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Speaker 1: This is Masters in Business with Barry Ridholds on Bloomberg

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Speaker 1: Radio Today. On the podcast, we have William H. Jane Way,

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Speaker 1: better known as Bill Janeway. You'll hear his whole curriculum

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Speaker 1: VITA in a minute, so I won't go into the

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Speaker 1: details on that. Uh. For those of you who are

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Speaker 1: interested in technology, venture capital, the history of financing, you

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Speaker 1: are about to sit through a master class in angel investing,

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Speaker 1: VC technology, how the world has developed to fund speculative innovation,

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Speaker 1: the proper role of government, of the private sector, of

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Speaker 1: the public markets. This is really a fascinating conversation, a

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Speaker 1: tour to force. I'm not exaggerating when I said we

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Speaker 1: have another eight pages of question. I could have kept

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Speaker 1: going for another hour of half, but I promised to

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Speaker 1: get him out of here fifteen minutes ago and we

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Speaker 1: still ran late. Um. He is tremendously insightful, with an

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Speaker 1: enormous breath of experience and thoughtfulness about what it means

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Speaker 1: to be a successful early stage investor in technology and

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Speaker 1: other fields. I think you're gonna find this to be

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Speaker 1: an absolutely brilliant, insightful, delightful conversation. So, with no further ado,

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Speaker 1: my conversation with Bill Janeway. This is Masters in Business

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Speaker 1: with Barry Ridholds on Bloomberg Radio. My special guest today

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Speaker 1: is William Janeway, better known as Bill. I think he

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Speaker 1: is the most important person our listeners may never have

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Speaker 1: heard of before. And that's only because some of the

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Speaker 1: things we're gonna talk about are a little inside baseball.

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Speaker 1: But let me give you a quick walk through of

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Speaker 1: his curriculum vita. He is currently a managing director and

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Speaker 1: senior advisor at Warburg Pincus, where he helped to develop

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Speaker 1: their Technology Investment division. Princeton undergrad got his PhD in

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Speaker 1: economics at Cambridge ultimately became the co founder of the

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Speaker 1: Institute for New Economic Thinking that he co founded with

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Speaker 1: George Soros. In two thousand and twelve, he published a

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Speaker 1: fascinating book called Doing in a Capitalism in the Innovation Economy,

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Speaker 1: and we're gonna talk a little more about that during

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Speaker 1: our conversation. He also helped to fund and create b

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Speaker 1: e A Systems. Is that an accurate way to describe that?

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Speaker 1: And we'll spend some time explaining how he a cash

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Speaker 1: investment of a little more than fifty million dollars became

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Speaker 1: a six point five billion dollar payout a few years later.

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Speaker 1: There's so much more stuff to go over. We'll we'll,

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Speaker 1: we'll get into it as we go. William Janeway, Welcome

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Speaker 1: to Bloomberg. Great to be here, Barry so I said

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Speaker 1: as in the introduction that many of the lay people

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Speaker 1: listeners may not know who you are. But let me

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Speaker 1: give a quote from your book by Mark and Reason.

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Speaker 1: UH currently a VC at Andreson Horowitz and essentially the

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Speaker 1: person who invented UH Netscape and and really created the

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Speaker 1: modern browser and the modern form of the internet. And

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Speaker 1: Reason said Bill Janeway is a key creator of modern

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Speaker 1: venture capital, and he tells an amazing story of the

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Speaker 1: intersection of economics and innovation. This book is essential to

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Speaker 1: anyone who wants to understand technology and how it's creation

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Speaker 1: will be financed for decades to come. That's That's quite

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Speaker 1: the endorsement, isn't it. It's a great endorsement. I have

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Speaker 1: a great regard for Mark, and he is one of

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Speaker 1: those rare people whose transition from building a business operationally,

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Speaker 1: which of course he did at Netscape and then opswhere,

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Speaker 1: to being a success will investor. It's a hard frontier

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Speaker 1: to cross. So let me ask you a simple question,

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Speaker 1: and I'm curious when people ask what do you do?

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Speaker 1: How do you respond to that? Well, it depends on

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Speaker 1: which morning I wake up. Some mornings I wake up

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Speaker 1: and it's a hundred percent Warburg Pincus. It's working with

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Speaker 1: my younger colleagues defining investment opportunity or thinking strategically about

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Speaker 1: where there's a hole in the market for innovative technology.

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Speaker 1: Sometimes I wake up and it's a Cambridge University day.

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Speaker 1: I'm deeply embedded in the economics department at Cambridge, which

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Speaker 1: is playing a key role in creatively responding to the

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Speaker 1: global financial crisis of two thousand and eight, which woke

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Speaker 1: up a lot of minds, a lot of economists who

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Speaker 1: have been living in a kind of fantasy world of

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Speaker 1: perfect expectations and efficient markets. So that's another part of

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Speaker 1: my life, and that, of course, is where the Institute

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Speaker 1: for New Economic Thinking comes in and and sometimes I'm

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Speaker 1: very much involved with the Social Science Research Council, a

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Speaker 1: not for profit based here in New York run by

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Speaker 1: a great social scientists named Irak cats Nelson, and where

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Speaker 1: we're creating an environment where economists can feel comfortable interacting

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Speaker 1: with other social scientists rather than playing at being sort

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Speaker 1: of physicists because they've got the math, and so these

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Speaker 1: different lives intersect and they keep the neurons talking to

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Speaker 1: each other NonStop. You know, I've long said that economists

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Speaker 1: have suffered from physics envy. You know, physics and astrophysics.

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Speaker 1: They can land a rover on a comet a billion

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Speaker 1: miles away. Economists don't quite have that practical application of

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Speaker 1: their models. Something you've been critical of and said economics

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Speaker 1: needs to move from a theoretical practice to something more practical. Well, here,

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Speaker 1: here's the problem. Economics is just so much harder than

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Speaker 1: physics because look, the molecules. The molecules don't have consciousness,

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Speaker 1: they're not aware of what they don't know. But every

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Speaker 1: human being, except for maybe an extremist who might be

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Speaker 1: running for president, wakes up in the morning knowing that

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Speaker 1: not only does she not know what the consequences of

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Speaker 1: her actions are going to be, but nobody else does either.

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Speaker 1: And frankly, that is the lesson I deeply learned when

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Speaker 1: I was a graduate student at Cambridge studying under the

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Speaker 1: students of the great John Maynard Keynes. The central thesis

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Speaker 1: of Cames's economics was making decisions that you have to

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Speaker 1: make about committing money, whether it's to household goods or

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Speaker 1: investment in new stuff, where you know that you can't

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Speaker 1: know what the return is going to be, so people

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Speaker 1: do the best they can, and all too often the

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Speaker 1: result is a mess. That's why to us in an

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Speaker 1: eight to me for economics and for everybody dependent on economists,

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Speaker 1: two thousand and eight was the gift that keeps on

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Speaker 1: giving a wake up call. To say the least, it

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Speaker 1: taught us humility about what the great hyak cames as

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Speaker 1: rival and friend called the pretense of knowledge we pretend

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Speaker 1: we know in our models more than we can, and

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Speaker 1: bringing back into the reality of decision making under uncertainty

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Speaker 1: and how that scales up into failures of coordination. That's

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Speaker 1: what new economics is about, and that's why I'm so

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Speaker 1: thrilled forty years after I left Cambridge to be back

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Speaker 1: involved in economics, having spent that time making decisions under

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Speaker 1: uncertainty about information technology venture capital. You're listening to Masters

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Speaker 1: in Business on Bloomberg Radio. My guest today is William Janeway.

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Speaker 1: He is a venture capitalist and author of the book

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Speaker 1: Doing Capitalism in the Innovation Economy. I want to pull

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Speaker 1: a quote out of the book and discuss something you

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Speaker 1: had written some time ago. The innovation economy emphasizes the

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Speaker 1: strategic role played by the state and by financial speculators

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Speaker 1: sources of investment unconcerned with economic value. Explain that a bit.

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Speaker 1: So when you're operating at the frontier, you're making investments

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Speaker 1: in new stuff. Maybe it's building railway networks, maybe it's

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Speaker 1: putting fiber optic cable in the ground, or maybe it's

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Speaker 1: trying to find out what this new stuff is good for.

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Speaker 1: The one thing that you share with other investors at

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Speaker 1: the frontier is you don't know what the return is

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Speaker 1: gonna be. You can't. You can you can run a

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Speaker 1: spread street. Anybody can run a spreadhet. Those are those

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Speaker 1: are really assumed numbers, and you know, when you start

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Speaker 1: out with that basis, who knows where it goes. So

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Speaker 1: if investment that the frontier is limited only to where

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Speaker 1: you have a really high degree of confidence that you're

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Speaker 1: gonna make a profit, you're not gonna have very much investment.

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Speaker 1: So there are two forces that historically, this is his

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Speaker 1: this is history, this isn't theory. Historically two forces have collaborated,

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Speaker 1: have intersected. One is governments driven by political missions, legitimate

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Speaker 1: missions that transcend cost benefit analysis economic calculation. Manifest destiny

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Speaker 1: is what we called it in the nineteenth century when

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Speaker 1: we took nine percent of the land mass of the

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Speaker 1: lower forty eight states and gave it to a bunch

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Speaker 1: of railroad promoters who criss crossed the country with railroad

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Speaker 1: lines on the basis of which came Railway Express and

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Speaker 1: Sears Uh Sears, Roebuck and cantal Monk created the the

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Speaker 1: the mail order retail economy, created a national market. The

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Speaker 1: state moved the technology building that network out to the

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Speaker 1: point where speculators could fund the exploration of what to

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Speaker 1: do with that. They mobilized capital on a scale that

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Speaker 1: those rational, careful green eye shade investors would never have done.

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Speaker 1: We saw exactly the same thing in the ninety nineties

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Speaker 1: when we built out the Internet and we had, you know,

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Speaker 1: two hundred dot coms that went bust, but we were

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Speaker 1: left with Amazon and Google and eBay. Amazon took two

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Speaker 1: point two billion of cash investment to get to positive

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Speaker 1: cash flow and transform the retail economy of the world.

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Speaker 1: You could only do that with speculative money. That is

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Speaker 1: investing to get out in time before the bubble bursts.

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Speaker 1: We can talk about bubba. So let's talk about bubble

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Speaker 1: right now. You mentioned railroads. They eventually be am a

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Speaker 1: giant boom and then collapsed just a handful of survivors.

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Speaker 1: In fact, every major technological innovation, it seems there's a

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Speaker 1: huge boom, it reaches a point of speculaive excess, becomes

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Speaker 1: a bubble, and then collapses. Whether it's cars that were

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Speaker 1: a hundred card manufacturers at one point, what are there

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Speaker 1: now three or four in the United States and a

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Speaker 1: couple of dozen worldwide computers, radio and television, and of

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Speaker 1: course the internet. Is this the nature of technology that

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Speaker 1: boom bust cycle. Well, first, the first thing, the first

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Speaker 1: law of bubbles is wherever you have markets in tradeable assets,

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Speaker 1: from tulip bulbs to beach houses in the Nevada desert.

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Speaker 1: Wherever you have market, you're gonna have hurting behavior. You're

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Speaker 1: gonna momentum investing. You're gonna have people who, just like

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Speaker 1: today with the unicorns, are motivated by fomo fear of

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Speaker 1: missing out. And by the way, when you have professionals

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Speaker 1: managing other people's money, if they don't follow the bubble,

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Speaker 1: they get fired, the money gets taken away, so somebody

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Speaker 1: else does. So bubbles are banal. There are indogenous, they

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Speaker 1: are ubiquitous. Everywhere you look in the history of finance

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Speaker 1: you find bubbles. But not all bubbles are the same.

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Speaker 1: So before we go into how bubbles differ, I have

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Speaker 1: to ask you a question. I'm going to assume that

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Speaker 1: you believe Himan Minsky was correct. Well, you know, Himan

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Speaker 1: Menski was a mentor of mine during the thirty five

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Speaker 1: years when I was totally immersed in venture capital investing

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Speaker 1: on the side, I kind of kept my mind open,

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Speaker 1: listening and looking for people who for thinkers, who who

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Speaker 1: who wrote and analyze the world I was actually living

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Speaker 1: in and I met Hi Menski in about two We

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Speaker 1: bonded he was out at Washington University. I read his books.

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Speaker 1: I wrote some essays for him when he moved east

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Speaker 1: and was at Bard College at the Levy Institute, I

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Speaker 1: used Tom up for his conferences. He had a tremendous

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Speaker 1: influence on me. And of course, in two thousand and

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Speaker 1: eight the world rediscovered the most neglected economists of the

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Speaker 1: second half of the twentieth century. I discovered him through

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Speaker 1: Paul McCulley, who has been a guest on the show

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Speaker 1: and I know for many years from his days of PIMCO,

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Speaker 1: briefly explain Minsky's primary economic thesis about stability leading to instability.

