Steve Jurvetson Interview | The Tim Ferriss Show (Podcast) | Transcription

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- This episode is brought to you by Four Sigmatic. You might remember Four Sigmatic for their mushroom coffee, which was created by those clever Finnish founders. And when I first mentioned that coffee on this podcast, the product sold out in less than a week. It lights you up like a Christmas tree, which can be really useful. However, recently I've been testing the opposite side of the Spectrum, a new product, and that is their Reishi Mushroom Elixir to help me end my day, to get to sleep. As you guys may know, long time listeners at least, I struggled with insomnia for decades. I have largely fixed that, but still shutting off my monkey brain has never been easy, still isn't easy very often. And I found Reishi, which I've been fascinated by for a few years now, has been very, very effective and calming. Their old formula, however, Four Sigmatic's old formula included stevia, and I like to avoid sweeteners, all sweeteners, for a host of reasons. And I then just pinged them and asked, "Hey guys, I would love to experiment with this "and maybe actually suggest it, "but I'd like a version without sweeteners "if you'd be open to it. "If too much of a headache, don't worry." And they are always game for experimentation, so they created a special custom version without the stevia, without sweeteners. Now it is part of my nightly routine. Their Reishi Elixir comes in single serving packets, which are perfect for travel, and in fact, I'm about to leave the country right now and I have a packet in front of me that's just gonna sit in the end of my carry-on bag. You only need hot water, and it mixes very, very easily. Here's some recommended copy that they put in the read, so I'm gonna read it and then I'll give you my take. Quote, "A warning for those in the experimental mindset. "Reishi is strong and bitter," in parentheses, like any great medicine, "so if the bitterness is too much, "I recommend trying it with honey and/or nut milk "such as almond milk," end quote. So I'm gonna say, "No, you should suck it up "and you should drink the tea, "because it's not that bitter, "and maybe you should take the advice of old Chinese people "when they're criticizing young'uns when they say, "bu nang shi kuo," which means, "You're not able to eat bitterness." Bitter is, in many cases, an indication of things that help liver detoxification and so on. Not saying that's the case here, but I've tested this Reishi Elixir on family members, on friends, everybody has liked it. It's a little bit earthy, it's not that hard. So I would just say, "Suck it up and no, "don't put in honey or nut milk or any of that shit. "Just drink the goddamn tea, it's delicious." I think, right? If you like Pu'erh, that kind of stuff, that type of tea, you're gonna dig it, so just try it. Okay, back to then my read. If you'd like to naturally improve your sleep, both onset and quality, I think, naturally, you might just enjoy this Reishi Elixir without any sweeteners. It has organic Reishi extract, organic fueled mint extract, organic rose hips extract, organic tulsi extract. And that's it. No fancy stuff, no artificial, whatchamacallit, anything. So check it out, go to and get 20% off this special batch. I don't know if they're gonna be making much more of this, since it was made specifically for you guys. So do me a favor and try it out, so that they continue to be open to experimenting with me to create products for you guys specifically. Check it out, Four Sigmatic, that's, F-E-R-R-I-S-S, and get 20% off this special batch. And you must use the code ferris to receive your discount, F-E-R-R-I-S-S. So again, go to, and then use code ferris for 20% off of this rare, exclusive, limited run of Reishi Mushroom Elixir for nighttime routines without any sweeteners. Enjoy. This episode is brought to you by Helix Sleep. Last year, I committed to making sleep a top priority, trying to fix onset insomnia, or continuing to fix that depth of sleep, quality of sleep. I tracked a lot, I tested a lot, and I revisited really everything, from the daily routine to the surfaces I slept on, playing with the chili pad, whatever. And when I moved to Austin, I got all new beds, including mattresses from Helix. Working with the world's leading sleep experts, certainly some of them, Helix Sleep developed mattresses personalized to your preferences and sleep style to make sure that you can have the best sleep possible, without costing thousands upon thousands of dollars. Helix Sleep has recently added a new layer to customize sleep with the Helix Pillow. The all new pillows are fully adjustable, so you can achieve perfect comfort regardless of sleep position or body type, or if you're a shifty type like me, I move around quite a bit when I sleep. Just take their simple two to three minute sleep quiz to get started, and that will help ensure that they can build a mattress or pillow that you will love. The mattress, whatever this bespoke mattress is that you arrive at, will get to you within a week, and the shipping is completely free. You can try the mattress for 100 nights, and if you're not completely happy, they'll pick it up and offer a full refund. I tested that refund policy, 'cause I test all of these sponsors, and kick the tires a lot. We tested it, and they came through on making sure that we got ultimately the right mattress for my body type. To personalize your sleep experience, visit, and you'll receive up to $125 off your mattress order. That's helixsleep, H-E-L-I-X,, for up to $125 off your order. - Why hello, boys and girls, this is Tim Ferriss, and welcome to another episode of The Tim Ferriss Show. My beautiful little matien. This show, as some of you may know, is about deconstructing world-class performers, teasing out the habits, routines, life lessons, thought processes, frameworks, and so on, from people in many different industries, many different areas of expertise that you can hopefully apply to your own lives. And my guest today is Steve Jurvetson, who really has his hand in many, many different worlds. You can say hello to him on Twitter, @DFJSteve. He is a venture capitalist, but a lot more than that, focused on founder-led, mission-driven companies at the cutting edge of disruptive technology. Now, you might think to yourself, well, that's what I might hear many venture capitalists say, but he was recommended to me by a past guest, as a guest, Matt Mullenweg, who I trust very implicitly. And to give you an idea of the street cred, he has been the founding venture capital investor in four public companies and many rapidly growing companies like Planet, Memphis Meats, Mythic, and Nirvana, and ERV, Nirvana. He also led investments in startups that were later collectively acquired for $12 billion, probably much more at this point. Before co-founding the firm DFJ, Draper Fisher Jurvetson, Steve was a R&D engineer at Hewlett-Packard, worked in product marketing at Apple and Next, many, many stories about his mentors there, and then spent a short stint in management consulting at Bain. He completed his electrical engineering degree at Stanford in two and a half years, think about that for a second, graduating number one in his class, and went on to earn all sorts of degrees, MSWE, MBA, et cetera. In 2016, President Barack Obama appointed Steve as a presidential ambassador for global entrepreneurship. Steve was also chosen as one of quote, "Tech's best venture investors," end quote by Forbes, and as the venture capitalist of the year by Deloitte. Steve will be launching a brand new venture fund sometime later this year, and you can read about it at Future.Ventures. So not, but Future.Ventures. That's how you would spell it out. Not surprisingly, he will be focusing on passionate founders who are on a mission to make the world a better place with a penchant for unique ideas and disruptive technologies. And disruptive may be an overused term, but Steve really understands what that means, and we dig into some very, very, very specific examples that might make your mind explode. So without further ado, please enjoy this wide-ranging conversation with Steve Jurvetson. Steve, welcome to the show. - Thank you, happy to be here. - I am looking here at all my notes, and you're kind enough to send links to various resources, interviews, discussions, and I have to tell you, I feel a little overwhelmed, because usually, if I have someone on the show, it's like, all right, we have person A, they're really good at rock climbing, I think we'll start with rock climbing. And in this case, we are not even gonna cover 10% of the notes that I have in front of me, and they've already been winnowed down, but there is, I think, one story that I came upon that I'd love for you to describe for people, just as a starting point. And it's a quote, and then you can give the background from Professor David Deutsch out of Oxford, and it begins with, and please correct me if I'm wrong, "The only way this computer can be as powerful as it is..." What is this quote?

Quantum Mechanics And Global Challenges

Quantum mechanics and quantum computers (09:23)

- Sure, and I may be paraphrasing, 'cause it's stuff he wrote back in 2002, 2001, at least I read the book Fabric of Reality in 2002, and he's talking about the power of quantum mechanics and the potential for quantum computers. And in so doing, he and Richard Feynman both realized that a quantum computer would be fundamentally unlike anything we have in this world today. And the way that quote roughly ends is that the only way to explain the power of these computers is to invoke the notion that it is sort of engaging the resources across parallel universes, that if you just use the resources of one universe, now there's so much you can do. But in this case, you actually are, in the most poetic sense, harnessing almost refractive echoes across parallel universes to do computation in a fundamentally different way. And that usually bends the mind of most scientists and even physicists to the point of breaking or looking the other way. And the common response to this is, "I don't understand one bit of that." And it had me captivated. - So I want to jump into a number of areas that I know nothing about or very little about, even though I might use the words occasionally. As people who spend a lot of time in Silicon Valley are want to do. But for people who don't have the background, I want to highlight a few things about you, or actually one, just as we're delving into some of the science. So your background, or a lot of your background, is engineering, correct? So electrical engineering? - That's right, I did a bachelor's and master's and started a PhD. - And you were able to do so much of that partially because you finished your undergrad in two and a half years? - That's right. - Okay, the point I wanted to make with that, and we're gonna come back to that, 'cause I don't know how that even happens, is that you have technical literacy. - So, yes, I'm also learning like a child. - Right, so can you walk us through one of the terms I was hoping to understand for myself, and that is quantum computing. What is a quantum computer? - Right, a quantum computer is a device. It's usually something that is either cooled down to almost absolute zero, or has some other phenomenon that it takes advantage of that is at the edge of what is the known universe. Meaning when you cool something to zero, behavior of materials changes dramatically. If you have a superconductor, the way it works is dramatically different from normal conductors. And so what people have found is that rather than look at quantum mechanics as something that is spooky and bizarre, the way Albert Einstein even described it, this spooky action at a distance, this ability to entangle things, to have their fates intermingled, can be not just used for things like really unbreakable cryptography and data transmission. It could also be used in a very bizarre way to build a computer. And this computer looks something like a row of, let's say, rings that are either magnetically in one direction or the other. You think of it in a traditional computer, it's a one or a zero. But actually it could be everything in between simultaneously. Much like when you dive into how an atom actually works, there isn't an electron at any given point, it's a cloud. It's a probability function around the atom. Well, that cloud is something we're not used to in the real world. It's not used to the statistical aggregation of many atoms. It's like there's a table, it's hard. I can't put my hand through the table. It's not sometimes here and sometimes over there. But the farther down you look, the closer and closer to, let's say, the atomic scale, you notice the behavior of physics becomes quantum physics. And rather than being something spooky, you can actually harness this to compute in a very peculiar way. In a way that, in a very simple level, you could say it's as if all of your memory bank in a computer was a one and a zero simultaneously, so you instantly jump or tunnel to the answer you're looking for to a particular problem. So rather than exhaustively searching millions or billions or trillions of possibilities to find, let's say, the key that unlocks a digital lock, you just jump to the answer. - That's seemingly science fiction, but these computers do exist. - Yes, and even within scientific communities, there's some backbiting that says, well, wait, do they really exist? Is this one an example? Is that just a fast analog computer? So it is at the edge of, A, what people believe is possible and I think we're actually literally at this period of history where these computers are starting to come out. I've been on the board of directors of one for, gosh, over 15 years now, so I was a little early in thinking when this was ready for prime time. It's now at the point where, for example, Google says that their quantum computer that they bought from a company called D-Wave outperforms their entire data center on certain computational tasks and that are important to what they do. And in other tasks that are meant to really show how fast is it, they found a hundred million-fold speed up over the best computer they could buy from anyone else. - How big is such a quantum computer? - They're almost all about the same size, not because the computer is big, but because the cooling apparatus and the shielding from magnetic flux is high. So if you think about a refrigerator size, slightly bigger, like two refrigerators, the actual computer is just on a little silicon chip that's as small as any other silicon chip. It's just cool to literally 500 times colder than the most remote part of outer space. I mean, like a few millikelvin above absolute zero, which is really cold. - So to put the speed or power in perspective, could you please describe a graph that I've seen you present, which I believe might start with, is it 2002? - Right. - And it looks like it progresses up to the right, almost at a 45-degree angle, not that the angle is that important. I mean, it depends on what's on the axis. But could you describe what these different-- - What these points are.

Rose’s Law. (15:10)

- Points represent? - It's something I've affectionately called Rose's Law, with a sort of homage to Moore's Law, because Moore's Law is actually named by Carver Mead. It wasn't Gordon Moore himself who labeled his law Moore's Law, and nor did Geordie Rose, the founder of D-Wave. But when I was first speaking with him in 2002, having just read David Deutsch's book, he had produced a single qubit. They're called qubits for like quantum bits, so I'll just use the acronym qubit. He had manufactured one of these and tested and characterized it and had sent to the manufacturing facility-- - That was the qubit the entire computer? - Yeah, so think of it as, by loose analogy, like a memory array. It would be like a one-bit memory array, but that's a really powerful memory array. So when you go from one to two, you're now able to explore all possibilities of two to the second power, so four memory states. If you have three qubits, you could simultaneously explore eight possible memory states, if you have four or 16 and so forth. - Right. - It's a doubling. So as you add a single qubit, you've roughly, with some hand-waving, doubled the power of your computer, roughly speaking, on the order of a two to the n phenomenon. So if you were to add one new qubit every year, which he just stated, so coming to like, where did this graph come from? He just stated in 2002, I think we're gonna double the number of qubits in a functional quantum computer every year in perpetuity. And so I had to ask, is that just 'cause Gordon Morse did something that sounds kind of similar? And we had a conversation, I don't remember being particularly persuaded other than it's a semi-conductor process, it takes roughly a year to digest the prior generation. Yeah, why shouldn't we be able to do this? And sure enough, that's held till today, right? So that's been 16 years of doublings. The way the graph gets interesting though is, as with Moore's law, it comes out of nowhere. So Moore's law, you could actually trace back hundreds of years, arguably, that our capacity to compute as a species has been doubling roughly every year since we started to compute, since we had any kind of abacus. I mean, it's kind of weird how this has been growing in the semi-conductor industry, it's just the modern version of that. On a quantum computer, that doubling starts to reach thresholds where you can do things that you couldn't do with any computer on earth. So on this graph, if you look forward, and here's where there's been a little bit of a time delay, by the way, just a full disclosure, where the power of some of these computers, there's been a bit of overhead, there's been a bit of setup and readout times, there's been a bit of noise, and other things that have made the power of it not, it still scales like the original curve, like that 40-degree angle you're painting in people's minds, but the power that that represents is, imagine you have to go like a little, maybe two or four times bigger to hit some of these thresholds. But unless something falls off the rails, we will soon, in like the next couple of years, have computers that can outperform any computer on earth, then you give it another couple years, and it would outperform all computers that could ever be built on earth, even if you used the entire matter of the earth to build them. And then, this is where David Deutsch started to run this thought process out, give it another couple years, you would outperform all computers that could possibly be built if you used the entire matter of the universe as at your disposal to build in the best possible computer any human could ever design, and you gave it the length of the universe and time to work on a problem, it still couldn't solve these problems, and the quantum computer could in due course, like in less than an hour. That's when, if your head hasn't already drilled out of your ears, it just really explodes, like pulp. And there's places where nature gives you a peek into its wonders, right? As a scientist or engineer, we get these in almost any field of exploration, whether it's inner space of quantum physics or outer space in the frontiers of the unknown. And here's one of those examples that just opens your eyes to how little we know, in that you'll sometimes see this, maybe in an experiment, I'll give an example of one that David Deutsch also likes, that some people might remember from their high school physics. If you have two slits, two very narrow slits, and you shine light through them, you get this diffraction pattern on a screen on the following side of the table. And that's always been something we learned at the bulk statistical physics of a lot of photons, a lot of light going and interfering with each other, these interference patterns. Well, what's fascinating is if you send single photons at a time, they will shoot through, and if you just tally up the statistics, they'll end up creating a distribution pattern just as if it were many photons interacting. So the whole explanation to wave theory of light is that waves interact with each other, and that's what creates this pattern, this ripple pattern on the other side. But there's no interaction when you're single photon at a time. It's not interacting with anything other than its sister photon in a parallel universe. Right? And David Deutsch is like, "Well, that's obviously the explanation "that makes all of this work "other than it bends people's minds." And so the two schools of thought are, "That's the answer," or, "I don't wanna talk about it." - What is David's background? Is he-- - He's a quantum physicist. Oh, he's a physicist. - He's a physicist. - Yeah, yeah. - Just to make sure. - Yes, absolutely. No, he knows a lot of what he's talking about. - He's not a cop-lick. - Way more than me, yes. - All right. - Yes, he's not a charlatan. - Yeah. - Yeah. - How do you even make sense of that?

Quantum computer usefulness (19:50)

I mean, in terms of considering the implications? Because this isn't, we're not talking about thousands of years away, potentially. I mean, this is in the relatively near-term future. What are the implications of that? - So the key to answering that question is, well, what are these computers good for? - Right. - And either good news or bad news, depending on your point of view, is they're very hard to program, at least historically speaking. Years would go by between major advances in the software, if you will, the algorithms that one can run on a quantum computer and do anything useful. - Right. - There was something called Shor's algorithm that came out a few years back that said, "Hey, you can actually factor integers," meaning break the number 15 into its prime factors. Three times five is 15. So if I give you 15, tell me what the prime factors are. And if the number's small, we can kinda work our way randomly through it, through either exhaustive search or some heuristic, but we don't really have a mathematical way to get the answer. And a quantum computer now can just give you the answer, which it turns out would break most of cryptography. Any of these mathematical asymmetries are at the core of public-key crypto. So that's kinda worrisome. What it's useful for beyond something that Spook should be interested in is, we literally also in a renaissance of software discovery. So things that really seem to be coming to the top of near-term opportunities are quantum chemistry and deep learning or machine learning, both of which are very interesting. Quantum chemistry is quite simply predicting accurately what a small molecule will do.

Quantum chemistry (21:06)

It turns out if you use a normal computer and you try to solve Schrodinger's equations and do what's called the bottoms-up ab initio model, like what does a water molecule do? What does aspirin do? How does it behave? You can't actually model this. It just computationally grinds to a halt. A quantum computer could do this almost on a one-to-one mapping. So a quantum computer of about the same complexity as H2O and all of its electrons is about the size of a computer you'd need to model it perfectly. Like when does it freeze? What about its phase transitions? All these weird properties of water that we take for granted that really don't come from the physics. We learn this in chemistry, but you don't learn it in physics because the math, it's computationally too complex. More interesting to me personally, by the way, I first invested in quantum computing for quantum chemistry. That was the reason I got excited about this, is we'd be able to design drugs more quickly, figure out, let's give you an example. Let's say you have some new H1N1 virus and you're trying to figure out how can I design a molecule that would dock to this virus at a particular place that like if I could only attach there chemically, I could kill it. Well, that's very hard to do. Very easy to state, very hard to solve. So you can test a drug, but you can't have an issue of just design it out of scratch. And that's what these hopefully will be able to do soon, rapidly accelerate drug design. The other area that has enormously wide applicability is in deep learning.

