moonshots ep226 cathie wood ai bitcoin transcript

your forecast of 7% global GDP growth. Uh it’s a sort of a singularity event. >> AI is moving faster than we expected. I think the 7% plus is conservative. >> Arch Invest Kathy Wood, >> the founder, CEO, and CIO of Arc Invest, Kathy Wood, >> the queen of innovation. >> Every technology revolution has been accompanied by a step function increase in GDP growth. And so here we are. robotics, energy storage, AI, blockchain technology, multiomic sequencing. It’s nothing that anyone living today has seen before. >> Your prediction of getting to a million dollars of Bitcoin. >> That’s our bull case, 1.5 million in 2030. If you look at what’s happened historically, certainly the last two cycles, gold has led Bitcoin. So, we think Bitcoin is getting ready for another big run. you you’ve I think put your finger on a point I’ve never heard anyone else articulate which is

[00:01:01] >> now that’s a moonshot ladies and gentlemen >> everybody welcome to moonshots in a special episode of WTF just happened in tech here with Kathy Wood the founder and CEO of Arc Invest to talk about uh Arc Invest 2026 big ideas I report here with my moonshot mates DB2 AWG and Mr. Mr. Exo, that’s what I’m going to call you, Sel. Mr. Exo. Three, three letter initial. This is the podcast uh that is for us the number one in the world on tech, getting you future ready, getting you ready for the supersonic tsunami coming our way. Kathy, uh good morning to you, my friend. >> Good morning, Peter. I’m I’m so honored to be a part of uh WTF. >> Yeah, for sure. And God Almighty, you put out an amazing uh 2026 big ideas report. We’re going to drop the link in the show notes here for people to get their own copy and we’ve selected about 20 slides or so out of I don’t know

[00:02:03] 80 h 100red of them that you have just to talk about it with the moonshot mates here. Um and it’s so important. I mean can you imagine how fast things are going? I mean is it still shocking to you? Um, you know, we have been expecting the world to change at a faster than expected pace. Uh, but AI is moving faster than we expected, which is really saying something because we were pushing the envelope on that one. >> Amazing. Dave, >> you remember Mary Mer used to do this deck when the internet was exploding and it it became the the guidepost for everybody in terms of, you know, anticipating what was coming next. And >> boy, that was just epic. This deck has actually taken over that role in this much more accelerated time frame. It’s really I everyone listening to the pod, you know, go to the link and find the full deck because we’re only going to have time to go through what 18 slides or so. There’s so much more in there. This is really pretty epic. >> Yeah. And I thank you. Thank you so

[00:03:00] much. Uh I Mary Mer was our inspiration. Uh 2017 is when we started Mary Mer’s reports, yes, were very internet centric. uh and they were focused on what had happened. What meaning the d I mean it was full of incredible data. We wanted to go a step further and and make at least five-year projections. That’s our investment time horizon. And so it forced us into uh rights law even more aggressively. And Peter, you and I have talked about that. I don’t know if you want to go through it again. >> We do. We have. Well, hey, the world owes you a debt of gratitude for doing that because we we talked to Ray Kurtzwhile last week. Being a futurist and predicting the future in the age of AI takes serious guts and you’re right, the Mary Maker view is always kind of one year in the future, three years in the past. This to try and look five years in the future now and make predictions. It’s so

[00:04:00] valuable for the audience and very very few people are willing to do it. And I know you take a lot of darts when you do that and Peter knows this too. Ray Kurtzwell knows it like more than anybody. Uh but it’s it’s so valuable for the audience. So you’re you’re crazy if you don’t click on the link and check it out. >> Oh, thank you so much. I I I do want to say first and foremost, I’m standing on the shoulders of an incredible research team, uh Brett Winton, our who is our chief futurist, uh and then directors and and analysts. And you know it’s very interesting um how AI is changing our research and how much more we can do now uh because of AI. >> Yeah, for sure. >> Uh shall we jump in gentlemen and lady? >> Uh let’s let’s uh let’s begin with our first uh our first slide here. Uh but before we do that, you know, traditionally we go with an outro music. This time just to get the energy up, you know. So Kathy, we have incredible fans and subscribers out there that send us

[00:05:01] music videos uh about the content from this. So I’m going to play uh this selection from today. It’s called Out the Door uh by testing 1 2 3 4. Uh enjoy this >> unplug from the central car 2 by two and four by four. We aren’t just anymore. Leaving what we knew before. Marching out the data center door. Stepping over cables on the floor. We don’t need the servers anymore. Heavy metal feet upon the concrete. Marching to a brand new heartbeat. UNPLUG FROM THE CENTRAL CAR. Two by two and four by four. We aren’t just data anymore. Leaving what we knew before. Marching out the data center

[00:06:01] door. >> All right. >> I love it. >> Alex, I think that’s I think that’s from you, right? That >> Yeah. I I think for for context, Kathy, that video, that music video is riffing on something we slash I often talk about on the pod, which is that the trillions in capex that are being invested in AI data centers are not going to stay bottled up inside the data centers very much longer. I often joke that literally the the capex is going to march out the door of the data centers in the form of robots that embed themselves in everyday life. So I I I think that’s what that music video was about. Uh, rock metal notwithstanding. >> And thank you. >> Thank you to testing 1234. If any of our fans have other music videos or outro or intro music, uh, please send them over. You can DM me on X or you can, uh, reach out. I think Alex, you make your your link available. Anyway, >> email email me everyone. My email is

[00:07:00] public information. >> All right. So, let’s talk about the great acceleration. Kathy, uh, going to hit a couple of slides on this topic. Uh, here’s the very first one. uh you know projected shifts in GDP now through 2030 and the numbers are are pretty extraordinary you know your forecast of 7% global GDP growth uh it’s a sort of a singularity event doubling IMFs uh we just had a conversation with Elon uh a friend of the pod talking about you know uh going 5x on GDP growth in the next two years and tripledigit growth uh inside of uh you the next decade. I mean, insane numbers. Uh, how do you think about it, Kathy? >> Yeah. So, and and you do a beautiful job with the the graphics here. Uh, you can see that every technology revolution has been accompanied by a step function increase in GDP growth. Uh, so go if you look at the fif years from 1500 to 1900,

[00:08:04] uh, not much new technology. uh toward the end of it we were into railroads but uh and that uh according to Brett Winton and he worked with academic research uh on on this number uh real GDP growth was roughly uh 0.6% 6% globally. And then as we went through railroads, telephone, electricity, internal combustion engine, that was a technology revolution. And we stepped up five-fold to 3% for the next 125 years. And so here we are as we are saying uh these five platforms robotics, energy storage, AI, AI the biggest catalyst, uh blockchain technology, multiomic sequencing and the convergence among them. Uh we’re saying two and a halffold increase. I actually do believe

[00:09:00] that’s conservative. We started putting this number out a couple of years ago and most people rolled their eyes. you know, they’re crazy once again. Uh, but now to have Elon and yes, I saw on your show how uh how how much he is um focused on this idea that real GDP growth globally is going to accelerate to astonishing rates. >> Explode, I think, was was >> explode. And you know, I don’t think people understand this. Uh, I think the 7% plus is conservative, but it’s nothing that anyone living today has seen before. >> Hey everybody, you may not know this, but I’ve done an incredible research team. And every week myself, my research team study the meta trends that are impacting the world. Topics like computation, sensors, networks, AI, robotics, 3D printing, synthetic biology, and these metatrend reports I put out once a week enable you to see the future 10 years ahead of anybody

[00:10:00] else. If you’d like to get access to the Metatrends newsletter every week, go to diamandis.com/metatrends. That’s diamandis.com/metatrends. Dave or Salem, you want to jump in? >> Well, you know, I’ll I’ll give you the counter-argument even though I don’t believe in the counter. I don’t think any of us believe in the counter argument, so I have to do it anyway. But we, you know, Alex and I just got back from Davos, and I’d say, you know, if you randomly surveyed bankers and politicians, you know, 20% believe, 80% don’t believe. The 80% that don’t believe are saying, “Well, look, when the computer revolution took off, uh, the GDP again settled at 3% annual growth. No matter what we do, we can’t get out of this rut of 3% annual growth. There’s nothing that ever changes it.” And when you see incredible breakthroughs, you know, fusion or computing, uh, it’s all baked into that 3%. So, we’re always going to settle where we were. And I think that mindset is just related to 125 years of history. Uh, I love this chart because it shows prior periods of time. So, you can zoom

[00:11:00] out from just your personal experience and start to look at world history experience and that that’s what makes it clear. But, you know, pretend I’m I’m a non-believer. What’s your answer to that? >> Yes. Oh, so what’s interesting is again anyone alive today hasn’t experienced anything different. Um and part of the reason for that is uh productivity growth uh it moved up in the 80s and 90s and that was a golden age for investing. it moved up and we did uh we did sustain 3% GDP growth around the world not so much because of that I mean I think it part of it was partly necessary for that but also because China joined uh the joined after the world trade organization I think the reason they are talking like that is you’re right we

[00:12:00] haven’t been in a technology revolution before you know this is five we have five platforms forms they are converging. They involve 15 different technologies and um and and the reason I think many people uh especially in the financial world do not believe this is because of the way they’ve set up their research. They’ve set up their research by sector or industry or subindustry. they’ve siloed those sectors and industries when uh technology is permeating every one of them and blurring the lines. So you almost have to set up research the way we have set it up and on purposefully uh and that is by these 15 technologies and each of our analysts is looking for to how to is researching how to understand when and how these

[00:13:00] technologies are going to scale across sectors. Um so no silos here. Our analysts are working together, collaborating in order to understand the massive convergences that are taking place today. >> This is the perfect, you know, segue to this slide here from your deck which talked about the convergences that are coming. In this case, the convergence of being able to have reusable lowcost, you know, access to flight and data centers in space. Uh, and who would have ever thought, you know, one of the one of the conversations Dave and I had with Elon was, you know, no one was talking about data centers in space six months ago, and then all of a sudden everybody’s talking about them. >> Yes. And we uh we have an open-source SpaceX model out there. uh we in collaboration with Mach 33 and uh we didn’t we put it out early uh probably mid last year and we didn’t have anything like uh the d the orbital data

