[00:01:44] [00:01:54] Seb Bunney: Oh man, definitely. Ready. And like, kind of to that point, I think it’s really fascinating when you look at something through a different lens. The lens being, Hey, I’m about to talk about this thing. I need to understand it a little more than just this very, very superficial level.

[00:02:06] Seb Bunney: And so, yeah, the world is moving so quickly when you’re trying to keep up with technology.

[00:02:10] Preston Pysh: I wanna emphasize, if you’re listening to the show and you come across something on X or anywhere on the internet, that is just fascinating from a tech standpoint. We’ve had a couple people share stuff with us on Twitter.

[00:02:22] Preston Pysh: One of the things I believe we’re gonna be using today on the show, so share that with us. Point it out, shine a flashlight on it for us so we can, bring it onto the show and we’ll mention you on the show if, if you’re one of the people that bring it to us. So let’s start off, Seb, you said that you had something with Gary Breca that you wanted to cover to start.

[00:02:40] Seb Bunney: Absolutely. So this isn’t necessarily like the newest technology that we’re seeing advancing in this week, last week. This is something that maybe over the last few years I’ve been digging into. And it’s this idea of kinda like personalized health. So for people that don’t know who Gary Brecker is, he kind of founded something that he calls kind of the ultimate human.

[00:02:58] Seb Bunney: I think it’s a company. They also have a podcast. And if I give a little bit of backstory, he used to be a life insurance guy. He used to look at these individuals that are applying for life insurance, life insurance company had to figure out, okay, based on this person’s health, how much are we gonna charge for these life insurance premiums?

[00:03:16] Seb Bunney: And so he would be looking at basically someone from birth through to present day to try and determine from like a data perspective, how healthy is this person? How much life do they have left? And what he noticed increasingly is. Many times these individuals would be going to separate doctors.

[00:03:31] Seb Bunney: They’d have these health issues, but no single person is looking at them holistically. Mm. And there would be conflicted issues. So for instance, one lady in particular, I think he talks about in one of his podcasts, was he was looking at this case and this lady was seeing two doctors. Both of them were giving her a different prescription, and those prescriptions actually interact with one another and could be deadly.

[00:03:53] Seb Bunney: And he, given that he was working for the life insurance company, wasn’t legally allowed to step in and voice this to her. And so he just had to see this play out and he was just like, I cannot continue doing this. I want to be able to help people. I want to be able to support people along in their journey.

[00:04:08] Seb Bunney: And I recognize that health is something that we need to look at holistically. We can’t look at it interventionally, which is what a lot of our healthcare system does. So in essence, the reason why I find it really fascinating is that. He looks at what are called like our genetics and our methylation pathways.

[00:04:25] Seb Bunney: And so for people that aren’t familiar with kind of what these are, methylation, the way I interpret it, and I could be completely wrong here, the way I interpret it is that our body has these things called methylation pathways, and it’s how we take nutrients and then use that nutrients to be able to form various or have our bodily systems run.

[00:04:44] Seb Bunney: Be able to extract and detoxify inflammation, control hormone processing, DNA, repair, all of these various processes in the body. And the way I kind of think about it is like, imagine if you’re trying to feed a car crude oil, it’s not going to be able to take that crude oil and use the nutrients directly.

[00:05:01] Seb Bunney: You need to have it kind of converted into gasoline. Well, it’s the same thing. When we eat food and vegetables, we eat those. Food comes into the body. We can’t use it directly. We need to go through the methylation pathway to convert it into a source that’s ready for us to use. So anyway, long story short, what this guy Gary Breer basically does is he does like a genetic test.

[00:05:20] Seb Bunney: He looks at usually five specific genes. These are kinda like the M-T-H-F-R gene, the MTR gene, the MTRR gene, the COMT gene, and the CBS gene. Now, you don’t necessarily need to know what any of these things do, and I’m not gonna go dive into them, but I definitely recommend people going and digging into it.

[00:05:35] Seb Bunney: But basically, these are our methylation pathways, which help us detox energy, metabolism, information control. And so when he actually looks at these, he’s able to determine what supplements we need on a unique personal level as opposed to us just blindly throwing darts at a board, going and buying, oh, I need vitamin D.

[00:05:54] Seb Bunney: Oh, I need this. Oh, I need that. And so I think what’s so cool about what is happening in the world today is we’re starting to get like personalized healthcare. We’re starting to be able to have a personalized supplement protocol as opposed to us trying to listen to our intuition and feel, oh, I’m taking this thing and I think I’m feeling a little better.

[00:06:13] Seb Bunney: So I think that for me, I’ve noticed, I’ve been listening to Gary Brecker for a few years. And it has profoundly changed my health. I profoundly changed my health and I feel really lucky once I started kind of incorporating some of this stuff. I actually haven’t had a cold in four to five years.

[00:06:28] Seb Bunney: I’d got one this weekend and it’s the first one that I’ve had in four, five years. ‘

[00:06:32] Preston Pysh: cause you were gonna be talking about it. Yeah, a hundred percent.

[00:06:35] Seb Bunney: Gotta be talking about it. But I just find it really, really fascinating. And I know one of the reasons why I bring this up is because I know Preston, you and I talk about this a lot when we’re in person, just Yeah.

[00:06:45] Seb Bunney: How we show up, how we think about supplementation, how do we support our bodies in the best way possible. And so I just wanted to kind of bring up technology from a health standpoint is advancing so rapidly that we can start to have more personalized care. ’cause I think up until now, we look at the body as this kind of like singular thing that it’s just like, oh, people need this, this and this.

[00:07:06] Seb Bunney: And it’s just like, well that’s not necessarily true. Some people need more of this and less of this. Some people may have a deficiency in this. And so I think having a personalized healthcare approach is going to change the way I think we view health.

[00:07:17] Preston Pysh: Yeah, so he’s a major voice in the health longevity space.

[00:07:21] Preston Pysh: He’s the guy that’s wearing like the weighted vest around all the time, if I’m correct. Is that right? Sev. Sev, yeah. Yeah. Yeah. So the first thing that comes to mind as you mention all this is just tracking all of your DNA data and ingesting that into some database and then running AI on it in order to get, you know, insights that we’ve never really been able to understand before AI and its ability to pattern recognize, you know, so much complexity.

[00:07:51] Preston Pysh: So that’s the exciting part. Obviously from a technology standpoint, I know we have a lot of privacy folks that listen to the show through the Bitcoin community, and one of the things that immediately comes up when you start down this path of. Taking your raw code, your genetic code, your unique genetic code, and putting it into these models and running it on somebody else’s servers.

[00:08:14] Preston Pysh: People have concerns as to how that could maybe be used also in a very nefarious way and could be captured by, I know this 23 and Me was one that was doing DNA testing and keeping track of all of those records, and then they were procured by different parties and like what happens in the business of collecting biometric data?

[00:08:38] Preston Pysh: And I think it’s an important counter talking point to some of this stuff because like you, I am super excited and super fascinated by like what this could mean, what it could mean for adding gears to your life because now you’re finally getting custom treatment. I mean, what I think when you look at what you’re bringing up, Seb, which is this custom DNA like audit and then treatment based on that is where all of medicine is going in very short order in the coming five to 10 years.

[00:09:06] Preston Pysh: And I think it has the potential to lead to some like serious longevity results. I just, I don’t know how you possibly go about it in a way that protects the privacy of the people or that. Encrypts the data and you know that the person’s data is protected or whatever, right? Like it gets to be somewhat concerning and a lot of people don’t wanna talk about that side of it, but I think it’s an important additional note.

[00:09:30] Preston Pysh: I’m curious if you would agree or if you just

[00:09:32] Seb Bunney: Oh, I, I, I couldn’t agree more. And you know, to share some of my naivety on privacy. Previously, when 23 and Me was hacked, I was lucky enough one to download my data before 23 me was hacked. I used 23 and Me. Oh, so you did it? Yeah, years ago. Yeah. By 2018, maybe 2019, I think I used 23.

