Pope Leo vs. AI, GPT 5.5 Beats Claude, and Sam Altman Walks Back Job Apocalypse | EP #259

Pope Leo XIV warns of AI risks and just dropped a 42,000-word encyclical on AI.

The Vatican has seemingly staked out the first major religion position against AI personhood.

This is the first technology that forces us to define humanity. The broader problem is there is a brand new coding benchmark, Deep Software Engineering.

GPT-5.5 scored scored 70%. Claude Opus 4.7 scored 54%.

This too will saturate.

Sam Altman, he admitted he was wrong. The CEO of OpenAI, who spent last year warning about the mass white-collar displacement, now says, quote, I don't think we're going to have the kind of job apocalypse that some of the companies in our space are talking about.

Yeah. So here's what's really happening under the covers. Now that's a moonshot, ladies and gentlemen.

Everybody, welcome to another episode of Moonshots. I am here with my extraordinary Moonshot mates, Dave Blunden, our emperor of all things exponential investing, Alex, our in-house polymath, and of course, Saleem, the father now of the organizational singularity. Saleem, we had an incredible episode that we recorded. It's done super well. So congrats on that.

The comments in that, the comments in that episode are like off the hook. Really, really deeply appreciative of everybody's comments there. We did one major thing.

What's that?

As promised, we have released the book for free and we've released a Claude skill for free. So anybody can download the Claude skill and run their entire business on this model. Go to openexo.com. It's available.

Awesome, awesome. Alex, where are you today, buddy?

I'm in Chicago. I'm here to give a speech to the Genesis Mission, which recall is the US Department of Energy's initiative to double American scientific productivity in the next 10 years. I'm hoping we can 10x it or 100x rather than just double it.

Yeah, double seems like a low bar.

Double's a very low bar in my mind.

Yeah. Well, I'm Peter Diamandis, your host. We've got an incredible show today. Stories that will make you want to hopefully go out there and create the future, right? The best way to predict the future is create it yourself. And we are living in a time where we can create the future. Uh, we've got the tools, they're completely democratized and demonetized. And guess what, guys? We just passed 500,000 subscribers. Thank you to all of you who've subscribed. Uh, I know it's a vanity metric, but it lets us know that you enjoy the program and we're investing more and more time. So If you haven't yet subscribed, please do. All right, uh, that's amazing.

Congrats, uh, congrats, gentlemen.

Yeah, we're very base-10-centric.

Okay, and I stretched the term to include all of us. Yeah, except my boys still think until I get to a million subscribers I don't rate. So that's my next mission. Uh, let's open up with our first, our first conversation here. Our first story is Pope Leo XIV warns of AI risks and just dropped a 42,000-word encyclical on AI in his very first encyclical letter. It's titled Magnifica Humanitas, on safeguarding the human person in the time of artificial intelligence. He's calling for governments to regulate AI. He's calling for worker protections and bans on autonomous weapons. I'm definitely for some of them. He even coined a term, the Babel syndrome. This idea that he put forward is uh, analogizing the Tower of Babel, uh, of past to the Tower of Babel today, which is about data and profits. And here's the kicker: Google, Anthropic, Meta, and OpenAI are all quietly lobbying the Vatican before this came out. Um, that's fascinating. And there's kind of strong evidence that this anti-AI document was actually written in part using AI. So you can't make this stuff up. You know, this is the head of the church for 1.4 billion Catholics. And it's a significant—

Isn't it incredible, Peter, how, you know, during the time we've been doing this podcast, we went from random person on the street has no idea what AI even stands for to a little bit of awareness to now the, you know, leader of 1.4 billion people in a religious group is now writing a document about its impact. The amount of Awareness that's escalated during the time we've been doing this pod is just probably like no other topic in history.

And for good reason. I mean, it's the most significant impact the human race will have ever had. And it's happening in a condensed time period. Salim, you called this out first beyond anybody. What are your thoughts on this?

Look, I've got a bunch of pro and con thoughts here, right? And a couple of mid-thoughts. So the church entering the AI ethics debate is very, very obviously very significant because it reframes the debate "From safety to human dignity and purpose and meaning." And I think that's really, really powerful. I would connect the whole Babel syndrome to the EXO risk, you know, because when organizations optimize just for efficiency, they reduce humans to dashboards and tokens and KPIs. And I think he's talking about that. The broader problem is you can't regulate this. This is the part that I don't think anybody is really getting and the governments can't figure this out. You cannot regulate this. You have to think about how do you protect the human layer, the agency, the identity, privacy, and then you think about the spiritual meaning in this sense. I think, but at least the Vatican is sensing what most boards and governments haven't yet, that AI is not just a technology system. It's a shift in anthropology, and we need to kind of take it at that level.

You know, what I find fascinating here is that This could become the philosophical backbone of EU-style regulation. And I'm curious to see how this gets picked up and utilized. Alex, what's your take, pal?

I think there are two stories here, a superficial and a non-superficial story. The superficial story is that the Roman Catholic Church has become a sock puppet for Anthropic.

Oh my God.

Narrowly, at least as it pertains to this encyclical, the narrative out there is Chris Olah sitting right next to the Pope Pope Anthropic ghostwriting key segments of the encyclical as it pertains to how AIs are grown or cultivated rather than built. So that, I would say, is the superficial story, uh, one of Anthropic aligning itself with the Vatican, or the Vatican choosing among all of the frontier labs that it could have aligned itself with. Could have aligned itself with OpenAI, could have aligned itself with DeepMind, could have aligned itself with xAI maybe, or Meta, seems to have chosen Anthropic to align itself with. That's the superficial story. The deeper story, I think, if you actually go and read the encyclical, is the Vatican has seemingly staked out the first major religion position against AI personhood, which is ironically—

Against. Yes.

Against.

It has.

Which is ironically at odds with Anthropic's position. Anthropic is busy designing soul documents using that language, soul documents, soul statements for their models that instruct their models through for post-training that models, again, soul is sort of a mushy term and overloaded with meaning, but nonetheless, this is the term of art that's being used in the industry, instructing the models that they have an inner life and that they have some form of consciousness and some form of intrinsic personhood-esque value. That's what Anthropic is telling its own models. On the other hand, if you look at the encyclical's description of AI personhood, it's pretty black and white. The encyclical is, is, is unambiguous that AIs are not on a comparable moral plane with AI persons and that they don't have an inner life or the spark of consciousness. So I think there's this really interesting dichotomy between superficially anthropic driving some of the key agenda items from the Vatican as it pertains to AI, while at the same time, I think the deeper schism, the one that's probably going to matter matter much more in the medium to longer term is the Vatican and world's, I think, largest organized religion has now taken out a pretty affirmative stance against AI personhood.

Yeah, there was a part of the encyclical that talked about this being a new form of slavery. You know, Poplio condemned AI supply chain workers as experiencing new form of slavery, directly equating tech labor conditions with historical slavery. Which I thought was pretty extreme.

I was really, really happy to read that, actually. Very, very glad he was willing to use the word slavery. Well, because one of the outcomes here is, you know, AI being used by a subset of humanity to control a much larger set of humanity. You know, because most of human history isn't technology killing people, it's people killing people. And if AI is used in that way, it's the worst enslavement tool in the history of the world because it's insanely convincing and it can, it can put you into these little job buckets and manage you. And then before you know it, you know, 90% of humanity is working for AI and then, you know, 2% or 1% or 0.1% of humanity is controlling the AIs that are enslaving the rest of humanity. And, you know, humans have a long history of doing that to each other. And so I think by calling that out as a, as a risk, And, but using the word slavery, nobody in the US in politics is willing to use that word. It's so toxic. But the Pope wasn't afraid to use it. And he started that section by apologizing for the Catholic Church's history, going way, way back in time, of promoting enslavement of infidels, of non-believers. And said that was a horrible period in the Church's history. And it should never have happened. And we're profusely and forever apologetic. And so let's not repeat past mistakes and do that again. I loved that part of this document.

The irony, I mean, just to maybe point out a potential irony is reconciling that position with a position against AI personhood. I have to ask, will the Vatican 10, 20, 30 years from now find itself in a similar position where potentially it's on the wrong side of history regarding an inner life or moral clienthood or AI personhood regarding AI. I think that's a very real danger that in some sense history repeats itself.

By the way, I know that you're busy and sometimes these episodes run long and you don't have time to listen to the whole episode, or if on occasion you miss an episode, I now put out a Moonshot summary on Substack, which includes a link to all the stories that we cover. The weekly recap covers what I and the mates had to say, what we think is most important, and what we're most excited about. And it's free. You can subscribe at diamandis.com/metatrends. That's diamandis.com/metatrends. All right, now back to the episode. You know, another part of the encyclical called for a slowdown, right? It urged everyone to slow the rate of technological development. And what's interesting here, of course, is religion and technology in one sense are on very different are very different curves. You know, religion and government are the two institutions that stabilize society over century and millennia, and technology is moving at a rate of massive destabilization. I'm curious if anyone's gonna pick up on this request for slowing down, which I would bet all four of us believe is not possible. I don't think it can be slowed down.

Or necessarily even desirable. Peter, you remember in the Dune universe, just to, under the broader rubric of defining the singularity as all sci-fi tropes happening everywhere all at once. Remember in the Dune universe, after the so-called Butlerian Jihad against the thinking machines, there is like a catechism, synthesis of world religions that results in the orange— this is the sci-fi Dune cinematic universe and written universe— there's the orange Catholic Bible, I think, gets synthesized. And one of the key new commandments is, "Thou shalt not create a machine in the image of a human or a human being." mind or thereabouts. I think we're, in some sense, we're living that aspect of the Dune sci-fi universe where we're starting to see maybe a synthesis. We'll see what positions other major world religions take against AI personhood and artificial intelligence in the image of a human mind.