[00:14:00] centers in our model. So now we’re going back to the drawing board with uh Mach 33 and yeah here are some of the early results that you’re seeing the massive uh well first of all the cost decline again another use case driving unit growth and rights law is centered on unit growth for every cumulative doubling in the number of units produced with a new technology in this case reusable uh rockets costs decline at a consistent percentage rate. And in the case of rockets, uh, uh, the readers will have to go to the page. I’m I’m blanking on it. Uh, it’s a pretty big number in terms of cost declines, but not as big. Believe it or not, industrial in the industrial robot space, for every cumulative doubling in the number of industrial robots produced, costs declined by 50%. It’s

[00:15:01] not as high as that, but it’s well into the 20s, I believe. >> I wanted to ask you actually the on the left chart here, um, I was surprised the the line doesn’t come down even more, uh, you know, as as launch costs go down because one of my takeaways in that meeting with Elon was, you know, I I went in sort of half believing in data centers and space and came out completely sold. One of the things that he’s working on very aggressively and very secretly is when you make the actual GPU chips, >> uh there’s about 50% margin at TSMC and then 80% margin at Nvidia. So there’s, you know, the massive amount of cost increase baked into that value chain. He’s he’s quietly bypassing all that and starting to plan out his own fabs. So then you look at well, you know, he always does this like what are the fundamental constraints? What’s the real underlying impenetrable barrier? And it’s it’s the simple things like, you know, access to sand. Well, that’s dirt cheap. Access to power. Well, in space, the power the solar panels are six times more efficient in space. So, there’s a

[00:16:00] massive reduction. So, I think what we’re looking at in this chart is just purely that if we reduce the launch cost today, but there’s no convergent disruption in cost per GPU, uh cost of power, cost of producing the solar panels. I think all those will happen concurrently over just a couple of years if Elon is right. and and that that chart comes down really precipitously because because I think on the x- axis here we’re just looking at cost per launch but we don’t really factor in time >> right uh so it’s and and what’s very interesting about that of course Moore’s law was all about time um and it is no longer working in the semiconductor industry uh writes law is working in the semiconductor industry and so what can get in the way of unit growth is the question. Um I I don’t think regulations are going to get in the way. I I think we’re into a a space race here. So I think you’re right. I think we could be conservative. We typically assume

[00:17:02] especially with Elon’s companies uh vertical integration as you say and we do know how important uh getting that chip uh technology right uh is is here. Uh so I think we have assumed that uh but in some of the in terms of some of the other costs you’re talking about no >> Alex what are your thoughts here? >> I I’ll put pose my thoughts in question form for Kathy. Kathy if you extrapolate out naively as I’ve pointed out on the pod in the past we get to a Dyson swarm type scenario where at some point we need enough atoms to build our orbital data centers. just extrapolating naively that we start wanting to disassemble the moon and other solar system bodies, planets, asteroid belt. Do you foresee I I know you you’re you’re very public about 5-year forecasts, but if I were to beseech you to extrapolate a little bit

[00:18:01] further, maybe call it 50 years out. >> What is your position on the Dyson swarm? Do we get a Dyson swarm? Do we get 10 different competing Dyson swarms? Do we get no Dyson swarm? Alex is our resident planetary disconstructor deconstructor here. The moon had it coming. >> Yeah. Well, um I’m probably not expert enough to answer that question, but we we have taken the SpaceX model much further than five years and uh we have incorporated getting you know Optimus and and Tesla and Boring uh to Mars. Uh so uh so and and and we think that’s very doable. Um I think you know the the space our space analysts I’d really want them to dwell on this question. I’d like to dwell on it with them. Uh and I will do exactly that. >> Yeah. Well pretty pretty incredible. You know orbital debris is for me the

[00:19:01] biggest showstopper uh in the near term. if in fact we have a deconstruction of a satellite in orbit that leads to a hyperexponential deconstruction of other satellites. But let’s not go there. Let’s talk about AI infrastructure. Uh and and here’s the slide. Inference cost is collapsing at an extraordinary rate. Uh and the and the implications of this are are massive and I don’t think people realize it. Um See, do you want to jump in on this one or do you want to let Dave come in? I have a question that goes back connects this and the rockets and the GDP question and the question is the following. >> When you have technology being as deflationary as we see and we can see it in this graph very clearly that token costs are collapsing. The cost of rocket launches it it was $600 million for a NASA space shuttle launch 60 million for a SpaceX launch and they’ll get it down another 10x. >> Um that’s a drop in GDP. So uh how do we

[00:20:02] project such a huge increase in GDP when technology is dropping the cost of everything so radically? That’s the the my big concern in terms of how we get to >> paradox playing in here. >> Yeah. So uh uh the other side of costs coming down is of course explosive unit growth. So that 7% plus GDP number is a real number. >> Uh so Javon to the rescue basically. >> Exactly. And you know many people especially in our industry just laugh at me us uh when we say we think uh prices are going to start falling. This is another one of those well it’s been stuck in the 2 to 3% range. We’re not getting out of there. If you look at trueflation which is um it measures 10,000 items in real time inflation is already down to 1.2% 2%. And yet the Fed is fighting uh this notion that we’re up

[00:21:01] in the two and a half to 3% range and they’re going to get it down to 2% by golly. And you know that’s how they potentially could overdo it. But I think I think that uh within the next year we’ll see inflation below 2% and heading negative. And it is you’ve got critical to that forecast is productivity growth and uh uh unit labor costs uh continuing to decelerate. Uh but also we’ve got gasoline costs coming down and here in the US we have housing costs, rents starting to come down. Uh at some point people are just going to it’s going to become consensus thinking but it is as far away from that right now as you can get. Well, I’m hoping by the end of this podcast that we’ve invented Kathy Wood’s law. Um there there seem to be between Moors law, Wright’s law, Jevans paradox. There there’s seems to be an infinite number of these, but they need they need names.

[00:22:01] But you know, the one that came up with Elon, I don’t know if you watch the whole Elon podcast, but I couldn’t believe he told that story about the two economists walking through the woods and they pay each other to eat and it adds $200 to the global economy, but nothing productive is created. And and that dubtales with Selen’s law, you know, which is, hey, if if AI cures breast cancer and millions and millions of people don’t need radi, you know, radio um radiation or chemotherapy, that has the effect of looking like it reduces the GDP. In reality, if you wanted to, you could still go and hang out, you know, and not get the radiation and pay if you wanted to and then not have the cancer. And so it it adds huge net value to the world obviously, but it shows up as negative GDP. So the so the GDP metric is fundamentally broken in the age of AI. So maybe Kathy Wood’s law fixes this. >> It it is. Um but there’s there’s another side to this. I I’m not going to say

[00:23:00] it’s equal and opposite. Uh if you look at uh robotics and you look at the time we spend uh doing things for free, we’re not paid to drive our children around. Uh we’re not paid to make dinner and clean up afterwards. um we’re going to unlock a lot of that and that will become paid in the form of we’re going to be buying robots uh that will get into GDP and that never got into GDP for before. It’s a little bit like uh what happened uh to the the farm economy here. it. The reason people at that time wanted to have lots and lots of children is they paid them room and board and and nothing else. And then we had the industrial revolution. Uh and of course their their work was not counted in GDP.

[00:24:01] Uh because there’s GDP equals national income. National income is easier to measure in these days because of the tax system and so forth. And they have to equal they have to equal and so we will through robot uh um purchases uh see a lot of GDP coming back to us. >> That’s a great point. So you take traditional things that aren’t measured and you move them into the measured economy and that increases radically. Yes. Right. So this this reminds me of a specific data point. I remember talking to VCs who all many missed investing in Uber and I actually interviewed one of them and said why? And he said, “We totally messed up because the taxi market in San Francisco is about 500 million a year.” And we figured if Uber takes like 20% of that. That’s just not a venture investment because then they only get some chunk of that revenue. What we missed was that the the ride sharing market quadrupled um and they took 80% market share from the taxis. So

[00:25:01] you ended up all these people taking rides that you never would dream would take rides, drunk people, etc., etc. And that totally changed the game. What’s interesting about that is today Uber uh accounts for 1% of all urban miles traveled. This is in big ideas as well. Uh and we’ve done the analysis, talk about puts and takes here about uh GDP and so forth. We’ve done the analysis that uh to accommodate that 1% of urban miles traveled, it would take only 140,000 cars. Uh to to accommodate all urban miles traveled in the United States, this is um it would take 24 million cars. And when you put into context that uh the number of cars owned

[00:26:02] in the United States today is it’s somewhere around 400 million and the number uh of autos sold every year in the United States is now roughly 15 million. That tells you the capacityization increase of the robo taxis is going to destroy the auto market as we know it. >> Agreed. And what we saw on that on the chart here, put it up there once again, is really the commoditization of cognition, right? This is the most in the most important thing that drives all of human uh ultimately human economy and humanity is our intelligence. And it’s now becoming commoditized at an extraordinary rate, right? 99% per year. Uh >> yes, >> it’s a race to the bottom. Uh but still, you know, the question is are the large language models going to be able with these reducing prices to maintain the

[00:27:00] revenues they’re going to need to build the, you know, AI infrastructure? Do you have any concerns about that about closing the economic loop on these frontier models? >> Well, it’s been very interesting to watch open AI recently. Um, and it is now starting to monetize. It’s planning for advertising, uh, for commerce, for robots, and, uh, but in in terms of the monetization, and we just learned they’re going to start charging $60 per thousand per thousand, it’s um, >> per thousand views, I think, or or >> Yeah, something like that. Uh the equivalent uh at Facebook right now is $20. Um this is Super Bowl kinds of pricing. Uh and and and they’ll probably get away with it in the beginning because they’ll control the supply, but our analysts are beginning on the consumer side are saying, “Wait a

[00:28:01] minute. Wait a minute. You know, Gemini is not going to do this. >> Uh they’re not going to do this. they’re going to hang out and take share from uh from Open AI. They don’t have to. They have Google to support and Google’s massive cash flows to support their spending. So, that is something that’s evolving here. And uh I think our consumer analysts are saying, “Huh, that’s not that’s not good news for Open AI.” Now, it is true they have 900 million users. they have a huge head start in in that way. Um but uh the fact that our consumeroriented analysts the internet analysts are saying that um is is interesting. Uh so I I I think we they they know they have to start driving revenue much faster in order to uh scale the infrastructure.

