#404: Books Ive Loved — Steve Jurvetson

#404: Books Ive Loved — Steve Jurvetson

Monday, December 30, 2019


Welcome to another episode of The Tim Ferriss Show, where it is my job to sit down with world-class performers of all different types—from startup founders and investors to chess champions to Olympic athletes. This episode, however, is an experiment and part of a shorter series I'm doing called "Books I've Loved." I've invited some amazing past guests, close friends, and new faces to share their favorite books — the books that have influenced them, changed them, and transformed them for the better. I hope you pick up one or two new mentors — in the form of books — from this new series and apply the lessons in your own life.

Steve Jurvetson (@jurvetson) is an early-stage venture capitalist with a focus on founder-led, mission-driven companies at the cutting edge of disruptive technology and new industry formation. Steve was the early VC investor in SpaceXTeslaPlanetMemphis MeatsHotmail, and the deep learning companies Mythic and Nervana. He has led founding investments in five companies that went public in successful IPOs and several others that were acquired for a total of over a $100 billion in value creation.

Before founding Future Ventures and DFJ before that, Steve was an R&D engineer at Hewlett Packard and worked in product marketing at Apple and NeXT, and management consulting with Bain & Company. He currently serves on the boards of Tesla, SpaceX, and D-Wave.

Please enjoy!

This podcast is brought to you by Four Sigmatic. I reached out to these Finnish entrepreneurs after a very talented acrobat introduced me to one of their products, which blew my mind (in the best way possible). It is mushroom coffee featuring Lion's Mane. It tastes like coffee, but there are only 40 milligrams of caffeine, so it has less than half of what you would find in a regular cup of coffee. I do not get any jitters, acid reflux, or any type of stomach burn. It put me on fire for an entire day, and I only had half of the packet.

You can try it right now by going to foursigmatic.com/tim and using the code Tim to get 20 percent off your first order. If you are in the experimental mindset, I do not think you'll be disappointed.


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Full Transcript

Steve [00:00:00]

Steve [00:00:01]
At this altitude, I can run flat out for 1/2 mile before my hands start shaking.

Steve [00:00:12]
I'm a cybernetic organism living to show a medal.

Tim [00:00:24]
This episode is brought to you by four Sig Matic, founded by the genius Finns who lit the Internet on fire. And you may have heard of their mushroom coffee, which features Chaka and lion's mane, which has taken Silicon Valley by storm. I use it pretty much every day. Either that or the chugga, which is decaf, a separate version, and I used both these primarily for focus and productivity. They just get you going, let you up like a Christmas tree. So definitely check it out. People are always asking me what I use for cognitive enhancement, and for right now this is the answer. I try to force this on all of my house guests. It is a hell of a thing. If I have employees or people come over who are working on projects with me, I always try to feed it to them because I'm going to get the limitless effect, get a lot. We're out of them. The first time I mentioned this product and four stigmatic on the podcast. Their products sold out in less than a week, so you may want to check them out soon. If you're listening to this and the coffee tastes like coffee, it takes just seconds to prepare with hot water and, oddly enough, on Lee includes 40 milligrams of caffeine, so it has less than half of what you'd get in a regular cup of coffee. I don't get any jitters, acid reflux or any stomach burn any of that. It's very unusual and very, very cool. So if you don't like caffeine, they also offer very strong but caffeine free mushroom elixirs, which I will sometimes have in the evening. I find Shag a specifically to be very, very grounding and earthy, so that is another option. And I have a cupboard full of their products at the moment, which is right around the corner of my kitchen. You can try something right now by going to four sig Matic dot com. Forward slash tim. That's four Sig Matic F o U R s I g m a T i c dot com forward slash tim and use the code. Tim T. I am to get 20% off of your first order, and they're not that expensive. Anyway. If you're in the experiment mindset, I do not think you'll be disappointed to try me.

