The Knowledge Project with Shane Parrish - #5 Chris Dixon: The State of Venture Capital

Episode Date: November 13, 2015

In this episode, a16z partner Chris Dixon and I discuss the history of venture capital, artificial intelligence, what makes a great entrepreneur, and why companies fail. *** Go Premium: Members get early access, ad-free episodes, hand-edited transcripts, searchable transcripts, member-only episodes, and more. Sign up at: https://fs.blog/membership/   Every Sunday our newsletter shares timeless insights and ideas that you can use at work and home. Add it to your inbox: https://fs.blog/newsletter/   Follow Shane on Twitter at: https://twitter.com/ShaneAParrish Learn more about your ad choices. Visit megaphone.fm/adchoices

Welcome to the Knowledge Project. I'm your host Shane Parrish. I'm the author of the Farnham Street blog, a website with over 70,000 readers that's dedicated to helping us learn by mastering the best of what other people have already figured out. In the Knowledge Project, I interview amazing people from around the world so that we can all learn from them, expand our minds, and challenge our thinking. On this episode, I have Chris Dixon. Chris is a partner at perhaps the most famous venture capital firm in the world.

Andresen Horowitz, or commonly known as A-16-Z. We talk about the history of venture capital, why companies fail, the future of artificial intelligence, and the idea maze. I hope you like this interview as much as I did. I'd love to hear your feedback. I'm at Farnham Street on Twitter. That's at F-A-R-N-A-M-S-T-R-E-E-T on Twitter. Chris, thank you so much for coming on.

Thanks for having me. I'm wondering, what's a typical day look like for you? For VC? Yeah, so it's a good question. It's an interesting job. I think, I guess I would divide my calendar somewhat between, I guess, two broad categories of things. One would be meeting with entrepreneurs who are starting companies and raising money and coming to us to talk about potentially investing. And then the other half of the time working with existing investments to try to help them, you know, everything from maybe they're raising more money or they're trying to recruit somebody or close a sale or some other kind of thing like that.

So roughly, I would say kind of half and half kind of looking for new things. What that means is basically a lot of meetings. So it's a big change for some people. Like I had a background in computer programming. There's a great Paul Graham blog post. It's called like Maker Schedule and Manager Schedule, I think, where he can contrasts kind of the schedule of somebody who builds things. So like a computer programmer or a carpenter or what have you versus sort of a manager.

And VC is very much manager. So it's sort of one hour scheduled meetings as opposed to kind of, you know, eight hours of getting into a flow state and thinking about a topic. So the bad part is it's sort of a lot of state switching and kind of jumping around. The good thing is, it's a fascinating job. You get to meet with incredibly smart and passionate people who are doing interesting things and they tell you all about what they're doing. So, you know, if you're kind of like intellectually curious, it's a pretty amazing job

because it's sort of, you know, one minute someone's telling you about some breakthrough in biotech and the next minute you're talking about. data center infrastructure and the next minute you're talking about computer security the next minute you're talking about you know I don't know what the transportation industry you know you name it so it's a fun job sounds amazing can we just back up for one second just so I don't make any assumptions here so you work for like a venture capital firm A16 Z I'm an outsider can you explain like what does that mean yeah so so yeah I work for

it's interesting Horowitz which is the shorthand is A16 Z it was a firm founded in 2009 by Mark Andreessen and Ben Horowitz. Mark and Ben both prior to that had Mark had co-founded Netscape which you know was the first kind of commercial popular internet browser and then they went on to do a bunch

of other interesting startups. So, and maybe if you want to I can kind of back up and tell you what venture capital is more generally and a little bit of the history of it. Would that be helpful? Yeah, that'd be awesome. Great. So basically venture capital, I mean as an industry started in the, I don't

know what the 40s and 50s or something I mean the kind of the practice goes back further if you go back and look at kind of wealthy you know entrepreneurs even in the you know whatever 200 years ago a lot of them after they made money would then invest in new you know and other entrepreneurs who didn't who maybe had a good idea and some good new technology but not enough money to to run it so actually I just read a great book recently about um it was how the world was won it was about the laying of the first transatlantic cables in the 1840s, you know, which they actually laid the tables onto the ground. And, you know, if you read about all those things, they were always funded by, you know, some cases governments, but a lot of times some crazy, you know, an entrepreneur

who had made money and then was investing in some other new thing, right? So there was always this practice going way back. But then what happened is in like the, really, I guess really in the 1960s, it became kind of formalized as an industry called venture capital. And there were firms kind of around, it all happened in Silicon Valley, around, you know, the rise of firms like Intel, Apple, you know, those kinds of things at Microsoft. And there were firms like Sequoia and Kleiner Perkins and other firms that basically started off as people investing their own money in new technology companies. And then at some point kind of became formalized and became the way it works today,

which is today we don't really invest our own money. We invest other people's money. specifically we invest you know a lot of our money comes from places like universities but you're not investing your own money no no we know so most vc's i mean we do invest our own money in the so the way it works is we have a fund and we raise money for a fund some of that money does actually come from us personally but but a lot of it doesn't a lot of it comes from like for example large large universities a lot of this is pioneered by places like yale for example very famously um started doing this in the 60s where basically they have you know they have their

endowment. You might read about it. You know, Yale has a large endowment. And they basically, you know, they put some portion of that in bonds and some portion in stocks. And they want to put some portion into, you know, other asset classes, as they call them, that have long-term horizons. So basically what's nice about those, about those pools of capital is that they, you know, they kind of plan things out in a 10-year, even 30-year horizon, which matches kind of our time horizon. So basically, that's what this industry is. actually, you know, it gets a lot of attention in the press venture capital, but it's actually a very small industry. So, you know, there are probably, there are a few dozen kind of firms that most

