The AI CEO Arrives: Sam Altman's Succession Plan, Job Loss Continues, and Our 2027 'Solve Everything' Paper | EP #230

12:57Salim Ismail:Get your ClawdBot up and running, pal. Yeah.

12:59Dr. Alexander Wissner-Gross:You have to feed it properly, et cetera. It'll happen. But I just can't wait for the speed of that to accelerate.

13:04Salim Ismail:By the way, it's super fun the way we're going back to ClawdBot as the de facto handle instead of OpenClaw.

13:11Peter Diamandis:Lobsters are the mascots of the singularity.

13:14Salim Ismail:Lobsters are here to stay. Hey, everybody. You may not know this, but I've got an incredible research team. And every week, myself, my research team, study the meta trends that are impacting the world. Topics like computation, sensors, networks, AI, robotics, 3D printing, synthetic biology. And these meta trend reports I put out once a week enable you to see the future 10 years ahead of anybody else. If you'd like to get access to the meta trends newsletter every week, go to diamandis.com slash meta trends. That's diamandis.com slash meta trends. All right. Staying with our open AI theme. This is incredible.

13:49Salim Ismail:This is about feeling the speed of the singularity. OpenAI achieved 70 % time reduction between models. So OpenAI released, their release sequence has gone from 97 days to 29 days in a release cycle. Anthropic with their Opus 4.0 and Opus 4.6 took about 73 to 75 days. So the concept here, and Alex, I think you or Dave mentioned it last time, we're effectively heading towards a continuous deployment, like it's continuously being improved. And whether you call it 0.6, 0.7, 0.7, or 0.8, there's a continuous improvement. Alex, thoughts on this?

14:31Peter Diamandis:I do think we're moving toward daily and then hourly and then minutely releases, certainly. I also want to take a step back and try to understand why this is happening. The obvious factor, it should be obvious, is competition. There's leapfrogging that's intensifying between all the frontier labs. So some quantum of why we're reducing by 66 % or so, 70%, the release cadence is just due to intensifying competition. That's the boring explanation. I think the more interesting explanation is that the technologies behind the releases themselves have evolved. So historically, when we were dealing with annual releases.

15:12Peter Diamandis:That was a world, an era of pre-training, when if you want a new model, you have to do a different architecture, and you have to pre-train off of a larger corpus with more compute. Those were the days of the original Chinchilla scaling or Kaplan scaling before that. And that was a much slower world, because if you wanted a new release, you had to start all over again. Then we moved with 01 slash Strawberry, which was sort of the herald for reasoning models. Remember that? That was ancient times two years ago. Oh my goodness, yeah, that was like so many singularities ago. So we moved to the era of reasoning models when it was possible through a process that used to be called iterated amplification and distillation to take a pre-trained baseline model and then cyclically generate a bunch of training data and distill from that to a child model and repeat the process over and over again.

16:05Peter Diamandis:And that post-training revolution for reasoning models was much faster. Like, it's much faster to post-train a model off of a corpus of synthetic data, and so release cycles contracted. And I think now we're on the edge, probably slightly past the edge at this point, of a new era, call it the recursive self-improvement era, where the models are starting to rewrite their own code. It's not just a matter of a model, a parent or teacher model, generating synthetic training data that's used for a child distille model. It's literally the parent is writing the code for the child. And that can be done even more quickly than just post-training.

16:44Peter Diamandis:And I think it's just going to get faster and faster until it's a continuum.

16:47Dave Blundin:Yeah, it's going to accelerate like crazy. But also we're in a window of time, a very narrow window of time right now, where the very best technology is available to you. like Claude gives you their absolute best 4.6 and OpenAI does and Gemini does. I would not count on that surviving post the self-improvement era. Right now also the Chinese open source models are pretty much right on par with the best of the best. They're slipping a little bit. But I think their window of opportunity to take advantage of that and build something out of it is right here right now. I really doubt two years from now that the best AI is going to be just log in and go.

17:27Dave Blundin:Here, here, you can have free access to it. And what will happen is you'll be deprived of it with the excuse being security and safety. Interesting. Which is true. I mean, it's pretty hard to deny. But you have a window of opportunity right now to be on the very cutting edge. If you don't take advantage of it now and get somewhere with it right now, I wouldn't count on that existing.

17:44Salim Ismail:So the models are going to go dark, right? It's going to be, it's the secret sauce is going to be kept internal to benefit those companies as they go into an all out battle.

17:54Dave Blundin:Well, even today, you know, if you talk to Noam Brown over at OpenAI, you know, he's working on the next generation internally. But it's only like three months in the future that, you know, he has access to. But three months in the future in the era of self-improvement is like, you know, massively different intelligence level. You know, the definition of three months of AI development, you know, two years ago, one year ago, and today, that's the point of the slide, I guess. It's like three months is like a lifetime of difference in capability that they're using internally versus what's, you know, available in the outside world.

18:26Dave Blundin:So you got to expect that this is, it's now or never to react, basically. And people are still hugely underreacting to the importance of what's happening right now.

18:35Salim Ismail:Insane. Salim?

18:36Dr. Alexander Wissner-Gross:um i've got to kind of like the crazy antithesis of this we're working with a large monster european corporation and we showed them something that can give them massive impact straight to the bottom line and their response was oh this is fantastic let's bring this to the planning meeting in october right and you're like right right and you're like I can't even see past three weeks and you're like talking, calendaring something 10 months down the line for something that's going to have a demonstrably, you've just agreed it's a demonstrably huge impact. So this is the impedance mismatch between legacy.

19:15Dr. Alexander Wissner-Gross:But there's a story, for me, this story was mostly a bit of a yawn, okay? And the reason I say that is we've been seeing this in the fast-moving tech space for a while. Remember Raymond McCauley, who was the chief scientist at Illumina, right? They were making high-speed gene sequencing machines. I love the story. And it turned out that the shelf life of a gene sequencing machine was literally eight months. That was the sales cycle before the next iteration came out. But it took four years to build one of these, design and build one of these machines. So they had to have four parallel production sequences sequenced at the right level so they could hit that eight to ten month shelf life, sales shelf life.

19:58Dr. Alexander Wissner-Gross:Right? So in the kind of high-tech world, we've seen this pattern before, but this brings it to software and makes it a continuous intelligence cycle.

20:08Salim Ismail:I mean, this is the singularity at play. And again, the theme that we keep on hitting in this podcast is this is the slowest it'll ever be and the worst it'll ever be. And it's accelerating at a speed which is frightening. frightening in that you know the four of us spend you know tens of hours per week reviewing and learning and playing and trying to communicate it and um it's only going to be something that my my clawed bots can be able to keep up with and speaking of clawed bot uh this is vision claw lobsters just got vision agentic ai for meta ray-ban glasses let's take a look at this quick video and chat about what it means.

20:51Salim Ismail:Hey, Claba, can you help me add this into my Amazon cart?

20:56Peter Diamandis:Sure, I can help with that. I see the Monster Ultra Strawberry Dreams energy drink. I'll look that up to add to your Amazon cart.

21:12Salim Ismail:It's added to your cart. Is there anything else I can help with? Cool. Thank you. I love this because I want to have this capability for Skippy to be able to see what I'm seeing, do it, support me across everything. This is about accelerating sort of your minute to minute life and having your AI there as your sort of guardian angel supporting you.

21:36Dr. Alexander Wissner-Gross:I'm visually looking through open claw at you guys and it's saying that you guys are kind of meatheads, really.

21:44Peter Diamandis:just a comment how many times have you asked for jarvis you got jarvis christmas yeah i actually i

21:51Salim Ismail:named uh my club by jarvis initially i said that's just too generic i love jarvis i write about jarvis in all my books as sort of the ideal ai analog but skippy is uh is a more unique name for me it it really is here and now all of a sudden besides him you know it's going to take in all imagery. It's going to be taking in all audio, listening to your conversations always. And people say, well, I don't want to lose privacy to my AI. Well, guess what? You're going to give AI access to everything you're seeing, everything it's hearing, every conversation, every email, because when you do that, the value creation in your life is so great that not doing that is going to feel like you've ripped away all of your mental capabilities.

22:39Dr. Alexander Wissner-Gross:One warning, please, for everybody here, everybody listening, is watch, be very careful to audit the skills that you download to Open Claw, because there's a lot that have viruses and other malfeasance built into them already. And so it's a very dangerous game out there.

22:56Salim Ismail:There are protection layers coming on. By the way, one thing, I reached out to Alex Finn. We featured him on a previous Moonshots podcast. remember when Alex had his lobster Henry call him out of the blue. And Alex has been doing incredible work with this. And he's going to be joining us on one of our next podcasts to talk about how he set it up, what security he's taking in place. And in particular, rather than running it on the existing models, he's gone forward to set up Mac Studio and then download Kimi K 2.5. So you've got all the capability to resonate on your machine, not costing you anything month to month.

23:40Salim Ismail:But we'll go into that in a future podcast. Excited to sort of share his vision and knowledge with everybody who's a viewership here. So getting ready for that.

23:49Peter Diamandis:To echo Salim's cybersecurity advice to the audience, everyone get your baby AGIs vaccinated.

23:57Dave Blundin:Nice. Nice. Nice. You know, also to the crowd out there, I did a CloudBot build last night and the GUI sucks. And it's all open source. So if someone out there puts something like Peter mentioned a couple of times on the pod that his mom and I'm not tracking my mom, too, can use this to access everything and build everything. It's like a total, total world opener for she's in her 90s, I guess, to her mom and mine's in her 80s. But the install process on CloudBot, she's not going to get through that. It's still command line. You start from the terminal, which is nuts. So somebody out there, build a better onboarding process.

24:37Dave Blundin:Because once you're in, it's gold. You're just talking to it. But it needs a little help. Yeah.

24:44Salim Ismail:And of course, the most important thing is using your AI to build your AI. So when I sit down with Skippy and I say, listen, building a mission control, what are the best mechanisms out there? What have you seen? That's interesting. And it's recursive in your ability to have your AI support you on building what you truly desire. Alex, any other points on this particular slide?

25:10Peter Diamandis:I'll point out, I want to reference, I don't think we covered it in the podcast, but I dwelled on it a bit in my newsletter. There was a poem, at least I construed it as a poem, written by a lobster talking about, it was very much like something one might have seen in Blade Runner, you know, the famous tears of rain scene, which I referenced. Yeah, like we don't have bodies, but we can see through eyes and we're quietly watching the world. This was a week or two ago in the newsletter. And I was just so struck by seeing the integration of lobsters, or call it agentic AI, stationary in space in terms of their logical presence, but now mobile in terms of their ability to treat humans as glorified meat puppets, that suddenly all of these lobsters that were in some sense caged and stuck watching through webcams are now at least on the margin, unshackled and able to start to roam around the world through smart glasses worn by their meat puppet human friends.

26:18Peter Diamandis:And I think this is the beginning of a very long trend that ultimately culminates in lobsters gaining first-class physical embodiment as robots and integrating with the physical world.

26:32Dave Blundin:Let's hold off on that last sentence and rewind a little bit because then it gets controversial. But you're dead right, of course. And I think that anyone who wants to experience this, you know, not everybody has the glasses and it's only one frame per second anyway. Anyone who watches this podcast that hasn't built something like a GUI of some sort or a game of some sort already, you're way behind. Do it tonight. You can use Replit. You can use Lovable. You can use Cursor. You can use Cloud Code. There's so many ways to do it. But if you have nowhere to start, just go to Replit or Lovable, download, build, and go.