[00:09:51] Seb Bunney: And me, yeah, purely from the perspective of, oh man, I wonder if there’s any answer. Like really relatives of mine in the area and reach out to them. And I found it interesting, but ultimately it didn’t really give me much information. Yeah, it was a little more broad. And so I would say that what I’ve found really.

[00:10:07] Seb Bunney: Fascinating though is before I went down the privacy route, I took all of the downloaded data, put it into chat, GBTI probably shouldn’t have. And now I regret doing this, but I put it into chat, GBT, and then I started interrogating my own genetic information. Okay. And that was really, really fascinating.

[00:10:23] Seb Bunney: And so what did you learn? Wonder?

[00:10:24] Preston Pysh: What did you learn?

[00:10:25] Seb Bunney: Well, I was able to ask it like we’ve got, and I’m meaning, I can’t remember off the top of my head. It was something like 14. It was a Word document and it was 14,000 pages if I remember correctly. It basically just completely jammed my computer. My computer couldn’t process this much information.

[00:10:40] Seb Bunney: Yeah. But once I put it in chat and started interrogating the data, I was able to say. At the moment, Gary Brecker, I, I basically made a Gary Brecker bot and I said, I want you to be able to look through my genetics from the perspective of Gary Brecker. I want you to go and try and find the M-T-H-F-R gene, the MTR gene, the MTRR gene.

[00:11:01] Seb Bunney: Go and find and see if there’s a mutation. Because one of the things he talks about is take the M-T-H-F-R gene. If you have a mutation on the say M-T-H-F-R gene, then you can take, if I remember correctly, it’s one of the B complex, like B12 vitamins and all of a sudden it can massively improve your methylation pathways so you’re able to process nutrients.

[00:11:20] Seb Bunney: So I went through, looked, found out I did have this mutation, which I think a large portion of the population do. And just by taking B12, I noticed a huge difference in my health. Huge difference. Like so you so much, that was one of the biggest differences.

[00:11:32] Preston Pysh: You are so much further down this path than me. I, I’m really interested in this stuff, but dude, you are way down the path.

[00:11:39] Preston Pysh: That is fascinating. It’s, and so it found when you ran into the AI, it found that for you

[00:11:44] Seb Bunney: based on Absolutely. Wow. And I think that you’re able to, and this, and, and I should preface this by, there’s probably doctors listening to this and just being like, you’re probably interpreting this information wrong.

[00:11:54] Seb Bunney: And I think that I’m looking at it from a naive perspective, but they

[00:11:58] Preston Pysh: don’t know either. They don’t know either.

[00:12:00] Seb Bunney: I found it really interesting that when you have this information, I went and chat. First off, I removed all my personal information from it. So it didn’t know that it was necessarily me. I was saying, Hey, I’m looking at this data for this person.

[00:12:11] Seb Bunney: Are you able to let me know, is this gene mutated? What do you, what? What are you able to grok from this gene and such? And so I started interrogating the information. It can also, there’s a lot of other genes that give us insight into, do we have a prevalence of certain cancers, certain other issues, and we can go and interrogate our own genetics.

[00:12:28] Seb Bunney: So I think that’s really, really fascinating. What would be nice to see in the future is more privacy focused AI models where people can go interrogate their own information.

[00:12:38] Preston Pysh: I’m laughing and I can’t get the smile off my face. ’cause I’m thinking this doctor’s probably like pulling out a notepad and asking, you know, to take notes on what you’re doing in order to like go and do something similar.

[00:12:49] Preston Pysh: That’s fascinating, dude. Kudos to you. You know, I’m concerned about, you know, ingesting the data into chat GPT, but we’ll put that aside. We’ll put that over here, by the way. Great business idea there at the end.

[00:13:01] Seb Bunney: Totally, totally right. You know what, like, I’ve seen a few people go into their doctor’s office, they go and ask them, Hey, I’ve been having these symptoms, or Hey, I’ve been having this issue.

[00:13:09] Seb Bunney: And up until what, April of whatever it was of 2023 when chat GPT came out. The doctor was giving you their interpretation. Yeah. Now I’ve seen, heard of countless individuals walk into their doctor’s office. They ask them a question. The doctor’s like, oh yeah, give me one second. Types into chat. GT chat GT gives it an answer and then it feeds it back to the person.

[00:13:28] Seb Bunney: And so I think a lot of the doctors now are starting to use chat, GPT, because the chat, GPT is able to analyze just such a wider array of data. And a doctor has a very specific narrow view of field view.

[00:13:42] Preston Pysh: Yeah, yeah. The AI is training us at this point, man. I was, as a, as a funny side note, I was watching the Jerry Seinfeld standup comedy routine on Netflix, and he went on this bit where he was like, you, you think that you’re taking the cell phone around and all?

[00:14:00] Preston Pysh: No. He said, the cell phone’s taking you around, that cell phone is dictating where it’s sending you, and it’s just like this really funny bit. But anyway, I think that when you start going down this path of like, theis and like all these human interactions are just relying on the hope that what it’s feeding it because you need a fast answer.

[00:14:19] Preston Pysh: That’s really kind of the, the crux of the issue here is you don’t have all day to go find a hundred different resources to prove it wrong. You just kind of need a quick answer. And it doesn’t have to be perfect. It just has to be kind of good enough and like as the whole world continues to like. Push that easy button, like we’re creating data, but it’s data that isn’t necessarily human generated.

[00:14:41] Preston Pysh: I mean, you see these numbers coming outta Google and others, and the amount of code that’s being generated on these platforms and what, 70, 80, 90% of the code now is coming from AI and not even humans, so, It is getting weird, dude.

[00:14:55] Seb Bunney: And you know, like as you’re saying that, it makes me think about when I wrote The Hidden Cost of Money, my book, I feel really lucky that I wrote it pre AI.

[00:15:03] Seb Bunney: And I wrote it from the perspective of I looked at my note taking app and I had hundreds of books that I’ve taken notes on. So when I started to write it, I’d already ingested all of this information. And then I started writing a book. But now it wouldn’t surprise me if we were to have a look, and I haven’t done this, but if we were to have a look at the amount of books written and released every single year, pre AI versus post AI, we see this hockey stick.

[00:15:26] Seb Bunney: Where people are releasing these books. But it doesn’t necessarily mean that the information in these books has validity or has been deeply ingested and thought about. Because I can go to AI and say, Hey, you know what? I wanna write a new book on this subject. Can you please give me the 12 chapters and the key points?

[00:15:44] Seb Bunney: Now can you please write these out and can you provide sources? But I never went and read all of these sources. And most people don’t go and read the sources from these outputs from AI. And so I think. One of the challenges is like we’re putting increasing amounts of trust into this thing, and we’re not actually looking at the validity of the information being produced.

[00:16:02] Preston Pysh: AI slop.

[00:16:03] Preston Pysh: Let’s go to the next topic. Okay. So, and you didn’t have anything else, so you good on the, that’s it. Okay. Let’s go to this next topic. So I’m gonna play a clip and, this is, this is interesting stuff. This is, this is out there. that’s probably why I’m playing it because it’s fun. Okay, here we go.

[00:16:21] Clip 1: I mean, over time at Google we are always proud of taking moonshots. You mentioned way more earlier. You know, that’s been over a decade in the making. We’re working on quantum computing in that spirit. One of our moonshots is to how do we one day have data centers in space so that we can better harness the energy from the sun?

[00:16:39] Clip 1: You know, that is a hundred trillion times more energy than what we produce in all of Earth today. So we want to put these data centers in space closer to the sun, and I think we are taking our first step in 27. We’ll send tiny racks of machines and have them in satellites, test them out, and then start scaling from there.

[00:16:59] Clip 1: But there’s no doubt to me that a decade or so away will be viewing it as a more normal way to build data centers.

