Musk's Early Investor: The 3 Bets That Will Define AI by 2028 | Steve Jurvetson

Steve Jurvetson has worked with Elon Musk for 29 years and was one of the earliest investors in SpaceX and Tesla, back when space wasn't even a category for venture capital. Today he runs Future Ventures, where he bets on nuclear fusion, epigenetic editing, and analog AI chips. We recorded this live on stage, with audience Q&A at the end. We cover: Why compute has compounded for 130 years, and what that curve says about the next 3 yearsSuperintelligence odds: why Anthropic co-founder Jack Clark gives it a 30% chance of arriving next yearWhat 29 years next to Elon taught Steve: focus, learning loops, and spotting talent (Tesla collects more AI training data in 4 days than Waymo has in its entire history)The 50-year question Steve asks every founder before writing a checkHis 30-day plan if you're one person with a crazy ideaWhere he's investing now: fusion, meat without slaughter, free healthcare via your phoneWhen machines do everything, what's left for us Links: 📌 Subscribe to my free newsletter where I go deeper on AI tools, career strategies, and building with AI: https://siliconvalleygirl.beehiiv.com/subscribe?utm_source=spotify&utm_medium=video&utm_campaign=futureproof-sub&utm_content=SteveJurvetson https://siliconvalleygirl.beehiiv.com/subscribe?utm_source=spotify&utm_medium=video&utm_campaign=futureproof-sub&utm_content=SteveJurvetson 🔗 Instagram: https://www.instagram.com/siliconvalleygirl/ 𝕏 : https://x.com/siliconvalleymm 💼 LinkedIn: https://www.linkedin.com/in/marinamogilko 💼 My Companies & Products: https://Marinamogilko.co

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

• 0:01Speaker 00

  This episode is brought to you by Google Chrome. You think you know a browser, but Gemini and Chrome? That's new. It can help you with practically anything on the web, like restoring a vintage motorcycle from a 50-page restoration block, or finally break down that long article you've had open for weeks. Gemini and Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses set up required. Compatibility and availability varies 18 plus.

• 0:26Speaker 01

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• 0:55Marina Mogilko?

  What will the next three years look like?

• 0:59Speaker 03

  I have this gut feeling that it'll be something architecturally variant.

• 1:03Marina Mogilko?

  This is Steve Jervitson, an early investor in SpaceX when almost nobody believed in private space. He backed Tesla before electric cars went mainstream. For over 30 years, he's been betting on the future, and history keeps proving him right. When someone comes to you with just an idea, what would be the best thing that they could do?

• 1:21Speaker 03

  Single person with an idea? I might try to find a co-founder. It's rarely an individual. Jobs and Wozniak, Batman and Robin.

• 1:29Marina Mogilko?

  You're working a lot with Elon. Top three principles that everyone should learn from him?

• 1:33Speaker 03

  I do try to observe leaders in action. Even with a focused effort, it's not always obvious, but a few things. One is this insane ability to.

• 1:43Marina Mogilko?

  Thank you so much. This is going to be very exciting, Steve. I am so excited to have you on this stage. What a fun time, right? SpaceX IPO, and you were there super early.

• 1:57Marina Mogilko?

  What did you see that most investors didn't see back then?

• 2:01Speaker 03

  So the simple answer to the question is there were almost no investors considering space. It wasn't a category on any site. So the slightly variant question is why in the world would we invest in a sector that is just not a sector for venture?

• 2:15Marina Mogilko?

  Exactly.

• 2:15Speaker 03

  Same could be said for automotive, a Tesla, energy with nuclear fusion. There were a handful of investments, but very few. So the short version is obviously an incredible entrepreneur, someone we've worked with before. I've known him for, oh gosh, 29 years now, and invested in all of his companies of the century and his cousins too. So all in, if you will. The uniqueness of the opportunity. So what we've come to appreciate in a sort of fuzzy way then, but now in a more crystallized manner, is the way in which a sort of software-centric system engineering approach to a sleepy industry that hasn't had any change for decades can actually unlock incredible value and opportunity. You can see it in aerospace, you can see it

• 2:57Speaker 03

  in automotive now. It was sort of a long bet when we first invested, but now we can sort of see in retrospect how that's going to play out in almost every industry over time, how they become information businesses.

• 3:08Marina Mogilko?

  Obviously, you're so good at predicting future. And part of this podcast, I really want to understand how you think about the future. You have this amazing graph, 130 years of compute, and it basically grows exponentially. What does it mean for all of us? What will the next three years look like because of what's happening to compute?

• 3:27Speaker 03

  I'm just curious, how many people have seen this version or this abstraction of Moore's Law? It was originally by Ray Kurzweil in like 99 book, Ages of Virtual Machines. Looks to me like 25% of the room. Okay. I always ask because I'm curious how much it has entered the zeitgeist, because I think it's the most important thing ever grafted, and I give credit to Kurzweil for even seeing this pattern back when no one knew they were fitting to a curve. So just for those who don't know, this covers like five different technology substrates from mechanical devices to relay-based computers to discrete transistors and integrated circuits. And only in the most recent era would what Gordon Moore called Moore's Law be almost a refraction of a much longer-term trend transcending

• 4:07Speaker 03

  You know, all kinds of dramas of companies that came and went. It's almost cosmological, like, why has humanity's capacity to compute compounded for 130 years? And for sense of scale, like, that's an exponential scale, right? Logarithmic scale, so a straight line is exponential. This graph shows a 10,000 billion billion X improvement in computation that a dollar can buy. This is what customers care about. No one buys transistors when they're buying ICs. They don't say, how many, how many transistors does that one have? I'll buy the one that has more. No, they buy compute capacity or memory. And both have been on rails. And so to your question, the first and foremost thing would be to just predict that it's going to keep going for three more years. Like, why would it suddenly just stop and hit a red brick wall, the way Intel's been saying it would?