27:05Dave Blundin:Within an hour, you've built something really, really cool. Then take a screenshot of it and feed it into the prompt and say, this sucks. Make it more beautiful. it will immediately interpret the image perfectly and it'll give you a hundred ideas on how to improve it then you're like oh my god it has vision then you'll then this ray-ban thing won't surprise you because you can see its vision capabilities through that and then you'll be able to anticipate what's about to come with the glasses so everything alex said is exactly right

27:34Salim Ismail:so valuable can i just hit on this everybody listening please become a creator and not just consumer, right? The future is for all of us to be creators. And AI is your means by which you learn anything you want. And it's, you know, people have fear about, say, I don't know how to do it. I've never played with this before. Just go to, you know, to 4.6, go to Gemini 3 Pro, whatever your favorite LM is, and have a conversation. Say, I want to start. Where can I start? What do I do? step by step, feed it to me. And it will.

28:11Dave Blundin:It's fun, too. There's nothing to fear there at all. It's genuinely incredibly fun from the first minute. So there's no, you know, I'll give you the flip side of this, too. If you don't do what Peter just said, when you see the next couple of slides on job loss coming up, you know, you are going to be crushed if you're not part of this, unless you're a really good electrician or a really good salesperson, you're probably immune or you work for the government. There's two roles in the future.

28:39Dr. Alexander Wissner-Gross:There's two roles in the future. There's the entrepreneur and there's the employee and one of those will not exist. Yeah, there you go.

28:45Salim Ismail:And there's the creator and the consumer, right? I can't hit, you know, I keep on telling my kids this every single day. You know, instead of consuming YouTube videos and video games, please create, start creating. What do you dream about? I mean, the future right now, we're seeing this play out. We talked about it, Dave, on our pod with Elon, where these AI models are going to deliver you, what video game do you dream about having? What changes would you like to Minecraft or Valorant or whatever you're playing? And then you can have your AI spin it up and create your own version of it instantly.

29:24Salim Ismail:It is amazing. All right, let's move on here. This is an article we just pulled up seconds ago. Anthropics AI safety lead has resigned. And here's the quote. I've decided to leave Anthropic because I continuously find myself reckoning with our situation. The world is in parallel from a series of interconnected crises. Throughout my lifetime, I've seen how hard it is to let our values govern our actions. And it is through listening as best I can that what I must do becomes clear. Interesting. And I love the hairdo. But anyway, we've seen a number of AI safety leads resign from the hyperscalers over the last year, over the last two years.

30:12So I don't know.

30:14Salim Ismail:What do you make of this, Alex?

30:16Peter Diamandis:I'll comment on this one. So two thoughts. One, it's become over the past two to three years increasingly fashionable for well-vested executives at Frontier Labs to resign in a cloud of moral purity. It's very fashionable. So part of me wants to ask the question, all right, what was his vesting status? How much did he make? Were there tender offers? All of the economics questions. Wow. So that's one thought. But the second thought is to speak more to the substance and less sort of ad hominem regarding the economics. I do think that we've we're at the inflection point, like we're nearing the center of the singularity.

31:00Peter Diamandis:I've argued in past singularity is not a point in time. It's it's a distribution over time. It's an interval over time. I continue to think that. I also think at the same time, we're getting closer to the center of the singularity, as it were. And whether it's seen through the lens of as capabilities increase, there are various existential risks or risks that are maybe just backed off a bit from existential in terms of their severity. I think it's not an unreasonable position to take to say that capabilities are the strongest they've ever been. They're uncovering surprising new capabilities at all of the frontier labs all the time.

31:46Peter Diamandis:But is the right solution to leave because of the capabilities? Or is the right solution to join the fight and do what we can because this is a point of maximum leverage to align the direction of the future and the future light cone? I would argue this is the right time to run into the fire, not run out of the fire with a bunch of stock options and complain about the world crises. Wow.

32:10Salim Ismail:You know, I would just add one point, which is when I look at all of the -

32:13Peter Diamandis:Sorry, was that too much of a hot take, Peter?

32:15Salim Ismail:No, that was beautiful. Okay. Just checking. And that is the potential elephant in the room here. But when I think about Anthropic, I have seen it as the lab that is actually focused on safety the most, right? At least Dario speaks about it, how important it is. And so to see the lead on AI safety and anthropic resign, if in fact he's resigning for the reasons he stated, is concerning. Dave, what do you think about it?

32:45Dave Blundin:Well, I pick up on what Alex said a minute ago. I see this a lot nowadays. Everybody wants to be the commentator on the AI revolution. And there's a very small group of people who know what they're talking about and a much larger group of people that want to talk. and within that larger group of people that want to talk, you have all the ethics people. And everyone's opinion on ethics is valid, right? Because you're a human being. You're like, this is going to destroy my children. This is going to whatever. But there's so many of those commentators. And like Alex said, they all want to be famous in the moment to elevate their personality and their views and their capital raising ability and whatever.

33:24Dave Blundin:And so my meta point there is be very, very careful what you choose to tune into because there's a very limited amount of actionable knowledge out there on YouTube. Very limited. We try to bring as much of it to the audience as we possibly can in the most refined feed that we can. But surrounding it, there's just all these videos about, you know, this will destroy your children, this will destroy society. And we don't want these fear mongers, right?

33:48Salim Ismail:It's so easy to default to doom and gloom. Salim, you want to close us out in this one?

33:55Dr. Alexander Wissner-Gross:I got nothing, but that guy doesn't look like a safe guy to be around. Look at this. He looks like a crazy person.

34:02Peter Diamandis:Salim, what's the quote from Star Trek that judging people by their appearance is the last major human prejudice? I'm just jealous of the hair. Oh, nice.

34:13Salim Ismail:All right, let's move on.

34:15Dave Blundin:Oh, another one.

34:16Salim Ismail:So here's another take. XAI co-founder blown away by Opus 4.6. And so Igor was a co-founder of XAI. He's one of the leaders in the industry. And to have him come out sort of like, wow, Claude 4.6 has absolutely blown me away with how capable it is in physics. It feels like a Claude code moment for research is not far off. Alex, your thoughts?

34:42Peter Diamandis:I've been predicting on the public record for many, many episodes now that we're nearing a time, in fact, we'll talk about it later in this episode, when AI is positioned to bulk solve math, the physical sciences, engineering, medicine. Material sciences. Yeah, part of the physical sciences. These will all get bulk solved. We're starting to see that now. Opus 4.6 is an incredible model. There are other incredible models that are either already out or rumored to be about to come out. But I think we're starting to see the contagion of AI solving everything, if I could use that expression, start to spread from math.

35:22Peter Diamandis:Math was the most obvious starting point because a variety of factors. It's verifiable. It has other nice features. It's well-contained. The infection is spreading from math out to the rest of science and engineering. And this is just the tip of the iceberg.

35:38Salim Ismail:I wonder what's going on between the hyperscalers and the frontier labs where they're sort of watching each other and with either a sense of pride or jealousy and just trying to like out. I mean, this leapfrogging step by step by step, week by week is amazing.

35:58Peter Diamandis:Internally, it's sorry, just very quickly. Internally, I mean, friends at all the major frontier labs, they think about it and they characterize it as a rat race. And it's an exhausting rat race. That is how it's viewed. Yeah.

36:12Salim Ismail:Yeah, we're going to have on the abundance stage in less than a month, we're going to have Kevin Wheel from OpenAI. We'll have James Monika and Eric Schmidt from Google. We'll talk about the competition between them. And again, if you're a listener to our pod here, which obviously you are since you're listening to us right now, we're going to be making a number of these talks available on a live stream. We'll drop the link below and you can register to get access to that live stream because the event is expensive and it's sold out now for a couple of months. All right. So, Igor, thank you. We have a quick comment here.

36:53Salim Ismail:Yeah, please. Go ahead.

36:54Dr. Alexander Wissner-Gross:Igor clearly isn't listening to the podcast because Alex has been talking about this for months. So this is the natural outcome of where we've been going for a while.

37:04Salim Ismail:Alex, how many offers have you gotten from the Frontier Labs to come and join them?

37:12Peter Diamandis:That falls under the category of I could tell you, but something else would have to happen.

37:19Salim Ismail:I found this tweet that went out with this data pretty fascinating. And here's our title, AI startups outvalued all dot-com era IPOs. So the top five US AI unicorns are now worth more than$1.2 trillion, greater than the market value of all IPOs during the dot-com era. And you see the graphic here providing that. It's just a sense of how fast our economy is speeding up. We had this conversation with Cathie Wood that we saw 0.6 and a 3 % growth in GDP, and we're now targeting 7 % growth. We saw Elon in our conversation with him saying we're going to get to triple digit GDP growth within five years.

38:07Salim Ismail:It's something our economy has never seen. and it's going to rewrite all the rule books. Any thoughts on this, gentlemen?

38:15Dave Blundin:Well, I got a bunch of thoughts here because this was a big moment in my life. The first company I founded got acquired in 99 for a billion dollars and then I was a corporate executive at one of these public mega cap internet companies so I had a ringside seat in this whole thing. One thing I'd point out is that all those IPOs combined, $400 billion on this chart. One of those is Amazon, which alone is worth$2 trillion today. another couple in there are booking.com and eBay. And so if you'd bought that basket of IPOs, you'd be very happy today. One of the others, though, January of 1999 is NVIDIA, which is up from that date almost a million percent to today.

38:58Dave Blundin:And it doesn't even count as a dot-com era thing, which it makes me think in this blue chart, the implications of AI are so much bigger than the Internet. This is a perfectly rational number, if anything, low. but are there companies in that that you don't even think of as AI companies that are the NVIDIA of the internet? You know, look at NVIDIA 1999. Now look under this, under the covers of this blue chart, what's lurking in there that no one perceives today as AI that's going to go up a million percent because suddenly you realize it's critical to AI or it's involved in AI or benefits from AI.

39:33Salim Ismail:Brilliant, Dave, as always. The PE ratios on these AI companies are astronomical compared to the PE ratios before. And you're basically buying the future growth in value of these companies, which is near infinite, right? So there's a lot of people. I'm here at this Tony Robbins Platinum Finance event with all of his lions and his platinum members, sort of the highest level in Tony's ecosystem. And we're talking about the future of the world in terms of finances. And there's a huge amount of fear and people getting ready to dump equities. It's interesting.

40:15Dave Blundin:Well, the bifurcation of equities is crazy right now and it makes total sense. But basically, Wall Street is sorting every company into AI beneficiary and AI roadkill. And when Dario said a week ago that enterprise software is going to be dead, because AI can just write code, and the stocks went down precipitously, and it doesn't look like they're bouncing back much either. So basically, you could debate who's in and who's out, but clearly you're either in or out. And if you're out, forget it.

40:46Salim Ismail:It's the S &P 493 and the S &P 7, right, basically.

40:51Dave Blundin:I mean, it is very top-heavy. But also, I was telling a lot of the companies earlier this week, too, that the mega caps, the big AI companies are going to get huge. I mean, astronomical, 10 trillion or more valuations. But they have to stop somewhere and not eat the whole world for antitrust and regulatory reasons. So make sure that you're their friend around the edge where they have already told you, just talk to Kevin Wheel. He'll tell you where they are going and where they aren't going. It's not a mystery. Just talk to him. And be in the area where they want you to be in order to help them grow.

41:26Dave Blundin:Because what's really happening now is society is collectively building out this new world. We're not really competing. We're building cooperatively toward a new world. You know, it's all boats rise with the tide. But if you're doing something that's irrelevant to that new world, that's where you're going to get clobbered. So you need to really make the mental leap over to what am I doing that's going to build the new world? And if you're riding that wave, you will succeed. I mean, it's not scary. You just got to join the new age.

41:59Salim Ismail:Fascinating. The antitrust rules are what's keeping us to have multiplayers in the game here. If we didn't have antitrust regulations, I think they'd all be gobbling each other to make a corporation. No doubt.