Deep learning. (22:22)

And we can talk more about that field later, but generally speaking, building little brains that can learn something very quickly. And like, let's say it's pattern recognition or image recognition for any number of applications and do that much better. So that's why perhaps it's not surprising Google's been the primary customer of quantum computers for the last 10 years, is they use deep learning everywhere. - So we're gonna, I'm sure get to deep learning. I shouldn't be so confident. Well, like 75 pages of notes. - We gotta come back to it. - 75 pages of notes. - Sure. - I will do my best to come back to deep learning folks. I'm not yet a deep learner, but clearly with all the notes I have. - Or neural networks, that's the same thing, basically. - Okay, all right. So this is-- - If you wanna come back to that. - Great, all right. So I'll put this-- - Synonymous. - On my mysterious pad here. But question that is tangentially related, but since you mentioned entanglement, this is something that's become very interesting to me.

Quantum entanglement. (23:15)

As a non-physicist, of course, my ability to dig into it is limited. But I heard, I believe it was Radiolab, I could be making that up, but an episode of Radiolab where they talked about some of the experimental design and results of using lasers to impact entangled, suppose it would be atoms, does that sound right? Or maybe subatomic particles. - They can create what's called the Bose-Einstein condensate with lasers, in a sense trapping light and making it stop or doing really bizarre things. - Yeah, so they were looking at entanglement across not just distances within a room, but-- - I think they sent it in a loop at CERN or in Europe. - Yeah, 60, 70, 80 miles. - That's right. - And so I started wondering to myself, again, as a professional amateur who's not terribly good at any one thing, I was like, well, wait a second. If you were to ask David Deutsch, you might just laugh this off as a ridiculous question, but if the Big Bang theory, or if the Big Bang happened, as many people imagine it to have happened, or think of it to have happened, is it possible that everything that we can see, hear, feel, touch is entangled? Like is there the possibility that everything is entangled? Anyway, that's a question that I think about, but I've never asked a physicist. - I'm not sure, not in the, well, my gut is not in the powerful way that the quantum computer takes advantage of it, but there is the possibility of, well, first off, I mean, just for those who don't know the experiment you're referring to, they sent two entangled photons down sort of opposing fiber optic rings, and then when they were far apart from each other, like miles apart from each other, they would observe one and notice that the other resolved its state instantaneously at the same time. So in other words, this notion of quantum indeterminacy, that you don't know whether it's a one or a zero or somewhere in between until you look at it, the moment you look at it, it changes the state. It's this really both strange and provocative notion of the quantum physics. And literally, if you look at one of them over, let's say on the left field, you know, miles away, it'll instantaneously resolve the other one as well, as if they were a single unit. And in fact, you can't imagine information passing between them because it's faster than the speed of light that this is like, it's at the exact same moment that these things resolve. - Oh, I'm gonna get out of my depth on so many subjects.

Theoretical vs. practical application (25:37)

- I think the main takeaway that fascinated me and maybe hopefully every listener is we are just beginning to scratch the surface of understanding what these phenomena are about and taking advantage of them in any useful way, right? So usually quantum physicists literally for, you know, since the beginning of the field have been more theoretical than experimental, more theoretical than useful, you know, might you say. And I think the potential crashing of this onto business shores is potentially upon us where again, when we talk about, let's say the power of deep learning, if you could build an artificial intelligence broadly defined of any kind, a simple one that plays games or a simple one that recognizes cancer in pathology slides or recognizes anything in an X-ray in medical imaging sense, if you can do that better than anyone else on earth, that's a business opportunity. And that capability might start to lend itself to those who have the cutting edge of computation. And in the past, anyone could buy a computer and catch up with, you know, someone who has another computer, it was a commodity, right? I just, I'll just go buy some more computers myself. But what if the practitioners of this sort of field are so esoteric and limited that there's only a handful of companies that know how to do powerful computing? That's kind of a worrisome future potentially. - So not to dedicate too much time to worrisome futures, but what do you see as the most likely existential or greatest existential risks to humans, animals, people, things on this planet?

Bridging the accelerating rich-poor gap (26:54)

- Oh, I think it's gonna be very different for humans, animals, and things. - Let's talk about humans. - Yeah, because I think there's all kinds of things we can do to hurt ourselves that nature won't have any problem with. And we'll just march right along the cockroaches, we'll still be out there for many years. - Since my cockroach audience is still very small, we'll go with humans. - They're incredible creatures. They're gonna last through a lot. So I worry about the way in which cultural evolution is, while it's progressing, it's not progressing fast enough. And we as a society are going through more rapid and gut-wrenching change of various sorts that we may or may not be prepared to handle. So for example, we may be in the midst, I would argue, of a ever-accelerating rich-poor gap that politicians and policymakers just don't have their head around and could lead to a future of abundance, as Peter Diamandis writes about, where everything's great because physical things are so inexpensive that even the poorest of the poor can live like kings of just a few years prior. But I think the cultural, in a sense, setup for this is not necessarily right, which is we don't have a lot of people thinking about it, whether it's how will, let's say 10 years from now, 20 years from now, we provide for basic human needs globally. Is it gonna be normal capitalism and a democracy? Is that gonna work just fine for everyone? Or will there be some that are horribly left behind? And I think social unrest is something that worries me more and more, I guess, in a succinct way. There are other things.

Protecting Earth from asteroids (28:33)

I've been involved with a nonprofit looking for asteroid defense. That's an existential threat of another kind that's easily addressed. I mean, for less than $400 million, you could take that one off the table. So hopefully that will happen. Pandemic flu or bioterrorism-- - Just to pause for a second. So taken off the table by somehow destroying the-- - No, the key is just detecting them long before they hit Earth. So unlike the movies Armageddon or Deep Impact, you don't wanna wait till final approach to try to do anything about it. - Seems like a good policy. - Breaking it apart, turns a bolt into a shotgun shell, it's way too late. What you wanna do, and it's actually, this is what's so interesting, is for the first time ever, we can put satellites up that have these infrared sensors that can detect these objects at great distances and track them, and we have enough computational power to, from a couple of, well, from three observation points, model out the N-body problem of what will the next 100 years of this object's orbit look like, and will it hit Earth at any point in the next 100 years? So that is a computationally complex thing we can do today. So putting up one of those satellites in a near-Venus orbit, looking out to capture all the threats to Earth, we could do today, with less budget than some museums have, right? And the key then is, when you see something that will hit Earth, let's say 50 years from now, or 30 years from now, you just bump it. All you have to do is give it the slightest little delta-V today, and all of its orbits around the sun, by the time it eventually intersects with Earth, it's in a totally different place. And we can computationally know, yeah, just rear-end it by a tiny bit, or hit it head-on by a tiny bit, and then you're done. Right, problem solved. - Wow. - But you need time on your side, that it takes years for that tiny nudge to accumulate enough distance delta that you miss something as big as Earth. - So I interrupted, I think, your segue to bioterrorism.

Synthesizing biological weapons (30:09)

- Yeah, bioterrorism worried me a lot post-9/11, 'cause I realized, looking into it, and from investments I had made, that it's increasingly becoming the case that a small number of people, in fact, an individual with, let's say, a college education in this field, could build weapons of mass destruction. It used to take armies, it used to take despots and fascist leaders of countries, and resources of countries to wield a weapon of mass destruction, to build one, to deploy one. - Using CRISPR gene editing, things like that? - Yeah, exactly. So synthesizing smallpox, weaponizing it, doing something like injecting the interleukin-4 gene, which makes it incredibly deadly in mousepox. Pox viruses affect all organisms that get to a certain concentration level on the planet, so ants, deer, anything that live in dense areas, chicken pox, develop a unique pox virus for that thing. It's kind of nature's way of telling you, there's way too many of you people on this planet, the nerd, they can be bioengineered like crazy. And this worried me, because when I spoke to people in various government agencies who spend their time modeling and doing red team simulations of bioterrorism outbreaks, their only answer at the time was, well, we hope they wouldn't do this. Just kind of like a leap of faith, that this is such a horrible thing to wield, that people would stop short. And at the time, that gave me no comfort. And as time passes, I actually think there is an element of truth to that. It's not the kind of thing that a typical terrorist cell can get someone fired up about, which is, it is a weird thing, even within the worst, whatever we put in quote marks, worst parts of societal troublemakers, if you will, on the planet, where this isn't a place they tend to go. Flying a plane in a building is a more natural vector of getting attention for your mission and getting someone to volunteer for the duty than saying, well, I'm gonna go kill a bunch of innocent people with a contagious agent. It's kind of a weird cross product of threat. - How did you convince yourself of that? - Well, I haven't, I worry about it too. - Yeah, it's on my top three list of worries. - What are the others? - Let's see, so inequality/unrest, bioterrorism, oh shoot, what is my other one? Well, climate change, of course, oh my God, climate change.

Coping with climate change through hibernation? (32:07)

The thing about climate change that worries me is the things I didn't know. I'll give one example. Last week, I learned of a new thing that I really didn't learn to worry about until last week, which is, of all places, out of NASA Ames, the former director was telling me they'd been doing these interesting studies trying to figure out how can we induce hibernation in mammals, which for interstellar travel would be great. You know, in the movies, the humans somehow go into hibernation mode, right, in all the movies we see. And they were doing studies with rats, and they could actually get rats to hibernate for two days at a time by exposing the hydrogen sulfide. And that immediately led me to ask, well, wait, why is that adaptive? Why would we have this sort of latent pathway that really doesn't seem useful for anything that puts rats to sleep for two days at a time, and they would die if it was longer than that. And it turned out, back, one of the major extinction events, and I'll try to be more concise here than I might otherwise be, there was a major volcanic outburst. It led to major climate change, and the polar ice caps melted, a greenhouse effect. And the problem with the ice caps melting wasn't that sea levels rose. That just affects Bangladesh, and Miami, but it doesn't take out humanity if sea levels rise. The thing that could take out humanity is that the ocean currents stop going, and part of that was driven by freshwater melt off the poles. So potentially long before the poles are completely gone, or perhaps completely unrelated to temperature change, if the ocean stops circulating, you get this complete dead zones, where organisms depend on the circulation of nutrients to survive, and basically purple and brown bacteria took over, and they are these hydrogen sulfide bacteria. So you'd have these waves, usually coupled up to two days at a time, of just literally lethal gases sweeping across the landscape that the survivors learn how to hibernate through. So in a long-winded way, the thing that was both interesting, like maybe here's a hint of how we can induce hibernation in mammals like humans, but also a reminder that we've had climate change many times on this planet, and really bad things can happen that have nothing to do with carbon, or methane, or all the things we're focused on. It could be the hydrogen sulfide gas that kills us, which is the rotten smell of eggs. You'll see, you know, it's nasty stuff. - On the social unrest piece, just because I know there are many people out listening who will be wondering this, what do you see as the preventative steps, if any, that can be taken to mitigate that risk?

Mitigating social unrest (34:14)

- Yeah, so first I was looking at like, well, does it feel like it's self-correcting? Is it self-rectifying? Is there something that's a natural governing feedback loop or negative feedback loop that says, well, the rich get richer? Is there something that naturally makes that not continue further? And unfortunately, there's a lot of, quote, positive feedback loops, not in the sort of normative sense, but in just the regulatory sense of it, it just is a runaway thing, right? Like runaway climate change. And that is, you can get, well, sir, first off, is every business becomes an information business over time. Like what I mean by that is if the basis of competition, why is company A winning over company B? Is it the way they process information? Is it a software layer to their business? That I think is rippling through every part of industry, whether it's the aerospace industry, the automotive industry, agriculture, right? It's not, oh, he worked harder. He was an artisan in his field. That's why he's a better farmer, or she. It's, oh, no, he's got better gene scripts from Monsanto or whoever, and like the basis of competition in agriculture has moved to information tech. As every industry goes that way, those industries will start to look more like, you know, where you see Google and Facebook, a winner take all kind of dynamic, where between firms, you have very few winners, and within firms, you have very few winners. So at every fractal scale, it's kind of like a winner take all. There's a few people within these firms that garner most of the wealth, and there's few companies that garner most of the wealth in each industry. Now, that's perhaps, so that trend is somewhat negative, and that technology takes over more and more, it innervates more and more of the economy, it subsumes or eats the world, if you will. That, I think, will be a side effect. One other side effect that's negative is people sometimes reject modernity when they can't keep up. Like you sometimes subscribe to a different belief system, not science and math is the progress vector of humanity. It's like, I'm gonna reject science. I'm gonna reject math, and there's entire countries that are taking this stance, which is scary, because they'll fall farther and farther behind, perhaps with an inability to catch up to modernity when and if they choose to. So that worries me. The only current, quote, negative feedback loop, the thing that prevents wealth from going completely crazy, is that luckily, and I think maybe understandably, the wealthiest tech entrepreneurs tend not to live like rock stars, or rap stars in LA. They tend to give back. And a simple explanation for me, having seen many of these people before they made billions of dollars and after, is that if you've made billions of dollars in, let's say, under five years, you don't tend to ascribe that to your incredible hard work and superior intelligence, right? It is a farce, right, to hold onto the belief that I'm better than others, that's why I'm a billionaire. And so they give back, like, in droves, like incredible acts of philanthropy. And so right now, the philanthropy, Governor, is the one thing I see that's at least a positive that says, well, maybe this actually will allow people like Gates and others to take on multi-year quests, like eradicating malaria or polio, or right now polio and next malaria, in a way that governments can't even take on, right? You have projects that exceed the budget of the GDP of nations, you have projects that exceed the lifespan of any politician, and luckily, this is what these people are choosing to do, rather than just show off, right? And so I'm really happy about that. And I'm trying to live my life that way as well. So the question though going forward is, there's a lot of debates about basic income, universal basic income, and experiments that are trying to get funded to see if it works the way people think it might. I think there could be all kinds of experiments in almost corporate health plans, writ large. So right now, most companies with more than 1,000 employees will manage the health plan of their employees. It's cheaper than going to a third party. Like, I will actually pay for your healthcare because, I mean, paying some third party, you know, they're just making money off that. And I've got enough critical mass with 1,000 employees that that makes sense. Well, imagine food, shelter, clothing, and healthcare are all equally cheap, meaning everything costs a dollar a pound in the world, that's a physical thing. That's where we're heading in the end point. All physical things should be the same cost. Bag of potatoes, dollar a pound, bag of chips, dollar a pound. Why is that? Because, and then what you'll pay for is the software, the intellectual property, the thing that in certain places could lock up, then yeah, maybe that Ferrari costs more 'cause it's the design, not the materials. But it's just manufacturing methods are all converging, whether you think of it as additive manufacturing or just traditional manufacturing, that stuff is not the rare commodity you pay for intellectual content like entertainment and software. It's like, that's what all future economies will based on, and physical stuff is all about the same. What are the means of manufacture? Well, we're gonna grow things, I think, increasingly in the future. I think we're gonna grow with algae and other things, chemicals, so we think about sheer metric tons of stuff. Liquid chemicals is a big part of it, and we got almost all that 90 plus percent from oil today in the petrochemical economy. It's all gonna shift to renewables, and so that sort of manufacturing stuff, like the stuff that goes into plastics, which is more and more of the physical world that we're in, obviously metals will still come from, unfortunately, metal sources, but I think we'll shift to carbon and other kinds of materials increasingly for structural stuff. This is potentially in the nanotech/carbon economy of the future that building things out of carbon nanotube-like structures and meshes is just much lighter materials, sort of effective, just efficient way of doing things. So we can look to nature, and how does a spider, silk thread outperform almost any other modern material, like there are startups that are building, synthetic silk now with these old nanomachines that reproduce what the spinneret does in a spider. So across, but coming back to just this inequality point in the corporate path potentially there, or it could be like a Peace Corps equivalent that says, you know, if you work for X number of years, you get healthcare in theory for a longer period of time, right, and why couldn't that start to subsume the way some companies already provide lunch for free? Why couldn't, in a sense, basic food shelter clothing and healthcare be provided for free? And the healthcare part, by the way, right now, is a huge part of the economy, but it shouldn't be, right? I think we're also, and this is something I want to invest in, we're going to find a way to make the information search of health free, so we don't have to pay for the diagnosis. And I can't imagine a future where knowing what I need to do to make myself healthy would be something I'd pay for. The actual doing, if it involves surgery, maybe. The pills, they should all be a dollar a pound, the physical thing. And that future, I think, will be incredibly enabling for changing a society to a stable one, where you don't fear for the health of your children or their ability to live, then you could have almost like a renaissance, where you pursue the things that are meaningful to you, whether it's poetry or science or what have you, meaningful work online. People do this all the time. We spend a ridiculous amount of our time on things that aren't paid, right, but are meaningful to us. And that, I think, increasingly is what the world will look like in the future. Meaningful work and contributions, not a job, in the traditional sense. - If the pills are a dollar a pound, how do you maintain the ability to develop and innovate those drugs?

Early Career And Investment Insights

The problem of affordable life-saving drugs (41:00)

Is it just because the computational power becomes so inexpensive that you have then competitors to the current incumbents who are, of course, highly incentivized to protect? - Exactly, it's the long run. Because you can imagine any current phase or even long term, whether you call it transition phase or just this is how the new ones come to market, is you have to reward, of course, that effort. To the extent that effort is still as expensive as it is today, you need to recoup it, right? And that would be an intellectual property question. It's almost, again, like the software of it. The generic manufacturers know how to make the drug, but for law around intellectual property, that it costs more. So the physical manufacturing is still gonna be a dollar a pound. Now the question is, is it priced as such? And so in my model of this, you'd start with the generics and have this massive distribution channel. Like if you want to reach a billion people, you could sign onto this platform for the poorest of the poor and reach a billion people at some sort of reasonable cost position for a generic. But I think the cost of discovery will also come down back to the computational and quantum chemistry side so that it doesn't need to take so long and be so expensive. And right now you have an FDA regulatory system that's a bit archaic in that regard, where they aren't quite set up yet and they're trying to transition, but they're slow at this, into a world where you have personalized medicine and a world where my medicine is different than yours and therefore the clinical trial concept really changes. - So we've been talking mostly current, or I say present and future tense.