people, you know, that constitute the majority of the industry, maybe a few thousand people work in the industry at the most. The amount of money invested is on the order like 10 to 20 billion per year, which sounds like a lot, but it's actually smaller than, you know, the R&D budget for a lot of, you know, for Apple and Google, for example. So as much as it gets a lot of press, it's actually a very, it's actually would most people consider kind of a cottage industry. The tech world, I mean, it seems pretty clubby

from the outside. To what extent is that true? Yeah, I guess it depends if you ask. The cynics would say it is clubby and kind of, you know, insiderish or something. I think my, you know, I would argue, my feeling is it's actually, it's small and people know each other,

but it's but but it's there's a there's an ethos of kind of inclusion anyone who's worked in the tech industry for more than a few years has seen people rise media like like like you know incredibly quickly um so you know I knew you know take people like Mark Zuckerberg or all these kinds of entrepreneurs like this like anyone who's worked in the industry for 10 years has met these people has met you know people like that who are now incredibly prominent back when they weren't. And it's very used to kind of new, very successful people coming out of nowhere. And as a result, the industry is very, I think it's very sort of inclusive and people just sort of expect, you know, new things to pop up. And people are very responsive, I think,

to, you know, I don't know, new people kind of coming. It's, it's a, everyone there in Silicon Valley. And by the way, Silicon Valley, but I think it's also that kind of spirit is now happening in places like New York and L.A. and Canada in Europe and Asia. Do you think that's a byproduct or do you think that's something conscious? like people are trying to develop the same culture or do you think it's just happening naturally? Why is it? Why is it spreading? I think part of it is people, people see the success to Silicon Valley and want to emulate it. I think part of it is, you know, I see a lot of people who move to California to join the tech industry and then decide they, you know,

it's too much of an industry town and then they want to move to New York, for example, to have more diversity. And, you know, to have, you know, what's great about places like New York and L.A. as an example, I spent time in both places, is, you know, you're surrounded with people that are in the arts and media and all sorts of other kinds of industries, and that kind of creates a different creative dynamic. And so I think it's just the natural kind of maturation of an industry, and as it spreads out, you have it kind of propagating to more places. I mean, China and there's other specific things like China is its own story, probably, where it's a country that sort of decided that tech is strategic and has invested heavily in it.

So it's a multifaceted kind of story there, I think. So the firm that you're a partner at A16Z has a stellar reputation. I mean, how did that come about? What do you guys do differently? Yeah, well, so, you know, the kind of philosophy of the firm is a little different than I think than the traditional philosophy in the industry. So traditionally in the industry, there were basically, there were very few venture capitalists. And so what happened was if you were an entrepreneur, you had to go.

And you had to, you know, basically go to one of these 10 or so firms and pitch them your idea. And, you know, I think these firms, they kind of thought of themselves like the little bit of the way that maybe a hedge fund things of itself as their job is to come up with theories about where the, you know, the future is going and, you know, pick the best entrepreneurs. And then once they invest, they kind of hang back and kind of monitor their investment in the same way that a hedge fund or someone might. With our firm, we've kind of, we think we've kind of flipped the model where we think of ourselves primarily. primarily as a service firm. So we think of ourselves a way of maybe a law firm or a talent agency or someone would, where our first job is

to provide services for the entrepreneur. And so we, you know, and our secondary job is to sort of pick the right company. So the service we provide for entrepreneurs, we basically have, we're staffed very differently and structured very differently than most you see firms. We have over 100 employees

who are not investors at our firm who's sole job it is to help companies do things like recruit employees, you know, build their, you know, their customers base. So now that people are seeing success with that, are your competitors copying that model? I think to some extent it's also, it's a very different financial structure. So it's hard to copy because we basically, the traditional structure is basically that VC funds charge fees and then most of those fees go to the partner salaries.

We don't, instead, we put our fees towards. these operating teams. So for our competitors to copy us, they'd have to kind of dramatically change their own compensation and pay structure. Which isn't likely, right? Well, I mean, I think what it ends up, I mean, I think we are seeing probably, I think you will see more and more of our kind of style. I think it will probably come from newer firms. And, you know, look, I mean, my broader view would be, I think it would be great. If more firms did what we did, I mean, yes, it would be competition on the one hand,

On the other hand, I think it would be good for entrepreneurs and good for the... Better for the system, and it was... Yeah, it's better for the system just to have kind of... It's just more alignment between the investors and the entrepreneurs, and investors acting themselves more like entrepreneurs who are taking risk. Right. You know, and our sort of compensation is aligned with the entrepreneurs. Like, we basically, you know, most of the money, if we make money on this,

will be because our company is successful, not because we collect fees. Right. So, yeah, and, you know, so we've worked very hard to help entrepreneurs. which we think is primarily where hopefully, you know, our positive reputation comes from. It seems like from an outsider's perspective that companies are staying private longer than longer in the funding cycle than they ever have before. And the valuations for some of these companies, I mean, before they, the rumored valuations, before they become public like Uber at 50 billion or something, what do you see as the implications and second order effects of this?

This seems like an unprecedented kind of scale. That's a great question. So, I mean, part of the answer is why are they doing it because they're able to do it? Because basically what you're basically seeing is that if you read the press, they kind of confuse this issue a lot. They say that VCs are investing in companies like Uber at later stages. Actually, I mean, we don't do those kinds of investments for the most part. It's actually what is what is happening is firms that are that historically have been public investors. So, for example, Fidelity, Tiber Price, like a whole Wellington, all of these kind of well-known public market investors have now moved to invest in private companies.