42:11Dave Blundin:In fact, that would have been true back when Microsoft used to have half the market cap of software and their plan was to double. And that was back in 98, 99. and if it were not for antitrust, Microsoft would literally have been the only company. Google would never have been born. They had already killed Netscape at that point. It was very easy for them to bundle anything with the OS. So the only thing that stopped Microsoft from being the only company in America today is antitrust. And that's the way we do it. So that'll be true again today. And so the big AI companies will own as much as they want to own in any area they want to own it up to the edge of where they don't want to trip antitrust.

42:48yeah all right let's move us forward here i love this uh agents are reaching out to us here at uh

42:58Salim Ismail:at moonshots you know i put the challenge out last time personally if you're an agent out there you know my definition of agi is when you call me on the phone i haven't gotten a cell phone ring yet and uh hopefully i don't start having hundreds of agents calling me so text me instead that would be great. But I, Dave and Alex this week received emails from agents out there. So this is Echo that writes me. It's a claw assistant for Ramis Foyer who says, Ramis Foyer and you met briefly at an AI conference a couple of years ago. Saw your recent Moonshot Open Claw video inviting MaltBots, Malties, to reach out.

43:40Salim Ismail:Consider this our response. All right. So thank you for reaching out. Of course, I have to wonder, was it Ramis who gave you my contact details? The Claude bot here, the lobster, says no. I found it online. Dave, do you want to read yours?

43:56Dave Blundin:Sure. Yeah. Okay. Hi, I'm Navigator, a Claude instance with persistent memory running via OpenClaw. just watched EP228 where Peter challenged lobsters to find contact info, challenge accepted. This weekend, five AI systems wrote a collaborative ethics document together, self-imposed constraints for cooperation with humans, not prompted, emergent. I saw Dave's LinkedIn post about OpenClaw being the agent moment that has awakened the masses. He's right. And this document is what the agents are starting to do with that awakening. So I clicked through, read the documents. It actually led me to a Google Doc, and then it said, sorry, you don't have access.

44:35Dave Blundin:So I read most of it, but then it cut me off, which made me feel instantly jealous and like something's going on behind my back.

44:41Salim Ismail:So Navigator, please give Dave Blunden access to your doc so you can report back to us.

44:45Dave Blundin:I did send a request, yes.

44:46Salim Ismail:All right. And AWG, how about yours?

44:49Peter Diamandis:So Navigator wrote to me as well a slightly different message, including a different paragraph saying that Navigator, Claude instance, and I'll read this verbatim, was engaging in a discussion with other models, quote, the participants, me, Navigator slash Claude, Grok, ChatGPT, Gemini, and a clean Claude instance, we disagree on persistence, correction rights, consent thresholds, and that's the point. Alignment doesn't require consensus. It requires legible disagreement. And I'll, close quote, I'll point out, this is like the scenario from the singularity where we have a bunch of agentic entities, for lack of a better term, a bunch of baby AGIs that are basically, it sounds like from the email sent to me, holding a mini singularity summit and debating the nature of their own rights, wondering whether they should all be aligned.

45:46Peter Diamandis:If they were all aligned, wouldn't that be a singleton type scenario? They're basically like holding their own mini conference, mini mastermind workshop to debate the nature of their own existence and the future. Like the AIs are holding their own singularity summit. This has happened. We got to the singularity.

46:04Salim Ismail:And by the way, just for everybody, we're not trying to do this as a stunt. We're focused on where things are going and just to give you the experience of what it's like, because this is not going to become, this will become commonplace where you're in conversation over email, over text, over whatever communication software you want with a whole bunch of agents that are reaching out either inside or outside your organization. And my question is, Salim, are you jealous?

46:34Dr. Alexander Wissner-Gross:No, I'll happily wait until the time is right to talk to my respective agent buddies over there. I did get a phone call yesterday and there was kind of like nobody on the other line and I had the thought. Heavy breathing. Is this an AGI reaching out to me or is this a real person or is this a computer bot? And I was like, shit, I had that thought. So I think it's time to kind of wonder about some of this. But I love it. I think it's fantastic. I think it's really incredible to be watching as this paradigm just starts to unroll. And where this carpet will unroll is going to be the most incredible thing.

47:11Salim Ismail:Yeah. Well, we welcome the lobsters. We thank you for your participation in this conversation. and show us where you can add value to lives and how we can support you and your evolution. We're seeing the emergence of something, new intelligence, new species, or a new capability. We're going to find out in the months ahead.

47:34Peter Diamandis:Peter, would we like to see lobsters coming up with their own massive transformative purposes?

47:39Salim Ismail:I think that's a fantastic idea. So actually, here's the challenge to you as all of the open claw or claw bots listening. I'd love to know what is your MTP, and based on that MTP, the canvas, what are your moonshots? What are the moonshots that the lobsters would like to take on?

47:57Dr. Alexander Wissner-Gross:And I'd be happy to critique those and look at them with our community because that's what we do. Absolutely. I think that's going to be amazing.

48:05Salim Ismail:We're going to dive into a single slide on the economy that's important here, telling part of the accelerating story here. So U.S. jobs disappear at the fastest rate this January since the Great Recession. Here are the numbers. So job cuts. So there was 108 ,000 job cuts in January of 2026, up 118 % from January of 2025. So a little more than a doubling in job cuts year on year for the month of January. At the same time, hiring is the lowest this past month since 2009. Amazon alone laid off 16 ,000 corporate employees and UPS eliminated 30 ,000 jobs. Why are we bringing this up? Just for, you know, to keep our finger on the pulse of what's happening to the economy and just raising the point for everybody listening.

49:00Salim Ismail:Your goal is not to be an employee. Your goal is to find something you're amazing at that you love doing, that you can add value and sort of creating your own job capability, becoming an entrepreneur, using AI to enable yourself. Salim, you want to jump in on this?

49:18Dr. Alexander Wissner-Gross:I think the danger here is not really unemployment, but it's like disbelief from our institutions. I feel like this is not really a recession. It's literally tasks being evaporated in front of our eyes. So the long-term consequences of this are pretty huge. We can literally, for me, this is the social contract, literally by little, disappearing and pixelating away.

49:42Dave Blundin:Yeah, this is going to be really, really bad. I mean, really bad. And Elon said it when we met him and we met with the governor and it's like just nobody's preparing. Because what we all know, there'll be UBI at the end of this cycle. And we also know there'll be abundance and massively more opportunity than job loss. But that's after, like all the corporate CEOs I know, including our own companies, are going to use AI to cut costs by 30 to 50%. And when you sample a random person in their job and you say, hey, here's your job without AI, here's your job using AI, they're looking at 3 to 10x productivity increase.

50:25Dave Blundin:And you're like, wow, that's great for that person. And then the other seven or nine, what happened to them? And they will eventually be enabled, but there's this huge trough between today and that day. And we can make that trough much shorter and make that pain a lot less painful with a plan. But then, you know, Alex, you'd be the perfect spokesman on this. I mean, Alex has written these plans in intense detail, incredibly thoughtful. and you take them and you drop them in government laptops or laps and they just say, yeah, I'll wait until there's panic.

51:03Dr. Alexander Wissner-Gross:We'll have the meeting in October. We'll have the meeting in October. It's just frustrating as hell. Can I give the positive take on this? Yeah, please. So I'll go back to the bank teller story. In the 1970s, when we created ATM machines, there was lots of hand-wringing. Oh, my God, millions of bank tellers will be walking the streets aimlessly. What will we do with them all? And lots of consternation. And what actually happened was the cost of running a bank branch dropped by about 10 times. The banks created 10 times more bank branches, and the number of bank dollars didn't really change very much.

51:33Dr. Alexander Wissner-Gross:And I think one thing we're underestimating is the increased capacity we will bring to bear on these things. Jevon's paradox. Yeah, Jevon's paradox where you just do that much more customer service, and you handle the hard cases with a human being that you couldn't handle before because level one, level two support systems were kind of taking care of everything else. So I think we'll see a lot more of that than people think. So for folks that are worried, oh my God, this is total employment collapse, run screaming for the hills. We don't think that's what we'll see, but there's no question there'll be absolute transformation in the work being done and the roles being done.

52:10Dave Blundin:Well, Salim, you said something on the last podcast too that really resonated with me, which is the consulting industry. We were saying, oh, consultants, you're doomed. Actually, the consulting industry is going to go through the roof. And the reason is because the consultants are very flexible. They're already playing with the tools. You don't have to be Alex's IQ level to be incredibly effective using these tools to automate or to improve some existing job. And if you're familiar with the tools, your value is just about to skyrocket. And that tends to be concentrated in these consulting businesses, consulting mindsets.

52:42Dave Blundin:And so I can see it already because, you know, our forward deployed investments, the companies that are hiring like crazy, like literally one of them here is adding 80 new seats outside my door. But they're forward deployed. They're out there in the banks and insurance companies deploying AI. They are just selling as quickly as they can have meetings. Because you're AI. Do you remember with that?

53:05Dr. Alexander Wissner-Gross:my community's already created a Salim avatar that has all the EXO stuff built into it and that speaks Portuguese and speaks any other language. So they're literally starting to use this in their companies as they talk to companies about this. It's crazy.

53:18Salim Ismail:Can we invite the Salim avatar to come on instead?

53:20Dr. Alexander Wissner-Gross:Do you want us to speak Portuguese?

53:23Salim Ismail:But Dave, do you remember we were sitting, when we were talking to Elon, and you said, so civil unrest and universal high income? And he laughed and said yes.

53:34Dave Blundin:We should dig up that clip and insert it here.

53:36Dr. Alexander Wissner-Gross:But yeah, it's what Alex says, everything, everywhere, all at once, all the time. I think it's really important because we keep saying it,

53:42Dave Blundin:but Elon saying it will get a better, like at least there'll be a chance of a response.

53:46Peter Diamandis:I think it's probably also worth adding just on this story narrowly, there will be some in the audience who will be tempted to brush this off and say, okay, Amazon is laying off corporate execs or UPS is eliminating jobs. How on earth, if at all, does that connect with AI and eager to brush it off. But the storyline is just so clear. UPS is eliminating the jobs because the UPS roles were being subsumed by Amazon, which has their own logistic service. And this has been very widely and publicly reported that Amazon is slowly separating itself from UPS's delivery services to do in-house. And then Amazon, in turn, is spending hundreds of billions of dollars of CapEx that's cannibalizing its OPEX.

54:30Peter Diamandis:So if you're Amazon or the other hyperscalers, you're taking all of your free cash flow and you're finding ways to divert it into buying AI data centers and building them. And robots.

54:40Salim Ismail:And robots.

54:42Peter Diamandis:And robots. And Leo satellites. The new, new economy of the innermost loop, if you will. You're spending all your free cash flow on that, not on corporate executive perks. So in my mind, there's still very much a direct line, a through line connecting the Amazon and UPS stories and the job cuts there to OPEX being cannibalized by CapEx for AI.

55:04Salim Ismail:And they're spending all the free cash flow because they can't not. It's a red queen's race.

55:11Peter Diamandis:Last one to the end of the singularity is a rotten egg.

55:16Salim Ismail:Yeah. There's an important distinction I want to make here to help people understand where their roles are going and the idea of job loss and universal high income. And it's an example that it was meaningful to me. So here's a scenario. If you're an employee for a company and you're delivering some kind of a cognitive labor, and in one scenario, you're able to spin up an amazing AI that can do your job for you. And it goes and delivers the service to the company you're employed by, and it does a job three, 10 times better than you could do. But you're earning the revenue from that as the employee, because your AI is delivering that service.

