone's coming to us. This, how awesome is this? We are the center of the universe."

• 1:33:45Speaker 02

  Right.

• 1:33:45Speaker 04

  That's a lot of ma, that's a lot of matter.

• 1:33:48Bob Novella?

  They must feel very special.

• 1:33:49Cara Santa Maria?

  Because do you think it does like, it has like, black hole features?

• 1:33:53Speaker 02

  I think it's just, just a galaxy supercluster, just the biggest boy in town.

• 1:33:57Speaker 04

  Super-duper cluster.

• 1:33:57Cara Santa Maria?

  But that means there would be a black hole in the middle of it.

• 1:33:59Speaker 02

  Yeah, probably. Most galaxies have supermassive black holes in the middle.

• 1:34:02Bob Novella?

  Yeah, I'm sure there's plenty of big galaxies there with lots of supermassive black holes, but not necessarily an uber-massive ridiculous, you know, at the, at the, at the edge of physics black hole, but just lots of, you know, just a lot, a, a big dense supercluster. It's not necessarily.

• 1:34:18Speaker 02

  All right, let's move on with science or fiction.

• 1:34:23Speaker 01

  It's time for Science or Fiction?

• 1:34:32Speaker 02

  Each week I come up with three science news items or facts, two genuine, one fake, and I challenge my panel of skeptics to tell me which one is the fake. We have a theme this week. Theme is genetics. You guys ready?

• 1:34:45Speaker 04

  Okay.

• 1:34:46Speaker 02

  Okay. Item number one, the smallest animal genome by number of coding genes is the trichoplax adherens at just 3,500 genes, while the largest belongs the, belongs to the axolotl with about 90,000 genes. Item number two, Deloitte rodifers are small aquatic animals with a high rate of horizontal gene transfer, with genes from other kingdoms of life responsible for about 10% of their genome. And number three, the Japanese pufferfish Fugu rubripides

• 1:35:28Speaker 02

  has the animal genome with the highest coding density at 17% compared to 3% in humans. Jay, go first.

• 1:35:38Jay Novella?

  All right, the first one here about the smallest animal genome. This is a creature I've never heard of before, the Trichoplax adhaerines, whatever that means. While the largest belongs to the Axolotl with about 90,000 genes. Interesting, okay, so why would the Axolotl have the most genes out of all the animals? It's a small animal, and I just realized that I don't know if the genome size equates to the size of the creature. Wow, I can't believe I don't know that. Deloitte Rotifers are small aquatic animals with a high rate of horizontal gene transfer, with genes from other kingdoms of life responsible for about 10% of their genome. What do you mean with genes from other kingdoms?

• 1:36:23Speaker 02

  So they're animals, but they have genes from bacteria, plants, and fungi.

• 1:36:27Jay Novella?

  Whoa, that's, that's cool. That's really freaking cool if that's true. And this is, and it wasn't artificially made, correct?

• 1:36:37Speaker 02

  Nope, naturally occurring horizontal gene transfer.

• 1:36:40Jay Novella?

  Cool, okay, and then finally, the Japanese pufferfish Fugu ripides, ripide, hello, has the animal genome with the highest coding density at 17% compared to 3% in humans.

• 1:36:52Speaker 02

  The coding density means the percentage of the base pairs that are part of protein coding genes versus junk DNA, non-coding regions, etc.

• 1:37:01Jay Novella?

  This is a remarkably difficult science or fiction, Steve. I hope you're proud of yourself. This is the kind of crap we're gonna get from you now that you're retired? Like, is it gonna be like this extra hard stuff?

• 1:37:11Speaker 02

  Oh yeah, just expect it to, the difficulty to go way up.

• 1:37:14Jay Novella?

  Oh my God, I'm dying to hear what everybody else has to say. There's something about the axolotl having 90,000 genes. Now, this is of all animals, correct, Steve?

• 1:37:26Speaker 02

  Animals, yeah.

• 1:37:27Jay Novella?