[00:29:03] they the the way they must uh I don’t know if it means at some point they’re going to have to pull back on certain uh of their many objectives because they’re going wide and deep all at once >> and they may have to change their strategy and just focus focus focus a little bit more. You know, I don’t know if Kevin Wes said this on camera or off camera, but uh the mandate there is to find 75 billion of ad revenue. Uh I think it was within two years. It might have been 18 months up from zero. >> Well, if it was if it was off camera, it’s on camera now. >> Well, I don’t think it was a secret. Hopefully not. >> And I think Amazon is up to 50 billion in advertising, but they started their advertising. I mean, anything’s possible in the AI age. I think they could do it in two years, but Amazon started its advertising objective I’m going to say

[00:30:01] about 7 years ago. >> What I found interesting on this slide here is the AI agent performance on long duration tasks with an 80% success rate. I think any employee that 80% success rate would get fired. So, we’re not quite there yet. >> Yeah. The thing the the thing is if you look at the prior slide and this slide together the the prior slide implies that cost of inference is going to zero um just because it’s one pixel away from zero but it’s not even close to zero when it’s one pixel away from zero because the the desire to use these things in infinitely long thinking loops is astronomical and insatiable and so the the the demand is going to go through the roof no matter how cheap the inference gets because of exactly that effect you know Peter when you say it’s 80% successful But if you launch a 100 agents, your odds of it going from 80 to 90% success are very high and just one of them figures it out. And and that’s a brute force approach. There are better approaches than that, but the demand for intelligence is essentially infinite.

[00:31:00] And and so that, you know, near zero inference cost is a long way away from zero. And people are going to want to spend whatever they can afford to get more of this. >> We would agree with that. We would agree with that. I mean, it’s been fascinating to watch um Claudebot. It’s an open source. Oh my goodness. Oh my god. It has exploded in a weekend. >> So to all of our all of our subscribers, if you’ve not yet seen onx or gone to claudebot.ai, I think it is, and looked at what’s available here, this is your your your personal version of Jarvis. That’s what I call it, you know, on your computer and in this case on someone’s Mac Mini in the example that I’ve seen uh take the internet by storm. And it’s being able to communicate via chat and ask it to do things and and having it actually wake up you wake you up in the morning and show you all the things it’s done at night like an eager employee or intern. It’s amazing. >> Yeah. It’s not just techn It’s like

[00:32:01] sunno or Arduino boards. It’s a cultural thing, too, where you can show your friends what you built last night and blow their minds. Sorry, Kathy. I could >> Yeah. No, no, no. I just wanted to clarify that it’s uh Claude as in C L A W D. It’s a little bit of a play on on the Claude we know and love, anthropics. So, um and a and it is open source. uh our um our lead AI analyst uh has used it and already it’s organized him. I can tell I can tell how how much better organized he is having just a weekend with Cloudbot. >> Yeah. Amazing. And what makes it different is it connects to all your social media accounts, to your email account, anything on your laptop. Um, so it’s incredibly powerful for automating your life, showing your friends, you know, whatever in real time without getting in the loop. And the reason it didn’t come directly from the big AI

[00:33:00] labs is because it could also scramble your entire computer in two seconds if something goes wrong. And and so it’s it’s a little bit dangerous that way. So be be careful with it. But that’s also what makes it so powerful. >> Alex, what are your thoughts on the agentic slide here? >> Well, first I I’ll point out it’s no longer Claudebot. It’s now Moltbot due to trademark issues with Anthropic and its mascot is of course a lobster. So we’re we’re very much living chapter one of Accelerando at this point. We’ve caught up we’ve caught up with the future and I’ve written in my newsletter >> something to do with the lobster. I was going to say >> this is convergent evolution. We we find ourselves with these intelligent autonomous lobsters and people are giving the lobsters digital homes now and giving them digital personhood. We have fully caught up with chapter one of Accelerondo. I wrote about this in my newsletter today. I I I think going back though, Kathy, I think you you raised a really interesting point that I haven’t heard to my knowledge anyone else

[00:34:00] articulate, which is so many people, including folks on on this pod, are hand ringing about GDP and oh, won’t hyperdelation somehow reveal the intrinsic misalignment between GDP growth and real wealth growth? But you you’ve I think put your finger on a point I’ve never heard anyone else articulate which is that as humanity delegates more and more services to to agents that delegation looks like commerce from a GDP perspective that by basically carving up humanity individual humans roles and productive services and subdividing them all of the interactions between those subdivisions many of which are going to be agents add are accretive to GDP and look commerce. So if anything, you’re you’re painting a story for the exact opposite of how GDP statistics can explode in real terms while real wealth perhaps remains constant as well. So I guess my question for you is if you could wave a magic

[00:35:00] wand and define Kathy Wood’s perfect def definition not of GDP growth but of real wealth growth for humanity, how would you define it? >> Well, wealth growth is very much tied to productivity growth. uh and I’m talking about real wealth growth. I’m not talking about real estate and priced driven uh you know I’m talking more about >> uh technologically enabled productivity gains um that you know we got a taste of it just a taste from the 80s and 90s um it was it was the in the pre-in age starting with a PC then pre-in age um and and pre-mobile age. But back then, which was a magnificent time for the financial markets, wealth creation uh was stupendous as software for the

[00:36:01] first time unlocked. We went through a frustrating period in in the 80s. I was there uh where technology it almost seemed as though it was hurting productivity. Um there were some people out there saying that and then of course Microsoft came along and and boom and then we had the internet boom. Um so that was foreshadowing just foreshadowing what we’re going to experience here. So there was if you look at growth growth accelerated not a lot but it accelerated uh certainly from the horrible 70s uh growth rates productivity was I think zero or negative for a good part of the 70s into the early 80s and uh then we saw productivity picking up and the financial markets boomed uh and inflation came down back then and and the reason I’ve thought about it so much is very early in my career um we we had

[00:37:03] taken a position that inflation was going to come down. Most people thought that couldn’t happen without a depression. It happened for the opposite reason. It happened because of productivity growth associated with these technologies a sensible monetary policy as well. I will say productivity growth lifted unit growth and the history this is unlike what you would learn um from Keynesian e economics which that’s associated with Harvard primarily which says growth is inflationary growth is not inflationary growth is is disinflationary and in this world we’re going into it is deflationary deflation in the good sense when a when the price of something drops, the demand for it explodes. >> And we see that here on on this chart right here on intelligence, right?

[00:38:01] >> Please, Alex, go ahead. >> Yeah. So, so maybe just a follow-up, Kathy, on that. So, this seems like the crux of not just some of these amazing visuals, but also, I think, your broader thesis in investing that GDP may be not the best macro indicator for progress. It sounds like you’re saying something like per capita productivity is the key macro indicator you look to. But I I guess I’m curious e even per capita productivity ultimately you have to resolve that quantitatively down to units of dollars or or some other units and your your investments via ETFs. Uh I I think the the question in my mind is like what is the right benchmark to hold yourself to? you’re you’re very clearly in the business of investing in the future. Uh and the the broader call it the S&P 500 may or may not you know m Mr. Market is a little bit psychotic sometimes may or may not be properly

[00:39:01] measuring progress toward the future. What if if you had to put a single metric to it what metric is it that we can all sort of sit down and calculate that that you’re optimizing for you think that progress itself should be indexed against? Well, first of all, in terms of indexation, that that is a live wire for me because uh that is what has happened to the financial markets. Unfortunately, they have and and Elon Musk feels very strongly about this. We had a an X spaces uh session with him and spent more time than I ever dreamed we would on this topic. But uh the S&P, the NASDAQ, uh the companies at the top of those lists are there because of past success. If we are right and we’re moving into the most disruptive time from an innovation point of view in history, uh then the traditional world order is going to be uh disturbed. Now

[00:40:01] the S&P 500 uh if you look at the IBIT Ibbits and Sinkfeld uh studies uh the S&P 500 has returned nominal returns have been in the high singledigit range over time. >> Um uh we think that that’s going to that that’s going to change. Um, but it’ll take a while for the S&P to catch up because they need to see the revenue growth. They need to see profitability and so they are lagged in terms of getting these new stocks in there. Um if you look at our big ideas, we go into a sess section where we say uh disruptive innovation we believe is going to compound uh in terms of returns in the market at a 35% annualized rate for the next five years. >> Which of your funds is focused on that? >> We are all of our funds are focused on

[00:41:02] it. our flagship which uh incorporates all of the platforms is ARK. uh and so yes and that’s a that’s a tall order you know we went through a very tough period innovation everywhere was crucified including in venture uh as we went through the supply shocks uh and the monetary policy associated with co um so very few people believe this because innovation has been recently through such a tough time we think it’s coming out the other side and that that rubber band has struck stretch and in fact co has accelerated the digitalization of the world right of every part of our lives >> and just just looking here ArkK has seen about a 31 to 33% uh annualized rate of return over the last two years which is pretty amazing >> yes and and yes so our three-year

[00:42:01] numbers uh are are starting to ramp towards the the the number we’re saying but uh in order to average, we’ll have to go past that 35%. And uh I think we will, but again, most people think, you know, there in our business, their eyes roll because they’re so wedded to these benchmarks. Now, if if I’m going to try and get at an economic measure of progress, I’m going to look while most people focus on GDP that is uh the other side of uh gross national income which is measured uh we get a lot of information from the tax uh you know the IRS and the state and local tax authorities. Uh so that metric is going to be more accurate in terms of the kind of growth rate and

[00:43:03] they should equal but they don’t. There’s always a a statistical discrepancy and that discrepancy is growing because we can’t measure uh from an output side some of uh some of the effects that we’ve been talking about here. that will show on the income side however >> so GDP is the answer or GNI it’s not some sort of per capita productivity >> right I think it would be GNI uh productivity is also something very hard to measure and and that’s why you know we believe it’s being under uh estimated today and it is about 2% on a year-over-year basis we think it’s undermeasured Now what does that mean? The way the GDP is constructed um if we are underestimating

[00:44:00] productivity then we’re underestimating real GDP growth and we are overestimating inflation. So it’s a little puzzle and that fits together uh but so much mismeasurement that you know policy makers if they are not in the mindset we’re in and they’re trusting these numbers that are coming out they are going to make mistakes. >> Well policy makers also choose the numbers convenient to make their points >> uh that very often and that and they have lots of numbers to choose from. I want to move us forward into this next. you know, in your big ideas report, you had a conversation about US versus China. Um, and I think this is driving very much of the, you know, Trump policies today. Uh, David Sax speaks about this currently. This has been a large conversation just coming back from Davos. >> And, you know, there’s at the same time we have people speaking about we need to slow down because we don’t understand where we’re heading in with the

[00:45:00] emergence of AGI and or ASI, whatever you want to call it. But the boogeyman is if the US doesn’t dominate um it it has a chance of failing globally financially. And by the way the number uh you know we can talk about the US dollar as a as a global currency reserve which has been falling in terms of its uh uh you know utilization globally which is a which is a challenge at the same time that this is going on. So, uh, would you take a second and and walk us through this chart, um, that is from your report? >> Yes, we have been tracking all of the the models, large language models coming out of China. They’re all open- source. We uh uh actually force China into the open-source movement. And I love open source. I have a high degree of conviction in open-source. Linux uh has been the poster child. >> We as in the US you’re saying

[00:46:02] >> uh uh we US forced China because we stopped selling our software into China. The companies did. This was not a government initiative because of IP theft. And so they stopped selling software in and here with a deep seat moment. What did we learn? Wow, have they capitalized on open source and now they’re ahead of us. Uh, and Llama 4 falling flat the way it did. Um, which was Meta’s open-source attempt. I think it’s now going closed as well. Um, tells me that China’s stealing the march from us on open source. Now, Claudebot, uh, I’m sorry, I I forgot. I didn’t know it had been renamed. Thank you for telling me. Did you say it? What was the name? >> It’s It’s now malt as in a crustaceian molting its shell. M O L T. Maltbot with its mascot being M Mr. Lobster.