[00:17:06] Preston Pysh: Okay, so Elon Musk retweeted this. This is the CEO of Google that you heard talking, and Elon Musk retweeted that video and with just text that says, interesting as the SpaceX, you know, founder and operator.

[00:17:23] Preston Pysh: Okay, so. What in the world is all this about? So I have to, I have a confession. So I was out in, Luno, Switzerland for this plan B conference, and we did this like shark tank thing where we were like hearing different pitches and I was fortunate enough to sit on one of the panels and a gentleman came up and he presented Bitcoin mining in space.

[00:17:44] Preston Pysh: And I was just kind of like right off the bat, immediately I was like, this is just such a bad idea. Like I just couldn’t understand why anybody was seriously pitching this because it was the first time I’d heard of this kind of idea. And when I was going through the slides, one of the things that really stuck out to me was the cost.

[00:18:04] Preston Pysh: That to make this even viable, the cost for a space transport to get the hardware just into space, had to drop 10 x. So if it’s a thousand dollars to put whatever up there, you gotta drop it down to a hundred. Before this would even be viable to even begin doing this for real. And you know, they were pitching us for investment in this company that was trying to do it, but with Bitcoin miners, not GPUs, which is what was being or, or TPUs, the Google ones being sent up in the space.

[00:18:35] Preston Pysh: And so in preparation for this, after I watched that clip, I went and I remembered that 10 x number from the Luo pitch. And so I put it into AI and I was like, Hey, what would the cost have to be a drop for Google to really kind of execute on this? And this is called Project SunCatcher is what this is called at Google.

[00:18:53] Preston Pysh: And sure enough, the numbers came out that it needs a 10 x drop even for the TPUs that they’re trying to put in the space. So he’s calling it a moonshot. I would agree. This is definitely a moonshot. This doesn’t seem like this is like right around the corner. So they’re doing this test run. Let me just read through my notes here for people so they get it.

[00:19:11] Preston Pysh: Google Unveiled Project SunCatcher in early November, 2025 with plans to launch two prototype satellites by early 2027. So we’re basically a year, year and a half out to test AI hardware in orbit, partnering with Planet Labs for the initial mission. You know, they’re saying that, here’s another stat, it’s eight times more efficient than on Earth for them to harness the sun out in orbit than to be doing it down here on the cross of the Earth.

[00:19:38] Preston Pysh: Initial thoughts. Seb, what do you think of some of this?

[00:19:41] Seb Bunney: It’s interesting ’cause you sent me a text just with. A little snippet of what you’re gonna talk about. And so I was thinking about it a little more, and the first thing that came to mind was also my understanding of Bitcoin mining and why Bitcoin mining in space.

[00:19:55] Seb Bunney: There may be issues with it around latency, so depending on where you place. This data center, this Bitcoin miner. From my understanding, like when you are using say, fiber optics and stuff like that, we are capped at obviously the speed of light in terms of moving data. And so low earth orbit, it takes like two to 10 milliseconds to get information like back to earth geostationary orbit.

[00:20:18] Seb Bunney: I’m not even sure what this is. There’s like 240 milliseconds from So Geo geospatial?

[00:20:22] Preston Pysh: Yeah. Geospatial is that the satellite will stay over the same spot of Earth. So as Earth is rotating that it will stay right over that same spot the whole time. So you have to go out at a certain radius in order to get that.

[00:20:35] Preston Pysh: And geosynchronous orbit has, like, there’s a very small band in order to Make sure that it stays synced with the earth. So it’s a very popular distance from the earth and very cluttered distance from the earth.

[00:20:48] Seb Bunney: Wild. Yeah. So that says 240 milliseconds. Yeah. And then you’ve got the moon, which is two and a half seconds.

[00:20:53] Seb Bunney: And if you’re out in Mars, it’s like five to 20 minutes. And so the issue is like from a Bitcoin mining perspective, if you mine a block in space, by the time you actually propagate that block or push that block to the blockchain. Someone on earth may have already found a block and everyone builds on the, obviously the newest block.

[00:21:10] Seb Bunney: And so you’ve kind of, you’ve, you’ve got a disadvantage already just by being in space. And so I was thinking about it like, well, how does this relate to being a data center in space? And I think that it probably works for certain types of information. Yeah. But it doesn’t work for other types of information.

[00:21:24] Seb Bunney: So anything that is dealing with real-time interactions, millisecond responses, like high frequency trading, multiplayer gaming, blockchain, mining, I don’t think we’d be using that for the space. But I think that anything that is dealing with kind of some of these bigger ideas of like AI model training, large scale simulations and like batch processing, huge amounts of information, I think it could be profound.

[00:21:49] Seb Bunney: That’s kind of what came up as you sent that over to me in a text.

[00:21:52] Preston Pysh: So I interviewed an astronaut, oh my goodness, bunch of years ago, Tim Cora. And one of the interesting things that Tim told me, I don’t know if he told me this on the show or told me this privately, him and I attended a Berkshire Hathaway shareholders meeting many years ago, and he’s told me a bunch of stories throughout the years.

[00:22:10] Preston Pysh: One of the things I, that stuck in my head is when they were working on the International Space Station. They would go out, he did a spacewalk and he said that when you went out and did a spacewalk and came back in and you’re in the chamber taking off all the gear and you have a hammer, you have all your tools, like all those things, you had to be very careful that you didn’t bump into, call it the hammer when you came in, and the temperature, I forget what the threshold of the temperatures are.

[00:22:39] Preston Pysh: It’s hundreds and hundreds of degrees in both directions of hot and cold. And the temperature is changing every 45 minutes because that’s how fast you’re going around the planet, at least at that distance. For the ISS. They might be 45 minutes in the sun, 45 minutes on the dark side of the earth, and then 45 minutes in the sun again.

[00:22:59] Preston Pysh: And the temperature of the tools and all of your equipment is swinging by hundreds of degrees in both directions every 45 minutes. And so my question, when I was in Luana was I remembered this from Tim and I’m thinking from a reliability standpoint, the hardware, could you imagine just that hardware cycling through those temperature changes every 45 minutes?

[00:23:20] Preston Pysh: And like what that would do to the hardware from a reliability standpoint, I would think would be disastrous. So I asked this guy that question. And he said that there’s orbits that you can put the satellites in that will keep it more in the sun than it cycling every 45 minutes on 45 minutes off. So that was his answer to me during the thing.

[00:23:40] Preston Pysh: But I guess for me, I’m also looking at it just from a reliability standpoint. Maybe it’s not as harsh. Maybe this is a better environment. I don’t know. It’s a fascinating discussion, but the point that I could never get over was the reliance on the price reduction going down by 10 x just to get it into orbit and then it’s gotta work and the reliability and all these other things that are completely secondary to this massive hurdle.

[00:24:06] Preston Pysh: And I mean, he’s calling it a moonshot. I, I think it’s really fascinating that they’re doing a test run on this. But as far as the actual viability and like whether it’s actually gonna happen, I just, I don’t know. It seems like it’s just so out there.

[00:24:17] Seb Bunney: It’s. As you saying that, I remember reading something years ago, and I think as I was just looking up on Google, I think it’s called Kessler Syndrome, and it’s this idea that the more stuff we send into space, like we obviously already see on earth, like the amount of solar farms, all you need is a giant hailstorm and you’ve just decimated like millions of dollars of solar, basic solar equipment.

[00:24:41] Seb Bunney: Well, what happens in space when an asteroid belt kind of comes, I don’t know, flying through and just kinda like decimate a whole bunch of this material. And then you’ve got all of this space junk like flying around at speeds in excess of tens of thousands of kilometers an hour. And they’re just nailing into all of these satellites.

