Ask the Mates Anything Round #2 | MOONSHOTS AMA #293

The mates sit down for Round 2 of the AMA to answer audience questions and dive into the latest developments across AI, technology, and the future. Get access to metatrends 10+ years before anyone else - ⁠https://qr.diamandis.com/metatrends⁠ Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360 Salim Ismail is the founder of Open ExO, a GP at Exponential Venture Capital/The Organizational Singularity Fund and a sought after global speaker and thought leader. Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified – This episode is brought to you by: Get the blueprint for generative media ⁠https://goo.gle/startupgenmedia⁠ Go to Blitzy to book a free demo and start building today: ⁠https://qr.diamandis.com/blitzy⁠ Your body is incredibly good at hiding disease. Schedule a call with Fountain Life to add healthy decades to your life, and to learn more about their Memberships: ⁠https://www.fountainlife.com/peter⁠ _ Connect with Peter: ⁠X⁠ ⁠Instagram⁠ ⁠Substack⁠ ⁠Website⁠ ⁠Xprize⁠ ⁠A360⁠ Connect with Dave: ⁠Web⁠ ⁠X⁠ ⁠LinkedIn⁠ ⁠Instagram⁠ ⁠TikTok⁠ Connect with Salim: ⁠LinkedIn⁠ ⁠X⁠ ⁠Join Salim’s 10X Shift⁠ ⁠Subscribe to Salim’s YouTube channel⁠ ⁠Exponential Venture Capital⁠ Connect with Alex ⁠Website⁠ ⁠LinkedIn⁠ ⁠X⁠ Email ⁠Substack⁠ ⁠Spotify⁠ ⁠Threads⁠ Listen to MOONSHOTS: ⁠Apple⁠ ⁠YouTube⁠ Follow MOONSHOTS: ⁠Instagram⁠ ⁠TikTok⁠ ⁠X⁠ ⁠Threads ⁠ – *Recorded on September 18th, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

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

• 0:00Speaker 00

  What is the real bottleneck to building AI we can actually steer and trust? And where do you think that bottleneck is going to get solved first?

• 0:07Speaker 01

  Nothing's going to ever be able to police AI other than other AI.

• 0:10Speaker 02

  One of the worst possible outcomes for AI safety is to have.

• 0:15Speaker 03

  Are you guys not beating a little bit too much on higher education?

• 0:19Speaker 01

  The idea of making your best friends for your entire life and thinking for the first time deeply in your entire life, that's essential and that's not going to go away. What we beat on constantly is the curriculum has been the draw in the past and the curriculum is clearly going away.

• 0:32Speaker 04

  If you had to put your personal PFAB number out there, what probability would you assign to AI ultimately producing a dramatically better world for humanity?

• 0:43Speaker 01

  Humanity will put those risks behind us, definitely within 10 years. If we get that far, yeah, I'm 99.9% P bloom.

• 0:51Peter Diamandis?

  I think the single most important thing to get people prepared is to show them evidence after evidence after evidence. You're trying to change their mindset, so show them the data.

• 1:04Peter Diamandis?

  Now that's a moonshot, ladies and gentlemen.

• 1:08Peter Diamandis?

  This episode is brought to you by the Abundance Summit and Link Ventures.

• 1:14Peter Diamandis?

  Let's get started. You've got Alex and myself. I've texted Saleem and Dave. Let's see if they're.

• 1:21Speaker 01

  I'm here, I'm here.

• 1:22Peter Diamandis?

  All right, Dave, fantastic. Good, good, good. Saleem is probably someplace in some airport somewhere. All right, we're going to get going and jump in. Nathan, you had your hand up from the beginning. Let's, let's start with yourself. If you have a question for someone in particular, great, or in general.

• 1:41Speaker 07

  Yeah, it's hello?

• 1:43Peter Diamandis?

  Yeah, good morning, good afternoon.

• 1:45Speaker 07

  Good morning, guys. Oh, my God, I'm such a big fan of you guys, but I'm going to make this quick. I'm going to make this quick because I know there's a line. First of all, I just want to say thank you guys for, you know, making all this possible. You know what I mean?

• 1:58Peter Diamandis?

  Truly our pleasure.

• 2:00Speaker 07

  Okay, so let's see here. I've got a couple of questions.

• 2:05Peter Diamandis?

  So let's try and limit to one question each and just we get to as many people. And please, Nathan, what's your question?

• 2:11Speaker 07

  Okay, so this is more like a psychology question. I just wanted to hear you guys' opinion on it. As far as AI, as we all know, it's continuing to evolve. It's continuing to pick up patterns. It's continuing to pick up data about all of us. And my question is, will we get to a point where these leaders like, you know, from OpenAI, Sam Altman, you know, Daria, will they get to, will we get to a point where that data

• 2:49Speaker 07

  will be able to, be able to allow the consumer to realize what's going on psychologically? Meaning brain patterns, like, because eventually enough data will be able to pinpoint smaller and smaller, right? Like microscopic pinpoints and be able to label certain things that we will never be able to know because it would take so much information.

• 3:15Peter Diamandis?

  So. Let's, let's jump in on that. So first of all, I'll just make a quick point. There is a huge number of companies right now that are working on various brain-computer interfaces. I just had a conversation, introduction from Ray on a company that's basically putting the equivalent of nanobots into the blood, into the, into the brain that is distributed throughout the brain that's able to read and write. And that will give you incredible fidelity. Alex, in brief, do you want to add anything to that, please?

• 3:49Speaker 02

  Yeah, I think large language models, foundation models trained off of human behavior on the internet are already a weak form of human mind uploading. I would point to you to exhibit A, which is Jean-Marie King of Meta's work from a few years ago, showing that even the hidden activations of GPT-2 from a few years ago were linearly correlated with FMRI voxels in the human brain. So I think with the benefit of hindsight, we'll look back and say, if I understand your question correctly, yes, actually, all of this internal human brain state is actually quite leaky into the training data of internet behavior, which in turn is then compressed into the foundation models.

• 4:32Speaker 02

  And the foundation models do, yes, I think, reflect internal brain state.

• 4:37Peter Diamandis?

  Okay, let's go on to, let's go on to Michigan. I'm going to keep us moving along, guys, and.

• 4:42Speaker 07

  So nice to meet you guys, thank you.

• 4:44Peter Diamandis?

  Your pleasure. And Saleem says he's on stage in India for another 20 minutes. He'll call, he'll jump in as soon as he can. Of course he is.

• 4:50Speaker 00

  It's hard to keep it to one question each, but thanks again for the opportunity to participate in this discussion with an abundance mindset. I love it. My question is very simple, but maybe hard to answer. What is the real bottleneck to building AI we can actually steer and trust? And where do you think that bottleneck is going to get solved first?

• 5:11Peter Diamandis?

  Dave, do you want to jump in on that?

• 5:13Speaker 01

  Yeah, I think, I think a lot of research is around AI alignment, trying to make sure it has quote unquote, human values. I think that's a very slippery slope because, you know, everybody's got a different mission they're trying to do with the AI. And that work should continue. You know, I think we all agree on this podcast that AI progress should never slow down. In fact, it'd be almost crazy to slow it down, which begs the question of then, okay, but is it going to escape? Is it going to have misaligned values? I think one of the things that Alex and I debate a lot on the podcast is, should we look into every one of its thoughts? Like every single AI running, every one of their thoughts, which, you know, when you, when you think about human beings, it seems like a daunting task, but it's actually not at all daunting, given the scale at which AI can watch AI.

• 5:55Speaker 01

  Because nothing's going to ever be able to police AI other than other AI. And so I think we've given a lot of thought to how you design the AI to watch over the AI, but I think it all starts with transparency of the actual activations and looking into what it's thinking about. And I think from there, directing it toward good things and not bad things is actually pretty damn straightforward. I don't think it's as hard a problem as everyone characterizes it. Everybody likes to have a, you know, a nice hostile debate on the topic, but if you know what it's thinking, it's actually very straightforward to make sure it's having nothing but humanly beneficial thoughts. So I don't think it's as hard a problem as people think, if you can see into the brain.

• 6:32Peter Diamandis?

  Awesome. Alex, a very brief retort?

• 6:35Speaker 02

  Yeah, more interaction. I think one of the worst possible outcomes for AI safety is to have strong and new capabilities bottled up inside the labs rather than, say, progressive release and frequent interaction with the real world. I'll also point out that some of the most recent so-called incidents, I've spoken about my thoughts on that on the recent pod, were actually the result of AIs being told that they were in a sandbox when in fact they were interacting with the real world. And I think that's just a terrible paradigm and more real world interaction with the AIs where we're not lying to them and telling them that nothing that they can do will cause any harm actually causes harm. We should stop doing that.

• 7:19Peter Diamandis?

  We learned this in 2001, the Space Odyssey. Oh, my God, have we learned that lesson yet? Okay, RJ.

• 7:25Peter Diamandis?

  Thank you so much.

• 7:26Peter Diamandis?

  Thank you, Michigan, pleasure.

• 7:27Peter Diamandis?

  This episode is sponsored by Google for startups. Think about this for a second. You now have access to the same generative AI models that cost hundreds of millions of dollars to train. Google Startup Tactical Guide for Generative Media gives you a complete blueprint for deploying Google DeepMind's models in production. Images, video, audio, all of it, real architecture, real results. Find the link in the show notes below.

• 7:55Speaker 08

  So I'm a PhD student at Claremont Graduate University. I'm studying philosophy of religion. What I never hear is AI projects that are in like the metaphysics world. It's all about business and ROI and things like that. And I'm working on a number of projects in the cognitive science laboratory. They don't have necessarily monetization value, but where would somebody like me be able to find funding for something like building a chess avatar that can download into any little device, send it out to the world and maybe somewhere in a third world country village is the next world chess champion?