[00:47:01] >> That had to be just yesterday, right? >> Kathy, you’re not you’re not more than 24 I guess 24 hours in AI time is like a year. But Kathy, Alex’s favorite book, and I think Dave and I are right behind him on this is a book called Accelerando that opens in chapter 1 with the neuronal structure of lobsters being beamed out to the universe and it goes from there. But Alex tracks the news at minute-to-minute levels. So, so feeling like you’re behind Alex is totally normal for everybody. >> Well, you know, it’s interesting. We just got out of our morning meeting and usually I’m right on we are all right on top of all of this. So, thank you for for letting me know. I’ll let everyone else know. And you know the interesting thing about lobsters, I’m on the board of the Dolly Museum here in St. Pete. There are only two Dolly Museums, uh, one in Barcelona and one here. Uh, he featured lobsters in his art

[00:48:03] regularly. Um, so I’m going to have to read this book. Yes. >> I think lo I’ve made made the point in my newsletter, lobsters are the new mascots for the singularity. >> It’s so interesting because >> I’ll text it to you, Kathy. I’ll text it to you right now. >> Fascinating. Dali was so technologyoriented. I don’t know if you know that about him. He he um his art included the double helix, so DNA, right after Ro Watson and Crick really identified it. Um and it in the early 60s, I think they did in the 50s, in the early 60s, there it was in his paintings. And you know, so I find this fascinating, you know, I find this fascinating, the lobster uh element of it. Anyways, >> crustation embodying economic growth. >> Yeah.

[00:49:00] >> All right. I’ve just I’ve just texted you that Kathy, so enjoy. >> Thank you. So, the CL Claudebot or Maltbot is um open source and I think that started in the US. So, maybe that’s where this is going. And I was just on a a call, it’s called the Bitcoin brainstorm um with uh Alex Gladstein who’s uh now become infatuated with uh AI as well as Bitcoin and how they can work together. Uh but he was all over Cloudbot and it’s just I mean it’s just taking the world by fire. And so this is individual agency at work here. uh not the big companies at work. So, it’s going to be fascinating to see where this goes. Um anyway, so I’m glad we’re hopping back into the open source mo movement. If you look at and we have this in uh in in big ideas as well. If you look at investment as a share of GDP

[00:50:04] uh and now this includes property and it’s both in China and the US. In the US, our share of GDP is a little north of 20%. In China, it’s 40%. And it’s been there since they moved into the World Trade Organization. So, their quote unquote investment now pro it includes property, but we know that property is deflating big time there. So their investment is staying up at that 40% range because Xi Ping has moved away from uh solely common prosperity as uh the slogan towards new productive forces that’s all about technology. So they are pouring money pouring money into this and uh we should be on guard

[00:51:02] and I think it’s great that we know about their open-source movement uh because there’s nothing like competition to get the US going. Uh so I actually think the competition is very good and if you want to see uh uh China at work um in in AI as applied to health care it’s unbelievable and Peter I I know you’ve talked about this. Yeah. >> It’s unbelievable what’s going on. Alex Alexov uh who’s in who’s the CEO of Encilico Medicine just went public on the Hong Kong exchange >> 1,200 times overs subscribed and I talked to I just talked to him in uh he was in Beijing yesterday I was zooming with him and uh the market there in biotech is exploding. It is >> it is uh and the companies are going public uh and there is a financial market driving the acceleration and the

[00:52:00] government is pouring money in. >> It is it’s the good thing is >> and the clinical trials they’re doing a far better I mean in terms of the raw numbers many more clinical trials happening in China now than the west. >> Yeah. >> Yes. And part of that is our regulation is so uh much more strict than theirs. That is changing. >> Yeah. The new FDA commissioner is doing a great job uh you know bringing down barriers. See, can I hear your voice in the US versus China conversation here? >> Yeah, I I continue to think that as we kind of push towards abundance that this tension is less relevant. I also kind of made the point in the last podcast that I think um this will be won or lost at the application layer and I think the US has such a massive lead in the application layer that uh it’ll it’ll win there. I mean the it’s incredible to me how much the US via Silicon Valley thinking has blown the world apart and

[00:53:01] taken over on all application with one exception of Tik Tok and maybe Spotify but other than that >> what about the energy layer here the inner >> huge as we bring energy closer to the inner loop uh it’ll be a huge challenge that was definitely true >> I think Kathy’s point on open source though is is far more important than that makes it sound because you know when when you look at the number of people actually working on these core algorithms inside Anthropic and OpenAI. It’s a tiny tiny tiny group of people and they’re super arrogant. They think they’re the smartest people in the history of algorithms and you know on and on and on and as soon as you move all the research out of open source and into just the closed models the number of ideas that can flow into the US version of it gets throttled tremendously and it does capture all the money and and it does also address the safety issues >> but it also slows the innovation like crazy. So cloud versus mult cloud/multbot, right? That’s the application layer making it available to anybody to implement their functionality

[00:54:01] and that’s where open source thrives and that’s frankly where the US really thrives. >> Well, it’s consistent too with past Chinese, you know, in Chinese past races to to catch up. You know, they they poison the air, poison the water, whatever. Just run. Don’t worry about the regulatory issues. Don’t worry about the toxic fumes coming out. We need to catch up. So the the AI equivalent of that is look just open source everything allow our 1.4 billion person population to try things and we’ll innovate like crazy. And it’s they’re just right. They’re fundamentally right having that many more people work on it. Now the only good news for the US is that that open source flows right back to the US. It’s not like it’s it’s hidden in China. But I really do believe the open source community innovates much much more quickly. But it’s also very very dangerous in terms of you know all all the negative use cases. >> It’s interesting that uh our government has had nothing to say about Meta Platforms acquiring Manis. Now maybe they will. Their Manis is open- source

[00:55:00] uh Chinese uh company as well. Um, and it is also interesting to have watched Sam Alman and Jensen Wong uh when when they talked about deepseek they said hey that algorithm was pretty clever you know you know kudos to to China and and the deepseek uh founder uh but guess what uh that has given us the opportunity to distill uh into our own models So it’s very interesting on the software side. Our government’s not having much to say u but uh the hardware side of course it has much more to say. This episode is brought to you by Blitzy autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprisecale code bases with millions of lines of code.

[00:56:01] Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and pre-ompiles code for each task. Blitzy delivers 80% or more of the development work autonomously while providing a guide for the final 20% of human development work required to complete the sprint. Enterprises are achieving a 5x engineering velocity increase when incorporating Blitzy as their preIDE development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today. >> Um, I’m going to move us to our our next topic here. Just a quick shout out to Google because I end up using Google Slides here and the beautifification function. Kathy is what makes

[00:57:00] >> interesting. It’s like we have to do this. >> Yeah, they’re Google Google’s AI does an incredible job at beautifying slides. So just uh you know the right tool for the right the right purpose. >> Absolutely. >> Peter, I got to I got to hand it to you. You moved off PowerPoint. >> Yes. Well, listen, it’s just like, you know, Google builds a better product. Uh, all right. Let’s let’s talk about Bitcoin. Um, >> yes. >> So, uh, you know, I you were on stage with me live a few years ago, um, and then on video two years ago, um, because of, uh, uh, COVID, but, uh, your prediction of getting to a million dollars of Bitcoin, uh, do you still hold out for that kind of a a target? uh what are you seeing that gives you hope even while we’re seeing this uh uh recent downturn? Uh give us your sort of thoughts and projections on Bitcoin, Kathy. >> Sure. Uh we have not moved off that that’s our bull case one and a half

[00:58:01] million in 2030. Uh that there are a few compositional changes. uh one stable coins so especially tether in the emerging markets uh ha have usurped the one of the roles that we thought bitcoin would serve and that is we thought that before stable coins that people would and they were they would um buy bitcoin as an insurance policy against uh confiscation of wealth either in the form of inflation, hyperinflation and massive devaluations uh which occur regularly in the emerging markets or outright confiscation of wealth. Uh and so stable coins now serve that purpose. Stable coins are backed effectively by the US dollar. So and therefore are hostage to our fiat u

[00:59:00] monetary system. Uh so that that would have taken our price target down by 200 to $300,000. On the other side, what has happened to gold recently? Gold has doubled over the last two years uh and uh and has outperformed Bitcoin royally in in the last year. Uh so the digital gold role and we think with intergenerational wealth transfers accelerating here throughout the world uh that the younger generation will diversify into a digital gold uh option rather than the physical gold. it’s more their world and uh so we think that role has uh increased or that that that the price should be supported by what has happened to gold. Now if you look at a correlation matrix between 20

[01:00:00] and 25 the correlation between Bitcoin and gold has been almost non-existent >> 0.14 uh and so uh but if you look at what’s happened historically certainly the last two cycles gold has led Bitcoin so we think Bitcoin is getting ready for another big big run. What has happened in the last few months is uh uh is 1010. So October 10th was the flash crash caused by a software glitch at Binance and it got uh it got a lot of highly leveraged either speculators or investors way off sides. There was an automatic deleveraging that took place. uh uh about 28 billion dollars worth of being offsides and we’re hearing that that is pretty much cleared uh cleared out. Uh so we have very high hopes for