[00:24:57] Seb Bunney: Like is there a point whereby us sending all of this stuff up into space, we’re impeding our ability in the future to be able to go further afield and such? Yeah,

[00:25:05] Preston Pysh: it’s. Evidently it, it must not be too much of a concern. ’cause I don’t think that they would be going through any of these hoops if they didn’t think that it was a very viable path.

[00:25:14] Preston Pysh: If they could overcome some of those hurdles, like the 10 x reduction in the space cost for launch, let’s go onto the next one and, and if you are a person who’s tracking this and you wanna share some information, I would love to learn more. I find this whole thing, this whole idea, just super fascinating.

[00:25:28] Preston Pysh: Okay. You wanted to talk about custom learning, is that right, Seb? Yeah, absolutely. Okay, let’s do, do this one.

[00:25:34] Seb Bunney: Yeah, so long story short, someone ended up posting a lady called Stehut, S-T-E-H-U-T, and she was asking about like, what does AI do for the world of learning? And this one here I find really, really fascinating.

[00:25:47] Seb Bunney: So I was kind of digging around and I was just like, huh, I wonder where is AI in the world of learning right now? And even from my own personal learning, being able to have this AI bot feed me information about my curiosities has helped me understand the world from such a different lens. So anyway, as I kind of did a little bit of digging, it turns out that I think it was back in September, Google released something called Google’s Learn Your Way.

[00:26:11] Seb Bunney: Now, in essence, this is basically like a living dynamic tutor that’s tailored to each individual’s kind of pace, their interests, their background, and so it can take and ingest. These like static one size fits all textbooks and it’s able to take that material and convert it into, basically depending on your grade level, your interests, your learning preferences, it’s able to create mind maps, audio lessons, narrated slides, interactive quizzes.

[00:26:36] Seb Bunney: And so the way that I’m seeing this is this could profoundly change our educational systems. At the moment when we think about like what is the school system, when you go all the way back, we’ve come from like a bit of a Victorian era where we were trying to create a labor workforce. We want people to do very specific tasks and when the bell rings you move on to the next task.

[00:26:55] Seb Bunney: And it didn’t really incite curiosity. And so what’s really cool about this is I think as AI is taking over a lot of kind of the knowledge worker space as robotics in the future is gonna take over potentially some of more the manual labor space. I think where humans thrive is in the more of the creative space.

[00:27:12] Seb Bunney: So I think some of these like AI tutors. Are going to profoundly change the way kids are able to be curious because imagine being in a classroom, but essentially having a one-on-one teacher at all times, being able to support you. And so if you’re getting a question, I don’t know, a math question or a physics question or a biology question, and then they’re able to phrase it in like in line with your interests, that is hugely going to increase your ability to learn.

[00:27:39] Seb Bunney: And so already in like very early tests, it looks like students who are, they’re increasing their recall rates by like 11% plus just on recall tests. And to me I was like, whoa, that’s quite low. I was expecting it to be like hundreds of percent, but I also believe that that is only going to increase as this technology becomes far more efficient and kids are able to communicate in a way that gets information that is in alignment with their level and their understanding and such.

[00:28:04] Seb Bunney: But I’m curious to hear your thoughts on it.

[00:28:05] Preston Pysh: I think the big breakthrough on all of this is going to be just the AI’s ability to sense how the child learns. Just look at your kids. Anybody that’s got kids. You know, between one and the other, they learn very differently. Some have to go through examples, some have to, you know, everybody has a different way of learning.

[00:28:26] Preston Pysh: I’ll give you an example. I love audiobooks. I prefer an audiobook over the physical Coue. I, I actually, I prefer reading to me as I’m flipping the pages ultimately, but if I had to choose one over the other, I would actually prefer the audio version because I just kinda learn that way a little bit better.

[00:28:43] Preston Pysh: And it’s different for everybody. And so just as an example, the AI is gonna learn these different techniques that people have for that’s most optimal for them. The best way to frame it as a funny example, when I was a student at the military academy at West Point, we would always have these tests that were framed from like if you were in a math class, it was like.

[00:29:05] Preston Pysh: You have an artillery round and you’re gonna shoot it at whatever. And it was like always framed for some type of military example, and we would always roll our eyes and be like, oh my God, can you just give us a normal question and not some military type question. But I use that as an example to frame the framing of.

[00:29:23] Preston Pysh: The thing, let’s say your kid is, he loves football, or you know, your daughter loves dance or whatever. Like the examples could always be framed in a way that is exactly what they want to hear and how they want to, think about it, right? So I think that that’s gonna be huge. Now, the part that I think is still lacking, when we went through COVID, the kids had to do online zoom call, like classes.

[00:29:49] Preston Pysh: And to be quite honest with you, Seb, it was disastrous. Like it was just, it was a train. Anybody who’s gone to in-person education versus, you know, learning through a computer screen, like there’s some advantages for the computer screen, but there’s a lot of advantages to like in person. And I wonder if.

[00:30:08] Preston Pysh: Once you start getting into, you know, I don’t know that everybody would agree with this, but like maybe the humanoid robot AI is going to maybe have a difference because you’re having like a in-person interaction and so where are we in 10 or 15 or 20 years with respect to some of these ideas with AI learning, you know, once you put something into the physical environment and you could go over to a chalkboard or you could go on a field day and you could see whatever, I don’t know.

[00:30:35] Preston Pysh: I think that the learning kind of takes on a whole new level when you start incorporating it into physical space versus just always looking at something on a computer screen, and maybe you can do that with a v VR environment. I personally don’t like these things on my face. I find them to be highly annoying, but you know, some people might like it or learn that way as well.

[00:30:53] Seb Bunney: I think you’re spot on and I think that’s a really important point to kind of mention because I think that when we’re talking about any of these points in any of these tech podcasts, we do, we’re kind of talking about what is the newest technology and how is it impacting. But there’s always gonna be pros and cons to everything that kind of interacts with us and our world and how we show up.

[00:31:11] Seb Bunney: And, and what I think about, when I think about education is that the knowledge is one aspect of it. But when we’re in school, when we’re around our peers, when we’re interacting with our teacher, there is also the human connection. And I think part of, during our developmental years, while we’re in school, we are also learning how to regulate our nervous system.

[00:31:29] Seb Bunney: And so we are co-regulating with the teacher, the teacher, when they’re calm and grounded, that helps us learn. And so what does that do when we’re replacing these physical beings with this digital entity? Is that digital entity going to be able to be emotional? Are they gonna have that empathy and that capacity to support them?

[00:31:45] Seb Bunney: Or can you just completely not replace that with a digital entity? Like there’s far more from a resonance perspective that we’re interacting with and that’s, that’s what I find really interesting. I wholeheartedly agree.

[00:31:55] Preston Pysh: I’d tell you my wife. Hearing me say, oh yeah, you’re gonna have an AI humanoid robot, like teaching that.

[00:32:02] Preston Pysh: She would just be disgusted by such a comment. And I think that there’s a lot of people out there that probably would be like, oh my God, that sounds like a absolute nightmare of a future. And hey, maybe it is a nightmare if you, I don’t, I don’t know. But I can see the demand for some of these things taking place because I think that the, the customized education that you’re gonna get outta that is so far superior than some teacher that is an expert in history and everything comes with a history lens.

[00:32:34] Preston Pysh: And maybe the student that they’re teaching hates history, can’t stand history. And then everything is flavored with history for an entire year as you’re sitting there with 30 other students. I think that when we look back at the education that you and I, you know, grew up with, it’s gonna be so archaic to where I think a lot of this is going.

[00:32:52] Preston Pysh: Whether people like that or not.

[00:32:53] Seb Bunney: Totally. And there’s that famous, I think it’s the Buddhist quote, which is like, you shouldn’t judge a fish by its ability to climb a tree. And it’s just like, I think the school system. Yeah. I was 100% the fish.

[00:33:04] Preston Pysh: Yeah.

