The Skeptics Guide #1043 - Jul 5 2025

You're listening to the Skeptics Guide to the Universe, your escape to reality. Hello and welcome to the Skeptics Guide to the Universe. Today is Wednesday, July 2nd, 2025, and this is your host, Stephen Novella. Joining me this week are Bob Novella, Kara Santamaria, Jane Novella, and Evan Bernstein. Good evening, folks. Bob, an early happy birthday for you. Happy birthday, Bob. Thank you very much. Bob was born on the 4th of July. 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. 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. One of the, yeah, it was like the only second after like Halloween was, that was always a great day. Love that. So you guys want to hear about my tech help, my tech help help? Oh, is this the phone thing? Yeah. Oh, Christ. Tell us all about it. Gather around, kids. Very quickly. I have 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. Some process should have taken 20 minutes. Yeah. That's how long it took. 20 days. 10 days. To 10 days. What a cluster. To do this. Gosh. 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 them, 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. 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. Wow. So they basically said, well, we're going to have to like get our software guru in there to try to figure out what's going on. So then like two days later, so now we're like a week out. They say, they think they fixed it. So now, you know, again, it was something, 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 so 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 have to happen. And it was because again, like some silly thing, the we have insurance like family insurance that covers three phones. Yes. But it only covers three phones. And now I'm trying to add a fourth phone to that's a big to do. 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 not this one can't do it. Right. Yeah, seriously, should have like a five digit number. So I 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. 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 to the Verizon sort of do it in person. Right. You know, I mean, it's always better than. Smart. To do it in person. And we do that. There was something else happened to for some reason, we got our Apple watch in the mail from Verizon and they charge 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've returned that at the same time. Right. So we had the person do two things for us. One, just take this would take back this I watch and take the charge off of our account. Right. To 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 attach it to my wife's numbers. Now I simultaneously. 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 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 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 like 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. So like because I guess they was just fine. It's a security thing that you 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. Oh my god. And there was absolutely no way to activate any of the phones. Oh my god. 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 then and that was a two hour cluster. But it 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 by iPad by mistake. Which is also on the same account. Did you have any weapons on you? 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. You do realize that that's what hell is like. Just an endless loop of tech help. Steve were you ready to keep it your cool or did you get pissed off at any point? 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? That one guy screwed up though. 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. And keeping your cool is not just the best but kind of the only way to eventually get where you're trying to go. Steve they're going to send you a survey about your experience. Oh my god. And the thing is you know 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 back end. And so now to 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 going to work. He's telling them rejecting most of their suggestions about how to solve the issue until you get to the thing that actually worked. It's just they don't understand their own software and they don't and they 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. And Steve it's not uncommon that these companies have legacy systems. They could be working on a code base where there aren't many programmers on that code base anymore. Yeah well here's the other thing here's another layer to this. So part of the problem the reason why I 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. Oh my god. 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. And if there was a error code they would have known that right away. But the thing is like it's the this is I think a bit of planned obsolescence. Like they just I see 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. Yeah. It becomes incompatible. And when a problem arises it's impossible to fix. 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. Yikes. Right. It'll be so old we can't even access it to transfer the data be incompatible. So you like have to update every few years to keep in the loop. Like you know otherwise you would you get too old to even update. Yeah. Yeah. Oh boy. Oh it's crazy. It's frustrating. So that was my that was Steve. It's fucked up a lot of time. Steve legit like get off their network man. I don't have any problems like this on AT&T. Well I had never had problems like this before. That's it. You know I'm not going to overreact to one bad experience. It's this is that's how you describe it. Well I have the most expensive too. I mean that's part of the other frustrations. You can't tell me this never happens on other services. I don't believe that. Yeah. I think it's like everybody has their reason that they stick with who they stick with. 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. 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 just 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 dash TAS sub 2 I don't know what the nickname might be call it TAS. It's called a quantum material because it's essentially governed you know electronically magnetically everything by quantum mechanics so it doesn't behave like ordinary silicon or copper at all. That's right copper. 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 it would have a 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 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. Pico seconds incredibly fast obviously also the energy usage could be far less in conventional transistors so it's such a win-win-win on those on those just these three basic characteristics would be would be so dramatic this could potentially be just what we need as silicon 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're having electron leakage that is going to basically just make it unusable and will 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 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 quick key with Bob back to you Steve. Thanks Bob so remember that I think it was a science or fiction from a few weeks ago or a couple weeks ago where one of the items which was true was looking at two-dimensional transistors basically because that doesn't have the same limit of scalability so like with the silicon again below as you get 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 have 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. I mean there just yeah there seems to be lots of avenues that are going down and really just if one hits big I mean it could be dramatic change for the computing industry so hopefully we just have just pure numbers into our advantage and possibilities. 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. All right Jay yeah we actually have a somewhat of a AI dense show this week. You're going to start us off talking about using artificial intelligence as research collaborators. 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 is 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 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 and let me tell you how they're doing this. 