Tim [00:02:28]
Hello, boys and girls. Ladies and germs. This is Tim Ferriss. Welcome to another upset of the Tim Fair Show, where it is usually my job to sit down with world class performers of all different types startup founders, investors, chess champions, Olympic athletes you name it to tease out the habits that you can apply in your own lives. This episode, however, is an experiment in part of a short form Siri's that I'm doing simply called books I've loved. I've invited some amazing past guests, close friends and new faces to share their favorite books describe their favorite books. The books that have influenced them, changed them, transform them for the better. And I hope you pick up one or two new mentors in the form of books from this new Siri's and apply the lessons in your own life. I had a lot of fun putting this together, inviting these people to participate and have learned so so much myself. I hope that is also the case for you. Please enjoy.

Tim [00:03:24]

Steve [00:03:25]
Hello, boys and girls. My name is Steve Jurvetson, and I am an early stage venture capitalist with a focus on founder led, mission driven companies at the cutting edge of destructive technology and new industry formation, I lead founding investments in five companies went public and successful I pose and several others that were required for a total of over $100 billion in value creation. I currently serving the boards of Tesla's Space X and the Wave, which is a quantum computing company before founding future ventures, the venture firm on that now and D. F. J. Before it, I was an Army engineer at Hewlett Packard and worked in product marketing and Apple and next and management consulting with Bain and Company. And I was originally trained in electrical engineering.

Steve [00:04:02]
Going all the way through to a PhD but not completing it. So today I'll present three books, the most gifted book by me, the one given to most people the most influential book on me and then the most important book for all. In my humble opinion.

Steve [00:04:16]
Let me start with the get book I've gifted more than any other. It is scientist in the Crib, by Alison Gopnik. She's a professor of developmental psychology at Berkeley, and I basically give this book to any geek friend of mine about to have their first child because it had such a wonderful influence on me.

Steve [00:04:31]
It is not a parenting book, but it nevertheless, it kindles in awe and awareness for the marvels of their minds babies minds, especially in the pre verbal years when it might otherwise be difficult to connect. Some practical experiments come out of this once you understand that baby's signal their interest in things by where there it focused their gaze is the fundamental research tool used by cop Nick and others in there petitioning of their art, and that that focus shifts over time as the brain develops and they face new developmental milestones. So, for example, at birth, much of the vision system is bootstrapping, and this is everything from the color space, the distance, vision and initially edge detection meaning seeing the edge of a knob checked and it's three dimensional distance, if you will, is how you sort of make a difference in foreground and background and make sense of the world in three dimensions. so I would notice that when I could take advantage of this basically, even at the hospital when my son was one day old, I noticed that when I pushed his bassinet with the sleeping baby through a hospital hallway, his eyes would just pop open. Whenever I turned a certain corner, it was like clockwork. And so I looked up and I saw a right angle in a long, bright line of fluorescent lights. So ran down the hallway and made a right turn. And sure enough, when I close my own eyes and looked up, I could see that sharp edge of light through my own clothes. Islets. Ah ha! This was like food for the baby's developing brain. It made him happy to open his eyes to this visual treat. That was the thing he was cognitively working on most of that time, and it made it great for me to show this to others. I could get him to open his eyes for visitors by repeating this trick for them and again, it was sort of a joyful way to wake a sleeping baby. Then later, when my daughter was first learning to speak but had not mastered all the sounds. I noticed her gaze would flip around to my mouth whenever made a butt or up a B or a P. But Pop imagine learning those for the first time is a very subtle difference in mouth, position and house. Could we learn this but to watch someone else? So I then had many days of enjoyable phone in practices. I called it with her as she came to master the elements of speech. I think science is the crib is fascinating not just for the life in the crib before he tells us about scientists as well. It is an inspiration for adult life. From what I can see, the best scientists and engineers nurture a childlike mind, their playful, open minded and unrestrained by the inner voice of reason. Collective cynicism or fear of failure. Isaac Newton and Richard Feinman or famous examples of this. I've come to celebrate the childlike mind, as I call it, and here is one of Alison got Nick's key conclusions from her book, and this is a direct quote. Babies are just plain smarter than we are, at least if being smart means being able to learn something new. They think draw conclusions, make predictions, look for explanations and even to experiments. In fact, scientists are successful precisely because they emulate with Children. Do naturally.