And so they're sort of the firms that are leading a lot of these late-stage investments. And basically, for a variety of reasons, I mean, so it's a complicated story. One reason that companies are staying private longer is the perception among the technology community that the public markets are somewhat short-term focused. So, you know, if you look at, if you just go read whatever the, you know, Barons or the Wall Street Journal and things, there's an extreme focus on kind of what happens next quarter. Do they make their, you know, their numbers that quarter as opposed to are they investing for the next, you know, five to ten years? I just push back a little on that. Like, aren't fidelity and like the TRO prices of the world who control, you know, hundreds of millions, billions of dollars and shares in a company, aren't they the ones that could be setting? that in the public market to drive the expectations to be longer term?

Yeah, no, that's a good point. And I think that that would be the, that would be a good counter argument. And this is a, and I'm not saying this is a subtle question. I think this is sort of two sides of the debate. So one side of the debate would say that public market investors are short-sighted. The other side would say what you said exactly, which is, you know, there are these very long-term investors. And like, and to your point, look at Amazon as an example where, right, it seems as

So the investors have accepted the idea that they'll be investing for the long term and forego profits for a very long time. So, you know, but there is on the flip side, you know, Facebook and Google most prominently they have dual class stock, which is, which means that they basically, when before they went public, the founders, you know, structured it so that they could never, basically never get fired by Wall Street. Right. What do you think of that?

I think it's great. I'm a proponent to that. you know, it's a, if you just look at what's happening, I just don't think, I don't think you can plan technology investment on a, anything shorter, like just the way technology products life cycles work. I think it works on a minimum of, let's say, three to five year cycle. Okay. And I just think it's very, very hard to have that kind of managed by a committee. So I'm not saying that those founders, you know, it's less, it's less that they have sort of superpowers and more which is simply that you really need sort of a small group of people or one person who's

managing for a very long-term horizon. And it seems to be, I mean, if you just look at, I don't know, I just look at what Facebook and Google are doing right now. I mean, I also have specific experience with some of these companies where it's just, you know, I don't want to name the specific companies, but some of these public companies, which where I think the CEOs felt like they were, you know, completely handcuffed or something, just simply couldn't make the kinds of investments they want to make. So I don't know.

I generally think things need to be, in technology, things need to be planned on a longer term horizon. There are a variety of different ways you could accomplish that. One of them is dual class stock. I mean, there are other proposals out there, for example, to increase, you know, short-term capital gains. to disincentivize short-term trading. I think that's another good idea. There's a variety of kind of proposals out there. I do think, though, that in general, that long-term planning, long-term thinking is very

good for us as a industry, country, you know, world. Yeah, I'm a proponent of long-term thinking. And I think dual-class stock is one mechanism to get there. I don't know if it's the best mechanism, but I think it's one of them. So I have a question, but maybe you can explain funding right before that. But my question is, like, to what extent is the first round of funding really about preserving optionality for the future so you can double and triple down on success? Or is it more about funding the idea fully? Or like, maybe you can walk me through some of the thinking.

From the investor, from the venture capitalist perspective? From your perspective, yeah. I mean, I don't even have a, what are the stages and why would you invest at a particular stage? And what are you looking for? Just briefly, yeah. Yeah. So basically there's, I mean, just some quick nomenclature. There's generally like what's called seed investing, which is, you know, one or two entrepreneurs, you know, maybe a couple and an idea. And that's also called angel investing sometimes. And usually it's people writing, you know, individuals writing checks or small firms. And maybe they'll raise something like a million or two million dollars. And that kind of gives them enough money to build a small software team that can build a first product. Okay. And that's, that's something I used to do. At A16 Z, we don't do much of that anymore. We do some of that, but not as much because we have a bigger fund. And we tend to focus on what's called Series A and Series B. And so Series A is usually after a company has built like an initial version of a product

and is now ready to build, kind of build out the product more and start selling it or taking it to market. Series B is usually a little later when they've got some initial results. and now we're trying to accelerate those results. And those will typically be in Series A, let's say, you know, $10 million might be an average investment size. And the series be $20 million or something like this. And so. And your Series A deal usually includes the first right of refusal, I would guess, on further funding or? Yeah.

Yeah. It usually lets us have what we call pro rata rights, which means we're allowed to invest a certain portion in the next round of funding. And mathematically, it's like a. enough that we can preserve our kind of ownership percentage. Is it your equity? Yeah. So basically it's like a, yeah, it just lets us kind of keep investing a sum, not a whole, not the whole round. It's kind of technical.

But basically the idea is just that we have the right to kind of keep investing some amount. Yeah. So that's usually, the industry's changed a lot. Like in the past, maybe 10 plus years ago, VCs would actually take control of a company and in many different respects, including the board of directors. like a hands-on kind of yeah and well it actually could like there's all these horror stories of like them firing the founders and things oh wow that that's not something that we do we really just don't even take control for the most part most of us do now we don't we couldn't we couldn't fire the founders if we wanted to not that we do want to but we couldn't and if you got a reputation for that

you'd probably stop seeing deals right you'd have very short yeah for air basically so not that we want to but even if we did it's just it's just not the norm to to have those kinds of provision. So basically, for the most part, it's a very simple transaction. It's actually, in all the areas of finance, it's relatively, it's probably the simplest, which is we give somebody, let's say, $10 million in an exchange. Let's say we buy 15 to 20% of the company, which means if the company sells for, you know, whatever, and million dollars, we get 15 to 20% of that. For the most part, that's kind of what it is.