Time at Stanford (42:28)

I want to go back to that two and a half years undergrad. How does such a thing happen? I mean, how is that possible? - It's interesting. I took it as a challenge. When I started at college, I was going to Stanford and I realized it was expensive and my folks are immigrants from Estonia and I kind of found it difficult and we were middle-class people at the time, so I didn't get financial aid. And I was looking at this, I'm like, "Oh, you know, this costs a lot." I just felt guilt. So I looked at the various rules for graduation and it felt like a simple system of equations, like this plus that has to equal this. I actually boiled it down to, "Oh, I see. They're just trying to get four years of tuition out of you." So where can I explore the corner cases? And so I came in with the maximum number of AP credits. So it actually goes back to my high school, St. Mark's in Dallas, that incredibly well prepared me for college. So I took the maximum number of AP units that I could, but of course, universities limit, not surprisingly, how much that applies. I also took a couple of summer classes that I could transfer in from another school. They'd have a certain number you could do. I maxed that out one summer. While I was doing summer jobs at HPS, I took night classes. But most of all, I learned a trick from the grad students. This is the key answer, actually. By the time you get to be a grad student, you realize that you're limited to something like nine units a quarter and that's kind of limiting. If you take five-unit classes, well, shoot, you know, you take a class and a half. So what they realized is you can sign up for a class for less units than it's listed, just not more. So the checksum on the computer algorithm was not, did you say it's a five-unit class or say it's six and it's only five, it's, you know, is it that or less? So you can just say it's a, even a zero-unit class or one, you can make it whatever you want. So you're not taking more than 20 units a quarter. So you meet that algorithm, yet you've got all the prerequisite classes you needed for the next one. You have to map this out early on, right? You have to start freshman year to make this work. Oh, and I had to get a physics teacher to let me take a class and a double teacher as sort of against the prereqs. So they're saying, "Look, I really can do this. Let me try to take your class a year earlier than I should so that I could get the prereq chain going." So there's all these simultaneous equations you have to solve. But the signing up for more classes was the key. There was like one winner quarter where I took the equivalent of eight classes where you'd normally take a load of four that made that possible. - So when did, if it did, when did the budgeting stop being a concern?

Masters program hacks (44:45)

Because you then went on to continue your schooling. - Right, it all flipped completely, like total mode shift when I started my master's program and I became a research assistant 'cause that paid for school. So the moment-- - So this was at HP. - Well, I was working summer at HP, but no, I started a master's in electrical engineering. So it was still at Stanford. I was a research assistant for Professor Hennessy who went on to do amazing things there and was an entrepreneur himself at one point. And I shifted gears. I didn't want to leave school. I mean, like going through two and a half years, the problem is like, wow, I kind of missed out on a lot of social life and like living. And so I basically at that point stretched out and tried to stay as long as I could. - Got a balloon payment. - It's kind of funny how instead of change, now I want to stay, I don't want to leave, right? And I found a way to be in the freshman dorms as a grad student, which was awesome as a computer coordinator there, which meant I kept the computers running and kept the paper and the printers, but it meant I could have sort of freshman dorm life all over again as a grad student. And that was fun. - So if we look then at your master's, and I suppose it would have been, maybe it was simultaneous, but if, or after, you could tell us, the MBA. - Oh, that came later. - That came later. So the MBA, why did you decide to get an MBA? And would you do it again? Why or why not? - A lot of folks who I knew and know are asking that same question. And I think it's a challenge a lot of higher ed is facing, which is, is this a vocational thing? Is this, I mean, one unusual thing about business school, it's the only educational program I know of where everyone comes in with prior work experience. Even law school and med school and what have you, you just go straight in from undergrad. And so it's got a very different kind of feel to it that way. And people might ask, especially when there's something like a dot-com boom going on in the '90s, do I want to step out for a couple of years from the economy and miss maybe that window, that opportunity that might be so ripe? So the main reason I went is networking, really, to expand the sort of, and to learn, frankly. But the networking came first to mind to meet a bunch of people who've come from all kinds of different backgrounds that I could learn from, not only at school but throughout my life. And one of the sub points on that is, for example, pretty basic questions like what do I want to do in my life? I had bounced around from engineering to management consulting prior to business school and thought, well, from what I know today, maybe I want to go to product marketing. I thought that's what I wanted to do. But I don't know. I don't know anyone who's done that. And well, if I go to business school, I mean, no matter where I look, there's going to be plenty of students who've done that in the past and they're looking to do something new. And so you have all the consultants trying to leave consulting, you have all the iBankers trying to leave iBanking and learn about something new. What better place? - Especially when your employer hoping to leave is paying for it. - Exactly. So that's exactly right. In fact, that's exactly what happened to me. I was financed by my former employer, so I had that sort of safety net. And then when I decided not to go back, I had to pay for all my tuition in one check. - Oh, I was wondering about that. - That was a tough decision. - They don't let that one go. - No, they don't let you go. It's a loan and rightly so. I didn't expect to get a free ride and not go back. But it did raise a barrier to leaving. Oh, the other thing is learning. I mean, I should go, business was not what I went to learn per se. I knew there'd be some classes about business that I thought would be helpful, but I'd done so much at Bain that I kind of had a small business degree already, and I'd taken classes back when I was an undergrad and a grad student prior in accounting and finance. So I'd really taken a lot of, again, the core courses. I placed out of every core course at business school too and went right into sort of the electives and the more interesting classes. But I also knew that it was an opportunity to take classes in other departments, to brush up on actually molecular simulation of all things. And one of the classes I took was on modeling quantum mechanical properties of materials. Like, you normally don't take a class like that. And that really all played out.

How did Steve enter the world of investing? (48:39)

So it gave me, so did it do what I expected? In a way it did. I didn't know venture capital existed. When I grew up in Texas, I'd heard the term. I never met a venture capitalist, never knew anything about them, wouldn't know how to reach one. No idea, right? I mean, I grew up, there wasn't the internet, so I literally would not know how to reach one. They're not in the phone book. There's no way to find them. They really aren't putting up billboards or advertising in any way. So the entire transition to venture occurred because of people I met there. And I learned a lot. - Good location for it too. - That's true, in the middle of Silicon Valley. That's true, yeah. And that was the only school I applied to, by the way. If you think about it, do you wanna go to business school? I did not apply to any other school because there was no other school that would have met that goal. And also I learned a lot, and the network, back to the network, almost every investment I made, I think it was almost, for the first year or two out of business school, and that was a lot 'cause it was the middle of the dot com boom for me, had some business school connection. It was either literally the entrepreneurs were from business school, or it was sent to me by a professor from that business school. For the first year, that's how I jump-started everything I did in animal. - So my madness slash method is usually not chronological, so we're gonna zoom out a little bit. What mistakes do you see otherwise very smart venture capitalists making?

Common investing mistakes (49:53)

Are there any patterns? Are there any particular types of mistakes? Could be investors, broadly speaking. - Oh my God, tons. All over the place. And to be fair, I'll try to drop in and mention when I made those same mistakes, so by no means I'm trying to judge as if I know better. But two that jump to mind, one is way too many seem to be loss-avoidant or fearful, and I'll elaborate that in a moment. But the other one that jumps to mind equally is they think they've hit upon the only formula for success. And yeah, that has many different levels at which that's worrisome. So the first one, this notion of being fear-driven, I've come across so many investors who will say something like, well, we have a strategy to try not to lose any company, as if that's like, we're in the trenches, every company will succeed. And if you've just been at this game for a few decades, you'll realize that's just folly. The earlier you go, the higher your death rate's going to be as a startup. So the majority will fail, just give them time. And that sad reality took a while to sink in for some, but until it does, you're going to be very timid in your investing. So most investors I see just let all the biggest home runs pass them by. Almost every term sheet I've written to a company that's turned out to be a spectacular home run, I had no competition at the time of the series. - No kidding. - Like, nobody else would invest in the company. - What were the reasons for not investing? - Yeah, it's crazy. It's way too early. It's a science project. - No traction. - Yeah, there's no product. I mean, so first off, almost everything I'm doing, there's no product, no customer yet. It's an idea, it's in prototype stage of a development, or there's no even prototype yet. Or they just don't agree the world is going to change in this way. So, and in often cases, conventional wisdom would support their point of view. Like, let's not invest in any automotive company, 'cause every investment since Henry Ford has failed, like 100% of them, they're just roadkill, I mean, scattered on the highway. And there's been, by the way, many, many startups funded well over $10 million, so like, decades ago, that's a lot of money, in the automotive sector, all of which have failed. Many in batteries, many in solar, I mean, just scores. I mean, maybe hundreds of companies have failed. So when you've, let's say, lost four times in a row, you just give up on the category. So sometimes it's the more experienced, 'cause those investors are like, "Well, that whole sector, I'm just gonna steer clear of it, "'cause I have too many scar tissues." Nah, they're... But that's not really the thing I'm talking about. When I think about new entrants to the venture business, people who you would think would take a strategy of differentiating myself from my peers, like having a basic strategy, let's say, that say, "Why would an entrepreneur want to work with me "versus all the other firms?" And if it's like, "Well, I'm investing in the hot sector," pick whatever it is, digital or consumer internet or social this or blockchain that, it's like, "Well, it's the hot thing." Well, yeah, but there's also 100 other people who have the exact same idea you just did, it's the hot thing. Like, why are you different? And there's like, no answer, right? So this lack of strategic thinking about a, and also lack of thinking of a long-term strategy, like, okay, whatever you're doing today, is that gonna work 10 years? No, whatever that strategy is. And I don't hear strategy from anyone. Like, okay, here's how I'm gonna stand out over a sustained period of time. Here's how I will, you know, either, and it can be simple things, like, I'll have a niche, I'll only do X, Y, Z, and I'll be known for my niche or my specialty. - What worked for you in the early days when you were just getting started?

Early success (53:13)

- It was, well, first it was a stroke of great luck, which is the dot-com boom, as we now call it, you know, was just starting to happen. And I was ready for that and open-minded enough. So I didn't have the scar tissue, which is, by the way, scar tissue for traditional investors was, if you invested in anything that was like entertainment or media or shrink-wrap software, as they called it, which is low-price software for consumers, that would be the consumer software segment. That was just a horrible place. Games, hits-driven businesses, it still is a horrible segment, is to do non-internet consumer price point stuff. It just, it's a death zone. So they thought the internet was that. They didn't realize it's an entirely different business model, the whole, what we now know around cloud computing, around subscription services, around viral marketing, its potential. None of this was known at the beginning. And if you put it into a prior bucket, it would be, oh, those are bad sectors. So unbelievably, one of the biggest investment opportunities probably the venture industry has ever seen was largely avoided by most venture capital firms. And when I started in 1995, we did about a third of all internet investing industry-wide, like the entire venture industry. And that quickly changed in '86, '87, and excuse me, '96, '97. And when Netscape had its IPO, boom, everything changed 'cause now there was this example of a winner. This pattern will come again in space investing and everything like that. As soon as you have a single winner, then the sheep phenomenon and the herd mentality kicks in. So you have scores of people then investing in the sector after it's had its first win. So to your question, being under the tutelage of Tim Draper to say, hey, actually, let's try to think big. I mean, I credit him for being my mentor into the industry to say, nah, let's think about it the way bankers do. Let's not be fearful. Let's ask the entrepreneur how they're underestimating the market size, right? To think how much bigger might this opportunity be than even the people pitching it are imagining. That's a thought experiment I often like to go through. And there'll be times when, occasional, not often, where I'll be like, wow, you are so underselling your opportunity. 'Cause normally, I'm an entrepreneur trying to sell to the maximum extent possible to predict the largest possible addressable market to think, well, phase one of my business, I do this, then phase two, I take over the world in some way, right? And then to actually try to push them further and then want to invest in them is an interesting adjunct 'cause then you're on the same page. So I credit Tim Draper, I credit the internet, and then most importantly is there was a simple rule I started implementing, and I don't remember when it started.

Entrepreneurship, Tech Industry And Risk Management

An early-stage investing rule (55:26)

It just seemed like the natural thing to do around early-stage investing. So when I thought about this, I was like, okay, most things fail. If they win, they've got to be huge. Okay, check, they should change the world, they should be disruptive. Those are words people use. Well, how would I know if something really is big and disruptive? Like, everyone, every entrepreneur claims it, right? Like, it'd be doing a payment processing thing for back-end whatever, payroll systems. Like, we're going to change the world of payroll, right? Okay, what really is going to make an enormous opportunity is it seemed to me that, A, they're describing an enormous market, but B, here's the killer. No one else has done it before. And so the simple rule I've used without my entire career of investing is I want to invest in things that are unlike anything I've seen before. And there's all kinds of correlates that come out of that. The first is, yeah, you're investing in some unusual things, like D-Wave back in 2002. There were no other quantum computer startups, zero on the planet Earth. There was not a single company claiming to build a quantum computer, big or small, actually for about five years afterwards as well. So that one was like the most extreme, maybe for good reasons. No one was doing it back then. When Hotmail first came, there was nothing like it that we'd seen when I first invested in Skype. There was anything quite like that, the way they did peer-to-peer voiceover IP. And similarly with Tesla and electric vehicles, and I can get to why that one maybe is the most corner case of, well, wait, there are a lot of electric car startups. Why is that one special? We can talk about it. But certainly SpaceX would qualify as well as unique ideas at the time in the startup domain. But the benefit for my career was it has me perpetually searching for the next great technology wave.

Signs of the dotcom crash (56:59)

So just when the dot-com boom was getting to its fevered pitch, I wasn't smart enough. I know that this is the case. I was not smart enough to predict a crash. I know that I wasn't, 'cause I was contributing in writings and other things at that time saying, oh, the boom is just starting. It's gonna go up, up, up, up, right? I believed that, 'cause I just wanted to, that it's gonna keep going and that we wouldn't have a correction. But on the other hand, I was not finding anything unique. I saw four business plans for selling pantyhose on the web, like all we're gonna do is, got venture backed, like three others. Like really, like four business plans to sell pantyhose? Or I'm like, oh my god. - Wait, what does justballs do? - Oh yeah, justballs, venture backed. - Just sells balls. - The name was awesome, we got What do we sell, balls? You want a bat? No, you want a glove? No, we got balls, balls of all kinds. Small balls, big balls, golf balls, tennis balls. - Wait a second, were you a founder? - No. - Okay, just making sure. - But this shows you how absurd it got to say, take the economy and the internet changes everything. We're gonna divide up the economy in weird ways that hasn't been divided up before and make that a business. Like that's when I knew this is crazy and I started investing in nanotechnology. Like total left field shift. And there's a reason I picked that particular sector, but the important point is I didn't keep investing in the internet companies long past their prime. Not because I was smart on when the correction would come, but it was 'cause they weren't unique anymore. There's like every viral marketing idea that I, at the time, that I could find had come. Now to my, so I avoided a lot of pain. We, like if you add up every internet, remember we did so many of them? If you add up every internet company we invested in, that lost money, add them all up, it was less than single deals lost from other firms. Like lost more money than everything we've ever done combined. Because we didn't load up the boat, sort of drink around Kool-Aid too deep in any one of them and we were, every one of them was unique. So there wasn't like this sector risk. So you get diversification for free. By definition, you're diversified in your portfolio. And it had me moving and has me throughout my career, always on the lookout to learn something new, knowing that I'm gonna have to hop to a new sector. Not saying I'm gonna spend my whole life as a semiconductor investor or as a consumer software investor. Because that is so limiting. That might have a good 10 year run. But if you're not continually learning something new at the edges, pivoting from the edges of what you already know to something slightly different, you're gonna be constantly. - Why did you choose nanotechnology? - That was a bit of a mistake. But it was a mistake in retrospect. But it's the only thing I felt I differentially knew better than others. It was harkening back to, which fortunately wasn't that many years prior that I'd been studying some really hard technologies like molecular modeling and chip design. I did some chip design at Hewlett-Packard. So I had enough, as I looked at the venture landscape, differential knowledge there to say, well, there's something I could harken back to that's not the internet. 'Cause the internet, anyone could do at this point. And the angel investors are flooding in. Every banker or consultant's flooding in. It's like the landscape's littered with capital and people investing in that sector. Well, there's nothing going on in nanotech. I had been exploring at the Foresight Institute and a number of other sort of think tank-like conferences that the radical potential this had to revolutionize a bunch of things. And the one part that I think was indicative of what's to come later in my career, it was not really in any way an industry. It isn't a sector. It doesn't describe a company. There's no such thing as a nanotech company, unless you're building tools to service that industry, in a weird way, manufacturing equipment maybe, but not in the attractive sectors. It more was a set of science and technology capabilities that would stripe across many industries. So even today, there'll be companies that I'll meet with and things that were unique from that era will play out. Like, well, the value of simulation on any molecular system. Like, well, how good is your simulation on any physical thing you're building? In general, these questions are process questions. Like, how do you do innovation? How do you do entrepreneurship? That carries through, but that platform technology, which, let me just tell you what I mean by this. Nanotech was like a platform applied in many areas, new ways of doing material science, if you will. Then there's this whole field of synthetic biology. Like, if you can manipulate DNA with CRISPR or other technologies, what are all the things you could do with that capability? And it's very broad. It's not just health and food. And then more recently, deep learning, neural networks, what we might describe as narrow AI, that whole field is widely applicable. I think every company will use it eventually. So again, we can come to that later, but that's like a platform that's not, sure, today there are some quote machine learning companies. All they do is stuff related to machine learning, but much more interesting is all the industries that'll be changed by the use of machine learning, the vertical industries. And so, yeah, to put a cap on it, nanotech, if you look back at it today, well, no, there isn't any nanotech industry. It'd be like saying, well, where's the thermodynamics industry? Well, shit, there isn't one, right? But there sort of is. Like, thermodynamics as a concept, there was a time when actually companies named themselves thermoelectron and, you know, thermetics or all these ones that it's just now subsumed into the fabric of science and engineering. So as a geek, I've always been fascinated. Are there sea changes in basically how we do science and engineering? Maybe that's the simplest way of saying it. And I think today deep learning is the best example that a fundamentally different way of doing engineering. - Say that one more time?