• 4:48Speaker 03

  And when companies say that, like, Intel usually assign they're losing their business to someone new, like Nvidia 15 years ago. So in the next three years, I think you'll see the analog chips continue to carry the mantle of Moore's Law. Some of the more esoteric and customized AI silicon that does discrete, discrete matrix multiply and add really efficiently. And this is what's going to carry the juggernaut that we all just take for granted, that it keeps going. In fact, I'd say without this sort of exponential change in technology, you wouldn't have startups. You wouldn't have this disruptive innovation opportunity like we talked about in SpaceX or in a bunch of companies. Because if business is predictable, if there isn't disruptive technological change, the big get bigger. You know, they have all kinds of ways to prevent new entrants from competing with them.

• 5:29Speaker 03

  It's usually somebody reinvents an industry and usually it's based on something computationally based. I think AI and everything we're talking about at today's conference is the epitome of this. It's like the most intense crucible of compute-centric innovation, economic growth and, and, and sort of innovation of the economy. The, the translation of formerly industrial crappy gross margin businesses into information age, information-centric businesses. That over the next three years means it ripples to, I think, energy, agriculture, construction, three industries that are enormous, growing as a percentage of GDP. And the least digitized industries on the planet, not to mention healthcare, right, soon behind that.

• 6:10Marina Mogilko?

  Are those the industries where you think we're going to see the most change? And? What will cause the change? Is it going to be more advanced LLMs? Or do you think there's something else? I know people are building world models. People are deep into robotics. What will be the technological driver for the most changes in the next three years?

• 6:30Speaker 03

  That's a great question because it's very difficult to answer with any certainty. I have this gut feeling that it'll be something architecturally variant. It might subsume the models that we know now. You could almost think of like a mixture of experts that's subsuming other architectures or the diffusion model we heard about earlier today that ultimately translates to a transformer. But it's a different way of thinking about the transformer massively parallel form of a diffusion model. And in the back of my mind, I, we have not, so what I'm about to share, we've not invested in this. So I'm, I've met with some companies and I've been intrigued in something my gut says they're gonna, they're probably gonna make a breakthrough. And this is the whole new generation of Neo Labs focused on reinforcement learning. Cause we're almost going back to the founding premise of DeepMind,

• 7:14Speaker 03

  which then they kind of, you know, just put to the side for a while when the whole Elon thing took off. And so if you could imagine what would be the, you could phrase in this in agentic language and say, what is the, you know, multi-decade-long agentic process? Minutes or hours, not driven by some outsider, you know, pulling puppet strings, but something that says almost like the drive evolutionarily for creatures or for humanity, for whatever we consider the mission statement of our lives or humanity in general. What will be that thing? Is it, you know, to understand the universe, the way Grok and XAI says it? Does that become a driver for unharness like that? Is it something like a novelty-seeking algorithm?

• 7:57Speaker 03

  That says, I'm going to continue to learn about the world and use novelty as my filter for, oh, I've just discovered something new. How do we know if I'm making progress? What is, if you will, the selection pressure in an evolutionary algorithm? What is success? It's not just reproductive fitness in the biological sense. It's something grander. And I, I know that some of these groups are working on what is, is there a single reinforcement learning algorithm with continuous learning, let loose in the wild with all the data sets of the internet that could bootstrap intelligence in that sense and the way that we Think we're seeing in the large language models today, but it's largely, we ascribe, I think consciousness to other beings, we ascribe meaning to other things, and we see

• 8:39Speaker 03

  patterns whether or not. And so I think a lot of it is a bit of, it's a fun interaction, but it's not quite the same thing, right? We just, we know there's nothing there inside. There's no light on inside, if you will.

• 8:49Marina Mogilko?

  So you're describing, I think, is it super intelligence when it's learning by itself, setting goals to itself? Are we gonna see some version of that in the next three years?

• 8:58Speaker 03

  I know Jack Clark, co-founder of Anthropic, gives it a 30% chance it happens next year.

• 9:03Marina Mogilko?

  Super intelligence?

• 9:05Speaker 03

  Yeah, absolutely. So I thought, well, that's kind of fun. There's at least one person putting a stake in the ground. I don't know.

• 9:10Marina Mogilko?

  But at Anthropic, they have a lot of strong opinions.

• 9:13Speaker 03

  But they do, but they also think that they're on the path. And there's a big debate as to whether this recursive self-improvement thing that they wrote about today, and that Jack's been talking about for a few weeks now, I spoke with him about it last month or two months ago. Is there gonna be some leap that we don't currently see for how these systems take on purpose and meaning in the wood I was referring to just a moment ago? Because right now, everything that they do is directed by a human. There's like, yes, the self-improving AI loop that they're witnessing already, these huge improvements, are coming from a number of steps that are still directed by humans. There's, you know, automated verification, improvement loops in the process of training itself, you know, adjusting hyperparameters from one training run to the next. A bunch of ways you could

• 9:55Speaker 03

  imagine, high-through experimentation being mediated by the AIs. But what is the goal? The goal setting is still by the human. And so it may only be a thin veneer of activity that it's not yet doing, but it's in some ways the most important, right?