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Speaker 1: Minsky's thesis the the evolution of the UH, of the

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Speaker 1: movement from the conservative, prudent UH system to one of crazy,

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Speaker 1: wild speculation that self destruction goes like this, and and

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Speaker 1: and let's remember Minsky was really applying this to the

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Speaker 1: banking system, not to the stock market. But there's an analogy.

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Speaker 1: So I lend you money, Barry. I lend you money,

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Speaker 1: and you not only pay me back the interest on

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Speaker 1: a timely fashion, but when you owe me back the loan,

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Speaker 1: you pay me act the loan out of your own income,

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Speaker 1: out of money you've earned. So guess what you want?

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Speaker 1: Another loan? You got it. And this time you know,

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Speaker 1: I don't really care. I trust you. You keep paying

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Speaker 1: me that interest on a timely basis. And if at

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Speaker 1: the end of the day we got to roll over

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Speaker 1: the loan, we gotta refinance it. Well, we've just moved

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Speaker 1: from what from what Minsky called the first the hedged environment,

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Speaker 1: there's a risk that the market may not be so

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Speaker 1: acceptable when it's time. But it's still it's still pretty

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Speaker 1: solid in its business as usual. But then, and this

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Speaker 1: is what happened in two thousand and seven. Then people

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Speaker 1: feel really comfortable lending you the third loan. And this time,

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Speaker 1: you know, you wake up one morning and things are

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Speaker 1: a little tight, and you call me up and say,

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Speaker 1: you know, yeah, I know, I owe you this interest payment,

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Speaker 1: but it would really help me if instead of paying

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Speaker 1: you cash, I pay you in kind. I give you

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Speaker 1: a little more of that debt. This is called pick loans.

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Speaker 1: Payment in kind, another word to recapitalize the interest and

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Speaker 1: the previous principle. And you're rolling the whole loan over again.

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Speaker 1: And the signal that you're in a banking bubble which

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Speaker 1: the borrowers the interest to pretend the loan is still good.

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Speaker 1: That's exactly what happened in two thousand and seven. You're

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Speaker 1: listening to Masters in Business on Bloomberg Radio, My guest

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Speaker 1: today is William Janeway. He is a venture capitalist, author

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Speaker 1: and managing director at Warburg Pinkis. And we are discussing

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Speaker 1: how you helped to create b e A Systems, which

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Speaker 1: is a technology company that really integrat rates databases with

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Speaker 1: the Internet. Is that a gross over simplification. B e

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Speaker 1: A was created in the mid nineties and became the

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Speaker 1: company that delivered the platform for running important commercial applications,

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Speaker 1: applications that involve people spending and collecting money across the

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Speaker 1: Internet with millions of simultaneous users. Companies now owned by Oracle.

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Speaker 1: It's the core of Oracles platform technology today, which is

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Speaker 1: called Oracle Fusion. But b e A, beginning in the

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Speaker 1: mid nineties through the mid audies, was a pioneer in

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Speaker 1: transforming the world of transactional computing, of commercial computing from

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Speaker 1: being dominated by IBM everything on an IBM mainframe to

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Speaker 1: being distributed out across millions of separate machines interlinked by

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Speaker 1: the Internet. So this this allowed the transition from mainframe

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Speaker 1: to server. And and so that's such a weird name.

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Speaker 1: B e A Systems would be a stand for well

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Speaker 1: in at Warburg Pinkers, we we had created an investment

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Speaker 1: thesis that it was time the technology had evolved to

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Speaker 1: the point where IBMS dominant control of the marketplace where

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Speaker 1: it could charge enormous premium prices, that that was was vulnerable,

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Speaker 1: and that around the commercial world of enterprises you were

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Speaker 1: seeing client servers Sun Systems running Oracle databases was opening up.

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Speaker 1: So we began a program that that went on for

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Speaker 1: a decade of investing in the way I like to

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Speaker 1: put it in frankly, and kind of helping IBM become

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Speaker 1: just another competitor. So in the middle of that process,

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Speaker 1: um I was introduced to a felic called Bill Coleman.

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Speaker 1: Bill had run UM the core software, it's Sun micro Systems.

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Speaker 1: He had actually been working for Eric Schmidt and and right,

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Speaker 1: and and Bill had a great idea sons sons mantra

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Speaker 1: was the network is the computer, So Bill said, if

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Speaker 1: if the networks the computer, the network needs an operating

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Speaker 1: system like a computer does that that allocates and manages

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Speaker 1: all the different resources. And he connected with a brilliant

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Speaker 1: young engineer named Alfred Twang and a seasoned commercial sales

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Speaker 1: and marketing guy named Ed Scott. So Bill and Ed

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Speaker 1: and Alfred had this idea that that they could, with

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Speaker 1: enough capital and enough time, build software that would effectively

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Speaker 1: replace IBM's core transaction platform. So we began having conversations

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Speaker 1: in the autumn of ninety four, and you know, I said,

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Speaker 1: you know, guys, I I get it. I get the vision.

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Speaker 1: We've been thinking about this ourselves for five years. You

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Speaker 1: guys are incredibly landed. But before we set down to

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Speaker 1: to build something's gonna take three or four years, gonna

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Speaker 1: cost a ton of money. Why don't we see if

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Speaker 1: we can cheat. Why don't we see whether there's stuff

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Speaker 1: out there that could play this role but is owned

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Speaker 1: by people who don't know what to do with it.

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Speaker 1: So we actually launched the e A with Bill and

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Speaker 1: Alfred with the working title it's like, you know, working

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Speaker 1: title for a play bill Out and Alfred b e A.

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Speaker 1: We did it as a research project, first to evaluate

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Speaker 1: all the existing technologies that were available, and then to

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Speaker 1: validate that there were real markets, real markets with real

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Speaker 1: customers that could buy into alternatives to IBM. And we

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Speaker 1: found this technology that had been developed in guests where

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Speaker 1: Bell Labs A T and T and Bell Labs A

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Speaker 1: T and T in those days when it was a

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Speaker 1: dominant communications company basically had to give everything away that

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Speaker 1: it wasn't using in communications because of the monopoly rules. Exactly. Well,

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Speaker 1: that was that became loosened. But before then A T

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Speaker 1: and T sold its Unix Systems Labs. This is where

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Speaker 1: the Unix operating system was, and this is where this

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Speaker 1: core technology called Tuxedo was. They sold it to a

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Speaker 1: little company called Novel nowhere competing with Microsoft, run by

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Speaker 1: a guy called Ray Norda who was dedicated to fighting

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Speaker 1: Bill Gates to the death. So he bought this technology

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Speaker 1: which was super complex, big heavy duty stuff. You needed

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Speaker 1: engineers surrounding it into a company that that told everything

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Speaker 1: in a red box at a computer land store. I

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Speaker 1: used to say, you know, I'm not well unless they

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Speaker 1: can microminiatureize three systems engineers and put it in every

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Speaker 1: red box so that they can come out and dance

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Speaker 1: and make it work. So in any case, Ed Scott

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Speaker 1: had a long conversation with the new CEO, Bob Frankenberg.

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Speaker 1: Bob Frankenberg had come from HP, he knew enterprise computing

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Speaker 1: and he knew that Novel and Tuxedo didn't mix. So

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Speaker 1: we put together a deal which launched the e A

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Speaker 1: by acquiring the Tuxedo technology and having it in the

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Speaker 1: hands of people Billonette and Alfred who knew what to

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Speaker 1: do with it. So that was a fifty five million

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Speaker 1: dollars was we we We had already bought a couple

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Speaker 1: of consulting businesses by this time. We had we had

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Speaker 1: committed because we knew we were gonna be buying stuff

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Speaker 1: from scratch. This was the innovation. We created what we

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Speaker 1: called the line of equity, not a line of credit,

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Speaker 1: a line of equity. So we priced out fifty million

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Speaker 1: dollars up front, and so when the guys went into

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Speaker 1: Novelle needing to do a deal, they didn't have to say, hey, Bob,

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Speaker 1: don't do a thing. We'll be back in six months

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Speaker 1: when we raised another round of venture capital. We were

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Speaker 1: there with them. We could do the deal in real time.

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Speaker 1: That meant in a year BA was running at a

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Speaker 1: hundred million dollar revenue base could go public just in

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Speaker 1: seven as the Internet bubble started to take off. But

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Speaker 1: Tuxedo wasn't designed for the Internet. And this was the

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Speaker 1: genius of Bill and Nett and Alfred and Bill and Alfred,

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Speaker 1: the technology guys really came together. They did a search

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Speaker 1: for technology that was that was Internet native, and they

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Speaker 1: found a little startup called web Logic. So web Logic

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Speaker 1: was already a hot company even though it was just

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Speaker 1: beginning to ship stuff, just beginning, and the valuation happened

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Speaker 1: it before it will happen again. This is what a

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Speaker 1: bubble starts to smell like. The valuation for the startups

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Speaker 1: started rising and rising, but so did the stock of

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Speaker 1: b e A because we've been able to go public.

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Speaker 1: Well you did it Beego public? And what sort of

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Speaker 1: value sen to go public at? Well, initially it was

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Speaker 1: at about a two dollar valuation and that's so that's

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Speaker 1: a pretty good return on fifty five million and we

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Speaker 1: didn't even have all the million in yet, But by

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Speaker 1: that valuation was up to a billion, which was a

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Speaker 1: very good thing because the Bye web Logic it took

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Speaker 1: a hundred and fifty million of shares of stock and

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Speaker 1: if we hadn't had the public market valuation, couldn't have

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Speaker 1: done it. So how long after that did it take

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Speaker 1: to get to six and a half billion, Well, first

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Speaker 1: it took it took about a year after that to

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Speaker 1: get to a billion dollars in revenues, a billion revenue.

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Speaker 1: That's a real company, that's a real company, very profitable,

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Speaker 1: becoming the standard. And with the bubble, with the bubble

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Speaker 1: and the stock market valuation went to twenty five billion.

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Speaker 1: So who ends up taking b e A out when

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Speaker 1: everything is well? First of all, the public speculative stock market,

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Speaker 1: war Paying Kiss owned after the I p O. Warburg

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Speaker 1: pink Is still owned more than fifty percent of the company.

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Speaker 1: And when we were the Soul funders, Soul funders through

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Speaker 1: this line of equity. So we began distributing our shares

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Speaker 1: to our limited partners. The shares were fully tradeable, completely liquid,

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Speaker 1: and the stock kept rising as we were distributing the shares.

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Speaker 1: And so that's where that's six and a half billion

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Speaker 1: of realized value came from distributing shares into a rising market.

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Speaker 1: And you know, we talked about high mensky. I My

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Speaker 1: my senior partner, John Vogelstein, who was the chief investment

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Speaker 1: officer at Warburg Pinkers, was a great student of markets.

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Speaker 1: And I bat Way back at Cambridge, had written my

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Speaker 1: PhD thesis on nineteen nine to nineteen thirty one in Britain.

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Speaker 1: So I'd seen, if you like, I'd seen the movie before.

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Speaker 1: I've seen the stock market bubble of nineteen twenty nine.

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Speaker 1: When our c A. She took the stock price chart

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Speaker 1: of our CIA from twenty six to nine. It looked

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Speaker 1: like b E A from nine six to and that's

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Speaker 1: all you needed to see. We knew it was a bubble.

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Speaker 1: We knew it wasn't gonna last. We knew we'd built

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Speaker 1: a real company, but it was time to realize the

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Speaker 1: value that we've created. You're listening to Masters in Business

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Speaker 1: on Bloomberg Radio. My guest today is Bill Janeway. He

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Speaker 1: is a managing director at Warburg Pinkus, an author of

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Speaker 1: the book Doing Capitalism in the Innovation Economy, as well

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Speaker 1: as a venture capital investor. Let's let's dive right into

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Speaker 1: the VC process. We were speaking earlier about B e

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Speaker 1: A systems. What's the decision process like when you're doing

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Speaker 1: more traditional sort of venture investing where someone brings you

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Speaker 1: a company and you're interested in it. There may be

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Speaker 1: other investors, other vcs or angels participating. What's that process like? Well,

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Speaker 1: I think we want to frame this in thinking about

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Speaker 1: venture capital as an industry. So to begin with, this

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Speaker 1: is not a very old industry. It's about nine eighty

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Speaker 1: when it went from being a craft practice by people.

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Speaker 1: We could get them all in this room, I promise you,

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Speaker 1: the founding and entrepreneurs, but American research and Development, Graylock,

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Speaker 1: ven Rock, J. H. Whitney, um Warby Pinkins was a

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Speaker 1: founder of the National Venture Capital Association. That were barely

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Speaker 1: twenty five firms in the country that were founders of

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Speaker 1: the NVCA, But one of the venture capital has been

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Speaker 1: studied intensely through empirical analysis, and there are a few

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Speaker 1: stylized facts that emerge over these thirty five years since

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Speaker 1: nineteen eighty. The first is there is tremendous kew in

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Speaker 1: the returns of venture capitalists, meaning a small number of

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Speaker 1: venture capital funds have fantastic performance, a large number have

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Speaker 1: very mediocre performance. We see something very similar amongst hedge funds,

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Speaker 1: and not quite as skewed, but still there is a

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Speaker 1: a shifted distribution most private equity as well. Now. Second,

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Speaker 1: and this has been confirmed right through two thousand and ten.