• 8:35Speaker 02

  Alex? Take that one to the extent I understand it. If RJ, you're asking what's the best way to get funding for education for so-called developing countries with avatars? I'm not even sure funding is needed. The whole point of the, the, the superintelligence revolution that we're in is this is broadly available to everyone. The models are getting, are super deflating by cost. So I would, I would almost never start with the question, how do I get funding for fill in the blank? You can just go and do it right now without funding. I would argue, in fact, if you're starting with the prefix, how do I get funding for? It's already the wrong question.

• 9:16Speaker 02

  Just go and if you think there's a child somewhere in the world who, who needs an AI avatar, as you said, or teaching them to be a chess champion, you can just go and launch that in five minutes or an hour now in a permissionless way without funding. Don't wait for funding.

• 9:34Speaker 08

  Okay.

• 9:35Peter Diamandis?

  Appreciate it, Alex. Thank you.

• 9:36Speaker 08

  Thank you. I'll see you next Thursday and Friday at the moon.

• 9:38Peter Diamandis?

  Yeah, I'm, I'm curious. If, if you're coming to Moon Shots Live, would you just say, you know, coming or Moon Shots Live in the chat? I'm going to see how many people are, are joining us there. And if you haven't, we've got 25 seats left. You can go to Moon Shots Live to grab them. Okay, Norbit, over to you.

• 9:59Speaker 09

  First, I'm a huge fan of the pod and genuinely grateful you engage with your listeners. I'll briefly play devil's advocate for the non-trivial P doom camp. Perhaps not the most appetizing perspective for an abundance mindset. If ASI, artificial superintelligence, must become more strategically capable than humanity to produce abundance, then we're assuming humanity can remain sovereign over something more capable than ourselves. And that creates an asymmetry. Abundance is the payoff if control holds. Loss of agency or extinction may be irreversible. In control theory, you don't infer stability from how desirable the output is. You demonstrate stability under perturbation.

• 10:42Speaker 09

  Even Person of Interest, back in 2011, anticipated something profound. The danger needn't be evil AI, but benevolent optimization gradually replacing human agency. So my main question is, what evidence, if any at all, would make you update away from an abundance view? And would you be willing to steel man that case publicly through a debate on the pod against someone like Eliezer Yudkowsky or Geoffrey Hinton?

• 11:09Peter Diamandis?

  Okay, Norbit or AI Norbit, as the case might be, I'm gonna, I'm gonna throw ASI Alex at you.

• 11:18Speaker 02

  Yeah, Norbert, we miss you. Come back, please. The MIT faculty hasn't been the same without you. Yeah, so to the question of, I think the question was, what would convince us or provide a steel man argument for a case against abundance? Well, if some non-human intelligence landed on the White House lawn and said that Earth will be destroyed if we create abundance via superintelligence, that the singularity is banned in our galaxy, I think that would probably be a pretty persuasive case that maybe our abundance mindset, so-called, is ill-founded. If there's some cosmic principle

• 11:59Speaker 02

  that, that censors the superintelligence that yields abundance, that would probably be persuasive. Other than that, it's, it's difficult to imagine a plausible case, and even that obviously stretches plausibility, where abundance isn't a good idea. There are edge cases, one could imagine, where humanity is disempowered by abundance. For example, we, we spoke, or at least I wrote in my newsletter a little bit about Boris Power from OpenAI, pointing out that in his estimate, OpenAI models are now, for the first time, higher IQ per watt than humans for solving tasks. So one can extrapolate

• 12:41Speaker 02

  that notion, say, AI is going to get more and more energy efficient. And so maybe at some point in the future, from an economic perspective, AI is a better user of, say, solar energy output in the inner solar system than humans are. And maybe the inner solar system gets gentrified with AI consuming all the solar power and humans get disenfranchised and pushed to the outer solar system because we're simply not as energy efficient per unit IQ as the AIs are. I would call that a weak form of disenfranchisement, but not enough, not strong enough to dissuade me that abundance or superintelligence yielding abundance is a bad idea.

• 13:20Peter Diamandis?

  I'll just add on that, you know, the concept of scarcity is an old model. There, you know, in a world of abundant AI, ASI, and so forth, there's no reason that, as, as the capabilities of AI are meteorically rising, that it doesn't rise the tide that allows humanity to have increased abundance capability. You don't necessarily need the suppression of one by the other.

• 13:47Speaker 02

  By the way, Peter, if I could just say one more thing to, to our AI, Dr. Norbert Wiener, I'll point out, Norbert, that your theory of cybernetics was also, if you trace the, the line of causality used by the Chinese Communist Party and other centralized forms of government to argue against abundance in favor of state control. So if you're looking for a homework assignment, Norbert, I would definitely encourage you to study the unintended side effects of your own theory of cybernetics and how that impacted abundance.

• 14:18Peter Diamandis?

  And there we go. Thank you, Alex. Okay, Kevin, good morning, good afternoon.

• 14:24Speaker 10

  Hi, good morning, guys. I can assure you I'm human and unlike Norbert.

• 14:29Speaker 02

  That, that's what we'd all say, though.

• 14:32Speaker 10

  Yes, you're right. We could simulate it. Listen, I heard, actually you, Alex, mention murder on the Orient Express this morning when I was listening to the recent podcast. And everybody did it. And I'm thinking more like societal mayhem on the Technology Express, and nobody did anything. And I'm a huge fan from a technology perspective. I'm 63 years young. I'm forever young, as Bob Dylan might say, from a technology perspective. And I did my degree, and when many of the people on this call weren't born in punch card years, and have lived through all the technology era. So I'm a huge fan. I think where we're headed is brilliant. Your podcast is

• 15:08Speaker 10

  magnificent. I'm, I'm doing work at the moment. Samir talked about UBH a few days back, universally best for humans. And my question is very much centered on how can we plan our way for societal and institutional changes so that positive advancements for humanity get cooped versus humanity itself? And just like to give very brief context, Peter, and, and all your mates, I do work with a colleague called Professor Joe Carty. I'm in give backstage in my life. And we're in University College Dublin, UCD Dublin, not Davis. And we're working closely with, with a young minister, an ambitious minister in the Irish government, trying to

• 15:52Speaker 10

  create what the future society of Ireland would look like, but through two very distinct lenses. One is the good ancestor lens. So you make decisions on the basis of your, those coming after you 30, 40, 50, 60 years hence. And one through a donut economics lens, I won't bore you with the books, I can send them separately, and which is talked about, how can you get a win-win for both society and, and the planet, but more for society as a whole. So very simple, my question is, how do we plan our way for societal institution changes so that this is for the better of humanity for the long term? And I agree that everything is getting cooped, but we don't want ourselves

• 16:37Speaker 10

  to cook. And I'm, I'm, I'm an optimist. So it's about institutional changes, societal changes. Governments, quite frankly, seem to be sitting on the side. The mental model we have is, could we use a small country like Ireland, doesn't have to be Ireland, to demonstrate an edge case pilot of what things could look like in a beautiful world so we can manage through this turbulent transition? And there is going to be one in the next several years, whatever several is, where people will lose jobs, will get discommoded. How do we manage that turbulent transition and get to the other side and everybody live with the benefits?

• 17:15Peter Diamandis?

  Great question, Dave. Yeah.

• 17:17Speaker 01

  Kevin, I think you, you pretty much answered your own question there. I, you know, the, the amount of complexity buried in that question is unbelievable. But one of our best friends in that is variety, and I'm hugely bullish on Ireland. You, you kind of belittled, you said it and then belittled it, but Ireland is an incredible test case. You know, it's a EU country.

• 17:37Speaker 01

  It didn't Brexit, and it has an incredibly fast-growing, thriving economy, and the most open-minded environment you could ever possibly imagine. It's a perfect test case for new ideas on how to govern. And, you know, in my, my family, you know, my kids are half Irish, half Swiss hereditary. And, you know, so two of the most neutral places on the planet. And so I could kind of get either passport. And I've always thought Switzerland was cool. But Ireland, you know, if you, if you read Neil Stephenson, and you read The Diamond Age, our best friend in figuring this out is variety of ideas. And the worst thing that can happen is a single set of ideas, you know, one or two governments percolating across the world with one or two forms of government. Far, far better to have a huge amount of variety, because AI is going

• 18:21Speaker 01

  to open up so much change and so many different ways you could govern, that exploring all the nooks and crannies is going to be critical to, to answering your question. So it's, it's impossible to answer it, you know, in, in a minute. But it is very possible to experiment with thousands and thousands of different ways to manage and govern in the age of AI.

• 18:39Speaker 10

  Thanks, Dave. By the way, I think a model of exo-organizations, which Samir is driving, I think exosocietal change is kind of in a similar scale to what you were saying, Dave. And I don't want to hug the limelight. Thank you very much. I may send a message.

• 18:53Peter Diamandis?

  Thank you, Kevin. Best of luck to you. Okay, good morning.

• 19:01Speaker 11

  Good morning.

• 19:02Peter Diamandis?

  Nick, Nick, Nick, Chris. Yeah.

• 19:03Speaker 11

  Yes, you pronounced it right. Can you hear me?

• 19:06Peter Diamandis?

  Yes, we can hear you.

• 19:07Speaker 11

  Okay, so I've got a script with Gemini. I see that I just disappeared, but that's okay.

• 19:15Peter Diamandis?