• 10:10Marina Mogilko?

  Yeah.

• 10:12Speaker 03

  And they'll admit, they're not sure, how does that just happen, right? What makes that transition? And I don't know if it'll need to recapitulate some of the functional specialization in our own brain. Like, we evolved to where we are today with a history of reactive limbic systems and what have you, emotional centers that then the cortex and more and more cortex layered on top of it. That whole construct may, as we heard in earlier Speech be the bootstrapped to consciousness as a perception of what we perceive. Do we need to have the same things in our robotic slash AI systems, right? There, there may be, so it's a philosophical argument. The main answer to your question would be, I do not know. And I don't really even have the odds on it.

• 10:56Speaker 03

  I give it the fuzzy future kind of, yeah, that might happen. But only because that's more convenient as an intellectual shortcut to actually thinking about it. As a, as a serious hard problem is to put off that three years feels far enough in the future. That it's hard to predict almost anything.

• 11:13Marina Mogilko?

  So we're seeing all the demos of robots and current technology. I think is stronger than the deployment itself. We're still adopting, we're still adjusting. What's this gap? How big is it from, from what technology is actually capable of versus how we're using it?

• 11:31Speaker 03

  Oh, right. Yes, that's a very good point. And there'll be inherently very differential domains of acceptance. So here's a great example, very simple to understand is if it involves the world of atoms, it takes time. So even though it is obvious today that fully autonomous vehicles are the inevitable future. That every car will be autonomous, every train, every airplane, everything that moves on earth will be fully autonomous in the future. How could it not? It's, it's insane to think now or to argue that it's not, even though we've been saying this for decades.

• 12:04Speaker 03

  The pace of switchover is going to be, it's going to feel glacial in certain parts of the world, right? People keep cars for an average of like 11 to 12 years. So you just have the physical swap out cycle for the car cycles. You have, you know, the change in mobility doesn't happen overnight. Okay, that's an obvious one. Physical robotics might be the same. How long does it take to make a billion robots? That takes some time, even with recursive manufacturing techniques. And so the place where I think it just sweeps like wildfire can be in areas strangely that we sometimes held as uniquely human or the creative arts. You know, the movie making the images, what have you, which we've already seen. It's in some ways shocking that that came first. And then the white collar jobs as was mentioned, because a white collar job capability.

• 12:51Speaker 03

  Take call centers, right? It's like 1% of USGDP. That like that just happens like that, right? I mean, you just do not need to wait for decades for that to switch over almost entirely. And interestingly, people will increasingly prefer these to human interactions when they're better, show more emotional understanding, more reading of the situation. And that's seen in everything from physician bedside manner to chatbots and or customer support agents is that the AIs do a better job with emotional connection than humans.

• 13:25Marina Mogilko?

  Yeah, it's crazy how in some industries it's happening super fast, especially when it comes to software engineering. Some of my friends were editing 70% of AI written code a year ago. Now it's down to 30%. I wonder what it's going to be in a year. So you worked with some of the most amazing entrepreneurs. You're working a lot with Elon. I know a lot of people in the audience are builders. Is there anything like maybe top three principles that everyone should learn from him?

• 13:50Speaker 00

  This episode is brought to you by Google Chrome. You think you know a browser, but Gemini and Chrome, that's new. It can help you with practically anything on the web, like restoring a vintage motorcycle from a 50-page restoration block, or finally break down that long article you've had open for weeks. Gemini and Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses set up required. Compatibility and availability varies 18 plus.

• 14:16Speaker 01

  This episode is brought to you by Indeed. You're ready to level up your business, but the pressure to find the right person to make that happen is intense. Indeed sponsored jobs can help carry the load. It boosts your job post to help it reach quality talent fast. Cut through the chaos with Indeed sponsored jobs. Get a $75 sponsored job credit at indeed.com/podcast. Terms and conditions apply. Hiring now? Then this is a job for Indeed sponsored jobs.

• 14:47Speaker 03

  It's funny, people have been sending me these books that just, I guess they directed an AI to write about AI, you know, about Elon, how he thinks, the secrets of Elon. I've actually been accumulating them on my bedside, but I'm not sure if the humans written any of them. A lot of people ask Elon's mom, you know, hey, how did you, how did you parent Elon? How did you get him to be the way he is? And that's a tough question. She hasn't been able to answer either. And so I'll take it with a bit of humility that even as a close observer, by the way, I do try to observe leaders in actions. I worked with Steve Jobs briefly, briefly, and it's like I put all kinds of energy to try to understand how that guy works. But even with a focused effort, it's not always obvious. People are complex. So, but, but a few things. One is this insane ability to focus, which may seem ironic, given how many companies he's simultaneously running, setting new