Difficulties of reverse engineering (01:02:15)

- So I think deep learning, or let me just call it machine learning broadly, 'cause there's a bunch of sub branches of this. There's everything from generative design in sort of the Autodesk CAD/CAM sense. It's studying solar automata the way Steve Wolfram does. It's genetic program. - What is solar automata? - These are simple little mathematical construct that just says, if you're gonna draw, oh my God, you're probably gonna want to edit this out of the final thing 'cause it may not relate to anything other than it created this book, "A New Kind of Science," and really a series of epiphanies for Wolfram and others that the world is really interesting when you look at iterative algorithms applied millions and billions of times. So, cellular automata is just, imagine you start with a random dot or two, and then the next line-- - Automata, like automaton, but with automaton. - Yeah, and it sort of unveils, so you have this little simple rule, almost like a Turing machine that says, I'm just gonna go left to right and look at the dots above me. And if the dot above me, I'll look at the three dots above me, one directly above me, left and to the right. And based on all possibilities of those three dots, which is two to the third power possibilities, I'll have either a dot or not a dot here. And so, you would think that such a simple rule that just says, look at the three dots, and there's literally only 16 possible things that I'm gonna, conditions that I could be seeing up there. I'll have some other, I'll do some something. In most cases, it's very boring. It's just like the whole thing's black, or it's got like a nice pattern of triangles. But in a few cases, like rule 31, it unpacks into this incredible complexity that is not repeating, and there's no way to jump to let's say the 40th or the 50th, the 100th layer of this unfolding. You have to run the experiment. And the reason I find this so philosophically interesting is this is the same thing in evolution. It's the same thing in neural networks. It's the same thing in all these new engineering modalities where you can't mathematically get a shortcut to the answer. You actually have to just run this little algorithm. Oh no, no, no, run again. So you can't, like for example, you can't reverse evolve. You can't figure out where did we come from in any just direct way. It's sort of lost. You can run the tape forward, you can't run it backwards. You can't do a mathematical shortcut across it. And so an example of why this is a thought experiment is important is whenever you're developing these neural networks, whenever you're training, let's say these little AIs, and I think this is the path to AI in general, so it's important that this is how it works. You can't understand the thing you've made, nor can you predict as you train them further and further what you're going to get. There's a bit of discovery, emergence, if you will. It's kind of like raising a teenager or parenting more than it is programming. You can learn about the process of creation. Like I know how to make a teenager, but I can't tell you exactly how it all works, right? And I certainly can't go in there after I'm done and tweak a few neurons to make them smarter or French speaking or whatever. It's like, no, that's a really weird artifact that works really powerfully, but it's not purposeful design. It doesn't do what I tell it to do exactly. It can learn to do what I train it to do, but with some edge cases, it's a little out of control. And that's what I think the AIs of the future will look like. So I can come back to it if you want to talk about AI and deep learning, but I just, you asked about cellular automata and the process learning. The key to this question you started with is engineering. So the thing that I wanted to say is I think deep learning slash machine intelligence is the biggest advance in how we can do engineering. So specifically engineering since the scientific method itself. So way back when engineering might've been random, like I think astrology is true, I think this is true. And then you have a scientific method, you list the method of compounding knowledge over time. This is a different way of, in a sense, growing solutions to problems instead of purposely designing them. You can build things that exceed human understanding. We're doing this all over the place. In molecular engineering, in software design, in a variety of fields, we have sort of reached the limit in many cases of what a human, any human, or even group of humans, can put their heads together and design. And now we can push way past that and build things beyond our own understanding, which is pretty powerful. - Yeah, could you define, just revisit, you might've already done it indirectly, but the deep learning and neural networks, I guess I have sort of an approximate equal sign here.

Deep learning and neural networks (01:06:08)

I'm not sure if they have the same- - They're synonymous. In the '80s, they were called neural networks and deep learning. There's a reason the word deep came in. Well, first you want a new name. When something kind of came and went, let's pass a couple of decades ago, 'cause I studied neural networks back in the '80s, you know, I have to give it a new moniker, but there is a reason deep in the sense of more layers. So what do they have in common? And in fact, neural networks, I think, could be a more generic term for all this. It's inspired by the brain. It's a way of simulating a brain-like subset. So not the whole brain, but imagine you were to take a little tiny chunk of your brain, a cortical column or some area, and say, well, what's really going on? Well, you have cells that connect to a bunch of others. In our brain, it's usually a fan out of 1,000 or so to 10,000 connections from each one. So a huge fan out. Each cell connects to a bunch of others. And when one fires, it sort of goes down the dendrite and the little synapse fires and it triggers another one. We all have some vague sense of, okay, neurons are in our brain and they are wired together and they fire together. So now if you want to simulate one of those in a very simplistic way, in a way that you, like imagine the programmers back in the '80s when they had pretty not very powerful computers. Well, how could you make a computer-like brain? Well, we don't need all that complexity. We don't need all the details of ion channels and synapses and all the neurotransmitter chemicals that are an artifact of our biology. What really is the essence of what's going on here? And the essence is something activates, it fires, it's connected in a network to some others, and if there's enough inputs that are firing beyond a threshold, then downstream neuron will fire too. So the simple idea is, to recap, is neurons fire, they're wired to other ones, you sum up all your inputs, like everything that's connected on the input, there's like thousands of inputs, and if it crosses some threshold, then you fire. That's it. And then you just layer on tons of these. And so the deep learning is having more and more of these layers instead of just like one or two or three layers, having scores of these layers. And a variety of other algorithmic advances. But really the biggest breakthrough has been that we have a lot of data today that we didn't have back in the '80s, from the internet, from Mechanical Turk, you name it, all kinds of data sets to train on. Like if you wanted pictures of cats with the label, that's a cat, that's a dog. I mean, that's obvious today. We take it for granted, like, oh, of course, you want a million of those, you want a billion? How many pictures of cats do you want, right? In the '80s, good luck, you could spend your whole career trying to get a good data set to train these neural networks with. Plus we didn't have digital cameras, I mean, it's crazy. You think, how little data we had in the '80s. Okay, so data's the first, the other is GPUs from Nvidia. They started about 10 years ago, it was a side project in scientific computing, realizing-- - GPUs, graphic processing units. - Graphic processing units, right, so any gamer would be like, I want the latest to play my video games to do all these polygon renderings offloaded from your main computing chip, the Intel chip usually, off on the side. Well, it used to be a peripheral processor or a coprocessor, an afterthought, if you will, that only gamers cared about. If you were a business computing user, you did it in the old days, in the '90s, you didn't care about your GPU, right? You only cared about what was your CPU, the thing that computes your Excel spreadsheet or whatever your database, but the GPU people were like pushing a whole different kind of computational math forward, which was a lot of math, like a lot of polygons. The more polygons, the more sort of resolution you have in your game. And so in a very interesting way, with a different objective function, not do a program that a human wrote faster and faster, but take the same damn simple math of basically, it turned out to be what's called matrix multiply and add, multiply a whole bunch of numbers together and add them up, multiply, add them up. It's like that core sort of mathematical operation, the more you could do, the better your graphics were. And so they had an economic incentive to really push the envelope where if you asked, let's say in the '80s or '90s, what else could that be used for? The answer was, well, nothing, right? That just does graphics. It is like totally optimized for rendering graphics, right? But somewhere along the way, people realize, well, wait a second, there's other areas in the scientific computing world. By this, I mean, let's say modeling the weather, modeling how nuclear explosions occur in government labs where they're like, we do a lot of that matrix multiply and add too, can we try to see if we could use it? And so it was like a skunkworks project. And then management had no resources against this. I knew actually one of the first four customers working in this R&D area of all things to model how neurons fire scientifically. To model how neuron actually fires. The actual biology of a neuron down to as much detail as possible. A company called Evolve Machines. And they were using GPUs. And I remember years ago saying, wait, you just bought for $2,000 at the local, we call it those fries, the local fries, electronic store. You just bought more power than any supercomputer of just two years ago for $2,000 because of this domain. So this incredible computer resource was pushed to the limits from gaming. And I think almost poetically, when you think about rendering three-dimensional worlds and making the photo realistic, you're doing something our brain does exquisitely well. We get an avalanche of information on our retina and our cortex and we downscale that to image recognition. Building over there, your face, the symmetry of your eyes. And much like a neural network, when you train them, it recapitulates our biology. It builds edge detectors and then symmetry detectors. And then eye face things. 'Cause you can probe what's been built a little bit and get a sense, oh my God, it just recapitulated the sensory cortex in an artificial system. That's when the-- - Recapitulated meaning effectively evolved. - Oh, they're recreated from scratch. - Evolved. - It's an analog, sorry. 'Cause you're just training it like a baby. It gets born, opens its eyes, starts learning. That's the same general thing going on with these neural networks. The fact that it has similar layers in its visual system as our babies do, it's just that's when people like me are like oh my God, this is incredible. So back to the GPU thing. What I think is poetic is that something that in a sense is meant to be as realistic as possible to our vision system has the kind of computational systems we need to, in fact, do vision systems in like, let's do, let's recognize cats on the internet or let's recognize cancer in a pathology slide. Those general constructs occur because our brain has evolved to do data reduction and pattern recognition in the world in a way that is optimal for what we do so that when we build these neural networks, what are they really good at? All the same stuff. And so all the applications today are in speech processing, visual processing, which is the simple stuff, the edge of our cortex. And then naturally it's gonna start moving into emotional systems and the frontal lobe and the rest of our cortical systems. And so that's why I think it's the obvious path to AI in the broadest sense. - So many questions. I love that story for, or that sort of story/explanation for a number of reasons. One is how careful one should be with dismissing certain fields, or even if they seem trivial or to be a waste of time, like gaming, right? You look at the by-product of the incentives that drove that, and then the off-label uses of GPUs. Are GPUs, am I mistaken in thinking that they also have a role in cryptocurrency mining? - Oh, absolutely. So that's a very computationally intense task. And so it moved definitely from Intel-like CPUs to GPUs, but then it even went further. Then it went to these field programmable gateways, and then the custom chips designed from scratch. Sort of it quickly went down that path. And deep learning chips will as well. That was one of my investment themes the last few years, is that deep learning is doing the exact same thing to custom chips. - So you mentioned something much earlier. - Oh, one last thing on this I gotta tell you. NVIDIA summarized something amazing, and also out of Google did a paper. The majority of code at Google now is built by a computer, not by a human. 'Cause that's one weird way of summarizing this is when you train a neural network, you're not coding, you know, if, then, else. You're setting up the same thing you set up every time. It's a very fungible skillset, by the way. And you train it, and the computer's generating its own executable at the end of the day. The majority of programming is that way now, by a factor of 10. - So wild. - And every product at Google embodies it, from search to, you name it. It's like, that is the key technological thing striving across every Google product. - So you're so excited by the science, by the engineering. You mentioned product manager a while back.

Why did Steve get involved with Apple and NeXT? (01:14:23)

And you did, in fact, do that for a period of time. - Summer jobs, yep, yep. - What I've observed, not always, but very often, at least when I lived in Silicon Valley, certainly, that a lot of engineers have a severe disdain, or at the very least a distaste for all things. Most things marketing related. - Right. - Right, it's just-- - I remember that HP-- - Just a bunch of like hand-waving-- - Yeah, the chef and us, them. - I mean, yeah, so many levels. - So why did you, with the background you have, set your sights on product management? - Yeah, so I remember exactly how this happened. I was at-- - Wait, am I getting that right? - Yeah, yeah, product management, product marketing-- - Product marketing, that's actually the word I was looking for, sorry. - And different firms use the terms differently, but I was open to both. Some cases it's more engineering rich, other cases it's, well, whatever. So when I was at HP, I was doing chip design, and marketing was in a different building, as it often is. And I basically was getting frustrated, even though it was not there very long, on what I saw all around me, at least at HP, which was promote from within culture, over 20 years I'll become an engineering manager, and most people there were lifers, as we call them. And that seemed kind of long. I was like, "Andrew, we really want to dedicate the rest of my life to that career path." And then I said, "Well, how can I accelerate this?" And that's when the first idea came, well, if I somehow got into marketing, and it seemed like the boss has more than just one narrow functional domain, like maybe I should get some experience over there, and then I'd be more of an engineering manager if I could know more than just my narrow barrier of engineering. I thought being an engineering manager was the end goal, and learning a bit about marketing and product marketing, 'cause that was the mystery. How are all these decisions that seem to sort of impact our product development cycles, products getting canceled, things succeeding or failing in the market? That seemed important on what I was doing, and not just did I make a breakthrough. So I wasn't, I guess you could say, I wasn't a scientist in my profession of, well, I'm just doing it to learn the best way to do something. I was engineering through and through, which is I want to have an impact. I don't want to design a widget that's going to sit in a room and never get used just 'cause I like to design widgets. I really would love to have something be meaningful in the world. And so that's why I thought about that. And yes, there was a big disdain for marketing amongst the engineers that I worked with. And I did finally get the chance, 'cause I wanted to work with Steve Jobs as well, so I got a chance to work at Apple and Next Software, it was called Next, when they were moving out of the hardware business into software only, but Next as it was called. And I actually wasn't from either though. I just didn't, something just didn't click about, I think it may be in my short attention span, and my interest in diverse things, that hunkering down to any one thing and committing to do it for five years seemed anathema to my course. That's why I left the PhD program after two quarters. Like, I'm not going to write a thesis. That's like, I spent four years on one little narrow area, actually neural networks would have been my thesis area, specifically neural networks applied to parallel processing computers, was what I was starting down. I would have been fascinated by that, but it would have been 20 years too early. Anyway, same thing in any operating job. It's like, I would be either job hopping, the way some people do, who have this problem I have, or I'd have to be unhappy, I think, in my job, 'cause just the pace of change in learning would stagnate so quickly, I could see these patterns over months, not years, that I'm not learning as much anymore, I'm just executing the same thing over and over again. And so, management consulting was an interesting way to play to that, like all kinds of different client engagements. It just didn't have the same agency of making it meaningful. In fact, you could point to, very vicarious, very diffuse and ambiguous, whether you've accomplished anything. And so that's why all the management consulting firms say we're adding value, all was talking about measuring how much value we added. All these things are being said because everyone knows in their heart, like, I can't tell if I'm adding value. How do I know if it was me or them? It's usually them. We can't really sing our own praises that much. So I love the diversity in management consulting. I didn't like the life balance nor the agency. And so when finally I discovered venture capital and learned what it was about, it was like the perfect combination for me. - Well, your investment, or at least that facet of things you haven't, the lens of looking for things you haven't seen before-- - Right, that's where it-- - Also feeds right into that. Your programming, so to speak. - Right, well, you can see maybe that's the origin. I hadn't connected those dots, but it seems obvious now as I say this to you that that desire to seek something new may have been the driver of that simple rule that I've been living my life by, which is investing in something that you haven't seen before. - So when you're looking at companies, and I am going to come back to Steve Jobs.

Mitigating risk (01:18:52)

I have some questions about Steve and Elon. I know you've spent a good amount of time with both. When you're looking at these companies that have no product that are in the idea stage, I mean, there may be some white papers or publications from think tanks or conference panels that discuss these subjects. How do you evaluate deals, or how do you vet deals? Because I've seen a lot of people attempt to go as early as you do, but have just gotten their faces ripped off. Routinely, right? So, I mean, there are, and particularly if you're trying to be bold, so not just invest at the early stage, but also go for things that are however many times out of 10 going to fail, how do you avoid running out of bankroll, right? I mean, so I'd love to just hear a little bit about what you look for. I mean, in a situation like that, at that embryonic stage, what are the check boxes that help you to risk mitigate, if that's even a consideration? - Yeah, no, it is. Well, sorry, risk mitigate-- - Maybe not the right expression. - No, no, great, yeah. So the last one hung me out, but part of the luck I had in starting in the best inner sort of economic boom for venture, you could imagine, the dot com boom, right? You know, small amounts of capital allowed companies to scale incredibly rapidly. There wasn't really historical precedent for something that good for venture capital. So, Chuck, part of this up to luck, but the side effect that then lasted is that I didn't have that fearful moment. I didn't slog through 10 years of just banging my head against the wall of failure, failure, failure, failure. It just was like shooting fish in a barrel to start, right? So that, I think, helped me, A, build enough track record that people would give me a bit more slack to pursue something, right, within my partnership, for example, to pursue ideas that, I can't imagine what life would be like if I was stuck in a partnership that wouldn't give me credibility or let me run with some ideas, right? And they certainly would push back. Believe me, SpaceX, a bunch of companies, like, really? You're gonna invest in rockets? Are you kidding me? So I'd have to defend some of these, but I didn't get the, no, no, no, you can't do this, right? So that, if I hadn't had that capacity to, in other words, to avoid the inner voice of doubt and the overt critic, right, both internal and external, I don't think I could have done what I did in the subsequent years. So fast forward to, let's say, midway through my career and to the present day. So in other words, the startup phase is a little different than the steady state. So now that we're in a steady state, I can realize, okay, there'll be some failures, that's fine. And what I then look for is a combination of some personal attributes, market attributes, and weirdly of late, sort of process technology attributes. So I would have, in the past, said, oh, technology breakthrough. Of course, there has to be people, huge market, and something disruptive in the technology domain that they'd like to nanotechnology, or something that we couldn't have done this five years ago. Oh, that's another question I always ask. Every entrepreneur, either explicitly or implicitly, if I know the answer, I don't need to ask it, which is, could you have started this business five years ago? And if the answer is yes, then I don't want to invest. - What are other questions you have to ask?

Comparison Between Steve Jobs And Elon Musk

Weeding out charlatans and opportunists (01:22:04)

- Another one I'd love to ask is, so what does this business look like at 10 years and 20 years out? And what is mind-boggling is, unfortunately, how this weeds out the Charlatans and the arbitrage-seeking opportunists like nothing else, so they're just like deer in the headlights. They've never thought 10 years or 20 years out. They don't have any idea. And it's not because things change so rapidly that you can't predict 10 or 20 years out. It's that they don't have a mission. They don't have a purpose for either starting their business. Right, if you ask Elon Musk that, he knows right away. If you ask Planet Labs, he knows right away. If you ask Zuckerberg, he knows right away. You ask Larry Page and Sergey Brin, they know right away what their business looks like in 10 and 20 years. And they have a mission statement that they hold to throughout their entire life, and it galvanizes the team. It motivates them. That's why they're in business. Other people that are, I call them arbitrage seekers, when people flock from some industry 'cause there's gold in the hills, you want to weed that out. This is a great way to weed that out. These people don't tend to have long-term visions if they don't really have a purpose for what they're doing. So on the people side, I increasingly have become enamored with purpose-driven businesses, as I was mentioning, or mission-driven businesses, where making money is not the prime objective. It's the byproduct of the way they intend to change the world, to usher in the transition to sustainable transport and clean energy, to colonize Mars, as a couple of easily understood examples. Those are both unique. There aren't any other startups at the time proposing to colonize Mars. Nor is it something that you get done in a short period of time. It's like the star on the horizon that galvanizes so much action. Do you want me to loop back, though, to the overall categories, the process stuff and the other elements?