  I don't know, something about that is rubbing me the wrong way, so I'm gonna say that one is the fiction.

• 1:37:32Speaker 02

  Okay, Evan.

• 1:37:33Speaker 04

  Coding genes, like you said, Steve, it's the good genetic material, the stuff that means stuff, not just the filler and the junk. And I could have sworn there were things that did have fewer coding genes, I thought, but maybe they don't fall into the category of animal. Maybe they are more bacteria, something else, right? Something non-animal, maybe that's where I'm getting confused with this. But I kinda think Jay's on to something here, and I think maybe that 90,000 for the axolotl is maybe too small. Something has more, whereas I'm just really guessing on the other two.

• 1:38:14Speaker 04

  I don't know about the horizontal gene transfer and the Deloitte Japanese pufferfish Fugu. I remember that from that Simpsons episode way back when. But I don't know, 17% coding density, but 3% in humans, wow. I suppose that could be, couldn't say why, though. I'll go with Jay. Jay, you're leading the way on this one.

• 1:38:37Speaker 02

  Okay, Kara.

• 1:38:38Cara Santa Maria?

  I'll take him backward. It's interesting, because I feel like with animals, there isn't a huge correlation between the type of animal, or like how we think of the, oh, that's really big and it moves, or that's small and it free floats. And plants, it was smart of you to focus just on animals, because plants' genomes are bananas, because you have like octoploidy genes, and you know. But generally speaking, animals are going to have just two sets.

• 1:39:10Cara Santa Maria?

  And so you can, you can kind of compare them. It's like comparing apples to apples. A Japanese puffer fish has the highest coding density compared to humans. So 17% compared to 3%. Wow, our coding density is really low.

• 1:39:26Bob Novella?

  Oh, yeah.

• 1:39:26Cara Santa Maria?

  17% feels high. So that just means that a lot of stuff was like conserved and really useful. I don't know if that's true or if it's another animal, like a shark or something that would be closer to that. Deloitte rotifers, so these little animals. In this case, the fact that it is small might be important, especially if they're like free floating in the water. So similar to bacterial gene transfer. Maybe it's picking up a lot of stuff from the things that are floating around it and mixing with it. But I don't know if 10% is normal. I don't know how much of our genome is horizontal gene transfer. Would have been interesting for you to include that. And then I hate that you do this one by the number of coding genes.

• 1:40:10Cara Santa Maria?

  That's like a whole other layer. Like, I don't know. I think humans have around 20,000, but I don't, I think that's coding. That could just be, no, it must be coding genes that we have around 20,000. And we always thought it was way more when, before we sequenced them. So my guess is that the smallest one has way fewer than that. And the largest one also has way fewer than that. I bet you these are over estimates on both sides because we tend to think big when it's actually smaller. At least in animals. So I'm going to go with the guys and say that one's fiction.

• 1:40:45Bob Novella?

  Okay, and Bob? Let's see, I'm gonna take these backwards as well. The coding density, yeah, it's 3% for people. I'm pretty confident about that. 17% though, for this Fugu dude? I mean, I don't know. Perhaps coding densities are higher. I don't know. It sounds, it sounds reasonable. Probably the most reasonable one here. Let's see, these are the horizontal gene transfer. So 10%. It might seem a little low to me because I mean, I would, there's a lot of conserved genes, the genes that are so good and so fundamental, everybody's got them. That's, in some sense, that seems maybe a little bit small.

• 1:41:21Speaker 02

  I don't think you understand what this item is saying. These are not conserved genes.

• 1:41:26Bob Novella?

  Why? They're from other kingdoms, right? So they were, so they what? They were just taken on?

• 1:41:31Speaker 02

  Yes.

• 1:41:32Bob Novella?

  Why couldn't these be conserved genes?

• 1:41:34Speaker 02

  They're not conserved genes.

• 1:41:34Bob Novella?

  They're passed on to each other. Do you say they're not conserved genes?

• 1:41:37Speaker 02

  Yeah, otherwise they wouldn't be due to horizontal gene transfer. That specifically refers to a gene being added to the genome of another, you know, species later on.