Steve [00:07:09]
At a recent talk, I heard the long now foundation, Alison Gopnik went further to say the three and four year olds do causal inference better than the best scientists we know. It's kind of fascinating. So what is this? Well, much of the human's brain power to restaurants. Massive synaptic interconnectivity, the connection between neurons. Jeffrey Western, Santa fan stewed, observed that across species synapses per neuron, meaning how many connections each neuron has to his neighbors, it fans out with a power law with brain mass. In other words, this is something that is endemic to larger and larger brains in evolutionary landscape.

Steve [00:07:40]
In an age of 2 to 3 years old, when your baby is now become a young child 2 to 3 years old, they hit their peak with 10 times the many synapses, as we have his adults, literally 10 times as many interconnects is we d'oh! And twice the total energy burn of an adult brain.

Steve [00:07:55]
Well, it's all downhill from there.

Steve [00:07:57]
The UCSF M memory in the aging center has tracked cognitive ability of age. For example, they have a delayed free recall tests, quite simply, a red 16 words, and after some time has passed, you're tested. How many you can recall unprompted from the teen years tore mid thirties. We all remember about 12 of the 16 words. It's pretty much a flat line on the graph. But then, about in her mid thirties, the line shifts to a completely different straight line that's declining over time until end of life.

Steve [00:08:23]
But it's at the same slope. In other words, the pace of cognitive decline is the same in our forties as in her sixties as their seventies and in her eighties. We just notice more accumulated decline as we get older, especially when we cross the threshold for getting most of what we try to remember in her late seventies, too early eighties. Per that graph. But we can affect this progression. That's a graft. Looking in the past, professor merge Initiate. UCSF has also found that neural plasticity does not disappear in adults. It just requires a mental exercise, the old adage of use it or lose it.

Steve [00:08:52]
So the bottom line from this in terms of adults, sort of learning and recommendations is that we should embrace life long learning. We should do something new. Physical exercises, repetitive mental exercise is eclectic. And that princess to the next book, an eclectic rump.

Steve [00:09:09]
Kevin Kelly, the founding editor of Wired magazine, on its book called Out of Control. Now this is the most influential book on me, and it has guided many of my investment feces over the last 20 years in technology development. It basically is a book that covers the dawn of the age of biology as the next phase of major technology vectors coming out of an age of physics, if you will.

Steve [00:09:29]
And these biological metaphors. Air right throughout Information Technology in Kevin Kelly very expertly explores the integration of these domains. So the injury things that this book was written in 1995 and it may have been 20 years ahead of its time. It was recently translated into Mandarin, and it is currently a bestseller in China, as if it were written today as if this was something that just went to a time capsule and now is really when it's hitting powerfully on our shores. So as an introduction to the power of evolutionary algorithms in information networks inspired by biology, Kevin Kelly basically explores what fundamentally are the underlying principles of complexity theory at the Santa Fe Institute. The properties of Emergence Self organization what some would call the wisdom of crowds when you have many people behaving as a team and outperforming as they would perform as just individuals or that of a hive mind, or how the social insects do what they dio, it motivates the benefits of exploring bio mimicry, basically learning from biology, especially in our information systems, like neural networks, what we now call deep learning or machine learning, which are basically recapitulating in silicon, the evolutionary and fetal development of our cognition. When you train these artificial neural networks, these layers are basically forming, much like they do in a fetus. Going back to the Elson. Gopnik basically starts with edge detection than symmetry. Subsystems eventually builds up to facial recognition and then identifying people's faces. These are different layers in the neural nets that form in that consecutive order, just like our infants. So basically.

Steve [00:10:54]
If you look at where Moores lost taking us and more computations thing us. We're now at the cutting edge of computational capture in biology, actively reengineering information systems of biology and creating synthetic microbes whose DNA is manufactured from bear computer code and organic chemistry printer. And the challenge we face in many of these synthetic biology domains is a question of what to built. So far, we've largely just copied large tracts of code from nature. But the question then spans across all the complex systems who might wanna build from cities to designer microbes to computer intelligence as all these systems transcend human comprehension. Basically, as we try to design more than we can comprehend more than we can understand, we will shift from traditional engineering to evolutionary algorithms and literate of learning algorithms like deep learning and machine learning. And as we shift this engineering to the training of these generative algorithms, the locus of learning shifts from the artifacts themselves to the process that created them. There is no mathematical shortcut to get through the decomposition of a neural network or to reverse engineer it or a genetic program. There's no way to reverse evolve with the same ease we converse engineer the artifacts of purposeful design.