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Speaker 1: Unlike most public market investors, there is persistence in the return.

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Speaker 1: So it's not just a few funds, it's a few firms.

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Speaker 1: So performance of firm one helps predict performance of firm

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Speaker 1: of fund to fund three and that's why you have

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Speaker 1: these iconic names and well, uh, Benchmark and Sequoia, these

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Speaker 1: firms have been successful over decades um So. Third, however,

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Speaker 1: for the industry as a whole, for the me infirm,

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Speaker 1: the returns are very closely correlated with the public market

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Speaker 1: because there and that's that's where we're going to come

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Speaker 1: to a very interesting change in the last fifteen years.

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Speaker 1: It used to be that we could take in the

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Speaker 1: eighties and nineties, we kind of take access to the

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Speaker 1: I p O market for granted each year. And this

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Speaker 1: is frankly, this is my own research when I went

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Speaker 1: back to Cambridge and became a financial economist again after

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Speaker 1: thirty five years as a venture capitalist. The correlation is

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Speaker 1: really tight with the state of the I p O market.

430
00:28:37,080 --> 00:28:40,840
Speaker 1: In a hot I p O market, venture capitalists look

431
00:28:40,920 --> 00:28:47,160
Speaker 1: like geniuses. When the market cools down and the exit

432
00:28:47,200 --> 00:28:53,440
Speaker 1: opportunities shrink, then the returns And since two thousand, venture

433
00:28:53,480 --> 00:28:56,520
Speaker 1: capital returns have been just for the for the average,

434
00:28:56,840 --> 00:28:59,560
Speaker 1: have been just about what you get from investing in

435
00:28:59,560 --> 00:29:03,040
Speaker 1: the nest AT index, where you also have complete liquidity.

436
00:29:03,560 --> 00:29:05,760
Speaker 1: So this is a stress, This is a strain and

437
00:29:05,920 --> 00:29:08,120
Speaker 1: a lot of people are concerned about this. Do we

438
00:29:08,160 --> 00:29:10,240
Speaker 1: have do we have too many vcs? Is there too

439
00:29:10,320 --> 00:29:12,560
Speaker 1: much money slashing around? Well, there certainly is a lot

440
00:29:12,600 --> 00:29:15,200
Speaker 1: of money slashing around, but you don't have to think

441
00:29:15,240 --> 00:29:20,080
Speaker 1: about the technology the environment for innovation, and that's changed too.

442
00:29:21,000 --> 00:29:24,600
Speaker 1: So back in the eighties and nineties, if you wanted

443
00:29:24,640 --> 00:29:28,200
Speaker 1: to build a new I T company, talk about biotechnology separately.

444
00:29:28,680 --> 00:29:31,200
Speaker 1: If you want to talk about a new I T company,

445
00:29:31,240 --> 00:29:34,600
Speaker 1: to get to the first dollar of revenue, you have

446
00:29:34,720 --> 00:29:37,320
Speaker 1: to be thinking ten to twenty million dollars of complete

447
00:29:37,480 --> 00:29:39,880
Speaker 1: risk capital. You had to you had to build a

448
00:29:39,920 --> 00:29:43,200
Speaker 1: company from scratch. You had to have your own hardware,

449
00:29:43,240 --> 00:29:46,479
Speaker 1: your own software, develop your own servers today, and your

450
00:29:46,520 --> 00:29:49,680
Speaker 1: own by licenses today. You could pretty much do that

451
00:29:49,720 --> 00:29:52,960
Speaker 1: with off the shelf stuff. Well, it's open source with

452
00:29:53,160 --> 00:29:58,960
Speaker 1: free stuff and renting by the or what. I was

453
00:29:59,000 --> 00:30:00,920
Speaker 1: talking to an old friend of mine, an old timer

454
00:30:00,960 --> 00:30:03,320
Speaker 1: who goes back then and is doing a new startup,

455
00:30:03,360 --> 00:30:07,640
Speaker 1: and he's building some software for investment banks how to

456
00:30:07,680 --> 00:30:11,160
Speaker 1: pull together all the data they need for spreadsheets. And

457
00:30:11,200 --> 00:30:13,200
Speaker 1: I said, so, Chris, when you get this to where

458
00:30:13,200 --> 00:30:15,040
Speaker 1: you can actually start chipping it to a customer how

459
00:30:15,080 --> 00:30:16,960
Speaker 1: much it will it have cost you? He thought for

460
00:30:17,000 --> 00:30:21,080
Speaker 1: a moment, he said, you know, sixtys it would have

461
00:30:21,120 --> 00:30:25,680
Speaker 1: been ten to fifteen millions years ago, when lots of startups.

462
00:30:25,840 --> 00:30:27,720
Speaker 1: When I was about to say, when people are a

463
00:30:27,720 --> 00:30:31,200
Speaker 1: little negative on the future of the country, the future

464
00:30:31,280 --> 00:30:35,720
Speaker 1: of the economy, when I go to certain conferences and

465
00:30:35,720 --> 00:30:37,640
Speaker 1: and I go to this thing on the West coast

466
00:30:37,720 --> 00:30:40,440
Speaker 1: in San Diego, of all places that are these young

467
00:30:40,720 --> 00:30:45,040
Speaker 1: entrepreneurs right out of college, my mind is blown at

468
00:30:45,080 --> 00:30:48,440
Speaker 1: how innovative and forward looking a lot of these new

469
00:30:48,440 --> 00:30:52,520
Speaker 1: technologies are. What we're playing off is the maturation of

470
00:30:52,680 --> 00:30:59,080
Speaker 1: the digital internet infrastructure, spilling over into the open source software,

471
00:30:59,160 --> 00:31:03,640
Speaker 1: the cloud computer. It is a golden age for innovating

472
00:31:03,680 --> 00:31:08,120
Speaker 1: and developing new digital services. Obviously we all talk about

473
00:31:08,280 --> 00:31:11,720
Speaker 1: Uber and Airbnb, but there are twenty more a week now.

474
00:31:12,400 --> 00:31:15,240
Speaker 1: Let me let me interrupt you there. If you have

475
00:31:15,360 --> 00:31:17,959
Speaker 1: a longer perspective, if if for the people who are

476
00:31:18,000 --> 00:31:21,920
Speaker 1: waiting for the US economy to collapse, isn't this the

477
00:31:21,920 --> 00:31:24,920
Speaker 1: antidote to that? Aren't we going to see a boom

478
00:31:24,960 --> 00:31:29,320
Speaker 1: in new services, new technology, new apps. Hasn't the whole

479
00:31:29,360 --> 00:31:33,800
Speaker 1: app economy just completely changed the game. Based on what

480
00:31:33,840 --> 00:31:36,840
Speaker 1: you're talking about, it's ten or twenty thousand dollars or

481
00:31:37,040 --> 00:31:40,600
Speaker 1: free to to change the world. Well, and it has

482
00:31:40,640 --> 00:31:42,920
Speaker 1: all sorts of impact. You know, it changes what kinds

483
00:31:42,920 --> 00:31:46,080
Speaker 1: of jobs are available, it changes what time, the terms

484
00:31:46,080 --> 00:31:48,560
Speaker 1: of employment. A lot of people think that in this

485
00:31:48,600 --> 00:31:51,800
Speaker 1: world you can't rely on your employer for healthcare. We

486
00:31:51,840 --> 00:31:55,600
Speaker 1: really need to expend even more the social safety net

487
00:31:55,680 --> 00:31:59,080
Speaker 1: so people can afford to play in the gig economy,

488
00:31:59,520 --> 00:32:03,720
Speaker 1: whether it's a uber driver, or whether making deliveries, or

489
00:32:03,760 --> 00:32:07,320
Speaker 1: whether writing software for a startup, writing code for open source.

490
00:32:07,760 --> 00:32:11,520
Speaker 1: So it has a lot of social impact. But you're

491
00:32:11,520 --> 00:32:15,640
Speaker 1: absolutely right, You're dead right. Innovation isn't over. It's on

492
00:32:15,680 --> 00:32:19,400
Speaker 1: a roll, and it's really just ramping up your building

493
00:32:19,880 --> 00:32:22,959
Speaker 1: on decades of innovation that have made so much things,

494
00:32:23,200 --> 00:32:26,240
Speaker 1: so much stuff cheaper and more available. And in fact,

495
00:32:26,320 --> 00:32:30,560
Speaker 1: again taking a long historical look back, it took you know,

496
00:32:30,640 --> 00:32:33,600
Speaker 1: fifty years from the invention of the microprocessor to get

497
00:32:33,640 --> 00:32:36,560
Speaker 1: where we are today. Well, going back to that railroad age,

498
00:32:36,720 --> 00:32:39,680
Speaker 1: it took fifty years from the Baltimore and Ohio Railroad

499
00:32:39,920 --> 00:32:42,680
Speaker 1: to get to Sears Roebuck. Going back to the age

500
00:32:42,680 --> 00:32:47,239
Speaker 1: of electricity. It took fifty years from Edison turning on

501
00:32:47,320 --> 00:32:50,640
Speaker 1: the Pearl River, the Pearl Street Power Plan in New York,

502
00:32:50,640 --> 00:32:54,080
Speaker 1: the first generating station to where you could have a

503
00:32:53,840 --> 00:32:58,360
Speaker 1: a mix master and a refrigerator in every middle class

504
00:32:58,400 --> 00:33:01,640
Speaker 1: home in America. And oh, by the way, you could

505
00:33:01,640 --> 00:33:05,360
Speaker 1: have manufacturing factories where you could just move the machines

506
00:33:05,400 --> 00:33:09,720
Speaker 1: around and reconfigure the process and create tremendous increase in productivity.

507
00:33:09,880 --> 00:33:14,360
Speaker 1: What what's the significance of that fifty year? It takes

508
00:33:14,600 --> 00:33:19,680
Speaker 1: a long time to first make the new stuff reliable

509
00:33:20,520 --> 00:33:24,040
Speaker 1: and ubiquitous. How much of that is it takes a

510
00:33:24,080 --> 00:33:28,480
Speaker 1: generation to grow up just assuming Hey, electricity, Yeah, I

511
00:33:28,480 --> 00:33:30,600
Speaker 1: could do stuff with that. There's a lot to There's

512
00:33:30,640 --> 00:33:33,080
Speaker 1: a lot to that, Barry, there's a lot to that. Um.

513
00:33:33,600 --> 00:33:36,760
Speaker 1: There's another aspect of it too, however, and that is

514
00:33:36,880 --> 00:33:44,520
Speaker 1: that it takes time to explore wastefully what this stuff

515
00:33:44,560 --> 00:33:46,840
Speaker 1: is good for. You. Remember we started out talking about

516
00:33:47,320 --> 00:33:51,640
Speaker 1: decisions under uncertainty. Why we need a mission driven government

517
00:33:51,720 --> 00:33:55,760
Speaker 1: to to to subsidize the railroads and initially create the Internet,

518
00:33:56,040 --> 00:33:59,239
Speaker 1: and why we need speculators. It's because we don't know

519
00:33:59,280 --> 00:34:02,960
Speaker 1: what's gonna work and what isn't we gotta try and try.

520
00:34:03,080 --> 00:34:06,800
Speaker 1: I like to say the innovation economy proceeds by trial

521
00:34:07,120 --> 00:34:12,040
Speaker 1: and error and error and error and error. It's learning

522
00:34:12,120 --> 00:34:16,440
Speaker 1: by doing. There's no roadmap that is given from on

523
00:34:16,600 --> 00:34:20,120
Speaker 1: high that tells us how to get there at the frontier.

524
00:34:20,360 --> 00:34:22,640
Speaker 1: It's a lot easier for somebody who's playing catch up.

525
00:34:23,200 --> 00:34:25,920
Speaker 1: But why not playing catch up? My friend Dan Gross

526
00:34:25,960 --> 00:34:28,920
Speaker 1: wrote a book called pop Why Bubbles are Good for

527
00:34:28,920 --> 00:34:35,720
Speaker 1: the Economy Ill and his thesis is railroads, radio, television, computers, fiber.

