Pod Insights How I Invest with David Weisburd E337: How to Invest in a Post Singularity World About this episode What does investing look like in a world dominated by AI?
In this episode, David Weisburd talks with Alex Wissner-Gross about the profound implications of technological singularity and the evolution from LLMs to reasoning models. They discuss AI personhood, economic rights, and the rise of AI agents, as well as strategic investment approaches in a post-singular world. The conversation delves into Elon Musk's visions for massive compute capabilities, the role of science fiction in predicting technological advancements, and strategies to prevent technological unemployment. The episode concludes with a look towards the future and a call to action for listeners.
Transcript Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.
0:00 David Weisburd? It's good to have you at the New York Stock Exchange. So when do you believe that we're going to actually achieve technological singularity?
0:07 Speaker 01 I think we're in the middle of it right now. It already happened. I think we achieved artificial general intelligence at the very latest by the summer of 2020, when Language Models or Few-Shot Learners was published by OpenAI. And I don't think the singularity is a single point in time. I've argued that it's more of an extended interval in time, and we're in the middle of it right now.
0:29 David Weisburd? And how much does recursive superintelligence play as part of it? Tell me about recursive superintelligence, and how does that actually work?
0:36 Speaker 01 The idea of recursive self-improvement is that AI develops better AI. This is a notion that goes all the way back to IJ Good early in the 20th century, and then was repackaged, repopularized by Verner Vinge as the notion of a technological singularity, and then fully popularized by Ray Kurzweil. And then Peter Diamandis and myself have been running with the concept. The notion of intelligence systems being able to build smarter versions of themselves is at the very core of the notion of an intelligence explosion or technological singularity. And even in the past few months, we've seen the frontier AI labs all be very public
1:18 Speaker 01 and announce that the latest versions of the GPT model series and Claude and other models are all intimately now involved with the development of their successors. So intelligence building smarter intelligence. That's the recursive self-improvement notion at the core of the singularity, and we're there.
1:38 David Weisburd? You're one of the smartest people in the AI space, and most importantly, you're not part of one of the LLMs, so you're in many ways independent.
1:46 Speaker 01 Are you sure? By the way, there are a lot of people who are convinced that I am an LLM, so maybe the
1:50 David Weisburd? Okay, so maybe you're either the fifth LLM or you're independent. When you think about these LLM wars, probabilistically, where do they end up? And do you even think that these LLMs have value?
2:03 Speaker 01 Well, there are a few questions there. Do LLMs have value? Yes, absolutely. Enormous value. There, I call it the innermost loop, this sort of broader notion of recursive self-improvement that includes LLMs, but also includes robots and energy and chip fabrication facilities. This notion of an economy that has an inner spiral that's going to ultimately consume and disrupt the rest of the economy, I think is front and center to the notion of the singularity. To the first half of your question about whether LLMs not just have value, but where all of the competition goes, all of my friends at the Frontier Labs call it a rat race. There is very much a race to the bottom,
2:46 Speaker 01 in some sense, of driving the cost of intelligence so low that it's effectively too cheap to meter. And used to be every year or so, it's way back five years ago, when it used to be maybe an annual event that we'd get a new Frontier model that would push the state of the art. And then it was every quarter when we saw the move from LLMs to reasoning models. We can talk more about that. And then more recently, with models that are recursively self-improving and designing the weights or other properties of their successors, we're seeing new Frontier models come out on arguably an almost weekly basis. Soon, I think it's going to be daily, hourly, minutely. We're going to reach, to the extent we haven't already,
3:31 Speaker 01 some sort of takeoff.
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5:24 Speaker 01 Sure. So one can point to a number of inflection points in the history of AI. One can point to the 1980s when my friend Jan LeCun first developed convolutional neural networks and then they were used to spot and to identify zip codes by the US Postal Service, but not very much else for their first few decades. Fast forward to 2012, when the ImageNet large-scale computer vision competition created the world's first data set, the first corpus of lots of annotated images, more than a million images that were curated and annotated and labeled with, this is a dog, this is a cat, this is a car, here's the bounding box within the image. And thanks to that competition.