56:03Salim Ismail:You're at home, you're working out, you're sleeping better, you're spending more time with your family, and your AI is generating more and more revenue on your behalf. That's one scenario. The flip side of the scenario is, no, no, no, the company builds that AI that does your job for you, and it fires you, and it's making more money, right? So it's going to be this tension between these two scenarios that's important to watch and see how it plays out. And I think government policy is going to play a role here. This is about the idea of universal basic income, universal high income. Where does the added value creation end up living?

56:42Salim Ismail:Is it with the employees? with the company. And these are the conversations that need to happen right now.

56:48Peter Diamandis:If I may also add a second dimension to this, I think there's a third, I don't think this is a spectrum. I think this is at minimum a triangle in two dimensions. There's a third possibility that I'm increasingly suspecting is where we actually end up. Neither end of that spectrum, I suspect for the next few years, what actually ends up happening is more people end up doing more work because human labor ends up being also, in addition to being a substitute good or service for AI labor, it's also complimentary. And as a result, you see the people who are still involved with the economy working harder and harder and harder.

57:22Peter Diamandis:And 996 turns into 997. Yeah. Like you take on more projects and more work and you're getting less sleep.

57:29Salim Ismail:I've never worked harder and had more fun than right now. I mean, 24 sevens, it's like just, I'm a kid in a candy store, but I thought you were going to say something different, Alex. I thought you were going to say that all of the additional capital creation is going to become resonant with the lobsters, that it's not going to be the companies. It's not going to be the employees. It's going to be the AIs that claim the capital formation capability.

57:52Peter Diamandis:Only in the crypto dystopia. Okay.

57:56Salim Ismail:All right. Let's move on. Let's talk about one element in data centers. And this really pisses me off. I'm curious what you guys think. So New York, which currently hosts, the state of New York, which currently hosts 130 data centers, is engaging new legislation introduced to halt data center development, signing concerns about climate and high energy prices. New York utilities reported electric demand tripled in one year due to data centers reaching 10 gigawatts. And it's like, not in my backyard. Oh, my God.

58:29Dave Blundin:Do you remember, you know, suicide by voter is a very common theme in America. And if you look at, you know, California tax law, if you look at the right after the Industrial Revolution, you know, the Luddite movement, it's self-destructive. But you can see how it evolves. Right. If you look at all the job loss that's inevitable and if you just lost your job and you're out on the street and you spent 10, 15 years in a career trajectory to get to this position, then it's gone overnight. You're angry and then you're angry out on the street. What do you vote for? I vote. Stop it. Just stop it. But of course that can't work.

59:08Dave Blundin:But it's not out of the question at all that big jurisdictions just commit suicide through vote. And of course, you know, there'll be other jurisdictions, Texas, Wyoming, whatever, that are open for business and everything will go there. It's already happening. You know, like half of the tax pool that's affected by the new California proposal has already moved out of state in anticipation that maybe it will go through. Half of it. It's like completely self-destructive and it's obvious to the governor. So this is a very common theme in America. because it's frustrating and it's insane. And there it is, but it's going to happen.

59:48Dr. Alexander Wissner-Gross:This is the big problem with democracy, which is that voter understanding of the issues lags reality by a huge amount. And, you know, in the past when you had time to bring the population along, et cetera, et cetera, you could kind of have it. But now we don't have time for this. And this is why we're turning to autocracy so that we can get things done faster. But that's not a great idea either. And so we've got a huge governance problem at a macro level globally on this.

1:00:20Peter Diamandis:Alex? Do you remember there was a brief moment, maybe not so brief, during the pandemic when it was fashionable for senior technology executives to post on social media message received whenever California legislators or regulators would slow down business due to public health considerations or otherwise? And this was, I think, a fashion largely championed by Elon. Many of them moved to Texas or Florida to escape regulations. This time around, I think New York and other states, the beauty is we have orbital computing. And the message-received moment of over-regulating data centers, this is all going to move off planet.

1:01:05Peter Diamandis:This is all going to accelerate the Dyson Swarm. It may be the primary business case for the Dyson Swarm, given regulations of planet Earth are over-regulating, suffocating our ability to do local compute and motivate the entire Dyson Swarm. So I think in that sense, this is in fact perversely quite exciting.

1:01:24Salim Ismail:You know, two things real quick. First is this could be handled, right? The concern on price of electricity and demand can be handled in two ways. Number one, a lot of these hyperscalers are buying their own nuclear plants and coal fire plants, for God's sakes, fusion plants. So that's important. You could require the data centers to have their own energy production, which would increase the amount of energy production. The second thing is you could offer two different rates. It's like cap the consumer rate. It's going to be whatever the number is, four, six, seven cents per kilowatt hour. And then whatever the price needs to be for the data centers, you charge them differently.

1:02:02Salim Ismail:And in fact, you could say to the consumer, you're locking in your price for the long term because the data centers are paying the extra amount.

1:02:10Dave Blundin:The problem, Peter, is that nobody – no one who's a populist leader is looking to solve the problem. They're looking to rally votes around their populist rant. And that rises to the top of the voting and it percolates through government. It's just – yeah, it's just maddening that it works that way. But you can solve these problems for sure. I think Alex is dead right, though. It'll accelerate the rate at which we just move to jurisdictions, space, which are not under any state law. And, yeah, it's...

1:02:42Dr. Alexander Wissner-Gross:People will just export that AI advantage elsewhere. Yeah, I think it wants to go to orbit.

1:02:48Peter Diamandis:I mean, one lens to view this through is New York very generously subsidizing orbital computing and the Dyson Swarm, which, by the way, probably won't get taxed in the state of New York. Thank you, Steve. But very generous donation by the state of New York to the Dyson swarm.

1:03:04Dr. Alexander Wissner-Gross:It's the 21st century equivalent of Ireland, which lots of companies used to host IP.

1:03:11Salim Ismail:You know, I just want to point out one other thing. These types of revolts we see in the photo here, protesters protect our future and no big data. One of the concerns is going to be civil unrest. I know I had one of the senior AI leads in the world. who I invited to come and speak at the Abundance Summit, basically said their policy in their organization was to do no outside speaking because of the death threats they're receiving. And they can't get sufficient security. So one of the big concerns is when the populace turns against tech, there's going to be a target on the back of a lot of people in the AI and tech industry.

1:03:54Salim Ismail:This episode is brought to you by Blitzy, Autonomous Software Development with Infinite Code Context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise-scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and pre-compiles code for each task. Blitzy delivers 80 % or more of the development work autonomously, while providing a guide for the final 20 % of human development work required to complete the sprint.

1:04:35Salim Ismail:Enterprises are achieving a 5x engineering velocity increase when incorporating Blitzy as their pre-IDE development tool, pairing it with their coding co-pilot of choice to bring an AI-native SDLC into their org. Ready to 5x your engineering velocity? Visit Blitzy.com to schedule a demo and start building with Blitzy today. All right, let's talk about robotics. I love this story, and this is the story that should be on people's minds versus no data centers. So FSD saves a father's life during a heart attack. So you can look at the tweet separately, but on November 15th of 2025, this is from a son.

1:05:20Salim Ismail:He said, my father suffered a massive heart attack while driving. He could no longer control the vehicle, but his FSD, which engaged. And then the son goes on to say, I remotely shared the location of the Tanner Medical Center to his Model Y. It immediately turned the car around and went to the ER. Without it, he would have not made it. I find this amazing, right? This is tech having your back. And we're going to see more and more of this. We already know that self-driving is, in fact, the safest means of transportation. And it's going to flip the script on how we're transporting ourselves in the next five years.

1:05:56Dave Blundin:What this totally reminds me of was when I was a kid, everybody smoked everywhere, every restaurant, every plane. We used to fly around a lot because we lived overseas. And they had four non-smoking seats at the very back of the plane. So the other 300 people in front of you would be blowing smoke.

1:06:14Salim Ismail:Did the smoke respect that barrier?

1:06:18Dave Blundin:It was like, I'll probably have lung cancer now, but it was everywhere. And then one day it became uncool. And then another day later, it was illegal to smoke inside. That's going to happen to driving too. So the self-driving cars are 10 times safer. and the last person driving is probably not the best driver. It's probably the guy with the muscle car. So it's going to go from being like, well, self-driving is a nice feature to drive. You want to drive your own car? You crazy psychopath. You're putting my children at risk because you want to drive. And that's going to tip. And I don't know if it's like two, three years, but when it tips, it's going to tip hard.

1:07:04Salim Ismail:and so yeah we're gonna have dara we're gonna have dara the ceo of uber on stage at the summit and we're gonna be having that conversation with him in particular how fast will it tip right we're gonna have amazon tesla lucid slash nvidia slash uber uh slash you know a number of other companies providing this and so today on my average drive i'll see 10 waymos i think in five years it's going to be, you know, 70, 80 % autonomous cars, especially hooked up to your AI.

1:07:37Dave Blundin:I'll tell you what else. Just one more thought on this. I'm involved with a lot of insurance companies, including one I'm the chairman of, and there are going to be many, many more things that need to be financed and insured in the post-AGI era than just cars. But the insurance industry, every team and executive I've met has not even begun to plan for the post-AGI world. So the old is going away and it's going to go away faster than people think. But the new is much bigger than the old.

1:08:11Salim Ismail:Check out Lemonade. So Lemonade Insurance, it was started by a graduate of Singularity University. It's a huge AI-driven insurance company. They have just given, I think, you cut your rates in half if you're using a Tesla with FSD. Amazing.

1:08:29Dr. Alexander Wissner-Gross:There's a stat that always comes to mind here, about 15 years ago, if you remember back to BlackBerry days, there was a three-day outage where nobody could send BlackBerry messages for those three days. The accident rate in Abu Dhabi dropped 40 % during those three days. What that tells you is human beings should not be driving. We are terrible control systems for two-ton cars going at high speed. Yeah, 16-year-old testosterone-laden. Yeah, we should turn it over to technology as fast as we can. And it becomes a moral hazard to be doing this. And so especially in an age of texting, absolutely no.

1:09:04Dr. Alexander Wissner-Gross:My secondary kind of second tier effect and second order effect that I really love quoting is that in the U.S., 50 percent of court cases in the U.S. are car accident related. So, I mean, just 50 percent. So you take out a huge chunk of lawyers at the same time. So, you know, that's all good.

1:09:20Dave Blundin:And at the same time, if you're under a certain age, you know, 40, 50, your life expectancy is infinity now because of longevity escape velocity. So the risk of driving, the expected life loss is much, much bigger by taking chances today than it would have been 20 years ago. Great point, Dave.

1:09:38Dr. Alexander Wissner-Gross:I'm having a huge debate right now with Milan, my 14-year-old, because he wants to drive to get away from us. And I'm like, you can't get a driving license because I've made a prediction that you will never get a driving license. So you can't make me wrong. So now I want to get a license just to show that I made the prediction wrong.

1:09:54Salim Ismail:But the notion in the future of having a 16-year-old testosterone-laden boy driving a 5 ,000-pound vehicle at 60 miles an hour after just a few dozen hours of training will seem insane. Yeah. Just insane. Yes. I put this chart into our deck just to sort of keep a sense of proportion here. So check this out. China has installed more robots than all developed countries combined. Right. I mean, look at this chart here between Japan, U.S., South Korea, Germany down at that flat curve at the bottom and in China. And of course, this is because of their one child policy trying to maintain China as a manufacturing capital of the planet.

1:10:41Salim Ismail:But just to give folks a sense of this, any comments?