There's a little bit more structure. There's things called preferences, which basically means that we get paid disproportionately more on the down, on certain downside cases and things like this, but it's relatively simple. To what extent in the, you say you do more series A than angel investing, and if I understood what you were saying correctly, you're more investing on people in the angel stage? I mean, to what extent in the series A are you investing in people versus investing in the idea? Great question. I think it's series A, it's definitely, certainly people is 90% of it. And the idea is also important with the proviso that the idea will, at that

point, we know it will change. So it's kind of more like you're investing in the general direction of the idea. Because just the world changes. I'll just give you something. Like, you know, I remember when Dropbox, I'll just take an example, raise their series A. I think it was like 2008. You know, and at the time, it was, you know, it was really pretty mobile. I mean, the iPhone had come out, but it was, it was, you know, much less widespread than it was today. Right. And so, so, And so, you know, if you look back at the original pitch deck for that company, or let's say for Facebook, for that matter, or LinkedIn, or all these companies today, Pinterest, none of them really had mobile as a big part of their business plan because mobile just

wasn't, you know, it was still feature phones, right? It was still like those little Motorola phones where you type the, you know, you have the little keyboards and stuff. And so the world, the computing world dramatically changed in the, you know, in the last seven years. And so all of those companies, so, you know, so if you invested in those companies early on, like a Facebook, you knew you were investing in a social network. You didn't know you're investing in a mobile apps company that eventually would buy a messenger and buy Instagram and

all the things. Right. So I would say you kind of directionally you're investing in an idea and you're investing in people, but you also know the world will change dramatically in unexpected ways. And so, you know, what you really are kind of looking for, it's kind of like, you know, these kind of black swan anti-fragile ideas of you're really looking for kind of, you know, what some people call, you know, optionality, meaning things which, you know, you know, you don't, you can't predict the future, but you can see that there are certain scenarios where, you know, this, these people, you're disproportionately rewarded. Exactly.

I mean, so like the, that's the thing you have to understand. It's hard to understand about the model of VC. It's very hard to internalize, I should say, which is that the best VC funds lose money at least half the time, which means half of our, if we're doing a good job, half of our investments will fail. Right. And then some small portion will be huge. hits and some other portion will be modest hits or something.

I wonder if most people even get that in the stock market. Yeah, no, it's very, it's very skewed in that way. And in fact, it's interesting. I wrote a blog post about it if anyone's interested in my website c.dixon.org called the Babe Ruth effect. And it actually, we have data. I remember reading that, yeah. Yeah, there's a lot of data in the VC industry that actually, interestingly enough,

the best firms actually have a higher loss rate, meaning they lose money more frequently. than the less... But when they win, the magnitude is so much greater. Exactly. So it's like, I don't actually, I'm not a big sports guy, but in baseball, you know, it's what you call slugging percentage, which is sort of on runs you hit, even if you have more strikeouts, the two tend to be correlated. So it takes, it's sort of an unnatural way to think in some ways because when you meet

entrepreneurs, you're not, you're sort of thinking somewhat like, will they succeed? But you're also thinking probably more about if they succeed, how big could it be? get. And so you have to kind of train yourself to think that way. And frankly, train yourself to be accepting that a lot of what you do will fail. And it's a little bit, it's just, it's one thing to realize that in the abstract and to write a blog post about it like I did. It's very different to actually experience it because these entrepreneurs are your friends and you know, and you're rooting for them. And the reality of this job has spent a lot of time kind of helping people in tough situations. So if you had to group the failures into kind of three buckets between leadership

execution and idea, what percentiles would you kind of put on those? I think that's a good question. I guess it depends on the stage. It's very different at different stages. But there's some reasonable percentage of the time where the entrepreneur kind of does everything right and just the market, you know, whatever. It gets, you know, bundled into, you know, Google, releases the same product and gives it away for free or something, right? Whatever it might be that, you know, just sort of like things happen that are beyond your control that just make it, you know, or regulators just decide it's, you know, you create a new kind of drug and the FDA decides it's, you know, not to, not to approve it or something, you know,

like there's certain things are just external factors and that's probably some, you know, it's like, I don't know, I'm just making up a number 25% of the time. There's some external factor that is completely beyond your control. And then I think some portion of the time, the sort of the hypothesis is wrong about the product and the market. And that's a pretty high percentage of the time. I think then the question becomes, you know, I think with really good entrepreneurs, they're able to kind of adapt then. And, you know, as some people call it a pivot or something where you change what you're doing. And so, you know, that's always an interesting kind of scenario.

but I would say my overall learning having done this for I don't know eight or nine years now as a I'm not I've only been to VC for two and a half years but I was investing personally before that for whatever six and a half years um successfully to you am I done it was pretty good the I would say my biggest learning is it's it's probably more people than I ever like I probably thought originally it was 70% people and now I think it's 98% people or something like it's a lot people. That kind of begs the question, like, what's the difference then between a bad founder and a good founder, so to speak, not to categorize them, but... Yeah, I think a lot of it is not necessarily that they're good or bad, but it's how, it's what we have a concept we call

product market, I'm sorry, founder market fit. So the kind of fit between the founder and the market, meaning, you know, kind of are they uniquely suited to do something in that market? And so a lot of times in our business, that means they have a strong technical background. So maybe, you know, they have a Ph.D. from Stanford and MIT and computer science. Right. Probably, frankly, I don't know, a third, if not half of our investments are like that. Are people just with very, very strong technical backgrounds who, you know, I worked in a lab is very typical stories.

I worked in a, I was at Berkeley, and I worked on in their big data lab, and I invented this new, you know, open source data analysis tool. And now I want to go make a business out of it. And that's literally a company we funded called Data Bricks, which is a technology called Spark. Like, you know, that's probably a third to half of our company. So someone with very, very deep expertise. And then they have to learn, you know, they're obviously their background as in, let's say,

computer science or some other technical field. They have to then go learn kind of how to run a business and how to hire people and how to, you know, get customers. But, you know, we kind of make the assumption that that's easier to learn than the opposite. It's easier to teach your computer science business and vice versa. You're never going to teach a business person computer science on the job, right? You have to go to school for that generally or have some kind of long work experience. So a lot of it is that.