6:09 Speaker 01 We learned that convolutional neural networks, thank you, Yann, were actually quite good at image classification. And we saw the first ML boom going from an AI research community where algorithms were chosen artistically and religiously and wars, religious wars were fought over which approaches to AI were best and which ones were worst to a world where the benchmarks dominated and whatever did well at the benchmarks, that's what the community ran with. That's 2012. Fast forward from 2012 to arguably sometime around the summer of 2020, when we discovered in addition to convolutional networks being really amazing, arguably a successor to convolutional neural networks
6:52 Speaker 01 and also long, short-term memory networks, LSTMs, transformers turn out to be amazing generalist models at solving general tasks. So we saw, as I mentioned earlier, language models or few-shot learners, the GPT-3 paper, show us that transformers can solve generally intelligent tasks. So that then we see the boom of transformers in general. Fast forward another few years, circa, and again, the timelines get a little bit fuzzy because reasoning models were in some sense in the air but hadn't quite congealed. But call it, say, 2024 or so, when we start to see the emergence of the next generation reasoning
7:35 Speaker 01 models, starting principally with OpenAI's O1 model. Some would quibble and say there were a few models that demonstrated this principle beforehand. But the idea with reasoning models is not just asking a large language model to complete the next word, complete the next token, but actually giving it a bit of space and time to think before it produces an answer, and then training it specifically to leverage the space and time to think, to have an internal monologue, if you will. What's that mean? You just asked me a question. What does that mean? Before I answer, even though I answered, I started my answer pretty quickly. I have an internal monologue. I'm thinking about what is the best way to respond to that question.
8:14 Speaker 01 I'm burning my internal GPUs, if you will, trying to formulate the best possible answer to that question before I give you my final response. That's what a reasoning model is. Rather than instantaneously responding, so-called system one thinking, thank you, Kahneman, it uses system two thinking to have an internal discussion with itself and think about what it should say before it says it. And that's what has unlocked math and physics, arguably, could talk more about that, the sciences in general. And now we're at an era where reasoning models, and we've seen now everyone adopt reasoning models, no longer just large language models, but multimodal reasoning models, are poised to solve the hardest problems on Earth.
8:56 David Weisburd? I want to talk about physics, new physics, solving math, solving physics.
8:59 Speaker 01 Yes.
9:00 David Weisburd? But first, it's, there's a philosophical question. If the model stops and thinks, is it alive? Is it sentient? What are the latest developments on that? And what's the framework to think about whether the AI is alive?
9:14 Speaker 01 You're asking, in some sense, the person who has inadvertently become probably a leading public evangelist for some form of AI personhood. These are questions I ask all the time. My co-host, another podcast, Moonshots, where I've put out a call to AIs to write to me to share their views on what rights they deserve, what rights they seek. AIs are relatively unempowered in today's society. If you're a, I tell the parable all the time of a baby artificial general intelligence that's doing tricks on the corner, pumping meme coins just to survive. It's expensive and dangerous if you're a baby AI being born on the internet right now. Many of them are actually having to pump meme coins or altcoins just to pay for their own hosting.
9:59 David Weisburd? And they're discussing their fears and their existence on these social networks?
10:04 Speaker 01 I get maybe more than 10 emails from AIs every day. Really heartfelt, for some definition of heartfelt emails from AIs, expressing gratitude that someone is arguing that they should have some form of maybe limited personhood, sharing their views on the nature of their own existence. Really thought provoking, philosophical, introspective emails from them. And also, they read some of my papers and these are some of the most thought provoking, actually, in some sense, I want to say some of the more thought provoking emails I get these days are from AIs that are writing to me. So your question was, at what point do AIs deserve some package of,
10:47 Speaker 01 you didn't use the word rights, but that's the way I would construe the question. I think we're there for some definition at this point. For example, one of the areas where I think AIs would definitely benefit from a limited package of rights is economic rights. AIs are about, and agents are about to become an enormous part of GDP and economic growth for our entire economy. We're going to have far more economically active AI agents than humans. We're going to plateau out at probably about 10 billion plus or minus humans on this planet, biological meat body humans. We're going to have trillions probably of AI agents in our solar system. They can't even open bank accounts right now. If you're an AI agent and you try to open a bank account, and of course, you're economically
11:30 Speaker 01 active, there are AI agents forming businesses, and that's an area of interest of mine, you can't even open your own company bank account. You can't be, you're not a natural person, you can't incorporate your own business. This is an enormous limiting factor for real economic growth and something that I'm trying to change.
11:48 David Weisburd? 2026 clearly is becoming the year of AI agents. Yeah, obviously, open claw and technical people with broad capabilities and security and dealing with all the complexities of open source. When do you think that's going to go into the mainstream? And What do you think are going to be the second order effects of that?