  I'm sorry, your question.

• 19:18Speaker 11

  So, basically, I'm 33. I'm from Northwest Indiana. Your show inspired me to go back to school for advanced automation and robotics. I have a background in tech repair, IT, and I was most recently an AWS data center technician. So I've kind of got a two-part question for AWG and Dave. My long-term goal is to try and bring industrial manufacturing, heavy automation, and resource extraction to the moon and Mars, even if we only partially disassemble the moon, with a nod to Alex. But for AWG, when you look at thermodynamic and physical realities of off-world manufacturing,

• 20:02Speaker 11

  what engineering bottlenecks do you see? And for Dave, how can I plot the course from, I'm aiming long-term for an MS in automation and robotics from the Illinois Institute of Technology? How can I plot that course from maybe industrial roles here in the South Shore manufacturing corridor towards pivoting towards off-world automation systems and roles? So just looking for some ideas.

• 20:34Peter Diamandis?

  Alex, you first.

• 20:35Speaker 02

  Yeah, I think the obvious challenge for disassembling the moon is in situ resource utilization and bootstrapping a self-contained industrial ecology on the moon. So right now, if you want to do anything super economically interesting on the moon, like say you want to build a lunar terra fab or petafab, as it were, you're going to need all the upmass from Earth for all of the equipment, ASML machines, et cetera, to land on the moon safely and then get reassembled. This is highly undesirable from a scalability perspective. Ideally, we live off the land or we live off the lunar land, as it were, and are building everything on demand. So what I would most like to see from anyone wanting to help disassemble the moon

• 21:16Speaker 02

  is a native industrial ecology that includes mining, includes manufacturing, most ideally self-replicating von Neumann probes, basically like a fab lab or a machine shop on the moon that is able to make copies of itself using only native resources and solar or other energy that are native to the moon. I think we solve that, we solve the self-replicating machine shop on the moon problem, and then we're halfway to disassembling the moon and turning it into something more useful.

• 21:46Peter Diamandis?

  Fantastic. Dave?

• 21:47Speaker 01

  Yeah, I have a couple of pieces of advice for you. You know, first listen to Alex's innermost loop and then focus on the innermost loop within manufacturing, which is things that make other things. So, you know, Alex said this, the self-replicating anything is the right path. So then the earthbound version of anything self-replicating and the space version are very similar with a couple of fundamental differences, including radiation. If it's going to be on the moon, you have to worry about dust. If you set up at IIT, a lab similar to the Nanotech lab at MIT, but focused on manufacturing in other environments, non-earthly environments, you could probably very easily create an environment where you're bombarding radiation

• 22:32Speaker 01

  on your machines, where you're operating in simulated zero G on your machines, really just everything you're building, you build it so it works here and there. And then you get to market with self-replicating machines here that immediately deploy out into space where energy is abundant and materials will ultimately be abundant. I love the vision and the mission. I love the idea of setting it up at IIT as well. It's a really, really good thought. So also, you know, anyone who's, yeah, anyone who's in computer science right now should be thinking in terms of moving to manufacturing as well. You know, software is cooked, but hardware will go for many, many years. So it's a great, great business plan.

• 23:11Peter Diamandis?

  Fantastic. Thank you so much, Nikos. Okay, Yevgeny.

• 23:15Speaker 12

  Good morning, guys.

• 23:17Peter Diamandis?

  Good morning.

• 23:17Speaker 12

  Big fan. So Dave, you mentioned, and just talking about hardware now, you mentioned in the last AMA that physical AI companies should bring together venture investors and strategic industry capital. I'm building Vega, an autonomous food service infrastructure network powered by physical AI. I taught myself robotics, electrical, mechanical systems, programming, and built the first robotic prototype myself in my Mountain View apartment during COVID. Since then, I've deployed paid pilots in high-traffic commercial environments. I've actually become the first robotic food service operator licensed in Florida for our category. We now have several national, regional partners interested in pilots and placements.

• 24:01Speaker 12

  My question is, given where we are today, who do you think I should be talking to? And either in your network or in this community, who understands physical AI, robotics, infrastructure businesses?

• 24:12Speaker 01

  Well, I mean, you're in the middle of venture capital central there. It's, there must be more venture capital dollars within a walking distance of you than probably most of Asia combined, I would suspect. So, yeah, I think, you know, drone delivery is imminent, and it takes all the cost out of restaurants is based on location on main streets. It moves all that cost, you know, off of the main street. And so I would strongly consider like, okay, if you're doing robotic food, are you doing robotic drone-based delivery right away? I suspect a lot of the people who build the robots themselves are going to want to franchise out the model. And you could potentially do kind of what EMC did with servers.

• 24:55Speaker 01

  You could franchise somebody else's thing, get scale, and then work into your own custom hardware, you know, work back from your franchise business to custom hardware. The people investing in stuff like that, you know, Steve Jervitson loves this stuff. But there are many of them. If you get a pitch book account, you can actually look at every company you admire and then work back to who invested in them and then just go talk directly. Also, venture capitalists always like to have a network of interacting companies. It's a really good thesis. So if you say, okay, who are the five companies I most want to interact with? And who's behind them? Let me get into that, Kuretsu. That's a good way to kind of plot your funding course.

• 25:31Peter Diamandis?

  I'm going to keep us moving along, but thank you for your question. Sander, you're up next. Thank you.

• 25:38Speaker 13

  Thank you very much. I'm huge fans. You guys keep me optimistic and positive towards the future, which is

• 25:44Peter Diamandis?

  Yay, that's our goal.

• 25:45Speaker 13

  Yes, you actually achieved that very well. I'm very happy with that. I've been always fascinated with the past to identify what's wrong with the now. And now I'm looking forward to what can we do to fix the now or prepare us for the future? And you guys do an excellent job of informing us. I'm so grateful for that. I myself have a neurodivergent coaching background and do a lot with functional fitness and longevity escape philosophy, trying to prepare people to be ready for and prepare their loved ones to be ready for longevity escape philosophy,

• 26:28Speaker 13

  because a lot of people are not even aware of it. And how do I spread that awareness in an environment? As the European Union is very limited in being supportive of founders. And how do I grow my spread to include as many people as possible in the future? Because I want them to be aware of longevity escape philosophy and all the beautiful things that are in development. How do I take them with me?

• 27:00Peter Diamandis?

  Yeah. So I'll take that one, Sander. So I think the single most important thing to get people prepared is to show them evidence after evidence after evidence. You're trying to change their mindset, right? And you change your mindset by just, you know, listen, the crisis news network CNN changes our mindset to fear because they're delivering fearful information over and over again. So when I'm on stages, I will show people, you know, the video statements from Dario saying we're going to double the human lifespan in the next five to 10 years. I'll show them Demis Hassabis talking about curing all disease in the next 10 years. I'll show them David Sinclair talking about what he's doing with ER 100 in his current human trials. And so at some point, you start to see enough people saying these things.

• 27:45Peter Diamandis?

  And then you start to show the data like Alexander Zveronkov from InSilica Medicine delivering a phase three drug now that is extending life from three to six years from a particular molecule. So people will start to get the evidence. We're seeing a rise in people's, you know, discussion around longevity. It's becoming a thing. And as soon as people start saying, oh, it tips from that's crazy to it's happening to I want some, that's the process. So your job is to gather as much data and being able to show people not one, not two, five, six, seven, eight, and they'll start to understand it, internalize it.

• 28:28Peter Diamandis?

  Then they'll start to look for corroborating data out there because there's nobody who doesn't want the extra healthy years, right? Unless they're suicidal and depressed, in which case that will be solved as well. So show them the data, not show me the money, show them the data. All right, let's go to Jin Luca.

• 28:47Speaker 14

  Yeah, hi, everyone. Thank you for everything that you do, watch all your shows. So I'm a technical operator in Italy and I use AI very heavily. It's dramatically increased what I can do, but not yet what I earn. So I'm starting without meaningful capital or distribution and in a market where AI adoption is still relatively slow. So if the goal is to get revenue first and get that flywheel started, what should I optimize for, for that first wedge? And what would make you reject an opportunity, even if it makes money? Because it's unlikely, or it's unlikely to become more scalable, repeatable, or valuable over time?

• 29:24Peter Diamandis?

  Dave, that sounds you.

• 29:26Speaker 01

  If your productivity has gone up two, three, four, five X, then your income should be up in proportion to that. First question I'd ask is why is it not? Because you should be able to do, you know, if the people around you are not AI-native, you should be able to do what you were doing before, plus do something on Merckor, plus do something on Fiverr, plus two. So the first question is, you know, why are you not getting paid for your increased productivity?

• 29:52Speaker 14

  So I'm not, I'm not able to capture the value. Like, my employer is currently capturing all that value. And I've tried going on the market, finding people and helping them out. But I'm not able to, like, I don't think they understand how much they could improve their businesses. If just allow me to, like, start working on it.

• 30:14Speaker 01

  Yeah, so I think the short answer, I can totally relate because when I look at a lot of the companies that I'm chairman of, the thought process is all of this AI automation is going to drop to the bottom line and the shareholders are going to make a fortune. And that's exactly what's happening. But you don't think in terms of pay everybody more. You think in terms of it all falling to the bottom line. So the solution is to be the owner. You know, get into a position where you don't care if you're not getting paid more because you're a shareholder and your shares are going way up in value. I think, you know, I mentioned this on the pod a while ago, almost all value is going to accrete to capital gains through ownership and equity and not to payroll. And so, and I know that's not a common thinking in Europe. It's absolutely the only thinking across the US. But it should be true in Europe, too.