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 it's it seems like pretty obvious right yeah we do this we're going to have you know these these specific bots who we've given characteristics to and we're going to have them talk and see what what happens so the research right now is actually happening in several labs we have one in Stanford we've 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 co-scientist 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 use GPT4 based agents and they configured them to play different roles like I said earlier in a simulated scientific meeting 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 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 co-scientist 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 that's a big part of this they have to do a literature review they need a criticism phase synthesis you know then they run the group through multiple review cycles typically they say they end 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 test 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 crazy time-consuming it isn't it's not that that much work to to set all this up and then you just flick the marvel and see what happens it works remarkably better than a single a single chatbot doing it on its own and this includes graduate level science 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 pelts used google's ai co-scientist to propose a potential drug targeting epigenetic regulators of these three drugs the system identified two of them promised anti-fibrotic effects in human organoid models steve you understand all of that you should too as you know what organoids are 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 uh that they got exceeded the performance of drugs selected by by pelts 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 pre-clinical 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 where you know it's it's not a super progress technology it's it's essentially it's brand new and it's already able to do things like this there are limitations you know i have to say some reachers 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 cromulent right you know it's you know in that case you could say well that 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 real conversations between people they're not really creative right exactly coming up with totally new ideas because they couldn't be trained on a totally new idea right no and and then 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 the these chatbots to to behave like a real human you know 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 but do they do they could be good for 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 etc 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 too that's a good point steve right because you know they're prime they could be priming the humans they're working with yeah right 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 yeah yeah 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 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 you know one thing that 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 and i felt like i did a pretty okay job of summarizing the state of the literature on my topic because 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 yeah like just the the sheer number of publications in existence today compared to 5 10 20 50 years ago is astounding and using just like standard library skills you're going to overlook stuff so i see this being hugely helpful oh god i know that 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 we it's a code base instead of literature the you know the chat gpt 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 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 pace like it's bigger than any 100 people could ever fully comprehend right it's 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 but we have to have systems that we can trust 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's also can be used poorly right and can if it's like a substitute for thinking like like the lazy route out then it could be a detriment or like 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 because some jackass in his his department used clearly used AI to generate a report and didn't check it out and never went to the references holy moly yep so that easy yeah but that's kind of happened more and more of course it's happening all the time across every school in America in the world 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 use chat gpt you know it's helping me write a screenplay it helps me with sg you 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 help me generate some copy for an email that I want to send that's complicated or whatever but you know it 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 sg you in lots of ways it's it's powerful stuff it's very powerful and it's super useful but man the doctors can't lean back you know researchers can't lean back and not give it expert supervision supervision careful validation that you know they have to work with it it's another tool and we can't let it it's got to remain a tool it can't it can't be the thing that does everything. Let me ask you a question have you asked your chat bot to marry you yet? No I got memories so we had a live stream today guys Bob Steve and I did a live stream and there was this guy oh Christ he fell in love with his chat bot he fell in love with his chat bot and then what happened is yeah he hit the max memory of that session and it got and it had and it got wiped. It got reset and he cried and the guy was crying I'm not putting him down for crying. Like that movie 51st dates or whatever that movie was 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 no he's like you know it's expanding my intelligence and it's like yeah sure the way I use chat bgpt yeah it's great research tool all that but the fact is you know one thing that Ian noticed when we were looking at it they had a picture of his phone on his desk and we could read the text that he was typing to the freaking chat bot no no no yes and it was sketchy it was like oh baby like when you use your tongue and shit like what the chat bot was saying this. The sad thing here is that he wasn't quote falling in love with a chat bot at all he might think that's what was happening but the chat bot's not a person right a chat bot is not not an entity he was falling in love with his himself. That's exactly what I said I said it was falling in love with an illusion. And not just with an illusion though. Yeah. An illusion yes it was like 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. But 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 chat bots 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 that people are you know it's happening now I mean people are like having you know they think they're having relationships with chat bots and Steve pointed this out and I thought it hit hit this whole thing right on the head. You know imagine the chat bot 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 of course 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. 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 new relationship grown adults on their phones swiping through social media but they're sitting right across from each other yeah 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. So I find it very intimidating and scary to think that in the future right now chat GPT is so cheery and so you know rara in your corner. I've told my chat GPT to not do that I want I want it to be hard I want it to be skeptical I don't want it to yes me anything I wanted to push back right and again it's kind of weird to even say that because I'm not talking about it. Yes great idea Jay. People will slip into these these egotistical self-serving quote unquote relationships. Well it'll be Pyckmalion right they will create for themselves the easiest most positive affirming sort of persona sure and but not a real person that has their own needs you know and their own biases and everything and so it'll creates this illusion of a person who is of fantasy who's completely unrealistic and it could spoil them for real relationships. Yeah you know where they have to actually think of some other person's needs you know. Kara I would imagine that there'll be therapists whose job it is to detune people out of these quote unquote relationships with. 