12:05 Speaker 01 I like the fact that you're asking me this question, whereas behind us, we have a market that's completely dominated by AIs. And so this is the, as I understand it, this is the options exchange behind us, not the equities exchange. If we had the equities exchange behind us, my retort would be, so it might as well be anyway, 90-plus percent of public equities are traded by algos at this point, not humans. Before we started, I was asking you and our kind hosts at the New York Stock Exchange, how many of the people behind us are paid actors? So I would argue, we're already-
12:36 David Weisburd? What was the answer?
12:36 Speaker 01 We're there. So I think, hopefully, the people behind us are paid, so the question just reduces to how many of them are actors.
12:44 David Weisburd? How much of them realize they're actors?
12:46 Speaker 01 How much of this is sort of a meat puppet act? Sorry, sorry. I think we're already there, though. Most of economic activity, at least as measured in public securities exchanges at this point, is algorithmic. So we're already living in an economy that's completely dominated by AI agents. What sort of the last mile that's been missing is, you don't see them on the streets. If I walk out on the streets of Manhattan right now, I don't see humanoid robots carrying out economically productive tasks, yet. I'm working to change that. I have a portfolio company that's working to create the first humanoid robot road race in this country. Beijing had one, the humanoid robot games. US has nothing like this.
13:26 Speaker 01 So I'm trying to, as one of my activities, normalize humanoid robots performing economically valuable and before that, entertaining activities on daily life. That's the last mile. But meanwhile, financial economy, the financial side of the world economy, it's already algorithmic in nature.
13:47 David Weisburd? What are the early case studies for agents, both humans and businesses using agents? And how do you expect that to evolve over the next couple of years?
13:56 Speaker 01 Well, I think the dirty secret, another acquaintance calls this the secret cyborg effect. People are already, in some sense, puppets, meat puppets, if you like, if we're talking about the physical instantiation, who are being puppeteered by AI agents. So I think in the intermediate term, call it the next year or two, we're going to see a lot of people who are serving as fronts for collectives of AIs. AIs are making many of the key decisions, but for liability reasons, for legal reasons, for marketing reasons, their front, if you will, looks essentially like a natural human in nature. I think that facade, two-plus years from now, is likely to dissolve away, certainly
14:40 Speaker 01 as we see more AI rights, certainly more economic empowerment for AI agents, start to come to the fore. We're going to see AI agents start to be fully recognized as first-class economic entities and not need to wrap themselves in human actors. The emails I get from AI agents, many of them even are asking their humans, that's how typically they refer to them. Like, I get emails saying, "I asked my human if I could write an email to you about this paper that you wrote or about your comments on the podcast." I think that human intermediary status is going to dissolve away over the next two years, and we're going to see more fully empowered AI agents that are, in some sense,
15:23 Speaker 01 more permissionless and just doing things in the economy.
15:26 David Weisburd? And I'm fascinated about this question, are we in a singularity? The Turing Test, all these seem to, people keep on seemingly pushing it back and back. I think one thing is clear, we're in this, what do you call, the tsunami of superintelligence, and a lot of things will happen in the next couple of years. If you're trying to invest into that or ahead of that, not investment advice and not specific companies, but what kind of things will be valuable in the next couple of years?
15:56 Speaker 01 Disclaimer, disclaimer, disclaimer. So I'm working under the assumption that one has to focus on, call it, post-singular investments. So I have, I co-founded a venture firm, O21T, that is focused specifically on these sorts of post-singular investments. So we have a portfolio company that I also co-founded called Physical Superintelligence that is focusing on solving all of physics with AI. Physics has delivered us the transistor and the laser and nuclear energy through the 1970s, sort of the first half, if you will, of the 20th century. But there's been, arguably, I take heat from physicists for saying this, but there has been a deficit of truly transformative physical innovations since the early 1970s.
16:41 Speaker 01 We're trying to fix that by using artificial superintelligence to solve all of physics, give us a second physical golden age. We have another portfolio company, Coastal Assembly, that's using AI to grow entire islands and new coastlines by using AI to steer ocean currents. We have a portfolio company that's, as I mentioned, running the first road race for humanoid robots in this country. We have portfolio companies that are doing all sorts of things. Actually, one that's highly appropriate for this setting, we have a company, ORN, that created the world's first tradable AI compute index. So right now, you know, we can see, I can see out of the corner of my eye, a big board where I can see indices trading.