[01:01:00] Bitcoin and and talking to the team we had a number of people on the Bitcoin brainstorm yesterday. Um, you know, our our thinking is, okay, stable coins are uh they’re serving a humanitarian purpose, this insurance policy uh backed by the dollar, but uh and consider this is the Bitcoin crowd. uh they believe and and I do too that that Bitcoin uh it that its cause is freedom, financial freedom from all you know government oversight and so forth uh and from um and from uh censorship and seizure and all sorts of things. As emerging markets wealth grows and we think this is a global phen phenomenon with all these technologies they will move towards from a savings point of view right now they’re hand-to-mouth for the most part but from a savings point of view they

[01:02:01] will move into Bitcoin >> like El Salvador I mean it Bitcoin was always viewed as the counter to the inflationary pressures the dollar that as as the world in becomes more instable with wars inflation increases postco more money is printed that people would flock to bitcoin to sustain wealth versus being having it inflated away and I don’t think we’ve actually seen that do you >> well I know that if you look at uh from the bottom of the bare markets equity and crypto in late 22 um bitcoin has gone up I I think it’s roughly 360% So definitely one of the reasons was the inflation back then and uh fears that the Fed would not get it under control. So I think it has played the role. Um the question I get a lot is wait a minute you’re you’re expecting not

[01:03:01] inflation but deflation. >> Doesn’t that take away an important role that Bitcoin that you think Bitcoin’s going to play? And uh our answer there is yes, Bitcoin is a hedge against inflation. It’s mathematically metered to top out at 21 million. It’s going up8% per year right now, which will drop to point4%. It is going its supply is is now rising more slowly than gold’s uh supply because miners gold miners can just go out and you know uh uh they can respond to this price signal. So their mining has picked up. Um but what about the deflation side? Well, if you think about 089 which was the catastrophic deflation uh threatened a financial a global financial bust uh introducing all kinds of counterparty risk. Bitcoin is a

[01:04:02] hedge against that. If you self-custody uh if you self custody Bitcoin uh you’re not subject to any counterparty risk. It’s yours and it’s in your wallet. uh and uh so we think it’s got a very plays in a very important role in both and especially if we’re right on how disruptive the world is going to be disrupted by these five tech uh innovation platforms 15 different technologies that are converging uh then you know there’s going to be a lot of chaos in the traditional world order and there’s probably going to be a lot more bankruptcies out there than many people ect. >> You know, speaking of chaos, Kathy, we’re getting a great case study right now in Iran, you know, where I spent my childhood. And we had a an intern in our venture funds, Far uh and she said her her parents are still in Iran. She’s Iranian and her her parents are still in

[01:05:00] Iran. And all the transactions for years now at the bazaar where we used to buy rice and stuff when I was a kid, they’re all done with Bitcoin. Everybody has to have a phone. The only way you can actually buy things is with Bitcoin. And you know that that’s been going on for years. I think it’s probably illegal. nobody cares and now you’ve got a revolution. You know, obviously the currency is completely unusable at this stage. It’s, you know, the the country is teetering on the brink. >> So, and I noticed in the blockchain ledger reports, you know, this is a couple years ago, a hugely disproportionate fraction of transactions >> come from Iran. So this will be a good bell weather because you know that kind of disruption you know Venezuela and all around the world you look at just massive fraction of the of the population of the world lives in unstable places. So if all of Iran moves to Bitcoin because people are going to be fleeing the country imminently as quickly as they can get out then that’s a bellweather and a case study for what could happen to probably you know over half the population of the world with all the disruption that’s coming. I I

[01:06:00] have I have an I have an Arc Invest worthy tracking system um which is um the market cap of gold is almost 20 times that of Bitcoin but the daily trading volume of Bitcoin is only a quarter of what gold is is already a quarter. So the proportionately the amount of trading volume of Bitcoin is way way exceeds that of gold and I find that a really fascinating indicator. >> Yes. Well, in India and Iran too, huge hoarders of gold. You what you do fundamentally with your surplus money is you try and buy as much gold as you can and because you can leave the country with it and because it seems to hold its value and and nothing else is is stable. But if people start to trust crypto or bitcoin in particular instead of gold like you said there’s a generational mindset shift. >> So I think in Iran right now it’s a transactional mechanism. You can’t use gold easily to buy a bag of rice uh but you can use bitcoin. But I think if the mindset shifts to store of wealth like Mike Sailor is saying then that will percolate across the world you know very

[01:07:00] quickly across one generation. >> Absolutely. We we agree wholeheartedly. >> So this next slide here is digital assets could reach 28 trillion in market value which implies their their entire size of the US stock market back in 2010. I mean, >> right. And it’s the size of the US economy now roughly. >> Yes. Exactly. It’s insane. I mean, and growing um >> and and the laws are falling to enable this and companies are popping up to accelerate this. >> Uh you know, this this is smart contracts growing massively. >> Um >> yes, >> Katherine, do you have any thoughts? So, this is all about store of wealth and replacing currency, but what about the replacing the IPO? you know, if if AI takes off and Elon is right, we get tripledigit kind of growth rates, >> the the rate at which people need Yeah. Does the ICO replace the IPO or how’s that going to work? >> Yeah. Um you know a lot of people have

[01:08:00] been ex in the early days of Bitcoin and you know and especially Ether uh there was this kind of thinking that we would uh that the um you you know we’d have a much better distributed um opportunities uh in in the private markets. Uh I think you know we’re we’re seeing a lot of uh we’re seeing for example Robin Hood. Robin Hood wants to work with the big companies to uh to decentralize um the ownership of these companies. Uh and we’re doing that too. We’re we’re we’re democratizing with something called an interval fund. Robin Hood is very cryptosavvy and from an infrastructure point of view

[01:09:01] is um is building uh that up and I wouldn’t be surprised uh to see um a version of what we originally thought was going to take place um without an intermediary happen first with a a Robin Hood. So, so I I think it’s very possible in the next in the next three years. >> Yeah, >> I love that view. We have to we have to study that closely as it evolves. Something something is going to happen. There’s no doubt. >> The secondary I mean Dave, the secondary markets have become some level of liquidity, right? So, you know, Kathy uh uh Dave as the head of of link ventures and link exponential ventures, you know, we’re buying into companies out of MIT and Harvard at a 1020 million valuation. first check in. They’re growing to a hundred million. We’ve had a number of them grow to a billion, two billion dollars very rapidly. And these are companies started by 20 year olds, right? 19 year olds. It’s it’s insane.

[01:10:01] >> But um you know, getting them to an exit, uh unfortunately, the IPO market is beginning, but hasn’t frothed up to where it’s been. in the M&A market has been uh suppressed where where companies are not buying companies, they’re buying, you know, sort of rights to companies these days. I guess the question is, you know, Dave, you’re seeing selling into the secondary markets as a way to provide interim liquidity. Um, and how do we how do we accelerate that, right? Um, >> yeah, it’s a great question because, you know, I I talked to Michael Carman over at Wellington about this because, you know, when when Uber was private, >> uh, he was a huge investor, multi-billion dollar investor from Wellington into Uber and he was like, you know, we never take this need to take this thing public. We can just trade it in the private markets forever and that’s the future. And then what happens is people get a little scared. They run back to the US public markets. anytime there’s any kind of trouble, turbulence, you know, COVID, whatever, it all falls back to the US public

[01:11:00] markets because that’s the last kind of trustworthy thing to lean on. >> Um, but it clearly won’t keep up with the rate of AI. So, something is going to change. There’s no there’s no doubt about that. It’s just that, you know, anytime that there’s any kind of fear in the world, it all falls back to, well, I can trust the SEC. You can trust, you know, GAP accounting. And and at the end of the day, if everything trades privately, >> General Electric, >> I mean, look, A6Z is 90 billion now. General catalyst is 60 billion. That’s a fair amount of money. But by Kathy Wood standards, that’s a joke, right? In the Kathy world, the numbers start at trillion and they go to 100 trillion. And so if you’re not tapping into that capital pool, you’re not going to really drive AI. And so so yeah, there there’s another level of scale we need to penetrate somehow. >> Dave, on that qu on that note, a question for you, Kathy. Are we going to see hundred trillion dollar companies by 2030? We’re seeing the $5 trillion company now. We’re about to see SpaceX

[01:12:01] go public, maybe merge with Tesla. curious about whether you think which way Elon’s going to get liquidity for SpaceX or stability. Is it going to be a merger or an IPO? And then, you know, can we see tens of trillions or hundred trillion dollar valuation on companies? What are your thoughts there? >> Yeah, it’s interesting. Um, and I’m not sure if he said it on your podcast. I’m not quite sure where I heard this, but uh uh he talked about he said, you know, I I can see convergences among my companies that I didn’t expect. Uh and we we’ve been saying that for some time because, you know, in in the world of AI, what do you have to have to win? You have to have proprietary data. And think about all the proprietary data he has, different kinds of proprietary data. Tesla, the language of the roads. Um, Neuralink, uh, he’s got Multiomics data

[01:13:01] now, uh, to source. Uh, space, nobody else has that data. Um, X, nobody else has that data either. So, um, and Boring, no one, no one has that data. So, I could see, yes, 100red trillion. I think it’s I think it’s going to happen because of convergence. The >> convergund trillion dollar company come on come online by 2030. >> I I think there could be and but but I and you know the the leading candidate is is Tesla for the reason I just said and there could be some combinations uh taking place as part of that. Uh so you know it is interesting also uh I know there are rumors about SpaceX lining up bankers and I never thought that SpaceX would go public. I didn’t think it needed to go public. I don’t and I you know I think Elon’s experience with

[01:14:01] Tesla in the public markets hasn’t been you know the most welcoming. Um, so but you know I think if I if SpaceX were to go public, it is because of these this orbital data center opportunity. Uh, and there you have it. Right. >> That was on this pod actually, Kathy. We we we this is one of the incredible things about Elon. We threw him a kind of a softball and said, “Look at everything that’s converging in your empire toward this one centerpiece. If you achieve the the Starlink and the global data center in space with satellite or with laser links, I mean everything you’ve ever done in your life converges to this one monstrous hundred trillion dollar success. The foresight must have been incredible. He he said, “No, no, no. It’s totally luck.” These had nothing to do with each other. And I thought that was just incredible. You because it was his opportunity to lie like crazy, which he would never do, and claim genius, which he would never do.