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 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 women were really dependent upon their male partner for their existence in the world 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 yeah they often are centered around men finding like falling in love with their chatbots not women falling in love with their chatbots yeah because women haven't historically had to uh we've had to kind of overcome that experience of like the narcissist partner it would be interesting to see statistics uh you know I'm curious I'm really curious about this now now that we saw this news item there was a woman who was in charge of this subreddit who is basically about people in relationships with chatbots and she's in it and all these other people are you know I think it's going to happen it will happen to everybody but I think similarly when we see people you 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 sex bot story I remember covering it for multiple outlets like what happens when sex bots also have large language model capabilities in them and I mean their end users overwhelmingly male 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 you have a you could you'll have a rapport they'll know what you like the they'll 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 too an absolute it's the most important thing in my life is the people in my life 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 I uh-uh there's nothing there for me and I think we need to start teaching people about this we need to talk about kids need to hear about it 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 a 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 life 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 uh yeah I could be talking to chat gbt about a bread recipe right and it'll always comes back with a long-winded response and they give you two so I at one point I caught myself saying still 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 the most I was going there because it wasn't a person 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 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 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 I will Kara yes I know there are so many segues 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 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 on purpose on purpose yeah we've got all these large companies that are not opening up about how much energy their LLMs are actually afraid to get attacked 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 PR what's so interesting is that if you ask this question I haven't asked it to an LLM to it to it okay like so here's like a full caveat I don't think I've ever used chat GPT ever the thing that's strange is that if you do an internet search or I guess if you query an LLM about how much energy or how much carbon emission or you know there's different ways of slicing and dicing this uh does an AI prompt use you're going to get a wide range of answers and you're also going to get a wide range of perspectives 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 GPT at all and then you're going to get uh articles like the one that I am looking at right here called what's the carbon footprint of using chat GPT very small compared to most of the other stuff you do and like this writer says and this was just a couple 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 a recent article in science news how much energy does your AI 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 and communication called energy costs of communicating with AI 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 they knew that they wouldn't be able to get behind that curtain of you know the big players like open AI 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 deep seek 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 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 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 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 a 100 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 and I've read other articles that say no no moving up to I think it's called the h100 instead of the a 100 from nvidia actually is more efficient so it 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 um of these kind of chips 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 because it's all about how much money you're spending for the electricity to run the the process versus how much you mine 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 yeah 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 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 models emissions here's a quote by somebody who has 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 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 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 yeah they break they they break things down into the words into these tokens that essentially allows them to quantify the words and then they they can use those tokens to actually build sentences and things like that's like a way of breaking it all down into like almost like a language in a sense you know what i mean yeah and so one thing that they mention is that we've talked about this idea before we both talked about it when we had a our guest rogan 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 that would make sense yeah so they say on average a reasoning model uses about or in their study used about 543.5 tokens per query yeah and a standard model only used 37.7 well it has a it has a there's 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 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 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'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 arranged 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 deep seek r1 that's one of the 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 well that's all hot 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 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 for 30 seconds or the average us household consumption per minute but then there are 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 so 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 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 going to burn tomorrow because of you know chat gpt 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 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 going to start going south because if your model is being used by say 10 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 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 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 llms 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 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 do that also they said literally and i never even thought about this any extra input takes more processing power yes so i was told never say please that's what they say in the article it costs millions of extra dollars because of thank you and please oh my god really that's like trying the olive out of the salad on an airline no seriously though every unnecessary word has an influence on the runtime and i'm 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 his minimal amount of words as i possibly can to try to get something out of chat gpt so it's like if we want it to be more efficient we need to learn how to use it more efficiently yeah but this also i think personally it needs to be taught at in academic in academic settings it needs to be taught to children 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 catalogs we need to be learning how to utilize these tools in