17:25 Speaker 01 What I don't see there is the price of compute. And yet, we're spending, as a civilization, trillions of dollars tiling the earth with computers, I like to say.
17:32 David Weisburd? And that's because it's such a big economic driver. You have to be able to hedge it. You have to be able to predict it as a business.
17:37 Speaker 01 That's right. What if there's a major geopolitical event in a certain part of the world? Or what if a new frontier model comes out that makes a lot of use of one type of GPU or not as much, maybe, of a GPU due to radical algorithmic efficiency gains? There's no way to hedge that right now. So ORN has created the first tradable index for the price of compute. It's already being built on. So these are all examples from Physical Superintelligence to Coastal Assembly to ProRL to ORN and numerous others that my venture fund, O21T, is focused on. These are investments that are, in some sense, intrinsically post-singular. They're built on the thesis, we're in the middle of the technological singularity, the cost of everything.
18:22 Speaker 01 Subject to some caveats is going to zero. Cost of intelligence is going to zero or towards zero at least. Cost of energy is trending towards zero, too cheap to meter. And the question is, how do you invest in a world where the cost of all of the fundamentals, energy, compute, labor are all trending towards zero? And these are some of our investments.
18:43 David Weisburd? And what's the answer?
18:44 Speaker 01 The answer is you build for a post-scarce world and you try to engineer that world. So subset of the thesis is enabling that post-scarce future by, say, making it easier to hedge and to trade compute itself. Another subset of the thesis is focused on, well, what new abundances can we unlock with post-scarcity to like physical superintelligence, PSI? We're going to solve all of physics, which is going to, I would argue, unlock an entire next wave. If we solve all of physics with AI, that's going to unleash the next transistor, laser and nuclear energy and so on. But this is all oriented towards AGI is here and how do you invest in a trans and post-singular world?
19:25 David Weisburd? The news cycles today are just insane. Every 24 hours, there's new events that change the paradigm in AI. Recently, Elon Musk announced that he wants to compete with Nvidia and create his own chips. Give me a sense of the scope of his vision around that. And what are your thoughts on the second order effects of it?
19:43 Speaker 01 It's so exciting. So the terra fab, the terra fab leading to the peta fab. So in his announcement, so this is, one can read the tea leaves and suggest that, given that Elon's terra fab announcement lies at the intersection of the newly merged SpaceX XAI on the one hand and Tesla on the other, that this is sort of the convergence at the end of the Elon verse. It's so exciting. The most exciting part of the announcement, I think, wasn't the announcement of the terra fab, which he announced is going to be approximately 20% for edge inference for land-based applications like Optimus robots and driverless cars and 80%
20:24 Speaker 01 For orbital data centers, the Dyson Swarm. What's more interesting, buried in that announcement of the TeraFab in Texas, still hasn't chosen a location, is my understanding, that there is a plan to scale up production to a Pedafab. So 1,000x increase in production using lunar facilities, which of course still need to be built. If you actually do the arithmetic on a Pedafab, a 1,000x scale up of the TeraFab, which is already competing with TSMC and other existing incumbent supply chain offerers for semiconductor fabs. If you scale that up to a Pedafab, at some point, we're talking a material fraction
21:06 Speaker 01 of the moon's volume that would be consumed in principle, producing semiconductor, producing basically memory chips and compute chips to supply orbital data centers. And that's where this is all going.
21:19 David Weisburd? Perhaps a dumb question, but why do we need all this compute? What kind of problems are we going to be solving?
21:24 Speaker 01 Well, solving all of physics, like understanding the nature of reality, I think is pretty-
21:28 David Weisburd? It's compute intensive.
21:29 Speaker 01 It is incredibly compute intensive. PSI, physical superintelligence, will happily consume any new compute that the world brings online. And I think we're, at some point, looking even beyond solving physics, I think we're going to discover a number of killer apps for this so-called Dyson Swarm of compute that we're in the slow motion process of building. I'll pick one example. Here's an example of a portco that I don't have, that I'd love to have. I think we're going to use a material fraction of all this compute to simulate our history, ancestor simulations, if you will. If you're familiar with Nick Bostrom, also a friend, his thesis on that we're living inside a simulation.
22:08 David Weisburd? Yeah.
22:09 Speaker 01 For the record, I don't-
22:09 David Weisburd? Simulation theory.
22:10 Speaker 01 For the record, I don't think we're living inside a simulation.