• 15:30Speaker 03

  records for that in a way that, you know, when Steve Jobs was CEO of two companies, that seemed strange. Now it's all the rage. But one thing that allows you to do is use the fact that you've got obvious competing needs for your attention as a way to focus, prioritize, and not go to meetings. If a normal CEO of one company didn't go to their holiday party, you know, it might be seen as weird and like, whoa, but no one questions if Elon, he's got other things to do, he's got other companies. So what that, whether it's an excuse or it just works out this way, he says no to things so effectively that are distractions, that are not mission critical right now. I mean, for example, years ago, I was trying to hook him up with Craig Venner to brainstorm ways we could, you know, terraform Mars more easily and do a sample return of life from Mars with

• 16:13Speaker 03

  gene sequencers and re-instantiating. Anyway, microbes on Earth, it was a fascinating topic to me. I was like, whoa, this is so fascinating. But he's like, no, it doesn't matter. Until we get Starship flying, none of this stuff on Mars matters. I gotta get that thing working first before we think about what we do when we get there. There's, I think, maybe more importantly than what I just said, even more importantly, is this maniacal focus on the, what I would generalize as the cycle time of innovation, which is How rapidly can we run experiments or iterate in our learning loop? What is the core learning loop? Whether it's the launch cadence, whether it's the data gathered from all the Teslas before fully self-driving vehicles came that could be used to train the models? How can we make sure that we have a leg up on anyone else on the rate at which we're

• 16:58Speaker 03

  learning from customer interaction, product features, and technology in general? And as an example of like how powerful that is when you do it right and the data fly where you can get it for, make for AI, just one example. Tesla's cars today and their cameras gather for their AI training set more data every four days than Waymo has in its entire history. And the brilliance was enabling every vehicle, whether or not the customer paid for full self-driving, to be a data collecting vehicle. Okay. So focus, learning loops, and this, um, a whole series of well-honed skills on identifying talent that I wish I could replicate. I just can't.

• 17:40Speaker 03

  It's like there's, sometimes there's a pattern recognition and he'll share bits and pieces of this, like, you know, not, not leaning on credentials or specific background or experience. In fact, it's often an albatross, but like having people really walk through major engineering crises or problem-solving things and then drilling down further and further and further to show if they, did they really master the, do they have mastery and understanding of what it took to make something successful? So broadly defined, being a magnet for talent, finding a way to pitch and, and refine a vision that people want to join you. So like one of, one of his brilliant things at Tesla, SpaceX, everywhere is not just saying, oh yeah, we're making rockets, we're making cars, but to really think of something much grander, right?

• 18:23Speaker 03

  Catalyzing the, you know, transition to sustainable energy or making humanity multi-planetary, understanding the universe, you know, now that XAI is merging into it. These are the sort of lofty goals that motivate some of the best and the brightest to want to work with you in that is a sort of compounding benefit that ripples out through a whole organization, right? Because great people want to work with other great people.

• 18:46Marina Mogilko?

  I'm talking to a lot of entrepreneurs and especially these days with things moving so fast, there's this new shiny thing every single week. How do you stay true to your mission when the rest of the world, 99% of the world, tells you it's too early? Like talking about space, we have so many problems here on earth.

• 19:05Speaker 03

  That's an interesting question. And I realize I have a bit of a sample selection bias in that I've tried as best I can, I've done VC now for 30 years, to only work with the people who have a true sincere, you know, messianic mission in mind that is driving them. And they're not the arbitrage seeking opportunist to see the next bright shining object or oh gosh, you know, where should I go to next? And one of the ways, and I'll get to your question, but one of the ways, by the way, that I filter for that in meetings is, let's say I'm getting really excited about a company, I'll often ask, you know, Kate, what does your business look like in 50 years? And I get usually two reactions most often. One would be a chuckle, like, what a ridiculous question, you know, like the arbitrage seeking opportunist is gonna be like, I'll be my third startup by then?

• 19:50Speaker 03

  Like, what, how would I possibly know what my startup is in 50 years? Like, they just laugh at the question. And then we pass on those. And then the best is when the person's like so relieved, like, oh, thank God. Now I can actually tell you what I've been wanting to say all day long, which is, this is what's driving me. It's this thing that's so many steps ahead of what you would probably want to invest in today. Like making, you know, colonizing Mars is an uninvestable proposition. Go back in the founding days. Like, when you start a business, day one, I'm gonna colonize Mars, like, yeah, next, right? For most investors, right? Like, that's not a door opener. And so most entrepreneurs that have that true sincere vision have found a way to like subjugate and put off what their true dreams are and talk about something much more prosaic

• 20:31Speaker 03

  and near term. So I think the answer would be as the entrepreneur, it just happens naturally and try to find investors and partners and certainly employees who are with you for that long ride and have a path to get there that is plausible. So you know, this is sort of a joint tension, I think, in the best startups. It's hard to simultaneously satisfy, which is an endatious, you know, 50 to 500 year vision. This is what this company is going to do to the economy or the universe. Coupled with, oh, and by the way, over the next three years, we're going to iterate with real customers, learn from that and have a can paint the path from where we are now to that future that is chaining. Sometimes

• 21:14Speaker 03

  they chain back from the past to the present, like to get there, what do I have to build now and then and then move forward on that path. But it's not like go into a research lab, pop out in 20 years and, you know, solve all the world's problems.

• 21:24Marina Mogilko?

  Yeah, this is a really fascinating feature that I see with a lot of greatest entrepreneurs. It's like if they're reverse engineering from 50 years ahead. Is there anything surprising that still surprises you about those amazing entrepreneurs?