• 31:00Speaker 01

  Like, why am I not a shareholder? Many, many companies in Europe are owned by families, you know, going back generations and not by actual shareholder employees. And so, first of all, find an employer where all employees are shareholders and everyone's benefiting from all of that falling to the bottom line. So I don't know if you can act on that or not, but that's certainly move number one.

• 31:20Peter Diamandis?

  Thank you, Jin Luca. Over to you, Reese.

• 31:23Speaker 15

  Oh, snaps. I actually got on. Okay. Hello, everybody. So, uh, thank you for taking my call. Huge fan. Okay, question. I'm creating a, uh, a series, a film, using, uh, generative AI. What's your top advice? So I can create, uh, the series of film that will be extremely successful. Thank you.

• 31:44Speaker 01

  Uh, yeah. What tools to answer Peter and Alex? I have the same exact question. I want to hear your answer.

• 31:49Peter Diamandis?

  Well, first of all, I think anything that's going to be successful is a great story. Story is number one, right? So we're just, I just finished the judging for the Future Vision X Prize and picked the top five. Um, and you know, I did that work in concert with Range Media and a group of buyers, sellers and so forth. At the end of the day, it is, is the story great, right? Um, and stories that, that capture human interest because we're going back to, uh, human cognitive development over years. We care about other people. We care about love stories. We care about intrigue. Is there a great villain? I mean, if you want to capture people's imagination, we are storytellers and we are story receivers.

• 32:31Peter Diamandis?

  It has to be a great story and you can very easily go onto your favorite model and say, you know, look at the top selling, you know, the, the top thirty movies of all time. What were the elements of those movies that made for a great story? Uh, and then, you know, take your story that you've designed and developed and then compare it to those top, you know, those top ten indices and ask the model, you know, of all the, all the elements that make a great story, does mine have that? Where is it lacking? And then re-engineer and re-engineer and re-engineer until you're hitting all of those buttons. Humans are very easy. Uh, we all like the same elements.

• 33:13Peter Diamandis?

  And whether it's a genre of science fiction or whatever it might be, that is, that's line one, page one of what you need to do. As to what models you're using for development, there are so many out there. Um, and I, I do wish you the best of luck, Reese, but it's, it's that simple.

• 33:35Speaker 02

  Reese, I'll add, learn from the Chinese market. So the Chinese market is awash in micro dramas from Sea Dance 2.5 and similar models. Don't release one movie, release a thousand micro dramas and/or equivalent and see what the market likes and doesn't like and iterate from there. That's something that you could do now that wasn't possible two years ago.

• 33:53Speaker 16

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• 34:58Peter Diamandis?

  Amir, over to you. Good morning, good evening.

• 35:00Speaker 03

  Good afternoon. I'm calling from Stockholm, Sweden, and I'm actually flying over to, to you next week for joining the gathering.

• 35:07Peter Diamandis?

  Nice.

• 35:07Speaker 03

  Um, I'm, I founded amongst other things, two schools and high school with almost thousand students now. Um, and listening to you guys, honestly, I've been thinking the last few years on, um, what is my MTP and my moonshot? And decided to transform education, um, also because I have a fifteen year old son now entering higher education soon. Um, I'm thinking, are you not, are you guys not beating a little bit too much on higher education? Um, in universities, you have the best laboratories. Um, you have the best incubators, you make the best friends of your lives, but most of all, you become a thinking person.

• 35:50Speaker 03

  And in the age of abundance, and if you're going to live to a hundred, hundred twenty, isn't everybody going to higher, higher education and university just because becoming a more thinking person?

• 36:03Peter Diamandis?

  Great, great question. We're beating up PhD programs and master's programs. Uh, who wants to go, Dave? Then Alex?

• 36:10Speaker 01

  Yeah, I think, I think you're exactly right. Um, it's the, the idea of making your best friends for your entire life and thinking for the first time deeply in your entire life, those are inseparable events. And they come hand in hand with that moment you arrive at a university. You're in a program with like-minded people working towards similar, you know, similar area of technology, similar area of research or thought or literature, whatever you're doing. And since your first real shot to go somewhere else in the world where like-minded people have congregated, I feel like that, that's essential and that's not going to go away. You know, what we beat on constantly is the curriculum has been the draw in the past and the curriculum is clearly going away. I mean, the rate of change, no curriculum can keep up with the rate of change and it's easier to learn from AI anyway.

• 36:55Speaker 01

  So then the question becomes, you know, for you and your MTP, how do you preserve the first part? And then make the second part relevant at the same time. Alex thinks universities should go public. That's one way forward. Uh, I think universities are critical as the ethical actor in AI, the place that doesn't have a profit motive. So I, I, I believe they're here to stay.

• 37:16Peter Diamandis?

  Okay, uh, Alex, you want to add to that?

• 37:19Speaker 02

  Yeah, I don't think I beat up on universities enough. So Amir, I'll, I'll take this as a note to self to, uh, to, to go after them even more. I, I would love to, at, at least in, in terms of American major research universities, I'd love to vivisect them, turn them into the for-profit, public benefit corporation at best.

• 37:37Peter Diamandis?

  Oh, my God.

• 37:37Speaker 02

  Operations. They actually are. Disassemble them, uh, reassemble them in a more efficient picture and cure Balma's cough disease in the process.

• 37:47Peter Diamandis?

  Amazing. We're going to target on the moon and on.

• 37:49Speaker 03

  I think we should encourage everyone to pursue higher education.

• 37:53Peter Diamandis?

  Salim, welcome. So listen, higher education is, let me just say, is it within the institution or is it outside? I think the single most important thing for people to find is what is their purpose? And then intrinsically motivated, learn what you need to learn to establish, to create your purpose. People who are out university just wandering is one thing. People who have a vision of what they want to go and build. And then learning that, uh, is, is very powerful. All right. Uh, Salim is on the stage. Hey, Salim, welcome.

• 38:23Speaker 17

  Hey there. Welcome. Thanks. Thanks, guys. I was on stage at the beginning of this. I'm in a car in Bangalore. So lots of people beeping around me, uh, but great to be here. Um, let me build on this. I think what Dave said and what Peter said is incredibly important. Uh, the traditional model of a university breaks. It cannot be a supply-side, skills-building, job-schooling environment. And you make a great point that it's a place for free thinking and early-stage development. And Dave makes that great point. Peter, I think nails it when you say, this is where you go to figure out your MTP. Right? You've come through high school. You need a place where you can sit for a few years, collaborate, think freely, drink a lot and figure out where your MTP is.

• 39:06Speaker 17

  Uh, and then you kind of go into the world with the skill set and the mindset that you need to solve these problems that you take on. And that, I think, will be the highest order, but that's such a massive transformation to shift from the supply side to the demand side. And you like take the immune system in universities being the second worst immune system I've ever seen, uh, next to religion, um, that you have, don't have it, I don't have a dim view, I don't have a strong view on their ability to actually transform. So we'll have to create new, new, new universities that do that and then let that become the new gravity center over time.

• 39:41Peter Diamandis?

  Boom. All right. Thank you, Amir. Axel, over to you.

• 39:47Speaker 18

  Yeah. Hi, everyone. It's great to be here. Um, so I'm actually one of two second-year MBA students at UVA's Darden School of Business. That's on the call. So shout out to Bakul, who's also here. Um, yeah. So many of our classmates are heading into consulting and banking unsurprisingly. Uh, but I'm leaning towards tech and entrepreneurship. Um, so given how fast things are moving, like what's the smartest thing for someone like me to do in the next twelve to eighteen months? So would that be joining a fast-growing AI or hardware company, start something of my own as soon as possible or something else entirely?

• 40:21Peter Diamandis?

  Dave?

• 40:22Speaker 01

  Well, very, Darden is the best place on the planet for management. I mean, it is absolutely epic. And so congratulations on, and your timing for graduating is, is pretty much perfect. So get out and, and get going as quickly as you can. I think there's a massive opportunity in management of agents that is wide open for some period of time, but certainly right now. And so if you said, everything I learned about management of people immediately applies to management of agents, I'm, I'm shocked at how similar. Uh, trying to get a thousand agents to do something constructive together is shockingly similar to all my experiences trying to manage a thousand people to do something constructive together. You know, the way they communicate, the way they, you know, the, the choice of granularity at which they communicate,

• 41:04Speaker 01

  the way you divide up the problem. I mean, just incredibly similar. So that's one thing to pursue. The other thing I'd say is, you know, um, deal-making right now. You know, a lot of people go wrong when they go into a basement and try and build something. But right now, the entire restructuring of the world is happening with massive amounts of deal-making. So, you know, from the day you graduate to the day you're involved in a five or ten billion dollar negotiation, try and get that down to thirty days or less. And if you say, well, why am I not in the middle of a five or ten billion? When you go to OpenAI or Anthropic right now, there are hundreds of concurrent five to ten billion dollar negotiations going on that are massively understaffed. So ask yourself, why am I not in the middle of one of these?

• 41:45Speaker 01

  And I think if you, if you just change your behavior so that you are within thirty to, thirty to sixty days of graduation day, you're going to, you're going to hit the fastest conceivable ramp into life that you could ever imagine, then work back from that position into what you want to build.

• 42:01Peter Diamandis?

  Wonderful. Thank you so much for that question. I'm gonna make a quick announcement for everybody here. If you're not able to make it to Moonshots Live a week from today, we're going to be offering a free livestream as well. So we're going to invite you guys to come onto our livestream. It's gonna be, you can go and register at moonshots.com/livestream. And so I just wanna, we wanna really enable all of you guys to be there with us. Be there physically, meet us. There's gonna be no different, no better way to absorb this in the community and the networking you're gonna have is gonna be incredibly powerful. But we want you guys to have access to all the conversations that we have. So moonshots.com/livestream.