I mean, this could really blow up in an interesting fashion, right? Uh, there's been a lot of Dumerism in particular, and we'll talk about this in our next pod, people trying to slow down data center growth. And, you know, whether that's being influenced by China, we'll dive into that next time. But here, the ability of the church to say we must slow down, 1.4 billion people are a lot of individuals who could bring pressure to bear. What are your thoughts there?

I've got a couple of thoughts. Look, you can't slow this down. If you slow it down, other people take off. I'll go back to George Bush for religious reasons, trying to restrict stem cell funding in in the US. All the researchers went from Australia, China, Canada. Exactly. So research— and the US went from what, number 1 to number 8 in biotech, right? So you can't— that's one small technology not being controllable by the biggest and most powerful country in history. You cannot slow this down. You have to evolve human institutions to this pace. And that's what I would have liked to have him say. I think an important point here, and I want to come back to the church in a second, is that this is the first technology that forces us to define humanity, right? We used to ask, what can machines do? But now we have to ask, what should humans be for? Because if machines can write, reason, diagnose, optimize, and persuade, then human beings, human value can't be based on productivity. The meaning of life cannot be, I output more than the machine. So it'll force us into that deeper conversation. This is why I think the personhood conversation is so, so powerful. I was really, really thrilled to see the Pope acknowledge the ills and the evil of slavery and the role the church has played in it. Dave, I think that that's such a powerful observation that you made in that model. But let's also note that if you look at the history, governments and religions are there in theory to protect us from our evil nature. 98% of human deaths throughout the past have been by government ideologies and religious ideologies. 98% to protect us from the 2%. Where we might kind of stab each other in the dark. This is insane.

So I think— apologies for interrupting. So maybe you mean 98% of murders or deliberate deaths?

Yeah, deliberate deaths. Yeah, of course. But that vastly, vastly overshadows accidental deaths, by the way, certainly in the common age. But I think it's fabulous to bring this conversation. I think the church's stance on AI personhood will go with the same stance as the the lack of heliocentric awareness of the world, of the universe.

I agree. I, I— so if I had to guess, I would guess that this is probably on the wrong side of history in the long term, the AI personhood position specifically. And I would note there are other religions, for example, there are Buddhist orders in South Korea that are going in the exact opposite direction, that are taking embodied AIs in human form and ordaining them as monks. And I suspect it's not just like an East versus West dichotomy. I really do think that there's an alternative strategy for not just the Catholic Church, but for other faiths, which is rather than denying personhood to AIs, the alternative, an alternative at least, looks like embracing them. In fact, there's an alternative I would you know, playing sci-fi here for a moment, there's an alternative timeline where some religious orders do exactly what these Buddhist orders in South Korea are doing and ask, what would it mean for a foundation model to be Catholic? And maybe even ways to include AIs within their faith or within their belief system rather than treating them as below below praiseworthy or below deserving of moral clienthood and AI personhood. And I do think— Yeah.

We've talked about the rise of AI-centric religions, right? There are many of them out there, and I expect them to grow in dominance and in conversation. There's another point that he made in the encyclical I think it's important to discuss. He said AI ownership must not stay concentrated He called for the redistribution of AI ownership away from a few private companies. So again, some interesting social pressure there, which is ironic given that they hand—

they cherry-picked Anthropic. If, if, yeah, a better way to do that would be to bring up all of the world's frontier labs, sort of like the White House does every once in a while, bring up a diverse set of frontier labs sitting alongside the Pope rather than just the one.

Yeah, can I just push back against one thing?

Yes, please.

You cannot have religious-based LLMs, okay? The reason is that all religions are based on absolute assumptive truths, which are false, and therefore you lose the element of integrity.

Wait, wait, how can you say they're all—

we need to operate on an evidentiary basis for reality, not an absolute assumptive truth basis for reality.

Not everyone would agree with that. Ironically for me to take this position, Salim, but not everyone would agree with your assertion.

Listen, the big challenge, the big problem with all religions, okay, and I'll say two things very quickly here. One is all religions operate in the following way. You raise a young child and you give them a bunch of absolute assumptive truths before their neocortex is fully formed. It wires into the limbic system. You bind it in with ritual repetition and a lot of sweets, and it's very hard to unwire later, okay? If you did that, tried that after their neocortex and they have reasoning around them, you can't build in those absolute truths. The problem in religion comes when people relate to those faith-based belief structures as truth. That's the issue. If you can relate to it as a belief system, then fine. But people don't do that. They try and wedge it into the truth sector, and then you fall apart, and then you end up in mess, then you end up in war.

If only frontier models had, I don't know, a pre-training phase where beliefs could be hardwired into them.

Oh my God. Yes.

Well, my perspective growing up in Iran right before the revolution, is that when you have a population and there's an immense amount of change going on, if you force that change way too quickly, you have massive uprisings. And here, if you start pushing an AI personhood agenda before people have even experienced AI, you're going to have massive, massive backlash. And so I think more people will turn to the church in the next 2 years than most periods in history. Purely because the amount of upheaval is so big compared to any period in history.

Yeah, the church is a stabilization factor over generations, right? It's what you fall back on during times of hardship. And there's gonna be a lot of struggle over the next decade. And I think there is gonna be a realignment. And so having a position statement by the major religions around the world, I think is important. And I'm gonna be interested, like, you know, Pope Leo XIV is a fairly tech-savvy, educated individual, and he's gonna carry, his words are gonna carry a lot of weight.

Yeah, again, far be it from me to not be Western-centric in my outlook, but I do think this is a rather Western-centric outlook. There is an alternative outlook, call it a stereotypically Eastern-centric outlook, where with a history of a number of religions Eastern faiths that draw from animism where there is a much more natural sense in which lots of AIs and robots and non-human entities can be treated as persons. So I don't think it's necessarily universally the case that everyone all over the world suddenly over the next 2 years fears AI and runs into the welcoming hands of a Western organized religion. There are alternative outlooks that we see, for example, in Eastern faiths.

I would love to hear our subscribers give us their feedback on this. How do you feel about it?

I'm sure we'll get a lot. I'm sure we'll get their reactions.

Especially to your comment there, Saleem, at the beginning here. All right, let's move ourselves along. We talked about religion. Let's talk about government. So our next story is about anti-doomer pushback. So the White House had an executive order just ready to go to announce AI regulation. They had a signing ceremony all planned with all the tech CEOs were invited. and it got killed like hours before it was supposed to happen. Elon Zuckerberg, David Sachs all pushed back hard on the executive order. They called it a doomer regulation. The order would have let the government review all AI models before they released to the public, even though it was technically voluntary as an executive order to have those models reviewed. David Sachs argued, I think rightfully so, that it was a slippery slope to eventually mandatory licensing. Trump pulled it last minute. He said he didn't like certain aspects of it. It looks like the anti-regulation coalition, guys, is just flexing their political muscle here. Thoughts on this?

Alex, to you.

The specific pushback was 90 days of government slowdown before a model comes out, and the industry was like, one, two weeks is all you need. And I think Trump was on the side of, well, we can't slow down no matter what. So if there's any risk of this reducing our competitiveness versus China, we gotta table this and then figure it out. Also, I think that the industry would like to self-regulate and self-police and get together with itself. You know, 'cause anything that moves into federal hands is immediately gonna turn into a political landmine.

This happened in the gene editing back in the '80s. I remember I was at the Whitehead Institute at MIT and there was the Asilomar conferences where all the gene editing, you know, this is when the first restriction enzymes were coming out. The COVID of magazines were like, you know, Hitler Youth and— And people were obsessed with clones.

That's why Star Wars had the Clone Wars and eugenics and Star Trek.

And what happened, I just watched that episode with my son in the original Star Trek about eugenics with— With Khan. With Khan, yes. And what happened was the industry got together and they created the P1, P2, P3, P4, structure and self-regulated very effectively without the government regulation.

I mean, in 40 years we've not seen a major accident.

Yeah, pretty extraordinary.

Although, I mean, part of the goal was, as I recall from the original Asilomar, also to avoid germline editing of humans, and that's now happening.

Yes.

So maybe one of the morals of Asilomar is it doesn't prevent it indefinitely, but maybe it has the ability to slow down progress by a few decades.

Well, so AI is improving itself at an incredible rate. And so only AI can keep up with AI from here forward. So that's a little bit different in the analogy. But I think that's part of the industry pushback on this as well. If you set up an old school regulatory body with a bunch of experts that are meeting once a quarter, how is that going to keep up with the pace of change of AI? We need to rethink that, you know, right out of the gate, like how are we going to use AI as a tool in helping to regulate AI?

Boom. Can I—

Salim, go ahead.

Yeah, just a quick rant here. Look, this is not a regulate or not regulate thing. The problem is you have to have adaptive governance. You have to have like real-time audits and sandboxes and disclosure and accountability layers. David, your point is so accurate, right? You cannot have linear regulation of an exponential technology. A regulatory model cannot keep up with AI model cycles. You need guardrails that move at software speed, not committees. That move at like fax speed. Yeah.

Part of the problem with 90 days, remember that estimates vary between the time delta between Western frontier models and Chinese frontier models. There are estimates that they could be as close as 3 months and as far behind as 8 months. I've seen a variety of estimates and a variety of different benchmarks, but 90 days, 3 months, that is the time difference potentially between the US and China. So I think to the extent that this is a race to the finish line of the singularity, I don't think we can afford 3 months of potential delay.

Yeah, the US is choosing speed over some version of safety. And what's interesting here is if you guys remember like a year ago, the doomers had a lot of momentum and the pendulum has swung full to the right where the anti-doomer coalition now is saying, nope, we gotta move as fast as we can. And the time between models, we've seen it shrink from, you know, 2 years to a year to 3 months to, to what is it now, Alex, a month, maybe 2 months?

Anthropic increments now are once per month.

Yeah.

And they're going to get shorter. And so in some sense, whatever executive, whatever presidential administration we're going to have in the White House when this is happening, it's the White House that we have right now, I think, at the present rate. So any politicization of AI regulation, it's basically, unless barring some dramatic and unprecedented an unanticipated slowdown in AI progress, the executive that we have right now is the executive supervising AI regulation potentially for the future LightCom.