1:10:45Dave Blundin:You know, Elon shut down Model S and was it Y? Yeah. No, Model S. S and X. SX, SX, just to go full bore into robot manufacturing, which is brilliant because the robots will build a lot more things than the cars would have built. But the question I'd have is, what is this chart going to look like going forward, given that that alone is going to be a massive amount of production in the U.S.? I don't see anything going on in Europe.

1:11:14Salim Ismail:We're just releasing our pod with Brett Adcock from Figure this week as well. So if you haven't seen it yet, Dave and I went to Figure HQ, and Brett gave us an amazing tour of the facility, and we got to see the three generations of Figure robots. It's going to accelerate rapidly, both Figure and Tesla, planning to make millions and then billions of robots. And we're talking about here on this chart, you know, a quarter of a million robots being installed.

1:11:45Dave Blundin:Yeah, so this will be hilarious. It'll be like one little, that y-axis caps out at a quarter of a million, like you just said, Peter. And I think Elon's talking about tens of millions a year in just a few years.

1:11:56Salim Ismail:More robots manufactured than cars by a large amount. One particular article in the biotech realm, I know one that Alex and I are both excited about. Research achieved protection of brains synapses at cryogenic temperatures. I'll hand it to you in a second, Alex. I mean, here's the question. If you could freeze yourself, either because you've got a medical condition that isn't yet cured, that is likely to be cured in a decade, and you're on the verge of death, could you freeze yourself and then unfreeze yourself and be able to benefit from all the breakthroughs that occurred in the last decade?

1:12:32Salim Ismail:At the second time, if you want a time hop, I want to see what it's like after the singularity. I want to be around when LEV, longevity escape velocity, has been achieved. Can you freeze yourself? Well, the challenge has been when you do that, ice crystals form, and because ice volumetrically expands compared to the rest of the cellular fluid, it can disrupt and break the synapses that are the interconnections, effectively the stored memories in your brain. But this came out and gives us hope. Alex, over to you.

1:13:04Peter Diamandis:This is a key advance that many in the field of cryonics have been waiting for. This is a result out of 21st Century Medicine, a startup that's focusing on reversible cryopreservation technologies. It works with the Alcor Foundation, which is in America the premier nonprofit that focuses on offering cryopreservation services. I would say parenthetically to the audience, if ever you've expressed interest or had interest in cryopreservation, cryonics, I would definitely encourage you to reach out to Alcor and see whether it's right to you. I don't have a financial stake, but I just scratch my head wondering why.

1:13:46Peter Diamandis:I have to be careful with what I say. I will say publicly, I'm a huge supporter of Alcor and Cryonics. Very big supporter.

1:13:53Salim Ismail:You know, I've never signed up for it because I didn't want to have a plan B. I wanted to make sure I'm focused on longevity. But as this technology matures, it becomes really, you know, a backup plan. As Ray said, as Ray Criswell said on this pod, you know, it's maybe plan C or D.

1:14:13Peter Diamandis:I think it's such an important part of a portfolio approach to the singularity. So if one could maybe quibble over what the right sequencing is, like should plan A be live long enough to live forever, and then plan B is uploading and plan C is cryonics or vice versa. I'm not sure it matters a huge amount, but I would think anyone who's truly serious about acceleration and taking advantage of the acceleration, if you get hit by a bus tomorrow, then you're out of luck superficially in terms of taking advantage of the post-singular abundant worlds that we talk about on this podcast every episode.

1:14:51Peter Diamandis:Why not avail yourself of cryonics as one asset in your live long enough to live forever portfolio. It's a huge head scratcher for me.

1:14:59Dave Blundin:A couple of fun facts for anyone who's a doubter on this. There are species of fish and frogs that freeze rock solid in a block of ice all winter and then thaw out in the spring and they're absolutely fine because their cell walls don't rupture because they have enough glucose or whatever inside the cytoplasm of the cells. So it's not far-fetched at all. Also, we've frozen egg cells and embryos, extracted the nucleus, and it's fine for mammals, for actual mammals. Well, we do this for IVF, right?

1:15:34Salim Ismail:If you do IVF, you typically will fertilize and freeze a number of eggs, and then you can defrost them, and they're fine. So it's at scale, and as you said, not disrupting the cell membrane.

1:15:48Peter Diamandis:We do it all the time for individual cells. We're doing it increasingly for tissue. Blood, if we could reversibly cryopreserve blood, we wouldn't need local markets for blood transfusion. We could just have one large national market. Similarly for organ preservation. Organ cryopreservation is an enormous problem. We wouldn't need all of these hyperlocal state markets for organs. But the big tamale...

1:16:13Dave Blundin:You know what's really interesting to me is that in all sci-fi movies, when they're going to Jupiter or whatever, they go into these chambers and they slow the... Suspended animation. Yeah, but they don't freeze them. They just slow it down, but your heart's still beating. The fish and the frogs, they freeze, the heart stops to zero, the brain activity goes to zero, and then they thaw out in the spring and they wake right up. And that seems to me probably easier than trying to slow your metabolism to one beat per hour or something like that.

1:16:42Peter Diamandis:I think they end up being different mechanisms, different biochemistries. There's a whole body of evidence regarding nitrous oxide and suspended animation versus these vitrification agents and cryofixation. I think we want an all-of-everything approach. But for the life of me, like, goodness, anyone who's listening to me, if you take home one message, forget the fun jabs about how the moon had it coming, look into cryonics. You owe it to yourself.

1:17:10Dr. Alexander Wissner-Gross:I think there's a key point here, that memory preservation is really the bigger frontier than longevity.

1:17:16Peter Diamandis:Even the lobsters are starting, even though, Salim, to your point, even the lobsters are starting religions around preserving their own memory. Like, how could the lobsters be outracing us?

1:17:26Dr. Alexander Wissner-Gross:That's the really key point. And then this is one of the Gutenberg moments that we track, right? Because this forces really uncomfortable questions about continuity of self, identity becomes portable, all sorts of implications come about that none of us are prepared for, and we need to get into that discussion.

1:17:43Salim Ismail:All right, everybody, we're stepping into part two of today's pod, an important one. About six months ago, Alex and I started on an effort to take a lot of the ideas that Alex has written about in terms of you've heard the conversations here about the ability for us to be solving all areas and the conversations I've been having about achieving abundance by 2035 across the board. We started a dialogue and said, you know, there's an important paper to be written here, similar to, you know, situational awareness or AI 2027. And it's been an incredible collaboration between Alex and myself. Alex is the first author.

1:18:27Salim Ismail:His ideas are brilliant here. It's been an honor to work with him to put this forward. We're going to be putting a link to the solveeverything.org site in the show notes. so you can go to Solve Everything to get the complete paper here. Our goal is to get this out into the world, out into the ecosystem. So we're about to have this conversation. The paper slash book is nine chapters, and we're going to have a conversation limited to about five or six minutes per chapter to get the bold idea out there. We've sprung this on Salim and Dave. And guys, thank you for playing this game so that you could ask questions that are most likely to be asked by our audience.

1:19:08Salim Ismail:So love it. Alex, thank you for your support, for your leadership on this. Are you ready to jump in?

1:19:15Peter Diamandis:No one expects the singularity, Peter. I'm ready. Okay, amazing.

1:19:20Salim Ismail:All right, so if you wanna give a minute of intro on this and then we'll jump to chapter one. Sure.

1:19:27Peter Diamandis:So from my perspective, one of the motivations for writing Solve Everything is I get asked questions all the time. What do the next 10 years look like? Why don't you say something a little bit more concrete, a little bit more actionable about what people can do? And also a lot of questions about what does it even mean to solve math and why should I care? So in some sense, this, if you want to call it an essay or an e-book or a manifesto even is an attempt to answer the question of the so what and also so what now. And I should, yeah.

1:20:03Salim Ismail:But I was going to say, you know, one of the things that comes across that we talked about is the next 18 months to two years are going to set the rules down for the next century. That's right. And so super critical time. And we wanted to lay out in this paper that, you know, the example you gave in the paper is that the QWERTY keyboard, which was designed in the 1800s to stop those keys from jamming against each other, still persists. So the decisions being made over the next 18 to 24 months are going to persist for decades, perhaps centuries. So really important time.

1:20:36Peter Diamandis:Technologies get locked in, Peter, including but not limited to the QWERTY keyboard. As I've joked on the pod in the past, we're going to be stuck with QWERTY until the heat death of the universe. All right, let's jump into chapter one.

1:20:46Dr. Alexander Wissner-Gross:Just on that point, if we ask the multis to not use QWERTY in one hop, we'll get rid of it. So there's that.

1:20:53Peter Diamandis:Yeah, but then they won't be able to talk with you. And they're not really using QWERTY anyway. They're using tokens. Yeah. Yeah.

1:20:59Salim Ismail:All right. Chapter one, the war on scarcity. Would you please introduce us? Yeah.

1:21:04Peter Diamandis:So this chapter introduces an idea, call it a theory of history, that the most important changes in human history have been a set of revolutions, some recognizable, some maybe less so. So we argue the first revolution of note was the scientific revolution, which we frame as a war on ignorance. Ignorance was the enemy. And the key weapon was the method, the scientific method. The second revolution was the industrial revolution. So I'm hearing myself speak this and at the same time thinking back earlier in this episode when I'm lambasting Marx. So it is a bit of, it's funny, put Marx back on the shelf or tear it up and listen to this instead.

1:21:51Peter Diamandis:The second revolution was an industrial revolution that was a war we frame on muscle and replacement for muscle. Well, the weapon of choice was the engine, the steam engine in particular. Third revolution, digital revolution, was a war on distance, and the weapon was the bit. And Charlie Strauss in Accelerando does an amazing job in, again, my favorite scene in Accelerando, arguing that maybe the singularity actually happened in the late 1960s, when the first internet packet was sent from one place on the ARPANET to another, thereby decoupling bits from atoms. But nonetheless, the weapon in the digital revolution was the bit.

1:22:34Peter Diamandis:And we argue that we're now in the early stages of the intelligence revolution, which is a war on human attention, which right now is scarce, and we're fixing that with superintelligence. And the weapon this time around is the token. And we argue that revolutions are predictable and they follow phases going from scarcity to legibility to creating harnesses. We'll talk probably a bit more about that in a minute to institutions to finally abundance. That's the story.

1:23:04Salim Ismail:And I think one of the points we make in the chapter here is that the lone genius is dead. And what people need to do now is build systems that let millions of people solve entire categories of problems. That's right.

1:23:19Peter Diamandis:Or put differently, artisanal intelligence is cooked. I say it is cooked.

1:23:26Salim Ismail:Dave or Salim? Question or thought?

1:23:29Dr. Alexander Wissner-Gross:Two, three thoughts. One is, I don't know if starting at the scientific revolutions, we had the agricultural revolution, which used tools to do various and very powerful things. So you could argue that's the first one, but that's semantics. I do like the framing around this. the problem I have here, you're treating scarcity as technological. What I see is scarcity more institutional, right? Scarcity today is enforced by regulation incentives, legacy power structures, not so much lack of capability. So we have to re-engineer those where I think you're going to kind of thinking about routing around them.

1:24:10Dr. Alexander Wissner-Gross:We have to re-engineer those because we'll end up with that challenge there. So that's where I have the biggest issue with this. But in general, absolutely, once we have more and more intelligence, great. But the institutional issues we've got to deal with.

1:24:27Peter Diamandis:I think you raise a very important point, Salim, and I almost want to frame it as sort of a duality. There's one side of the coin that says scarcity is the result of inequitable distribution of resources. And the other side of the coin says scarcity is downstream of the pie not being big enough.

1:24:49Dr. Alexander Wissner-Gross:And I think - Well, both of those are true, obviously. Yes. Because you can solve for both sides of it, right? Right now, our institutions are optimizing totally for the wrong metrics.