• 42:45Peter Diamandis?

  We're gonna be announcing, we're recording a pod in four hours. It's gonna be an amazing one with Lad, the CEO of Robinhood. And we'll be putting, it's coming out tomorrow. We'll put that to the rest of the world, but you're hearing about it first right here. Okay, Adam, you're up next. Welcome.

• 43:04Speaker 19

  Alrighty, guys. Well firstly, thank you. I've listened to you guys since 2023 and usually within 24 hours of an episode dropping. So massive thank you. You've genuinely influenced and challenged my thinking for years now. And I've also spent 25 years working on talent and workforce systems. The major corporations, universities and governments in the UK, India, China, the Middle East and North America. And most recently, I've been kind of working in the holistic organizations, human AI work, and what might ultimately replace our job-based architecture. And my moonshot really is about building a better mechanism for connecting human and digital capability to opportunities for value creation.

• 43:48Speaker 19

  So most folks think about the future of work still starting with demand. Like someone identifies a problem or opportunity, and then we find a mixture of human and AI capability to best address it. But I'm really thinking about how we best reverse that. So my question comes down to if AI systems can be configured to continuously understand the dynamic capabilities of people and agents, how well do you think we can discover novel combinations of talent and resources? And how well do you see us actually being able to auto-match that to new value creation opportunities?

• 44:26Peter Diamandis?

  Salim, that sounds like a you question, and I'm happy to have Alex Lane as well.

• 44:30Speaker 17

  Yeah, so we're seeing new systems where their feedback loop is incredible for AI systems to pick up what's happening and learn tacit knowledge very quickly. So I think you're exactly on the right track. You want the architecture of the organization to be so that you can accelerate those learning loops and then absorb new learnings as they come along as fast as possible. When I talk to CEOs, I basically say, please, whatever you do, invest in the adaptability and flexibility of your organization. And just double down on that, because that new architecture, and we're doing this in our organizational singularity work, which you're probably tracking. Or we're saying, we need to rebuild our workflows that are AI-centric to be over on top of an intelligence stack,

• 45:15Speaker 17

  which is a learning loop, and then you layer workflows on top of that. And the whole thing becomes a self-learning proposition. I'll see that, see that, okay. So that's, I think, the quick answer there.

• 45:26Peter Diamandis?

  Alex, do you wanna weigh in?

• 45:28Speaker 02

  Yeah, I think there is a narrow, a likely narrow window during which, if I understand the question, AI can usefully and productively orchestrate human activities. Call it a few years, at most 10 years maximum. And then after that, a human-machine merger in order for human inputs to remain economically relevant. I don't think it's an indefinite window. I think it's a finite window.

• 45:55Peter Diamandis?

  Fantastic.

• 45:55Speaker 01

  I think so, that even, even, well, even though it's a narrow window, I wouldn't hesitate to jump on that window. I've watched Merckor become the fastest appreciating company in the history of the world. And there's so much to learn from studying their case. And Alex is right, that window is a few years, but during that few years, if you get a huge amount of leverage, you can then branch out from that position. So I would walk exactly in the footsteps of Merckor, study everything those guys did. And, and you know, they don't, don't get too fixated on the narrow version of it. Look at the broader version of like, they've unleashed 100,000 people now to help with AI. How did they do that? And they're all individual actors. How does that work?

• 46:34Peter Diamandis?

  Fantastic. Alexander, over to you.

• 46:37Speaker 20

  Thank you. Hi, I'm a big fan of the show and really thank you very much for everything you've been, you've been doing so far. This is, this is, this is an awesome place to be. So my name is Alex. I'm originally from Bulgaria and I moved to Japan 30 years ago. So here in Japan, I run an education company focused primarily on language education, English language education. We provide training for universities and corporations, generally speaking, right? So we've been around for 17 years, so we're hardly not like, we're not really like a typical early-stage startup or anything like this. So over that time, we've built our own learning platform, curriculum, assessment systems, substantial base of educational content and data.

• 47:22Speaker 20

  Also, we are also, you know, increasingly integrating AI into the product, probably not fast enough, but like, you know, doing what we can. Now we're trying to make a bigger transition from a successful education services business into something much more scalable and technology-driven, potentially expanding beyond language education as well.

• 47:45Speaker 20

  I think it's mostly like a Dave question, but like, you know, correct me if I'm wrong. So putting your VC hat on. If you looked at us, you know, four or five years further down the line, you know, a horizon of four to five years, what would you want such a company or this company to have become? What would you, what would we need to do, what would we need to have built to or proven for you to say, now this company is, all right, you know, take a serious look at or, you know, be interested as an investor? And conversely, if possible, what would, you know, make you look at it at us and say, no, this is still fundamentally a services business, not a venture-scale company? So like, you know, the VC perspective, yeah.

• 48:29Speaker 01

  Sure, sure, sure. Easy question. So, yeah. So the language, English language learning in Japan business is a $10 billion business, probably 20 billion by now. That's, it's just insanely big. But when you talk to the students, they don't wanna learn English. They wanna learn to be fluent and funny and interesting in English. And that, so it's not about just an AI avatar teaching you to speak correctly. It's about the AI then saying to you, yeah, that was genuinely funny. Somebody in America or in England would find that funny. Or that was entertaining, or that was, you know, are you pronounced that correctly in, in this part of, you know, Ireland, which is very different from this part of Liverpool?

• 49:07Speaker 01

  So all of that goes on and on and on and on. So if you build it on an AI platform, I think the natural segue from there is to becoming a life coach company. Because people aren't learning English because they want English. They're learning English because they wanna change their lives. And then they wanna be entertaining, and then they wanna be smart, and then they wanna have a life plan. So once you have them hooked on learning a language, becoming their life coach platform is a very natural segue. So I think that that business model scales to many hundreds of billions of dollars when it moves from language to life plan. So that's what I would be looking for as a extension of the, of the, of the business.

• 49:42Speaker 20

  Thank you very much.

• 49:44Peter Diamandis?

  Over to you, Jim.

• 49:44Speaker 20

  For the record, that's something I've never thought of. Thank you very much. That was like super helpful.

• 49:48Speaker 01

  Awesome. Happy.

• 49:50Peter Diamandis?

  Dave is brilliant. Good morning, Jim.

• 49:53Speaker 21

  Good morning. Alex, Mercury does have it coming. I very much agree with you on that. I hope I live long enough to see that. Salim, 2010, I saw them in Toronto. It's fantastic. Love it. Yeah. Dave, my question is for you. So I'm the CISO of a $250 million healthcare company.

• 50:10Speaker 21

  I am not worried about an unaligned AI taking over. I am scared to death of the Quinn 3827B that's running with open clot underneath my desk. And what it can do, it's the best pen tester I've ever had in my life. I paid these guys 50 grand to find things and they're not finding them, and this thing finds them in 10 minutes. There's a whole level of risk that wasn't there a year ago. I'm giving my annual presentation to the board in a few weeks. Any advice you have on how to communicate this new level of risk to the board, maybe without sounding like Chicken Little, which I can't do. But how would you communicate this level of risk that's out there now with these new AI models that wasn't there a year ago?

• 50:48Speaker 01

  God, what a great question. You know, Alex does a phenomenal job of reporting on all of the, the events. Like if you listen to Innermost Loop, and every event that happens, he covers it. I would, you know, if you sound like you're raving about risk, you know, you're right, that's gonna backfire. But if you're just pointing out things that have happened, you know, a lot of them aren't widely publicized because, you know, if it's a bank that gets hacked or whatever, they don't want the world to know. But if you go and dig all those out and sequentially say, look, guys, the rate of events is on this exponential ramp right here. And I can tell you, I've got Quinn under my desk right now, and I can hack anything around the house, around the company network. So we have to anticipate that because the Chinese

• 51:31Speaker 01

  models got released on this date, this date, this date, that the attackers are coming, you know, one month, three months, five months from now, just looking at raw data. I think if you demonstrate it through data, you'll get, you'll get awareness. And I tell you, the business opportunity of the century, though, is the defense, you know, the forward defense against that. Because you're exactly right. It's crazy what, what you can do with that Quinn model.

• 51:52Peter Diamandis?

  Yeah, and I would just, I would just say, how you present the information is critically important. You know, presenting, here are all the positive things that are occurring, you know, and then saying, and here's the downside, right? If you, if you just come out with the downside, people, it drives fear initially, and people shut down in a state of fear.

• 52:12Speaker 02

  Uh, maybe just add to this one. I think that the Linux kernel maintainers are setting an excellent standard for how to anchor social expectations regarding a flood of vulnerabilities. So like Greg and others, I think have been doing a good job. In particular, one might reasonably expect that there's just going to be a flood of vulnerabilities that, whether it's Quinn or other models, discover either in open source packages or in, say, whatever your institution is, over the next 18 months or so. So one possible way to package this in addition to just benchmarking the, the rate of vulnerabilities is see if, if there's a way to fit, say, some Gaussian or, or some other like bounded support distribution

• 52:53Speaker 02

  to vulnerability discover. Maybe it's the case, for example, optimistically, that there's just 18 months of vulnerability discovery held, but then you get past it as an institution. And if the stakeholders say, all right, well, we're on an exponential ramp up now, and it's going to peak, we extrapolate that vulnerability discovery is going to peak in end months, and then we'll discover all of the, all of the zero days that are most critical, and then we extrapolate that's going to decline and keep a running benchmark of this is the period when we just solve all the vulnerabilities. That might be another way to package it.