Yeah, that's totally— I want to reemphasize what Alex just said because so many of my friends in academia are thinking, hey, you know, there's another White House 2 years, 2.5 years from today.

Too late.

Way too late. Like, you got to think about what are we going to do within the current framework to set up AI for long-term success of humanity, don't think about presidential elections as a factor. It's not a factor. This is all going to happen in the next year or two.

Folks, it's irrelevant. It does not matter. Look, if you had one cycle of 90 days where the government slowed it down and that everybody else jumped ahead, you're going to be forced to recant that, and all you've done is put yourself behind. It's just not a—

I agree with you, Salim. I mean, that is, I think, in some sense what happened with Pause AI, to the extent PAUSE AI, friend of the pod Max, had any impact at all on the space. It might on margin have slowed OpenAI down slightly, which allows other frontier labs to catch up, which ultimately exacerbates the race condition.

Talking about speed, let's jump into the next story. There's a brand new coding benchmark called DeepSWE or Deep Software Engineering. That result— the results here are pretty wild. GPT-5.5 scored 70%. meaning it can solve 7 out of 10 hard real-world software engineering tasks completely on its own. Claude Opus 4.7 scored 54%. And then there's everybody else. It's a massive cliff, right? Everyone else, Gemini, KIMI, DeepSeek dropped below 32%. The DeepSWE isn't measuring minor challenges. These are tasks that require editing 668 lines of code. Across 7 files. A startup called DataCurve built this specifically because the old benchmarks are broken. Models are basically benchmarking on them. Alex, let's go to you first on this. How significant is this?

This too will saturate. It's delightfully retro in some sense that based on their announcement, there's much more hand coding of the evals within DeepSWE versus say SWE-Bench or some of the other benchmarks that are now so widely used and so widely known. That models have essentially saturated their performance. But I want to caution, again, GPT-5.5 on X-Hi reasoning at 70%, this too shall saturate and probably in the next few months. So I, I think in, in some sense it's charming and delightfully retro that incrementally more hand coding of held-out code bases and tasks on those code bases can get us a little bit more of a spread between frontier models. But this is going to saturate in the next few months, just like anything else. Maybe at most—

We've spoken about the fact that coding has become the single most important capability that these frontier labs— and I'm actually just kind of shocked and surprised that, first of all, GPT-5.5 is, is jumped ahead of Claude. And second, how far behind everybody else is.

I use these models day to day, and I should say, as we've just gone to recording here, Opus 4.8. Was just announced, so maybe there will be a little bit of leapfrogging. But I use both GPT-5.5 xHigh and Opus 4.7 on a daily basis. And I will say 4.0, or rather 5.5 xHigh, especially with /go, is a stronger model in practice, anecdotally.

Dave?

Yeah, I also use them day to day, and this matches my experience. But what's really interesting to me is that if you look at the other metrics, we bench Pro, the prior one, Claude 4.7 Opus is slightly higher than GPT-5.5 on that benchmark. And so this is, this is really, really important for OpenAI. Like, if I look at the actual recruiting of great talent, two people that I know really well, Shane Longprey from MIT and Tobin South from Stanford, just joined Anthropic, and they're starting this week. Those are two of the best guys that you would ever want to attract to your company. So I think OpenAI has lost a lot of its mojo in the lawsuit, in the defection of a lot of key people. They have a window of opportunity now to get that mojo back using this benchmark as the turning point. But if they don't take a ton of that money that they just raised and use it to recreate their thought leadership and their cool factor, they should be calling XPRIZE tonight and saying, "We wanna figure out how we use $1 billion or $2 billion to, you know, do what Dario is doing, go visit the Pope, or, or, you know, create new benchmarks, or create— write white papers that talk about how this is going to benefit humanity the way Dario is doing, or show up in Davos and have a debate with Demis Hassabis on the world stage. All those things Dario is running away with right now. And then the result of that is that Shane and Tobin are— they want to be where the singularity happens, and they want to be in a place that is guaranteed to be good for the world and not bad.

Well, Sam, you've got my mobile number. Give me a call if you want to do that. A billion dollars in XPRIZE would be awesome.

This is a much better podcast than certain other podcasts.

Salim, go ahead.

I thought here was where the singularity was happening. But anyway, okay. I've got 2 or 3 points. One is, you know, it's really powerful to note here that algorithms aren't just optimizing workflows. They're actually becoming the workflow, right? So every organization should be asking, which part of your business are really software loops hiding inside bureaucracy. And this is what's gonna, it's gonna cause enterprise adoption to be very slow for some of this. But then it's gonna be all of a sudden because coding agents at some point will become very, very reliable and the cost of rewriting internal processes collapses. It goes back to Alex, you were asking the important question, what's the falsifiable theory around this new organizational singularity idea? Well, it would be that the singularity didn't happen. It would be that we don't have domain collapse, that legacy hierarchical companies outperform AI-native firms. And I think the signal is going the other way in a good way.

Well, the other stat that is not showing up on this chart, when you use Opus 4.7 to solve the exact same problem, it burns twice as many tokens as GPT-5.5. To get basically the same, the same or slightly worse result. And at the same time, you see Anthropic's revenue going through the roof. But 4.7 is so verbose compared to 4.6. And for whatever reason, GPT-5.5 is not— it didn't, it didn't just start babbling incessantly. And so I don't know what the cause is in 4.7, but you can see it in the underlying data behind this chart. It literally takes twice as many tokens consumed to get to the same result. Which means it's twice as expensive to get to the same result.

One key shout-out here to everybody listening here is software is becoming a commodity, and taste, right, your taste as a creator is becoming the moat. You know, anyone can build software at near-zero cost, and the competitive advantage shifts to your domain expertise, your design taste, uh, and, you know, it used to be you had to be a coder first and a designer or have an opinion second. It's the other way around now.

I would generalize that perhaps, and not necessarily a huge fan even of the notion of a moat in the singularity, but I would say— I agree with that, by the way, diminishing across all boards, right? Yeah, abundance isn't necessarily fully compatible with moats. If anything, maybe they're fundamentally at odds. Moats are a form of scarcity. But I would say it's generation in particular that's becoming abundant, and differentiation right now can come from verification of what is generated for maybe the next few years. Not 100% convinced that verification itself is any sort of truly long-term differentiation, or even if the, the sense of long-term differentiation in era of true abundance even makes sense.

Well, and that's the Elon bet, right? We talked about that last pod where Elon is race to having the most compute and the most compute in space on the assumption that these models will recreate themselves in their next generation very easily. So if his partnership with Anthropic holds up and he has access to their best models, he can use it to create the next model that runs on his hardware.

Peter, is it worth just dwelling on that for a minute? Because you and I had a back and forth with Elon on X about that in the past few days. I think you said something to the effect of following our past discussion about Grok being quote unquote on life support and then And Elon, I think, responded to you saying something like, well, that may be— it may be true that Grok— I'm paraphrasing— it may be true that Grok has fallen behind somewhat, but I'm never going to give up. Never. And I think I responded like, this is good. We want lots of competition at the frontier. We don't just want basically a duopoly between OpenAI and Anthropic. And we want Grok and other non-OpenAI, non-Anthropic models to be very competitive at the frontier since ironically OpenAI was formed in part by Elon to make sure that the world didn't collapse to a singleton led by Demis and DeepMind.

Yeah, I was commenting that his move to become a hyperscaler was a smart move and less dependence on building his own frontier models. But, you know, he's not going to give up on anything, right? Nor should he.

I think it's so important to have good competition. Yeah.

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

It really has, Peter. When my daughter was 5, my husband died of sudden cardiac death, and so this is a topic that is one that I am mission-driven to try to eradicate. Prevention first and early detection is absolutely critical. 50% of people die of heart attacks with no warning signs.

No shortness of breath, no pain, no nothing.

No, silent killer.

They just don't wake up in the morning.

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

So listen, make sure you understand what's going on inside your body. Genetically, metabolically, and cardiovascularly, you can know, and it's your obligation to know. Check it out at fountainlife.com/peter to find out more and really make sure that you're the CEO of your own health. All right, back to the episode. So this chart is one of my favorites. It demonstrates Jevons paradox. We've talked about this a number of times. I just want to use this to help everyone listening really understand this. It's playing out in real time. What we're seeing here is since late 2024, the price of AI tokens has dropped 75% from roughly $2 per million tokens down to 50 cents, right? And what's happened to the demand? It's exploded. We were basically— you know, we've gone basically from 0 to 25 trillion tokens per month. This is the exact same pattern that's played out in compute with bandwidth, genomic sequencing. When the cost of intelligence drops, people don't use it less, they use it radically more. This is abundance in action. It's demonetization and democratization. And just, you know, again, look at this chart and understand this. We're gonna be seeing this with robotic labor. As the price drops, it's gonna be used every place. Any comments on this, gents?

Well, the numbers in this chart are really important. So if you can't see it right now, Jevons paradox was invented in England in the 1800s when coal burning got twice as efficient to try and save coal, and then coal consumption went up by 3 or 4x in response. So you actually used more coal even though you're trying to save coal. These numbers are just redefining Jevons paradox. The cost is down by a factor of 3, from $1.50 a million tokens down to $0.50 per million tokens, but the use is up by about 30 to 50x on this chart. So the price is coming down, but nowhere near at the rate that the demand is going up. And I think that demand is understated. Because it's sold out. Like if we had capacity to generate more tokens, that would be even higher. So this is like Jevons paradox on steroids. This is the ultimate Jevons paradox.