It's like technical expertise. Sometimes it's domain expertise. So, you know, someone will come out of, a person comes out of, you know, the media industry or the fashion industry or you name it, right, whatever industry it might be and says, you know, I've been working in this industry and I realized, you know, there's a whole bunch of things that are done in backwards ways and I have ideas and how to improve them. And, you know, and it comes from years of experience and deep expertise in that field. That's another common one. You know, another one will be kind of like, you know, maybe like Airbnb where it's just, for whatever reason, it seems like those founders, you know, kind of were part of a certain cultural movement that was, you know, around, you know, just sort of maybe it was a generational thing. I don't know what it was, but people, you know, they had been sort of sleeping on friends' couches and things. Seeing that behavior emerge and sort of, you know, built out, you know, kind of rode that kind of, I don't know, that cultural wave.

So that's typically a very important, you know, that sort of founder market fit. I think also a lot of it is just, you know, tenacity. Almost all companies were involved with run to extreme adversity have almost never been involved with a company that didn't have moments of, you know, almost failure. And so it's how, you know, how resilient are the entrepreneurs and how do you, how do you go about determining that? Like, I mean, how do you go about testing their grit, their tenacity, or not testing? Yeah, I mean, it's a good question. It's a good question. It's very hard to do.

I mean, we do spend a lot of time with the entrepreneurs and try to get to know them. I think a lot of it will come in through their, through their personal backgrounds. You know, it's one reason why you'll, you'll see a lot of VCs will invest, you know, in repeat entrepreneurs as an example. Right. So, you know, like if you look at like, you know, Travis who founded Uber, you know, he had been involved and I think he started two companies before and, you know, had a long track record and people, you know, and he had varied levels of success. But people who knew him spoke very highly of him as a, you know, tenacious and resourceful founder. There's lots of examples of that of sort of people with some kind of track record. If they don't have a track record, it's hard. And it's, you know, and it's something you really don't know until, you know, the moment the adversity comes. What are the obvious things you're trying to avoid in founders? Well, I think at the moment, startups are having a moment of kind of pop culture trendiness or something.

There's a lot of news articles about startups and venture capitalists. It's become very sexy, right? Yeah, you know, in the social networking movie. So I think what we're having now is a bunch of people entering the industry who maybe are, you know, coming it for the wrong reasons, who come to, you know, try to make sort of quick money or something. and don't. And it's just really just not.

They don't appreciate how hard it is. And how do you pick somebody like that out? Like when they come and they present to you, how do you determine that, you know, oh, I think they're in it for the money versus I think they're in it because they're passionate about the idea or some other, you know, narrative that we want to wrap around that? Yeah, a lot of it's just depth of experience.

How, you know, how long have they been working on the problem? You know, I'll just give you an example. Like I was an early investor in Kickstarter. And, you know, have, you know, Perry and Anci and the founders of Kickstarter, they didn't have kind of the classic computer science background I described. Right. They had basically been working on the idea for, I'd say, seven years at the time.

Oh, wow. And, you know, had tried everything to kind of get funded and, you know, and had, and, you know, you talked to them and, and it was really motivated, you know, the original idea for Kickstarter Perry was, he was living in New Orleans and he was involved in the kind of music an art scene and had wanted to actually a service like Kickstarter for himself because he I think I think he had tried to organize a thing where like a band that he wanted to come play would come play and he had a bunch of fans who wanted to see them and he just didn't have a way to kind of coordinate the two things to have the fans put up the money he didn't have Kickstarter right right

and he kept thinking about that and he kept thinking about you know the the kind of going back in the history of the arts and the patronage model you know they're going back to the renaissance Italy and things and how the internet could kind of let you reimagine that model. And, you know, when you talk to him, so I think I invested, I don't know, when it was like 2008 or nine, when he was first starting, you know, it was clear this was a person who was, you know, this was his kind of white whale he'd been pursuing for, you know, forever in time. And you ask, you could tell, just you ask him questions and this was, you know, the depth of thinking. He had thought of everything. He had gone through. We have this concept we call the

idea maze. And the IDMAs is sort of the idea that the start-up ideas aren't really just kind of a static thing. It's kind of like, you know, you see the TV or the movies and they have the way they kind of, you know, have these, you know, someone has this epiphany and I imagine that it'll be like a, you know, a intermittent windshield wiper or something. In reality, it's much more of kind of a maze, meaning like, you know, you sort of imagine how the product might work, but then you imagine if the world responds in a certain way or the technology changes in a certain way, here's how I'll adapt, and you sort of imagine yourself traversing through a maze, and at various points in the maze, there might be a dead end, or there might

be a trap, or there might be a prize, or something like this. And you don't really know how the maze is going to turn out when you first start, but really obsessed founders will have thought through all the possibilities. And so a lot of what I like to do, at least in my, when I meet with entrepreneurs, is kind of try to traverse that maze with them. And understand the depth of thinking that they have you know kind of gone through to get there and so in a case like Kickstarter you know I mean it was just it was I mean like it was I'm not saying it was easy it was an obvious investment or that it was you know obviously going to work but I will say that like it was obvious that they had thought through very very deeply was a mission for

them it was not you know it was sort of a fun you know whatever a new career choice or something or something done for some kind of more mercenary reason. So I don't know, but the answer, look, is this is not, there's no great science to this. People have tried many, many times to use data science and other things to try to quantify these kind of questions you're asking, and the results have been pretty poor. It's been very hard to predict these things. I don't have. I was hoping you had like this secret recipe for us.