• 21:39Speaker 03

  Well, I suppose it's a bit surprising in a way each and every time it goes incredibly right. So weirdly, this may sound weird. I don't think I've ever thought about that question before or been asked it before. And so the perpetual surprise for me is like, wow, like in the year eight, nine, 12, some new opportunity that opens up and unfolds from the, in a sense, the expanding option value of going into some new frontier of the unknown. So what I mean by this is we try to invest in, by the way, at our firm Future Ventures, in things that are unlike anything we've seen before, yet adjacent to where we've been. So ideally, it's a company that's literally one of a kind.

• 22:22Speaker 03

  Based on things we are used to, whether it's AI, whether it's something synthetic biology, whatever it might be, but they're taking it in some new direction. So the window, as long as you have an agile mind and you're looking at it, wow, like no one thought of that when we started. So for example, when Tesla, when we first invested in Tesla, there was no concept whatsoever, autonomous driving was not in the business plan, there was no talk of it, it was not in anyone's mind. The way in which electric drivetrain uniquely enables that and control and fidelity was fascinating. Or in SpaceX, the Starlink, you know, opportunity, like, oh yes, of course, when you lower cost of launch that much, you can have mega constellations, but what would be the new thing that that would make sense that we weren't doing before? Not just, we invested in planet labs for earth observation, yes, constellation of telescopes,

• 23:05Speaker 03

  but this whole notion of building a network backbone for the internet in the sky was, and then direct to cellphone, like each one of these things is unfolding, then orbital data centers, right, not on the dance card even five years ago. So that continues to surprise me. In some ways, it's not easy, but it seems so much more powerful as a business vector than purposeful design, if you will. It's almost like exploring the option space that, or the light cone, if you will, of possibilities in an economy versus, you know, sort of planning out something 10 years in advance and having it go according to plan, if you will.

• 23:45Marina Mogilko?

  It is so fascinating how you were successful in so many different bets that you made in the past, and they're so different from each other in different industries. What are you betting on now? What should we be looking out for?

• 23:56Speaker 03

  Plastics, no, let me think.

• 23:59Speaker 03

  Some people who know the old movie, let's see. So we, so taking that thesis that AI and information technology will innovate every economy, meaning add a nervous system to everything. We saw in automotive and aerospace, just expanding on that thought a bit. We are looking for additional things in energy. We've invested in a variety of nuclear fusion and, and, and subcritical fission that doesn't trigger NRC regulations, basically avoiding the Nuclear Regulatory Commission, but figuring out energy, which by the way, is the third bottleneck for AI. It's not just good people and a lot of compute, it's also energy. There are a bunch of things that you could imagine 500 years from now have been solved, and we're trying to figure out, the entrepreneur will open their eyes to how we get there. So free healthcare forever via cellphone, all diagnostic information you could possibly need

• 24:43Speaker 03

  for your personal health should be a free service globally. Trying to figure out how to get there, probably won't be in the US that it launches. You know, bypassing FDA, bypassing insurance and reimbursement. On food, we won't slaughter animals for meat. It's the, the products are getting there, but that you can sort of see the future. It's so close. You can almost taste it, so to speak. Whether cellular ag, mycelium, or other techniques, mycelium being the fastest growing thing, but, but we are going to eat meat like things that are delicious, healthy, and not involve slaughter of animals. Uh, construction, growing as a percentage GDP and like labor productivity has been flat for 30 years. So that it's such a hard industry to change, though we've tried and failed a few times, but we're looking.

• 25:25Speaker 03

  Again, so what the best I can do to answer your question is, I don't know what the answer is, but I know there is categories that I don't, that we want to look at. Recently, we've been investing in epigenetic editing across a variety of things, crop health, pesticides, herbicides, um, human health. It's fascinating. It's basically the software of biology instead of going to the firmware of our, or our genome. And, uh, we've been investing in materials, critical minerals and metals, uh, everything from deep sea mining to copper refining. Uh, because of incredible need, sort of like the workhorse of all these chips is you need these materials to make the stuff. And there's a couple of that, a reshoring or, you know, bringing back to the US capacity to build that which we had, uh, atrophied over many years.

• 26:06Speaker 03

  Analog AI, I mentioned it, we have three different investments coming at it from different angles, using AI to develop, to design AI chips, uh, sorry, analog chips. Yep. Uh, analog, um, in-memory compute from Mythic where they can do eight bit multiplying add in a single transistor. And then unconventional, which is taking a very, very strange and forward looking, um, big bet on, you know, in every case, trying to get in a hundred X and then another hundred X on power reduction, power per, per, um, per calculation. Overall, we're about 40% life sciences, 60% IT and, and we, in the life sciences side, just see, we look for the weird things that are like. On the edge, you know, harvesting organs for transplant and growing humans without brains so that you can use their organs. There's a company here, actually in the audience, doing

• 26:49Speaker 03

  the same thing, a male birth control pill, improving IVF dramatically, things that fall through the cracks of a traditional pharma VC.

• 26:59Marina Mogilko?

  So I'm hearing agriculture, biotech. I'm just thinking in my head, how can I replicate your strategy with ETFs?