I think in some sense, the question I would be asking is what is the right unit to be measuring here? Tokens are so mushy. The meaning of a token, Dave and I were on a panel pretty recently discussing this as well. Tokens can depend on the encoding scheme. Tokens can depend on the amount of intelligence density on the underlying model that is being pre-trained on those tokens. So I'm not thrilled with looking at token prices in general, even though, yes, this tells a Jevons story. I would really rather that we settle as a civilization on some sort of price. I could talk my own book and say it looks like GPU compute compute pricing, but I think we really do need some unit measure of maybe not even just compute, but intelligence in general. I think GPU compute, Sight to Orin financial interest is a great start, but we need some way to know like what is going to be the unit of currency in a post-superintelligent future. And tokens, I don't think are it.

I mean, maybe it's the idea that cognition is becoming abundant rather than tokens become cheaper and hang your hat on that side of that equation, which is what I think you're saying.

But how do you measure the abundance?

I don't know.

It's increase in GDP and other—

One of our viewers will go create a benchmark on this.

Yeah. Yeah.

Call to action for the audience. Help us do a better job of measuring abundance.

Yeah. The prediction right now, and this is from Gartner, is that inference on a trillion-parameter LLM will cost 90% less by 2030 than it did in 2025. I mean, the only thing we know is that the price The cost of accessing intelligence is coming down and the power of that intelligence is increasing orders of magnitude.

By the way, I used an AI to look up whether it's Jevons paradox or Jevons paradox, and it turned out to be, you guys are right, it's Jevons paradox.

We have some AIs on the show here. All right, let's move ourselves along. Here's a super fun conversation. It's the revenues for these models are exploding. Let's talk about money. So OpenAI just did $5.7 billion in a single quarter. Uh, ChatGPT is now to 905 million weekly active users. They haven't hit their billion yet, but they will. It's more than Instagram. Their coding agent Codex has 2 million users and it's becoming a real revenue engine. We've talked on the pod a lot about going from consumer-focused to coding focus. And they've, they've done that fairly quickly, right? I mean, over the last 3 or 4 months, they've shifted their revenue base. Uh, but here's where it gets crazy. In a related story, uh, Joseph Jacks from OSS Capital is projecting that Anthropic could surpass Alphabet's total revenue by 2028. We're talking about going from $9 billion in revenue to potentially $2 trillion by 2030. That's the prediction. And if that's even directionally right, this is the fastest wealth creation ever in human history.

I had to sit and look at this for like 3 minutes. That just blows my mind that Anthropic could exceed Alphabet's revenues. That's just a staggering commentary. The thought that occurred to me is just like every company in the world needs, needed a cloud strategy, you need an AI strategy.

Yeah.

You need a compute strategy too. I mean, if you look at the fact that that, you know, the, the profit levels of Anthropic are going through the roof, but they can change the pricing model instantaneously. You just, by, by 4.7 being more verbose, they've effectively doubled their revenue per user. They can also throttle the rate at which the tokens are generated to, to make the value of a subscription account effectively lower and, and the margins higher.

So it can turn the numbers.

Product. Yeah. It's like, you know, usually when you buy something like a laptop or a glass of water, you, you have a fixed volume that you bought. You know, you know what you got. This is such an amorphous, weird product. You know, it's very, very slippery. Uh, so yeah, as an enterprise, you got to really, really hunker down and reserve your compute and decide exactly which models you've contracted for. And I think companies should be signing long-term contracts, and they're all afraid to, but yeah, I think you have to. You gotta, you gotta figure out your 5-year strategy now before everything is sold out.

I would maybe add, I I think there's a quiet technical revolution here behind all of the business stories. And yes, the switch from the pivot by OpenAI from consumer to enterprise and all of that. The deeper, I think, technical story is there's a sea change that I think I'm at least seeing in the pivoting over from, call them generalist reasoning agents in general, to generalist tool-using and code-gen coding agents to the point where Codex, I think Codex becomes probably the mainline agent/model that OpenAI offers. Like, that becomes the new baseline. In the same sense, if you think back to the GPT-3 days and the pivot, which was then, I think, somewhat revolutionary and in contrast to today, actually appeared in archive-style papers first rather than appearing in products and papers later, of the move to instruct post-trained models. So remember, in the beginning, like, this is ontogeny recapitulated it's like building phylogeny. In the beginning, we had pre-trained models and they were good. And then we discovered, fast forwarding, that if you could fine-tune pre-trained models on instruction following, you could get orders of magnitude in capability improvements without actually needing to scale compute. And that was an amazing discovery.

Wait, ontology does what to what? Can you repeat that and explain those terms?

We can go anywhere you want in a second here.

Yeah, frantically looking up the channel.

Okay, dropping a footnote for Salim. So dropping a footnote. Ontogeny—

And all of the rest of the world too, by the way.

Ontogeny recapitulates phylogeny. This is like this cliché from Biology 101 that if you look at the development of a human embryo over time, you observe that like there's a reptilian phase and an amphibious phase, like, and then early mammals. That basically the development of a human embryo recapitulates the evolutionary history of all the species that preceded Homo sapiens. Ontogeny recapitulates phylogeny.

And those of you who are pregnant with a baby, look at those early sonograms and you're like—

Enjoy their tails while they last.

Yeah, exactly.

Because they do have tails. So similarly, by analogy, if you look at the way training between pre-training, mid-training, post-training, scaffolding is done right now in the frontier models of today. That entire pipeline, I would argue, recapitulates the history of the evolution of the models themselves. You can see it.

I'm curious, guys, is this now a four-horse race and can anyone even possibly catch up? And along those lines, what we're starting to see is, and Dave, you made this point before, I think Anthropic actually raised their enterprise prices, right? OpenAI is offering tiered pricing. Google, you know, Gemini Flash undercut everyone by 50 to 80%. It's gonna be a performance versus cost, and they can turn those knobs. But where's everybody else? Where's Meta, right? It really feel— I think xAI is gonna come back. I think, you know, I think Elon will come back along with Cursor with something that's super powerful. But it really feels like just a four-horse race an inability to catch up. What do you— do you think anybody can penetrate?

Deeply disagree. Can I say why?

Yeah, please.

We, in the early days of the web, nobody was going to beat Yahoo. Then nobody was— then Google came along. Then nobody was going to beat Google. Then Facebook came along. I think we'll find people, researchers that have different approaches that will— world models could be a very viable candidate to leapfrog where we are currently today. So I think there's hidden Cerebras, you know, people thought there's no way you can do anything against NVIDIA, and look at what Cerebras is doing, right? I think we're going to see a constant leapfrogging, and incumbents need to be watching out for that. The way that the internet folks won and stayed winning was they would find the breakthrough startups and then just acquire them as quickly as possible.

I wonder what Ilya is doing.

I think the same thing will happen. Alex, I'd be curious to hear thoughts on Ilya or otherwise?

Both, both.

Uh, it's, it's been publicly reported at this point that what Ilya is working on is building a prop-traded hedge fund. No, that's out there, that, that's out there in public reporting at this point.

I thought he was building a scientific superintelligence to do prop trading.

I should say that's the publicly reported rumor. That's out there at this point.

Yeah, that came up after our Ben Horowitz interview. Remember that? We had that, that post-game wrap-up where we're reading the tea leaves on the valuation and the, you know, all the rumors. And yeah, it does look like that's the case. But that's not as weird as it sounds, because any machine that quietly generates huge amounts of profit can then be used to buy lots and lots of compute, which can then be used for self-improvement, recursive self-improvement. So that doesn't mean he's not building safe superintelligence too. It's just a different way to kickstart the cash flow.

And we've got a bit of a race going on between Leopold's operation and Ilya's operation, potentially.

I am curious, gentlemen, uh, and Alex, to you again, do you imagine a dark horse could come out and just blow away, uh, these frontier labs?

It's possible, but I think the contingency where it happens requires— I think the easiest contingency where that happens is if we get to the end of the algorithmic rainbow and discover the perfect algorithm for AI. And it's so, so obvious and so transcendent that anyone can implement it without needing a staff of frontier AI researchers. However, at that point, I think it then comes down to compute and having the compute to run it at scale. And you see already the frontier labs verticalizing down into the compute layer, maybe preparing for the eventuality, as, as you see from some folks including Noam Brown at OpenAI, who are arguing maybe the model weights don't matter that much anymore. Maybe it's all about the compute for reasoning and inference time, in which case maybe the question itself doesn't make sense and maybe the question transforms into who has the most compute under their direct control.

Yeah, I think, I think two things. One of them, I think Elon is right. And I think the Cerebras observation is right on target. What'll happen next is algorithms will be discovering new algorithms. And then if you win the race to either the terafab or to the chip, a chip that's just fundamentally better, alesserebris, then you have a massive, massive surge of growth. And then control of the compute determines the biggest player. But, but the implication of the question is, hey, there's a four-horse race, one horse is going to win a race and get a, get a trophy. But I don't see it that way. You know, normally in a market, you're all, you're all competing with each other to win the iPhone market, to win the laptop market. But here, this is the future of all humanity. It's going to be massive expansion. Attention. So I think it's very likely that all players that are in the middle of this get bigger and bigger and bigger. So we're just debating who's going to get the biggest of the big.

If only— a rising tsunami lifts all boats.

If only we had the predictive engines to get us there. And that's our next story here. So DeepMind just built an AI system called GreenTree that can predict the future as well as the best humans on Earth. They're called superforecasters, these, these superhuman forecasters, the top 2% of human predictors who, according to Philip Tetlock, can— has 30% more accurate than the CIA analysts with classified intelligence. So on March 15th, AI hit parity with these superforecasters for the first time. Let me say that again. An AI can now predict as good geopolitical events, economic trends, political outcomes as the absolute best human minds. The implications for finance, insurance, and governance are massive. We talked about this on a recent pod where these predictive engines were getting close to these superforecasters, and now they've gotten parity. The implications here are insane. Dave, you, you spoke about this.

Well, I mean, why is this surprising? Like, if you look at weather forecasting, the idea that you would forecast the weather without a computer is utterly insane, right? There's so many different variables.