• 1:41:49Bob Novella?

  Okay.

• 1:41:50Speaker 02

  They don't share it because they don't, they didn't get it from a common ancestor. It was, that's vertical transfer, right? You're talking about vertical gene transfer. Horizontal gene transfer is not that. It's being transmitted.

• 1:42:02Bob Novella?

  Okay, so vertical, horizontal, what's the difference? All right, I get it. It's a huge difference. I get it. All right, so the, yeah, the first one here, let's see, I love Trichoplax. That's such an awesome name. Axolotl, so 3500, which is, that's kind of low. Not as low as the smallest synthetic organism, but that's not what we're talking about here. 90,000 genes doesn't sound like enough. Now, I know the axolotl is probably one of the biggest healers in the animal kingdom. I mean, you chop off anything and it grows back. It's Wolverine, I think, of animal regeneration. So it kind of makes sense that it would be, it would have a high number.

• 1:42:45Bob Novella?

  But I think that number is even higher than that. So I'm going to go with everybody and say that that's fiction as well.

• 1:42:52Speaker 02

  All right, so I guess I'll take these backwards, too. We'll start at number three, the Japanese pufferfish, Fugu rubribis. Has the animal genome with the highest coding density at 17% compared to 3% in humans. You guys all think this one is science and this one is science. This one is science. Yeah, so it is a very compact genome. It only has 400 million base pairs compared to

• 1:43:23Bob Novella?

  Two with three billion?

• 1:43:24Speaker 02

  Several billion for people, yeah.

• 1:43:26Cara Santa Maria?

  How many coding genes does it have?

• 1:43:28Speaker 02

  It's very efficient, about the same. It's got about the same.

• 1:43:33Bob Novella?

  Same what?

• 1:43:34Speaker 02

  As humans.

• 1:43:35Cara Santa Maria?

  Yeah, okay.

• 1:43:35Speaker 02

  Yeah, so yeah, and the question is why? Like, was there some selective pressure for a more efficient, if you will, genome? It has less junk in it. And, you know, that's probably why that's the case. Sometimes smaller animals have to have more compact genomes. But there actually isn't, since this came up. There isn't much of a relationship between the size or even the complexity of animals and their genome sizes. There's so many other factors. Okay, let's go back to number two. Deloitte rotifers are small aquatic animals with a high rate of horizontal gene transfer with genes from other kingdoms of life responsible for about 10% of their genome.

• 1:44:17Speaker 02

  You guys all think this one is science and this one is science. You guys got it, Ken? So yeah, it's very unusual. You know, this is a much higher rate than any other animal. Now, these things are, they're not just small, they're microscopic. They're not visible with the naked eye, right? So they're kind of like the little water bears.

• 1:44:41Bob Novella?

  Oh, tardigrades.

• 1:44:43Cara Santa Maria?

  I was gonna say, is it because they're bacteria-like that they have so much horizontal gene transfer?

• 1:44:47Speaker 02

  Maybe, maybe. Yeah, but they have incorporated genes from plants, fungi, and bacteria into their genome. So it's a much higher percentage than

• 1:44:57Bob Novella?

  What about the method of horizontal transfer? I mean, I obviously haven't read about that in quite a while, but what's the, how does that work? How does it take these in?

• 1:45:05Cara Santa Maria?

  I wonder if it's from the stuff it eats.

• 1:45:07Speaker 02

  Usually, it's usually from eating them.

• 1:45:09Cara Santa Maria?

  Yeah, that's what I would think. If they're just floating through the water and they're like rotifers, right? So if they're just like The like, kind of receiving all this microscopic stuff in their, in their little bodies all the time.

• 1:45:21Bob Novella?

  That's just bizarre. I mean, eating is one thing, but incorporating is, you know, wholesale is just like, how does that?

• 1:45:27Cara Santa Maria?

  Yeah, but if the bacteria are like, you kind of look like a bacteria. I'm gonna hang out with you. So I wonder if it's just, it's just mistaking it for bacteria.