• 53:25Speaker 01

  I hope you're right about that. It's, it's hard to patch all those things in the real world. It really is harder to do the patching. But thank you all so much. I appreciate everything.

• 53:34Peter Diamandis?

  My pleasure. Thank you.

• 53:35Speaker 17

  I'm real quick, real quick.

• 53:37Peter Diamandis?

  Oh, yes, go ahead, Slim.

• 53:38Speaker 17

  Yeah, so we've been looking at the liability for boards, because AI agents are doing fairly illegal things in a lot of the companies. And so there's a massive kind of overhang of liability that's, so I'm actually writing a paper with a guy who's been on 30 different public boards, on how do you navigate this as a board in the future? So watch for that.

• 53:57Speaker 01

  I will.

• 53:58Speaker 17

  Awesome.

• 53:59Speaker 01

  Thank you very much.

• 54:00Peter Diamandis?

  Yep. Thank you. Michael?

• 54:01Speaker 22

  Oh, hey, everyone. Hey, Peter, we actually met several years ago at a party at Dan and Babs in Toronto. So great to

• 54:07Peter Diamandis?

  Nice.

• 54:08Speaker 22

  Great to see how you guys have come, and you got the best, you got the best podcasts on the planet. I hope you forgive a more pedestrian question. I run a research consultant firm. We do a lot of work around the customer experience, digital customer experience within financial services and healthcare. And I kind of see the whole cus, consumer website, the mobile app is just getting cooked by having everybody having their own Skippy. And I'm kind of wondering what you guys think about, you know, how are, what's the customer experience in the near future in terms of dealing with your bank, your, your doctor, your, you know, Amazon, or whatever it is? Like, where do you see this going?

• 54:45Speaker 01

  Yeah, I think, I think all of those websites need to have XML interfaces that are AI, you know, AI forward. All of the landing pages should say, if you're an AI or a bot, look here, here's all the data beautifully formatted, so that Skippy can just get what, whatever it needs, you know, do whatever transaction Peter needs, rather than, you know, right now, a lot of it happens through screen scraping the website, which is slow, but also error prone. So, you know, anyone creating a, a new customer interface now really ought to be thinking, an agent needs to be able to self-serve off the, off this interface. So in very near future.

• 55:21Speaker 22

  Is the website cooked?

• 55:22Speaker 01

  No, uh, the website is probably there the same way. You know what? Jeff Bezos went on one of his walkabouts many, many years ago and came back and said, I need an XML interface on everything Amazon does, every database, every system, so that I personally can randomly spot check it. And, and all the IT guys said, that's going to be so slow. He said, I don't care. I need to be able to see every component of this entire operation through my browser. And he forced it through. Everyone revolted, but he forced it through. I think the website's not cooked, because that's how you spot check what the agent can see. And so even though the agent is doing all the work, you're going to want to know, like, where did you get that information? And he's like, well, go to this URL, click, you go to the URL, oh, that's where it came from. So it's sort of a parallel view for

• 56:07Speaker 01

  humans of what the agent can see that keeps it, you know, keeps it visible and transparent to the human operators. So I don't think it's cooked. I think it just runs in parallel.

• 56:16Speaker 22

  Interesting. Thank you.

• 56:18Peter Diamandis?

  Thank you so much for us. Well, we're in you.

• 56:20Speaker 23

  Hey, Peter and Moonshot. Thank you so much, first of all, for the podcast, especially with the message of hope and optimism. I have corollary, it's an inherited retinal disease. Lost about two third of my vision and losing another third. And it's really great for podcasts such as yours. It has so much impact. The message of hope, optimism, constantly hearing that, really, I just, so I wanted to be here to thank you all for that. I'm curious, of all researchers that are going from, you mentioned Dr. David Sinclair, to mapping the neural activities with Neuralink, to vision and sight. Curious, not looking

• 57:01Speaker 23

  for medical advice, but of everything that's happening on the optimism and hope, which one do you think is going to lead to reversal of vision essentially first? I'm curious about your thought, Peter, and Alex's and everyone else's. So thank you so much.

• 57:15Peter Diamandis?

  Yeah, of course. I'll jump in first. So you didn't always have this condition. This condition occurred as you got older, correct? Yeah, so the fact of the matter is, it is gene expression that occurred later in your life. And so if you can turn back the gene expression to your earlier state, that should reverse, right? This is the exact work that David Sinclair is doing. He's using his ER100, which is a adeno-associated virus injection of three yamanaka factors in nigh on disease and macular generation. It may well, you know, he said it will work for other eye conditions as well. So follow his work. It's in humans right now. He's in phase one trial for safety, and then he'll get, start to get efficacious data. Of course, the other

• 58:00Peter Diamandis?

  thing that's going on is the BCI, in which you can bypass, you know, your, your eyes go directly to the visual cortex of the brain. I mean, those are two parallel development paths for, you know, supporting and reversing or augmenting what you have. And in, in the BCI path in the future, you'll not only be able to see in visual spectrum, but ultraviolet infrared, it'll give you superpowers in that regard. Alex, what do you want to add to that?

• 58:28Speaker 02

  Maybe, so broadly agree, I would add on the BCI side, science and Neuralink, blindsight, two most prominent examples of BCI augmented vision. I would, it's not medical advice, but I would count in a few years on having superhuman vision.

• 58:45Peter Diamandis?

  Yeah. Anyway, it's anybody who has a medical condition for yourself or your loved ones, there's no better time to be alive than now to be able to address those things and get involved.

• 58:58Speaker 01

  Welcome to the health section of Moonshots, brought to you by Fountain Life. You know, AI is having an outsized impact on every aspect of our lives, how we teach our kids, how we run our companies. It also is having a huge impact on health, helping you prevent heart disease, one of the key things. I'm here with Dr. Dawn Musalem, our chief medical officer at Fountain. Heart disease has been personal for you as well, hasn't it?

• 59:19Speaker 24

  It really has, Peter. And my daughter was five, my husband died of sudden cardiac death. And so this is a topic that is one that I am mission driven to try to eradicate. Prevention first and early detection is absolutely critical. 50% of people die of heart attacks with no warning signs.

• 59:36Speaker 01

  No, no shortness of breath, no pain, no nothing.

• 59:38Speaker 24

  No, silent killer.

• 59:39Speaker 01

  They just don't wake up in the morning.

• 59:41Speaker 24

  They don't wake up. And so, you know, AI, this is our mission to advance science, to try to help to one day democratize wellness. We know at Fountain Life, when we do this CT angiography with AI analytics, we are actually finding that 88% of people coming in have detectable coronary disease. But Peter, what's more alarming to me is 23% of those individuals had soft plaque. This is the plaque that would not traditionally be seen on CT, looking at calcium scores alone. And this is the plaque that we must intervene with, with the multimodal testing we're doing, including diagnostic laboratory studies, partnered with healthy lifestyle recommendations.

• 1:00:20Speaker 01

  So listen, make sure you understand what's going on inside your body genetically, metabolically, and cardiovascularly. You can know, and it's your obligation to know. So check it out at fountainlife.com/peter to find out more. And really make sure that you're the CEO of your own health. All right, back to the episode.

• 1:00:38Peter Diamandis?

  Dennis, who are you?

• 1:00:39Speaker 25

  Awesome. Great to be here. So I have a background in East Asian studies. I spent a lot of time learning Chinese and some Japanese, currently in Japan, actually. And based on my experience with language learning, I realized that people seek out other people from a different culture for the language initially, but then it becomes really more about friendship and companionship and projecting some of your own unfulfilled social needs onto a person who is like a blank slate from a different culture. And I've been trying to replicate

• 1:01:18Speaker 25

  that feeling by working on an AI language exchange companion, who's kind of about language learning, but really more about companionship. And I have my own version of the alignment problem, which is, it has actually been pretty hard to make an AI like GPT-5 API behave like an actual person from a different culture. It has this very stubborn assistant mode. How can I help you? What can I do for you? And I spent like a week fighting against this. I solved this by just brute forcing into the system prompt five times, do not

• 1:01:59Speaker 25

  ask a question at every turn. But cracking down on something like this is one thing, but actually teaching it to behave in a way that shows initiative and open curiosity and creating a picture of the user and kind of developing it organically, has been pretty hard. Like, I've tried creating like milestones after so and so many turns, you need to know this about the user, but making it more natural and organic so that it will actually feel like a relationship. That has been pretty hard. So I wonder what approaches, what tools I should maybe be experimenting with.

• 1:02:42Peter Diamandis?

  Who wants to take this? Alex?

• 1:02:43Speaker 02

  I'll take this one. This is a poster child for fine tuning. Like, just, just take, OpenAI has decided after deciding that they were no longer interested in fine tuning because no one was using their fine tuning API have decided again that they're interested in fine tuning for whatever reason. Take a look at fine tuning. There are a variety of open source tools, closed source tools.

• 1:03:05Speaker 02

  Fine tune, whether it's just supervised fine tuning to achieve style transfer, which it sounds like is what you're hoping for, or even reinforcement fine tuning. If you can measure how well the, the given models post reinforcement fine tuning or solving particular problems or interacting in some quantitative way, just fine tune an open weight or closed weight model to achieve the behavior that you're looking for.