• 27:05Speaker 03

  Well, it's hard to replicate. See, our strategy, I can state, it's very unusual. I can state it openly and then it's hard to replicate because when I say we invest in things that are unlike anything we've seen before, well, that's great, but how do you know what we've seen? So, you know, what we're actually doing is not as

• 27:18Marina Mogilko?

  But at least it's in the areas. So if they are dramatically changing a market, then it's going to be reflected in.

• 27:24Speaker 03

  Especially if it's an old crappy business that hasn't seen a new entrant in years. So like boring company for tunnel boring machines, like, like the four largest companies were all started in the 1800s. That's who you're competing with.

• 27:34Marina Mogilko?

  We have a lot of entrepreneurs who have crazy ideas. Can you give them a 30 day plan to execute on that idea? What would be the best thing that they can do?

• 27:44Speaker 03

  What stage are they, are you

• 27:46Marina Mogilko?

  They just have an idea.

• 27:47Speaker 03

  Oh, single person with an idea?

• 27:48Marina Mogilko?

  Yeah.

• 27:49Speaker 03

  Hmm, 30 day plan. I might try to find a co-founder who agrees with you or whoever this person is. And the reason I say that is a lot of startups tend to have a dynamic duo at their founding. It's rarely an individual. And you can, you can imagine Jobs and Wozniak as a mental model for this, or these superheroes, Batman and Robin, you know, Sergey and Larry Page. Even Larry Ellison had Bob Miner, who's less well known because he's an introvert, but you know, there was not like a singular cult of personality of a founder. And part of the reason to have someone is, I found this as an investor, having a colleague, Mariana, my co-founder, is I am so much better as an investor, having someone to bounce ideas off versus like being the sole, you know, like an angel investor or something. And similarly

• 28:32Speaker 03

  for a startup, having a diversity of backgrounds, like an engineer and a marketing person, an extrovert and introvert, whatever it might be, that have mutual respect for each other. Not only makes it better that you like some, you got someone to bounce ideas off of in a rapid iteration loop where just two of you, but it also sets the culture for everyone that you'll hire. It's not like, oh, there's a singular person that everyone works for. It's more like there was a pair and they're very different and That that ripples through the culture of a firm and types of people that are hired and the cognitive diversity that follows. So finding and the reason I say that is finding someone who agrees that your crazy idea is worth pursuing is better than finding zero people. In other words, I think the best outcome is if you're literally your premise, you question a crazy startup where no one else is doing it.

• 29:16Speaker 03

  It's one of a kind and most people tell you it's crazy. Well, it is possible that it's crazy. All right. So if a hundred percent of people that you've ever met think it's crazy, take that as feedback. If it's, you know, nine out of 10, that's pretty good. If it's eight out of 10, that's pretty good, too. If it's like only two people think it's crazy, that's bad because it's clearly not bold enough. If it's an obvious idea, other people will do it, right? And ask yourself, is this a business that couldn't have been started three years ago? If the answer is yes, that's good, right? If it's like, oh, yeah, no, it's anyone could have started this business if they just had this idea, probably a bad sign. And then somebody that your co-founder agrees with you and thinks, oh, my God, this is me. That just shows that as almost as a case, you can persuade persuade someone to give up their job and join you in this mission.

• 30:01Speaker 03

  Then before you go out and fundraise, that that says a lot more than just this old person with an idea, like the inventor in a garage, you know, off all by themselves. There's so many cases like that that just never manifest as a business because they just never made that first step of being able to persuade anyone to join them in the mission.

• 30:16Marina Mogilko?

  It's great advice because a lot of people start with building an MVP or like even pitching investors right away. The co-founder, it sounds incredible. From all the startups you founded, where did the best co-founders meet? Is that university or?

• 30:30Speaker 03

  Good question. I'm not sure. I haven't I haven't thought through that.

• 30:35Marina Mogilko?

  Is it so hard?

• 30:35Speaker 03

  Because they often they often come to us having already done that and often, yes. So for all the university ones, there are many of them are from that's probably your your question had embedded within it the most common answer, which is, you know, we met in some interdisciplinary way at a university, which is fascinating, by the way, the word disciplinary, you know, or disciplines, academic disciplines, they're a way of stove piping information into a systems vernacular and domain expertise that often doesn't cross pollinate. And university is one of those few places where you get these spanners, you get these undergrads or other people who take courses outside their department, unlike the professors and their little stovepipes. And despite a lot of institutional efforts to share information, it's often the students that are the cross pollination between academic disciplines.

• 31:17Speaker 03

  And that's at those boundaries or interstices between formerly discrete disciplines that you find, I think, most breakthrough innovations, certainly in the sciences. As a quick aside, that's something that large language models do very well. Translating between academic domains, seeing patterns in the, you know, almost the translation, if you will, between languages, between concepts. And that, I think, is allowing a fountainhead of possible idea discovery using AI to figure out new ways of cross-pollinating between academic disciplines that I think we're only beginning to tap into.

• 31:51Marina Mogilko?

  This makes total sense. I think I can be talking to you for hours because you are someone who's really good at predicting future and betting on it and seeing where we're going. I have one last question before we open it up for Q and A. When machines do everything, what's the meaning of life?