528
00:34:35,760 --> 00:34:38,440
Speaker 1: He said, if it wasn't for global crossing and Metromedia

529
00:34:38,520 --> 00:34:43,080
Speaker 1: fiber that laid thousands and thousands of miles at hundreds

530
00:34:43,120 --> 00:34:47,399
Speaker 1: of dollars per mile and then ultimately it's pennies per

531
00:34:47,440 --> 00:34:50,600
Speaker 1: mile out of bankruptcy, you don't end up with YouTube

532
00:34:50,640 --> 00:34:54,640
Speaker 1: and Google and Facebook and all these other things. That

533
00:34:54,800 --> 00:34:58,520
Speaker 1: exactly right. So so in the last minute we have

534
00:34:58,719 --> 00:35:01,719
Speaker 1: you you mentioned, and we'll we'll get a little more

535
00:35:01,719 --> 00:35:03,960
Speaker 1: into this in the next segment. In the last minute,

536
00:35:03,960 --> 00:35:07,759
Speaker 1: we have what is the proper role of government in

537
00:35:08,000 --> 00:35:13,560
Speaker 1: fostering this sort of speculative innovation. Well, government isn't good

538
00:35:13,560 --> 00:35:18,800
Speaker 1: at picking winners, but it's good at enabling competitive entrepreneurs

539
00:35:18,880 --> 00:35:23,200
Speaker 1: to become winners funding science and also, and this WEE

540
00:35:23,200 --> 00:35:26,320
Speaker 1: can come back to, it's not just providing research funding,

541
00:35:26,520 --> 00:35:31,160
Speaker 1: it's being a customer and early supportive customer for stuff

542
00:35:31,239 --> 00:35:34,759
Speaker 1: that is not yet ready for commercial prime time. If

543
00:35:34,800 --> 00:35:38,960
Speaker 1: people want to find information about your writings or or

544
00:35:39,000 --> 00:35:41,960
Speaker 1: what you're doing doing, capitalism in the innovation economy is

545
00:35:41,960 --> 00:35:45,000
Speaker 1: available at bookstores and at Amazon. Where else can they

546
00:35:45,040 --> 00:35:48,200
Speaker 1: find your writing? And Amazon outlet near you, and they

547
00:35:48,200 --> 00:35:51,200
Speaker 1: can also find me. I've written for Forbes, i write

548
00:35:51,360 --> 00:35:55,680
Speaker 1: UH for Projects Syndicate, and I'm pretty visible on the

549
00:35:56,280 --> 00:36:00,279
Speaker 1: on Google. And thanks good part to Bloomberg Television, Tom

550
00:36:00,360 --> 00:36:05,080
Speaker 1: Keane and Surveillance and UH and now with Barry ridhlt UH.

551
00:36:05,120 --> 00:36:08,360
Speaker 1: If you enjoy this conversation, be sure and hang around

552
00:36:08,400 --> 00:36:10,960
Speaker 1: for our podcast extras where we keep the tape rolling

553
00:36:11,320 --> 00:36:15,000
Speaker 1: and continue chatting. Be sure and check out my daily

554
00:36:15,080 --> 00:36:18,400
Speaker 1: column on Bloomberg View dot com. You can follow me

555
00:36:18,480 --> 00:36:21,759
Speaker 1: on Twitter at Rid Halts. I'm Barry Ridhults. You've been

556
00:36:21,760 --> 00:36:25,640
Speaker 1: listening to Masters in Business on Bloomberg Radio. Welcome to

557
00:36:25,680 --> 00:36:28,759
Speaker 1: the podcast extras. We've been speaking with Bill Janeway and

558
00:36:28,760 --> 00:36:31,000
Speaker 1: in case I forget to say this later. Thank you

559
00:36:31,080 --> 00:36:34,480
Speaker 1: so much for doing this. This is fascinating stuff. I

560
00:36:34,520 --> 00:36:41,320
Speaker 1: am just holy entranced by the intersection of technology, finance,

561
00:36:41,360 --> 00:36:45,080
Speaker 1: and economics. And that's a space you know, really really well.

562
00:36:45,600 --> 00:36:49,239
Speaker 1: There's so many questions I did not get to. But

563
00:36:49,360 --> 00:36:52,560
Speaker 1: before I even get to my favorite questions, let me

564
00:36:52,760 --> 00:36:54,880
Speaker 1: let me go back through a few things that I

565
00:36:55,480 --> 00:36:59,160
Speaker 1: blew through and might have missed. By the way, be

566
00:36:59,320 --> 00:37:01,359
Speaker 1: e a sist is that I get the numbers right.

567
00:37:01,719 --> 00:37:05,320
Speaker 1: The initial investment from Warburg was fifty four million dollars,

568
00:37:05,880 --> 00:37:10,240
Speaker 1: and then the distribution two limited partners was six point

569
00:37:10,280 --> 00:37:13,560
Speaker 1: five billion in less than a decade, about six years later.

570
00:37:13,640 --> 00:37:16,720
Speaker 1: Is that right? That's right, Barry, that's an astonishing number.

571
00:37:16,840 --> 00:37:19,359
Speaker 1: I hope you were one of those limited cards, right.

572
00:37:19,400 --> 00:37:22,400
Speaker 1: I assume that's a fair statement that. Uh do you

573
00:37:22,440 --> 00:37:24,520
Speaker 1: ever look back and say, if only I put another

574
00:37:24,600 --> 00:37:27,719
Speaker 1: hundred grand into that, it would have been worth bajillions.

575
00:37:27,960 --> 00:37:30,839
Speaker 1: One of the things I've learned over time is good

576
00:37:30,960 --> 00:37:33,520
Speaker 1: enough is good enough? There you go, that's the right,

577
00:37:33,640 --> 00:37:36,000
Speaker 1: that's the right attitude. You know, the would have could

578
00:37:36,000 --> 00:37:39,080
Speaker 1: have shoot a philosophy will just eat away. I know

579
00:37:39,160 --> 00:37:43,440
Speaker 1: people who constantly kick themselves my my, my, my wife.

580
00:37:43,520 --> 00:37:46,040
Speaker 1: We met as partners in the firm where we both

581
00:37:46,040 --> 00:37:48,440
Speaker 1: worked before I joined Warburg Pink. She was an investment

582
00:37:48,440 --> 00:37:51,520
Speaker 1: professional and her boss had a great saying because somebody

583
00:37:51,520 --> 00:37:53,080
Speaker 1: would come to him and say, you know, you know,

584
00:37:53,160 --> 00:37:55,960
Speaker 1: I knew we should have we should have recommended that stock.

585
00:37:56,000 --> 00:37:57,560
Speaker 1: I knew we should have, and he said, you know what,

586
00:37:57,920 --> 00:38:00,479
Speaker 1: put it in the retrospect fund. That's the one where

587
00:38:00,520 --> 00:38:03,759
Speaker 1: nobody ever loses any money. That's right, and everything they pay.

588
00:38:04,040 --> 00:38:08,200
Speaker 1: You know, I'm I remember writing getting my hands on

589
00:38:08,239 --> 00:38:11,960
Speaker 1: the first iPod, literally one of the first iPod and

590
00:38:12,000 --> 00:38:14,839
Speaker 1: writing it up. And at the time, many many splits ago,

591
00:38:15,280 --> 00:38:19,520
Speaker 1: Apple was fifteen with thirteen cash. You're risking two dollars

592
00:38:20,200 --> 00:38:23,319
Speaker 1: and the guys I knew board of fifteen and they

593
00:38:23,360 --> 00:38:25,480
Speaker 1: sold it at twenty and they were thrilled to death.

594
00:38:26,120 --> 00:38:28,000
Speaker 1: And I can't tell you how often you see a

595
00:38:28,040 --> 00:38:30,840
Speaker 1: stock like that. But the reality is, no one's going

596
00:38:30,880 --> 00:38:33,719
Speaker 1: to hold it for a thirty seven thousand percent run.

597
00:38:34,360 --> 00:38:38,840
Speaker 1: Think about how many drawdowns Apple has had over that period.

598
00:38:38,880 --> 00:38:41,880
Speaker 1: Most people have no choice but to get but to

599
00:38:42,040 --> 00:38:44,200
Speaker 1: panic out. There's no other way. Well, this is what

600
00:38:44,480 --> 00:38:47,360
Speaker 1: we were talking about. We were talking about bubbles. We

601
00:38:47,480 --> 00:38:50,680
Speaker 1: talked about Minsky in the banking system bubbles, the stock

602
00:38:50,719 --> 00:38:52,840
Speaker 1: market bubbles, and and and this is something that I

603
00:38:52,840 --> 00:38:56,120
Speaker 1: think is is really important. Bubbles are you, big buddess?

604
00:38:56,160 --> 00:38:59,200
Speaker 1: Bubbles happened everywhere, and you can think about them in

605
00:38:59,239 --> 00:39:02,160
Speaker 1: two dimensions. One is, where is it taking places that

606
00:39:02,239 --> 00:39:05,640
Speaker 1: the banking system highly leveraged when it blows up, it

607
00:39:05,640 --> 00:39:08,759
Speaker 1: blows up the economy, or the stock market very little

608
00:39:08,840 --> 00:39:11,360
Speaker 1: leverage when it blows up, the world doesn't come to

609
00:39:11,400 --> 00:39:13,920
Speaker 1: an end difference between two thousand and two thousand and

610
00:39:13,960 --> 00:39:17,600
Speaker 1: eight bingo. But the second dimension is what's the object

611
00:39:17,640 --> 00:39:21,600
Speaker 1: of speculation? Is a toolip bulbs? Is it those beach

612
00:39:21,600 --> 00:39:25,760
Speaker 1: houses of the Nevada desert, Or is it some kind

613
00:39:25,800 --> 00:39:30,640
Speaker 1: of technology that if it's deployed at scale and if

614
00:39:30,840 --> 00:39:35,440
Speaker 1: enough exploration, enough trial and error takes place, it really

615
00:39:35,480 --> 00:39:38,120
Speaker 1: can change the world. It can create a new economy.

616
00:39:38,440 --> 00:39:41,759
Speaker 1: So that's why the lecture I give today mostly is

617
00:39:42,080 --> 00:39:46,400
Speaker 1: called productive bubbles, separating out that small number of this

618
00:39:46,520 --> 00:39:52,840
Speaker 1: phenomenon of this crazy irrational speculation, which again and again

619
00:39:52,920 --> 00:39:55,680
Speaker 1: for the last two hundred years has been responsible for

620
00:39:55,800 --> 00:40:02,319
Speaker 1: moving us from the Malthusian economy of misery through the

621
00:40:02,400 --> 00:40:06,200
Speaker 1: railroad age, the electricity age, the automobile age, and now

622
00:40:06,239 --> 00:40:08,879
Speaker 1: the Internet age. That you would think the Malthusians would

623
00:40:08,880 --> 00:40:12,560
Speaker 1: give up the ghosts, but they seem to be perennially

624
00:40:13,680 --> 00:40:18,480
Speaker 1: forecasting doom and gloom even though the genius of human

625
00:40:18,640 --> 00:40:23,480
Speaker 1: intellectual capital is this never ending parade of even though

626
00:40:23,480 --> 00:40:27,080
Speaker 1: it began his wartime technology. You look at at innovations,

627
00:40:27,080 --> 00:40:29,719
Speaker 1: it all goes back to how can we become a

628
00:40:29,760 --> 00:40:35,000
Speaker 1: better finding machine a thousand years ago? It's now trans

629
00:40:35,000 --> 00:40:39,759
Speaker 1: transposed itself and become something entirely different, which leads me

630
00:40:40,239 --> 00:40:43,239
Speaker 1: to a really fundamental question I have to ask you.

631
00:40:43,600 --> 00:40:48,160
Speaker 1: So you get your PhD at Cambridge in economics, how

632
00:40:48,200 --> 00:40:51,720
Speaker 1: did that turn into a career in venture capitalism? That's

633
00:40:52,120 --> 00:40:55,560
Speaker 1: not the typical route. Well, I'll tell you what happened.

634
00:40:55,680 --> 00:40:58,919
Speaker 1: I studied, as I mentioned briefly, I studied on Derrick

635
00:40:59,000 --> 00:41:02,600
Speaker 1: Kanes's directs students. I'm what they call, you know. They

636
00:41:02,640 --> 00:41:07,480
Speaker 1: have post Kinzians and Neo Kaanesians and new Canesian's. I'm

637
00:41:07,520 --> 00:41:11,680
Speaker 1: a Paleo Kanesian. I'm an old Kynesian. I took to

638
00:41:11,880 --> 00:41:17,240
Speaker 1: heart the core message of Canes in the general theory

639
00:41:17,320 --> 00:41:21,800
Speaker 1: and the other writings, which was, first of all, decision

640
00:41:21,840 --> 00:41:26,880
Speaker 1: making under uncertainty. Nobody knows the future, and everybody knows

641
00:41:26,960 --> 00:41:29,879
Speaker 1: that nobody knows the future. I would challenge a lot

642
00:41:29,920 --> 00:41:31,799
Speaker 1: of you on that, because I think a lot of

643
00:41:31,840 --> 00:41:36,719
Speaker 1: people believe either they know the future or experts, economists,

644
00:41:36,760 --> 00:41:39,719
Speaker 1: analysts have a good sense of the future. But you're

645
00:41:39,840 --> 00:41:43,040
Speaker 1: singing my song. I believe no one has a clue

646
00:41:43,080 --> 00:41:45,520
Speaker 1: what's going to happen, and they spend most of their

647
00:41:45,560 --> 00:41:47,839
Speaker 1: day lining to themselves that they do, and then they

648
00:41:47,840 --> 00:41:50,040
Speaker 1: wake up one morning and it's two thousand and eight

649
00:41:50,120 --> 00:41:53,960
Speaker 1: or it's nine. That's when the uncertainty meme raises its head,

650
00:41:53,960 --> 00:41:57,279
Speaker 1: when people start saying, well, things are very uncertain. No, no,

651
00:41:57,320 --> 00:42:00,799
Speaker 1: we you just realized temporarily that you don't understand what's

652
00:42:00,840 --> 00:42:03,040
Speaker 1: what's going to happen. But then take that one step further,

653
00:42:03,280 --> 00:42:06,360
Speaker 1: take that one step further. So I'm worried about the future.