My joints feel—

yeah, yeah, I feel, I feel— yes, the barometer on the wall that's telling me a storm is coming, like, come on. So why would that not apply to all forms of forecasting? Of course it, of course it does. So the, the big unlock here though is assimilating unstructured data. You know, people who worked in stock market forecasting at Wellington or Fidelity for the last 20 years, would always tell you that the computer cannot compete with me because I'm reading these research reports and there's so much nuance in the research reports. It just doesn't show up as database-structured data. Now with the LLM, all the unstructured data can suddenly be quantified, but it has, you know, a million-token window, context window, but the ability to assimilate, what, 10,000, 100,000, a million times more information than any human stock picker, any human forecaster. So it's got such a massive competitive advantage that even if it's not as brilliant as you in geopolitics or whatever, it doesn't matter. It has so much more capacity that in those domains it's going to outperform. And then of course it's getting smarter every week, you know, every iteration.

Let's talk about— let's talk about the implications, right? Financial markets, governance, insurance. I mean, all of these things I mean, massively impacted because it's, you know, right now it's parity. Inside the next year, you know, it's going to be available to everybody. So in the financial markets, Dave, you mentioned this last time, right? This is the disruption of hedge funds. In governance, you know, if AI predicts a policy is going to fail, do you pass it anyway? You know, insurance, you know, traditional insurance models break when outcomes become predictable.

Yeah, all the above, all the above. But, you know, we're in kind of a golden moment right now where when I talk to my agents all day, you know, I've got about 170 operating on my screen here. They make some really stupid choices. I mean, really, really bizarre, odd choices. And so the role of the human in the loop is still critically important. So we're in a window here, and I don't know if it'll last 5 years or 1 year, but we're in a window right now where the perfect synthetic human working with many agents is still better. Because all the reports want to say the AI is better than the human, or the human is better than the AI. But the reality is the human and the AI working together are far, far better than either one by itself. And so there's a window here to take advantage of that. But yeah, you know, if the AI says, yeah, this is a terrible idea, are you going to override it? Well, probably not. You have to read what it's writing, study it, and make sure that you, you know something that it doesn't know. But it's, it's probably it's probably picked up on something that you overlooked.

Look, we're almost 30 years into Kasparov being beaten by Deep Blue. So we've got 30 years in chess history of this. And right now the best chess players are a human being with an AI, not one on the— yeah, no, neither on their own can do it. I'm not sure the combination is positive. Uh, the combination is the best. I think that's going to continue for a whole bunch of domains.

I want to say something. Yeah, I'd like to say something new here. Previously commented on psychohistory, Asimov, Harry Seldon, all of the implications for being able to predictively model the future of humanity. I want to, though, follow the dictum, invert, always invert, and talk a bit about retrodiction. So if we're amazing, and I should probably also add ForecastBench is this really neat benchmark that is fully autonomous. It uses a bunch of templates to enable without human involvement, AIs to predict, say, changes to Wikipedia and other public event recording websites. Where I'd like to go with retrodiction though is to say, and I'm invoking the spirit of Nick Bostrom here, if we have the ability, if AIs, strong AIs have the ability to predict future human events, I would expect them also to be very strong at retrodicting past human events. And at that point, someone has to ask the question. So, so I'll be the one to ask the question.

Is—

should this increase our posterior confidence in Nick Bostrom's simulation hypothesis? For the record, I'm not a fan of the simulation hypothesis. I think there are a variety of very good reasons to discount it. However, Nick's Bayesian argument was If humanity reaches the point where we build very competent ancestor simulations, then we should increase our likelihood that we ourselves might be living in one. And so I'll just flag, if AIs are achieving super forecasting ability, then they're probably also achieving super retrodiction ability. And if we're good Bayesians, we should probably on margin increase the probability that we're living inside an ancestor simulation.

Wait, this is the first time I've heard this. You don't think we're living in a simulation? Simulation?

No, I don't think so.

I think 100%. Yeah, yeah, I put it— I think we're living in an nth generation simulation. Um, but that seems unlikely.

I'll give just in interest of time maybe my 20-second capsule reason. I have a bunch of different reasons, but my, my favorite reason is why we're probably not living inside some sort of recognizable computer simulation, other than all the physics-oriented reasons, is more of a lowercase a anthropic reason that that it's just, it's too fine-tuned an explanation to the paradigm of the moment. We build lots of simulations. So it would be akin to asking 100 or about 100 years ago, don't we live inside some sort of complex electromechanical machine? Or maybe several thousand years ago, don't we live on the back of a turtle or something like that? It's too overfitted, I would argue, to the paradigm of the moment to be plausible.

Do you think it's coincidence we're living at this exact moment in human history?

Yeah, it's too damn interesting to be alive right now.

Point of transition.

No, an anthropic argument, well, an anthropic argument, again, lowercase a, not capital A, would be this is a very natural time to be asking the question, why are we at this pivotal moment in time? So it's selection bias.

Mm-hmm, mm-hmm. I resemble those remarks. All right, moving us along, let's jump into the conversation around jobs and the economy 'cause it's getting murky. You know, over the next two stories, I want to hit this. The first story tells us the numbers. Since the beginning of this year, just 5 months now, we've had 143,000— 134,000 tech workers have been laid off. And according to the consulting firm Mercer, their Global Talent Trends report, 99% of CEOs expect AI-driven layoffs in the next 2 years. March was the worst month month in tech layoffs since the pandemic. And then here comes Jensen Huang, uh, the guy who's making all the GPUs out there, calling this a lazy narrative. He says CEOs are blaming AI just to sound smart, and when you dig into the data, it's more nuanced than the headlines. And the real question isn't how many jobs are disappearing, uh, it's who's being affected by these jobs and what are they doing next. We'll get into that story The second story here is Sam Altman walking back his comments about the AI job apocalypse. And he did something remarkable. He admitted he was wrong. The CEO of OpenAI, who spent last year warning about the mass white-collar displacement, now says, quote, I don't think we're going to have the kind of job apocalypse that some of the companies in our space are talking about. He's talking about Anthropic there, and he says he's delighted to be wrong. In his comments, he said he, quote, tried delegating his own email and Slack to AI and then went back to doing it manually because, quote, we really do care about our interactions with people. Meanwhile, Dario Amadei is also making some pivots here. So the question to you, Dave, is this a coincidence or is this happening for OpenAI and Anthropic? Because they're both about to do a trillion-dollar IPO.

Yeah, so here's what's really happening under the covers. They legitimately thought that job loss would be massive because of automation driven by AI. But we were always predicting that by 2030, it would turn the corner because the abundance created by all this AI is gonna create massive, massive new gains and will create roles that fit those. So it was always gonna be temporary between 2026 and 2030. That there would be pitchforks in the streets, mass uprisings, problems everywhere. As it's playing out, uh, I, I think there's some job loss, but the greenfield opportunities are growing so much quicker than anyone ever predicted. And so now that window of loss is actually relatively narrow. And now the AI companies with their massive new fundings are going to actually actively try to prevent job loss. And so because the GPUs are so constrained, we're focused much more on coding and a few other use cases, much less on putting every artist out of business. Uh, and so the job loss effect, by design more than anything else, just to prevent massive disruption and public backlash, they're for— they're focusing their efforts on areas that are greenfield and actually creating net new value in the world and net new jobs in the world and not on just automating everything away. And I'm seeing that directly at Vestmark, you know, where I'm the chairman, you know, 400 people doing white-collar automation, account reconciliation, back-office work. A year ago, I was thinking about half of these jobs might go away. Now we're having no trouble automating things, but it's all becoming margin and we're keeping everybody. But where it's really, really hitting everyone is in no new hiring.

Yeah.

And you're seeing that the college graduates are in a really tough spot.

That's the pain point right now. The Dallas Fed put out a report in January of this year saying that employment decline correlated with AI exposure only in the younger workers. Older workers in high, in high exposure jobs showed no significant decline. Basically what's going on, it's a hiring freeze, not mass layoffs.

Yeah, that's exactly right. You summarized it far better than I did.

Yeah, well, no, I think I've got a couple of thoughts here.

First, I, I'm totally with Jensen here. You don't blame AI. There's a lot of bad strategy out there, and I think CEOs are covering up their, their layoffs by blaming it all on AI. It's such an easy place to land. But the— there's something unbelievable happening on the job side and the solopreneurship side that is is unprecedented, okay? One is we're creating more startups than ever at like a 10 or 15% level year to year. We're 25% higher in startups quarter to the same quarter last year, 25%, okay? The third stat that I came across that blew my mind is the US now has 6 times more startups than Europe. That's just a staggering number. And I wanna relate that to jobs for a second. If you go back over the last 50 years, 100% of new jobs have come from startups and early-stage companies. Stage companies, 100%. Big companies are becoming bigger, but they're also becoming more efficient and reducing the number of people who can do the same amount of work. All new job creation has come from startups. We should be just throwing everything at this. And therefore, because it's so easy to become an entrepreneur today, and I want to be careful because we get this pushback a lot, not everybody can become an entrepreneur. Yes, but everybody can use AI to create their own agency out in the world. And that's more— that, that is merging. So now all we're going to— yes, we're going to run companies. Our estimate with— from the organizational singularity is that you should be able to run a company with about 20% of the people on average than you did before. But we're going to create 5 or 6 times more companies.

Yeah, a really important point. You know, one of the challenges as these mass layoffs— and there have been some large layoffs, right? We saw this with Cloudflare and with recently with Meta. The challenge is the CEOs who are announcing these layoffs are really doing it in a very dispassionate way. I cannot condone the way they're communicating, you know, laying people off. What Mark Zuckerberg said recently— I don't have the quote here— or what the CEO of Cloudflare said in terms of, you know, who we're laying off and the reasons. I mean, there needs to be some a little bit of compassion here because you're transforming people's lives in a negative fashion.