I wish I did. I've certainly tried. Many people have tried. But a lot of it's like any kind of creative endeavor. You know, how do you pick a musician early on? How do you pick, you know, a writer early on? There's certainly, like, having spent years practicing in the field is very helpful. But ultimately, a lot of it comes down to kind of an art, I guess.

So many things do you. So switching gears just a little bit here. What's one thing that you think the future holds that no one is talking? about? Oh, good question. I don't know about no one because I think... We're very few people then. I mean, maybe I could change the question.

Sure. Just say that some of the things I'm excited about. I mean, I think some of the investments I've made have been things that are somewhat unpopular. So for example, I'm not unpopular, but I would say I don't know what, controversial or I don't know. So I'm an investor in a company called Coinbase, which is the leading Bitcoin company. I'm excited for Bitcoin as an example, which I think is someone controversial. So digital currencies. I was an investor in Oculus, which Facebook, you know, which is a virtual reality company

that Facebook acquired. I'm very, very excited about virtual reality. How do you think that's going to change our lives, virtual reality? So I think it's the next day. I think it will be, like when we look back on the history of computing, it will be, the key milestones will be, I mean, this is, I'm at the extreme end of excitement here, but there'll be, you know, the PC, the Macintosh or something like this, then the internet was the other next key moment,

and then the mobile phone, like the iPhone, and then I think virtual reality will be the next wave. What about artificial intelligence? That's another interesting one. That's sort of separate but related. Okay. I'm happy to talk about that too. I think virtual reality, though, will, I mean, I don't know how long it will take.

You know, Oculus is going to release their, it's announced. They're going to release their consumer product. in the beginning of next year and I think initially for the first year or two it'll be primarily used by people playing video games but I think in the next few years after that it will be used much more broadly

I think it will be the predominant way that people at some point interact with computers and other people at long distances I think in 10 years we'd be probably having this conversation in virtual reality and we'd be looking at each other across the room and it would feel like we're in the same room

and, you know, I think it's going to have, it'll be, the implications are far beyond gaming and it'll be all kinds of, you know, I think movies, there's lots of interesting health-related applications, communications, social things. Do you think that brings the world closer together? I do. I think it will. I think it will, you know, there's some great videos on YouTube. I encourage people to go on there and check them out. If you just search YouTube for Oculus or virtual reality, you'll see a lot of them where, There's one the other day where it was a guy who was using virtual reality, a demo to experience. I think it was like the Apollo moon landing or something. And you watch these videos, people are literally crying at the end of the day. I mean, I've never seen a computing medium that has such a strong emotional impact.

Because, you know, in that case, it was a guy who had dreamed his whole life about seeing this. And he was crying. And he was like, I would never be able to see this in any other way. And, you know, I think it what it does. it lets people, you know, I think, like, I think, for example, a big application will be virtual tourism, so just going and simply, you know, visiting the Great Wall of China and the Taj Mah, all sorts of the kinds of things, and things which right now are very expensive and, you know, one of my favorite demos, I say demo now because it's all very early and

it's not, like, they're not full products, but is a thing called Ocean Rift, which is a, just, let's you just, like, scuba dive around the ocean and, and, and observe different, you know, aquatic the sharks and the you know underwater having the experience but not going right yeah yeah exactly so um you know i think it'll be all sorts of things like that i think actually the gaming side is probably in some ways overblown because right but we underestimate everything else you think i think so i think so that's vr so i'm very excited about that AI only talking about AI or yeah i'd love to hear more about that the singularity let's talk about this whole like so okay there's a lot to say about AI. So I think that, well, I think there's two things. When people talk about AI, they often

are really kind of talking about multiple things, right? So there's AI, like the, there's sort of like the how singularity, like when we have a talking computer. And then there's automation and like our, you know, computers take jobs away and things like this. So I think a lot of people have what I would call kind of a world's fair view of technology. So you remember like the World's Fair and I don't know if you see like the Captain America movie or a bunch of other movies where they show, you know, it was like Howard Hughes type guys and they're showing, you know, the Tesla coils and the Android robots and the flying cars. And so a lot of people, you know, a simplified way to think of technology is like the, you know, the robots are coming

and people are going to build robots that take away our jobs. If you actually look at how automation works, it's actually, I think, a lot more nuanced and less obvious. So I'll give you an example, like, you just kind of take any, almost any technology company that's on our website that we've invested in. I'll just take an arbitrary example, a company called benefits. So, benefits is a company, is a, you know, a web product that lets you, if you're a small business, go and, you know, sign up new employees for health care and other benefits, right? Right. So it sounds like, just like, you know, it's whatever, it's a benefit software, right? Actually, what it ends up doing is it ends up letting you hire fewer people at your

company because you now no longer have to hire somebody to do that job, right? So what I would argue is things like, like a lot of automation doesn't really look like automation. It looks like just regular software. That's a lot of ways what AI really is. It's sort of taking what smart people do and embedding it in software and giving that software out to lots of people. And so every new piece of software that you see in some ways is sort of a piecemeal form of AI. And then when you sort of when you combine it all together, what you get is kind of this broader kind of functioning super system of all the software interacting together. I think a lot of the real AI, the kind of the real automation ends up sneaking up on you. Now, there's this other kind of AI, which is the

kind of more spectacular stuff that you read about, which is, you know, it's the headlines. Yeah, you know, so Siri as an example, like, you know, which is speech recognition. And then, you know, Google's doing a lot of interesting stuff with image recognition. I do think this, this, this, this stuff is at a, a lot of people in Silicon Valley believe that this kind of AI is at a inflection point now, and specifically around a technology called deep learning, which is basically a, I don't know if you remember neural networks, so neural networks of the trendy, you know, there were a lot of books written about them and things in like the 90s, which are basically computer systems that were kind of designed to replicate the way that the human

brain does. Yeah. And it was sort of, held out as his promise and then it was and then it was sort of there was a letdown afterwards because it didn't kind of deliver the results people wanted but basically what we've now discovered is it turns out that if you do neural networks and you use a lot more computing power which we now have available because of Moore's Law which is the idea that basically all computing gets faster and cheaper very quickly over time basically if you take neural networks and you make them a lot lot, you know, a lot more computing power, a lot more storage, a lot more memory, a lot more networking, a lot more computing resources, it works really well.