654
00:42:06,960 --> 00:42:09,480
Speaker 1: So I want to save more money. Okay, I want

655
00:42:09,480 --> 00:42:11,840
Speaker 1: to save more money. And by the way, you're worried

656
00:42:11,840 --> 00:42:14,160
Speaker 1: about the future too, and you save more money, and

657
00:42:14,160 --> 00:42:17,480
Speaker 1: all of a sudden, everybody saving more money. Paradox of

658
00:42:17,560 --> 00:42:23,600
Speaker 1: thrift coordination failure. Each person individually does what's rational, and

659
00:42:23,640 --> 00:42:28,000
Speaker 1: the result is a systematic mess, which which makes perfect

660
00:42:28,040 --> 00:42:33,200
Speaker 1: sense and also raises the role of government. Two, During

661
00:42:33,280 --> 00:42:37,920
Speaker 1: periods of a collapse in private sector business household demands,

662
00:42:38,320 --> 00:42:42,440
Speaker 1: the government should temporarily step in and and fulfill that,

663
00:42:42,480 --> 00:42:47,560
Speaker 1: which is eventually what the United States has done most crises,

664
00:42:47,600 --> 00:42:50,360
Speaker 1: but didn't really do it this last crisis. At least

665
00:42:50,360 --> 00:42:54,359
Speaker 1: it did some. It did more than Congress wanted to do.

666
00:42:54,800 --> 00:42:58,120
Speaker 1: It could have done more, as the president's advisors begged

667
00:42:58,200 --> 00:43:00,560
Speaker 1: him to. But in any case, but where we get there,

668
00:43:00,600 --> 00:43:04,759
Speaker 1: Before we get to the policy message that there's another aspect.

669
00:43:05,160 --> 00:43:11,160
Speaker 1: There's another aspect of this. Why I left academic economics

670
00:43:11,400 --> 00:43:18,759
Speaker 1: because the third piece is economics by nineteen seventy had

671
00:43:19,000 --> 00:43:25,239
Speaker 1: fundamentally come to be about how do we allocate resources efficiently?

672
00:43:25,480 --> 00:43:28,759
Speaker 1: How do we eliminate waste in the system. Now you

673
00:43:28,840 --> 00:43:32,600
Speaker 1: need two assumptions for that to be the case. First,

674
00:43:32,640 --> 00:43:35,879
Speaker 1: all resources have to be already fully employed, so you're

675
00:43:35,920 --> 00:43:38,799
Speaker 1: just it's a question of moving to the most productive

676
00:43:39,120 --> 00:43:45,719
Speaker 1: application of labor capital natural resources. And second, coming back

677
00:43:45,760 --> 00:43:48,239
Speaker 1: to where we began this whole discussion, you have to

678
00:43:48,280 --> 00:43:50,440
Speaker 1: know what the return on that next investment is going

679
00:43:50,480 --> 00:43:53,720
Speaker 1: to be in advance? Can you really do that? Well,

680
00:43:53,960 --> 00:43:59,560
Speaker 1: I in nineteen seventy nine seventy there were jobs available

681
00:43:59,680 --> 00:44:03,960
Speaker 1: at the best economics departments everywhere because frankly because of

682
00:44:03,960 --> 00:44:06,880
Speaker 1: the federal government, because of the response to Sputnik, the

683
00:44:06,920 --> 00:44:11,840
Speaker 1: federal investment in higher education, huge increase in graduate schools.

684
00:44:12,960 --> 00:44:15,080
Speaker 1: And I had a real heart to heart talk with myself,

685
00:44:16,200 --> 00:44:21,040
Speaker 1: having been immersed in kains and uncertainty and ignorance and

686
00:44:21,080 --> 00:44:25,840
Speaker 1: coordination failure, was I really going to be capable of

687
00:44:26,000 --> 00:44:30,759
Speaker 1: teaching these naive and innocent young minds that we all

688
00:44:30,800 --> 00:44:35,560
Speaker 1: know how to allocate resources efficiently, that the problem of

689
00:44:35,680 --> 00:44:40,160
Speaker 1: economics is just about efficient allocation, that we can assume

690
00:44:40,200 --> 00:44:44,520
Speaker 1: that all resources will always be fully employed. And I said,

691
00:44:44,560 --> 00:44:46,839
Speaker 1: I can't do that. I said to myself, I can't

692
00:44:46,840 --> 00:44:49,640
Speaker 1: do that. So how did you How did you morph

693
00:44:50,280 --> 00:44:56,200
Speaker 1: from an academic economist too a pragmatic investor in technology.

694
00:44:56,400 --> 00:45:00,759
Speaker 1: Well it happened by way of a very unusual firm. Now,

695
00:45:00,800 --> 00:45:03,200
Speaker 1: this is back in the old days of Wall Street,

696
00:45:03,640 --> 00:45:08,000
Speaker 1: when there were hundreds of private investment partnerships in Wall Street.

697
00:45:08,400 --> 00:45:10,640
Speaker 1: They were all subsidized by being members of the New

698
00:45:10,719 --> 00:45:16,879
Speaker 1: York Stock Exchange. Back then, brokerage commissions were fixed. Monopoly

699
00:45:17,040 --> 00:45:21,160
Speaker 1: profits were available, so you couldn't compete on price, but

700
00:45:21,360 --> 00:45:25,440
Speaker 1: you competed for business. There were usually three ways to compete.

701
00:45:25,640 --> 00:45:27,880
Speaker 1: First of all, we all went to school together. We

702
00:45:27,920 --> 00:45:32,480
Speaker 1: all went to St. Grattle, Sex together. Second, the three Bees,

703
00:45:33,320 --> 00:45:36,480
Speaker 1: Booze babes and baseball tickets. That was literally how you

704
00:45:36,480 --> 00:45:42,239
Speaker 1: would you would attract four brains. Donaldson, Lufkin and Jenrette

705
00:45:42,640 --> 00:45:47,040
Speaker 1: the LJ had created the idea of the research based

706
00:45:47,320 --> 00:45:51,600
Speaker 1: brokerage firm doing fundamental research. That that was a new

707
00:45:51,640 --> 00:45:55,520
Speaker 1: innovation that hasn't always existed, did not always exist, and

708
00:45:55,600 --> 00:45:59,200
Speaker 1: it was it was It grew up with the rise

709
00:45:59,239 --> 00:46:03,160
Speaker 1: of institute sational investors who would pay for research by

710
00:46:03,200 --> 00:46:07,840
Speaker 1: directing brokerage commissions to the firms that provided smart guidance.

711
00:46:08,320 --> 00:46:11,800
Speaker 1: So the firm I joined was one of those research

712
00:46:11,880 --> 00:46:16,280
Speaker 1: firms which had a very distinctive style. It focused only

713
00:46:16,719 --> 00:46:23,640
Speaker 1: on the science based industries chemistry, chemicals, pharmaceuticals, electronics, and

714
00:46:23,719 --> 00:46:27,360
Speaker 1: this new stuff called computing. But you come with a

715
00:46:27,719 --> 00:46:31,560
Speaker 1: economics background, you don't have a science or undergraduate what

716
00:46:31,680 --> 00:46:33,560
Speaker 1: was your background? I did I did not have a

717
00:46:33,600 --> 00:46:40,200
Speaker 1: technical background, but pretty good reader, and I learned, actually

718
00:46:40,280 --> 00:46:45,360
Speaker 1: as an economist, about this new computing stuff. In V

719
00:46:45,640 --> 00:46:49,120
Speaker 1: three we had the first oil crisis. The economy went

720
00:46:49,160 --> 00:46:54,040
Speaker 1: into freeze free fall. Simultaneously, inflation went up, unemployment went up.

721
00:46:54,080 --> 00:46:58,200
Speaker 1: That wasn't supposed to happen. The models, the first econometric models,

722
00:46:58,200 --> 00:47:01,000
Speaker 1: all broke down, and I went in search for people

723
00:47:01,000 --> 00:47:03,200
Speaker 1: who are trying to make sense of this. I found

724
00:47:03,239 --> 00:47:07,400
Speaker 1: some guys at M I T who were building simulation

725
00:47:07,480 --> 00:47:11,920
Speaker 1: models of the economy, not purely statistical models, but what

726
00:47:12,000 --> 00:47:15,080
Speaker 1: are now called agent based models, where you could watch

727
00:47:15,239 --> 00:47:19,359
Speaker 1: an artificial economy evolved. And I got it. It just

728
00:47:19,440 --> 00:47:22,239
Speaker 1: hit me like a ton of bricks that computers were

729
00:47:22,280 --> 00:47:27,640
Speaker 1: not just flexible typewriters or quick adding machines, that they

730
00:47:27,680 --> 00:47:32,880
Speaker 1: were engines for exploring systems that were too complicated to

731
00:47:33,120 --> 00:47:37,239
Speaker 1: model in simple mathematics, and I fell in love with computing.

732
00:47:37,760 --> 00:47:41,279
Speaker 1: I then discovered by way of the getting involved and

733
00:47:41,400 --> 00:47:45,080
Speaker 1: understanding the first wave of artificial intelligence. I found my

734
00:47:45,120 --> 00:47:49,040
Speaker 1: way out to Xerox Park in uh Palo Alto, California.

735
00:47:49,080 --> 00:47:54,040
Speaker 1: This is in the seventies nine. I spent as many

736
00:47:54,160 --> 00:47:58,360
Speaker 1: nights after dinner, hanging out there watching the future unfold,

737
00:47:59,040 --> 00:48:04,240
Speaker 1: seeing things lie um mice for controlling a computer. Steve

738
00:48:04,320 --> 00:48:09,440
Speaker 1: Jobs got the tour of Xerox Center two years before

739
00:48:09,480 --> 00:48:11,840
Speaker 1: he was So why didn't you start Apple? The graphical

740
00:48:11,960 --> 00:48:17,439
Speaker 1: user interface, the mouse, there's a the network, the dot

741
00:48:17,480 --> 00:48:20,680
Speaker 1: matrix and uh ink jet printer. There's a run of

742
00:48:20,719 --> 00:48:25,440
Speaker 1: things that that is just an astounding like a T

743
00:48:25,600 --> 00:48:28,520
Speaker 1: and T labs. But that but that was how. That

744
00:48:28,600 --> 00:48:32,640
Speaker 1: was how I made the transition and and became immersed

745
00:48:33,239 --> 00:48:37,960
Speaker 1: in learning the technologies, learning enough about the technologies to

746
00:48:38,000 --> 00:48:41,120
Speaker 1: be able to talk to entrepreneurs in their own language,

747
00:48:41,880 --> 00:48:44,279
Speaker 1: and to see the world in the course of the

748
00:48:44,360 --> 00:48:49,520
Speaker 1: eighties to see these these these highly special technical styles

749
00:48:49,520 --> 00:48:53,600
Speaker 1: of computing that we're used by engineers and by academics

750
00:48:53,840 --> 00:48:58,200
Speaker 1: begin to grow in scale and reliability. And that led

751
00:48:58,280 --> 00:49:02,480
Speaker 1: to this sense by none ten nine that these technologies

752
00:49:02,480 --> 00:49:05,359
Speaker 1: could spill out of the laboratory and come into the

753
00:49:05,480 --> 00:49:09,640
Speaker 1: big markets for commercial computing. That's how we got to

754
00:49:09,719 --> 00:49:12,040
Speaker 1: be e A. How did you How long did you

755
00:49:12,440 --> 00:49:14,879
Speaker 1: spend on the West Coast? How long were you out

756
00:49:14,880 --> 00:49:19,239
Speaker 1: there for? Well? I I spent probably a week to

757
00:49:19,520 --> 00:49:23,080
Speaker 1: ten days a month for thirty five years. I had

758
00:49:23,120 --> 00:49:29,280
Speaker 1: three million miles on American by about and uh we

759
00:49:29,280 --> 00:49:32,400
Speaker 1: we we um when I I should first say that

760
00:49:33,480 --> 00:49:35,600
Speaker 1: the world of Wall Street was changing through all this

761
00:49:37,760 --> 00:49:43,040
Speaker 1: pict brokerage commissions go away, commissions start to decline fundamental

762
00:49:43,080 --> 00:49:45,719
Speaker 1: research by the mid nineteen eighties. You can see two

763
00:49:45,719 --> 00:49:49,520
Speaker 1: paths forward. One, it becomes a commodity because you can't