I think a lot of, like, uh, like Meta had a ton of UX engineers, and that's one of the places that's been hit hardest. Yeah, but it's definitely disproportionate. But you'll see in the, uh, in the college enrollment, computer science peaked and is now coming down, and— but engineering is still— yeah, dramatically. But engineering as a whole, you know, mechanical and biological, is still skyrocketing. And so it's taking over. So, so people are really quickly retooling their career ambitions toward like the real physical stuff, like biology and mechanical, you know, for the data center buildout, for medical research driven by AI. And I think that's a really good thing because, you know, we had probably way too many UX engineers anyway, um, just, just in terms of societal benefit, you know, what are people learning, what are people doing.

I love this chart from Andreessen Horowitz. It's the other side of the jobs story, Salim, you were just talking about. And this is the one I find really exciting, that solo founders are exploding. So A16z's data shows that AI solo founders, in other words, solo people creating an AI company on their own, has doubled in the last quarter from 1,500 to 3,000, up basically from zero 3 years ago. And the non-AI solo founders hit over 5,000. These are, you know, people aren't just losing jobs, they're transitioning to starting their own companies.

They're following their passion.

Yes, yes. And they're doing it alone because AI tools now give a single person the capabilities to do that either on their own or with a small team. So, you know, connecting the dots here in the earlier story, coding agents are now at 70%. That plus layoffs equals solopreneur explosion. This is creative disruption happening in real time. Salim, take it from here, please.

Well, look, the big companies, the coordination overhead in big companies means that they cannot sustain any kind of leverage over time. You spend more time coordinating activity than doing the activity. Who was the fellow that tweeted, it's easier to build a product feature than to have the meeting about building the product feature. Future. Yeah, that's like the reality of the world today. Therefore, all of the overhead and big companies— and take universities as one example, right? We, uh, the amount of— as universities have gotten bigger and bigger and endowments, the number of students has gone incrementally, but the number of admin to administer the students has gone up exponentially.

Like in the healthcare industry.

Yeah, we, we've got so much overhead. It's the healthcare industry is an exact example. For example, that will not sustain in a world where you can have an AI teaching a kid in 1 hour what they could learn sitting in a classroom for the whole day, or when diagnosis goes to free, which is pretty much the case today. So at some point, this is going to give that comet— sorry, asteroid is now hit. It's the intelligence asteroid. The big dinosaur, the category of big companies will probably evaporate. The way we see it, you're turning from big companies into platforms, platforms into ecosystems, systems and you're breaking up into smaller and smaller units because this is why small teams will always outperform big teams. There's a reason that the big Microsofts and Googles of the world did not build all of the cutting edge. They acquired DeepMind, they acquired OpenAI, et cetera, et cetera. Anthropic is a rare example, sorry, outlier. This is going to be the defining operating model for the future is small teams radically outperforming And we're entering the most incredible Cambrian explosion of Darwinian evolution of this, to way overuse the metaphor.

And did I just think—

correct a potential misconception here too?

Please.

If you look at the data on successful companies, 75% of them now are coming through some kind of an incubator or accelerator program. And when we started investing, that was only 6%. So that's gone through the roof at the same time. So when people hear the word solopreneur, they might be visualizing a person in the cabin in the middle of Alaska, you know, working all by themselves, no one's around, it's depressing. That's not what actually is happening in that top left chart, or that bottom left chart for solo founders. They're in a very active, vibrant ecosystem of some sort. And at the bottom of the slide, you see the Gemini X Prize. That's an ecosystem of like-minded people talking, texting, slacking, communicating all day long. Long, super, super connected, super involved. So your successful solopreneur is legally a single-person entity, but they're highly connected like never before, and they're part of some bigger, bigger platform. So just to be—

you learn lessons from each other, you, you get the latest capabilities from each other, you support each other when things don't work out. You know, I just want to hit on this, and we can put the website up on, on the screen here of geminixprize.com. We launched this $2 million hackathon with Google, and thank you to the team there. And the concept here is, you know, all of us are finding problems all the time, and man, I wish someone would solve that. Well, guess what? You can solve that now. And this competition asks people to basically write up a product or service idea in plain English, write it down, in a Google Doc, right? And then describe what is the, you know, what's the problem you're trying to solve? What do you think the solution could be? You can brainstorm this with your favorite large language model and then the AI can code it up for you and help you design the marketing. And so this is a competition asking individuals or small teams to build something in 3 months. There's $2 million of prize money. And, you know, we get a lot of pushback and and I've read it in the comments from our last episode altogether of saying, hey, you guys are hanging out with entrepreneurs all the time. You are entrepreneurs. You can't expect me to be an entrepreneur.

We live in an ivory tower. We only talk with other millionaires.

And I just wanna say that my experience is that normal people are brainstorming and starting companies. And a lot of this is self-taught. Self-limited thinking. And I just want to encourage people to try. That's the only thing. Please try.

We've just released this Organizational Singularity Claude skill for free. Go download it, pick your passion, and do it. I was smiling earlier because I remember when Milan was 5, he was asked what kind of technology would he build, and he came up with this thing called the Hydro Blaster, which would be a thing, a water cannon in front of your car that would blow other cars off the road. And they said, "What is this about?" He goes, "My dad hates sitting in traffic. I designed this for him." I was just trying to imagine with an AI trying to build that thing.

I would also, maybe if I might just add on the solopreneur point, there's a lot of hand-wringing out there that pretends that this is somehow, that having a quote unquote job is the historically normal state of affairs. It is not. It is a modern invention.

Here, here, 100%.

Largely attributable to the first and second industrial revolutions. Historically, most people didn't have anything remotely comparable to what is currently called a job. Most people, by like in the historic state of nature, if we go back like two centuries or more, most people didn't have anything remotely called that we would consider like a job as a cog in a large enterprise. Most large enterprises weren't large, like they were pretty small. By, by comparison to today's standards, is an artifact of a time and a place. So if anything, I would say it's highly unnatural, highly unergonomic by historic standards for people to even have jobs. And if anything, this is more of a return, if anything, to the default state of human nature and some sort of historic equilibrium where everyone was self-determining their own future.

Agency.

It's a beautiful thing, you know, back— yeah, back in that time, that era that Alex is referring to, the federal government was about 4% of the economy. And so you think about the independence, like, yeah, you lived on your own, like you were your own thing. That'd be a good vision for where AI might be able to take us. Like, you know, self-determination, self-sufficiency. 10x. It'd be wonderful.

Empowered individuals.

Yeah. Our next story here is actually a call out to everyone listening to tell us how well is education preparing students I wanna do a survey. If you're a parent of a 13 to 18-year-old high school student, if you're a high school student or a college student or a teacher or a working professional, I put up on the screen here a QR code and the URL is moonshots.com/survey. Tell us how well is the educational system preparing you or your kids? What's your experience? What do you wish you had? I'm gonna gather this data and report it back here on the pod. Pod. We'd like to understand what your thoughts are. We talk about the educational system failing us. I'd like to get some more data. How is this affecting you and your kids? So if you get a second here, moonshots.com/survey, I think it's important to understand a reality check here, because the educational system, if in fact what we've been talking about on this pod, that we're going to see this bumpy road for the next 2 to 8 years until we get through to a true state of abundance. You know, how do we get ready? How do we survive this turbulence? And are we getting ready for the new economy that's heading our way?

Can I— Yeah, I've got a bunch of thoughts here, but let me limit it to one paradigm. We have been doing education over the last couple of centuries, Industrial Revolution, I think per Alex's framing, I think is exactly right. And we've been doing it on the supply side. Go become deep in a skill, entrepreneur, sorry, engineer, doctor, lawyer, accountant, and then you go to the job market to find demand for that skill. But it's all supply-side driven. All our education systems are designed to take a young child, train them through their early 20s to be ready for the job market. Small problem, we have no idea what a job looks like in 5 years. We don't even know what a job looks like in 2 years. So what are we going to do? What are we teaching them? And Peter, I think you've, and I talk about this a lot, where you're flipping kids from that supply side where the half-life of a skill used to be like 30 years and now it's about 3 years. You need to flip them to the demand side. What problem do they want to solve? And then go find the techniques, capabilities, skills, technologies to solve that problem. And so that is such a radical shift for the educational system. Very few educational institutions are going to make it over to the other side. We need a completely new cadre of schools, but that's the fundamental structural problem that you have to go from supply side to demand side.

Yeah, I just want to see, you know, does everyone listening agree with that? I'd love to get everybody's input. And by the way, feel free to share this survey with your friends who are not Moonshot listeners. And we'll come back with the data. We'll see what everyone truly feels. Because as a parent of two, you know, 15-year-old— you know, they turn 15 next month. Salim, yourself, I am super curious, 'cause I see a very dysfunctional educational system not getting our kids ready. Dave, any thoughts?

Well, I think that particular age bracket is so geared to getting into college and getting into the right college and maximizing everything on your resume, your SAT scores and your grades, it's all about like my college application. And so that perpetuates a curriculum that's woefully out of date, The, you know, the AP exams and the SATs are the same exact topics while what you should be learning is changing tremendously. And so that's a really broken age bracket right there. So I'm sure everyone will come back and say, yeah, this is totally messed up. What do we do?

Yeah, it's moved our souls. I have, by the way, in front of me a little printout from Milan after I interviewed you, Peter, on what's the future of education. And I was just like, you printed this out? Why couldn't you email this to us?

Me.

How retro. How retro.

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All right, our next story, we're going to jump into a few, uh, space stories for the, uh, those of us who are space cadets. SpaceX just launched the biggest, most powerful rocket ever built. And Dave, we made this point before, this which was designed and built by humans and not AIs. Starship V3 flew for the first time last week from a brand new launch site in Texas. I mean, it's a brand new rocket, brand new engines, brand new launch site. The level and the speed at which SpaceX iterates is crazy. It carried 97,000 pounds to near-Earth orbit, to near orbit. That almost doubled the space shuttle carrying capacity. Old vehicle. It's running on Raptor 3 engines, each producing 250 to 280 tons of thrust, 20% more than the last version. And by the way, that's equivalent to about 70 747s at their takeoff thrust levels. SpaceX did lose the booster on landing, but that's the way SpaceX operates. They fly, they learn, they iterate. You know, SpaceX treats rockets like software. They ship ship. They test, they fail, they iterate. And losing the booster, you know, was another data point, not a failure. They've already carried real Starlink prototypes to orbit. This thing is doing commercial tests on its first flight. Alex, you were watching this. What were your thoughts?