Steve [00:11:59]
The beauty of these compounding bit of algorithms. By this I mean evolution fractals, organic growth art.

Steve [00:12:05]
That derives from their irreducible ity there. Computational, irreducible iti know mathematical shortcuts. And it empowers us to design complex systems that exceed human understanding. In short, we're re engineering engineering itself. It starts to look more like parenting than programming.

Steve [00:12:21]
And that brings us to the Age of spiritual Machines by Ray Kurzweil, inventor and futurist. I think this might be the most important book, and even, maybe more shockingly, I would say there is a single graph in the book.

Steve [00:12:32]
That itself makes this book the most important book one could read. And obviously therefore, it's simply this one graph the graph of the 120 year version of Moore's Law. So let me explain what I mean by this and also just mentioned, perhaps, and starting that it's really just the first few chapters of this book I'd recommend not the entire book that looks into the distant, distant future like the next 100 years, but really just the background, the historical section, and then let yourself make your own conclusions, and it basically this book introduces the best extraction of Moore's law that I've seen out there, one that is understandable, meaningful, even cosmological and has predicted power. So it is, I think, essential protect futurism, predicting where we're heading as well as business planning. As most businesses become technology businesses, understanding how to predict our future becomes all the more important. So the popular perception of Moore's law that getting Gordon Morrow from Intel predicted computer power getting better and better, basically, is this sense. The computer chips are compounding in their complexity at a near constant unit cost, So it's a sort of bang for the buck kind of representation. And but this is just one of the many abstractions of Moore's law. People have all kinds of different ways of defining it. You get different answers from different people, but it relates to the compounding transistor density and true dimensions. Other renditions of this Moore's law just relate to speed, like how many megahertz or gigahertz do we have in our chips that some of the early days when people didn't really know what they were talking about? And it makes sense that, you know, as you miniaturize a chip the distance traveled by any given signals less so. Everything runs faster where some people refer to computational power, which is basically speed times density because both benefits accrue as you miniaturize. So for a long time this was thought to be very specific intel.

Steve [00:14:06]
But unless you work for a chip company like Until and unless you focus on fab yield optimization, you don't really care about transistor accounts. Nobody goes out and buys a 1,000,000 transistors or give me a 1,000,000,000 transistors. That makes no sense, right? Integrated circuit customers don't buy that. They are basically consumers of technology, and they buy computational speed and data storage. That's what we care about. And quite simply, Ray Kurzweil in his book plots the calculations per second. The computational power counts per second that you could buy for a constant dollar. So again, adjusting for inflation over a long period of time and rehearsals. Abstraction of Moore's law shows that computational power has followed a smooth, exponential curve for over 120 years. Basically, since the beginning of data on any kind of computer is a straight line on semi log paper men, there's years along the X axis and a logarithmic scale of computational power per dollar on the Y axis, and it shows a geometrical compounding curve of progress when we cast. In these terms, Moore's law is no longer transistor sentry in this abstraction allows for longer term analysis. Similar is not specific to Intel.

Steve [00:15:07]
What more Gordon Moore, the person observed in the belly of the early integrated circuit industry, was a derivative metric, a refracted signal from a longer term trend, a trend that begs various philosophical questions and predicts mind bending futures through five paradigm shifts such as electro mechanical calculators and vacuum tube computers. The computational power that dollar buys has doubled every 18 months for 120 years. Every dot on this curve.