764
00:49:49,560 --> 00:49:52,480
Speaker 1: afford to pay the smart guys, they're going to the

765
00:49:52,520 --> 00:49:55,600
Speaker 1: buy side. There are people like Ben Rosen, who was

766
00:49:55,640 --> 00:49:59,640
Speaker 1: a great computer analyst at Morgan Stanley creates seven rows

767
00:49:59,680 --> 00:50:02,560
Speaker 1: in the your capital firm. So there was a migration

768
00:50:02,600 --> 00:50:08,040
Speaker 1: of the real talent. Uh So, either it becomes a

769
00:50:08,040 --> 00:50:13,400
Speaker 1: commodity or you need another subsidy. If the subsidies investment banking,

770
00:50:13,960 --> 00:50:17,360
Speaker 1: it's not a commodity, it's prostitution. So we sold the

771
00:50:17,400 --> 00:50:20,560
Speaker 1: firm in night five to a great British investment management

772
00:50:20,600 --> 00:50:23,560
Speaker 1: firm called Robert Fleming. Our firm was called f Ebberstat

773
00:50:23,880 --> 00:50:26,600
Speaker 1: sold it to Robert Fleming in eight five. I served

774
00:50:26,600 --> 00:50:29,040
Speaker 1: out my contract as part of the deal, and the

775
00:50:29,960 --> 00:50:33,640
Speaker 1: I had the great opportunity to join Warburg Pincers and

776
00:50:33,719 --> 00:50:37,759
Speaker 1: to help build this technology investing at Warburg pink You

777
00:50:37,840 --> 00:50:41,040
Speaker 1: really created that. At Warburg they didn't have much of

778
00:50:41,040 --> 00:50:45,440
Speaker 1: a technology footprints or am I overstating that, well they

779
00:50:45,680 --> 00:50:50,360
Speaker 1: we we No, that's not quite fair because, for example,

780
00:50:50,600 --> 00:50:53,240
Speaker 1: Warburg Pinkers was one of the founding investors in Gartner

781
00:50:53,280 --> 00:50:56,600
Speaker 1: Group back Gideon Gartner, another one of those great sell

782
00:50:56,719 --> 00:51:00,200
Speaker 1: side investment research analysts who got the message and created

783
00:51:00,200 --> 00:51:02,120
Speaker 1: one of the great advisory firms. I was gonna say,

784
00:51:02,160 --> 00:51:06,200
Speaker 1: that's not a technology innovation, that's really a alright, someone's

785
00:51:06,239 --> 00:51:11,920
Speaker 1: leaving to do a research independent company play. But it

786
00:51:11,960 --> 00:51:13,759
Speaker 1: gave you. It gave you a view of what was

787
00:51:13,800 --> 00:51:16,600
Speaker 1: going on in technology, and there were some really smart people.

788
00:51:17,040 --> 00:51:20,200
Speaker 1: But the center of gravity of the firm was was

789
00:51:20,320 --> 00:51:24,680
Speaker 1: not doing these relatively earlier stage, risky technology investments. So

790
00:51:24,760 --> 00:51:28,560
Speaker 1: you moved them down downstream to a much or upstream

791
00:51:28,600 --> 00:51:31,520
Speaker 1: to a much earlier stage. The Lionel Pinkus and John

792
00:51:31,560 --> 00:51:36,600
Speaker 1: Boglestein were great entrepreneurs. They were pioneers of private equity

793
00:51:36,640 --> 00:51:41,279
Speaker 1: broadly defined from venture capital through growth equity investing. In

794
00:51:41,440 --> 00:51:45,960
Speaker 1: nineteen eighty six they had raised the first billion dollar

795
00:51:46,040 --> 00:51:49,360
Speaker 1: fund that anybody had ever raised. WARBURI Pinkas was always

796
00:51:49,719 --> 00:51:54,279
Speaker 1: large relative to the industry. And given that they decided

797
00:51:54,360 --> 00:51:59,600
Speaker 1: that we ought to explore investing in technology as Warburg

798
00:51:59,640 --> 00:52:03,960
Speaker 1: Pinker as a lead strategic investor, rather than following other people.

799
00:52:04,160 --> 00:52:06,840
Speaker 1: What was the billion dollar fund they had raised initially?

800
00:52:07,160 --> 00:52:09,480
Speaker 1: What was that for? Was that was for the same

801
00:52:09,520 --> 00:52:15,759
Speaker 1: breadth of investing, investing in emerging growth companies, investing in turnarounds,

802
00:52:15,880 --> 00:52:23,359
Speaker 1: investing very occasionally in buyouts, but very broad. Warburt Pink

803
00:52:23,400 --> 00:52:28,600
Speaker 1: has always had a very broad expanse investing contrarian to

804
00:52:29,680 --> 00:52:32,000
Speaker 1: what the stock market thinks is the great thing to do.

805
00:52:32,200 --> 00:52:37,920
Speaker 1: So when did the first pure technology early early stage

806
00:52:38,360 --> 00:52:42,040
Speaker 1: funds come out of Warburg Pinker. Well, we always invest

807
00:52:42,120 --> 00:52:45,160
Speaker 1: out of one fund. It's one fund, we invest across it.

808
00:52:45,200 --> 00:52:47,600
Speaker 1: And that means that when markets changed as they did

809
00:52:47,600 --> 00:52:54,440
Speaker 1: in we could be realizing the investments in technology while

810
00:52:54,560 --> 00:52:57,240
Speaker 1: putting new money into energy at twelve dollars a barrel,

811
00:52:57,840 --> 00:53:00,640
Speaker 1: so we could move against markets within un fund. We've

812
00:53:00,719 --> 00:53:05,400
Speaker 1: we've always invested from one big fund. The actually the first,

813
00:53:05,600 --> 00:53:09,000
Speaker 1: the first real technology investment that we lad. There were

814
00:53:09,000 --> 00:53:11,759
Speaker 1: there were several, the first really early stage it's a

815
00:53:11,760 --> 00:53:15,480
Speaker 1: company called Level one. Remember Level one, I'm thinking that

816
00:53:15,640 --> 00:53:21,880
Speaker 1: Level one. Level one was not unrelated with silicon optimized

817
00:53:21,920 --> 00:53:26,840
Speaker 1: for communications and particularly for digital communications for d s L.

818
00:53:28,440 --> 00:53:33,200
Speaker 1: Warburge was a big broadband in between what we have

819
00:53:33,280 --> 00:53:37,200
Speaker 1: today and and the twisted copper playing a whole telephone.

820
00:53:37,280 --> 00:53:39,799
Speaker 1: When I got to warburg Pin because we made a

821
00:53:40,000 --> 00:53:44,440
Speaker 1: small investment with some other investors um and the first

822
00:53:44,520 --> 00:53:49,080
Speaker 1: go round, the first customer had been acquired by IBM

823
00:53:49,160 --> 00:53:52,799
Speaker 1: and basically closed down. So we had a choice. We

824
00:53:52,800 --> 00:53:57,520
Speaker 1: could either restart but if, or just give up. But

825
00:53:57,560 --> 00:53:59,960
Speaker 1: if we and and and the leadership of the company

826
00:54:00,280 --> 00:54:03,719
Speaker 1: with an outstanding scientist named Bob Pepper who would work

827
00:54:03,920 --> 00:54:06,799
Speaker 1: very closely at r c A. Starnoff Labs, with my

828
00:54:06,920 --> 00:54:11,520
Speaker 1: new partner, Henry Crissell, who was himself a great applied

829
00:54:11,520 --> 00:54:14,799
Speaker 1: physicist and also a great investor. So we took a

830
00:54:14,840 --> 00:54:17,600
Speaker 1: deep breath and we said we're gonna restart Level one

831
00:54:18,000 --> 00:54:22,400
Speaker 1: behind Bob Pepper, make a second effort and focus on

832
00:54:22,680 --> 00:54:28,160
Speaker 1: making it possible for the plain old fashioned copper wires

833
00:54:28,680 --> 00:54:32,880
Speaker 1: to carry data at a high enough rate so that

834
00:54:32,960 --> 00:54:36,200
Speaker 1: you can actually interact with a computer, not just you know,

835
00:54:36,840 --> 00:54:40,439
Speaker 1: push a button and have a cigarette wait to see

836
00:54:40,480 --> 00:54:44,960
Speaker 1: what happens. And so this is still pretty early stage stuff.

837
00:54:45,000 --> 00:54:47,120
Speaker 1: This is not this was this was a restart of

838
00:54:47,120 --> 00:54:51,000
Speaker 1: a startup. So it really was a startup UM, but

839
00:54:51,080 --> 00:54:54,239
Speaker 1: we had tremendous confidence in Bob Pepper. We helped bring

840
00:54:54,320 --> 00:54:58,480
Speaker 1: up a board of really strong people. UM. Some years

841
00:54:58,560 --> 00:55:01,560
Speaker 1: later into wound up acquiring the company for more than

842
00:55:01,600 --> 00:55:04,800
Speaker 1: a billion dollars. Really, let's talk a little bit about Intel,

843
00:55:04,960 --> 00:55:10,840
Speaker 1: because you mentioned that vcs really blossomed in nine eighties.

844
00:55:11,440 --> 00:55:18,279
Speaker 1: But my recollection of National Semiconductor and then Intel and

845
00:55:18,560 --> 00:55:22,040
Speaker 1: that whole line of companies that starts in the like

846
00:55:22,200 --> 00:55:25,759
Speaker 1: early nineteen sixties, well, Butt Nick and all that is

847
00:55:25,840 --> 00:55:29,560
Speaker 1: where Kleiner, Perkins and some of the other big vcs

848
00:55:30,360 --> 00:55:33,920
Speaker 1: traced back to. Well, getting the timing, there's it's it's

849
00:55:33,920 --> 00:55:38,080
Speaker 1: an interesting history. So American Research and Development a R

850
00:55:38,120 --> 00:55:41,520
Speaker 1: and D. The great General George Dorio starts a R

851
00:55:41,560 --> 00:55:44,680
Speaker 1: and D in the late nineteen forties, takes them about

852
00:55:44,800 --> 00:55:48,040
Speaker 1: five years to scrap together a few million dollars out

853
00:55:48,080 --> 00:55:52,400
Speaker 1: of the Boston Trust industry and makes a bunch of investments,

854
00:55:52,440 --> 00:55:54,960
Speaker 1: none of which really worked very well, but put seventy

855
00:55:54,960 --> 00:56:01,439
Speaker 1: thousand bucks behind an engineer named uh Ken. Oh my God,

856
00:56:01,480 --> 00:56:05,680
Speaker 1: I'm blanking. No, No, that's Bob Neiss's Intel. No Digital

857
00:56:05,719 --> 00:56:11,799
Speaker 1: Equipment Corporation, Ken Ken Ashman, No, We're gonna look it up.

858
00:56:12,239 --> 00:56:16,800
Speaker 1: But filling in um that becomes seventy dollars becomes hundreds

859
00:56:16,800 --> 00:56:19,279
Speaker 1: of millions of dollars. Digital Equipment is the in a way,

860
00:56:19,320 --> 00:56:24,440
Speaker 1: the first truly great technology investment out of a R

861
00:56:24,480 --> 00:56:28,600
Speaker 1: and d uh. Some of the youngsters got some backing

862
00:56:28,640 --> 00:56:32,200
Speaker 1: from the Watson family created Graylock Ventures. This is still

863
00:56:32,200 --> 00:56:36,120
Speaker 1: in the sixties. And then on the other hand, an

864
00:56:36,120 --> 00:56:41,759
Speaker 1: extraordinary entrepreneurial stockbroker named Arthur Rock follows the New York

865
00:56:41,800 --> 00:56:47,840
Speaker 1: Giants to San Francisco in the baseball giants in the

866
00:56:47,920 --> 00:56:51,040
Speaker 1: end of the fifties, and he puts together the financing

867
00:56:51,160 --> 00:56:55,719
Speaker 1: for Fairchild Semiconductor with Sherman Fairchild, the industrialist. That's why

868
00:56:55,760 --> 00:57:02,480
Speaker 1: it was called that those were the geniuses, the treasonous six.

869
00:57:02,560 --> 00:57:06,680
Speaker 1: I guess seven who left Shockley. That was Bob Nois

870
00:57:06,760 --> 00:57:11,600
Speaker 1: and Gordon Moore and by the way, you go fajen uh.

871
00:57:11,640 --> 00:57:16,160
Speaker 1: And they started what from Fairchild, which then begat Intel,

872
00:57:16,800 --> 00:57:19,880
Speaker 1: And that's when Silicon Valley begins to be Silicon Valley.

873
00:57:20,080 --> 00:57:23,320
Speaker 1: And by the way the book. I don't remember the

874
00:57:23,440 --> 00:57:27,960
Speaker 1: Intel book. I don't remember if it was Um, I'm

875
00:57:27,960 --> 00:57:31,560
Speaker 1: trying to remember who wrote it, or it's not the

876
00:57:31,640 --> 00:57:35,920
Speaker 1: CEO of Intel, but it was someone who was Andy Grove.