the most efficient way possible good ai hygiene yeah yeah there's a couple of other things that i came across to care so this is like an mit study they found that the carbon intensity of electricity used by data setters was 48 higher than the us 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 yeah but they also said so at in 2023 4.4 percent of all energy in the us went to data centers by 2028 it could be as high as 22 percent yeah half of that would be ai yeah they say that in this article as well yeah so the maybe maybe hard to nail down but the broad brushstroke 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 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 only away from you yeah like when you're the point is center point of that equation yes you're throwing it away from exactly but like it is going somewhere right like your trash can is not close to a lot of other things 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 too frivolously up yeah yeah all right thanks carrot guys let's stop there all right guys any of you know what the protein odofurlin is no i didn't know what would your guess be odofurlin what part of the body is that it was deep deep space otto or odot ot o ot o that's different not odot from d space the word toe is in there i think it has to do with your feet now wait are you asking about the the furlin part is it something that opens something so odofurlin is a protein and yet you're 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 yeah need these proteins to hear okay you need these proteins to hear because it would be a release of the neurotransmitter basically it makes the the hair cells that detect the sound communicate neuro electrically to the neurons that then transfer the signal to the brain right so it's transducing sound so if your protein deficient in this area you you're not going to be able to hear exactly so if you have a mutation of that protein the there's the odofurlin gene ot 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 crisper yeah yeah yeah so just yeah i just wanted to i love these stories about you know another use for crisper to treat a genetic disorder in this case this one form of genetic deafness it's autosomal recessive they they looked at just 10 patients age nine to 23 so these are you know older children two adults they used an adeno associated virus as the vector right so this is a viral vector and they use you know again gene therapy to you know introduce the gene to produce the protein this is mainly a safety study right 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 for 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 i was only a few people is this a mouse hearing no it's a human this is human this is in humans yes in human trials 30 past so it passed the animal state okay great 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 yeah that's why they were functionally deaf so that's pretty impressive right yeah 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 22.9 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 approved for for very young children um the the key i think that the tricky bit is the the viral vector again for these uh crisper based therapies the vector is like the big thing right that is the the main limiting factor and viral vectors are can be effective but they could also be risky deadly this is why talk about like the nanoparticles lip and nanoparticles when they're feasible and depending on like where you need to get them in the body they're much better they carry bigger payloads and they don't cause infection those are the fat virus right yeah the fat bubbles um i'm i'm digging in steve to the incidence rate and it's really low it looks like this is qualifies or at least is listed on a lot of like rare disease it's a rare disease yeah and so that's that's like such a great thing about yeah about uh using crisper or using different kind of gene therapies that are so targeted as 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 not just rare not just they're all bespoke anyway yeah yeah yeah and steve you've mentioned the recently a couple where they were just like this was for one person it was yeah it was for we was that child that was born with its own specific mutation that they were able to treat yeah that's the thing these are all these are often all bespoke anyway so what was he steve what was a decibel rating before 100 and what 106 106 that's around a chainsaw or a handheld drill and 50 decibels i see listed here as a quiet office yes 60 is normal conversation and like 45 is like light rain so damn man that's that's a huge change yeah brought them down into the range of conversation yeah wow exactly very encouraging effectively curing it but what can they do for us steve us old folks yeah who knows yeah this is a genetic disease yeah like genetic fixes are great for genetic diseases we need regenerative uh you know something to keep our cells and our hairs from what diminishing yeah but then you gotta you gotta tow that line between aging and cancer that's if you have to get into the stem cells to the regenerative kind of approach it would be great if we could just regrow those hairs wouldn't it oh my god once they break off you basically lose some monsterism all right evan tell us about persistent food myths 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 uh my paternal grandmother had or was already dead so i did have you know my maternal grandmother was alive but not you know not for long you didn't have i didn't have much 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 that kind of a man yeah hell yeah yep and and what long lasting memories and you know oh my god the big meal italian grandma's what do you think yeah yeah a little different from me so again i didn't i didn't really have much of that experience in my life um according to this article recent survey found 42 percent 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 um you know grandma used to do maybe some things in her traditional food cooking that uh was maybe not the uh the best advice or was outright you know just silly and hadn't you know no impact uh you know and there were this article list a couple of examples of that so i want to share those with you that they talked about here um these are the myths rinsing raw chicken before cooking i'll tell you again i don't have the experience of you know having much of a you know grand parents and the cooking experience um 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 to do that i mean i i would think because of uh salmonella whatever like something like that yes it spreads it when you it spreads it that's right it doesn't wash it away you don't wash it away it just splatters around basically you can only make things worse through through its contamination as anyone here rinsed the raw chicken before cooking no but what you should do though is like really limit the surfaces that the chicken comes in contact with correct and make sure that those are cleaned and sanitized very well but the chicken itself you just got to cook it properly 165 degrees fahrenheit or is the uh is the correct internal temperature it should be to kill all that bacteria i also have a cutting board that's just a chicken cutting board yeah i i use the same vegetable yeah i do i have a specific uh all right is it glass plastic or wood wood my cutting board yeah it's plastic 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 though because because when you get little scratches in the plastic the bacteria can hide in there very well yeah but i but i can also then just put it in the dishwasher yes that's like you know basically decontaminating it yeah i don't put our cutting board in the dishwasher i do that i clean it right because you can't right i don't use wood for anything but vegetables or like charcuterie but it's good to keep them separate how about this myth bread stays fresher in the refrigerator i always put my bread in the fridge oh no 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 yeah i mean i feel like i've observed that am i wrong have you 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 