The uncertainty of enormous markets (01:23:36)

- I'd love to hear about some of the attributes. - Sure. So on the market side, I think a lot of venture investors in the early stage would have the following common answer to your question. Invest in good people, pursuing big ideas in enormous markets, right? Okay. But sometimes they actually won't execute on that because enormous markets usually means that it's something really radical that's changing. There's a lot of unpredictability. So if you're investing in ride sharing, as you did, before it was obviously a good idea, it was not obviously a good idea. And most same people probably thought it was a really bad idea. - Well, there was an email that Naval Ravikant put up not too long ago, which was the email that was sent out through AngelList, which was ignored by something like 297 people out of 300. - Exactly. - It was not clearly a great idea.

Hotmail origins (01:24:32)

- Actually, I would say that when I first invested in Hotmail, I felt this. I felt it when we first invested in Skype. - Side note really quickly, just 'cause I'm cheating a little bit here, but I didn't know this. Where'd the name come from, Hotmail? - Oh, Hotmail. It was spelled with a capital HTML. So it was, oh, we're gonna do web-based email over HTML. It's big H, small O, yeah, exactly. Is that dorky? And that was it. And even more interesting, because they were offering free email, they put a lot of effort into the free aspect of this. So they located in Fremont, California on Liberty Avenue. They launched on the 4th of July, which is a national holiday, so they got no news pickup. That's really-- - So it's all free, baby.

Successful companies that were “bad ideas” (01:25:19)

- So anyway, those companies were widely regarded as bad ideas. Sabir of Hotmail famously was turned on by 21 venture capitalists before he found us. And I would say without a doubt, 'cause I've met a number of these venture people at the time the Series A was happening for eBay and Google, the vast majority of venture capitalists would not have invested in the Series A. In fact, after the Series A of Google, the two primary investors demanded to get their money back. They wanted to be redeemed at cost because of a little spat they were having about the founders not getting a new CEO. Not well-known fact. Or one of the major venture investors in Apple sold their entire stake pre-IPO. They still brag about being an investor in Apple, of course, but people lose faith in the greatest companies they've ever invested in. - And I know we're bouncing around a lot, but that is what I like to do. So I was doing a bit of homework, and you were very helpful in sending me links to a few things.

Why Steve never sell shares (01:26:07)

One was an interview with Jason Kalkanis. - Oh yeah, I love that guy. - And you had created a very nifty index of subjects on your Flickr account. And one of the bullets was why I never sell shares of our companies. And biggest misses also. But could you explain what you mean by that? - Sure. - Listen, what does never sell? - Never, never sell. It's a wonderfully liberating stance. And at first people were like, yeah, I can see your face. Like, wait, that doesn't make sense. Buy low, sell high. It's kind of a mantra. Yeah, no, I've never sold a share. Now, let me add the caveats. When I have control. So the vast majority of time in our business, this would apply, which is we invest in a startup, it either has an IPO or it gets acquired. Those are the two outcomes where it has a liquidity event. And IPO, some point after the IPO, years later, or at least 180 days later, a venture firm will distribute those shares to its investors. So I, as a general partner, get shares. So I get shares of Tesla. I get shares of you name it, right? Now, what I choose to do that is my own personal decision. And from that point on, I've never sold a share. Now, what I do is give them the charity over time. And some might argue that's kind of a sales decision, but not entirely. And partially because it's not like I'm trying to time the market. I'm betting on them in perpetuity. And I'll give you another answer to why I do this in a moment, but let me just, let me flush this one out a little more. This has been wonderfully goal aligning with entrepreneurs. Because if I'm thinking, when is the time to punch out? It's kind of a corrosive thought process. When they're thinking, the ones I like, what's the next 20 years look like for this business? How can we make the most out of it in this next phase of growth? 'Cause the best companies are like these sort of power laws of compounding potential. They, you know, would you want to be punching out? And you wouldn't, right? At Facebook or Google, you know, 10 years ago. God, that would have been really a bad mistake, right? And actually, let me jump to the point number two. Some of the very first advice I got when I was entering this field was from someone who had spent their entire career at the Rockefeller Group, I forget, which was Foundation or something. His name's Peter Crisp, and I remember him vividly. 'Cause we were, I think my first week on the job, it was our first pitch to people who give us money. And here I met someone who has just coming off a long career, sort of winding down slowly off a long, illustrious career, investing in some of the best companies you can imagine. And his two comments to me were, "Wow, first, I'm super envious," this young group of people, "that starting your career right now, "this was like, you're gonna love this. "I wish I was your age doing this again," this whole second wave. So I just, here I am changing careers, as we mentioned earlier, not sure which careers were made for me, that to hear something like that. And the second thing is, looking back over his whole career, he wished he had never sold anything. And I had a similar reaction, "What do you mean?" He goes, "Well, I tried to time the market, "and if I had just held onto my Apple shares," right? "And who cares what would have happened to everything else? "Like the as-if held value today, "it would have trumped everything else. "I would be a much richer man, "I would have avoided all that anxiety." And that echoed in the back of my mind to this day. So in my, I won't show the specifics, but in my personal portfolio, there's a similar power law. There is a single company that's worth more than everything else combined, 'cause I've never sold a share. And then if I look at number two, maybe I have to actually go back and do the math. Number two plus number three probably, that kind of thing about a long tail, exceeds everything else combined. So it's like a traditional power law. And that is pretty amazing. So I just like, when I made this decision, and also around the same time to give it all to charity, that was another thing. I created a living trust to give everything but a small fixed dollar amount to the kids, everything else is gonna go to charity. Then when you have major crashes, it's not like, I know this is gonna sound weird, I don't stress that I just lost 90% of my net worth, 'cause that happened once. It's like, oh, the charity just lost 90% of its net worth. And so I was able to write it through when it came right back, 'cause I didn't panic and sell when I literally lost 90% of my net worth. - I recall seeing, I don't remember who it was, but one of the, and there aren't that many, as you know, but A tier venture capital firms looked at their return on, something, or their return to limited partners of the, let's just call it 10 companies that had reached IPO, and that they'd subsequently distributed, and they compared that with the amount made by someone who would have invested the amount in the companies at first opportunity at IPO and ridden it out something like five years, and they would have made just as much money in most of the cases. - Yeah, there was a fund called Technology Cross-Over Ventures, I think, formed with that insight in mind that says if you can pick some winners still private and have the judgment from seeing the track record, the passion of the entrepreneur over a number of years, and then load up the boat either just pre-IPO or at IPO, then you could put a large amount of capital work in that. But the key was it was those prior years of exposure that really gave you confidence. So like my years with Elon, allow me to look at him in a very different way than other entrepreneurs, right? And if you just literally had no prior data and he just walked in off the street, how would you really know, right? - You mentioned Elon, so you spent time with jobs, Elon, many other impressive folks, but what are the commonalities you've observed, biggest commonalities, biggest differences between those two?

Steve Jobs vs. Elon Musk. (01:31:18)

- Sure, well, let me start with differences, because I think it's tempting to draw an analogy, and I've been tempted, trust me. But I think it's really important to keep in mind, so I'll start there, there's pretty big differences. Jobs was a marketing-centric individual with very weak engineering chops. Elon is more of a physicist turned engineer slash computer scientist, basically. Deep engineering chops, thinks of everything from first principles of what can be done from the physics, and then scales up to the product vision. Jobs, it's much more of a almost Zen Buddhist approach to parsimonious design and the visceral agitation of imperfection in design space. The famous calligraphy font thing, getting rid of all the buttons from the phone. There's all these maniacal missions he had where at no point did he clearly lay out, well, here's the business strategy. Like, you get rid of the buttons, everything lives in the cloud, you have software services later, you can iterate more quickly. This is gonna be an awesome business opportunity if we can get rid of all the buttons. That, and say, no, buttons are ugly, get rid of them. That's shit, that design is shit, he would say. But he wouldn't really give this like, ah, I get it, that's the master plan, right? Whereas Elon is like, master plan part one, master plan part two, in the French. He lays it all out and he's basically executing according to the master plan. There's actually a really well-thought-out series of steps to get from here to colonizing Mars, a series of steps to get rid of the petrochemical economy, which is pretty amazing. And it's all there for anyone to read. That's like night and day difference. Now, similarities, simple one. CEO of two companies, I think that's interesting, structurally, not too many people have the shut spot to do that. And I think, by the way, in both cases, it allows you to focus, interestingly, in a way that you couldn't otherwise. - Oh, I see what you're saying, sorry. I heard that sentence too. - Oh, CEO of two companies. - Each of them, independently, CEOs of two companies at a time. - You got Tesla and SpaceX, you got Pixar and either Next or Apple, depending on timeframe. To be fair, Jobs was really not quite the CEO at Pixar, but he was by title. In any case, what you can do, though, is avoid meetings. Imagine it's the company holiday party, and you just don't want to go, right? No one's gonna double guess. Like, if you're a normal CEO in a normal company, you avoid your own holiday party, like, what, really? What better thing did you have to do? But this is awesome. You can basically avoid time-wasting meetings, and you have to delegate more. And so, in both cases, it's an intriguing thought experiment that being CEO of more than one company has some interesting benefits for both companies. - Huh, never thought of it that way. - The similarity, I think, there's one area in design where the maniacal attention to detail, I described it as this visceral agitation that, I mean, almost painful to Steve Jobs to see things that were not right. There's a bit of that in Elon as well. I interviewed him once about design, and it sounded so spookily similar in that regard, but in a completely different wrapper. Meaning, you wouldn't really know or see it as a similar vector of, like, both think it's just easy. And maybe it's the sign of brilliance, but it just, there's certain parts of this whole space that are intuitive, and they do naturally, and I wish I knew how to, A, do it myself, and B, spot it in others. So everyone also wants to ask, like, how can I raise my kid to be like Elon, or how can I find entrepreneurs that are like him? And if you think about just one element of that and how miraculous it is, to be able to go into a number of industries, commercial banking, arguably, with PayPal, the aerospace industry, with SpaceX, the automotive sector, the energy, competing with utilities, with the SolarCity idea, really left field. Now it's part of Tesla, but when it started, it was really a left field sector. It wasn't one industry. That was like, well, that's energy generation. That's like competing with regulated utilities. Without any prior business experience in those sectors, to become the dominant company in all of them, to have failed at none of them, to be the most important company in all those fields is kind of mind-boggling. - Oh, it is mind-boggling. - It is mind-boggling. I forget, right. And the thing that I look for in companies that say, we've got this mission, as I was mentioning, but we're going to get this through incremental steps and engaging with customers all along the way. We're not just going to hunker down for 20 years and then pop out with Colonizing Mars on the other end. To actually paint the picture of how we get from here to there, that's even more miraculous in some ways. It's like everyone can have a big dream. Like, oh yeah, thousands of people could have the dreams that Elon has. Almost none of them can paint a compelling picture of how to get there. - Mm-hmm. That's where the, what's your 10-year vision, what's your 20-year vision comes into play. So, Elon has this mythical status for so many people. I mean, just this kind of superman who's got everything figured out. I found this article on Business Insider.

Coping With Challenges And Adversity

Is Elon Musk the most risk-immune person in the world? (01:36:09)

It was talking a little bit about your relationship with him and there are two things. One, I'll just, actually two questions I want to ask. So, the first is, you called him the most risk immune person I've ever met. And then I'll follow up to that, but what does that, what's an example of him being risk immune? - Yeah, I think, yeah. - And is it because he does, is it because he feels differently in the face of the same risk or is it because he defines risk differently or something like that? - Yeah, that's a great question because I think it's passed through the filter of the observer. We perceive risk, incredible risk in some of the things he's done. I don't know that we have perfect vision on, how could we on really does he perceive the risk the same way we do, right, as external observers? And so I think part of the answer, and his brother made a somewhat similar statement once, so I feel comfortable at least talking about this, not as if I'm speaking out of school, that there, like here's one way I can say it externally. I've never seen an entrepreneur go all in for his companies, and I say plural, as Elon. Like some entrepreneurs will take risks. They'll quit a job, they'll spend their entire life savings on some idea, they'll do whatever, right, the personal commitment, personal sacrifice. I've never seen anything like Elon. And I think this story came out, where I was referring back to December 2008. - Yeah, this-- - In the darkest period for Tesla. - Yeah, so Musk thought it would take 50 million to get his first trip to Mars. And then next sentence he was 200 million. He was 200 million and had, quote, spent all of his money between that and Tesla and he went into personal debt by 2008. - Exactly, so 2008, for those that might remember was financial crisis was happening. For context, at that time, Tesla had just gotten rid of the CEO. Elon had not been the CEO up until then. And it was tough. A large investment bank, one of the most prestigious, had just failed to do a fundraise. This is where you hire them, pay them lots of money, go out, get us the money, you know, you expect it to come in at the end of this process. They're like, sorry, we have nothing for you. And the company was rapidly running out of money. In fact, it was heading towards December 2008 and it couldn't even make payroll. And so Elon wrote a check personally for $3 million just so they could make the December, Christmas time payroll of the employees. But like January's gonna be just as bad and there's like no money anywhere. And by the way, for context, there was no government program, there was no Daimler investment at this point. It was just a company that had a roadster that was negative gross margin, meaning every car you sell, you lose more money. It was a surprise discovery how bad the proposition was is why the CEO was let go. He was like, oh my God, like contrary to our belief, we're actually losing money on every car. And that's not easy to fix, by the way. Sell more cars does not solve this problem readily. And you had your largest inside investor. This is a term of art in the venture community. There's a lot of symbolism when your largest investor is or is not supportive of what you're doing. Doesn't mean they actually have a thing, a lever they can pull to kill you, but the symbolism's bad 'cause they're in the trenches with you and if they're refusing to write a check, that's a really hard fundraising environment. And the largest investor was as hostile as I've ever seen an investor. They did not want Elon as CEO. They did not want anything to do with the company. They wanted to pivot to a different business strategy that seemed a little too cozy that it would support one of their limited partners and it felt really icky. And they were openly hostile. So, oh, and he was going through a divorce and SpaceX rockets were blowing up, by the way. And he spent every penny he had. So what does he do? He borrowed $20 million and he said, okay, our lead investor's not here. This large investment bank has failed. I'm gonna invest the $40 million that's needed. No, he didn't have $40 million. I'm gonna invest the $40 million that's needed. To hell with all of you, here are the terms. Not to hell with any, but like I'm doing it. Train's leaving the station. And it flipped the zeitgeist, if you will, from fear to greed, right? And this is-- - Meaning everyone's thinking, what does he see that I don't see? - And to be fair, there is a dynamic, which I'm sure you've seen, which is you can have a bunch of people around the table, like we were, DFJ was very enthusiastic and wanted to invest but we can't do the full $40 million. We need somebody to be the lead investor and we'll do our full share. We actually did more than our full share. But somebody's gotta step further, this missing nut, when your largest insider won't and you don't have any outside money. Someone's gotta step up. So he stepped up and said, I don't care. I'll do the whole thing if need be. Who's with me? And we took as much as we could. We brought our growth fund in for the first time. And it is an easier decision to say, will I write a check, let's say for $2 million, let's say you're just one of the random investors there, as part of 40, knowing that at least there's 40, at least we're gonna get through this roaster cost problem and be able to turn some cards, if you will, see does the government come through, does the Daimler relationship actually happen 'cause there's verbal conversations going on. We'll get resolution, at least those major things, and so there'll be hope to get to the next phase of actually building the Model S car if all that falls in our favor. Let's be part of it. So our $2 million check leverages the $40 million check. I'm just saying too arbitrarily. So if all you can do is write $2 million checks, you would never just write a $2 million check. That's like a peer. It's not a bridge to something. And that's what A, Elon was willing to do in December all by himself, and then B, he was willing to do another one all by himself. I've never seen anything like it. So he, in retrospect, was perfectly right. Everything went exactly according to plan. This is gonna change the world. It's gonna be an enormously valuable company. This was an incredibly good investment to make at the time. In retrospect, at the time, it seemed like the riskiest thing I've ever seen. I've never seen an entrepreneur fund their own company, first, when no one else would, second, go net negative by $20 million. - Unbelievable. Have you asked him what he was thinking at the time? - Not directly. I didn't want to, I liked it. This is great. It just felt like the right thing. It's like I could see the fear of going to greed. By the way, in tough times, you sometimes also learn who is gonna stand by you and who won't. And so that lead investor, and then also, maybe I won't mention the names, there's at least one board member who's like, "Oh my gosh, they showed their stripes." And there's nothing like a crisis to know if you're in the trench with the right person. - Yeah, who your fair weather friends are. - Yeah, exactly. - To that point, it's mentioned in this piece that Elon called you around the darkest times, right?