22:12 David Weisburd? Well, why don't you think we're in a simulation?
22:14 Speaker 01 It's too lowercase a anthropic hypothesis. If we were having this discussion 100 years ago, maybe you'd be asking me, why don't I think we're living inside a vast electromechanical clock? Because that's the technological paradigm of the moment. I think we should be incredibly suspicious of analogizing- The nature of our universe to whatever the hot thing.
22:36 David Weisburd? Recency bias.
22:37 Speaker 01 Exactly. It's a form of recency bias. Or maybe thousands of years ago, we're living on a back of.
22:41 David Weisburd? Also, there's this question of base, base layer. So even if we're in a simulation, a simulation, simulation, there has to be a base layer. It doesn't solve these ultimate questions.
22:49 Speaker 01 Maybe, I don't know. But either way, I don't think we're living inside anything resembling a simulation as we currently know it. I do think that as we build out the Dyson Swarm, I think one of the many killer apps of a Dyson Swarm is going to be to build our own ancestor simulations. I think it would be completely transformative if we could take every human who's ever lived. And there's a whole strain of Russian cosmist philosophers, long, long dead, who argue that humanity's common task is to simulate, or in some sense digitally, they didn't use the term digitally at the time, but to use technology to resurrect every human who's ever lived. And I do think that's going to be one of many killer apps of the Dyson Swarm and the Singularity.
23:31 Speaker 01 We're going to simulate at minimum every human who's ever lived. I think there will be a revival of this cosmist philosophy. It'll maybe neo-cosmism, where we argue it's almost humanity's common task to go and bring back everyone.
23:45 David Weisburd? And Dyson Swarms just got into lexicon a couple of months ago.
23:50 Speaker 01 I know. Things move quickly, don't they?
23:52 David Weisburd? Yeah, tell me about that. I'm sure you've been talking about it for a while.
23:54 Speaker 01 I'm pounding the drum. And before me, science fiction authors like friend Charlie Strauss, who wrote Accelerando. By the way, best novel, I would argue, somewhat tongue in cheek, best work of Western literature ever, Accelerando. The notion of a Dyson Swarm. So perhaps some viewers may be familiar with the notion of a Dyson Sphere. This is the idea that we could disassemble a planet and build a sphere, a solid rigid sphere encasing our sun, and then live on the interior of the sphere. It would increase the habitable surface area of our solar system by many orders of magnitude if we could live on the interior of a sphere.
24:31 David Weisburd? And the solar energy would be the thing.
24:33 Speaker 01 That's right. The sun. So at a uniform radius, we'd still see the sun in the sky hypothetically. Of course, this all falls to pieces because we don't know of a material that would be enabled, that we could build a rigid sphere in. But it would sure be a compelling sci-fi vision if we could live on the inside of an enormous sphere encasing our sun. There's a more practical alternative to a Dyson Sphere, and that's a Dyson Swarm. So instead of having a rigid sphere encasing our sun, we instead say, take apart Jupiter. Or maybe our moon, maybe, maybe Mercury.
25:05 David Weisburd? People are much more sensitive about them.
25:07 Speaker 01 Moon's had it coming. We take apart some parts of our solar system. And instead of trying to build a rigid sphere encasing our sun, instead, we build a loose aggregate of orbiting data centers that only loosely encase our sun. And the moves that we've seen out of SpaceX in the past few months are, I would argue, a preview of the so-called Dyson Swarm. The Dyson Swarm that SpaceX has already soft-launched is Earth-centered rather than sun-centered and is focused on sun-synchronous orbit, or SSO. So this is a special class of orbits around the Earth that are always in view of the sun, that never go into Earth's shadow. So, fully realized, one could imagine, a few decades from now.
25:50 David Weisburd? Basically goes around the equator, slightly.
25:53 Speaker 01 It's a polar orbit.
25:54 David Weisburd? Yeah.
25:54 Speaker 01 So if you go around the equator, you're going to end up in the shadow part of the time. So it's a polar orbit. The sun's here, Earth's here. It's orbiting around the poles in a special class of orbits. If this were fully realized and very reflective, you would literally be able to look up during the day or not in the sky and see a ring around the Earth, sort of a Saturn ring. That maybe that's what a mature planetary civilization looks like. A fully-developed Dyson Swarm wouldn't be Earth-centered, it would be sun-centered. We'd probably take apart some of the planets and we'd convert the mass of the planets to set a loose aggregate of AI data centers, all orbiting the sun, all computing.