• 32:07Speaker 03

  Yeah, yeah, and your question, I think, is an interesting one to contemplate. What do we do when machines do everything that we do better than we can? Every physical activity, everything that involves employment. And it's going to come soon, right? Roughly 19% of global employment is in driving vehicles. And that's obviously going away, just not as rapidly as we might imagine. I think we, we want meaningful work. I think all humans have a fundamental desire for symbolic immortality. This belief that we've contributed something to the world that transcends our brief time on this world. And we see that, of course, in the drive to have children

• 32:50Speaker 03

  or in writing works or in philanthropy or creating companies, sometimes even named after their founders, like Hewlett Packard or what have you. These are instantiations of that urge. And so I think there's still a creative desire. And I could translate the question to be like, what is the mission statement for humanity? It's a question that Yuri Milner and Elon Musk and others have asked. And they've come to a similar conclusion, which is to understand the universe, to try to contribute to the wisdom, the accumulated knowledge. That we have, you could think of human culture and our knowledge base that we pass on from generation to generation as the primary vector of our own evolutionary progress. It's not biological evolution, that's glacial in comparison. And any progress we feel humanity is making is not because we've changed our biology,

• 33:31Speaker 03

  it's because we've changed our accumulated basis of knowledge, the way we comport ourselves, the rule of law, the understanding we have around what works and helps with human flourishing. So I think we all want to contribute to that. It doesn't have to be paid employment, though. So you can't imagine some sort of hyperspace jump, because that's conceptually what it requires, because there's no way to imagine how we get here, from here to there. But somehow, if we just jump there, to a world of abundance, like Peter DeMandis envisions, you know, everything physical costs a dollar a pound, there's nothing that requires human labor, we all are the indentured rich, like in the days of yore, we had, you know, servants or serfs or slaves that did all, you know, menial work, and we could just

• 34:15Speaker 03

  be, you know, philosopher kings, or artists, or pursue whatever we might want. And some people, some, not all, but some people really loved that era. Well, the machines will be those slaves, right? Not, because even in slavery, humans will not be cost-effective. And I say that somewhat tongue-in-cheek, but it's like, finally, the scourge of human slavery might finally end when that's no longer even cost-effective compared to machines. What does that leave for the rest of us? And so I think it's going to be a man's search for meaning that really is the core question. I think it's going to be really fun if we could hyperspace there. But I will add the caveat, that's not the path we're taking. Like, there's nothing that indicates that we're just going to peacefully march from an economy of full employment to an economy of no employment and pass through the 30,

• 34:58Speaker 03

  40, 50% unemployment points, but lots of issues.

• 35:01Marina Mogilko?

  It's going to be turbulent, yeah.

• 35:02Speaker 03

  That's going to be tough, and I don't see any politicians taking long-term perspectives on any of that. So I don't want to end on a downer. Let's go back to that hyperspace to abundance. I think, I think we inherently find that in our curious exploration of the universe.

• 35:15Marina Mogilko?

  I really like the rule of going back to your mission statement, because a lot of us these days are questioning our jobs, what we're doing, is it going to exist in the same shape and form in three years? And again, going back to your mission statement, I think this is brilliant. Thank you so much, Steve, and let's open it up for Q and A.

• 35:38Marina Mogilko?

  Quick pause here. If you're enjoying this podcast, you will absolutely love my Inner Circle newsletter. So what I basically do is I take all the tips from these podcasts and I apply them to my personal life, to my investment portfolio and to my businesses, this media company and my language teaching business. Sometimes we get amazing results and I share our real tactics. Sometimes we don't and I share that too. Think of it as an insider version of this podcast. The link is in the description. Join my free newsletter to stay ahead.

• 36:05Speaker 05

  Thank you, Steve, for your fireside chat. Since you're a big investor in Elon Musk companies, I'm curious, have you invested in Neuralink?

• 36:15Speaker 03

  Yeah.

• 36:16Speaker 05

  Yeah, so honestly, in my opinion, everybody is excited about SpaceX, but I'm looking forward for an IPO of Neuralink. Do you think it's happening soon? And honestly, I think it's basically brain-machine interface is the future. But essentially, currently, if we use voice mode on ChatGPT or OpenAI, right? Or we type, we are limited in our throughput of how many tokens we send to the LLMs. And if we have brain-machine interface from Neuralink, we're able to unlock even more creativity and faster throughput from our brain to machine.

• 36:56Speaker 03

  Yeah, I can't comment on IPO timelines, but the enthusiasm there is interesting. It was originally sparked, as many things are, from a science fiction novel, Inbank's Surface Detail, where they have a neural lace. Fascinating book, I recommend it. And I think what you see... So I have a somewhat unique perspective not shared by Neuralink. So, but I'll just share my perspective, which is I think it is an amazing capability for expanding the sensory cortex, adding the processes to the mind. In other words, restoring function where it's broken, expanding function, like let's say seeing in more wavelengths or hearing better than we could hear, not just repairing hearing, fixing spinal cords,

• 37:40Speaker 03

  basically working from the periphery of these systems. As opposed to a much more difficult and yet to be solved task, which is upgrading core functionality, like just making someone smarter. So I think the example you gave is a very interesting one. Could you have a higher data rate communication? Absolutely. I think that is very doable. And the reason I have this belief, it's more of a pattern recognition across decades of complex system development. Basically, the high level statement would be, any product produced from an iterative algorithm, which would be evolution, genetic programming, all neural networks, you know, cellular automata, whatever it might be. If you iterate something billions of times and accumulate complexity from that algorithm,