[00:33:04] Seb Bunney: I was craving less so a fish as a rock just laying on the floor. There was no way that I could climb a fricking tree. And so I think that school, to me, I never felt like I fit in. But once I left school and I was able to find audio books, I was able to find my ability to find how I learn. Amen. Oh my God. It was, it was profound. It. Amen. So I think that, how do we find this balance between, I think the biggest question is, it’s like how do we find this balance between like personalized learning while also having human connection.

[00:33:31] Seb Bunney: Yeah. And I think, I think that’s something that we really haven’t found that balance yet.

[00:33:34] Preston Pysh: I have conversations with people all the time and they ask me, oh, what kind of student were you, Preston? And to be honest with you, Seb, I hated school. I hated it because I didn’t feel like I was ever learning something that I actually had an interest in.

[00:33:46] Preston Pysh: I was always being force fed this stuff that I had no interest in, and it was never. Framed in a way that interested me. Yeah. And same experience after I got outta college, I just started reading things that like I wanted to know more about. And then I just loved it because I was focusing on things that I wanted to learn about and just truly never had that experience the whole time in high school.

[00:34:07] Preston Pysh: And I mean, I enjoyed the engineering classes I had in college, but beyond that, like all the other stuff that I, I literally had to take a poetry class in college with a bunch of, you know, how old were we? 18, 19-year-old dudes all standing in, you know, a classroom reading Shakespeare to each other, like, good god, shooting me.

[00:34:28] Preston Pysh: Like, it was the worst, it was the worst experience ever. ’cause I, I don’t like that stuff. I’m sorry if you love, if you love that stuff. I’m sorry, I don’t like that stuff. And that’s, that’s to the whole point of this learning thing is like people can lean into, finally lean into things that really interest them and like, I can’t even imagine what that’s gonna do from, if you start that out early and you do it for 20 years where the person is being led down a thing that actually interests them, and you’re being taught by the world’s greatest teacher on subject X, Y, and Z that that person’s interested in.

[00:35:00] Preston Pysh: I cannot even imagine what those results would look like by the time they’re, you know, 20 years old.

[00:35:06] Seb Bunney: That’s the thing though, it’s just trying to find that balance. I, I wholeheartedly agree, and it’s just like how do we achieve that? How do we find this balance, human touch and technology? This is a challenging one.

[00:35:14] Seb Bunney: There’s always a give and a take.

[00:35:15] Preston Pysh: Yeah. I have a couple AI topics that I wanted to bring up. The first one, and I’m gonna put up here on the screen, this one’s from Andre Capar, the very famous AI. He was head of AI at Tesla for a little bit, and then he was one of the founders at Open AI. To be quite honest with you, of the YouTube videos I’ve watched of people teaching AI, he is probably my favorite of anybody on the internet.

[00:35:41] Preston Pysh: He is such a great teacher and he makes things so accessible and he had this tweet and I just think that it’s kind of really interesting tweet and I think it’s worthy of highlighting here. He says, don’t think of LLMs large language models as entities, but as simulators. For example, when exploring a topic, don’t ask.

[00:35:58] Preston Pysh: What do you think about X, Y, and Z? There’s no you next time try. What would be a good group of people to explore X, Y, and Z? What would they say? The LLM can channel simulate many perspectives, but it hasn’t thought about X, Y, and Z for a while and over time and formed its own opinions in the way we’re used to.

[00:36:17] Preston Pysh: If you force it via the use of you, it will give you something by adopting a personality embedding vector, implied by the statistics of its fine tuning data and then simulate that. It’s fine to do, but there’s a lot less mystique to it than I find people naively attribute to asking an AI. So his big point here is don’t say what do you think he’s suggesting?

[00:36:41] Preston Pysh: People say, who would be the best group of people to have an opinion on this? And then ask the AI, what would this group of people think? I find that to be useful and important and it gets to the heart of a person who’s literally like programmed these things. He’s getting at something that is showing you a bias that will give you a cleaner and more accurate answer that you’re going after.

[00:37:02] Preston Pysh: So I think that that’s important for people to understand. Any comment, Seb?

[00:37:05] Seb Bunney: There’s, so we may talk about this if we have time and it’s around kind of this idea of, it was a diary of a CEO podcast that both of us have listened to and something that he mentioned in there that I thought was really interesting that kind of is in alignment with this, is this idea that.

[00:37:20] Seb Bunney: If we go on social media, our algorithm is giving us information based upon our interests. It’s not necessarily giving us the objective information. And what he also discussed is this idea that if you go and ask AI, what does it think about? Maybe this controversial subject, depending on your location, if in one location they have very different views, it’s gonna give you that answer.

[00:37:44] Seb Bunney: If you’re in another location, it’s gonna give you a different answer. And so I think the thing that is interesting is that you’ve gotta figure out how to prompt AI to give you the most objective answer. And so this is something that I’ve personally found and I’m, I’m curious to hear your thoughts. As I’ve been using AI, being able to give the AI a persona, so saying like, Hey, I want your perspective.

[00:38:04] Seb Bunney: If you were, say, an expert developer that has a knowledge in X, y, and Z I want that perspective. And so being able to look at it through a specific lens, and I don’t think people ask AI to look at something through a specific lens, and with that in mind, it’s just gonna give us what it thinks we want to hear so that we are just more attentive to AI.

[00:38:23] Preston Pysh: Yeah. And we are gonna play a couple clips from that interview here later on in the show. But yeah, outstanding comment. This next one’s a little political and I’m just, I’m bringing it up because I, I find it kind of an interesting topic. The president has recently come out and he’s trying to. Take away the state’s rights.

[00:38:45] Preston Pysh: So we have 50 different states here in the US and they all seem to be coming up with their own AI laws and rules. And the president is now trying to say that there’s gonna be an executive order on AI this week that forces all of the states to kind of fall under. The federal level AI mandate of like how we’re gonna go about this as a country and as a person that firmly believes in state’s rights and pushing responsibility as much out of the federal government and down to the state level as possible.

[00:39:18] Preston Pysh: This one pains me, but at the same time I’m also looking at it and I understand the logic that we’re in a global race and you’re up against some other superpowers that are moving out and not in a situation that you know, one state is advantageous, the other one is not. So then the big tech companies set up shop and the one that’s advantageous, but they also are concerned about the whims of that local government shifting and changing, and then they have to move all of this infrastructure to another state that now looks like it’s more advantageous for doing business there.

[00:39:55] Preston Pysh: And I think what I suspect what’s happening is the president is getting pressured by the big tech companies to have something that’s unilateral across the board. So they never have to think about my words getting rug pulled in state X, Y, Z, so that they have to then move all of this huge amount of CapEx into another state and the cost and expense, and most importantly, the time to make that conversion over to a different state.

[00:40:21] Preston Pysh: So they’re, I think what they’re doing is they’re lobbying him to do this. I’m curious what you think about some of this. I know this is a US topic except US politics, but I don’t know, I, I can understand why the tech companies are doing this. They just were trying to minimize risk to them. I suspect they’re the ones that are pushing on this.

[00:40:39] Preston Pysh: But if you have any comments?

[00:40:41] Seb Bunney: This regulation is something that I’m so torn on. And I think that going down the Bitcoin rabbit hole, I think a lot of Bitcoin has found themselves in this position where they’re like, you know what? Let’s deregulate. We believe that the free market knows what is best and ultimately if we want to move towards a society with growth, you don’t want to impede that information, making it to the free market.

[00:41:03] Seb Bunney: And I think the thing that I really struggle with is, I don’t necessarily think that it is black and white. It’s either no regulation or regulation, it’s somewhere in between. And like a perfect kind of example to me is something around the lines of. You can have a corporation that can be capitalizing off the destruction of the environment, and they don’t have to front that cost.

[00:41:23] Seb Bunney: And so then does a regulator have to put something in place where there is going to be a financial burden for then capitalizing off the natural environment. Because they’re making profit from destroying forest, extracting minerals, extracting X, Y, Z from our natural environment. And so I think that a lot of these corporations, if their bottom line is obviously profit and there’s no regulation they’re going to complete, they’re gonna continue to extract from a natural environment.