Elon’s “battle mode” of focus during crises (01:42:26)

So during some of these really tough periods. And it doesn't, of course, keeping it whatever private should be private, but what does someone like Elon? You've interacted with a number of these people who have incredible capacity to do big things. What does someone like that say to a friend during their dark times? I mean, why do they call friends? - Well, so I'm not gonna relay any specifics, but I can try to get to the gist of the question. I won't relay any specifics to the phone call. And to be fair, I don't even really remember the specifics 'cause there've been so many calls over so many times. So with the caveat of-- - Because if you look at the list of difficulties he was going through, like any one of those. - Yeah, soul crushing. - Soul crushing, completely paralyzed and send millions of people into a downward spiral. - So he has said some things, 'cause I don't wanna speak out of schools, but there is something I can share that might be helpful. He has spoken himself, that it was like eating glass, that this was like really terrible times. So he's made some comments personally. I'll just let him speak for what it felt like for him. But I would say that what I've observed in that crisis and other crises that we generalize is that he goes into a battle mode of focus that is really remarkable. In this battle mode is allows him, I think to ignore distraction and to have a laser focus on what needs to get done. So it'll sometimes be, I'll observe it as these sort of thoughtful, deep moments of like, wow, like you see it on his face and you wanna give him space to think. 'Cause I think there's like for people that can be times when you're generative and thoughtful and brainstorming and thinking about all possibilities and the wonder of the world. And other times when you're like, you've gotta like solve the problem and like focus in. And in those modes, he can avoid distraction like no one else I've seen. So a lot of the smart CEOs and entrepreneurs I've worked with are, some of them share attributes that I have in spades, which is I'm interested in many things, I'm easily distracted by something. And sometimes I'd rather avoid tough crisis in my, you know, in thinking about it when there's something more fun to spend time on, right? And so I'm almost the opposite of this. Just to give credit to how valuable this is. When let's say Tesla has faced various manufacturing challenges, these sort of production hell times that he's described, he physically sets up his office on the production floor in a very visible area with no walls. So everyone can see that he's there through the weekend. They know the vice president see that and that ripples out. When he's calling a supplier, let's say he was often the cause of a problem. He's like, and he's like, well, I'm here in the factory. Where are you? Why aren't you here solving this for us? - Yeah. - It has a lot of impact, right? And I want to give that personal attention to right now, everything else needs to be gone. I have to solve this problem. I've witnessed this, for example, in a more subtle way more recently when I was setting up or trying to set up rather, a very interesting phone call between the Mars Tsar, a person who's the Mars Exploration Program for NASA, Craig Vander, who's a pioneer in synthetic biology and gene sequencing and gene synthesis. And I want to just get in on a half hour call because the sort of idea had occurred amongst us that we could do a much cheaper Mars return mission. In other words, if there's any life on Mars, either archaic or currently living, the best way to explore it would be not to send it back from Mars, which is very difficult, but send a gene sequencer to Mars, sequence it locally, beam the data back and create the living organism on Earth. That actually is doable. And I thought Elon should certainly be interested in this 'cause in the next phase of Mars exploration, terraforming, finding out what organisms do live on Mars or not, if they mutate on Mars and actually start thriving, send the data back, create a version on Earth to study it here and more rapidly terraform Mars. He's like, "That's great." He said, "I can't take that phone, "only half hour phone call. "One day that will be important. "Right now I got to get a Falcon Heavy to fly "or there won't be that need for me to be doing that." So I'm like, I would love this half hour phone call amongst us to be with him. He's like, "That can wait a few years." And it can, right? And that remarkable ability to push aside all these interesting things when there's, I got to get XYZ to ship or fix the problem. And so fixing the gross margin problem back in 2008, getting a CEO, which turned out to be himself, in place and solving all the myriad problems that were in place was battle mode. And he would also lean on confidence and friends. So to be fair, there were others like Antonio Gracias and others who really rolled up their sleeves, got on the factory floor. - Who's a close friend. - Yeah, he's amazing. So folks like that really come and prove that they're some of the most valuable investors out there. - Antonio is happy to fight to support his friends too. - Oh, exactly. I'll just say, he's my favorite investor I've ever met in my entire career. - No kidding. So I mean, catch up more over a bottle of wine about this. But so we were, Antonio and I were in the Henry Kran Fellowship Program together at the Aspen Institute. So we've had a chance to spend a lot of time together. Yeah, great guy, absolutely great guy. So two things come to mind. The first is, and I'm sure I'm gonna butcher this, but it's a quote attributed to Steve Jobs.

Steve Jobs, team sizes, and meetings. (01:47:18)

I feel like there are a lot of mistributed quotes. I'm pretty sure this is accurate. I don't think it's an Abe Lincoln situation on the internet, but that innovation is saying no to a thousand things. That the-- - I haven't heard that one, but yeah. - In any case, the other was-- - He's also, by the way, Jobs was very proud of, and that's what his greatest creation or greatest contribution to the world, his greatest invention, his greatest thing on his death. It was Apple, the organization, and it was really the process learning, coming back to something I was starting to talk about earlier. He was focused on physical space design, keeping the engineers and the marketing people, thinking about where the bathrooms are, Pixar, so you have to walk by certain areas to get to them. He was maniacal about architecting the way people communicate, kicking people out of meetings if they're too big. So he had an intuitive sense of a team size long before I did, and now I'm like-- - If the people are over a certain weight class? - No, no, no, no, no, no. You don't want more than seven people on anything productive. No development team, actually five's the ideal number. Five plus or minus two. Boards of directors, development teams, creative groups. That's one of the secret advantages of small companies is they have less people, and they get shit done. When it's a big company, has hundreds of people and sclerotic layers of management, they've lost the small team dynamic. - So I always like to ask about, and I asked about it with Elon, some of the tougher times or challenges, because it's easy, I think, and I explore this with lots of, everybody who's on the show, I try to, and ask them about how they try to deal with overwhelm, or if they feel scattered, what do they do? And we talked a little bit about Elon.

On bad press and dealing with allegations (01:48:54)

I'd love to ask you, because you recently had an experience that a lot of people have in the sense that I and many others get their turn as kind of the punching bag. If you're public facing, I mean, you're gonna run into things, and you had an experience recently that I'd love for you to describe if you're open to it, and then I have some follow-up questions just about how you then reacted to it, right? Self-talk, things like that. Maybe if I could just leave it open. - Yeah, so yeah, maybe it's an elephant in the room, but in the last couple months, I have faced the most surreal experience of my career, which is, what's it, 23 years of venture capital, and many before that, all positive press experiences, and then I faced a bizarre, almost autocatalytic, self-generating theme that I hosted a sex party with my fiance in Silicon Valley, and at first I laughed, "Oh, this is hilarious." As an ex-geek, growing up my whole life with glasses and braces and what have you, the notion, I mean, my first date was in college, I really thought that was hilarious at first, and then it got a little more serious. I'm like, "Wait, this is ridiculous." And it really, the thing that's even more, it derived from a book that then came out in February where there's no such claim that we hosted a sex party, but it's in a chapter about sex parties that other people had, and we just happened to be the only party that has been even mentioned by name, and then, I mean, if I try to put a simplistic spin on this or try to make sense of it, it looks like people just didn't read the chapter very carefully, and they'd blog posts or other very sort of non-professional postings online that, oh my gosh, the sex party was at Steve's house. And I'm like, "What, what, what, what, what?" Not only did the book not say that, it wasn't true. And by the way, there's 150 people that attended this thing that know it's not true, and 10 of them go publicly on, which is kind of a risky thing to do, say, "I was at this party and there was no sex." - Including Elon. - And Elon Musk was like, "This is irresponsible journalism "or something to that effect." And he condemned the writer. And it's kind of bizarre because I know this author. I've been on her Bloomberg television program many times. She knows my email, she knows my cell phone. She never called me for a fact check, which I didn't realize in book publishing today, in what's ostensibly a nonfiction category, that the publishers do no fact checking. That's just a fact now. That's transformed from decades ago. And they leave it up to the writer, and the writer just didn't even try to see if it was true. And more disturbingly would retweet, even though she never said we had a sex party, she would retweet other people who did. So some other publication in Europe would say, "Oh, the orgy." So it starts to grow, the orgy at our house. And she retweets it. I'm like, "Really? "You know this isn't true." And I know she knows it isn't true, but she keeps retweeting it 'cause it sells more books. And I know executives, for example, who've been pressured by their PR people to say positive things about the book because of her ongoing role as a Bloomberg reporter. She had this weird conflict of interest when you want to sell books and salacious stories sell to propagate something that's not true, even if you didn't say it yourself, and then turn around and use your leverage and your bully pulpit on Twitter and elsewhere to gain support for your book 'cause you know people want to continue working with you and you're going to be the journalist of record in the tech industry at one of the biggest news organizations. It's kind of unfair. - Yeah, so it feels really horrible. - Yeah, well, I was going to ask you, how did it feel and what was your self-talk, maybe in the short term? And then I ask a lot of people about self-talk, which I'm fascinated by. So the day of, let's just say, when it ceases to be funny, and then maybe, I don't know, I'm making this up in terms of timeline, but a few days later when you've had a chance to maybe gather your thoughts a bit. - Yeah, so despite the initial burst, almost like this defensive, "Aha, this is funny," and then when I really allowed it to sink in, probably took some number of hours. I'm like, wait a minute, like for example, there's 150, probably more in total, but 150 that really knew there was nothing there and they were there the whole time. They had to explain to their spouses and others, like, no, I really wasn't at a sex party. It's really embarrassing. Those poor people, totally innocent. Anyway, and again, not to condemn a sex party, I mean, I've never been invited to one. I've never held one. I don't want to say it's a terrible thing, but let's just say if I haven't been the one, I don't want to be accused of one. - Yeah, well, just to inject some levity real quickly, so I just moved to San Francisco, this was a long time ago, and one of my neighbors said, "Oh, welcome to the neighborhood. "You should come over Saturday, like we're having a party." I was like, "Sure, no problem." So I end up having a late dinner. I'm like, "Okay, is it too late?" "No, it's not too late, come on over." So I walk in and I'm like, "What's happening here?" People in various states of undress and just in time to realize, "Oh my God, I'm actually at a sex party. "There's food served, "but I'm fully clothed with a beanie in it "and a hoodie on." And then they go, "Okay, everybody sit down. "We're gonna do a round of introductions." And so I sit down, I'm like, "How do I get out of this?" 'Cause there were like 40, 50 people there. And I did manage to scurry out and then say to my neighbor, well, I won't name my name, but I was just like, "Please, in the future, let me know. "Give me a heads up." And I have nothing against it, but it's like, "Let me know what's going on." In any case. - Exactly. - So yeah, I was like, "You're in the Bay Area." So it's like-- - I'm sure these things happen. I literally never been invited to one. It's not my thing. So I don't want to sound too preachy, 'cause, you know, but it's just not my thing. And it does feel weird to have a room full of tech executives and some of our closest business colleagues, scores of them, maligned in this indirect way. So the way I felt though is I felt really betrayed. And there were, and it wasn't just the single journalist that I've highlighted, like, wow, what happened to professional journalistic ethics? Like just fact checking and caring about the truth. That's one branch of disappointment. The other was a little more invisible. I'll keep this anonymous, but there were a number of people I noticed who would immediately lend support to this idea online. Like either simple things like retweeting something without checking with me. People who ostensibly know me. That was really disappointing. So I felt betrayed by luckily only a handful, I mean, a remarkably small number of people who just, and frankly, there was some of my least well-known contacts. So these aren't close personal friends that are like, let's say other venture capitalists, let's say just as a category. On the other side, I was blown away by the outpouring of support by people who do know me. So a couple of coworkers of ex-employees that I used to work with came out with blog posts. And in every case, it was after they published that I even knew they were putting something together coming in my defense. And like female entrepreneurs of all types, you're like, no, is there anything but this happened at this event? I'm going to be eternally grateful for, again, when time is really tough, you find out a bit more about people's character and you find out who is really someone who knows you. Because someone who knows me knows this is not true. And what's weird is that I thought that'd be obvious for the larger set, but at least the ones who really know me, they don't even need to ask about it. They don't know, oh my God, dude, what's going on? This is crazy. - So what prevented you? I mean, you had the outpouring of support. You also had a few people show their true colors. Some people, when they get hit with something like that, anything, I mean, I've had periods where it's like, I remember this kind of hit piece came out on me, and I'm not saying these are the same thing, but like it's hit piece came out on me. It came out on my birthday at one point where I have this annual gathering of my closest friends. And it was through a credible, I mean, a very well-known publication that had not only, they had contacted me for fact checking via phone. I had corrected a bunch of misquotes and then they ran it as is without making any of the changes. And it really bummed me out. Like I was considering not doing any interviews ever in the future. Maybe I'll have to make a number of changes to my life so that I'm not exposed. And I think that there are certain ways you can mitigate, like always doing fact checking email responses as opposed to via phone. - Right, 'cause then they can't deny you did it. - You always direct it to email. I mean, there are a number of different ways that you can risk mitigate there. But was there anything that you said to yourself or that other people said to you that was particularly helpful at the time? - Oh. Let me think about that for a second. Well, the thing that jumps to mind is how supportive my fiancee Genevieve was throughout this. I mean, she's a fighter and she was at my side throughout. In some ways it was incredible. And I'm incredibly thankful for her support throughout this. At the beginning of what you were saying, the part that was going through my mind as you were asking the question is that one of the toughest things, and it relates to advice other people gave me, was the advice to not say anything. The advice to be just mum. I got advice from people who focus on PR. I got advice from people who've been through similar situations or worse, have been accused of crazy things or crimes, right? Falsely accused of crimes, which luckily I've never been accused of. And in every single case, with zero crack of there's another side to this point of view, you say nothing. You do not point out the obvious flaws in these false accusations. And the research supporting this is disturbing but true, that anything you say, even definitively proving your innocence, will only worsen people's perception of you at large. Just the mere recanting or resurfacing of that topic to then say it has been decidedly proven false will make people think worse of you on average. Now, from a media perspective. So in private conversations, that's not the case. And I've asked psychologists about this. I don't know all the studies, like real clinical/science-driven studies show that you do not want to say anything even to prove your own innocence. So that's horrible, right? It's like that's where you're torn up with all the virtual conversations you'd like to have with the people who've done you wrong, with the media. 'Cause you know you can set the record straight. It's like I wrote pages of stuff that I never used. Yeah, like let's just set the record straight. My mind played for months, it would play through, well, here's what I would say that would just either A, clear it all up, or B, get back at the person who I know is being dishonest to prove they're being dishonest. So you're like, you know, fess up. How about you own this one? So that is the most difficult. I really have a hard time with that. 'Cause in every aspect of my life, I don't have to do that. You can speak openly about, like I disagree with you. Well, that didn't really happen. Or that's a science-based fact or something. I hate that.

Other trying times (01:59:31)

- Well, it seems like this, I mean, you were able to withstand the flack very well. If you think back on, it could be at any point in your life, but has there ever been a particularly difficult period for you? I mean, that you've-- - No. - No? - I mean, my whole high school, I could say. But that was a long, retracted series of pain of just feeling insecure. And that was a late bloomer. I can tell you about tough times, there wasn't a shock to the system. There wasn't like, I mean, I was deeply hurt when my dad died. I mean, that was tough. But it was something that's life. It was a natural cause. - That qualifies though. - It was tough, yeah. I mean, remorse. So I've gone through some tough things, but nothing that was quite like this, which is, wow, that really, someone did me wrong. I've been betrayed. As opposed to, life has its cycles and I can feel sad about the passing of a dear loved one, but it's a different category, I think. - Yeah, no, it's totally different categories.

On grief (02:00:32)

But I'm interested still in the coping mechanisms or the thinking that goes with it. So when your dad died, I'm sorry for your loss, it's hard for me to imagine, but what was most helpful during the period of grieving or recovering from that? - It wasn't, I didn't have a playbook of what to do. And what seemed most natural, and it may have been the habit of mind, was to focus on my mom and helping her, who survived him, who was there at his side when he passed, of a heart attack. And so it's one of those things where like, wow, you're trying to revive me, you're trying to call 911. I was like, my heart went out so much to her and how her situation was worse than mine in a way, that that consumed almost all my thoughts for some period of time, dealing with, I'm the only child in that family, dealing with what needs to be dealt with. I went into sort of almost non-emotional operations mode and may have been sometime late that night or the next day that I finally allowed myself to cry and really face what I had lost. Part of what gave me incredible solace is perhaps some wisdom I could pass on to others who worry about parents who go. And I know Tim Urban and others have written some wonderful pieces about, think about your parents, if you're anyone near our parents generation, like how many days do you have left with them? - Yeah, the essay, the tail end. Everybody should read it. - Absolutely. - And it was recommended to me just as a quick side note by Matt Mullenweg, mutual friend, - One of my favorite people. - Wonderful person who also lost his father not too long ago. And he recommended it to me before it happened. - Exactly. So maybe the thing that I took solace in that I'll share for others is it's not what you do in the weeks before someone passes that really defines your relationship, it's what you've done over your life. And so I had been going to the TED conference, I brought him with me. It was one of the greatest joys of his life for years prior. The fact that we had all those weeks together, sort of these one-on-one times of intellectual pursuits in a way almost to welcome into my world, like take dad to work day in a sense in this sort of virtual world of like ideas and science technology. When he went through a pancreatic surgery procedure just around Thanksgiving and came out of it. And I was told by the nurse who first saw him when he came out of it was that he was like, oh my, 'cause there was a chance he would make it even through the procedure. I said, oh, I get to go to TED again. It was like the first thing he said. I was like, oh my God. - That's amazing. - And so hearing that, and then he had complications a few weeks later that he passed from, but just knowing how much that meant to him and how much time I did get to spend with him purposely really took the edge off. Like if we were estranged, if I was at odds with him, then I'd really, I think be torn up with guilt of having not come to closure. And we had nothing. I mean, he's my hero. I've only had positive thoughts about him throughout my life so that made it easier, ironically, to lose the guy that I had the best relationship with. - Yeah, I mean, this is, as you said, it's part of the cycle. I'm certainly not looking forward to it. I mean, people ask me like, what do you fear? What are you afraid of? And there are certainly things, not as many as one might expect. I mean, I don't want to be eaten by sharks or anything, but I don't spend a lot of time dwelling on the fear of that happening. - Statistically unlikely. - But watching my parents get older and ultimately pass away is something that I, yeah, I think qualify is definitely something that occupies my mind. And I owe Matt a huge debt of gratitude because he led me to the tail end. I read the tail end and that led me a number of years ago to start taking extended trips with my parents twice a year. So at six month intervals, we have not just the trip, which is usually, let's just call it two to three weeks, but where I usually take them somewhere they haven't been, but also the entire period in between during which we can look forward to the trip and plan the trip and talk about the trip. And that anticipation, I feel like, is for 70, 80% of the enjoyment of it. - Exactly. - And so I owe Matt a huge thank you. And he recommended a book to me I haven't yet read, but I'm hoping to soon, which I believe is on grief and grieving. And he's been on the podcast, so people look up his last name and grief and grieving. I'm sure the correct title, if that isn't it, will pop up. But he recommended that everyone read it even before passing of loved ones. So we talked about Matt Mullenweg. I pinged him to ask him what subjects or questions might be interesting to explore. And one of them was parenting, so it's a good segue.