• 1:45:36Bob Novella?

  Yeah, they do have like, what they have like circular DNA and they can just plasmids, they can just transfer. So that's, yeah, that's why they're, what makes them so nasty is they, they go, hey, look what I learned, look what I could defend against, now you can too.

• 1:45:48Speaker 02

  Now, like water bears, they can enter a state of dormancy known as anhydrobiosis, right? They get dried out.

• 1:45:56Bob Novella?

  Desiccate, yeah.

• 1:45:57Speaker 02

  And then they could survive in this dormant state for a long period of time. In fact, what do you think the longest duration is?

• 1:46:04Cara Santa Maria?

  Thousands of years?

• 1:46:04Speaker 02

  Twenty-four thousand years.

• 1:46:06Cara Santa Maria?

  Yeah, that's really cool.

• 1:46:08Speaker 04

  That's a nice net, man.

• 1:46:08Speaker 04

  That's got some advantages, yeah.

• 1:46:10Speaker 02

  Yeah. Not forever, but basically, I mean, that was an upper limit there.

• 1:46:15Cara Santa Maria?

  Well, but that's just the longest we've found.

• 1:46:17Speaker 02

  That's the longest we've found, right?

• 1:46:18Cara Santa Maria?

  Yeah, it could be, it could be.

• 1:46:19Speaker 02

  We found a twenty-four thousand year old Siberian permafrost. Uh, and they think that that probably that the gene transfer is part of why they can do this. Right? They use these genes to, in order to be able to do this. Okay, so this means that the smallest animal genome by number of coding genes is the trichoplax adherence at just three thousand five hundred genes, while the largest belongs to the axolotl with about ninety thousand genes. Is the fiction, and I'll tell you that those creatures are correct, just the number of genes is incorrect. I altered the number of genes. So what do you think? Now, Bob, you thought that the axolotl has more than ninety thousand genes. What do the rest of you guys think?

• 1:47:03Speaker 04

  I said the same thing.

• 1:47:03Cara Santa Maria?

  I think they both have less.

• 1:47:06Speaker 02

  What about you, Jay?

• 1:47:07Cara Santa Maria?

  I'm gonna always go with Kara. Ninety thousand sounds really high for an animal.

• 1:47:13Speaker 02

  You're all wrong.

• 1:47:14Bob Novella?

  Wow, why don't you feel smart?

• 1:47:16Cara Santa Maria?

  Wait, how can it not have more or less?

• 1:47:18Speaker 02

  Well, you said they, you said they both have less. The axolotl has less, the trichoplax has more. Oh, I went the opposite direction. I made, I made the difference more extreme. I see. Bit of extreme. But animals are actually pretty consistent in the number of genes that they have because we're all animals. You know, we just share a lot of genes just as animalia. So you get different numbers as estimates, but the trichoplax has about 11,500 genes. And the axolotl has about 30 to 35,000 genes. Whereas again, humans are 20,000, pretty much in the middle. So for all of animals, you're talking 11 to 30,000 genes is the range. Which is not that much when you consider about all of animals.

• 1:48:01Cara Santa Maria?

  Yeah, it might be part of what makes us animals.

• 1:48:03Speaker 02

  And the trichoplax is a, it's a placozoa. It's a basal group of multicellular animals. Possibly, possible relatives of the nodaria.

• 1:48:13Cara Santa Maria?

  Oh, cool.

• 1:48:14Speaker 02

  It looks like just a blob, though.

• 1:48:17Bob Novella?

  Guys, the, the minimalist synthetic cell that they created a bunch of years ago, how many genes you think that has?

• 1:48:24Speaker 02

  Hundred and eighty-five?

• 1:48:25Cara Santa Maria?

  A thousand.

• 1:48:27Bob Novella?

  It's got, it's got 531,000 base pairs and 473 genes.

• 1:48:34Cara Santa Maria?

  I win, Price is Right rules.

• 1:48:35Bob Novella?