And that's what, you know, a couple of years ago, Google did a very famous experiment where they basically took, I think it was on the order of tens of thousands of computers, had them study YouTube videos, and at the end of it, those computers were able to correctly identify cats, like whether it contained a cat with a very high degree of accuracy. That was one of the kind of results they released, that really shocked people as to how accurate it was because basically a lot of this stuff in AI and maybe if you use Siri as an example a lot of it is it's a relatively easy to get to like 80, 90% accuracy. It turns out if you just like a regular programmer downloads a bunch of open source software and spends a weekend.

You can make like a decent replica of Siri in like a weekend. Oh wow. Okay. But to get it higher accuracy on that is like exponential. 80% really quickly. And then it turns out all of the work is in the last 20%. So like self-driving cars is another good example where. If somebody tells you, oh, I saw a self-driving car and it was able to drive on the highway during daylight, that's actually not very impressive. And that's actually something that almost anyone can build. I mean, anyone with a programming ability can build. What's hard is all of the millions of edge cases. So by edge cases, I mean it's dark, it's raining, a dog jumps out, two dogs jump out, you know, a shadow that looks like a dog jumps out, like, you know, whatever.

Like, you name it. There's a million little special cases where. to learn all those different special cases takes lots and lots of additional effort. And so the kind of the big breakthrough with the cat video in Google was that they'd gotten kind of to this point of like 99% or something like that, which no one had ever gotten to before. It might have been 97. I forgot with the exact number.

But it was a very high number. And they've since gone on to do more experiments where they've done things that do like what they call image classification, which is basically take an image and describe what's in the scene. and the results are getting very, very good there. So, you know, you'll take an image and the computer will say, this is, you know, three children eating pizza and it's right, you know, and like things like that.

And so they've been a lot of really promising results. And it's still very early. I mean, you know, look at your phone and the autocorrect. And every day you'll see it make, like, ridiculous mistakes. I hate autocorrect. Right? I mean, like, so, you know, we can't make an autocorrect today that seems to work, you know. Even most of the time.

Doesn't even get the swear words, right? You know, so I still think we have a long way to go. I think the sort of the, I would call the laboratory results are very promising. Right. Those laboratory results require like 10,000 computers. Right. Yeah. It's unfeasible right now to have that, yeah.

That's right. So the one of the questions will be just kind of how long does it take for that kind of of computing power to, for the price to drop and become more ubiquitous. And, you know, there's Moore's Law, there's all sorts of questions around Moore's Law. Some people think Moore's Law is slowing down. I think one of the big potential interesting things here is what's called quantum computing, which is this whole new kind of theoretical area of computer, basically how to build computers that use quantum effects,

so things from quantum mechanics. I would say the optimistic people, including some very well-respected computer science professors at Stanford, for example, believe that in five to ten years we'll have quantum computing in the mainstream. If that happens, you could see a dramatic... AI will take off. It could lead to a dramatic acceleration in the performance of AI. There's a bunch of things. One of the reasons it's very hard to predict these technology things

is that you often have these things that have kind of feedback loops, which means like if we get quantum computing and if we, you know, and if we get, you know, that will let us compute things faster, which will let us store more, you know, and then we'll build store more data and And that'll have all sorts of second and third order effects on everything that's possible. It seems a very complex kind of feedback loop systems. And so if I had to bet, I think we're still pretty far away from kind of the singularity. But there are certain scenarios people can conceive of that it's much sooner. So with all these different companies, like how do you filter information and how do you do that personally? Like how do you know what's important and what's not important? Like how do you determine signal from noise when you're, you know, surfing the internet? That's a great question. I'm a huge fan of, you know, Twitter, for example. I use Twitter constantly. And for me, it's probably one of my most important work tools and that I've, you know, have a carefully curated list of people I follow who essentially I have, whatever it is, 2,000 of the smartest people in the world finding information for me and telling me what to read. That's how I view Twitter. So that's obviously very important. You know, at the firm, we have a whole bunch of different things we do, including, you know, lots of people.

that we interact with and that we talk to regularly. We try to do things like, for example, we have a big academic conference coming up in a few weeks where we invite 50 plus of the top computer scientists in the world to come and kind of do like a mini, almost like TED Talks or something at our firm. We do lots of outreach with academia and things.

We try to get involved also in like the open source communities, go to lots of events, do lots of press outreach, A lot of what we try to do is just kind of be in the flow of a lot of different, you know, interesting groups of people working on new things. Right. So what do you think people are focused on that it's a waste of time? Like, what do you think misplaced attention? Where would that lie?

Good question. So in the tech world specifically? Yeah, or in general, I mean, like, other than Donald Trump. I think that I'll give you, well, I guess I'll give you one example of the food industry. Right. So I'm an investor in a company called Soylent, which you may have heard of, which is kind of... Yeah, yeah, I've tried their stuff. Okay, so I think with Soilent, I mean, the idea with Soilent is that we're trying to create kind of what we would consider a scientifically perfect food.