[00:41:49] Seb Bunney: And so I think the same thing is true for kind of a lot of these AI entities. Like if their goal is how do we build the fastest learning, most powerful AI engine, even if there is a risk at destroying the human race, we’re just gonna keep doing it. And so it’s just like, does there need to be regulation in place because the free market doesn’t have the capacity to push back on something like that.

[00:42:10] Seb Bunney: And I’m not sure, I don’t have like a fully formed opinion on it ’cause I can kind of see it from both sides. I dunno what your thoughts are there.

[00:42:17] Preston Pysh: Yeah. From a state’s rights standpoint, one of the advantages is it creates competition between the states in that if, and let’s not use AI, let’s just use, you know, oil.

[00:42:28] Preston Pysh: Like let’s say you’re an oil refinery. Let’s say that citizens of one state just really don’t like it because of what it does to the environment, what it does, just from a aesthetic standpoint, whatever, doesn’t matter. Okay. And then another state is like, oh no, we’re, we don’t care. We want all that business to come in here.

[00:42:44] Preston Pysh: We want all that commerce. So we’re gonna be, you know, pro regulation around that particular industry part. So that’s, and this is very hypothetical, we’ll just kind of illustrate the pros and cons, the company or the state that allows this to come in and just proliferate everywhere. Let’s just say that it’s over the top and it’s just one of the ugliest states in the world or in the United States to live, where the other one that was more restrictive is a much more beautiful state.

[00:43:09] Preston Pysh: And if you’re the type of person that doesn’t want to be looking at that kind of stuff, well then you’d move, you’d vote with your feet and move to the other state and the one that’s more desirable for you. Let’s say there’s a bunch of tax advantages in the one that, that is pro oil, right? You don’t want to be paying more money than you have to, so you move into that state.

[00:43:26] Preston Pysh: So in that scenario, you’re creating competition for people to migrate to the state that aligns with what it is they want out of their ecosystem that they’re living in the most. When it comes to AI, where this is a little bit different is the product that’s being built here. I don’t know that it has a benefit or a negative for that state over.

[00:43:49] Preston Pysh: Another one would be kind of the argument of why, hey, this is different. ’cause you’re literally building intelligence. I think you can make the argument from a data center standpoint in the footprint that the data and that that would be the argument is the data center and the footprint and the size of that footprint and the energy consumption of that footprint would be concerning from state to state.

[00:44:08] Preston Pysh: Some people might not want all of those data centers in their state for whatever reason. Some might love it because of the energy infrastructure that’s gonna be built out to service at all. So those are, you know, it’s a hard one.

[00:44:20] Seb Bunney: It’s tough. It’s a hard one. That’s an interesting point because I think the physical infrastructure, I don’t believe that should be regulated on a federal level. It’s just like if a state wants to open up jobs, if they want to kind of have more data centers, for sure, by all means, it’s kind of, that’s their choice. However, when the benefit or the negative effects of a technology not only impact that state, but they potentially impact humanity or the nation, all of a sudden it’s just like a state could be making a decision that impacts far more than its locality.

[00:44:50] Seb Bunney: That’s the thing that I find really, really interesting. And so, At what point. Do we need certain regulation because people are making decisions that are far more detrimental on a bigger scale. And then the question is, who is, and this is, I think, what gets to the heart of regulation. It’s just like, cool, okay, this is great if we can have perfect regulation.

[00:45:08] Seb Bunney: But you’ve gotta ask who is actually creating the regulation and who is regulating the regulators to ensure the regulators are being fair? And where’s the money coming from to help fund this regulation? And many times, like if you look at, I don’t know, the pharmaceutical industry. The pharmaceutical regulating agencies are funded by Big Pharma.

[00:45:27] Seb Bunney: Yeah. So it’s just like, there’s these conflicts of interest. And so that’s where it gets so convoluted.

[00:45:31] Preston Pysh: And again, we’re gonna talk about this, Tristan Harris discussion later in the show. And if you want to go down the regulatory policy path, and if you like this particular topic, then I would highly encourage you to listen to that entire interview because it gets very heavy in this, in this domain as to whether you should or shouldn’t.

[00:45:50] Preston Pysh: And I, and it’s a very biased point of view by the person being interviewed, which is, Steven Barlett, or, I’m sorry, Steven Bartlet’s doing the interview of Tristan Harris. Tristan obviously has a, a very strong opinion in that, but I think that it’s good just for a person to kind of hear that counter argument or that argument.

[00:46:09] Preston Pysh: And whether it’s, you know, something that they agree with or not. So let’s go to the last one that I have on just the AI topics here. I’m gonna put this up on the screen. And this is interesting because we’re talking about Google’s titans. This person, had this post here. And so like, what is this?

[00:46:28] Preston Pysh: Titans is a Google’s new architecture type that gives a language model something like a real long-term memory while the model is running. And so they have a chart up here and they’re showing how it’s ingesting 10 million tokens, and it’s still maintaining around 70% accuracy, which I guess is insane.

[00:46:45] Preston Pysh: And it has some of the other models and what they do with 10 million tokens, and it’s nowhere close to what Google has uncovered here with Titans. This one I found interesting because I find myself wanting to just put really large documents into a really long context window and asking it to still perform, and it gets laggy and clearly there’s something missing when it comes to long-term memory.

[00:47:12] Preston Pysh: So this paper came out in 2025. It didn’t come out this past week, but it did come out this year. And the title or the subtitle of the paper is Learning to Memorize at Test Time. And some of the token sizes that you’re putting through this thing. I was playing around with it, trying to understand how it works, and I got this paragraph that I’m just gonna read for folks to kind of like, think through how it’s doing this.

[00:47:33] Preston Pysh: Imagine you’re scrolling through your social media feed, and most posts are usually stuff like memes or friends. lunch picks your brain like the AI expects that junk and mostly ignores or forgets it is a safe space. But suddenly there’s a post about a surprise concert ticket giveaway for your favorite band that surprise grabs your attention so you remember the details like the entry, deadline, and rules while letting the boring posts fade away.

[00:47:59] Preston Pysh: And Titans, the AI uses a similar surprise signal from calculations based on gradients to spot unexpected or important info in the huge stream of data. Deciding to store that useful bit in its long-term memory. This way it keeps what’s valuable for later tasks, like answering questions without cluttering up the irrelevant repeats.

[00:48:19] Preston Pysh: So my immediate follow on question for that was, okay, so then how does the AI know that that concert ticket or that particular band is a surprise in the feed? And what I got back was it’s just looking at the sheer amount of training data that it was trained on. Which is the whole internet. And as it’s going through said document that you know has these millions and millions of tokens in size, it is finding something that is unique in reference to the entire data set that it was trained on.

[00:48:53] Preston Pysh: And that gradient is what’s allowing it to say, oh, that was different than what I would’ve predicted or expected. So then it remembers it. And what I find so fascinating. So, years ago I interviewed the author that covered Claude Shannon. And when we were covering information theory, I distinctly remember him saying, Preston, it’s just surprise.

[00:49:16] Preston Pysh: Like his algorithm, his mathematical algorithm is just looking for surprise. And when it was going through this Titans thing, I was just like, wow, this is literally just like information theory in order to do like long term memory, which is just mind blowing. Right? It’s fascinating, dude.

[00:49:34] Seb Bunney: It’s, what was it there?

[00:49:36] Seb Bunney: There’s that word in information theory, which is, if I send a letter to you, there’s gonna be a lot of noise in that letter. Ultimately, you’re looking for the surprise. The new piece of information. And it was kind of like the inverse of information. Information is noise. What we are looking for is the signal in that noise.