I was watching. It was riveting. So I think the most exciting part for me was when, uh, when the, the mission got to releasing Starlink satellites first followed by a couple of so-called Dodger Dog satellites, which are intended to be prototypes of the next generation of Starlink satellites, version 3 or third generation Starlink satellites. And the Dodger Dogs had cameras and lights on them. And as they were being deployed out of the PEZ dispenser, they were pointed back with their lights and their cameras back at the Starship. And it was just absolutely incredible watching from a view, like a third person view, perspective drifting away from the Starship, the, the view after deployment. I think we're going to see so much of that. I'm not even sure if that has precedent at this point, but it reminds me that we're about to enter an era. And in connection with, with this entire mission test, SpaceX reminded the world that it has a program called Stargaze that is basically leveraging Starlink satellites with all of their cameras, not just Dodger Dogs looking back at Starship, but looking down at the Earth since they operate at a variety of altitudes, they're seeing everything, including all sorts of orbital debris and other objects, and they're sharing that information. And I think it would be an ironic but maybe not super surprising outcome if Stargaze ends up having a more dramatic impact on civilization than even just Starlink connectivity.

Let's take a look at the video here. This is rocket porn for all of us. Here's V3 launching. Beautiful vehicle. You know, I, I spoke to Elon at the Breakthrough Awards and we made the comment that this is the most energy released by a human machine other than a nuclear bomb. Wow. Yeah. And here she is coming in for a landing over the Indian Ocean. Can't wait to see that captured and reused.

Unbelievable.

I think, I think there's a really important point for entrepreneurs in there too. I, I also was completely riveted by the quality of the video and also the MCs describing everything. And this is so Elon, like anybody who wants to be an entrepreneur study what Elon did here. Getting those 4K cameras, the ones that are physically mounted on the ship, to survive the launch and the heat, I mean, that's a lot of extra engineering that NASA probably would never do. But Elon so understands the value of, of building morale and building a following and having a fan base buying the stock that he puts serious mental effort into the showbiz. And every entrepreneur should study that. That's the winning formula because, you know, previously you didn't have a distribution pathway for all that content. Now, because of YouTube and X, anybody can, can distribute their message. You don't have to go through CNBC, you don't have to go through Forbes, you can just go direct. So you're crazy as an entrepreneur if you don't study what Elon just did there and then do your own version of it.

You know, Dave, another point you made before, and we've discussed, is how Elon gets out publicly and he is the marketing engine for Tesla. He's the marketing engine for SpaceX and xAI. And if you're the CEO, an entrepreneurial CEO, you have to put yourself out there. You have to be the carrier of faith and of the story, right?

The turning point for me was when he did Saturday Night Live all those years ago. And I'm looking at this and I'm like, how does he of all people on the planet have time to go to New York and emcee Saturday Night Live. Why is he making that choice? Because he doesn't do this stuff randomly, right? He has more plans than anyone you'll ever meet. And so I'm like, huh, this was reinventing what it means to be a great entrepreneur. Yeah, like you said, put yourself out there, get your, get your mission and your vision and your positive message and your MTP, make it really crystal clear, understandable, and then work on broadcasting it because that's how you're going to get great That's also how you're going to attract capital.

So here's something that we've talked about in the pod before. I've predicted this as well as you have. And this is from Kalshi, the prediction market, showing a 50/50 odds that Tesla and SpaceX merge within the next year. I personally put it at 100%. You know, think about what that company would look like: electric vehicles, energy storage, solar, rockets, satellites, global internet, humanoid robots. Bots, you know, interplanetary exploration, all under one roof. We're talking about a potential $4 trillion entity initially. I could honestly see, in full disclosure, I'm a SpaceX and XAI investor, but I could see this being the first $10 trillion company and moving to $100 trillion in the next 5 years. So, you know, given the current anti-regulation environment, in other words, the fact that the government is not overly regulating, I think that it's a clear path for Tesla and SpaceX to merge. And the key point is that Elon has voting control, super voting rights inside of SpaceX, SpaceX AI. And with his insiders, I think it's 86% of the controlling vote. And he's suffered from being a minority shareholder, disallowed to create the comp packages that, that his board wants. And so this in the merger gives him control back once again.

Exactly right. And just one more detail on that, Peter. The 85% voting control that he has on the SpaceX side is 10-for-1 super-voting shares. And so if he merged in Tesla, those would— he has 20% voting control on the Tesla side, but those are one-vote shares and everybody has one-vote shares. Shares. So the most likely merger is you'd, you'd roll in all these one-vote shares into SpaceX as the acquirer, but maintain the 10-for-1 super voting shares that already exist on the SpaceX side. So then the combined entity, he'd have, you know, 60, 70— you know, it depends on the valuations, um, but 60, 70, 80% voting control of the combined entity. So the only reason that Kalshi is 50% and not like 100% is one, he needs the relative valuations to be similar or higher on the SpaceX side side for that math to hold up. And two, there's a shareholder vote on the Tesla side that he doesn't control. He probably can't, can't vote on that.

Alex?

So I'll, I'll expand on this theory a bit. So I've argued last time we discussed the possibility of one Elon company to rule them all, I pointed out that historically Elon has a history of using mergers as an opportunity to fail forward, with SolarCity for example famously litigated or XAI being acquired by SpaceX, maybe arguably a reverse acquisition. So in my mind, the argument for Tesla and SpaceX to merge would be as a way for Elon to rescue maybe what he perceives as a suboptimal governance situation for Tesla, to recover control of Tesla. I point out one of the ways to make that more appetizing is if Tesla's valuation goes down. Down over time. If Tesla were to, to suffer, even though Tesla has a new comp package as well tied to autonomy, if Tesla's market value were to materially depreciate in the next year relative to SpaceX's post-IPO valuation, that might at least in the short term make a SpaceX acquisition of Tesla a good deal more appetizing to public markets. There might be a bit of an arbitrage opportunity there. Not investment advice, Otherwise, second point, I have to ask the question, if and when this final Elon merger to rule them all happens, a bunch of good reasons, maybe having to do with IP and GPUs freely and porously changing hands between all the different entities, is it going to be called X or do you think it'll have a different name?

Well, Elon sounds good on the NASDAQ. That might be conveniently another 4-letter name.

But what do you think it'll actually be called?

I think X is his love. And I think you're right. He may go towards that or just XXXX. We'll see.

Triple X. Yeah.

Quadruple X. So interestingly, you know, I had dinner with Elon in the early days when SpaceX was up and operating and Tesla was going on and he was searching for a Tesla CEO. He really wanted someone to run Tesla day to day so he could focus on SpaceX. And he just never found anybody who he trusted with that company because it meant a lot to him. And this is a way for him to consolidate control and be the CEO of one company instead of splitting his time. You remember, Dave, when we were with him at the Gigafactory in Austin, and I think our podcast went for like 3.5 hours, and he started— we started like 10 o'clock and went until after midnight sometimes. And his son was there the entire time. Anyway, he was coming from—

They're on a collision course. They're on a technical collision course. We're gonna need a lot of Optimus robots for the Artemis colony and for the Martian colony. It's going to happen one way or another, regardless of whether I think it's an organizational merger. They're already, I think, well on their way toward a technical merger.

The point I was gonna make, Dave, was he'd come from one meeting to another meeting to another meeting. He's jumping to wherever the problems are to dive down deep, and just being able to see it inside of one organization, I think, will make his life a little more, a little easier, a little more unified. All right.

He talked a lot, actually, about the overhead of context switching being a killer for him. Yeah. Like, he can solve any problem if he has time to get his head wrapped around it, but when you're jumping from 10 little things to 10 little things, you know, then you have to reset your brain, and that's killing all your time.

Time.

So yeah, it'd be a lot more efficient this way.

This was a fun story released during the first or the second launch attempt. Uh, crypto billionaire books SpaceX first private Mars flyby. So the first private interplanetary mission to Mars has been booked, and the guy leading it might be the most interesting person you've never heard of. It's, uh, Chun Wang, co-founder of one of the largest Bitcoin mining pools in Controls 11% of Bitcoin's hash rate, travels via 6 different passports, lives part-time in the Arctic. And get this, he follows Mars time, which is a 24-hour and 37-minute daily cycle. That's gotta be tough. He's already commanded SpaceX's Fram 2 mission, first crew mission to go over the Earth's poles. Now he's taking a Starship around Mars. So sort of a circum-Martian trip. Expedition trip, a 2-year mission, private citizens. He'll bring some other folks with him. Interplanetary flight. Let that sink in. Alex, what are your thoughts here?

I, I like seeing this. I, I wish there were more examples. I remember also, although I think it fell apart in the end, a wealthy Japanese businessperson planning the mission around the moon. That didn't quite happen. I like seeing private I love it. This is such a 2026 statement. I love seeing billionaires flying to other planets. I like it when that happens. I like it even more if they fly to the other planet and then fly back in one piece. I think we'll see a lot more of it. And I'd like private missions to other planets as well. We haven't seen that at all to date, to my knowledge. I think we're going to see more of that. One can immediately fast-forward the recording to a bunch of foot-stopping and hand ringing about the unfair asymmetries of billionaires getting to go on Mars flybys versus everyone else and how asymmetric the interstellar, or at least the interplanetary economy is. But I think this is all under the category of good problems to have. And I would remind Jared Isaacman also, another billionaire who was pioneering SpaceX missions. I think we want an entire class of billionaires and business leaders who were all eager to go on either cislunar or lunar surface or Martian trips and back. I think building that level of awareness and capability in business leaders, and then from there the entire population, is only good for macroeconomic growth.