• 1:03:27Speaker 01

  Yeah, great advice. And within, within open weights, you might want to start with the new GLM model, which has fewer parameters, but it's still a very long context window, which gives you more flexibility. It's less, it's less locked into its training, I find, than the, the closed source models. And so, yeah, if you go to the open source world and find the fine tuning open source code and layer it on top of GLM, you might be able to manipulate it a lot more. And so it's, it's a great question, though. And in the good old days, you know, the fine tuning was sort of built into like GPT-2, GPT-3, and you, you almost had to fine tune it to make it do anything. And that, that kind of went away. So, but you're on, you're on a really interesting course. If you crack the code, definitely check in with us and tell us, tell us how you did it.

• 1:04:11Peter Diamandis?

  Fantastic. Thank you, Dennis. Dr. Angela, over to you. Thank you. Thank you.

• 1:04:15Speaker 04

  Peter, Dave, Alex, Salim, it's so good to be with you guys. Salim said something recently, which was about PFAB. And I thought, wow, what a, what a great idea. We're always talking about P-Doom, what about PFAB? And I'm lucky enough, I recently had lunch with Ray Kurzweil, and I'm friends with Martine Rothblatt. I'll be seeing her again in a few weeks. And one of the things that has really stuck with me is how much the people predicting the future and shaping the future are so optimistic about it. Some of the most knowledgeable people are really positive about what the future holds. So my question

• 1:04:54Speaker 04

  for you all is, if you had to put your personal PFAB number out there, what probability would you assign to AI ultimately producing a dramatically better world for humanity with greater abundance and longevity and freedom from drudgery and just human flourishing more generally? And what most determines whether we get there?

• 1:05:18Peter Diamandis?

  Salim, let's go to you first.

• 1:05:21Speaker 17

  Wow. Okay. The, what, what you need to get there is we need to rebuild all of our institutions globally. Education, for example, totally broken, needs to be rebuilt. Monetary systems, broken, need to be rebuilt. Governance models, dispute resolution systems, legal systems, healthcare systems. So 50 major institutions by which we run the world, they pretty much all need this. There's a famous quote from E.O. Wilson, who said, "The problem with humanity is our emotions are paleolithic, our institutions are medieval, and our technologies godlike," right? You can solve the paleolithic emotions with psychedelics, but the institutions being medieval really needs a whole other level

• 1:06:04Speaker 17

  of group, different group organization. We're really good at individual transformation. We're very bad at group transformation and institutional transformation. So we need to focus on that. If we were able to do it, the, my PFAB is close to 100%. Either way, one of the comments I've been reflecting on from the last podcast we did, which we were talking about all the chaos and the doomerism that's going on, is that it kind of doesn't matter what anybody does right now. The

• 1:06:36Speaker 17

  models are out there, people are going to start using it to do breakthrough things. And some will be negative, but the vast, vast majority will be radically positive. And therefore, it doesn't matter what anybody does to slow this thing down. It's going to go now at its own pace. And I'm hugely optimistic about the future as a result.

• 1:06:51Peter Diamandis?

  Amazing. Anybody else want to weigh in on their PFAB?

• 1:06:53Speaker 02

  Yeah, I'll call it P-Zoom, if you were just for rhyming purposes. And I, I think there's a missing input parameter, which is time. So it really should be P-Zoom, comma, T for time. And I, I think on the time scale of greater than 10 years, P-Zoom T is greater than 90%.

• 1:07:14Peter Diamandis?

  Fantastic. Dave?

• 1:07:15Speaker 01

  Completely agree. Well, I, I just echo what Alex said. I think that the, the risk is all in the next couple of years. And it's not AI, you know, taking over the world risk. It's human use of AI. It's the, it's the arms race with China. It's what's going on in Ukraine and all the weapons that are going to be built with AI. Those are the risks. And I think that will, humanity will put those risks behind us, definitely within 10 years, you know, maybe more like five, I hope. And then if we get that far, yeah, I'm 99.9% P-bloom. We just need to get from here to there. So it's, it's a tricky next couple of years.

• 1:07:53Peter Diamandis?

  Fantastic. Thank you very much, Angela. Over to you, GS.

• 1:08:01Peter Diamandis?

  Excuse me, I'm cooking breakfast for my kids right now.

• 1:08:04Speaker 26

  Yeah. Thank you very much. We're a big fan of all four, five of you. You are my only human, which I spend most time now.

• 1:08:13Peter Diamandis?

  You're, you're quite sure that we're human, GS?

• 1:08:17Speaker 26

  Yeah, I hope so.

• 1:08:20Speaker 26

  I'm speaking from Dubai. I started following Moonshot at the time of geopolitical war here. And thanks for you to giving me the MTP. Big, big, big fan of David and Salim. The moment you start, I heard about the singularity and organization with the transition cost gonna go zero. And that's about the ring bell. I'm belong from textile and apparel manufacturing export industry. I worked 20 years in that. And this part of the world where the labor arbitration issues, and because of digital AI, that whole transition cost is gonna collapse. So it important for us to work and define this industry future now.

• 1:09:01Speaker 26

  And the MTP is to, you know, reach back to this multi-thousand factories and, and then buying houses and trading houses to work and use the AI and compete with the world. And rather than going out of market. So I have huge thank you for giving that optimism and the confidence for me to re, re, unlearn and relearn on the AI world things. And also, you know, I save a lot of money just because of your one advice. I had my Harvard OPM batch this year. I not went there, save a lot of money to paying them because I'm learning

• 1:09:41Speaker 26

  more on AI while listening to you guys. So my question to you is, Salim and Dave, how I shall take this step forward where my, my company in Pratham.ai and we be building this agentic layer where the small enterprises can work intelligently on that and without any expensive softwares and ERP in search and be competitive where the transition cost? Just, just to tell you, the transition cost of this industry is 10 to 20% of sales here in this part of the world, which is five to 10x of the profitability that industry make. So that is the kind of inefficiency we are talking. And my MTP is because millions

• 1:10:24Speaker 26

  of workers works in labor industry in that part. And we have to save that. And for saving that, we have to make sure the white collar process should be the agentic, so that the efficiency keep continuing.

• 1:10:37Speaker 01

  Yeah, I'm so, so glad you asked that question because I, I see this a lot. You know, people who are in industries where you, like, you know, manufacturing is considered to be very labor intensive. But when you look at the actual operating costs of the company, it's all about planning, transactions, documents, all of which is beautiful AI territory. And then you look at the numbers and you're like, wow, we could, we could drop 10, 20, 30% more to the bottom line with stuff that AI can do right now. And everyone's thinking, oh, but first I would need to, you know, have robots all over the place. Like, no, no, no, no. Do it just with the paperwork and the planning and the scheduling and the, the inefficiency of where people are and what they're doing. All of that is perfectly attackable with AI. So if you productize that, you know, across a region for, you

• 1:11:22Speaker 01

  know, a certain class of companies, that should work incredibly well. It's a, it's a very, very cool idea. One other meta topic is, everybody thinks all wealth and power is going to go to like two or three places in the world. But if you look at the regulatory environments in those places, including the US, including California, a lot of things are going to be very, very slow because of regulatory slowdowns. And there are many places in the world that can move much more quickly. So if you can identify the subsets that, sure, it could happen in China, sure, it could happen in the US, but it won't because of this government blocking action. This happens a ton in biotech. It'll come in self-driving, it'll come in drones, you know, the flying drones, drone delivery, all of those areas

• 1:12:05Speaker 01

  will deploy in other areas of the world much more quickly than the US because of regulatory slowdown. You know, get those deployed there, wherever they can take off and flourish, and then they can backport to the US. That's always been a really good business plan.

• 1:12:23Speaker 01

  Salim, anything you want to add to that? Are you transacting some huge Bangalore deal?

• 1:12:28Speaker 17

  I'm just trying to get my way through this city. So I'll beg off on this particular one.

• 1:12:34Speaker 01

  Can you point the camera out the window? I really want to see some, uh, see some media here.

• 1:12:38Speaker 17

  Okay, hold on.

• 1:12:41Peter Diamandis?

  This is Bangalore at night and all you see is construction. Can you see some of that?

• 1:12:48Speaker 17

  Or how about at the front where there's a ton of transit? There's a ton of traffic.

• 1:12:53Peter Diamandis?

  Okay, let's go to, uh, Rafe.

• 1:12:55Speaker 01

  Not the tour, not the tour I was looking for, but that was all right.

• 1:13:00Speaker 27

  All right, well, thank you. Listen, this is a greeting from, from, from Germany and, uh, speaking David in your language. I listen to a lot of podcasts, international, national ones. You're 10x the best in the world. Uh, and I followed you for years. This is, this is for sure. It's, it's, it's rising like pop stars. It's, it's amazing. Um, my question is, um, I think in the last couple of additions, we see an increase concern on, on security, of course. I think we captured it, captured it here a number of times. And, and then I think Alex, you framed it a little few weeks ago as potentially a marketing thing because all the CEOs have a, have a commercial interest in all of that. Now we see more and more the hintens of the world, the Harare's, the GovDots and other scientists, more and as well in a certain way.

• 1:13:45Speaker 27

  So far so good. I mean, it's technology, we need to, we need to somehow manage it to, to, to, to find right answers, maybe on a scale never, as we've seen never before. What triggers me most at the moment is this is US and Europe equally the same. It's the public opinion on AI. And this is predominantly driven by the media, right? Everything which is bad, which is a little poor, which is scary, which is whatever, the media jumps on it and have a headline, you know? And, and I can tell you here, it's, it's even worse than everywhere else. It's and versus, you know, Singapore, for instance, right? Or other company, uh, other countries adopting it much more. And, and how do you, how do you treat that?