  It's self-replicating, smallest genome of any self-replicating organism.

• 1:48:39Cara Santa Maria?

  That's scary.

• 1:48:40Speaker 02

  That's pretty cool.

• 1:48:41Cara Santa Maria?

  Hopefully they put a kill switch in there.

• 1:48:43Speaker 02

  It's, think about it, though.

• 1:48:45Cara Santa Maria?

  They probably do.

• 1:48:46Speaker 02

  Oops. The reason why I said that, Bob, is because the animal, the creature, not animal, with the fewest genes is the carcinella rudi i, which has 182 protein coding genes. But this is a, it's a bacterium, but it's a parasitic bacterium, so.

• 1:49:05Cara Santa Maria?

  Ah, so it's hosting.

• 1:49:06Speaker 02

  It doesn't need that many genes because it's, it's, it's a. Lives off its host. Living off the host, yeah. The host with the most.

• 1:49:13Bob Novella?

  We're still not at the very minimum, though, and that's, that's what, that's the goal, right? They want to find out what, what are the critical ones for life?

• 1:49:20Speaker 02

  Exactly. Among free living organisms. Non-parasitic. The fewest genes, this is natural, not artificial, is the mycoplasma genitalium.

• 1:49:30Speaker 02

  525 genes. So 525 is the smallest number for a free living organism, 182 for a parasite, and then 11,500 for an animal. And you're right, Kara, I didn't use plants because they're crazy. They just like

• 1:49:45Cara Santa Maria?

  They're in, yeah, it's just

• 1:49:46Speaker 04

  Yeah, right.

• 1:49:46Speaker 02

  The biggest genomes are in plants and like the, the, the single biggest genome is in a fern that has this, this crazy number of base pairs.

• 1:49:56Speaker 04

  Why?

• 1:49:57Speaker 02

  It's mostly non-coding.

• 1:49:59Speaker 04

  Well, some, some animals and plants have, it was like, what, like gene duplications, like bam?

• 1:50:04Cara Santa Maria?

  Well, that's why, yeah. Like I said, it's got, they're like octoploid-y. No, no, it's just that they have, they don't just have pairs of genes. They'll have like four or eight or 16. So it like

• 1:50:13Speaker 04

  Oh, I see, I see.

• 1:50:14Cara Santa Maria?

  quadruples and yeah, yeah, that's why.

• 1:50:16Speaker 02

  So yeah, so one, this one fern, the New Caledonian fork fern, has 160 billion base pairs, um, whereas humans have 3 billion.

• 1:50:26Speaker 04

  What the hell?

• 1:50:27Cara Santa Maria?

  But what, what's its ploidy, do we know?

• 1:50:30Speaker 02

  Um, I'd have to take a little

• 1:50:32Cara Santa Maria?

  New Caledonian fork fern.

• 1:50:33Speaker 02

  But the thing is, it's like, it's actually a disadvantage. It's slow growing. It's, it takes a, it takes a lot more energy and a lot more raw material to reproduce because it's got to copy these massive genomes. It needs more

• 1:50:47Cara Santa Maria?

  It's octoploid.

• 1:50:48Speaker 02

  Yeah.

• 1:50:49Cara Santa Maria?

  So maybe that's the highest it can be. I said 16, that's probably not real. Um, yeah, it's octoploid, whereas we're diploid.

• 1:50:55Speaker 02

  Mm-hmm, right.

• 1:50:55Cara Santa Maria?

  So right there, that's, yeah.

• 1:50:57Speaker 02

  Eight versus two.

• 1:50:59Cara Santa Maria?

  Divide it by four and its genome is suddenly not nearly as impressive. It's still big, but

• 1:51:04Speaker 04

  Take that fern.

• 1:51:06Speaker 02

  Well, it's still 40 to three, not just 160 to three, right? If you divide it by four, still big.

• 1:51:13Cara Santa Maria?

  Yeah, I mean, it's still, it's still really impressive, but not as impressive. It's 50 times more than the human genome is what it says.