877
00:57:36,240 --> 00:57:39,080
Speaker 1: It wasn't Andy Grove, only the Paranoid survivor. But it's

878
00:57:39,080 --> 00:57:43,240
Speaker 1: the history of Intel, which is really a discussion of

879
00:57:43,240 --> 00:57:46,800
Speaker 1: the early history of venture investing. I remember that was

880
00:57:46,840 --> 00:57:50,040
Speaker 1: a fascinating read, but it was It's important to remember

881
00:57:50,120 --> 00:57:53,440
Speaker 1: this was a craft. These were a tiny number of firms,

882
00:57:53,480 --> 00:57:55,920
Speaker 1: half a dozen, tiny number of individuals. There were a

883
00:57:55,920 --> 00:57:58,600
Speaker 1: bunch on the East coast. East Coast tended to be

884
00:57:58,720 --> 00:58:03,200
Speaker 1: family offices like ven Rock, the Rockefeller family, J. H. Whitney,

885
00:58:03,240 --> 00:58:06,520
Speaker 1: the Whitney family UM and the West coast tended to

886
00:58:06,560 --> 00:58:10,480
Speaker 1: be these new partnerships. But even as late as nineteen seventy,

887
00:58:10,520 --> 00:58:14,640
Speaker 1: the model, the business model hadn't been established. So there

888
00:58:14,680 --> 00:58:17,760
Speaker 1: was a guy called ned Heiser in Chicago. He started

889
00:58:17,760 --> 00:58:20,440
Speaker 1: the front. It was a corporation and had some preferred stock,

890
00:58:20,880 --> 00:58:23,280
Speaker 1: which was what was owned by the limited partners and

891
00:58:23,360 --> 00:58:27,080
Speaker 1: had the preferred return, and the common stock, which was

892
00:58:27,120 --> 00:58:29,840
Speaker 1: in effect that carried interest, was owned by the general partners.

893
00:58:30,400 --> 00:58:34,120
Speaker 1: When Warburg Pincus was went from putting deals together on

894
00:58:34,160 --> 00:58:37,560
Speaker 1: a case by case basis, you know, was some entrepreneurs

895
00:58:37,560 --> 00:58:41,080
Speaker 1: in one room and some rich family representatives and another

896
00:58:41,200 --> 00:58:45,360
Speaker 1: and created its first fund in nineteen seventy one. Uh

897
00:58:45,440 --> 00:58:49,840
Speaker 1: wear EM E MW Ventures was forty forty one million dollars.

898
00:58:49,880 --> 00:58:51,520
Speaker 1: Lionel used to say, it was all the money in

899
00:58:51,520 --> 00:58:54,520
Speaker 1: the world, and it was set up as a corporation

900
00:58:54,640 --> 00:58:56,439
Speaker 1: and they took all the money down on day one.

901
00:58:57,280 --> 00:59:02,000
Speaker 1: Despite that, it generated net to the investors through the

902
00:59:02,080 --> 00:59:06,000
Speaker 1: nineteen seventies when the stock market was a disaster. If

903
00:59:06,040 --> 00:59:08,400
Speaker 1: they'd taken the money down step by step the way

904
00:59:08,440 --> 00:59:11,760
Speaker 1: we all do today, it would have been so there

905
00:59:11,760 --> 00:59:17,520
Speaker 1: was an experimentation, trial and error going on about financial innovation.

906
00:59:18,000 --> 00:59:24,280
Speaker 1: Venture capital was an institutional innovation which by nine eighty

907
00:59:24,640 --> 00:59:28,320
Speaker 1: began to reach scale because of a regulatory change. What

908
00:59:28,480 --> 00:59:30,600
Speaker 1: was that? What was that change? It was under the

909
00:59:30,840 --> 00:59:36,000
Speaker 1: law that governed pension funds, the Ariskle Law, the Employment

910
00:59:36,160 --> 00:59:43,280
Speaker 1: Retirement Investment. Well, originally when it was first established, there

911
00:59:43,280 --> 00:59:47,080
Speaker 1: were very tight rules about what pension fund trustees could

912
00:59:47,080 --> 00:59:50,000
Speaker 1: do with the money that they were responsible for. They

913
00:59:50,000 --> 00:59:54,840
Speaker 1: had to be very conservative. The amendments to the regulations

914
00:59:54,920 --> 00:59:58,720
Speaker 1: in seventy nine created a kind of safe harbor. You

915
00:59:58,760 --> 01:00:03,720
Speaker 1: can take a portion of the pension fund and a

916
01:00:03,800 --> 01:00:09,640
Speaker 1: little more risk seeking, and that enabled pension funds to

917
01:00:09,680 --> 01:00:12,840
Speaker 1: start investing in venture capital. Before that, it had been

918
01:00:12,880 --> 01:00:17,280
Speaker 1: wealthy families, and it had been a few university endowments,

919
01:00:17,760 --> 01:00:22,320
Speaker 1: but it was very limited capital. After night, the capital

920
01:00:22,360 --> 01:00:26,880
Speaker 1: began to open up, and then in eighty three the

921
01:00:26,920 --> 01:00:30,560
Speaker 1: I p O market opened up. Between seventy three and

922
01:00:30,680 --> 01:00:34,120
Speaker 1: eighty three, there were just a couple of windows. One window.

923
01:00:34,200 --> 01:00:38,040
Speaker 1: December nineteen eighty Apple goes public, jan Entech goes public.

924
01:00:38,600 --> 01:00:42,760
Speaker 1: Then the Great Federal Reserve Chairman Paul Boker sends rates

925
01:00:42,800 --> 01:00:47,760
Speaker 1: to I p O stop It reopened in eighty three.

926
01:00:48,200 --> 01:00:50,960
Speaker 1: We thought, hey, we thought it was a bubble. What

927
01:00:51,040 --> 01:00:54,520
Speaker 1: did we know? But from seven it must have felt

928
01:00:54,520 --> 01:00:57,760
Speaker 1: like it. After fifteen years in the desert, a little

929
01:00:57,800 --> 01:01:01,080
Speaker 1: bit of water, it looks like actually very well put

930
01:01:01,080 --> 01:01:03,560
Speaker 1: barry so. But but there were real returns and a

931
01:01:03,600 --> 01:01:06,480
Speaker 1: whole wave of new companies that began to go public,

932
01:01:06,520 --> 01:01:10,280
Speaker 1: and the validated the venture capital model, particularly around it

933
01:01:11,480 --> 01:01:16,840
Speaker 1: also around biotech. Now biotech biotech shares with I T

934
01:01:17,520 --> 01:01:24,080
Speaker 1: the same dependence on long term government investment in research.

935
01:01:24,320 --> 01:01:27,000
Speaker 1: You can't you can't just do this bootstrap it. You

936
01:01:27,040 --> 01:01:29,720
Speaker 1: can't just pull a bunch of things off the shelf.

937
01:01:29,800 --> 01:01:35,720
Speaker 1: This is really complex, sophisticated, expensive research to create a company,

938
01:01:35,760 --> 01:01:39,160
Speaker 1: well to create the science on which you company can

939
01:01:39,200 --> 01:01:42,680
Speaker 1: exploit for a particular application. But there's one big difference,

940
01:01:43,040 --> 01:01:49,360
Speaker 1: fundamental difference between biotech and information technology. In biotech, when

941
01:01:49,360 --> 01:01:51,800
Speaker 1: you sit down and say we're gonna try to apply

942
01:01:52,440 --> 01:01:58,240
Speaker 1: this molecule to cure that disease. If it works, if

943
01:01:58,280 --> 01:01:59,800
Speaker 1: you get through the f d A, you know what

944
01:01:59,880 --> 01:02:03,960
Speaker 1: the market is. You know it's big. And one way

945
01:02:04,000 --> 01:02:07,200
Speaker 1: to think about this for investors, early stage investors is,

946
01:02:07,720 --> 01:02:10,360
Speaker 1: you know there are two states of the world. We

947
01:02:10,360 --> 01:02:13,720
Speaker 1: get to the FDA, we make a gazillion dollars, we fail,

948
01:02:13,840 --> 01:02:18,320
Speaker 1: we lose everything. Half a gazillion sounds pretty good, right,

949
01:02:18,520 --> 01:02:21,280
Speaker 1: half a gazillion, of course, But the fact that the

950
01:02:21,360 --> 01:02:25,360
Speaker 1: market risk is low, even though the technology risk is huge,

951
01:02:25,960 --> 01:02:32,040
Speaker 1: is what distinguishes biotech from infotech and information technology. The

952
01:02:32,080 --> 01:02:35,720
Speaker 1: market risk is at least as big as the technology risk,

953
01:02:36,080 --> 01:02:40,640
Speaker 1: whether you're building the infrastructure or whether you're exploiting it.

954
01:02:40,680 --> 01:02:44,920
Speaker 1: With these new applications and solutions. How many dot com

955
01:02:45,040 --> 01:02:49,680
Speaker 1: babies went bust? How many of the unicorns today are

956
01:02:49,680 --> 01:02:53,600
Speaker 1: going to wind up lying down and falling over after

957
01:02:53,840 --> 01:02:57,040
Speaker 1: their mark to reality. Let's talk about the unicorns, and

958
01:02:57,160 --> 01:03:00,360
Speaker 1: we mentioned how much money is out there slashing a round.

959
01:03:01,480 --> 01:03:05,200
Speaker 1: Do we have a technology bubble? We have a unicorn bubble.

960
01:03:05,400 --> 01:03:08,840
Speaker 1: We have a unicorn bubble, meaning the most desirable companies

961
01:03:09,040 --> 01:03:12,600
Speaker 1: everybody wants to get. Here's what's really weird. This has

962
01:03:12,640 --> 01:03:17,560
Speaker 1: not happened before. This is unique. Here you have major

963
01:03:17,680 --> 01:03:21,920
Speaker 1: investment firms, you know, Fidelity, t Row, who are paying

964
01:03:22,080 --> 01:03:27,040
Speaker 1: public companies that normally own publicly traded equities, and they

965
01:03:27,200 --> 01:03:32,480
Speaker 1: have been paying valuations that are higher than the comparable

966
01:03:32,560 --> 01:03:39,000
Speaker 1: valuations of already public web services companies. They're paying premium.

967
01:03:39,080 --> 01:03:41,880
Speaker 1: They're paying a premium. Now. In the old days, back

968
01:03:42,000 --> 01:03:43,920
Speaker 1: back when there was no I P. O market in

969
01:03:44,000 --> 01:03:47,600
Speaker 1: my prior life, we raise capital my old firm at

970
01:03:47,600 --> 01:03:51,320
Speaker 1: Eberstat back in the late seventies for emerging growth companies

971
01:03:51,360 --> 01:03:55,880
Speaker 1: that were already profitable that we're growing and we and

972
01:03:56,160 --> 01:04:01,200
Speaker 1: we valued them at below the public companies because there

973
01:04:01,240 --> 01:04:05,280
Speaker 1: was no liquidity. Because my my question is why I

974
01:04:05,360 --> 01:04:09,560
Speaker 1: was about to say, why it's strictly driven by the

975
01:04:09,560 --> 01:04:16,080
Speaker 1: liquidity factor. Well, the premium paying premium for illiquidity is

976
01:04:16,400 --> 01:04:18,560
Speaker 1: the one thing you know is it won't last. It

977
01:04:18,600 --> 01:04:22,000
Speaker 1: won't last. You can every bubble, and the Unicorn bubble

978
01:04:22,160 --> 01:04:26,280
Speaker 1: is is a bubble. Every bubble has a plausible story

979
01:04:26,560 --> 01:04:30,080
Speaker 1: somewhere under the hood, right, Well, the narrative always gets

980
01:04:30,080 --> 01:04:33,880
Speaker 1: you to suspend your irrational self because the narrative is

981
01:04:33,920 --> 01:04:36,680
Speaker 1: so compelling. Even the south Sea Bubble, the south Sea

982
01:04:36,680 --> 01:04:38,680
Speaker 1: Company was going to take over all the trade to

983
01:04:39,160 --> 01:04:43,439
Speaker 1: South America as the Spanish Empire collapsed. But this time

984
01:04:43,480 --> 01:04:48,000
Speaker 1: the story is very plausible because with the Internet matured

985
01:04:49,120 --> 01:04:56,360
Speaker 1: as a medium for distributing and consuming services with zero

986
01:04:56,480 --> 01:04:59,920
Speaker 1: cost and and just incremental renting the cost of run

987
01:05:00,040 --> 01:05:04,000
Speaker 1: in it, the reach the potential scale of these new

988
01:05:04,040 --> 01:05:08,000
Speaker 1: companies appears to be limitless. So you have the appears

989
01:05:08,080 --> 01:05:10,440
Speaker 1: to be limitless, but we know nothing real well, but

990
01:05:10,760 --> 01:05:13,560
Speaker 1: so you have these examples, you have these proof points.