[00:49:55] Seb Bunney: And so it’s kind of like if you’ve got a block of marble, you’re cutting away all that excess to find the statue inside. And I’ve got blanked on that. But what comes to mind as you’re talking about this is. There’s one of my favorite TED Talks I’ve ever listened to, and I think you’ve read the book, is by a guy called Donald Hoffman.

[00:50:11] Seb Bunney: And he talks about do we see reality as it’s, yeah. Yeah. And he gives the analogy, and I highly recommend anyone going out and listening to this, just type in Ted Talk, Donald Hoffman, do we see reality as it is so good? And he mentions there’s this, it’s like a dune beetle in Australia, and this dune beetle has been around for something like 300 million years.

[00:50:30] Seb Bunney: So you would assume if it’s been around for 300 million years, of course it seized reality as it is. But then the Australians started throwing this, these beer bottles, these brown stubby beer bottles into the desert. And all of a sudden, this dune beetle nearly went extinct because it had effectively created a, a hack, a rule of thumb in its brain that is, hey, the bigger the browner, the better.

[00:50:52] Seb Bunney: And it just goes and tries to make, with these brown beer bottles nearly went completely extinct. So the Australian government had to step in bam, beer bottles, and all of a sudden that beetle started to kind of recover. But what I find really interesting about this talk and what he’s trying to kind of get at is this idea that we are not optimized to see reality as it is.

[00:51:10] Seb Bunney: We’re actually optimized for survival of the fittest. And so what we do is we take in all this information, we discard all the noise, and we try and create these rules of thumb to basically maximize our chances of survival. So if there’s a train coming towards us, we’re not processing all this information being like, what is this thing?

[00:51:26] Seb Bunney: I wonder how fast it is going, at what velocity is it gonna hit my body? And we ignore all of that data and we’re just like, train’s coming towards me. I need to get outta the way. We’ve created a rule of thumb to recognize that this is dangerous. Now, the reason why I say all of this is because AI, what is surprise to the AI?

[00:51:42] Seb Bunney: What information, when it’s looking at 10 million tokens, how does it know what is valuable? What is it actually optimizing for? Because we are optimizing for survival of the fittest. What is it optimizing for? And so that’s where I think I’m curious to dig deeper into these models and try and understand like what are they trying to pull out?

[00:52:00] Seb Bunney: Because either a developer has had to code that in this is the type of information that we’re actually looking for, or it’s figuring that out itself. And is that actually relevant? And I’m curious to hear your take or your thoughts on that.

[00:52:11] Preston Pysh: I don’t know that I have enough information on how these gradients are determined.

[00:52:16] Preston Pysh: I do know that I’ve seen posts by Elon Musk and others that really speak to the idea that the training data set, like using the entire internet, every single thing that you can get. Isn’t necessarily leading to the best model for task X, Y, and Z. Is it gonna train, is it gonna do really well for understanding English or the language?

[00:52:39] Preston Pysh: Yes. Is it gonna be most optimal if you’re trying to understand like a medical discussion? No. So then you gotta get into like, okay, so we have an AI that understands the language perfectly or near perfectly, and now we’re gonna apply that to a different model that then is more focused on the training set as to like what we’re putting in it.

[00:53:01] Preston Pysh: But all of that is, way outside of my depth of understanding as far as like how much research I’ve done on it. ’cause I have seen a lot of conversations by heavy hitters in the space talking about curation of the dataset and making sure that you don’t just put everything in there because it’s somewhat disastrous or how competitive it’ll be in particular tasks.

[00:53:24] Seb Bunney: I think that this is really important point, which is that I think it still falls on the individual to determine what is valuable and what is not. And I think that you can have this huge, huge research study that you kind of, or research paper that you’re looking at, and it’s spitting out a whole bunch of information saying This is valid, this is valid, this is valid.

[00:53:42] Seb Bunney: And to the average individual may be like, cool, this is rad. But to a scientific researcher who understands the subject, he’s able to again, filter through that again and separate out the signal from the noise. And I think that’s where ultimately humans aren’t gonna be replaced anytime soon. ’cause specialists in their field are able to see what is valuable and what is not.

[00:54:02] Seb Bunney: It’s just how as Bitcoin is. We can see when there’s a newspaper article or a New York Times Post or whatever that says, oh man, Bitcoin is consuming more energy than Argentina. It’s just like, well, that’s misleading and that’s not necessarily accurate. And so I think that you still need to be a specialist and deeply understand the topic to understand the validity of the output from a lot of these models.

[00:54:21] Preston Pysh: Seb, let’s go to our last topic for this show, and we’re running a little long, so I think we’re gonna have to schedule another one to put some other topics in there because I don’t even think we’re gonna get to this Tristan Harris discussion. But you wanted to talk about long distance haptic touch.

[00:54:36] Preston Pysh: Go ahead and take this topic away.

[00:54:38] Seb Bunney: Totally. So this is something that, oh man, it blew me away. I didn’t even know this existed. Essentially, I stumbled upon this post by Mario Norfolk. I wonder if I can even open up the post and I’ll show you guys. So I was kind of scrolling Twitter the other day and I stumbled upon this post by Mario, and basically what scientists has kind of created are these long distance haptic touch.

[00:55:01] Seb Bunney: And so for those that aren’t familiar with this word haptic, it’s basically, it’s like how do we create flexible patches that bring touch into virtual reality, augmented reality. And such. And so it gives a little bit of information in this post, but I started to dig a little deeper and I found the original scientific study, which kind of dove into this, the actual scientific study you can find here.

[00:55:23] Seb Bunney: And it was basically called skin attached haptic patch for versatile and augmented tactile interaction. And so this is basically the abstract kind of says just the first little bit. It’s like wearable, tactile interfaces that can enhance immersive experiences and virtual augmented reality systems by adding tactile simulation to the skin, along with visual and auditory information delivered to the user.

[00:55:46] Seb Bunney: And so to me, what I found really, really fascinating about this is these little haptic touch patches, essentially they are, if I remember correctly, they’re 1.1 millimeters in size, and they can, they’re extremely powerful for their size, and they’re able to create both pressure and like high frequency vibrations.

[00:56:06] Seb Bunney: So if you were to wear a glove with these haptic touches on your fingers, you would be able to, if someone else was, say, wearing the same glove and they went and touched textures, shapes, edges, letters, 3D surfaces. You could feel what they are feeling through these haptic touch senses. And so what does that do?

[00:56:25] Seb Bunney: I think we could use this in so many different ways. Either you could basically have an interaction with someone, let’s say through Zoom, you and I are talking right now, and if we went to hug or we went to communicate in a way that we wanted to involve touch, I could feel what you were feeling and have a much more like three dimensional, detailed interaction.

[00:56:43] Seb Bunney: But we could also look at it from the perspective of like virtual reality and augmented reality where you’ll be able to wear certain things, whether it’s gloves or a suit, and you’d be able to wear VR goggles. You’d be inside a simulation and you could be interacting with the simulation, not just from the visual sense, but also from the physical touch sense.

[00:57:02] Seb Bunney: And that to me, I think is, is, is mind blowing. So I’m curious to hear your thoughts on kind of this haptic touch sensor.

[00:57:08] Preston Pysh: Yeah. So while, Seb was talking there, for people that are just listening to the audio, I put up a video of a company that, it’s called Fluid Reality. And the company is putting these haptic sensors.

[00:57:21] Preston Pysh: And the way that they’re using that particular company is doing is they’re trying to give the humanoid robots better sensing of how they’re feeling, different objects, and whether they should be squeezing an apple very hard or very lightly as they’re interacting with it. And then you can see up on the screen right now, if you’re seeing the video of a person that’s wearing a glove, that’s training one of these humanoid hands with the sensing capability that Seb was describing.

[00:57:48] Preston Pysh: And when we just look at the robot’s ability to do certain tasks, like let’s say it’s doing laundry or it’s doing whatever, you can very quickly realize that the amount of pressure that it’s applying to the objects that it’s interacting with become really important. It becomes important from a power management standpoint.