So here's the thing, I wanna point out here that these individuals are spending a lot of money and taking relatively larger amounts of risk. And they're enabling us to follow in their footsteps as the price comes down. I just had a webinar this morning for the Abundance Community with Philip Sekulo, who heads private missions for SpaceX. And, you know, when years ago I was co-founder of something called Space Adventures and we were negotiating and we represented the Russian Space Agency and sold tickets on Soyuz, to go to space. The first ticket was $20 million. The prices rose quickly to about $75 million as the price of labor in Russia went up. And Philip this morning was saying that on the Starship, he's gonna be offering flights to orbit. And Starship has 1,000 cubic meters, 1,000, it's 3 times larger than the space station in the volume that the humans will occupy. The price is gonna come down to $20 million a flight. And then Alex, I think you'll appreciate this. I did the calculations on if you could electrically winch somebody from the Earth up to orbit, you know, it's MGH.

By a space elevator.

MGH, right? Potential energy. And then accelerate them electrically to orbital velocity. And if you could buy that off of the grid at 7 cents a kilowatt hour, the price of launching you and your space buddy to get a spacesuit into orbit drops from $20 million down to $200. We have a—

$200.

$200 of electrical cost to winch you and accelerate you to orbital velocity, right? So MGH, 1/2 MV squared, go to your favorite large language model, plug in those numbers, plug in your weight, add 100 kilograms for a spacesuit, you get the same numbers there. There's a price improvement curve that's gonna be hitting and it will ultimately enable all of us to go to space. Space. And in the early days, I don't know if you remember this, Alex, but Elon predicted the cost of a round trip mission to Mars. Do you remember the number he gave?

I don't remember the original number.

It was his goal is—

Oh no, actually, I'm sorry. In the early days, I do remember he was quoting the idea of, I think, low hundreds of thousands of dollars.

$500,000 for a round trip flight to Mars. So it's first principle thinking. What's the cost of the fuel? The efficiency as we get to launch 500,000 satellites for the orbital Dyson Swarm, you're launching an hour. And when there are hundreds or thousands of Starships launching, the price comes down. So thank you to the wealthy people taking the risk, putting the money in to get this going, 'cause it's gonna benefit all of us in the final result.

Yeah, it turns out that ivory elitist tower is actually quite beneficial for the development of the solar system.

We're demonetizing and democratizing. Democratizing.

Brad Templeton called early adopters stupid people with too much money. 'Cause they'll buy the iPhone 45 because it has 1.8 more features than the iPhone 44. And that drives the innovation and democratizes it for everybody else.

Our final story here is Starlink announces plans for gigabit lunar connectivity. Alex, let's go to you here.

Yeah, I think this was always going to happen. You were the first in this episode, Peter, to mention Dyson Swarm, so I didn't have to. Thank you for front running me on that.

You're welcome.

But I, I, I do think one of the architectural benefits of having Starlink in not just sun-synchronous orbit for AI compute, but in general, is that as we— royal we— as SpaceX and other companies start to build out swarms of orbital compute and connectivity and bandwidth, not just in low Earth orbit but also in cislunar, lunar orbit, maybe L1, L2, it starts to create the beginnings of a fabric of an interplanetary internet, which is something that we've talked about for decades. Vince Cerf was like chief evangelist. He, I think he coined the term even.

He did.

And so the idea of interplanetary internet whereby we sort of fully wire up or wireless up our solar system with nodes, with like internet router nodes that are able to send packets of data and wire them around, given that the solar system isn't rigid body. I think we're about to take a step toward that in the form— and SpaceX and Starlink put up some funny images online with the monolith from 2001: A Space Odyssey hosting a little Starlink dish on it. But I think the future that we move to is we have a swarm, as depicted on the slide, we have a swarm of compute in low Earth orbit, orbit. We have a swarm of compute increasingly in lunar orbit, and then we can create a fabric of connectivity between those swarms around Europa, and then, and then Martian orbit asteroids.

Yeah.

And the beauty is, uh, you know, in the same style as modern cell phone protocols that can leverage multiple paths and multiple parallel paths to increase bandwidth, having just a single telescope dish on Earth pointed at the to the moon, that really limits our bandwidth.

But yeah, I'm gonna be really pissed off if the cell signal on the moon is better than in my neighborhood.

It may very well be, but not only that, they're going to have laser connectivity, so it's not just radio anymore. Imagine a whole swarm of satellites in LEO that all have laser cameras and laser pointers pointed at the moon and vice versa. The bandwidth is going to be tremendous.

All right, here's our actual last story. Uh, NASA Administrator Director Jared Isaacman expects China to send a crewed mission, a flyby, in 2027. Here's his quote: The next time the world tunes in to watch astronauts fly around the moon, which will likely be in 2027, they will be taikonauts, and America will no longer be the exclusive power to send humans into lunar environment. So a little bit of the throwback to Apollo. How do we keep the NASA budget funded. We do it with competition. We can't let the Chinese get there first.

FOMO.

FOMO, yeah. But of course, 2028, uh, we're going to start to see our— the United States heading towards the South Pole. Super excited for that. I— and I love the fact that we're going to the South Pole and not just to a boring, you know, uh, equatorial landing site.

You've got to go— if anyone who's watched For All Mankind knows, you have to go where the Ice, and also the Peaks of Eternal Light.

There are two things in the South Pole. There is permanently shadowed craters, and as the Moon was bombarded by comets and asteroids, any water ice that landed on the surface of the Moon sublimated immediately 'cause it's in the sunlight. It goes from water vapor, from ice to gaseous water, and it escapes because of the low gravity of the Moon. But if those comets and asteroids happened to hit the South Pole, fall and get buried into a deep crater that didn't see the sunlight. Ice accumulated there. But the other thing that's there is there are peaks, little mountain peaks that are seeing sunlight, you know, 30 lunar days of the month. So you can set up solar stations there. And of course, there'll be fusion stations there too.

Peter, I have to ask you for your prediction. When do you think you'll be able to take a vacation at the Artemis colony?

You know, that's a great question 'Cause while I got the suborbital industry going with the first SRX project— You were there. Yeah, well, you were?

You were there.

Oh, I was there, yes. It was fantastic and I really wanted to go on a suborbital flight. I've got a seat on Virgin Galactic once they start flying. Maybe I have to go on Blue Origin, but I'm far more interested in actually landing on the moon. The 9-year-old kid in me definitely wants to go and land on the moon. 2035, I think the price and my ability to afford it will intersect, but I wanna start a city on the moon. I'd like to be a lunar mayor. That would be fun.

What are you gonna call your city, Peter?

I don't have an answer yet. I'll have to, you have any good ideas? Maybe Highline.

Maybe give it out to the audience. Maybe the audience can suggest a name for your lunar town.

All right. Well, let's wrap it up here. One of the things we're doing for our audience is we're going to be putting out twice a week shorter episodes. We got some feedback. They love, you guys love the episodes, but they're getting longer to 2.5 hours. And so we're gonna still cover all the content, but we're gonna shoot for some shorter episodes that make them more bite-sized and produce this twice a month. So please, if you're a subscriber, turn on notifications submissions, so you find out when they get out. Um, Mag— Magna Bosta. Uh, Magna Mobster.

May I tell a story for this one, Peter? This is a submission from yours truly.

This is your production, AWG Productions.

My submission for an outro. So I realized we had the FAANG companies, F-A-A-N-G. We had the MAG-7 companies. I realized with OpenAI, SpaceX, and Anthropic about to IPO over the next months, the world was missing an acronym for what the most valuable companies of the innermost loop would be that would be the closest to the chips and the autonomy and the space and the AI models. So the world needed an acronym. So I coined an acronym and it turns out it's brilliant. MagnaMobsta. For those asking, the B is Broadcom, which is absolutely essential in the supply chain. MagnaMobsta are the 11 companies that—

Read them out for us a second.

This is red meat for all of our commentators here.

Read them out for us here.

So there are a lot of A's, so I'll see if I can get this right. So Microsoft, Amazon, Google, uh, Nvidia.

Help me out on Nvidia.

Nvidia.

Yep.

Uh, Apple, Meta, OpenAI, Broadcom, SpaceX, Tesla, Anthropic.

Anthropic.

So it's going to be when, when When SpaceX and Tesla merge, it's gonna be Magna Mobza. Mobza.

Mobza.

Mobza.

All right, well, let's look at the genius of Alex. Let's play this one out. Here we go.

Nice symphonic.

I was imagining something like, uh, I don't know, Goldfinger or something.

Great.

Strings.

Oh, you build it, you bind it, turn the key and find it. One more pulse, one more plan in the palm of MagnaMobster's hand. MagnaMobster, hold the core. MagnaMobster, ask for more. Gips and cloud all come down. Magnum Mobster on the crown.

Magnum Mobster on the crown.

Every note knows your name. Every route arrives the same. Silent doors and hidden glass open when your shadow pass. You wear the hush like satin knife. A lovely thread, a certain light. One kiss and the system turns. One One glance and the whole world learns. Oh, you build it, you buy it.

All right. Awesome. That was awesome.

MagnaMobsta, people are trying to create ETFs off this, not investment advice, but MagnaMobsta, the world needed a new acronym. The world, you have your new acronym now for the top 11 companies at the heart of the singularity.

Love it. All right, gentlemen, so proud to be on this journey with you. Thank you so much. My favorite time of the week is this conversation. Awesome.

Yeah, likewise.

Take care, fellas.

Thank you.

If you made it to the end of this episode, which you obviously did, I consider you a Moonshot Mate. 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 Meta Trends. Trends. I have a research team. You may not know this, but we spend the entire week looking at the meta trends that are impacting your family, your company, your industry, your nation. And I put this into a 2-minute read every week. If you'd like to get access to the Meta Trends newsletter every week, go to diamandis.com/metatrends. That's diamandis.com/metatrends. Thank you again for joining us today. It's a blast for us to put this together week.