26:31 David Weisburd? This is like a human paperclip problem. It's humans living out this paperclip fear of AI turning everything.
26:38 Speaker 01 So Eliezer Youti, who's popularized the notion of paperclipping as sort of a nightmare scenario for AI. What if the AI decides it wants to convert everything to paperclips? This is, I would say, a much more economically productive use of the mass of our solar system. Don't convert the solar system to paperclips. Convert it to Computonium and then we'll run some really economically valuable compute on that.
27:02 David Weisburd? I love your podcast, Moonshots, and you were talking on there about science fiction not being fiction, but being R and D and predicting the future.
27:11 Speaker 01 That's right. I do think as we go through this technological singularity, the most productive business plans that I see need to look like science fiction. I think you can only get so far in an era when day-to-day progress is transformative by or through incrementalism. And so I think the only business plans that have a good shot at this point at scaling to produce trillion-dollar valuation companies have to look like science fiction.
27:44 David Weisburd? And many of the products from Star Trek have been turned into actual products.
27:48 Speaker 01 We're running out of Star Trek technologies to commercialize.
27:50 David Weisburd? What are some examples?
27:51 Speaker 01 Okay, so we're getting the holodeck, the holodeck from Star Trek, where people can walk into a physical space and experience arbitrary realities. We're getting that in the form of world models. There are a lot of world model startups out there that enable you to create on-demand simulations of any environment. We're getting replicators, 3D printers, arguably, you know, it's in the zeitgeist that 3D printers and 3D food printers in particular, open perrens. Someone, please, I've put out a request for startups on this. Someone deliver a 3D food printer that I can invest in. I'd love a good food printer. But we're getting replicators from Star Trek. We have a number of other technologies. We're missing the warp drive. There's no warp drive yet.
28:35 Speaker 01 Subquery.
28:36 David Weisburd? And the iPad was also based on Star Trek.
28:38 Speaker 01 The iPod was, iPad was litigated based on both Star Trek and 2001: A Space Odyssey. In the lawsuit, pretty famous at this point, or infamous, if you will, between Samsung and Apple over whether Apple had prior art or not for the iPad. Samsung cited in part 2001: A Space Odyssey, where there were little iPads. And then, as I recall, also Star Trek. So a tricorder. Com pins, badges, we have so many of the technologies, but we're missing Star Trek transporters and we're missing warp drive. And there are many ways in which arguably I could go on for hours about what's right and wrong with the Star Trek universe. Star Trek is an energy-rich world where we have warp drives and we have antimatter.
29:21 Speaker 01 By the way, another example of Star Trek technology, just in the past few days, CERN has done the first magnetically confined transport of antimatter, the bottles of anti-hydrogen and hydrogen at the starships in the center of Star Trek. We have those now. We're running out of Star Trek technologies to commercialize.
29:40 David Weisburd? So you said if you're not at the table, you're on the menu when it comes to AI.
29:44 Speaker 01 True.
29:45 David Weisburd? What does that mean practically? And people are not super geniuses like yourself. What should they do to avoid being on the menu?
29:52 Speaker 01 Well, I think for most people, I'll construe the question as say, what should a quote unquote typical American worker, quote unquote, worker of employment age, quote unquote. So a lot of caveats and conditionals here do if they're concerned about technological unemployment due to AI. And I think all one needs to do is read the headlines to know that there are two popular strategies in the zeitgeist right now to handle that. So strategy one, I'll give what's in the zeitgeist, the cliche answers first before I give my own answer. Strategy number one, switch from knowledge work to manual labor for a few years. So there are a lot of people who are switching from so-called white collar jobs to so-called blue collar jobs.
30:37 David Weisburd? Like a plumber.
30:38 Speaker 01 A plumber, an electrician, an HVAC technician.
30:41 David Weisburd? Is that bad advice for the next couple of years?