Parenting And Other Personal Experiences

Benefits of parenting (02:04:59)

How do you think about parenting? Or maybe doing it differently is too awkward a question to answer, but what are some of the things that you think are important in parenting? - Well, you know, we don't really get manuals on how to do it. People, young parents and first-time parents, are sort of thrust into it and you find your own way. The thing I, the only thing I did to prepare for being a parent was to read "Scientists in the Crib" by Alison Gopnik. It's not a parenting book. It's basically about the neuroscience of infants and, you know, up through two and three years old. That made it fascinating to study, and I mean, literally, this incredible creature, when they were pre-verbal, it sort of created a bond that some dads lack, I think, when they don't have that physical connection, and you say, in nursing or what have you, that a mom might have. And yet, to marvel at this creation that is in front of you, things like how they pick up language, how the vision system develops, it actually gave me, I'm going on a strange rat hole here, but it gave me strange experiments to run, like pushing the bassinet on the first day of life under a light overhead that was an L shape, and the baby's eyes would open immediately every time one ended there, 'cause you could actually see it through the closed eye and any edge detection just fires up the brain. So it's like, if you have visitors, you're like, "Hey, watch this." Pop the eyes open. And then during phoneme development, meaning learning a language, practicing bah, bah, and pa, pa sounds, 'cause it's like, it's sort of, we take it for granted, but we learn how to speak by watching others, like, "What are you doing with your lips "to make that sound?" So it made young childhood development easy. Then I got into my groove, which is like my power alley, which is playing with kids, getting down at their level, whether it's Legos or blocks or whatever, and just exploration and fun. So what I loved about being a parent in the early years was an excuse to rediscover Mindstorms NXT, or first Legos in general, then Mindstorms, which got so much better. The toys have gotten so much better, the drones and everything, right? So when the kids are older, but basically playing with kids to me is super invigorating. And metaphorically, I think a lot of engineer scientists and people close to that field, like even venture capitalists, would do well to try to be creative like a child, to engage like a child does with the world. - Well, in that childlike wonder, right?

Steven’s billboard (02:07:11)

- So yeah, not to interrupt, but this brings to mind, and just for long-time listeners, the reason that I'm not going to ask a lot of my rapid fire questions that I normally do is because, Steve, you were kind enough to answer a good number of them in my last book, "Tribe of Mentors," but in that, I asked you what you would put on a billboard, and you said, "Celebrate the childlike mind." So I don't want to interrupt the discussion of parenting. - Right, so it's almost like a mantra that came out of parenting, which is I could see how, and then this is something, by the way, that hearkens back indirectly to this book, "Scientists in the Crib," that babies are like scientists. They form conjectures and hypotheses.

Children are like scientists (02:07:38)

They test the world. They're putting things in their mouth. They're playing with everything. Sometimes it frustrates a parent, but when you see them as scientists doing experiments and learning how the world works from a sort of boot-up phase, it is metaphorical for what we lose, oftentimes, after many years of traditional education that can beat the creativity out of you, and I think the best engineers and the best scientists have that kind of a childlike mind. You can see it in the writings of Feynman and even Einstein and Newton and others. Like Newton, I think, once famously said, I felt like nothing but a child playing on the she-saur, that there's something deeply resonant about seeing the connectivity in things as a child would and avoiding the strictures and mental ruts that academic disciplines foster and job sort of tracks. Think about it, discipline, track. Those are both two things I don't like. I'd rather have less discipline and less tracks, right? I'd rather be exploratory and creative. And so I found children to be a wonderful opportunity, and it's such a win-win. You're connecting with them, you're mindful, you're present, and that later rolls into reading with them. And I spent a lot of time and try to, whenever I'm with them, do what they like to do, right? Engage with them in the kinds of toys and things that they like, and then push that a little further with all kinds of, how should I put it, tech-infused adjuncts to what they might normally be playing with. - We probably don't have time to go into it right now in this conversation, but where can people learn about your rockets, your rocket building? - So I did a short TED Talk on the joys of rocketry, or yeah, I think it was called the joys of rocketry.

Model rockets (02:09:15)

So ever since my son turned three, we started launching a lot of rockets. In the story there was I just went to a local toy store back when they had them, a physical place, and saw this Estes rocket kit ready to fly. I'm like, wow, I sorta remember rockets when I was little. I wasn't that into them, I built a couple. And so we did this, and to make a long story short, I found a mentor that could teach me, you can get really bigger engines and bigger rockets. To the present day, I've probably launched thousands of rockets. I 3D print these designs. My son and I have been working on this. We go out to the Black Rock Desert every year and launch really big things going well past supersonic speeds routinely, launching large rockets, the rockets he could fit inside, as a hobby. That's, by the way, where I first met Planet Labs was out in the desert launching rockets. - Oh, okay. - Yeah, as an aside. So occasional good business comes out of it, too. But most of all, it's this incredible hobby of making science real. Like when something fails to launch or explodes on the pad or comes back in 'cause the parachute didn't deploy properly, it is just visually exciting. I don't know, I just, I can't really put my finger on why it's not universally exciting. To me, it just feels like something everyone should do a little bit of. - Talking about making science real, there were a few tidbits that I pulled from one of your indices on various talks.

Drones and how to eliminate the TSA (02:10:36)

And they were just, seemed like fantastic attention-grabbing headlines at the very least. Not intended to be that, but I was like, "You know what, I'd be interested in hearing the answer," or just a little bit of elaboration on this. One was drones and how to eliminate the TSA. So what's the short-ish, doesn't have to be super short, but explanation of what that means. - Sure, and so the drones thing is peripheral, but how to eliminate the TSA was, it's an epiphany I had back, I think it was around 2005, or maybe earlier, maybe 2003. Post-9/11, TSA's, you know, oh God, in full effect, doing all kinds of crazy things. I think they just implemented the shoe thing for the first time. And I met this sort of brainstorming effort with them where they gave us the challenge, how can we rapidly or radically streamline airport security operations to get on the plane sooner? And this was at the time looking at 18 years. I don't know why 18 years, maybe it was 2002, and this would be 2020, maybe it was 2002. - Okay. - And so I came to that, I think I was the only tech guy there. The only thing, 18 years, that's a long time to predict things. We'd invested, by the way, in some airport security technology stuff, but I didn't really talk about any of that. I was like, "18 years, that's gonna be, you know, "perhaps 18 doublings of Moore's Law, "which would be, you know, 256,000x compute power. "Hmm, what might someone do then that they couldn't do now?" Well, autonomous flight, it's like, by the way, it was long before autonomous driving or autonomous flight or drones was a thing. Those words didn't exist. - Right. - At least not in vernacular products. And I said, "Well, there's no question "that we could have autonomous flight by then, "18 years in the future, by the year 2020, "like autonomous planes?" 'Cause we already can today, right, by the way. Airbus and Boeing, every one of those planes can land better than the pilot could and take off. Everything but taxiing is easy compared to autonomous driving. Any case, no one else was on that page, and I said, "Well, wait, do you realize what happens "when there's no cockpit? "You make that a really nice first-class lounge. "The plane can't be used as a weapon, right? "So why have any security gateway, right?" So just what you could do instead is go in with some biometrics, we know who's on the plane, have video surveillance on the plane as the trade-off, and bring whatever weapon you want on the plane. This would be a really bad place to go kill 200 people, right, 'cause you're gonna get caught, right? If you're a terrorist, sell it, you will get caught. If you can't use it as a terrorist weapon, then why have the TSA at all? And then there was the, "Well, wait, will it really work?" And it will to have autonomous flight. And we should be doing it today with today's technology, no doubt about it, and you could telematically operate at each airport for the taxi part, if that's really so hard. But I don't think that's that hard. And then you could go a step further, say, "Well, okay, well, what about bombs? "Maybe the plane falls out of the sky." Your luggage could fly separately in an autonomous thing from the plane itself. You could have a smaller luggage-only plane for the actual cargo part. You could have smaller planes. The whole design space starts to change in terms of what the optimal design is if you're not amortizing a pilot anymore in terms of that operational cost. And you could have multiple flights where there was a single one before. Now there's even less people per plane and more flexibility in your routes. All this unpacks, and I ask them, "Have you even calculated the economic impact "of the shoe policy?" And they didn't know what I meant. They're like, "Well, you could just take "how much time did that just add to the Q "of the average traveler times the average salary "of the average American and just economic deadweight loss." And part of what I tried to show them is that the immune response of a system is often worse than what kills you, not your pathogen. So it's often our own immune system that kills us literally as the method of death. And I said, "Wait, how long 'til someone "puts a battery on fire? "Are you gonna keep the laptops and cell phones "off the plane? "Do you realize the economic impact of that?" And they didn't wanna hear it. I was like, "I'm glad that hasn't happened quite yet." But I'm like, "That's what the terror cell "should be doing to cause the most harm." Just have one Yahoo make a half-assed attempt to light a battery on fire on a plane and now look what it'll do. - I was in a flight from, I wanna say it was, I mean, I was in a far-flung place, but I think it was Uzbekistan to Istanbul or Istanbul to London. It was one of the two, and we actually had to surrender all of our laptops. And it created the amount of confusion and congestion and craziness that that created was just unbelievable. So the end of the TSA. - That's right. Wouldn't that be wonderful? - How do you budget as a technology investor for regulatory or political opposition from incumbents?

Budgeting for regulatory or political opposition (02:15:01)

You could look at many different examples of this, whether it's lobbyists or extremely powerful unions of various types that would be strongly, strongly, strongly incentivized to not allow something like the TSA to go away. - Yeah, no. - Pilots, unions, I mean, some people would point out the usual, like, well, you got a bit of an issue here. So in the past, in the '90s especially, when the internet was like, you could just do internet for a while and that was fine, we had the mantra to never invest in a regulated sector. And still to this day, I try not to invest in anything that requires any law to get passed in order to be in business. And the one exception is we went all in on autonomous driving, the product is currently illegal, but we know it's gonna become legal, fully level five autonomous driving. But without exception recently, in the old school, if we not only tried to avoid regulated environments, we tried to avoid if you had to deal with in any way, as a customer or partner with utilities or the government or in any of that sector. But I think, frankly, that left a lot of large sectors just plump, like a lot of entrepreneurs were avoiding them like the Blake. So when Elon opened our eyes, it says, you can actually take on what might be perceived to be the most non-market, if you will, non-market factors, not like the best product doesn't necessarily win, like the military industrial complex, you can take that on head on and just win with a better product. Right? And similarly going up against the regulated utilities with SolarCity and like sort of distributed solar solution. And yes, they're fighting with every dirty trick you can imagine, right? They're trying every angle, but sometimes there's just such a compelling advantage because there's been no new entry for like 25 years. They haven't faced a competitive threat in their institutional lifetime. They really don't know how to behave and respond. So you have on one hand, yes, they'll try to do dastardly things. And I don't know what to say other than you just kind of hope that enough of normal democracy will flourish that you can overcome that and not have critical wounds. We'll see. But on the other side, you don't usually know-- like when I was in software investing as a primary focus, you don't usually find opportunities to make 100-fold or 1,000-fold cost advantage in a product. But you do in some of these areas because they literally have faced no competitive threat for so long, they don't even know what it's like to compete. They take like the aerospace industry. There's a number of Chinese ministers who early on when SpaceX gave their pricing for the Falcon 9, they said, those prices are not real. We could not compete at those price points even if we had all Western technology. Like, it's game over. And other US competitors said, well, we basically have to shut down our product lines. Imagine if some competitive Oracle or Microsoft said, we're going to come out with something. Like, oh, yeah, you're right. We better stop selling Windows. Or we're just going to not do databases anymore because, oh, that's better. No company responds with, we're shutting down our entire product line. And we were the monopolist prior. We were the thing. And the only caveat is they say that we're shutting down our product lines. But government, you've got to have another company. So give us $4 billion, we'll build a better one. We can do it. We can build it. Give us $4 billion. Like, we forgot to innovate for 25 years. But now, give us a pile of money, we'll start. It's wild. Yeah, I've never seen anything like it.

Advancements In Health And Science

Synthetic “clean” meat (02:18:27)

So one thing that we chatted a little bit about before recording that I wanted to ask you about is printed organs and synthetic meat. So-- Hopefully not in the same dish. Hopefully not in the same dish. You never know. Could be organ meats. The old nose to tail. But in this case, you would have to, I suppose, imagine the exterior would be a figment of your imagination in the case of synthetic meat. But where are things currently with synthetic meat, and where will they be in the relatively near term? Yeah, it's-- And why is it important, for that matter? I think that's a great question. So the reason I think it's great is I think it's one of the major tech themes or factors that will affect a lot of people's lives over the next 10 to 20 years. And not everyone's fully aware of it yet, and it's an inevitability. So back when we were talking about these inevitable futures, like all cars will be electric, all vehicles will be autonomous, this is one of those. We will not slaughter animals to get meat. And the question is, is that 50 years out? Is that 500 years out? But just like we won't burn oil and gas 500 years out, there's no way we would do that 500 years out, especially not in small internal combustion engines. We won't slaughter a cow to get a steak. And so the insight occurs when you realize, first, it's a much cheaper and efficient way to grow the product you need without the whole cow. The hide. You don't need the methane production. You don't need all the inefficiency that was an artifact of biological evolution. You don't need the land use, the water use, the energy use. You can cut all that somewhere between 10 and 100x, all of those factors. Which, by the way, for the listeners who don't know this, about a third of all usable land on Earth goes to meat production. So this is the grain that gets fed to cows and pigs and chickens and the land that those animals live on. So like a third of all usable land. It's astounding. It's like one of the biggest water problems, the biggest methane gas, which is one of the most serious greenhouse gas problems, it's sort of on par with the whole petrochemical economy. Or on the other hand, if you could say, I will get rid of oil and gas forever, or I'll get rid of meat production, you'd be better off getting rid of meat production in the short term in terms of greenhouse gases and the environment. So pretty big, big deal. So why is this possible? There are two major branches of companies that are trying to solve this. One branch is to replace meat with something that's not meat. And I applaud those efforts. It's a little bit more of an engineering challenge to get it past the consumer. And each product has its own engineering-- each and every product is challenging. Make the duck taste like duck. Make the chicken taste like chicken. And have it not just be like sausages and hot dogs, but actually filet if you want to take on the whole core of the market. So that will make a meaningful impact. And it'd be important. It's just going to be slow moving because of how hard it is to do each product. And to make anything passable is challenging. Extremely hard. Exactly. I've tried a lot. People have been trying every which way to do a veggie burger. There's big breakthroughs recently by using heme and plant-based heme. Just for those of you who are impossible. That means you get a veggie burger that blades, basically. Exactly. They found a root of soy plant that has a molecular cage that holds an iron atom in the center that's called a porphyron. That's the same molecule kind of structure as we have in hemoglobin that makes you blood red, that makes it turn color when it gets out of your body, that makes your steak turn red, that makes it taste the way it does, that makes it barbecue the way it does, the way it browns. All those things you put in a plant. You can also put it-- by the way, you can make chicken or red meat. It's kind of fun. Anyway, that's the plant-based approach. A lot of engineering, a lot of effort, a lot of money per product. The other approach, the one we invested in, called Memphis Meats and others like that, says let's just make steak. Let's make chicken. Let's make any of these products in not just a substitute, make the exact same thing, but don't grow it in a cow. So it's more of a change in the manufacturing method, quite simply. Do you have the cow making the steak, or do you have it in a lab? No, how do you make it in a lab? Well, the team came from cardiology and other medical backgrounds. They have people that have done work in stem cell biology, and people have worked in the whole synthetic biology area. And it's pretty straightforward to grow cells. You take stem cells. You can induce them to be pluripotent or induce them to be immortal, basically. And you can just grow an infinite number of these cells that could become anything. They could become skeletal muscle. They could become nerves. They could become skin. And the way you differentiate them into skeletal muscle, which is like our muscles and our arms, is you put them on a scaffold that causes them to differentiate into that kind of thing, a scaffold that is an edible gelatin-like thing, basically some other food product. Like we have collagen and other stuff. You have the scaffold of things, aerogel. The cells differentiate, and they merge together into these long fibers, just like our muscle cells. So what were formerly discrete standalone cells formed into one long, multi-nucleated cell, it twitches. It does everything like a normal muscle. It is a muscle cell of that species, where I have tasted the duck most recently. So it's duck muscle. And over time, you can add the irregularities of sinew and all this. Right now, it's just like a perfect cut of duck muscle. The mouthfeel, everything is just the same thing. Everything's a filet mignon. Exactly. And by the way, in the future, you can make it healthier. You can make it all omega-3 rich oils. You could tune things. But let's just start with a simple-- don't confuse the market with, no, it's not turducken. It's turkey or it's duck. You're right. It's not a blend. But you imagine blending is like a simple thing. There's no reason you can do infinite blending, like blending a wine, to make it just the right mouthfeel or just the right whatever. But in the near term, let's not jump ahead of ourselves. It's just a substitute. And you can do this in small, like a Chinese shipping container kind of thing, so you could put this near the point of consumption. You could have this in urban areas, so you're not shipping meat all around the country. It's growing the steak sort of to order. The end cost point should be much, much lower. And so to me, this had one of those sort of lightning bolt moments of this is the inevitable future. There's no technical risk that says this couldn't happen. There isn't like we have to invent something that hasn't-- there's a lot of system engineering to optimize it, the feedstocks, whatever. It's building the right reactor size. It's going to take some engineering, but it's not going to take breakthrough science. It's the same epiphany that when I first rode in an electric car, when I first had an autonomous ride early on with the Google ones, the old Prius is that they had automated. It's like, this is the future. You could just see it like a clarion bell ringing in your head. And then a few implications started to hit. Like, wow, this will transform the world. In a lot of ways, the amount of land and resources and real estate plays that relate to meat production today. Not to mention, oh, mad cow disease, influenza, H1N1, all these other things that we don't-- those collateral damages of the food industry. We've gotten to that. You can see how we'll get from here to there. The buyers, the largest buyers of meat would absolutely like to diversify their supply chain. So they are not vulnerable to influenza or mad cow or any other disruption to the supply chain. You can see how they're going to want to feather that in. So by the way, Tyson and Cargill, two largest meat companies in America, invested in this company as well, in the series A with us. But then I realized something about myself. I realized for the first time something where my future self will condemn my present self as immoral. So I know that 50 years from now, once I'm eating the bacon and steak that has not killed an animal in its production, will I be able to visit a slaughterhouse for the first time? I won't do that today. I like eating meat so much that I refuse to go visit a slaughterhouse. In fact, of the USDA meat inspectors, 99% of them become vegetarian. They don't start that way. If you see how it's made, you wouldn't eat it. And yet, I won't do that. And when I say moral, I think our humanity's circle of empathy expands over time. First, it was family unit, then the tribe, then the nation state, then maybe global citizens. Now I think the interspecies, if you will, empathy, is inevitable trajectory where I would welcome that. That would just be more thoughtful about other sentient organisms and their well-being. That we just look right past today. It's kind of like being a slave owner in America back in the 1700s. The economy depends on it. I don't want to ask questions about how those slave ships-- I'm sure slave owners didn't visit slave ships. And the few that did were like, oh my god, we've got to change this. You just don't want to look. And once you have the economic alternative that doesn't have any compromises, it's not like, oh, it's not really bacon or it's not really steak. It's the same thing, just no animal died. Then you'll have the moral shift, I think profoundly. Where-- what is the current state? I mean, what products do they have that-- They're still in development because of the cost side at scale. So this company's-- so when I mentioned the challenge of the plant-based substitutes is engineering something that people won't mistake. I mean, they taste as good. That's the key engineering challenge. Here, the whole thing is just cost. Because you can make something that's indistinguishable, it just costs too much right now. And there's three vectors of making it cheaper. Two are total gimmes and one just engineering. The gimmes are just making a bigger plant. So if you brew beer, if you just have a one liter facility on your desktop at home and you're amortized to cost you a home to make one liter of beer at a time, it's going to be an expensive liter of beer, even if the formula is the same as a huge production plant. So scale. The second is cheaper feedstocks. Just feed it something other than the very, very expensive serum they're using now in R&D purposes to minimize variables. They're using pharmaceutical grade inputs to feed the cells, if you will. What do they feed them? Is it like a glucose mixture with amino acids? It's like a serum, like a blood serum. It's kind of like what you'd find in your blood to make your blood cells live. Oh, wow. So it's a variety of stuff that's used for very research purposes. But there's no reason it couldn't be-- but the reason it doesn't exist is there's no market for food grade plant-based feedstocks that cells can grow off of. And now we have a good reason to do that. And then the third is just various engineering optimizations on the cells and the mixtures and what combinations of cells. Do you want to try to boost the fat content of each cell or have separate muscle and fat? Do you want to have it all be like one bite does all, or do you want to have two different types? Well, a few thoughts occurred to me as you're describing this.