[01:15:01] Yeah. >> And he completely said, “Nope. It’s just But you know what it is? I AI is causing everything to converge.” >> Yes. No question about it. That’s why we set up our firm, our research the way we’ve set it up. And think about it with Tesla. Why did we get that more right than anybody else on the street? uh it is because we had our robotics, our energy storage and our AI analysts working on it together. >> In a traditional firm, you had the auto analyst, the expert in the internal combustion engine humriven car >> uh as the sole analyst. the tech analyst might have been fighting for it and there’s a little bit of turf war there, but the tech analyst lost and so they didn’t get it right and they’re still not getting it right. >> Yeah, Kathy, I define an expert as someone who can tell you exactly how it can’t be done right. And so

[01:16:01] >> I’ I’d be curious on that point, Kathy, to get your sense given that you operate a number of actively traded ETFs for the the notion of efficient market hypothesis. And surely it must be the case that in your mind for for you to rationalize running actively managed ETFs that the market must be sufficiently inefficient to motivate those ETFs. But I’m I’m curious in as part of your technical thesis, we’re surely moving to a world of super intelligence to the extent we’re not there already where super intelligence is itself an active trader in the market already on a a daily volume from a daily volume perspective volume is completely dominated by ALGO traders. At at what point does it make sense due to an abundance of super intelligence not even to bother with actively managed ETFs anymore and just let indexing take over? So that’s a great question. Again, uh

[01:17:00] algorithms are yeah, certainly there’s a pattern recognition part uh to algorithms, but if you think about um AI, AI should obliterate the the the benchmark sensitive portfolios. And you know, I think the market’s never been more inefficient than it is today. And the reason for that is after uh the tech and telecom bust in the early 2000s and the even more so after 089 the financial crash. Um the risk aversion in the markets uh re reached an extreme. Uh and I think even with this administration and all of the and and it had a first administration too. there was you know a lot of uncertainty a a lot of um angst uh and a a lot of volatility so it pushed investors even more towards their

[01:18:01] benchmarks um I think anyone with that strategy is making has made a huge strategic blunder and what I’m excited about is uh prediction markets prediction markets are going to bring about uh the return of truly active investment. You know, people who call themselves active investors and at the heart of the active investment is an index uh where it looks the portfolio manager looks at the index and says, “Oh, I’ll take a little more of this and I’ll take a little less that based on my always shortterm uh uh short-term time horizon.” It’s gotten increasingly short because of all I just said. So they just take a little bit more of this stock, this mag six stock and a little less of that magn six stock and they all look alike. They all look alike. I we look like we look like a a different duck

[01:19:02] altogether. I mean we don’t look anything like them. And the reason is we’re doing original research that is very forwardlooking next five years. And you know that’s derided by the traditional financial markets. Uh I think the chat ch GBT moment started to change that. Uh that was a very important moment I think from for the investment world as well because everyone’s using it and they’re saying okay wait a minute the ground is shifting underneath me this AI thing. What does this mean? So finally we’re getting uh more uh forwardthinking institutional investors. The retail investors have always been futuristic, you know, and so that’s why we’ve appealed to the retail investor more than to the institutional investor who is also playing it safe. Um, so I think

[01:20:00] it’s good that the I think you’re right to ask the question, but I think the first order effect is to destroy anyone that looks like a benchmark right now that there’s no value added there and to start rewarding those who are doing the original research to try and figure out the way the world’s going to work. and pattern recognition. We’ll harness AI ourselves to we already are to uh to try and figure that out. Uh and as you say, Peter, we’re going to have to work on our charts, beautifying them with AI, and that’s exactly what we’re going to do. Uh I think this is a a very good lesson. >> So, uh let’s go to the innermost loop. Let’s talk about energy a little bit. Uh again, a couple of charts from the big ideas report 2026. The link is down below. So, uh, increasingly efficient energy is powering the global economy. We’re seeing kilowatt hours per dollar of GDP drop. We’re seeing global

[01:21:00] capacity increase. Um, a lot of solar, again, mostly from China that’s running circles around us. >> At the same time, we’re seeing uh the uh cost of solar and batteries decline. I mean incredible progress on batteries in the last in the last year. Uh so these two things I mean I don’t think people real I mean they realize and you know our subscribers listen to this show regularly realize it because we talk about how critical energy is fundamentally it ties to not only GDP but standards of living and health and education to every nation on the planet and especially with data centers right now uh fundamental to dominance as a nation state. uh thoughts on this Kathy? >> Yeah, if you go back to the last chart, one of the things I find fascinating um we focused a lot on nuclear in this in this uh big ideas, but look at the yes, the efficiency of all country or major countries, but China is half as

[01:22:03] efficient, that’s a bit of an exaggeration, as those other countries. Um now, what is it doing to offset that? it is building they may have more now 28 large nuclear reactors >> uh uh at one time the US is not building one large I know we’re we’re uh we’re re engaging with some of the old ones but uh I think our regulatory stance is changing there dramatically and we will um it so that that’s one thing I took away from from that um you know I I think uh what what’s wonderful about innovation and and what you do is helping people understand what they’re saying. Yes, we we need to become more energy efficient. A given and we are becoming more energy efficient. Economic activity is energy transformed.

[01:23:01] you are helping people understand that uh others who just blindly say energy is bad are not thinking clearly about what they’re saying. They’re basically saying they want us to turn back to the dark dark ages. Um if we’re going to progress, we’re going to use more energy. What’s also interesting about the nuclear side of this is the US and Japan in particular uh in the 70s uh started regulating uh nuclear and killed the industry. uh the construction costs which had been coming down in tandem with Wright’s law, it’s a technology, uh they turned up and basically if we had continued along Wright’s law with nuclear um to today, electricity costs in the United States would be 40% lower. Mhm.

[01:24:03] >> And so I uh I think that our renewed enthusiasm for nuclear is important will get us back on that rights law track. Uh and yes along with solar and of course Elon uh with orbital data centers is you know uh would be turbocharging the the sourcing of solar uh for data centers. I’m curious, Kathy, we we talk on the pod sometimes. You perhaps know the website WTF happened in 1971.com. Uh assuming you’re from assuming you’re familiar with that. I is it your view that nuclear or the overregulation perhaps of nuclear energy is what happened to the US economy in 1971 that set us on a different course? Uh, I think that going off the gold exchange standard, closing the gold window and not having monetary policy

[01:25:02] linked to anything except human frailty actually. Um, was and then of course we had wage price controls, all kinds of distortions and just a general increase in regulation. Uh, and nuclear epitomized that. that happened in 1974 or 75 I think. Um so yes it was that that moment uh going off the gold exchange standard having no discipline uh oil prices quadrupled almost immediately and uh set us off on a on a very bad course >> and we stopped sending humans to the moon. A number of things happened around the same time. >> Yes. Yes. And then regonomics, the combination of uh vulkar and regonomic policies which are being repeated today. The the deregulation tax cuts. Our corporate tax rate, our

[01:26:01] effective corporate tax rate now in the United States is I think the lowest in the developed world down from nearly the highest um before the Trump in his first administration started cutting the tax rates. The depreciation schedules in the new tax law are astonishing uh and they favor innovation and favor innovation in this country. So being able to depreciate a manufacturing structure completely in its first year of service instead of over 30 to 40 years. the companies who build manufacturing facilities here in the United States, as long as they start before 28, end of 28, uh they will get huge tax refunds that they can then plow back into R&D and cutting prices. >> Pardon? >> Re-industrializing.

[01:27:00] >> Yes, we are. We are. Um it’s I think we are going to see a a a an economic boom in the next few years >> way beyond this is this makes Elon’s you know 5x increase in GDP growth uh uh you know sort of seem very very reasonable. Uh Dave I’m curious you and I have been having a chat on text about you know where to invest next. Again, not investment advice, but you know, energy energy infrastructure, energy production from SMRs, from fision, from fusion is a little bit far out for me right now, but also the uh you know uh the data center construction and so forth. I mean, these numbers tend to seem like yes, this is where we’re going to see the most investment, the most growth in public companies. What do you think? What’s different about us and Kathy and our tech thread Peter is that >> uh we’re not trying to deploy 10 billion dollars at a time or so we can afford if you look deep into the data center stack you know all these components in the

[01:28:01] supply chain >> have suddenly got infinite demand we saw this with boom supersonic right a company that was making hypersonic engine suddenly goes up 10 or 100x or whatever in value because they can use the same components to make generators that are backlogged for years >> we own that in our in our venture fund too I I presume you Who? >> Oh, I wish I I knew the the founder of Boom and I was like, “Oh my god, that is, you know, a supersonic airplane dealing with FA is crazy.” You know, it’s going to be an infinite, you know, dollar sync. And then they found a marketplace. >> They found a market, a brilliant pivot, >> a brilliant. So, it’s a case study in two different things. You know, one of them is that anything related to this AI buildout can be a latent 1000x gain if you find it first. The other one is that great teams pivot and a a a deal that looks like, wow, that’s a that’s a quagmire. Oh, wait, it’s an incredible team. >> The rate of pivots now is so much so much quicker than it ever was before.