• 1:51:19Speaker 02

  Yeah, it's huge.

• 1:51:20Cara Santa Maria?

  Yeah, that's a lot.

• 1:51:21Speaker 04

  For all the good it's doing it.

• 1:51:22Speaker 02

  All right. Well, good job, guys. Thank you.

• 1:51:25Cara Santa Maria?

  Thanks, Steve.

• 1:51:26Speaker 02

  Evan, give us a quote.

• 1:51:27Speaker 04

  There's a kind of spatial association between music and math, the intersection of science and art. Medicine is an art and research is an art. You have to be creative in the way you design experiments. And that was from an interview with Dexter Holland, Dr. Dexter Holland, by the way, Doctor of Molecular Biology, a PhD.

• 1:51:49Speaker 04

  You maybe know him as the lead singer of the punk rock band The Offspring.

• 1:51:55Speaker 04

  No idea that he was a doctor. He had a degree in molecular biology. It's really cool.

• 1:52:01Jay Novella?

  That's cool.

• 1:52:01Speaker 04

  Never knew that about him until very, very recently, like today.

• 1:52:09Speaker 02

  All right. Thanks, Evan.

• 1:52:10Speaker 04

  Thanks.

• 1:52:10Speaker 02

  Well, thank you all for joining me this week.

• 1:52:12Speaker 04

  Thank you.

• 1:52:13Cara Santa Maria?

  Thanks, Steve.

• 1:52:13Jay Novella?

  Steve, let me ask you one quick question.

• 1:52:15Speaker 02

  Sure.

• 1:52:16Jay Novella?

  Are you happily, you know, happy to here retired? Is everything good?

• 1:52:19Speaker 02

  I mean, my life is really not any different. I've been busy working the last few days. You know, it's only been three days where my schedule's been different from not working. So we'll see when things settle in in a few months.

• 1:52:31Speaker 04

  Spent most of it dealing with the phone.

• 1:52:33Speaker 02

  I know. But most of it was trying to get my phone upgraded.

• 1:52:36Jay Novella?

  I'll ask you in a couple of weeks.

• 1:52:38Cara Santa Maria?

  Yeah, that's gonna be your next big hurdle, right, Steve? I remember a private show once, you kind of admitting to the group that you you struggle with feeling lazy. And that you often feel like internalized pressure to fill your time. So now you're gonna have all this extra time. How how well do you think you're gonna be able to just sit and do nothing?

• 1:53:00Speaker 02

  Not well, but I'm filling it with stuff to do.

• 1:53:04Cara Santa Maria?

  Yeah.

• 1:53:05Speaker 02

  I already have way more stuff to do than I have time to do, you know? But that's what I was saying. I think it'll take a few months to really settle in. Like, I've done all my projects. I've done, you know, all the things, the busy work that I could give myself. We have my new projects for the SGU going. You know, Bob and I are gonna be writing another book. We're adding another podcast. We're doing more live streams. We're bringing back AQ6. We're gonna have more time to put into just the the primary show itself. And I'll have more downtime, but we'll see. It's gonna, it'll take a couple of months to settle in.

• 1:53:35Cara Santa Maria?

  I think you're gonna fill all that downtime.

• 1:53:37Speaker 02

  I will fill it.

• 1:53:38Cara Santa Maria?

  Yeah.

• 1:53:38Speaker 02

  I'm good at filling my time.

• 1:53:39Speaker 04

  Yeah.

• 1:53:40Speaker 02

  But some of that, more of that will be like video games than it is now.

• 1:53:44Cara Santa Maria?

  Right.

• 1:53:46Speaker 02

  I'll be able to do more of that kind of stuff. All right. Thanks again, guys.

• 1:53:51Speaker 04

  Sure, man.

• 1:53:52Jay Novella?

  Thank you.

• 1:53:52Speaker 02

  You got it, Steve. And until next week, this is your skeptic's guide to the universe.

• 1:54:00Speaker 02

  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 [email protected]. 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.

• 1:54:37Speaker 07

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