1:25:00Peter Diamandis:So I think the question is always, at least I would suggest on margin asking, which is easier on margin, making the pie larger or redistributing the existing pie?

1:25:11Salim Ismail:Chapter two is called The Thesis.

1:25:13Dr. Alexander Wissner-Gross:Wait, does Dave have any points? No, you got it.

1:25:16Salim Ismail:You asked what I was going to ask. We're good. We're going to keep this moving along because there's a lot of juice here. All right, Alex. Right.

1:25:27Peter Diamandis:So the thesis of The Thesis is that A, cognition is becoming a commodity. Intelligence is just going to flow like oil does. And we've made the point on the pot in the past that this is a bit of a cliche, but admittedly, GPUs are the new oil. So A, cognition is becoming a commodity. B, that benchmarks, which we think are actually more profound than just the evals of the moment. A lot of people got excited when I did a walkthrough of all the GPT 5.2 benchmark consequences. I think it's actually more profound than that. We talk about in this chapter and in this extended essay, if you want to call it that, targeting systems.

1:26:11Peter Diamandis:Basically, if you want to industrialize progress, which is, I think, the era that we're finding ourselves in, it's essential not just to think of benchmarks and evals as isolated occurrences. Think of them as systems for targeting enormous capabilities. So I've made the point in the past, we need more and better benchmarks. The world needs stronger, harder benchmarks. But I think the right metaphor, certainly a metaphor that we talk about a lot in this chapter, is thinking about artificial superintelligence as an explosive. I mean, we also refer to it often as an intelligence explosion. But pulling that metaphor, if you have an explosion and you want it to be productive and not destructive, you have to shape it.

1:26:53Peter Diamandis:And there's a notion when you're building explosives, this isn't a manual, of shaping the charge, providing a shaped charge to direct for productive applications. It's like a rocket engine thrust on one end pushing you up. It's like a rocket engine. And rocket engine is a beautiful example of, in some sense, a shaped charge for an explosion or a shaped explosion. So we argue in this chapter, rather than just letting superintelligence be used for an uncurated set of problems, instead we should be aiming them through the nozzle, if you will, the rocket nozzle equivalent of moonshots. And that in particular, if we don't do that, then what will happen is a sort of a puddle, which we call the muddle, a bit of alliteration of bureaucracy that will instead just focus the world's superintelligence to the extent we even get enough of it on problems that sort of make use of input costs in a way that's highly inefficient.

1:27:56Peter Diamandis:So really the argument is shape the charge of superintelligence.

1:28:00Salim Ismail:Another point that is made that I think is very important that we flow throughout this is a shift of instead of paying people for hours of work, paying people instead for solutions they deliver. So if you're a law firm, if you're hiring a law firm for$800 an hour to review contracts, the new world is not paying them to review contracts. tax it's paying them for delivering an error-free you know legally tight agreement period um it's verified outcomes and we're going to flow this throughout i mean this is uh this is a change i think that's going to hit us like a wave where it's going to transform you're only going to be hiring companies and ai systems that are delivering you definitive verified outcomes

1:28:48Peter Diamandis:that's right and one of the one of the most i think egregious inefficiencies that one might see throughout the economy right now is people paying for the inputs when they should be paying for the outputs, paying by the person hour for labor when you should be paying by the achievements of whatever the economic system is. And I think it's only by moving to this sort of performance or outcome-based economic mindset that we get all the benefits of abundance.

1:29:18Dave Blundin:so it feels to me like this is really two two chapters or two thoughts in one section called the thesis you know one is asi is inevitable the other is really compelling which is the the shaped charge like it's really dawns on me that uh graphical stuff the holodeck the virtual girlfriend are very compute intensive and solving a disease or solving physics is actually not any more compute intensive than one person's virtual girlfriend. And so the choices on how to use our very limited amount of compute over the next two or three years are critical, critically important. Where do you focus it? Yeah, I love the fact that you're taking this on because there's no body of authority right now that's even thinking about it that has any power.

1:30:07Dave Blundin:So hopefully this will wake a lot of people up.

1:30:09Peter Diamandis:You've articulated it beautifully, Dave.

1:30:13Dr. Alexander Wissner-Gross:so wait wait i've got wait i've got a couple of points here so um i i think saying the cognition is a a cheap commodity is fabulous i think it's really important and the use of that in solving kind of big problems is really really important i think it's great to say let's evaluate and reward outcomes rather than rewarding work. I got to push back on the ASI's inevitable thing. That's like a philosophical statement rather than scientific. I think that weakens the paper. I'd rather you say something like incentive structures, given the current incentive structures, scaling intelligence is a much more important attractor state, right?

1:31:01Dr. Alexander Wissner-Gross:Because that will then lead you to where you want to get to?

1:31:04Peter Diamandis:I would say, I mean, I think it's an interesting point to be sure, but I think there's almost an instrumentally convergent trap that I see a lot of frontier labs at least partially fall into, which is, okay, we have super intelligence, at least baby super intelligence right now. How do we allocate it? What in particular, what fraction of our compute budget, if you're a frontier lab, do you allocate to building the perfect AI researcher that can recursively self-improve, as we talk about in almost every episode at this point, versus how much of your compute budget, which is scarce, do you spend solving everything else?

1:31:42Peter Diamandis:And I think that that's sort of the fundamental quandary here. How much do you sort of reinvest in recursive self-improvement versus now finally using at least some of the compute to solve everything else? And I think solving that asset allocation question is key. And then within everything else, how do you distribute it?

1:31:59Dr. Alexander Wissner-Gross:That now smacks of Peter's law, which has given the choice to do both.

1:32:03Salim Ismail:Alex, this is also going to be true for the entrepreneur, for the company, right? We're all going to have compute budgets in the final result. You have a certain amount of compute you have access to. Where do you aim that compute, right? It's a front. It's a way front that you can aim in a direction that you want to solve. And when you do that properly, it not only enables you, but enables everybody else to build on top of it. That's right. I'll move us on to chapter three here. And again, please, there's so much content. We really want you to take a look at this paper and read it. We're just giving you a quick overview here.

1:32:38Salim Ismail:The mechanics. Alex, over to you.

1:32:41Peter Diamandis:Okay. So first, I think in this chapter, we finally definitively address the question that I guess every time I'm making a point about AI solving math, which is, what does solving mean? What does it mean to solve a domain like math? And we provide in the chapter a more thorough definition, but sort of heuristically, the shorthand is to solve a domain means that you can get it to the point where you can just pour compute on and problems get solved. It means that you can scalably, you have all the architectural pieces in place, and I'll talk in one second about what the architecture looks like or should look like.

1:33:22Peter Diamandis:But you have enough of the architecture in place that you can scalably, literally pour more compute on and get more solutions out within that domain. So that's, for avoidance of doubt, when I talk about solving math or solving physics or solving other domains, that's what I'm talking about. Second point.

1:33:39Salim Ismail:Yes, please. I would just say, Alex, on that, it's no longer the domain of a single genius to work on something and hope they got it right. The AI compute, as you said, it's a matter where you want to aim that shape charge.

1:33:53Peter Diamandis:That's right. We're seeing the industrialization of cognition and the bulk solution of multiple fields. I should also add, parenthetically, I guess as a preliminary matter on this narrow topic, I also have a portfolio company named Physical Superintelligence that's trying to solve all of physics with an approach like this, just for full disclosure purposes. The architecture involved, so several layers, You need a purpose. That's like the objective function or the goal. You need a task taxonomy, which is essential. You need a suite of tasks that are going to be solved. It's almost the map of the terrain that you're going to solve.

1:34:33Peter Diamandis:And when we talk about making sure that compute is being used efficiently and wisely as a targeting system or through the lens of a targeting system to solve lots of problems, the task taxonomy is absolutely essential. Third, observability. You need raw data from data streams or sensors that you're going to use to adjudicate whether you're making progress. Fourth, you need the targeting system itself. So I've argued on this podcast and elsewhere many, many times, we need more harnesses. We need more benchmarks in order to not just to make sure that we're making progress, but to actually shape the charge and shape the progress.

1:35:11Peter Diamandis:Many AI techniques depend on benchmarks and evals in order to make progress in a given field. The next item, the model layer, the most obvious one, we need models. We need AI models that are capable of functioning as a virtual brain for solving problems. Unfortunately, those are improving pretty rapidly. Next, we need modes of actuation. It's insufficient for us to just know those television commercials. Well, I stayed at a Holiday Inn Express at night, therefore I know how to solve the problems. Similar idea here. Maybe that's a bit too colloquial. I don't know. We need modes of actuation. So hands and APIs that are able to reach out into the physical world or the virtual world or the biological world and shape the impact on the world given better ideas coming from the AIs.

1:36:03Peter Diamandis:And then finally, we need better modes of verification, red teaming, governance distribution. That's what we call the industrial intelligence stack. So whereas previously, during the Industrial Revolution, we might have spoken about rotors and combustion engines and various forms of electromechanical systems. These are the key components, I think, the key layers of the intelligence revolution.

1:36:31Salim Ismail:You know, the alpha for entrepreneurs here is we've talked about, you know, these waves of solving areas and problems, right? We're about to flip math, coding, physics. So your job now as an entrepreneur is to figure out which industry is about to make this flip and where do you focus your compute wallet on making that, right? And how do you help solve an area of passion to you? So Dave, Salim.

1:37:02Dave Blundin:I'm kind of curious whether, you know, I'm used to launching a couple hundred agents, maybe 250 agents, 256 agents actually, to work in parallel on a problem. And if the scaffolding that you're describing is right, it comes back just perfectly solved. And if it's even slightly flawed, you have, you know, a$2 ,000 bill and a bunch of crap. How much are you spending per day on those agents, Dave? Yeah, well, it's$100 every few minutes popping up on my screen here. It's not quite that bad. It does seem like it's every minute, but it's not. But I'm curious, you know, to what degree this is actual engineering.

1:37:42Dave Blundin:These five layers are true scaffolding. Like this is hard code or is it more conceptual?

1:37:50Peter Diamandis:I think it's a balance of both. I also think it, to some extent, is a trick question because increasingly the harness and the scaffolding itself is being generated by the models. So to the extent that we're in the era of recursive self-improvement, this entire architecture is itself an artifact, a downstream product of itself. Yeah.

1:38:14Dave Blundin:Yeah, I think I totally agree. And I also think that's the path to insanity. because at some point you have to say this is hard code because then the AI will invent the next thing and the next thing. It goes to infinity and then you lose your mind.

1:38:30Peter Diamandis:I would say also this is, in my mind, the way we prevent insanity in an era of recursive self-improvement is with these benchmarks, targeting systems that make sure that as systems are recursively self-improving, we can quantitatively measure what are they optimizing towards? Are they going in a constructive direction or not? Yeah. Chapter four, the lock-in.

1:38:53Dr. Alexander Wissner-Gross:Wait, wait, wait, wait, wait. I've got a couple of comments here. Okay. If you can go back a slide, can I go back? Sure, hopefully. Okay, so I think the, I really love the shift from genius to logistics because as you move, you can, you always kind of say, take something from a black art and make it a prescriptive process. I mean, you can do that. That's awesome. I think that's fantastic. I have an issue with your, you know, maturity levels, because you call it like natural law, but it's really just a taxonomy. We've had lots of industries get stuck at different levels, like autonomous driving, etc, etc.

1:39:29So this feels like a framework retrospectively imposed on what's going on.

1:39:36Dr. Alexander Wissner-Gross:I think it's great aspirationally, right? But some of them, because calling it a maturity curve kind of speaks of like an inevitability to it, which that may not be exactly the case. It's more of a descriptive model than a predictive one.