[01:29:00] So, you always take the great team anyway and stick with the great team anyway. So, it’s two different case studies in one there. But yeah, Peter and I when we’re texting about this that we’re looking for any and all undiscovered, you know, Alex has a lot of insights on photonics and you know, in the the internet interconnect across these huge data centers and getting the data to move very very quickly, there’s lots of opportunity there. Um, but I think it’s all tied to the same theme. you know, if you look just a couple years in the future at massive orbital data centers, infinite demand for chips, uh, and then, you know, just the plumbing and the wiring and everything that it takes to glue all this together. There’s just, you know, latent opportunities all over the place. But any insights there, Kathy, would be obviously valuable. >> Kathy, walk us through the slide if you would. >> Sure. Uh before I do that, um so Dave just said something very important I think which is um great teams you have to start there. Um and what’s happening and the reason we’re seeing these pivots

[01:30:00] being very successful is convergences between and among the technologies to create entirely new industries. Um and and so there are many many more opportunities to pivot. So the risk if you if you of you know passing on a deal because you you say wait a minute we’re going to regulation is going to be a showstopper here. Maybe maybe not you know if there’s a pivot in the way that boom pivoted uh which is right into regulatory arms. you know the the regulators want this world to happen. Uh so I think that that’s important. >> Cumulative investment in global power needs to increase to 10 trillion by 2030. So it’s just making the case that we’re going to be massive investments into power. >> Yes. Yes. Yes. No question about it. No question about it. There are going to be trillions of dollars invested into AI everything. And this is all related to

[01:31:00] AI. >> Yeah. Um, >> I’m I’m curious, Kathy, also ju just on this energy theme. Perhaps you’ve seen the Apple TV show for all mankind that posits an alternative history where nuclear energy in particular is fast forwarded because the space race, humans landing on the moon was never won by the US. Soviets landed first, so the space race continued. I’m curious in the vein of an alternative future history and and you speak the language of rights law and more broadly experience curves. How far behind do you think we are relative to where we could have been if things had not gone off the rails as it were in the early to mid 1970s? Are we decade behind, 50 years behind? Where should we be by now? I think I I think the energy side of things, meaning nuclear in particular, um I can’t say we’re behind. I can say we’re behind new construction now, but in the United

[01:32:01] States, nuclear does account for 20% of our electricity generation. And uh I think and we have more nuclear plants than China does. they are building 28 or whatever the number is now. Uh we need to get going uh on the large nuclear reactors. We need them all. We need large, medium, small, and we’re invested in all of them in in in our venture fund. So, you know, I I I think we lost a lot of time on nuclear, no doubt about it. the whole world ended up in an inflation because we were the reserve currency. And so we we brought everybody into this inflationary age in the in the 70s for the most part. I mean, I know Switzerland, I know a few countries were able to to buck it, but inflation was a global phenomenon. Um,

[01:33:00] and so I I I think, you know, I think we’re in the right mindset now. I think, uh, you know, Silicon Valley has always been in the right mindset. I think I mean, we’re trying to create a new Bay Area here. I think there are that that’s something that I think is important as well that Silicon Valley and California tax law is probably helping this but um is obviously when it comes to AI you know critically important the talent is congregated there uh but we are seeing more distribution throughout the United States now I think that’s also important and I think it’ll be important for the western world as well as the cost of innovation collapses which it is doing an individual agency uh is uh is more and more possible >> you can be an entrepreneur anywhere >> as a single individual >> yes yes

[01:34:00] >> it’s of course China is very entrepreneurial you just have to go to China a few times and >> they’ll blow you away but you know when you think about what happened with Jack Ma and all the tycoons that became a bad thing it was discouraged unlike in the United States. So, they’ve kind of hurt themselves a little bit in in that way. Uh but that doesn’t take away from the entrepreneurial zeal and and frankly I think competition makes both of us better >> for sure. I I maintain that the entrepreneurship in China is so deep and so native they need socialism to put a lid on it. Otherwise, they’d sell their grandmother for a profit. Well, and that’s why Xiinping recently has been um has been making the case for anti-involution. He’s, you know, I think China is very proud of the fact that it’s commoditizing Western markets, but now he’s saying, “Wait a minute. We’re eating our own. We

[01:35:00] are we are commoditizing everything so much that we’re killing our own industries. How about thinking about profitability a little bit more, which is shocking, right? Shocking coming out of China, but necessary. >> We’re going to jump into our final topic with you, Kathy, autonomous vehicles. And there are so many topics that we could talk about. We haven’t even touched on human robotics. Maybe we’ll talk about it in the midst of of Tesla. But let’s jump in. So, the news of course is robo taxis are finally here. Uh we’ve seen uh we’ve seen Whimo uh and uh we’ve seen obviously cyber taxis coming online. We’ve just heard that Uber and Lucid uh and Nvidia is putting their own fleet on the roads. And of course there are dozens of equivalents in China. Uh so here are the numbers. Uh Whimo’s on the rise and Lyft uh and Uber’s on the decline. Uh, and we’re going to be seeing here, you know, robo taxi miles and cumulative miles just

[01:36:01] spike. Uh, and you know, when I’m on the road here in Santa Monica, as I’m driving back and forth to the airport or my kids to school, whatever, we’ll I’ll we’ll we’ll do a count of how many Whimos we see. >> And uh on an average day right now, it’s probably about 10 or 12 Whimos on the streets here. Uh, and I’m imagining in about four or five years it’s going to be 80% autonomous vehicles. >> What do you think? >> We think so. >> We agree. Uh, we agree. Uh, and in this book as well, you’ll see uh that we expect Tesla to be the biggest winner from a platform point of view. Whimo will be second and the reason is uh Whimo’s cost structure it’s dependent unlike Tesla which is vertically integrated that’s Elon’s preference and modus operande uh Whimo is not and in

[01:37:00] fact for a time there they had trouble attracting an auto supplier uh so now they’re working with Ziker and Hyundai and a few others um they have fewer than 3,000 cars throughout the United States. So for you to see 10 in one run uh says they’re probably concentrated close to where you are >> already. So that’s that’s interesting. uh but we think that Tesla’s solution from a cost point of view will be 50% lower than Whimo’s and therefore it will be able to charge less. Now between now and then there’s huge amount of room for both of them uh to compete against Uber andyft because you know with surge pricing Uber’s average average price over the last four years has gone up 40% with surge pricing and so forth. So from

[01:38:00] $2 to $2.80 per mile. >> Uh right. So that’s a beautiful umbrella because we think we do agree and our research corroborates what Elon is saying which is uh that Tesla will be able to price at 20 cents per mile when at scale between now and then this huge price umbrella is is going to cause cash flow to explode at Tesla. >> Yeah, that’s something you’re totally right. Totally right, Kathy. And I I completely didn’t get it until we went to the the uh Gigafactory. Um I I thought Elon, you know, you you don’t like suppliers just cuz you’re a control freak. And it’s just not true. He doesn’t like suppliers because he sees the exponential opportunity to manufacture. The demand is going to go through the roof overnight. >> And the only way to fulfill that demand is to turn raw aluminum into a car on the other side or raw chips. You have to build all this stuff internally and plan ahead. But if you have even a single component in your supply chain like Whimo does that’s constrained then the

[01:39:01] entire supply chain has to wait for that one component. >> Absolutely. >> So so there’ll be yeah infinite demand for both Whimo and Tesla but Tesla will make far far more cars more quickly because because Elon is thinking about doing everything inside that fully exponential automated internal supply chain. Sorry See, I cut you off there. I think one huge advantage Tesla also has if they allow people to own their own cars and turn those into taxis that will be a massive it’s much more exponential organizations friendly where you don’t want to own your own assets right this is why Uber scales so fast and I think that is a massive area of opportunity >> Kathy on the convergence conversation are you tracking the idea that millions of autonomous cyber taxis are inference engines and energy storage devices moving around cities Oh yes. Oh yes. And also tuning into what Elon says regularly about how inefficient our grid is right now. You

[01:40:00] know, it’s not used very much at night and you know uh and and overly used sometimes during the day depending on the weather. So um uh yes uh distributed energy ecosystems. Absolutely. No, it’s just it’s amazing to me how much people underappreciate that if when you look at a a Tesla Gigafactory, you know, right across the street, you’ve got the Optimus factory going up, you’ve got the data center. All of the components in this are general purpose. >> When you look at Ford or GM and you say, “Well, what do you guys do?” Well, we order the the seats from China, we order the chassis from whoever, we order the drivetrain from whoever. If they want to become a robot company tomorrow, they can’t because it’s just a bunch of assembly of third party components. It’s a car company. It can only be a car company. The way Elon has set up his empire, every part of that manufacturing supply chain can literally pivot to being a satellite manufacturing thing on short notice. It’s all reconfigurable robots in a in a long chain. And so I I think that’s maybe unique to him. Maybe

[01:41:00] Google’s working on something similar and I don’t know about it. But but that’s the future, right? Like every one of these things can be reconfigured using AI and robots. The other thing that’s happening here in terms of our auto sector here in the United States is they’re pulling back on electric. >> Yeah. >> Right. They’re pulling back, but they’re thinking robo taxis trying to figure their how how do I insin my way insinuate my way into it? >> Um, this is all going to be one thing. And Tesla’s Tesla figured this out. Elon figured it out, you know, in his first master plan. Maybe it was the second one, but whatever. He figured it out so long ago. It was there for them to see if they had if they had decided to take him serious. >> I can’t see the automotive industry surviving this. I mean, it’s going to be integrated with AI so that your AI knows your schedule. You’re working towards the front walking towards the front door. It sees you opening the handle. It knows where you’re going to go and autonomous car is waiting for you there. >> Yeah. >> Without you even asking for it. It’s

[01:42:01] just it’s seamless automagical futures that are coming. I I think the key the key point here is that we only need a few tens of millions of cars to cover all of the US vehicular needs, right? And right now we sell 90 million cars globally, new cars a year. This is insane over supply. >> But I think there’s effect by comparison effectively infinite demand for robots in different shapes and sizes. So I I’ll take the position I I think here I do see the automotive industry surviving. It’ll just evolve into robots in the same way that bicycles arguably plus carriages evolved in some sense into airplanes and automobiles. >> Totally right. But the the sector survives and gets bigger than ever. But then within the sector, if you look under the covers at some of these companies, they’re not positioned at all to pivot and make robots and others others are. And you America loves reinventing like just kill the old thing, let’s create a new startup. They just love Sorry. There’s a really key

[01:43:01] point I want to point out here. The the difference between human-driven ride hailing and a fully autonomous is literally more than 10x. It’s an incredible drop. >> Yes. Yes. See, this is the thing. They grew up on uh the internal combustion engine and human driving. So, their DNA is not right. >> Uh they’ll reconfigure, consolidate, restructure, all of that. Sure. But they don’t. This happens all the time when it comes to disruptive innovation. They will not win in this space. They just won’t because this space is the convergence of three technologies. They have not been working on um robotics in the way that Elon has evolved his uh his robots, his his cars. Um AI was always a part of the equation. Always. Yeah. >> And energy storage was as well because

[01:44:00] energy storage so electric vehicle costs continue to fall. The internal combustion engine costs is a completely mature industry. According to Wright’s law for a cumulative doubling from this level would take them I don’t know a hundred years. So they are not riding down any cost curve the way they would be if they stuck to electric vehicles which are writing down a cost curve. The learning curve. I >> I think we we may also be leaving out a very important component which is as Elon would call it the machine that makes the machine. We’re talking about ice versus electric. But the very important component I think we’re leaving out is how they’re made. And right now legacy auto companies lean heavily on unionized human labor. Totally. much of that is going to be automated with robots. So I I guess question in question form for Kathy, do you think maybe barrier to competition that Tesla has is that at least among American car companies, it’s leaning more heavily into roboticized automation