Steve [00:15:32]
Is basically on the frontier of computational price performance of the day. One machine was used in the 18 90 census. One cracked the Nazi Enigma cipher in World War Two. If you saw them with the imitation Game one predicted. Eisenhower's went into 56 presidential election. I've been updating this graph since basically the time of the book, which was a wild A while back and has basically found over the last 10 to 20 years that I've added to this curve the latest CPI use and specifically, and Video GP use. The graphic chips carry out this precise same curve of progress to the present day and that sort of extending Kurzweil's analysis. And I think, 20 years past when he stopped the curve. So every dot every machine on this curve represents a human drama. Prior to Moore's Law, which was first formulated in 1965 none of the people on the curve even knew they were on a predictive curve, right? It wasn't until Gordon Moore basically him with Moore's Law that we would have thought to even plot such a thing. And every Dot represents an attempt to build the best computer with the best tools of the day. Of course, we also use these computers to make better design software, better manufacturer control algorithms, and so progress continues. But notice that the pace of innovation, a straight line, imagine that for 120 years is exogenous to the economy. Think about how long this has held. True, the Great Depression, World War I, World War two in various recessions have not introduced any meaningful change in the long term trajectory. Moore's law. Certainly the adoption rates, revenue profits and economic fates of each of the underlying computer companies behind the various dots may go through wild oscillations. But yet the long term trends emerges nevertheless, as one technology such as the sea most transistor, the current technology de jure follows an elongated S curve of slow progress during initial development, upper progress during a rapid adoption phase and then slower growth from market saturation over time. But more generalized capabilities such as computation, which isn't tied. The one thing storage more generally banned with more generally, they tend to follow a pure exponential bridging across a variety of different technologies in their cascade of S curves.

Steve [00:17:24]
Well, in the modern era of accelerating change in the tech industry, it's hard to even find a five year trend with any predictive value. Yet let alone a trend that spans centuries. I would go further and assert, as I did, that this is the most important graph ever conceived. So why why don't think is the most important graph in history? Well, ah, large and growing set of industries depend on continued exponential cost declines in computational power in storage density. Moore's law drives electronics, communications and computers and has become a primary driver in drug discovery. Biotech, bioinformatics, medical imaging and diagnostics is Moore's Law. Across his critical thresholds, a former lab science of trial and error experimentation becomes a simulation science, and the pace of progress accelerates dramatically.

Steve [00:18:05]
Right, becoming an information business and creating opportunities for new entrance in new industries. That's why is a venture capitalist. I love it.

Steve [00:18:13]
Basically. Think of an example bowing building aircraft they used to rely on wind tunnels to test novel aircraft design performance. Ever since CFT modeling became powerful enough to simulate, this design moves to the rapid pace of inter of simulations in the nearby wind tunnels at NASA, Ames and all around the country, life fallow there aren't used for aircraft design. Ever since the Boeing 777 the engineer can operate at a rapid rate while simply sitting at their desk. Now every industry in our planet is going to become an information business. I think that's an important statement. Every industry consider agriculture. You ask a farmer in 20 years in the future about how they compete. It will depend on how they use information from satellite imagery driving robotic field optimization to the code, meaning the programming code in their seats. The genetic code. It'll have nothing to do with marksmanship or labor.