Kind of the idea is you go and the guys, you know, have a team of scientists who went and read every scientific paper about nutrition and then design and built this perfect food. I think when you look at the food industry, there's an interesting movement. Soilent's one example. There's a bunch of other Silicon Valley startups that are trying to do new things around food. I think that's an industry, which is just a very backwards industry today. It's, you know, if you look at the U.S. right now, the diabetes and obesity are, you know, really at the epidemic level. And a lot of that's caused by, you know, excessive sugar and other kinds of ingredients like that. If you just go, you know, just down just down just now this morning trying to find something healthy to eat at the local store and, you know, everything is filled with junk and sugar and all sorts of other things.

And it's really just an industry built around advertising and marketing and distribution and almost no money is put into actually researching healthier and better foods. So that's something I'm very passionate about. I think you know we like to say sugar is into smoking so we think we need to look back

20 years from now people will just be stunned by the kind of foods that we ate today I think the whole organic food movement is a great thing I think I think that's mostly

only accessible to wealthier people so I think a lot of what I think is interesting are the people that are trying to think more broadly

about how to reform the industry not just for people that can afford organic food a lot of my friends would call that you know, the luxury of the rich, right?

Yeah, exactly. So, like, just what can we do more broadly? So that's an interesting one. I know, I'm very interested also in healthcare generally. We're doing a lot more, spending a lot more time, making investments in sort of areas that intersect between healthcare and computer science. And just think there's a lot of things there that, you know, if you just look at the statistics of, you know, why are health care costs going up so dramatically,

A lot of it has to do with the inefficiencies in the system. You know, everything from, you know, medical records are still kept on paper. You know, the insurance system is very complex and in many ways backwards. The incentives seem all over the place. Incentives are all over the place. It costs more and more now to, people debate the exact reason, but basically it costs more and more to create new drugs. Right.

So there's all sorts of interesting things there. I think they can be improved. I'm totally conscious of your time here where I'm nearing the end. I have three questions that I always ask everybody. So what's the one book you've read that had the greatest influence on your life? Oh, man. I think when I was in high school, I read Gertil Escher Bach, you know, Douglas Hofstetter's book. I don't know if you know that book.

No, I'm going to look it up now, though. So I was interested in computers since I was a kid. and this book was sort of it tied it tied together computers and philosophy and music and it for me it was really important because it really broadened my horizons and I ended up majoring I went to when I in college I majored in philosophy and that I think that book kind of got me to do that that would be that would be a huge one for me I also anything by Daniel Dennett do you know you read Daniel Dennett yeah like consciousness explaining of this stuff yeah this that kind of there was this whole kind of uh thread of, I think, you know, Oliver Sacks, who sadly just passed away and schooled. I used to just read all of those kind of popular science. No wonder, you're so smart. I don't know. Those are great.

Those are great teachers. So when I was kid, you know, whatever, high school, college, I read all those books and I, and those were all just sort of hugely influential on me. So what's on your nightstand right now? What are you reading right now that you're really into you? I just read, what's it called the three body problem? I just finished it. You've read this book?

It's this Chinese author It's a science fiction book It just won the Hugo Award or something It's really interesting book What else did I read? I'm reading, I just bought this Was it called The Martian Which is I guess this popular book

That's now made into a movie And I, you know, books are one thing I like to I'm not digital on books I buy only Oh, you're still physical. I just really like physical books I like having them on my shelf. I like the feeling of reading a book.

I don't know. I just, it's something where I'm in the same way. I live in this like weird world where, you know, I read physical books and then go out and buy a Kindle copy. Just because I can't keep every physical book, right? Like it's. That's true.

That's a problem. I just like the feeling of them. And it's also, I feel like I look at the screen too much as it is. Yeah. It's distracting too to have like the thing I, you know, I read on the iPhone and then I can like check Twitter. And it's like, it's too distracting.

Oh, I just read the Elon Musk book, which I thought was good. Sort of the biography of Elon Musk. Right. And, oh, I read a really good book called Sapiens. Have you heard of this? Oh, I heard of that book, yeah. Somebody else recommended that to me. It's sort of like, it's kind of like gun germs and steel, like one of these, I think

they're calling the genre big history where it's kind of the panoramic view of history and it's just the history of almost apians. I've heard that was amazing. Yeah, it was really awesome. I highly recommend it. And so you know what I'm trying to do with the Knowledge Project? Who would you like to see on the show? Out of anybody?

Yeah, out of anybody in the world. Can you narrow it down a little? No, like who would you like to hear me interview, I guess? That's a good question. I'm going to call them and tell them you recommend that they come on. It would be good. You know, it would be great is, do you know Venkat from Ribbon Farm? I do, yes, yes, yes.

He's one of my favorite writers. He's already agreed to come on. Oh, wow. Okay. Well, there you go. So I'm already, I have too much overlap. That's awesome. You know, you know who's incredibly brilliant is Ben Thompson. He has his thing. It's called Stretechari. Yeah, definitely. I just started following him on Twitter. Yeah, he's awesome. Well, thanks so much, Chris. This has been great fun. I really appreciate you taking the time.

Yeah, well, my pleasure. And thanks for having me. Hey, guys. This is Shane again. Just a few more things before we wrap up. You can find show notes at Farnhamstreetblog.com slash podcast. That's F-A-R-N-A-M-S-T-R-E-E-T-B-L-O-G.com slash podcast. You can also find information there on how to get a transcript. And if you'd like to receive a weekly email from me filled with all sorts of brain food, go to Farnham Street blog.com slash newsletter. This is all the good stuff I've found on the web that week that I've read and shared with close friends, books I'm reading, and so much more.

Thank you for listening.