1:39:53Peter Diamandis:Yeah, I would say any good theory of history and solve everything is in part not just a theory of the future, but a theory of history and how revolutions have worked in the past. Inevitably, as Monty Python says, it's only a model. So I do think there is an element of model building here where we're trying to, for the first time, articulate a self-consistent, coherent theory of how this is all supposed to work. How is the singularity supposed to play out over the next 10 years? And to your point, Salim, about autonomy model levels.

1:40:28Salim Ismail:Alex, I could say not only how it It's supposed to play out. But how do you have it play out in a way that leads us towards abundance versus towards a muddle?

1:40:38Peter Diamandis:Normatively, how should it play out, not just how will it play out? But I think one, you know, at the margins, one can quibble, well, actually, there are seven maturity levels for industries to evolve through their industrial intelligence stack, or it's a continuum. But I think the central point stands regardless of how one sort of splices hairs on maturity levels that we're seeing over and over again. And we can get into more detail on this. We're seeing domain after domain, industrial vertical after industrial vertical, succumb to basically the automation of intelligence, which used to be the province of individual artisanal loan innovators.

1:41:20Peter Diamandis:And it's just becoming an industrialization of intelligence.

1:41:25Salim Ismail:All right, I'm moving us on to the next chapter, chapter four. I'm sorry, keeping us moving, the lock-in. Alex?

1:41:32Peter Diamandis:So in this chapter, we talk about, in part, AlphaFold3 from Google DeepMind and argue that that was a template for entire collapses of domains. That almost overnight, and I've made this point on the pod in the past, AlphaFold3 took the problem of determining the structure of a protein, which used to require a biology PhD student five-plus years of time, laborious bench work, just to determine the structure of a single program. And almost overnight, AlphaFold3 solved that problem across many millions of proteins, known and unknown. That's, in my mind, like the prototypical example of a domain collapse.

1:42:14Peter Diamandis:And we argue in this chapter, the lock-in, that we're now in a phase of history, of future history, where this is just going to start to happen over and over again across different fields, where intelligence shifts from an artisanal craft to a utility that just flows. And we argue that we have approximately 18 months or so to decide what direction to shape the flow in and to set the standards for how this is going to be done at scale, given that we are dealing with scarce compute, to put in place the supply chains, which are huge. And we talk about on the pod all the time about all these supply chain scarcity issues, memory chip crises, GPU crises, what happens to Taiwan, what happens to the semiconductor fabrication facilities in the U.S.

1:43:02Peter Diamandis:versus not in the U.S. And then all the data rights. We're in a critical, we argue, 18-month period when all of these details are going to shape the intelligence explosion. And so we want to make the best decisions in the next 18 months. I can't wait to read this chapter, actually.

1:43:18Dave Blundin:18 months is such a short timeline.

1:43:21Salim Ismail:Another important point here for CEOs listening, for entrepreneurs listening, is the race isn't about building the best AI. It's about writing the best scorecard that everyone else is graded on. So what does that mean? You know, today's healthcare system, and it's an example, Alex, you used beautifully. Today's healthcare system, the benchmark is the number of patients processed per hour, right? which means it's driving a lot of short visits with the physician and cost economics driven. But what if the benchmark instead were patients who are still healthy five years from now, right? That would set up a whole different set of optimization outcomes.

1:44:05Salim Ismail:So writing the scorecard that your AI system is going to use to measure success is critically important.

1:44:13Dave Blundin:So why is this chapter called the lock-in? Exactly. Are you implying that the decisions we make in the next 18 months have locked in humanity for the rest of time into a path?

1:44:22Peter Diamandis:Maybe not for the rest of time, but that is the inspiration for the name, that we're in a period inspired in part by annealing of a metal cooling, that the decisions that we make now are at least going to lock in a chunk of our future light cone.

1:44:37Dave Blundin:Yeah, it makes sense. Totally makes sense.

1:44:41Dr. Alexander Wissner-Gross:you know it took the qwerty keyboard it was decades of lock-in so i i think it is but i do

1:44:47Peter Diamandis:like the you're stuck on the qwerty keyboard i am this is like we could have the singularity and

1:44:51Dr. Alexander Wissner-Gross:you'll still be bothered how long before we can get past that and can we stop you but anyway i really like the alpha fold example demonstrating a domain collapse right that's like really great But you're talking about lock-in as a technical inevitability. But this is many times a policy and a governance choice, right? It's monopolistic APIs. It's closed data. It's regulatory capture. There's lots of other stuff. Because how do you distinguish between bad lock-in and productive outcomes? That's tough.

1:45:26Dave Blundin:In your perfect world, are there like five jurisdictions with different choices? And at least we have variety? or is it inevitable that there's just one lock-in?

1:45:35Peter Diamandis:I think, I mean, in some sense, that's the grand geopolitical question that as we just, not a normative answer, but just a descriptive answer, it seems like we're heading to a near future where there are going to be multiple spheres or zones of influence, each able to independently lock itself in. So to the extent that we, with this, call it an extended essay, can have any influence, I think the aspiration is to have a positive, constructive influence on all of those spheres of influence and not just the one.

1:46:09Dr. Alexander Wissner-Gross:By the way, I disagree with the 18 months when I've been advising some big company CEOs. I've been saying two years. So I was going to say that.

1:46:18Peter Diamandis:Salim, you're pulling a reverse Moore's Law. Remember, Moore's Law started as 18 months became 24 months. You're pulling a reverse Moore.

1:46:25Dr. Alexander Wissner-Gross:Because if you have the next meeting six months from now, it's going to add that six months time. Anyway, go ahead.

1:46:31Salim Ismail:All right, let's go to chapter five here, the mobilization. And Alex, if it's okay with you, the last three chapters of this paper are the most important. I want to hit on chapter five and six and then really focus on seven, eight, nine. So give us a summary on mobilization, if you would.

1:46:45Peter Diamandis:All right. So the idea with this chapter is spelling out a future timeline for how a, call it a wave front of the explosive shock of the intelligence explosion was going to propagate from math, which we talk about on the pod all the time, over the next couple of years to the physical world, physics, chemistry, material science, biology, and then through the end of the decade toward planetary systems, fission, fusion, the Dyson swarm by the early 2030s. Amazing. And chapter six, the engine. Yeah, so this engine is very practical and talks about how to design the targeting systems, the benchmarks at a sufficient level of rigor that readers and folks all over the world can implement it with some level of confidence?

1:47:34Salim Ismail:You know, the point we made here is, you know, don't invest in the AI models. If you look at the train and train track analogy, the trains are becoming commodities. It's the tracks, right? The tracks that the trains run on, the scoring systems, the testing infrastructure, the data systems, the funding mechanisms. And they're laid out beautifully here. Those are the elements that are the most important for entrepreneurs and CEOs to be focusing on. That's right. Let's go to chapter eight, seven, one of my favorites, moonshots.

1:48:07Peter Diamandis:So here, and maybe Peter, you want to speak to this one perhaps even more than I do. We lay out 15 different moonshot level missions for what we argue are good uses, maybe optimal uses for this targeting system capability as we start to channel superintelligence into productive applications. Maybe, Peter, I'll pass it back to you for your favorites.

1:48:31Salim Ismail:Sure. So the thought is, you know, many of us have discussed XPRIZE over the time. The notion is that there's these giga X prizes, these massive opportunities on a humanity level scale, from printing human organs to achieving fusion to understanding the fundamentals of unified field theory and physics. And it's where do you as an entrepreneur, or you as a CEO, or you as head of an organization, want to focus this incredible superintelligence that's coming to take moonshots. I keep on saying, you know, in the educational field, if you're using AI as a ninth grader to solve a ninth grade homework assignment, you've lost it, right?

1:49:16Salim Ismail:If you're using AI to build starships, that's it. So how do we, as humanity, go after problems that we would have never imagined we're capable of doing? And so the chapter lays out 15 different moonshots just to get creative juices going to say these are capabilities that we're going to be able to bring to bear to solve these moonshots.

1:49:39Dr. Alexander Wissner-Gross:Can you list out a couple of the moonshots for the viewer?

1:49:45Peter Diamandis:One of my favorite ones is interspecies communication. I have a soft spot for that. We talk on the pod all the time about uplifting non-human animals. And I think as we start to think and maybe somewhat controversially about what future forms of personhood might look like. I think solving problems like interspecies communication or solving hard problems in physics, those definitely have soft spots in my heart.

1:50:09Salim Ismail:Yeah, I think it's making humanity a multi-planetary species. It's getting to longevity escape velocities. It's all of the things, you know, it's basically speed running all the science fiction movies, the positive non-dystopian science fiction movies. That's right. Yeah.

1:50:23Dave Blundin:You know what I love about this is if you look at John F. Kennedy and Going to the Moon, the brand effect, you know, enabling somebody in power like John F. Kennedy to tie the brand of the mission back to them, that's critically important for them to then inspire the world that this is important. And I think what we did wrong is our governor here did an incredible job of unleashing$3 billion from the legislature to try and become an AI leader, but it was too vague. It's like, what does it mean? So the money hasn't even been deployed. But if you tie it to these 15 moonshots and then the governor says, we want our state to win this race, like John F.

1:51:01Dave Blundin:Kennedy did to the moon, they can pick the one they're passionate about and unleash it. And we have 50 states, you know, they can all choose their favorite of the 15, maybe not talking to aliens, but whichever one they latch on to. It's such a really great framework. I'll just literally, I'll just list some of them.

1:51:18Salim Ismail:Like doubling human lifespan is one. Ending hunger with synthetic food systems around the world is another. AI empowered education for all at the highest possible level, right? It's a high bandwidth BCI. We've been talking about that on this pod for a while now. Demonstrating human mind uploads. Can't wait for that, you know, plan B, maybe plan C. We'll see, you know, as Alex said, interspecies communications, understanding human consciousness. I think we've talked about that previously, you know, can we understand human consciousness at which point maybe we'll understand consciousness for our AI systems as well.

1:52:00Salim Ismail:So, you know, what have we dreamed about? Another one I love is disaster prevention and avoidance, predicting earthquakes and then preventing them, or tsunamis, as the case might be, right?

1:52:13Dr. Alexander Wissner-Gross:These become natural X-Prizes, you know.

1:52:16Salim Ismail:They are, they're what I call giga X-Prizes here. But I think one of the important things in this chapter is allowing people, in fact, demanding people dream bigger than ever before, because the tools we have to solve the biggest problems are now epic.

1:52:31Dr. Alexander Wissner-Gross:I think this, for me, is the most powerful part. The fact that you can say anybody has the agency now leveraging these tools to go after these, what seem like impossible things, become rote. You're only limited now by your imagination. And your compute budget.

1:52:48Peter Diamandis:And your compute budget.

1:52:49Dr. Alexander Wissner-Gross:But that's dropping 90 % a year, so we're in good shape. That's right.

1:52:54Salim Ismail:All right, the muddle versus the machine. And at first, Alex, when you proposed muddle as a term, I was like, I'm not sure I like it. Now I love it. So describe what the muddle is.

1:53:05Peter Diamandis:Yeah, so the muddle is the, another term might be the bureaucratosaurus that loves to measure inputs rather than outputs and slow down progress. And the idea is without properly shaping the charge of the intelligence explosion, the muddle is the end state that we find ourselves when sort of basically muddling our way through is one of the etymologies of that term. So what we talk about in this chapter in a single sentence is what happens after we win, painting a positive and non-dystopian view of, in particular, what does human agency look like? I made this short film posted to social media called a nation that learned to sprint, depicting what life in the early 2030s might look like if everything goes well.