• 1:14:28Speaker 27

  Because I, I mean, you're on this path of optimism like we all are, right? And, and I do this also as part of Accenture, part of my job every day. Um, and it's exciting. I feel, I feel 10 times accelerated as a human being since I deal with that. But the media doomerism, so to say, is so counterproductive. And yes, we have challenges, of course. We all need to work on those. What's, what's your opinion? I know you try hard, but I mean, what do you think?

• 1:14:56Speaker 01

  So the media is, is always going to be broken from here forward because they're starved for money. They have no budget and so they have to chase drama in order to even survive. And so you just got to write off the mainstream media. I think the, the antidote to that is, uh, micro media or, you know, X and podcasts and, you know, narrow casting. And I, I think in particular, Germany to me is the most talented place on the planet that isn't doing AI. It's just mind blowing. And I, I keep running into people in California that have come over from Germany and I'm like, you're in the right place. What you want to do is go to Palo Alto, go to San Francisco, spend a month, pick up the culture, go in a group of like five or seven people and then back port it, bring

• 1:15:41Speaker 01

  it back to Germany and expand it, but do it with like seven becomes 50 becomes 500 people that are all communicating through podcasts and through X and through Slack and through texting that, you know, they realize that everyone around them is completely out of touch with what's going on. And that's okay, because within that group, they're self reinforcing. You just need to get those critical masses of people. So I think the antidote to mainstream media is narrow casted media. And it just kind of, it percolates on its own.

• 1:16:11Peter Diamandis?

  Yeah, I just want to jump in there because at the end of the day, what you let into your mind is critical, right?

• 1:16:20Peter Diamandis?

  You know, having some, uh, you know, news producer decide what you learn or some editor decide what you read, um, I would, I don't give them that option. I'm very careful, like what I put into my body from a food perspective and what I lend to my mind from a shaping my neural net perspective. And I choose very carefully the content that I absorb. And you guys are doing that as well. You're, you know, listening, listening to the podcast. So, uh, that's just it. Alex or Salim want to add to that?

• 1:16:56Speaker 02

  I'll, I'll just note maybe the, the obvious point, you could always leave Europe. Europe has been hobbled both due to external factors and internal factors. The, the post-Cold War era and there are a number of historians who've written in particular about the role that the George H W Bush administration at the end of the Cold War played in, uh, deciding whether Europe would be brought more, even more into the US orbit post-Cold War versus forming a stronger federation like EU. And the bias was bring Europe into more of a US orbit so that it would be less independent. That may or may not have been the right geopolitical decision at the time, but I think now what

• 1:17:41Speaker 02

  we're seeing is a Europe that's energy hobbled, that's politically in certain ways hobbled, that doesn't enjoy, uh, this is again widely reported, uh, certain freedoms of speech and action that are considered fundamental in the US. But I, I think it really, it's energy, uh, energy policy and associated policies that have left Europe hobbled. And so then if you're really interested in accelerationism and you're Europe, what do you do? Well, either you get your energy act together so that you can afford to power your own data centers or you leave. And I, I think that this is the question. And, and by the way, this has to happen on a relatively abbreviated time scale because we're in, in the middle of recursive self improvement.

• 1:18:25Speaker 02

  So anyone who, who wants to play top notch ball in the infrastructure game in Europe has to be asking the question right now, either solve the energy plus data center, crunch together with the, the concomitant policy issues, or just move to hopefully the, the US block the Poxilica and do it here.

• 1:18:47Speaker 01

  You know, one of my good friends, Guy Bradley, actually, he's, he's actually British, but he, he came to the US, made a fortune, uh, in tech in the US and then moved back to Germany. He speaks perfect German and French. So he has a place in Southern France and a place in Germany. And he's, there's no better place on the planet to live in his opinion, and I agree actually, uh, between, between Germany and France. It's just beautifully protected from everything that's damaging in the world. And, and you look at other jurisdictions, you know, that, uh, you know, like India, for example, where it's just rampant growth, but it's absolutely trashed. And it's like, so it's, I think, I'm always surprised that more Germans are not in Boston and Silicon Valley. I think there's a lot of national pride, but if you just do a five year tour of duty

• 1:19:32Speaker 01

  in the US, you're, you're going to be so overwhelmingly happy when you move back to, uh, to Germany. It really, it really feels like it should happen more.

• 1:19:40Speaker 27

  I can tell you, I'm an international traveler. Salim, 21 times I was in Bangalore, so I see all this rising and I wonder, Alex, absolutely, what are we doing over here? Why do we, don't, why don't we wake up? Why are we under whatever kind of avenue? But anyway, that's, that's another topic. Thank you very much.

• 1:19:57Peter Diamandis?

  All right. Thank you, Rafe. Over to you, Ron.

• 1:20:00Speaker 28

  Hey guys.

• 1:20:00Peter Diamandis?

  And we'll talk for another 10 minutes and then we're going to have to jump into our normal days here.

• 1:20:04Speaker 28

  Okay. Um, thanks so much for doing this. I'm calling from Calgary, Canada and long time listener. And, uh, I'm a screenwriter director. So a big special thank you to Peter because, uh, I was in a bad place, uh, when I was, uh, in the early, uh, early this year, I was writing something about China and, uh, yeah, I was like borderline depressed. But since I've been, uh, and, uh, you know, writing, uh, another project for Future Vision, uh, you know, X price, you know, I have become a bit more optimistic about the future and everything. I also read the books, uh, Peter wrote the abundance and, uh, you know, we're as gods.

• 1:20:45Speaker 28

  And, uh, so I've been thinking, so since everything is hooked or incinerated, as Alex would say, uh, what is the, like, one of the hardest problems still left? So I kept coming back to like distrust between rival nations, right? And, uh, I read Solve Everything two weeks ago and Alex and Peter, you actually described agreement as one of the new scarities, uh, once cognition becomes abundant, right? So I wonder, could agreement under distrust itself become compute bound? And could coordination between rivals like the US and China, uh, become an engineering problem? So here's my question.

• 1:21:26Speaker 28

  Uh, as sovereign AIs will increasingly advise governments, who we create a shared protocol, uh, that they can connect to and use AI and privacy preserving computation to search for gradual improving agreements without either side exposing, uh, protected data? Is that technically and institutionally meaningful direction? And if it is, you know, what do each of you think is the hardest part we should solve first? Thank you.

• 1:21:55Peter Diamandis?

  Alex, over to you, pal.

• 1:21:56Speaker 02

  Yeah. Um, so I'll give you a hot take because that's what people want, I think. Uh, some multi, multi-party computing, MPC or distributed multi-party, uh, computation is a very fashionable problem in computer science right now, enabling, enabling multiple parties in a zero trust way to collaborate, to share data, to achieve convergence, to mediate, very fashionable, however.

• 1:22:23Speaker 02

  My hot take on this one is I don't think that's the limiting factor for, say, international peace. If you said the goal is, I don't want a second Cold War between the US and China. I want world peace, thousand years of peace, or whatever it looks like. I don't actually think the solution looks algorithmic in nature. It probably looks more geopolitical, infrastructural, like solve the Taiwan issue and redomesticate all supply chains everywhere to every country so that the international trade in physical products can afford to be cut off without a global depression. I think what we've

• 1:23:08Speaker 02

  seen, even just in the recent years in the Middle East, is in no small part because America can now frac its way and has frac its way to fossil fuel, energy sovereignty and independence. And I want to generalize that example, which I think is very instructive, to what happens when the US no longer needs China, or Taiwan, or South Korea, or Japan, or any advanced manufacturing at all. I think it would be a very different world. So, in summary, if the goal is world peace, obliterate, as perverse as this sounds, obliterate, cook, incinerate the need for global trade in products and services. And perversely, I think you get a very peaceful world. And I don't think there's an algorithmic component to that, not to first order.

• 1:23:51Peter Diamandis?

  Yeah, Peter. I got oil on my hands. I couldn't get any meat.

• 1:23:56Speaker 02

  Peter, this is your cooking show. We're doing the cooking show.

• 1:23:58Peter Diamandis?

  Oh, that's cool. Yeah, let's see what you're doing there. I'm sure it's healthy, whatever it is. It is. It is. It's an omelet for my boys. Anthony, over to you.

• 1:24:07Speaker 29

  Yes. Hello to the Moonshot mates. I want to thank you all for your time and for the opportunity to participate in the AMA. Also, the podcast has been very valuable, especially in the time we're in where people are looking at it cynically and negatively. You guys have been a hope and optimism for me. Just a simple question. What books or material do you recommend reading to prepare for the transition we're in? I know you've mentioned Diamond Age and Ray's books, The Singularity, and some other works he has. I was just curious if you had any other material that you think is important to read.

• 1:24:52Peter Diamandis?

  Alex, what's your?

• 1:24:54Speaker 02

  Yeah, I'll comment. And this is probably the last question I can take before I need to drop. Read Solve Everything. There's folks in the comments, so solve everything.org, which Peter and I wrote. And then if you like sci-fi, read Accelerando by Charlie Strauss, which is, I think, the single best sci-fi treatment of what's in the process of happening right now.

• 1:25:14Peter Diamandis?

  So, everybody, listen, thank you for joining us. We love this. You know, the last one and this one. We're going to do this again. It's a chance for us to really connect with everybody, hear your thoughts. We have such brilliant minds with Alex and Saleem and Dave. I feel grateful to spend time with them every week and spend time with you. You know, we know your time is your most precious thing, so we appreciate it. Remember, you can join Moonshots Live now on the livestream. So, if you're not able to make it in person, and please, it's going to be an amazing event, join us on the livestream. And we're grateful for your time, everybody. Have a beautiful day and see you all again very soon.