• 38:24Speaker 03

  the thing you make is inherently inscrutable. It is an artifact of absolute, like, inscrutable complexity. Despite attempts at mechanistic interpretability in AI, I don't think that's going to bear fruit. I don't think control and alignment is possible in a cutting-edge system that is pushing, back to AI for a moment, pushing the capabilities of what we can build. Similarly, it'd be like asking about controlling, aligning, mind-controlling a teenager. So I swap teenager and AI whenever I think about this. So the reason that's relevant is when the brain is a complex system itself. And reverse engineering its inner workings for uploading or for, you know, brain-to-brain or like adding speech, like the way Jeff Hawkins thinks you just like

• 39:09Speaker 03

  cut and paste like a French-speaking module into a human brain or a neural net, I don't think that's going to be possible. On a timeframe of relevance, meaning it'd be easier to build a new intelligence than it is to reverse engineer one that you've made. So I do think Neuralink is fascinating, but I don't personally get faith that it's going to keep up with AI. Maybe that'd be the safest way to phrase it. Not that it can't be done, but the time scales, you know, FDA cycles, human biology, nothing happens on a time scale comparable to the learning loops. Back to Elon Musk saying, focus on learning. Where do you learn more quickly? You can learn more quickly in the synthetic domain. I think humanity always wants to believe it's part of the future in that regard, but the Kerswell's uploading, I could just see why he wants that to be true within his lifetime, and that's what he predicts will happen, but it doesn't mean it will.

• 39:54Speaker 06

  Steve, I'm really curious, what do you think about Ben Roethlisberger's argument that the consciousness is go far beyond algorithmic processes to quantum-level processes, meaning that...

• 40:10Speaker 06

  AI would never be able to to develop consciousness itself just by its nature. So what do you think can AI develop consciousness? Or it will be only imitated and that's it?

• 40:28Speaker 03

  And you were referencing Penrose's.

• 40:30Speaker 06

  Yes.

• 40:30Speaker 03

  Yeah, so Penrose is a brilliant guy in UK generally. But here he has this gut feeling that there's some quantum process in the brain that makes it unique. And yet there's no real clear mechanism by which that would happen. There's some argument around some lithium isotopes that might be coupling, but but it's wishful thinking. We don't, so to speak. But I can also generalize your question. Is there something vitalistic, naturalistic, unique to our brain that is irreproducible in others? And there was a reference earlier to Neil Seth's work. I find the arguments completely unconvailing that there's something vitalistic or unique to the substrate, just because it's the only example we know of of consciousness and consciousness,

• 41:13Speaker 03

  for example, is a tricky thing like, do how do we know if the dog is conscious? What how do we how do we test for this? Right? But we believe we see it in ourselves. I mean, I don't know if you're conscious, but I'm kind of just guessing you are, right? And you seem awake and you're human, therefore we generalize it conscious. Okay, so I have not seen a compelling argument just because we have an example of one doesn't mean it's the only possible example. It's you could make a similar argument that says, does all life need to be carbon based, right? And there is something unique about carbon and it's be able to do single, double and triple bonds and all the weak bonds. It is kind of you could actually make, I think, a better argument that says carbon is special to life than you could to say neurons as we have them are essential to consciousness.

• 41:56Speaker 03

  Now, a totally different question is, but I won't digress, is like, is anything that we're doing in AI development going to lead to consciousness? That's a different question because you could you could argue that's a dead end and won't get us to consciousness, but it doesn't mean it's not possible. It's much higher order proposition to say something is impossible than to say, I don't know. And so my answer would be, I don't know, but I certainly wouldn't say it's impossible. And I don't believe that we have. Any evidence of a quantum process going on in the brain? And if we did, why couldn't we replicate that with quantum computers? I mean, that's a different question. And then if I broaden your question a little farther, just animus or spirit or life, is, does it have to be a living thing to be conscious? And the analogy I would use is imagine you substitute the word memory for consciousness. And I just picked memory just randomly. It's an overloaded term.

• 42:41Speaker 03

  Do we mean memory, like I have memories? In a human sense, human memories, which are holographic and it can have graceful degradation. And they're not at all the way we do memories in a computer chip. But when we talk about computers, they have memories too. And we don't debate is memory possible in a computer? Can it remember things? Well, in the, at that level of abstraction, of course they can. And yet it doesn't have human memory. And that's fine. So consciousness, it may not have human consciousness, but maybe it has a different kind of consciousness, whatever that thing is, if we could be more precise about defining it. And I don't think you make the argument that everything we have in our brain is essential for conscious. In other words, there's a lot of there as a garbage collection for our metabolism. You know, the, you know, things that happen when we sleep and cleaning up by, you know, waste products and the way mitochondria work.

• 43:25Speaker 03

  You don't, you don't have to have all of that in a computer to be intelligent or to have memories. You don't need all that baggage for consciousness either. But that doesn't mean we know what the minimum set is. But it does, I think we'll figure it out one day. So in other words, I'm more on the, my gut tells me, oh, sure, I think one day they will be conscious. I don't know if we're on a path to get us there. Maybe something more akin to evolution and reinforcement learning algorithms would get us there more, more. Obviously, just because whenever you recapitulate what we've already done with our biology, that makes me give hope that, well, why can't we do it in a different substrate?

• 43:59Marina Mogilko?

  Thank you so much.

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