Producing human tissue and organs for transplants vs 3D printing (02:28:13)

The first is, would this company ever utilize the technology to produce human tissue for regenerative medicine or other purposes? And then I thought to myself, wow, you could also-- you could become a moral cannibal if you wanted. Like you could produce-- not that you would want to produce human burgers and eat them, but you could ostensibly do that. But that was just more of a thought. I was like, wow, that's-- Well, you could also-- a small dinner to revive and restore, which is trying to bring back the mammoth and extinct species. So you could go back to have the mammoth burger-- That's true. --without growing the mammoth. Yeah, that's right. Yeah. It's a little-- it's a little gamey. I mean, it's just really gamey. Yeah, the brand burger. I'm just a brand. But is that maybe just a distraction, or I don't know the technology well enough to think of it from a medical-- human medical perspective? No, it is a good question. In fact, the first sort of clean meat or alternative meat company that I came across was using, ironically, the reverse sequence, which is it spun out of a company that was doing organs. They had printed bladders. There's a kid I met who's-- he's 18 years old. He's lived with a grown bladder for many years now. But that was more like a 3D printer. So when you're growing a specific organ that needs to be functional, it's super important to get a lot of the details right. A chunk of skeletal muscle, you know, you just take it from the centerpiece versus the end with sinew. There's variation if you want to make it function like a muscle. Right. And the connection to your sinews and what have you-- If you're making ground beef from scratch. If you're doing just the chunk of meat out of the middle, it's just the chunk of meat. So do you have much bigger challenges with the printed organs that lent itself naturally to a 3D printer kind of approach? And it works wonderfully for some organs. They've been growing kidneys and some of the connective tissue stuff around reconstructive surgery for the face and what have you. But it's slow. It's also a great example of personalized one-to-one market. Like you want to grow cells that are compatible with your body so that they would source your stem cells to grow your organ for you. And it's kind of a different approach in a number of ways intuitively from what you want to mass produce for consumption where you can just have-- who cares where the cow-- it could all be the same cow clone that you're growing the beef from, whereas every human implant wants to be immune compatible with what you've got. So the spin out didn't make as much sense to me to say, well, let's try to produce metric tons of meat using that 3D printer. In any sense of a 3D printer. I'm sure they're going to figure out some way to scale that up. But it just felt like to me there was a definite technology risk there. I couldn't see the hand waving around and says, why is that going to get 1,000 times better? It probably could. But I don't see why it has to. It might not. Whereas this other thing, growing cells in a vat inherently scales. It's like, just have a bigger vat. It's like, it's 3D to start with. It's not a 2D layering. There's something about the manufacturing method that gets us born out in things like brewing beer and a variety of fermentation tasks where you kind of understand how to generate metric tons of stuff with a fermentation process. For people listening, like myself, who are not particularly-- I'm being generous-- not technically trained.

Scientific literacy (02:31:13)

I'm certainly not an engineer by any stretch who want to make themselves more scientifically literate. Are there any books or resources or approaches that you would recommend? Yeah. There's two things that jump to mind. One is a general purpose overview of what's important, almost like a survey level where if you're just a business executive and you want to make sure you're not blindsided by some development that may be relevant, but not be a practitioner. And then there could be a question of, well, is there something that-- let's say you're a former autonomous vehicle driver and now you're looking for the next thing. Like, what might you want to study to engage in the economy as a practitioner? And there are some areas that are more, I think, easily approached than others. So first, in the overall survey, I think there are some writers who do a good job bringing you with a sort of overview mentality to what's really going on in the world, people like Kevin Kelly and maybe Matt Ridley and maybe a few others like this, going back with Hofstadler and Gudelesher-Bock, there's been a variety. But I might highlight, let's say, Kevin Kelly. Because the single book that's had the most influence on me in my entire life is one of his earlier ones called Out of Control. And it really started my lifelong fascination of the biological metaphors in technology. Everything from all that stuff we're talking about earlier, about cellular automata and iterative algorithms and evolution is itself an iterative algorithm. The power of evolution, the power of genetic engineering, all this stuff. So he was ahead of his time. He wrote this book in the last century. And it recently got translated to Mandarin. In the current day, it's one of his probably most popular books in China today, even though he wrote it decades ago, because it's actually very relevant today. So that'd be a good starting point, I think. It segues into the technology that either as a practitioner or just you can read about this if you just direct yourself, either simple Google searches or there's-- I don't know if there's a particular book I'd point out-- just to learn about deep learning, learning about neural networks. The reason I say that is I've never seen a greater demand for a technology and a scarcity of supply. Like the salaries being afforded to engineers in this area are out of control. Half a million dollars for beginners. Who are some of the more credible thinkers or practitioners who talk publicly about deep learning? Let me think. Yeah, I'm trying to think if there's a good overview. The places-- well, I know that Coursera and some of these places are trying-- and Sebastian Thrun's Udacity are trying to do deep learning courses and such. And I haven't taken those. I don't know how good they are. I would imagine even some of the very technical people have given non-technical talks, whether it's at Google or elsewhere. I would imagine some of the thinkers that might be in their day-to-day work way too technical or specialized have probably given-- This is a tough one. Maybe for your show notes, I can try to come up with some. So part of the challenge I had is because I started a PhD in this, I didn't seek the generic ones. And I've been reading once. In the back of my mind, I'm like, well, is that too technical? But I bet you I can dig some up. And it may sound self-serving, but I've tried to give some of those talks. And when I go to conferences a number of times, there's a real dearth of other people doing that same summarization. But I would say that the group out of Canada-- so everything from Hinton to Yoshua Binjo to Andrew Ng, who's coming back to the US in his case-- they are both the leading edge of R&D and such. And they give really good talks. It's just not all of them. Some of them are deeply technical. Some of them are overviews. So I'll try to find for you some examples of talks they gave that are for the average person. Perfect. Perfect. So that's what we'll do then. Oh, and the last thing I want to say about if someone actually wants to get into it is it's actually remarkably easy to learn. When I say it's weird labor market arbitrage is I don't think it takes more than six to eight months to become really a domain expert in this.

Preparing to work in deep learning fields (02:35:04)

And you don't have to be spectacularly good at computer science before. The background is it's just so different from normal computer science that arguably a new entrant has a great opportunity to just learn how these things are trained and forget about normal computer science. And I can say a few things in response to that. The first is to recommend people check out-- so we talked about Tim Urban a little earlier, and the tail end, and so on. So I had Tim Urban on this podcast. And I asked him how he got up to speed on topics. And he went through his exact process. He just talked to Elon. Yeah. Yeah. Elon lays it out to him. He just calls Elon. He just calls Elon. I call the guru on the mountain. He just calls Elon. For those people interested, if they just search Tim Fairshow Tim Urban, that'll pop right up. And he spends about 20 minutes talking about exactly this, getting up to speed, which would be, I think, helpful for a lot of folks. And then in the show notes at, you can just find this. And we'll have some additional resources for people who want to, including myself, dig into this and learn more. Have you ever given a-- this will be maybe the last question or second to last question. Have you ever given a commencement speech?

Steve’s high school commencement speech (02:36:20)

Oh, funny you should ask. Once for my high school. And it was the most terrifying thing I've ever done. I love public speaking. I did debate back in high school. And when I'm speaking to an audience that's somewhat similar to the audiences I've spoken to before, check. If it's on subjects I've spoken about before, check. This is my power alley. I don't mind that. Oh my god, trying to be relevant to a bunch of 18-year-olds? Wow, that was tough. It was back in Dallas. Yeah. But I did that a few years back. What did you talk about? And maybe if it's broad, what did people respond most strongly to of what you told them? Oh, I can actually give you show notes. I managed to keep a copy. And someone even translated it in Spanish. Oh, amazing. Yeah. Great. So I'm trying to remember what it was. I was trying to-- well, here was the advice I got. That really helped was think about when you were their age. And the more time I spent thinking about what life was like for me as a senior, because I went to that same school, it all sort of clicked into place. What do I want to do with my life? What's going on in the world? And sort of weaving what I was learning from Rich Capital and all the amazing entrepreneurs that I was seeing to convey to them, like, wow, you are entering the most exciting period in human history. And I shared a little bit about things we spoke about on this podcast around things going on in synthetic biology, things going on in AI, and what have you. Each of these areas is so rich with opportunity. And I gave them some general advice about just thinking about your career as a pursuit of passion, thinking about what you're uniquely good at that no one else in your random walk through life may have done, and to keep that in mind as you hopefully infuse with a bit of technical open-mindedness and creativity and childlike mind and exploration of what you want to do. That there's just like, it's no better time to be entering the world and trying to make a difference. I tried to encourage them a lot to think entrepreneurially, to think about being change agents for the world, that everything that history books we've written about is some new entrant entering a field they didn't know much about prior, and encouraging them that this is what increasingly defines the world we live in. You know, one question that somebody posed to me when I was considering the question, or considering unique strengths. I was like, I don't know if I have any unique strengths.

Talent stacks” and unforeseeable breakthroughs (02:38:25)

I do a lot of things kind of well. But I'm not sure-- maybe that's it. Maybe it's the pattern matching across those. And the question that they asked me was, what do you find easy that a lot of your friends find hard? And I was like, huh. And that actually ended up being a very helpful question for somewhat indirectly landing on the strengths. Because I had a lot of trouble with that. So maybe folks find that helpful. - Yeah, 'cause everyone does have some aspect element to that question. And they also have something they've done that, back to that early question when I was entering venture capital, how am I different from every other venture capitalist who's trying to do this job? There's something about your personal background. It could be a language skill. It could be, wow, you had to take care of an aging grandmother in your youth, and so you have a sympathy and empathy for what the aged are going through that others lack. Like, that actually could be superhero strength if you want to be an entrepreneur for this aging demographic of baby boomers. Not everyone, in fact, very few entrepreneurs think about the aged, for example. - And your unique strength can also be an unusual combination of two strengths, right? I've heard Marc Andreessen talk about layering public speaking on top of anything else and separating yourself. Warren Buffett would say something very similar. Scott Adams of Dilbert fame has talked about this. Let's say you have an unusual combination, right? So maybe you have double E degree, and then you have an MBA, and then you know how to debate. You don't have to be the best at the world at any of those things. - There's a lot of wisdom there. - 'Cause it's that pairing. - That's, I think, why most scientific breakthroughs are interdisciplinary. There are someone outside of the field of chemistry working with someone maybe in the field to come with a breakthrough, not someone at the core of, again, an academic discipline. This is why universities are such areas of foment of innovation is 'cause they have all the disciplines in one physical campus. But if you just had a chemistry department or just a chemistry college, it wouldn't make world-breaking changes, right? The people who figured out the structure of DNA were like an ornithologist and a physicist, not chemists. Right, not crystallographers. Well, actually, Rosalind Parks needs to get credit. Let's give a shout-out to her. So she's the traditionalist in that regard. But more and more people, think about Elon, not domain expert entering a new domain. It's the cross-pollination, right, bringing, let's say, software design modalities to the aerospace industry. - Or calligraphy into personal computers. - Exactly, and so that pairing, I think, harkens back to one other thought that might bring this whole thing full circle, which is every great idea is a recombination of prior ideas. This is a really powerful and simple idea that was popularized in three different books at the same time, which I think is meta-ironic, that their argument at the same time as every good idea happens around the same time.

Philosophy On Innovation And Ideas

Every great idea is a recombination of prior ideas” (02:40:52)

And the reason that that's interesting is, you can think in history, Edison and Tesla and Marconi, it's like the time was ripe, given the breakthroughs that had just happened, electricity and magnetism, to think about AC induction motors and radio and everything else that got invented by all those same people are all within months of each other. Today, writ large, we have many more ideas. We have the internet allowing us to cross-pollinate ideas like NERVIFOR. These two things that are unique that you pollinate together, the calligraphy and the computer design for jobs or what have you, the number of possible pairings is growing combinatorially. And I think that's why we have accelerating change in technology. That's why Moore's Law exists over such a long time frame. It's not because of the semiconductor industry. It's because the number of idea pairings is growing as a to the n factor, what's called Reed's Law, with the number of ideas on the planet. And once you break down the barriers between formally discrete academic disciplines and strip all that vernacular away of their independent ways of communicating with each other that are so isolating, and you see the common pattern, like, wait a second, that's just like an information theory I saw there on the microbial design front. It's like, then that same problem's happening. All these rich array of new ideas is a sort of meta reason where you can't really quantify how strong this will be. We'll probably see more innovation than ever before. And it's not just because we all will see more innovation than ever before. It's because this combinatorial explosion of idea pairings is happening globally. And oh, by the way, it's about to explode when the next 4 billion people come online. We go from 2 to 6 billion people online because of satellite broadband that SpaceX and others are developing. That's all coming in the next five years. Holy shit, we're going to have just explosion idea possibilities and innovation across the planet. Exciting time to be alive. Exactly. Especially when you have quantum computers accessing potentially parallel universes. That's right. Where does it end? It doesn't. Well, Steve, thank you so much for taking the time. This was really fun. And as meandering as the path I forged, hopefully you had fun as well.

Conclusion And Future Plans

Parting thoughts and what’s next for Steve (02:42:51)

Absolutely. And to be continued, hopefully we have many more conversations. And I have so many more questions for you. So another time. For another time. But where can people find you online to say hello, see what you're up to? Sure. So on Facebook, I'm just username Jurvitzen. On Flickr, username Jurvitzen. That's the ones-- most of my old writings are the old stuff. Come back 2004 is mostly on Flickr. And then my social network addiction du jour is Facebook. And what is next for you? What's next? Oh, I'm going to start a new venture fund. Some point this year. I haven't picked the name yet, but I'm bouncing some ideas around to focus entirely on purpose-driven businesses with really long time frames where we never sell a share. At least I don't. And we will be investing in the kinds of things we talked about today. Companies that hopefully history books will be written about. Companies whose founders have a purpose greater than their own life on this planet and a purpose greater than certainly making a quick buck. And there are more opportunities and more industry sectors than I've ever seen. Like, in the '90s, it was like software, semiconductors, and life sciences. That was it. I never imagined I would invest in the array of things we are today. Throwing in a freaking venture. And Justballs. Then it really went horribly wrong for a while. Justballs and Gazelle being the pinnacle or the nadir of intellectual curiosity. But now it's just a flourishing coral reef of innovation everywhere. And it's an incredibly interesting time in the investing startups. Well, can't wait to see what you do next. Thank you. And to everybody listening, there will be plenty of links in the show notes, including the things we promised, resources to deep learning, and much more. You can check that out at And as always, thank you for listening. Hey, guys. This is Tim again. Just a few more things before you take off. Number one, this is Five Bullet Friday. Do you want to get a short email from me? Would you enjoy getting a short email from me every Friday? That provides a little morsel of fun for the weekend. And Five Bullet Friday is a very short email where I share the coolest things I've found or that I've been pondering over the week. That could include favorite new albums that I've discovered. It could include gizmos and gadgets and all sorts of weird shit that I've somehow dug up in the world of the esoteric as I do. It could include favorite articles that I've read and that I've shared with my close friends, for instance. And it's very short. It's just a little tiny bite of goodness before you head off for the weekend. So if you want to receive that, check it out. Just go to That's all spelled out. And just drop in your email, and you will get the very next one. And if you sign up, I hope you enjoy it. This episode is brought to you by Helix Sleep. Last year, I committed to making sleep a top priority, trying to fix onset insomnia or continuing to fix that, depth of sleep, quality of sleep. I tracked a lot. I tested a lot. And I revisited really everything, from daily routine to the surfaces I slept on, playing with a chili pad, whatever. And when I moved to Austin, I got all new beds, including mattresses from Helix. Working with the world's leading sleep experts, certainly some of them, Helix Sleep developed mattresses personalized to your preferences and sleep style to make sure that you can have the best sleep possible without costing thousands upon thousands of dollars. Helix Sleep has recently added a new layer to customize sleep with the Helix Pillow. The all new pillows are fully adjustable, so you can achieve perfect comfort regardless of sleep position or body type, or if you're a shifty type like me, I move around quite a bit when I sleep. 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