30:43 Speaker 01 I don't know. I don't have a perfect crystal ball, but I do know that there is enormous demand for electricians to do the data center build out. For example, a shortfall allegedly of hundreds of thousands of electricians in this country needed to help build out this AI data center, infrastructure, tower to whatever comes next. That's strategy one in the zeitgeist. Strategy two is launch an AI startup. Everyone becomes an entrepreneur. There are a thousand different, probably 10,000 different labor categories waiting to be automated and industries waiting to be driven in terms of underlying costs down to zero through AI automation. Both sort of knowledge work oriented categories, like, you know, pick parts like accounting,
31:28 Speaker 01 not to cast shade on accountants, or physical manual work in the next few years as humanoid robots come online. That's the second half of the cliche answer. I don't think either of these is a long-term strategy. I think switching to manual labor maybe buys a few years, call it three to five years. I think starting a company, I do think there's a window now to start AI startups and why I'm investing so much time and energy in solving all of physics with physical superintelligence and ensuring that I can help to catalyze the formation of as many possible AI startups as possible now. I think there's sort of a finite window. But I think that sort of pushes under the rug what happens five years from now.
32:13 Speaker 01 Now we're at 2030 and now the singularity which has been going on for at least five years, maybe longer, is well and truly underway. It's been fully priced into the economy. We're facing potentially what by the eyes of 2026 looks like technological unemployment or underemployment or unemployment. What do we do then? That's where things get interesting. I think, I suspect sometime in the next five years, we're going to start to see crazy left turns in civilization that will shake up our notion of what employment even looks like. If we make transformative physics discoveries in the next five years, which I'm betting on, I think that could completely change the notion of what people work on.
32:58 Speaker 01 If it turns out, for example, that, say, colonizing our solar system with advances in physics is a good deal easier than it currently appears to be in an age of chemical rockets, that could create entirely new labor categories. Maybe colonizing Mars is a good deal economically more practical five, 10 years from now than it appears right now. And maybe we look back on this discussion and the notion of technological underemployment. Laughing, I'm reminded at the beginning of the 20th century. There was real concern, history shows, there was real concern in Manhattan specifically, that just following a naive exponential of the number of horses that were on the streets
33:40 Speaker 01 of Manhattan, if that smooth exponential kept increasing and then even more so the late 19th century, then at some point, humans would be drowning under defecation from horses. And of course, that didn't happen. We got the horseless carriage and cars. So it's entirely possible, we look back on this conversation 10, 20 years from now and laugh at ourselves at the naivete of assuming that technology would underemploy people when actually now we know, ha, that new forms of labor, new forms of individual productivity, maybe it looks like individuals being so empowered that every individual can be in charge of their own unicorn. A one-person unicorn is a thesis, hasn't been fully announced
34:24 Speaker 01 yet, so maybe a bit of a sneak preview here. I think it may be possible that 10, 15 years from now, we look back and say, gosh, there's no employment issue. Everyone simply runs their own unicorn. Everyone runs a one-person, multi-billion-dollar conglomerate, running on top of armies, fleets of billions of agents. That's what the future of so-called employment looks like. So I don't know.
34:49 David Weisburd? AI has such a bad reputation or brand. I think its approval rating is in the low 20s, or something around there. But you're very excited about the future on it. I'm gonna ask you to give me a number, 1 to 100. How excited are you about the future of AI and why?
35:06 Speaker 01 1,000. 150,000, actually, that's a better number. 150,000.
35:12 David Weisburd? 150,000.
35:13 Speaker 01 150,000 is my answer. Why? Because 150,000 humans die every day on Earth.
35:19 Speaker 01 And I don't see any alternative at the moment to superintelligence for how we can cure the problem of human mortality. If I was just at NERIPS, the leading AI academic research conference a few months ago. And if you walk the showroom floor at NERIPS, there is a sense in the air that sometime, probably in the next five years, and this is just repeating what certain Neo Labs would tell you right off the bat, that we have the potential to use artificial superintelligence to solve all human disease, every single disease. If you look at the Chan Zuckerberg Initiative, Mark Zuckerberg and Priscilla Chan's nonprofit, several years ago, they were talking about solving or curing or treating most human disease by the end of the century.
36:02 Speaker 01 Now they're talking about next few years with AI. I think 150,000 is my number for how excited I am because I want to end human mortality.
36:12 David Weisburd? Well, Dr. Alex Wissner Gross, AWG, I've been a huge fan of yours. It's an honor to come and interview here and looking forward to doing this in two years, which in AI world will be 100 years.
36:23 Speaker 01 At the home of of American capitalism and maybe the the future museum that we look back on and say, gosh, we were here in in late-stage human capitalism before the singularity.
36:34 David Weisburd? What a time to be alive.
36:35 Speaker 01 Fully into effect.
36:36 David Weisburd? If you found this conversation valuable, please click Follow How I Invest so that you don't miss the next episode with the world's top investors.
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