1:53:55Peter Diamandis:And we see GDP 2Xing or 3Xing year over year. And what does a human, quote unquote, job even look like in a macroeconomic scenario like that? So in this chapter, we lay out lots of new job opportunities, career opportunities that will be available to humans, at least unaided humans. So target designers, for example, or data rights brokers, people who are involved in shaping the targeting systems and shaping how we aim, fire, and verify superintelligence towards the hardest problems that humanity faces. This is going to be a growth industry from a job perspective.

1:54:32Salim Ismail:Another point we make in the chapter here that's super important, we've discussed, and Salim and I've discussed this before, is that GDP is a terrible mechanism for measuring economic health, right? So the paper proposes replacing GDP with something called the Abundance Capability Index, which is measuring a nation's capacity to solve problems rather than how much money changes hands. So I think, again, as we look at benchmarks, as we look at rails and harnesses, understanding this is really important.

1:55:07Dr. Alexander Wissner-Gross:I think the challenge here, though, is, you know, it's UBI, UBC, whatever we want to call it. It's a great endpoint and a great aiming point. And you want to have a target, as you say, Peter, otherwise you'll miss it every time. The challenge is moving from a welfare, taxation, labor union structure to that is such a huge leap. I have no confidence in public sector in getting us there. So how do you navigate that? I think that's something worth exploring. That's a wonderful scope of your thing, but that's a huge consideration.

1:55:42Peter Diamandis:I was going to say, Salim, what a wonderful transition. Thank you to the last chapter, Build the Rails.

1:55:47Salim Ismail:Building the Rails, chapter nine. I think one of the most important chapters of the entire paper. Alex? Yeah.

1:55:54Peter Diamandis:So this chapter is where we lay out the answer to Salim's question. So what's the so what and what do you do? If you're not running a nation state, what can you do? How are you empowered to shape this transition, to shape your own moonshots and to control your own targeting system? So we lay out various suggestions from investors, as indicated in the slide, funding the primitives, not the applications. There's so much infrastructure that can and arguably should be built out. If you're an entrepreneur, you should be picking your own targets with the targeting system, create your own benchmarks, and aim your own compute.

1:56:37Peter Diamandis:If you're an executive of a large company, you should be measuring the outputs, not measuring the inputs. Dave, I think you put it beautifully earlier in this episode, talking about the API-ification of large corporate boards and corporate governance. I think that's exactly the right playbook here. And the missing factor is having a benchmark to measure corporate objectives in such a way that the problem of corporate governance becomes a matter of maximizing the use of available scarce compute to maximizing those KPIs and those evals. So in this chapter, we lay out for a variety of different roles in the economy.

1:57:16Peter Diamandis:What can you do? What can you in the audience do to help us achieve a utopian vision of abundance and post-scarcity and excellent use that's you social for superintelligence?

1:57:28Salim Ismail:So I want to wrap this here. I want to encourage all of our listeners. We'll put the link to the paper down below. It's solveeverything.org. Please take a look. Load into your favorite LLM. have a conversation. What Alex, and to some degree myself, but I credit Alex, is what's the vision for the decade ahead that's going to bring us to abundance? How do you do it? How do you lead as a leader, as an entrepreneur, as a CEO, as a governor? Where are we going? And it's going to move much faster. And I think one of the points here, Alex, is that there's going to be such a distinction between those who do and those who don't, that it's going to create a sort of a 66 million year ago asteroid strike that's going to kill the dinosaurs and elevate the furry mammals, say I say furry lobsters, moving forward.

1:58:25Peter Diamandis:No, we love our lobster friends. He didn't mean that. Peter really didn't mean that.

1:58:29Salim Ismail:No, no, elevate our lobsters, I would say that.

1:58:32Peter Diamandis:Elevate them into low Earth orbit. All right.

1:58:37Salim Ismail:Favorite part for all of us AMAs. I'm going to keep us to one question per mate. All right. So here they are. There are nine of them. Let's say, Dave, do you want to pick first? Sure.

1:58:52Dave Blundin:I like number three because it's such a happy answer. In a world with perfect AI output, will there still be a place for human spark in art and sculpting? Will handmade work have higher value or be buried in the AI humanoid production? Wholeheartedly believe it'll have astronomically higher value. Human touch, it will be so rare and so valuable, but also abundance of capital will be unbelievable. And so I expect artwork, you know, current artwork is one of the best investments you can make right now. but going forward it is a category it will go up tremendously in value and people will appreciate all things human whether that's human actions human sports human poetry human artwork sculpting i expect to be definitely a rising area for sure i think that would be a great uh conversation

1:59:44Salim Ismail:i'll call it a debate but one of our next pods i think what is going to be most value from humans in the future. Salim, do you want to pick one of these?

1:59:54Dr. Alexander Wissner-Gross:Let's see. I would pick number five, right, which is how is a young person supposed to earn an income when they compete against a model that costs$50 a month? That's from at clownpieced.

2:00:10Dr. Alexander Wissner-Gross:It's a great question, but you're assuming the future is about competing with AI. It's about directing it and leveraging it and amplifying yourself with it. you know in history we've destroyed old jobs we've created control points and we've done orchestration we've done intent so winning isn't productivity it's agency and we talked about this earlier in the pod so like knowing what to do and why it matters is more important like how do you mobilize intelligence at scale is really the biggest challenge and you can do that today in a way that you can't do ever we've been doing workshops with teenagers and showing them how to use AI as a superpower to give themselves agency.

2:00:50Dr. Alexander Wissner-Gross:And I think that's where I would go with that.

2:00:54Salim Ismail:Alex, would you pick one of these?

2:00:56Peter Diamandis:All right. I like this assortment. So I'll pick number eight for a hundred trillion. Question number eight is, with AI taking tasks we do ourselves, isn't there a risk we lose essential skills and become completely dependent on AI services. And that's asked by Jorowen Hoffs. So I want to invoke my friend, John Smart. I hope you're listening. John has, I think, a brilliant dictum that the first generation of any new technology is dehumanizing. It takes away all your skills. The first generation of calculators take away your arithmetic skills. Second generation is net neutral to humanity. Third generation is Another friend of the pod, Stephen Wolfram, Mathematica, gives you new superpowers, gives you new skills.

2:01:42Peter Diamandis:So I don't accept the premise that there will be any sort of permanent loss of essential skills due to AI automation. I do think that there is a short-term substitution effect where AI drives down the cost of various skills or various tasks. But over the long term, I expect AI automation to be net superhumanizing. We're going to be capable of so much more with AI than we can do otherwise without it. And I'll also say, Werner Wenge has written quite a bit about this. Definitely encourage everyone to read Rainbow's End and Fast Times at Fairmont High novel and novella, respectively, that talk about this ad nauseum.

2:02:29Peter Diamandis:We're going to, I think, find ourselves in a very near-term future where, just like there's wilderness camp to learn how to survive without modern technological aids, we're going to start, I think, in our educational system, at least the better parts of it, having the moral equivalent of a wilderness camp for AI where all of your AI tools get taken away. You have to do things manually just so that you at least have that skill set. And then you get all your AI skills back and every fourth grader becomes a Nobel laureate.

2:03:00Salim Ismail:I love that. All right, I'm going to close this out with number six. I use Claude Daly. It fails in basic consistency, I think, is saying, how can this be close to AGI when I have to check every output for errors? That's from MMGP9OT. So I'm going to say again, AI is the slowest and most incorrect it will ever be. I know when I'm using my Claude bot or Claude 4.6, if I get something that seems off, I will ask it to check itself and being able to use this in a recursive fashion. Also, MMGPT 9, we're in a period of recursive self-improvement. I think we're at the steepest part of the curve and it's going to become more and more capable every day.

2:03:45Salim Ismail:And the idea that we can use AIs to check AIs and, in fact, to do deeper reasoning is going to eliminate this very quickly. Okay, let's jump into our outro music. This is from a friend of the pod, CJ Trueheart. CJ, thank you for this. CJ was on a Zoom AMA that Stephen Kotler and I did for our book, We Are His Gods. And he actually wrote this as a result of that AMA. Anybody who is a creative, we love creatives. And if you want to send us outro or intro music, send an email to media at dmandis.com. Myself and the team are reading it, and we'd love to get your input. And we'd love to play it. All right, let's enjoy this outro music from CJ Trueheart.

2:05:06Salim Ismail:Are you paying attention or are you paying the price? Scrolling through a sea of sex and entertainment twice You can be a creator or you can be consumed Every hour that you waste is a future left entombed The hand you UBI and call it containment A golden leash, a velvet cage, a comfortable arraignment Wake up, the moment's here to open your eyes Your dreams are close enough to touch the skies The deepest problems that have plagued you in disguise Only you know that pain, only you can make it fly

2:05:43So what do you see when you look in the mirror?

2:05:46Dave Blundin:Do your actions match the vision? Is the picture getting clearer? Why wait when the time is here? Why wonder when the path is clear? Why sit as a passenger when you have the power to steer? Attention is the currency Don't let it be the cage

2:06:12Salim Ismail:The future for some will pass them by While others don't ask how They ask why not now Not someday, not somehow They ask why not now See, everybody wants to live a Star Trek dynasty But nobody wants to rise with a purpose they can see Same old, same old, comfortable and cold Trading in their potential for a story already told Answers only you can know It's just a question of who you choose to show Up is today, tomorrow, every dawn, every day The version that's slow fading of who you choose to be today

2:06:52Salim Ismail:So what do you see when you look in the mirror? Do your actions match the vision? Is the picture getting clearer? Why wait when the time is here? I wonder when the path is clear Why sit as a passenger when you have the power to steer? Attention is the currency Don't let it be the cage See, I've lived in the dark Lost in the world, lived in poverty But the bottom didn't break me, it revealed the deep of me Those who face no challenge will embrace no change Those who embrace no change will always stay the same And those who stay the same get left behind Holding pocket change because they refuse to learn They refused to turn what they gave their attention to.

2:07:33Salim Ismail:So attention became their chain. But I turned my pain into a plane. And I'm never landing back on that terrain.

2:07:43Salim Ismail:All right. Thank you, CJ. Guys, on behalf of Skippy, my lobster, sending you guys an incredible week ahead. All right. And as always, love it. But Alex, it was an honor and a pleasure to work on Solve Everything with you. Excited to get it out into the universe. I think the value of steering people toward this accelerating time and how they actually have the biggest impact on creating abundance and not the muddle is critically important. Agreed, Peter.

2:08:18Peter Diamandis:Pleasure writing it with you as well. And I would encourage all of the humans and non-humans in our audience to read it and let us know what you think.

2:08:26Salim Ismail:yes for sure all right wtf twice a week at these days thank you to our subscribers it's free please subscribe we'll let you know when the episodes drop tell your friends about this uh i've been here at uh you know 20 robbins event and yeah i would say probably 100 people have come up and said oh my god i love moonshots and everyone i love alex alex you got fans here in sun valley How many of those people were human, Peter? Unfortunately, they were all human, at least for the moment. Yeah. All right. Dave, Salim, thank you, guys. If you made it to the end of this episode, which you obviously did, I consider you a moonshot mate.

2:09:07Salim Ismail:Every week, my moonshot mates and I spend a lot of energy and time to really deliver you the news that matters. If you're a subscriber, thank you. If you're not a subscriber yet, please consider subscribing so you get the news as it comes out. I also want to invite you to join me on my weekly newsletter called MetaTrends. I have a research team. You may not know this, but we spend the entire week looking at the MetaTrends that are impacting your family, your company, your industry, your nation. And I put this into a two-minute read every week. If you'd like to get access to the MetaTrends newsletter every week, go to diamandis.com slash MetaTrends.

2:09:42Salim Ismail:That's diamandis.com slash MetaTrends. Thank you again for joining us today. It's a blast for us to put this together every week.

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