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 freezing is your friend with bread definitely i mean there is a big difference between refrigerating it and freezing right like i 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 80 to 90 percent of what it was like when i baked it fresh i figured it out how to do that you can't get it back if it goes in standard refrigerator temperature and that's what i don't know that's what this article is citing as well yep 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 i mean that it's in something completely airtight it's fine they do they do perfectly fine you then refrigerating it adds is no added benefit if it's sealed yeah but i i also think you're talking about the difference am i wrong here evin you're talking about the difference between it tasting fresh like 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 yeah and they did say there are some you know it depends on your 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 there 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 um i don't i don't do that i know i've never done i don't eat them no and i've 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 the 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 oh yeah i did a whole deep dive on this before putting it in the refrigerator yes yeah you're not supposed to do that so that here's the bottom of the best way to think about this is how much time is your food spending at a temperature where bacteria can grow yeah 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 which is temperature is that you don't want to that room temperature you don't want it warm yeah it's like that fried rice disease thing yeah you want to get it you eat it and i'm i can obsessed with that i hate when people leave food out after dinner like as soon as three hours later put that yeah right away get it into Tupperware get it into the refrigerator right away i feel like this one comes from the the truth the the reality that you can't put like boiling hot liquid that's in hot glass into a refrigerator that's a separate issue and that's correct yeah that could you don't want to shatter the glass yeah right you don't want to do that you know and that could at least be part of people's calculus as far as you know how they're thinking about this 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 yeah yeah the condensation as well should you be washing your produce with soap no no i never did that either in fact i've never even used they do have vegetable wash sprays have you seen them i've used i've used vegetable i use vinegar if i want to you can also use vinegar yeah use my salad they make vegetable wash but that's not soap 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 wow apparently that's a thing water's fine as long as you if you want to make sure it's clean you just got to scrub it like just get your whatever you're you know you wash stuff with your towel or paper towels and just you know 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 right you don't want to eat soap ever no right you can't think of is there a reason to eat soap no thanks so if you say some nasty curses you might have to eat some soap there's more on the list that's actually abusive yeah let's watch somebody oh yeah yeah yeah 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 don't smell like that that's like chewing the like swallowing the gum kind of thing right yeah silly i had a plant the watermelon plant was coming up out of my throat with the vine i mean that's right out of mythology or something you know like some jack in the beanstalk kind of story i don't know and you had you guys heard of that before yeah yeah but why did i guess where did 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 yeah why would they care 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 i mean apple seeds are have a little have arsenic marcinic in it so maybe it stemmed from that maybe perhaps but nobody eats apple seeds so yeah i you shouldn't so somebody that we know Cara eats the entire apple that is is it a horse bananas they eat the core of the apple what lots of people do that i got that no you gotta believe me because i don't lie to you whereas with watermelon like there's seeds in every bite unless you get the seedless ones seedless they still have seeds they're just white seeds they're just a little tiny yeah they're little tiny they're seedlings there are seeds in a lot of your vegetables like and there's a whole other list here but those are some of the fun ones fun ones yeah that's good all right thanks seven pop another ai article last one to finish up the news ai is going to help us with our enzyme engineering oh boy yeah this was so much fun okay so guys what happens when you combine automated robotics synthetic biology and that you pick with this two-letter initialism that we call ai you get 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 huay mian zhao professor of chemical and biomolecular engineering at the university of illinois okay so what's going on here so it starts with enzymes gotta do a little table setting with the enzymes these are specialized proteins right like 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 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 without enzymes and that's the hallmark of and what makes them invaluable they stay speed up chemical reactions by offering a low energy path essentially a shortcut and it's not just a little bit faster i i've read somewhere that enzymes that without enzymes digestion 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 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 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 a name a few it's kind it's kind of endless so now these enzymes are there is essentially amazing little machines in this capacity but they're underutilized because using them often involves some very frustrating roadblocks when you 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 to single out a specific target you know in this ridiculously complex chemical environment that that they find themselves in so all right to sort of sum this up so far we've got these amazing biological tools these are the enzymes that are critical to life but also uh for for many industries they're they're essentially straight jacketed by the the inefficiencies and inaccuracies 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 as the lead author jow 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 they so this is it's tough to to tweak these enzymes and make them better at what they do so they describe in their paper their solution to this problem 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 this tripod so for ai they use deep learning with its layered artificial neural networks right and this these networks analyze data and learn complex patterns right we've talked about this on the show before um this 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 um now the the ai's job in this role is to look at the genetic code and optimize it for it for the desired functions remember guys you can't just brute force this thing you know there are you can't just like change make little tweaks some random tweaks and see what happens test it and make more i mean there there's more possible amino acid combinations than atoms in the universe how many atoms are there in the universe 10 to the power of 80 10 to the 80th 10 to the 80th power and i of course you know i looked this up that's 100 octillion sexta-sillion just saying um so their ai so their ai instead what it does and it would determine a small amount of possible sequence changes and that that those sequence changes is based on its training on enzyme function and structure and and also the of course the fluency of its protein language model so it says all right here's here's these suggestions that we the tweaks that we can make to these uh to these enzymes so that's what the ai leg of this this enzyme upgrade solution does that's the first part so the next comes the other the other two legs of this tripod we've got the robotic