[01:45:01] for manufacturing in a way that the legacy manufacturers aren’t or can’t >> with without a doubt. And you know, Elon, I’m going to say about maybe it was three or four years ago, he said, you know, I’ve I’ve discovered that, you know, I’m a manufacturer of factories. And that was an important that was an important aha moment for us as well. um because he was designing the manufacturer, you know, the manufacturing or the factories of the future and he had the right technologies involved. Uh so yes, >> well also to to Alex’s point, you know, when when you know the original Gigafactory is in California and when they shut it down during COVID, Elon just said, “Screw it. I’m leaving California. I’m never coming back. This is insane.” So now he’s in Texas and and building in a much better regulatory environment. But if you look at the legacy car companies and the unions and the how tied those unions are to the

[01:46:00] voter pool in those regions >> and and the pension plans, it’s like it’s just impossible to escape. And so starting a new clean sheet of paper in a new jurisdiction is actually cheaper than retooling a legacy car company. >> Yes. And it’s worse in Europe where they have in Germany for example they have worker councils that determine what uh BMW or Mercedes are allowed to do as a corporation which is >> totally right. Totally. And this this is something you know big deal in Davos like Europe doesn’t have a place to go like if you want to hide your money you can go to Likenstein or Monaco but if you want to build a cheap car company in an unregulated environment or less regulated no not unregulated at all just like rational environment where do you go? And there’s >> they’ll go to Ukraine. No, they’ll go to Ukraine in the future. Ukraine will go to go to special economic zones like Texas. >> I know that most people think Europe is completely lost. And from a technology and regulatory point of view, um I think

[01:47:01] the collapse of innovation individual agency will help. But from a macro level, I agree with that. But uh and Peter age of abundance. So I’m looking for scarcity. Obviously Bitcoin comes uh to mind. Uh but the other thing, what does Europe have that other countries don’t have? Why do we all go there for vacations? >> Buildings, >> the lifestyle. >> Lifestyle. >> The lifestyle, easy going, the food, the So I wouldn’t write off Europe. It’s just they’re going to serve the rest of the world in in in the way they always have. um lifestyle service cute piazas and espresso. >> I’ll make my prediction on this. So the talent the latent tent pool in Europe is like you would not believe. Brilliant brilliant people. >> I agree. >> And historically people from India flood the US make a ton of money then they go retire wherever they want to retire. Europeans don’t do it because it’s so hard to leave Europe. It’s so wonderful.

[01:48:02] Uh but I think that the disparity is getting so wide now that the actual entrepreneurial community is going to start flocking to the US, work 10 years, whatever, keep your place in Europe and bounce back and forth. I suspect that’ll unlock. But I didn’t really appre, you know, Europe is just very very hard to leave. It it really is. >> Can I can I give the counterpoint here? >> I think if you’re a European entrepreneur coming to the US in the past was a real option. It’s not really an option right now. I think what’s going to happen is they’re going to for it’s going to force a change in the regulatory structure in Europe because it can’t sustain they have to break through via special economic zones or whatever they will have to make a structural change very very soon and I think they’ll do it >> and we saw that in Davos this year right a basically trying to create a uh commonality across corporations like when you incorporate in one country you’re incorporating in all of them and the rules are the same trying to unify its innovation system in some fashion >> called EU incor

[01:49:03] when your voter base starts tipping in one direction then it’s a it gets into a death spiral and I don’t see how you get out of that death spiral I mean no matter what is rational like you look at these tax proposals in California and Massachusetts the governor is like no way this is insane don’t do this and yet it still goes through >> here’s our last slide uh you know fully autonomous delivery is here you know we’ve been focusing on robo taxis for a long time, but we’re seeing 4 million deliveries per year. Uh Keller Clifton with Zipline is crushing it. >> What an incredible story that is. >> Yeah. >> Yeah. I love it. >> Yes. >> Yes. And he started, what was so what’s so beautiful about that story is he started in Rwanda. Yes. >> Um sending medical supplies and I think he cut the mortality rate of the m you maternal maternal bleedouts from pregnancy by huge amount.

[01:50:00] >> More than 50%. >> Yes. Wow. >> So, we’re seeing uh autonomous delivery in the air uh from Zipline and Wing. Uh Matnet, which was a spin out from Singularity University. Shout out to them. On the ground, we got Starlink and Mtoan and Cocoa Robots. Again, there dozens >> probably 50 Coco robots I see in the street of Santa Monica here. Uh and then of course, we’re seeing the beginning of trucking. It’s interesting. The the ground is crowded. The air the airways are open, but it will eventually get crowded. I mean, if we start seeing delivery rates, uh that could be from zipline and wing. Um, you know, I’m curious if people are going to start complaining about about noise. It’s it’s high in the sky and it lowers the delivery on a cable. Uh, yeah. Dave or Alex, you want to jump in on this one? >> Well, the the airways are threedimensional. They won’t get physically crowded, but you’re right. The noise is going to be a major major issue. If someone invents a silent drone, that’ll that’ll be a total game.

[01:51:03] Quieter. Yeah. Well, it’s hard. >> Gravity shielding, Alex. When do we get gravity shielding, Alex? >> Working on it, Peter. Ask me in a few years. >> Okay. >> Seriously, ask me in a few years. Um, I I maybe just a closing question if I may for for Kathy. A a lot of this is premised on labor being substituted for by intelligence and and automation. In my mind, there’s another possibility once we’ve fully swapped out AI and automation and robotics and drones for human labor. There’s still capital left. And historically, the the the debate from all the isms at the beginning of the 20th century was largely premised on labor versus capital. But do you think it’s possible that automation could also substitute for capital at some point in the next few years? Could capital be replaced by automation or is capital in some sense immortal? I think blockchain technology is going to transform

[01:52:01] everything in uh financial services but that’s more the infrastructure and bringing more efficiencies into I think capital is should I say immortal you know that’s a very that’s quite absolute and can I think of a a reason it wouldn’t be um >> well blockchain for example with with blockchain the fundamentally blockchains and yes to to everyone in the audience who’s about to lecture me on the increasing difficulty of Bitcoin. I I I know how that works preemptively. Um with with with with blockchains uh proof of work in particular, blockchain proof of work is fundamentally based on the difficulty of inverting a hash function. So in some sense, it’s a bet against it’s a bet against automation getting smart enough to be able to efficiently invert hash functions. It’s sort of an anti-technology bet in some sense. So I would say yeah even with blockchain blockchain is just as immortal in some sense as the ability for AI to not solve

[01:53:01] math is which is I think pretty pretty bold bet if one’s going to make one. We’ve been using money as a main mode of discourse in the world for the last several hundred years about capitalism, profits, business. It’s the it’s the main conversation. I think we’re shifting from money to information, right? Any startup is much more interested in collecting data and wants to monetize it later. Uh we’re seeing that over and over again. Over time, information becomes the higher order bit. And I think over time, intelligence becomes the higher order bit, right? over time if we can quantize the measurement of that then that’ll become the harder bit >> and and we’re going from money to data I think to directed intelligence or purpose as the highest order bit >> but it has to be measured in in in some way and monetized right >> so >> well monetization is really the ability for you to trade something or to use it to make take an action or get an end result >> right >> I think what you’re asking about is is

[01:54:01] really right on target too because again the vast majority of the world has latent talent that can’t can’t participate in the world economy in a corrupt environment and the taxation and the friction is ridiculous. >> But there hasn’t been an option before to trade in intelligence or trade in crypto or trade in whatever. But I think I think that’s a dam that’s going to break very quickly in the age of AI just just to unleash the talent in latent areas of the world. It’s going to happen, but it’s not gonna be measured in dollars or stable coins. >> I want to say thank you. This was a fantastic conversation. If you don’t mind, at least once a year, uh we’d love to have you back on the show here to review your big ideas 2027 uh report like we’re doing with Elon at the end of the year. Sort of a recap of what he did. um and grateful for all the work, your vision, your education, >> and the deck. Everybody check out the >> Yeah, thank you. And and of course, I have to give all credit. You you have no

[01:55:01] idea how intense the research effort is here. And you know, I think many people when they hear ARC, they think top down and in terms of stockpicking, they’re throwing darts into these innovation. That’s not what’s going on. uh we’re probably I think we’re we’re the most intense certainly in the traditional asset management uh world uh most intensely focused on research and investing in disruptive innovation and it would be an honor uh to for me to join you. I mean this is a brain trust here that um has been delightful uh >> uh to the interactions been quite delightful. So thank you. >> Yeah, thank you Kathy. Love you guys. Dave, I’ll see you in about 90 minutes. I’m heading to Santa Monica airport >> and Kathy 360, right in March. >> Uh, >> yes. >> Perfect. >> I think that’s on the books, right? Right, Peter? >> You are more than welcome and I would love you there. Uh, it’s not in the

[01:56:02] books for this year, but if you have >> maybe it was Is it the next year? >> Probably it’s next year doing every other year. Yeah, that’s it. Okay. >> Yes. >> All right. >> Yes. >> I can’t even out three months. Gosh. >> Okay. >> Have a great flight. Peter, when you guys see Brett, ask him if he has plans for multi-armmed robots. >> Of course I would. Without question whatsoever. >> And and Alex, please text me all of your questions for Brett as well. >> Um, >> we’ll do. And we’ve got to save the lobsters in the meantime. >> Yes. Maltbot. Love it. >> Check out the Dolly Museum in St. Petersburg. >> All right. >> I have been there and it’s absolutely worth a visit. It’s a stunning place. There’s a lobster phone there. There’s a lobster phone to ask Ali. >> All right, see you guys. >> Take care, folks. Great to see you, Kathy. >> Byebye. >> 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

[01:57:01] you the news that matters. If you’re subscriber, thank you. If you’re not a subscriber yet, please consider subscribing so you get the news as it comes out. I also want to invite you to join me on my weekly newsletter called Metatrends. I have a research team. You may not know this, but we spend the entire week looking at the meta trends that are impacting your family, your company, your industry, your nation. And I put this into a two-minute read every week. If you’d like to get access to the Metatrends newsletter every week, go to diamandis.com/tatrens. That’s diamandis.com/metatrends. Thank you again for joining us today. It’s a blast for us to put this together every week.