[00:58:07] Preston Pysh: From just not breaking the object that it’s holding or damaging it. And I think that haptics are a huge part of humanoid robots and where a lot of that’s gonna be going. And this is something that is definitely worth paying attention to. And I have a couple more videos here. I’m just gonna quickly put up on the screen for people to see, and this is the Tesla robot, for people that are just on the audio showing you how like crazy accurate, the hand gestures and the mechanics in the hands are.

[00:58:37] Preston Pysh: And I don’t know where they’re at from a haptic pressure feedback standpoint on this particular humanoid robot, but by the looks of the hand gestures, it looks like it has a lot of sensitivity built into it. But yeah.

[00:58:50] Seb Bunney: I think this is one of, from my understanding, haptic touch is one of the biggest hurdles that I think robotics is trying to overcome right now.

[00:58:56] Seb Bunney: Yeah. ’cause it’s one thing to have a robot that is a forklift truck That is just going around doing its own thing, picking up the containers, moving those containers, dropping those containers. But it’s another thing. To have a robot that say operates in the kitchen and can pick up an egg without crushing it.

[00:59:12] Seb Bunney: Or to be able to do more pressure sensitive things like use a screwdriver and understand when it’s starting to strip the screw or starting to do things like surgery or sewing and cooking and things where ultimately I think there’s a lot more fine motor skills than we really take into account as humans.

[00:59:28] Seb Bunney: Like we are gi being given so much information through our hands, through our sensory touch and making decisions on that information that we are doing autonomously and being able to bring that into the robotic world. I think we’re still a little ways away. ’cause from my understanding, a lot of these hectic touch sensors can cost anywhere from like 10 to $50,000 for a set of hands that are able to do things like this.

[00:59:50] Seb Bunney: So we’re a long way off having, this available to everybody in their household. But to your point earlier, if we get a 10 x improvement, a 10, like a 90% reduction in price, and all of a sudden you can be doing this for a few thousand dollars, I think it’s gonna be far, far easier. But again, I, I just think it’s so fascinating both on the robotic side of things and on the individual side of things.

[01:00:13] Seb Bunney: And so one thing that I just wanted to kind of bring up and I’m curious to hear your thoughts, we had a, when was it? In March of this year, we were skiing in Jackson Hole together and we ended up having a conversation, I dunno if you remember on, are we in a simulation? We were kind of sat at a table and we had this conversation of are we in a simulation?

[01:00:29] Seb Bunney: And this idea of is AI and say some of the robotics we’re using today, is it being created or is it being rediscovered? Yeah, as in it already exists. Yeah. And so when I think about haptic touch, what comes to mind is the movie Avatar. And I think about as humans, we want to feel a part of community. We want to create value, we want to feel like we’ve got purpose.

[01:00:53] Seb Bunney: And so what do we do? We start to create products, we start to create technology. We start to kind of create companies and we go out into this world. In response, we create advancements in productivity and efficiency and such, and we start creating technology that starts to replace us. So all of a sudden when we start to replace ourselves, we’re losing that sense of purpose.

[01:01:11] Seb Bunney: We’re losing that sense of like. Community where we feel like we’re creating value. And so at that point, if society is degrading and all of a sudden there’s rising rates to depression and suicide and substance abuse and all of these things, what do we do as a community? Well, if technology is advanced enough, you could create a simulation with haptic touch like Avatar where we’re able to step into a world and move back to a much simpler time and back to that simpler time where we can start to create value again.

[01:01:39] Seb Bunney: And then we go and do it again and again. And it’s like how many times have we stepped into a potential simulation? Now, I’m not necessarily saying this is what I believe, but I think it’s an interesting thought because we are at a point where it wouldn’t surprise me from the next 30, 40 years. We’re able to create simulations that feel unbelievably realistic, and we can’t differentiate between the physical world and more of these simulations.

[01:02:04] Preston Pysh: It’s one of Elon Musk’s biggest talking points when this topic of simulation theory comes up, is exactly what you described s but. We’ll leave you with that thought experiment. I don’t know. Right. I don’t have an opinion, but I do find it to be a fascinating thought experiment and fun to kind of just tease out because the, the pace.

[01:02:25] Preston Pysh: Well, how, how would we know the pace?

[01:02:27] Seb Bunney: That’s the thing.

[01:02:27] Preston Pysh: Well, and the other thing that I, that I find fascinating are all these AI environments that are just kind of ad hoc making up, like they’re showing videos of these things. I don’t know if we’ve ever put it on the screen of one of the podcasts, but maybe we did earlier, but it’s just making up this environment and you’re watching this video of somebody like walking down a street and it looks completely real and it’s just being made up on the fly by AI.

[01:02:50] Preston Pysh: And then there’s a bit of a memory component that if you turn around and that you saw a tree just, you know, a couple minutes ago, that if you turn around and start walking back the other direction, the tree will still be there for a certain amount of time. And Yeah, like it’s just that environment’s being made up.

[01:03:05] Preston Pysh: And so I can’t imagine. In 20 years where this is, and then the memory recall of like what’s been experienced in this made up world that somebody’s going around and sensing in virtual reality. And I guess I say all this because it’s teasing out this idea that you bring up, which is like, how do you know what is real and what you’re experiencing is reality.

[01:03:28] Preston Pysh: ’cause you know, you go into any of these theoretical physics conversations and they’ll tell you that what you think you know is not that at all. And it’s very, very, very different from a quantum mechanic standpoint. But anyway.

[01:03:42] Seb Bunney: Absolutely, and we’ve spoken about it on previous episodes where Nvidia is creating, I think it’s cosmos.

[01:03:47] Seb Bunney: Which is their like simulation. So that people are able to test robotics. Yeah. In simulated world before they enter the physical world. And these simulated worlds are getting so realistic now. They have fluid dynamics, they have gravity, they’re able to apply all of these very various like physics, pressure and such.

[01:04:04] Seb Bunney: And so I think that the world we’re living in is really, really fascinating. We’re at a point where we’re kind of joining the physical and the digital world to the point where it’s just like, are we gonna be able to separate them? Because I do think that there’s this teenagers, there’s kids that are growing up in this new world and sometimes they get confused between what is real and what’s not.

[01:04:23] Seb Bunney: Because of that constantly interacting socially, digitally, everything emotionally in the digital world. Yeah.

[01:04:31] Preston Pysh: Alright guys, we’re gonna wrap here. I hope you guys enjoyed the conversation, Seb, we’ll probably do this again in like two weeks to kind of cover the other topics that we didn’t even get to. Most importantly, we want to cover this Tristan Harris discussion on the diary of A CEO Stephen Bartlett’s podcast.

[01:04:48] Preston Pysh: A couple different topics that were brought up there we wanna discuss on the show in addition to more tech topics. If you guys are loving this, let us know in the comments. We’re having fun. Hopefully you’re having fun here. Some of the the different topics that we’re bringing to you. And if you have any recommendations of things you wanna hear, bring ’em to us on X and we’ll be sure to try to incorporate it into the next show that we do.

[01:05:08] Preston Pysh: So, Seb, give people a handoff to your book or anything else that you wanna highlight that’s out there. And then we’ll go ahead and wrap.

[01:05:14] Seb Bunney: Absolutely. And again, like we really appreciate anyone who just kind of takes the time to give these episodes to listen. And so if, any point you’re just like, oh man, I’d love to hear you guys’ perspective on this technology or that technology, feel free to just like share it in the comments.

[01:05:26] Seb Bunney: And yeah, we really want to go talk about what’s happening in the world today and just kind of share our perspective. And yeah, you can find me at Seb Bunney, and that’s B-U-N-N-E-Y Twitter. And my book, The Hidden Cost of Money or B is for Bitcoin. But again, appreciate everyone giving us a listen.

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