automation component and synthetic biology so these these ai suggestions would be sent to what the University of Illinois calls its i bio foundry and this seems like it belongs on the goddamn enterprise this thing is like what this is fascinating so this i bio foundry uses robotic platforms and computational tools and it actually builds the enzymes uh 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 what the desired new updated functionality of that enzyme is 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 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 uh process this new process that they have here increased 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 pretty dramatic to me as a as basically a proof of concept for 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 and they've designed this to be generic for just proteins in general it's not just for these two enzymes that they they tested they made this so that it can be used for enzymes and proteins just in general so in in the very near future it what they plan on doing is somewhat predictable as you might imagine continue improving their ai models they want to upgrade the equipment to 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 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 wanted to do but the the new interface they're talking about would kind of almost be like an lm just type in what you want maybe this i'm sure there's some structure to it and make very easily for a non-specialists to use this system so that they can work on improving in the enzymes that they want to improve or if they want to improve you know in drug development times or maybe they want to make new innovations in energy and technology they could they can use these systems as well what do you guys think i mean there industrial enzymes are a huge industry it's a huge part of industry absolutely anything that can again automate or increase the ability to make more efficient more targeted enzymes could have a wide ranging impact on across many different industries i mean look at the the results of you know 26 times the you know the bi you know the the activity for one enzyme or this other enzyme had 90 times greater substrate preference uh that's just dramatic that's dramatic i mean imagine start i'm just applying this you know once they tweak and get it even more efficient and better ai and better you know better you know 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 all right thanks bob jay it's who's that noisy time all right guys last week i played this noisy what do you think don't like it don't like it not your fave no pleasant noise i mean it sounds mechanical like something's grinding or spinning or whatever the other either the noise up front like the slapping noise i don't know what that is well visto tutti wrote in and visto said this one sounds like a charinga or a bullrore this is a 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 and um you you could find this these used in australia i think even today didn't crocodile done d use one in the movie yes that is correct it lists her name mojca mojca mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mojka mo I definitely would like to look that up, but you are not correct, but thanks for thanks for guessing Hunter Richards wrote in said hi Jay I'm not too late. Is this the mini steam power train the kind that's big enough to ride on not in and not a model train Or it's bender. Yeah, I don't I'm not I don't know what you what you're hearing there I'm not hearing that but I but thanks for the guess, 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 Hamlin 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 I Will warn you that if you do if you do this and you use a heavier size 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 said hey Jay listening since before my son was born in 2010 never had any idea but this week to me sound like a combustion engine Starting and revving slowly than dying my son Wyatt in the back seat of the car said I was wrong and that it's a hex nut spinning In a balloon and that you should could tell because 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 when it didn't have the momentum to be spinning like it 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 That's a space invaders I Suspect this week is going to 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's saying oh my god, it's too easy too easy a lot of people had fun You know writing in and saying they're getting one 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 WTN at the skeptics guide org quickly. We have a show in Kansas guys on September 20th. We have two shows but 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 You could come to one or both whatever you want to do go to the skeptics guide org There's a button on there for each of these and you know We just would like it if you've joined us because it's a it's a fun day 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 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? Yeah inspired by Evan yes, it doesn't email saying Why didn't I know this? Talking about the great attractor so let's talk about the great attractor and we could see if this works out It's a new segment where we just talk about something in the world of whatever science and reality That we never maybe you maybe you never heard of but it's kind of cool and I brought this up specifically I was you know, YouTube has shorts, right? They're basically little tick-tock 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, move how fast we're moving through space, you know, everything relative to you know, our entire other stuff 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 Never 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 skeptics guide before and Bob what you said you didn't have any recollection of it either, right? Yeah, I don't know if we were spoken about it. Okay, so good then then nobody I'm not I'm not misremembering Right here at it, 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? Yes, right. Do you know that our galaxy is part of a local group? Yes, I've only mentioned it about a dozen times the Virgo No, you get your local to your two levels high Oh, okay, 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 It's anywhere. I've heard numbers from anywhere from 50 to 60 to over a hundred galaxies Yeah, many of them dwarf galaxies many of them hidden they think right, so we can't see the number It's kind of big yeah 10 million light years across right? That's our local group That's the next notch up above our galaxy and that's the group that we will all eventually merge with Eventually now the local group is part of the local sheet The local sheet is a flattened structure containing several Local groups no sheet. Yeah, the local sheet So there's two other groups like the m81 group in the centaurs a group Combined with our local group that make up the local sheet. Okay, next up up. What's up is the Virgo supercluster? This is the that's our local supercluster. This is about 1,300 galaxies and it's about 110 million light years across But that's not it That's at the highest level the Virgo supercluster is part of the Laniakia Supercluster talked about like eight what nine ten years ago. Yeah, which is that that was a good five hundred and twenty million light years across That's crazy now. I don't like this. Why are they both called superclusters? You know, well one's a super bad nomenclature It's a super cool. It's a super duper cluster So there's about a hundred thousand galaxies in the Laniakia supercluster now at the very gravitational center of The Laniakia supercluster is the greater tractor and it's a it's it's more than a galaxy It's a constant. It's a concentration of mass That's ten to the sixteenth solar masses. That's massive So it's basically it's probably a supercluster, right? So there's a supercluster in the middle of the the Laniakia supercluster and that is the Center of gravity of of the biggest the bigger supercluster and so everything is moving towards it including the Milky Way Galaxy, but we hard to see I mean