Steve [00:18:59]
Again. Nothing to do with their workmanship or labor. The historical basis of competition, perhaps in agriculture or a breeding line, right. It'll become eventually information business and that will eventually percolate through every industry. As information technology innovates the economy, it makes it have a nervous system. So interesting thing about Moore's law. Nonlinear ships in a marketplace are also essential for entrepreneurship and meaningful change. Technology's exponential pace of progress has been the primary juggernaut of perpetual market disruption, spawning wave after wave of opportunities for new companies. Without disruption, entrepreneurs will not exist. Moore's law is not just exogenous to the economy. It is why we have economic growth and an accelerating pace of progress at future ventures. My venture firm, we see this in the growing diversity and global impact of the entrepreneur ideas we see each year. The industry's impacted by the current wave of tech entrepreneurs are more diverse and an order banning to larger than those of the nineties. Today we're looking everything from automobiles, aerospace to agriculture and energy so that we might ask the question. As I said, it's almost cosmological. Why? Why would this trend hold for 120 years? I mean, it has nothing to do with the semiconductor industry. It is nothing. You were first told by Intel on others that this was something very unique and tightly coupled to how we do integrated circuits. Why, more generally does progress perpetually accelerating for humanity? That's a really important thing. By the way. That wasn't obvious. The people back in the pre agricultural period when bearded profits could only forecast doom where the occasional flood or natural disaster wiping out humanity, that was the perception of the world basically struggle through. Occasionally it wiped out by calamity. We now can understand, and hopefully those in technology fully understand that we are in a pace, perpetual progress. We keep getting better culturally, evolutionarily in the way that we live our lives in our overall happiness, in the amount of human suffering in our circle of empathy. We just keep making progress. How could that be? Why is that? Well, here's one simple possible explanation coming again back to Moore's Law as one canonical example. Why does this 120 year version of Moore's law perpetuate? Well? Consider that all new technologies are a combination of technologies that already exist. It's a re combination of prior ideas. Innovation does not occur in a vacuum. It is a combination ideas from before, Like standing on the shoulders of giants in any academic field. The advances today are built on a large edifice of history. This is why major innovations tend to be ripe, intend to be discovered in the nearly the same time by multiple people. Think about Edison Tesla, Marconi in history, all discovering massive major new innovations within months of each other. The compounding ideas is the foundation of progress, something that was not so evident to the casual observer before the age of science. Science tuned the process parameters for innovation. It basically became the best method for culture to learn. And the scientific method, I'm still assert, has been the greatest advance in human history on how we can let knowledge and how we make progress over time versus personal beliefs. You know, you name it right just saying, I think something's the case and having that be as valid as any other person's thoughts. So from this conceptual basis come the origin of economic growth in accelerating technological change. Think of it as the combinatorial explosion of possible idea pairings, which it grows exponentially as new ideas come in the mix. It basically grows in the order of two to the power of possible sub groupings by something called Reads Law. R E E D. If you don't look it up on Wikipedia, they say, explains the innovative power of urbanization and network globalization. It explains why interdisciplinary ideas. They're so much more powerfully disruptive than those who just come from the warmth of the herd. It's like the differential immunity of epidemiology, where islands of cognitive isolation think of academic disciplines with their own boundaries and vernacular are vulnerable to destructive means. Hopping across much like the South America was the smallpox, um, Cortez in the Conquistadors. If disruption is what you seek, cognitive island hopping is good place to start mining the interstices between academic disciplines. And it is this common a toile explosion of possible innovation pairings that creates economic growth, and it's about to go into overdrive. In recent years, we've begun to see the global innovation. Effects of a new factor. The Internet people can exchange ideas like never before. Long ago, people were not communicating across continents frequently, ideas were partitioned. And so the success of nations in regions pivoted on their own innovations. Richard Dawkins states that in biology it is genes that really matter. And we, as people, are just vessels for the conveyance of jeans. It's the same idea with names, names, meaning ideas were the vessels that hold and communicate ideas. And now a pool of ideas percolates on a global basis more rapidly than ever before. So I think we'll be entering a period of innovation like never before. And in the next 4 to 5 years, three billion new minds will come online for the first time to join this global conversation via inexpensive smartphones connecting in the developing world to satellite links from StarLink, this new product from Space six, and perhaps others.

Steve [00:23:59]
These people are not currently coupled to the global economy, any meaningful way other than Unilever, a Procter and Gamble. They're just out there doing subsistence farming and not communicating and not contributing the ideas that they might be able to contribute to the global conversation. This rapid influx of three billion people to the global economy is unprecedented in human history.

Steve [00:24:18]
And so, too, will be the pace of idea pairings and progress. We live in interesting times at the cusp of the frontiers of the unknown and breathtaking advances, but it should always feel that way, engendering a perpetual sense.

Steve [00:24:31]
Future shock.

Steve [00:24:35]
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 enough for me every Friday That provides a little morsel of fun before the weekend and fiber Fridays, every 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 have discovered it could include gizmos and gadgets and all sorts of weird ship that have somehow dug up in the world of the esoteric as I do. It could include favorite articles that I have read and that I've shared with my close friends, for instance, and it's very short. It's just a little bite of goodness before you head off for the weekend. So if you want to receive that, check it out. Just get a four hour work week dot com. That's four hour workweek dot com 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.

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