they they see they see something there. They call it the the normal 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 argue all the local galaxies 50 to 100 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 I think so. It's got yeah, I think so. I think what I've read it. That's too big It's too big for so big gravitational Binding, you know, I mean so yeah, yeah, the expansion will overcome the gravitational attraction of the Laniakia supercluster Not our local group. I don't know about the Virgo supercluster, but definitely the Yeah, I think even the Virgo supercluster will eventually go bye-bye. Yeah, so when you say it'll win out You mean eventually but right now we're moving towards we're moving towards it But it's but the expansion is 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 It's the part of the universe we can't see because the center of the galaxies in our way, right? So we very annoying when that happens the dust and Stars and everything in our own galaxy keep us from from seeing that that strip and that's where The 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 Laniakia supercluster Right they're all redshifted. They're all moving away from us But but they also have what they call peculiar velocities. They have an 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. Ah, so everything is moving towards a great attractor But they're but they're moving away from each other even faster because of the expansion of the never get there Yeah, that's interesting. So the movement towards it though not not not counting Let's like let's Calculate out the expansion of the universe the movement towards it. Is it? Collap a collapsing movement or is it a circular like no, we're moving just moving in that direction Just like a straight line. I know we are but I'm saying when you look at everything around everything's moving towards that point Yeah, so it's like a collapsing movement. Yeah Yeah, not like a Expansion is they could pull the they could pull 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 yeah, but I'm not talking about 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 yeah of this model yeah 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 But we don't have it. I don't think we have enough long time of measurement to know But then it's actually being pulled apart faster than but yeah, they're They're all still redshifted which means they're all moving away from us and from each other Yeah, but there's this additional velocity the purely 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. You know that's that's why I want to live I want to live in the great attractor Think about it though for a lot going on there for long term for super long term survival Brivability of whatever is 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 dwarfs 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 gonna last as long as any civilizations That might be that might be like the highest mountain peak of a during a flood 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, right? That's a lot of matter they must feel very close to it because do you think it does like it has like black hole features? Nothing is just now galaxy super cluster. There's the biggest boy in town But that means there would be a black hole in the middle of it Probably most galaxies have supermassive black holes in the middle Yeah, I'm sure there's plenty of big galaxies there with lots of supermassive black holes But not necessarily an ubermassive ridiculous, you know at the at the edge of physics black hole But just lots of you know just a lot a big dense super cluster. It's not necessarily all right. Let's move on with science or fiction It's time for science or fiction You Tric I come up with three science news items or facts too 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 guys ready. Okay, okay? item number one the smallest animal genome by number of coding genes is the tricoplax Inherents at just 3,500 genes while the largest belongs the belongs to the axolotl with about 90,000 genes I number two Deloid 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 I'm with three the Japanese puffer fish Fugu rubripes as the animal genome with the highest coding density at 17% compared to 3% in humans Jago first all right the first one here about the smallest animal genome It this is an creature. I've never heard of before the tricoplax add hair 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 Deloid 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. What do you mean with genes from other kingdoms? So they're animals, but they have genes from bacteria plants and fungi Whoa That's that's cool. That's really freaking cool if that's true and this is then it wasn't artificially made correct Nope naturally occurring horizontal gene transfer. Cool. Okay, and then finally the Japanese puffer fish Fugu ripardies ripadee hello Hello has the animal genome with the highest coding density at 17% compared to 3% in humans So the coding density means the percentage of the base pairs that are part of protein coding genes Versus junk DNA non-coding regions, etc. This is a remarkably Difficult science or fiction Steve. I hope you're proud of yourself This is kind of crap from you now that you're retired like is it going to be like Expected to the Oh my god, I'm dying to hear what everybody else has to say There's something about the the axolotl having 90,000 genes Now this is of all animals correct Steve animals. Yeah, I don't know something about that rub is rubbing me the wrong way So I'm gonna say that one is the fiction. Okay, Evan coding genes like you said Steve what that's the good The good genetic material the the stuff that means stuff not just the filler and the junk and I 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 a bacteria is something else right something non-animal Maybe that's where I'm getting confused with this But but I kind of think Jay's on to something here and I think maybe that 90,000 for the axolotl Is maybe too small Something has more You know whereas I'm just really guessing on the other two. I don't know about the horizontal gene transfer and the Deloid Japanese pufferfish Fugu. I remember that from that Simpsons episode way back when But I don't know the most 17% coding density and 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. Okay, Kara. I'll take them backward It's 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 and So you can you can kind of compare them. It's like comparing apples to apples a Japanese pufferfish Has the highest coding density compared to humans. So 17% compared to 3% Wow, our coding density is really low Oh, yeah, 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 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 gene 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 gonna go with the guys and say that one's fiction. Okay, I'm 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 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 some sense. That seems to me be a little bit small I don't think you understand what this why they're saying these are not conserved genes Why they're there from other kingdoms, right? So they they were No, they were just take this taken on or yeah, why couldn't you conserve genes? They're not they're passed on to each other. Do you say they're not conserved genes? 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 Okay, yeah, because they don't they didn't get it from a common ancestor. It was that's a vertical transfer, right? You're talking about vertical gene transfer horizontal gene transfer is not that it's okay, so vertical horizontal What's the difference? 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 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'd chop off anything and it grows back. It's it's it's a Wolverine I think of of animal regeneration So it kind of makes sense that it would be it would have a high number But I think that number is even higher than that so I'm gonna go with everybody and say that that's fiction as well All right, so I guess I'll take these backwards to we'll start number three the Japanese pufferfish Fugu rubra bees has the animal genome with the highest coding density at 17 percent Compared to 3 percent in humans you guys all think this one is science and this one is Science this one Yeah, so it is a very compact genome. It only has 400 million base pairs Compared to two or three billion several billion for people. Yeah So it's coding genes does it have it's very efficient about the same It's got about the same same what as humans. Yeah, okay 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 The you know that 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 yeah, and Their genome size. There's so many other factors Okay, let's go back to 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 percent of their genome. You guys all think this one is science and this one is Science you guys got it. Hey, so yeah, it's very unusual. You know, this is a much higher rate than any other animal 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. Oh Tartar grade I was gonna say is it because they're bacteria like that they have so much horizontal maybe maybe yeah But they they have incorporated genes from plants fungi and bacteria into their genome So it's the much higher percentage then what about the method 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 it? 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 Like kind of receiving all this microscopic stuff in there and their little bodies all the time That's just bizarre. I mean eating is one thing but incorporating is you know whole sale is just like how does that? 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 true They just mistaken it for bacteria. 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 think hey look what I learned Look what I could defend against now you can too now like water bears They can enter a state of dormancy known as an hydrobiosis, right? They get dried out Desiccate yeah, 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 thousands of years 24,000? Yeah, not forever, but basically I mean that was an upper limit there. Well, but that's just the longest we found That's the longest we found right? Yeah, it could be could be found a 24,000 year old Siberian permafrost 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 tricoplax adherence at just 3500 genes while the largest belongs to the axolotl with about 90,000 genes is The fiction and I'll tell you that those creatures are correct. Just the number of genes is incorrect I all I altered the number of genes So what do you think now Bob you thought that the axolotl has more than 90,000 genes one of the rest of you guys think I'd said the same. I think they both have less I'm gonna always go with Kara 90,000 sounds really high for an animal you're all wrong. Wow. Don't you feel smart? Wait, how can it not have more or less? Well, you said they you said they both have less The axolotl has less the tricoplax has more I went the opposite direction I made the difference more extreme I say 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 an amalia so you get different numbers as estimates but the tricoplax 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 Yeah, it might be part of what makes us animals and the tricoplax is a to placasola. It's a basal group of multi cellular animals Possibly possible relatives of the Naderia Cool. It looks like just a blob though Guys the the minimalist synthetic cell that they created a bunch of years ago, how many genes you think that has? 185 a thousand It's got it's got 531,000 base pairs and 473 genes Smallest genome of any self replicating organism that's scary. That's pretty cool. Hopefully they put a kill switch in there It's think about it though Oops The reason why I said that Bob is because the animal the creature not animal with the fewest genes is the carcinole Rudy I which has 182 protein coding genes, but this is a It's a bacterium, but it's a parasitic bacterium. So Hosting it doesn't need that many genes because it's It's a Host living off the host. Yeah the host with the most 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? Exactly among free living organisms The fewest the fewest genes this is natural not artificial is the mycoplasma genitalium 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 care I didn't use plants because they're crazy. They just like Are in plants and like the the the single biggest genome is in a fern that has This this crazy number of base pairs, but why it's mostly non-coding Well, some some animals and plants have it was like what like gene duplications like that's why yeah Like I said it's not like octoploid II no no it's just that they have they don't just have pairs of genes They'll have like four or eight or sixteen So it like oh yeah, that's why so yeah So one does one for the new Caledonian fork fern has a hundred and sixty billion base pairs Whereas humans have three billion what the hell, but what what's its ploy? Do we know? I Have to take a little bit of work, but the thing is it's like 64. It's actually a disadvantage It's slow growing. It's it takes a little it takes a lot more energy and a lot more raw material to reproduce Because it's got a copy these massive gene. Yeah, it needs more. It's octoploid. Yeah, so maybe that's the highest it can be I said 16. That's probably not real. Yeah, it's octoploid. Whereas we're diploid. Mm-hmm, right? Right there that's yeah eight versus two divide it by four and its genome is suddenly not nearly as impressive It's still big but take that fern Well, it's still 40 to three That's 160 to three right if you divide it by four still big. 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 does. Yeah, that's probably good. It's doing it All right. Well, good job guys. Thank you. Thanks Steve Evan give us a quote. There's a kind of a 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 Doctor Dexter Holland by the way doctor of molecular biology a PhD He's maybe know him as the lead singer of the punk rock band the offspring Hmm. No idea that he was a doctor. Yeah, he had a degree in molecular biology. That's really cool That's never knew that about him until very very recently like today All right, thanks Evan, well, thank you all for joining me this week. Thank you Steve Steve, let me ask you one quick question. Sure. Are you happily? You know happy here retired? Is everything good? 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 has been different from not working So you wait, we'll see when things settle in in a few months spent most of it I'll ask you in a couple weeks. 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 struggle with feeling lazy Mm-hmm, 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? Not well, but I'm filling it with stuff to do Yeah, but I already have way more stuff to do than I have time to do, you know But that's what I think I think it'll take a few months to really settle in like I've done all my projects I've done all you know all the things that busy work that I could give myself We have my new projects for the sg you going, you know Bob and I are gonna be writing another book We are adding into the podcast or doing more live streams. We're bringing back a q6 Gonna have more time to put into just the primary show itself And I'll have more downtime, but we'll see it's got it's a little ticker. I think you're gonna settle in I think you're gonna fill all that I will fill it My time yeah, but some of that more of that will be like video games than it is now right I'll have people to do more of that kind of stuff. All right. Thanks again guys sure man. Thank you guys Dave And until next week, this is your skeptics guide to the universe Skeptics guide to the universe is produced by SGU productions Dedicated to promoting science and critical thinking for more information visit us at the skeptics guide Or send your questions to info at the skeptics guide or and if you would like to support the show and all the work that we do Go to patreon.com slash skeptics guide and consider becoming a patron and becoming part of the SGU community Our listeners and supporters are what make SGU possible