991
01:05:13,840 --> 01:05:16,120
Speaker 1: One of the jokes, one of the lines people use

992
01:05:16,280 --> 01:05:21,480
Speaker 1: is um it's motivated. The Unicorn bubble is motivated motivated

993
01:05:21,560 --> 01:05:29,760
Speaker 1: by fomo fear of missing out in pursuing the next FAGA, Facebook, Apple, Google, Amazon.

994
01:05:30,800 --> 01:05:37,400
Speaker 1: So the for the time being, as long as these

995
01:05:37,440 --> 01:05:42,040
Speaker 1: companies have access to what appears to be limitless capital,

996
01:05:42,120 --> 01:05:47,120
Speaker 1: so they they're avoiding too marks to reality. There are

997
01:05:47,160 --> 01:05:50,200
Speaker 1: two ways these these valuations will get marked to reality.

998
01:05:50,640 --> 01:05:53,360
Speaker 1: One is they do an I p O. You know,

999
01:05:53,800 --> 01:05:55,680
Speaker 1: you get a price every day, and you know, the

1000
01:05:55,760 --> 01:05:57,880
Speaker 1: joke is the I p O is the new down round.

1001
01:05:59,120 --> 01:06:01,200
Speaker 1: You know, look at school. I do not know that,

1002
01:06:01,280 --> 01:06:04,840
Speaker 1: but that's very funny. And and the other is sooner

1003
01:06:05,000 --> 01:06:11,480
Speaker 1: or later, positive cash flow is corporate happiness. Sooner or later.

1004
01:06:11,960 --> 01:06:15,000
Speaker 1: If you have a sustainable business, you're gonna be paying

1005
01:06:15,000 --> 01:06:18,680
Speaker 1: your bills based on what your customers give you, not

1006
01:06:18,840 --> 01:06:21,520
Speaker 1: what your investors give you. And therefore you have an

1007
01:06:21,520 --> 01:06:25,480
Speaker 1: objective way to mark the valuation relative to earnings. And

1008
01:06:25,520 --> 01:06:29,960
Speaker 1: we're gonna see which of these companies are able to

1009
01:06:30,240 --> 01:06:37,040
Speaker 1: monetize the usage that they're generating in order to generate

1010
01:06:37,160 --> 01:06:40,680
Speaker 1: positive cash flow. Doesn't have to be a lot. Amazon

1011
01:06:40,800 --> 01:06:43,480
Speaker 1: doesn't generate a lot of positive cash flow. But you

1012
01:06:43,560 --> 01:06:45,840
Speaker 1: and I know that Jeff Bezos has about fifty three

1013
01:06:45,880 --> 01:06:49,440
Speaker 1: different levers he wants to generate cash. He just tweaked,

1014
01:06:49,600 --> 01:06:54,680
Speaker 1: you know, tweaks uh free shipping another buck on Amazon Prime.

1015
01:06:54,720 --> 01:06:57,600
Speaker 1: He's got an infinite number of ways because he's got

1016
01:06:57,600 --> 01:07:01,280
Speaker 1: a real sustainable business. Amazingly, his investors have allowed him

1017
01:07:01,280 --> 01:07:05,200
Speaker 1: to take twenty years to be profit free while building

1018
01:07:05,240 --> 01:07:09,200
Speaker 1: out what is now one of the most valuable, disruptive

1019
01:07:09,360 --> 01:07:12,240
Speaker 1: businesses in the world. And he has been He's been

1020
01:07:12,280 --> 01:07:17,240
Speaker 1: a genius at exploiting the opportunity to maximize growth subject

1021
01:07:17,280 --> 01:07:21,240
Speaker 1: to minimum positive cash flow. And I think it is

1022
01:07:21,320 --> 01:07:24,600
Speaker 1: because people appreciate that he can generate more cash flow.

1023
01:07:24,600 --> 01:07:27,040
Speaker 1: He can trade growth for cash flow any day he

1024
01:07:27,120 --> 01:07:31,560
Speaker 1: wants through a dozen different levers. So you you mentioned Amazon.

1025
01:07:32,200 --> 01:07:35,000
Speaker 1: Not too long ago, Tim Cook was on sixty Minutes

1026
01:07:35,040 --> 01:07:39,080
Speaker 1: and he mentioned, they're not that far away from the

1027
01:07:39,280 --> 01:07:44,400
Speaker 1: billion iPhones sold. Stop and think about a billion of

1028
01:07:44,480 --> 01:07:49,240
Speaker 1: these at five hundred bucks apiece. No wonder that the

1029
01:07:49,240 --> 01:07:52,880
Speaker 1: biggest and wealthiest company. We could talk about Facebook, we

1030
01:07:52,920 --> 01:07:55,360
Speaker 1: could talk about Google, but I know I don't have

1031
01:07:55,480 --> 01:07:57,760
Speaker 1: you all day, So I want to get to some

1032
01:07:57,840 --> 01:08:01,280
Speaker 1: of my favorite questions that I asked, and and we

1033
01:08:01,320 --> 01:08:04,440
Speaker 1: we skipped enough questions that we could do another hour.

1034
01:08:04,560 --> 01:08:06,320
Speaker 1: But let me let me work through some of these,

1035
01:08:06,360 --> 01:08:10,720
Speaker 1: because um, these are what really hangs some meat on

1036
01:08:10,720 --> 01:08:13,800
Speaker 1: the bones. So you mentioned going to M. I. T.

1037
01:08:14,040 --> 01:08:18,080
Speaker 1: And seeing what they were doing with economic modeling, and

1038
01:08:18,160 --> 01:08:20,800
Speaker 1: you've mentioned another number of people have been influential. But

1039
01:08:20,840 --> 01:08:24,160
Speaker 1: I have to specifically ask who were your mentors? Who

1040
01:08:24,160 --> 01:08:29,400
Speaker 1: are the people who really shaped your intellectual philosophy. I'd

1041
01:08:29,400 --> 01:08:31,960
Speaker 1: say there were three. First of all, there was the

1042
01:08:32,000 --> 01:08:35,200
Speaker 1: founder of the firm I joined soon after he died.

1043
01:08:35,240 --> 01:08:38,840
Speaker 1: His name was Ferdinand Everstadt. He was probably the greatest

1044
01:08:39,040 --> 01:08:42,280
Speaker 1: unknown American of the middle of the twentieth century. Really

1045
01:08:42,360 --> 01:08:47,440
Speaker 1: in nineteen twenty nine he wrote nineteen He wrote the

1046
01:08:47,439 --> 01:08:49,639
Speaker 1: the Young Plan that was going to save the world

1047
01:08:49,720 --> 01:08:53,400
Speaker 1: from reparations and war debts blown up by the depression,

1048
01:08:53,439 --> 01:08:56,000
Speaker 1: by by the crash of twenty nine and the depression.

1049
01:08:56,040 --> 01:08:59,880
Speaker 1: But during the war he ran industrial mobilization for World

1050
01:09:00,000 --> 01:09:03,840
Speaker 1: War Two on a dollar a year. In between, he

1051
01:09:04,000 --> 01:09:07,719
Speaker 1: started his own firm and created the first mutual fund

1052
01:09:08,120 --> 01:09:12,559
Speaker 1: after nineteen nine, the first fund investing only in the

1053
01:09:12,640 --> 01:09:15,880
Speaker 1: science based industry. That's why it was called Chemical Fund.

1054
01:09:16,400 --> 01:09:19,240
Speaker 1: After the war, he wrote the National Security Actor nineteen

1055
01:09:19,320 --> 01:09:22,920
Speaker 1: forty seven, which created the Defense Department. He was a

1056
01:09:22,960 --> 01:09:28,080
Speaker 1: public private financier, public servant. I knew him from when

1057
01:09:28,080 --> 01:09:30,440
Speaker 1: I was a boy. He was a great Princeton alumnus.

1058
01:09:30,840 --> 01:09:32,879
Speaker 1: He was one of the funders of the original Woodrow

1059
01:09:32,920 --> 01:09:37,439
Speaker 1: Wilson School. He taught me about this intersection between Wall

1060
01:09:37,479 --> 01:09:41,200
Speaker 1: Street and Washington, this dynamic play between private and public

1061
01:09:41,240 --> 01:09:49,439
Speaker 1: sector in a positive way. Lawrence lobbying votes factly, how

1062
01:09:49,479 --> 01:09:52,759
Speaker 1: the collaboration between the two could create a great country.

1063
01:09:53,280 --> 01:09:56,360
Speaker 1: Second mentor was Ed Giles. Ed Giles gave me my

1064
01:09:56,439 --> 01:09:58,639
Speaker 1: shot at every stat He was one of the greatest

1065
01:09:58,880 --> 01:10:04,360
Speaker 1: investment analysts in history. He had three business cards, Chemical Analysts,

1066
01:10:05,120 --> 01:10:09,040
Speaker 1: director of Research, and President. He only used the chemical

1067
01:10:09,040 --> 01:10:15,000
Speaker 1: analyst card. He taught me about going deep, really understanding

1068
01:10:15,040 --> 01:10:18,520
Speaker 1: the dynamics of the industry, whether it's chemicals or computing,

1069
01:10:19,000 --> 01:10:22,280
Speaker 1: in which you want to play a role in in

1070
01:10:22,479 --> 01:10:26,960
Speaker 1: finding investments, in defining investment opportunities. And then the third.

1071
01:10:27,000 --> 01:10:31,080
Speaker 1: The third was an extraordinary man named Fred Adler. Fred

1072
01:10:31,120 --> 01:10:35,800
Speaker 1: Adler in the nineteen eighties, nineteen seventies and eighties was

1073
01:10:36,000 --> 01:10:40,840
Speaker 1: an iconic venture capitalist. He was a lawyer, he was

1074
01:10:41,080 --> 01:10:46,080
Speaker 1: a turnaround artist, a crisis manager, and he was a

1075
01:10:46,160 --> 01:10:52,840
Speaker 1: venture capitalist. And Fred Fred had an unusual personality. Um

1076
01:10:52,880 --> 01:10:55,960
Speaker 1: he Uh. He was very tough, very tough with people

1077
01:10:56,000 --> 01:10:59,439
Speaker 1: who worked for him. Uh. He had funded one of

1078
01:10:59,479 --> 01:11:04,120
Speaker 1: the second of the great mini computer companies, Data General.

1079
01:11:04,479 --> 01:11:07,920
Speaker 1: He built a firm, He built a firm Uncle. Data

1080
01:11:08,000 --> 01:11:11,120
Speaker 1: General became a huge company absolutely, and Fred put the

1081
01:11:11,160 --> 01:11:14,880
Speaker 1: money together financing together for that ten years later, fifteen

1082
01:11:14,960 --> 01:11:17,280
Speaker 1: years as after Arthur Rocket put the money together for

1083
01:11:17,400 --> 01:11:21,160
Speaker 1: fair Child, semi same kind of way. Um. Fred taught

1084
01:11:21,200 --> 01:11:28,720
Speaker 1: me about how to understand the internal dynamics of a

1085
01:11:28,920 --> 01:11:32,880
Speaker 1: business followed the cash Fred, you had these had these

1086
01:11:32,920 --> 01:11:36,320
Speaker 1: pillows made up that said corporate happiness is positive cash

1087
01:11:36,320 --> 01:11:39,320
Speaker 1: flow and used to throw them at his entrepreneurs. In

1088
01:11:39,400 --> 01:11:41,439
Speaker 1: between yelling and screaming at him. I used to tell

1089
01:11:41,479 --> 01:11:43,760
Speaker 1: him that the only compliment he ever gave me was

1090
01:11:43,800 --> 01:11:47,240
Speaker 1: that he never offered me a job because he but

1091
01:11:47,240 --> 01:11:49,200
Speaker 1: but the guys who found an Axcel one of the

1092
01:11:49,240 --> 01:11:52,479
Speaker 1: great firms in the world, they were they worked for

1093
01:11:52,520 --> 01:11:55,600
Speaker 1: Fred back in the in the early nineteen eighties. So

1094
01:11:55,720 --> 01:11:59,799
Speaker 1: Fred and I collaborated. We created a number of companies together.

1095
01:11:59,840 --> 01:12:03,720
Speaker 1: One of them was emerged as Life Technologies, the the

1096
01:12:03,760 --> 01:12:08,479
Speaker 1: company that provided the tools for all the people doing biotechnology.

1097
01:12:09,080 --> 01:12:11,639
Speaker 1: So that was my third mentor before I joined before

1098
01:12:11,640 --> 01:12:14,200
Speaker 1: I joined Warburg Pinkas. So so these are mentors. What

1099
01:12:14,240 --> 01:12:18,599
Speaker 1: about investors who influenced your approach to investing? You mentioned

1100
01:12:18,680 --> 01:12:22,080
Speaker 1: Keynes as obviously a key influencer. I think a lot

1101
01:12:22,120 --> 01:12:25,280
Speaker 1: of people don't realize what a great investor he was.

1102
01:12:25,800 --> 01:12:29,320
Speaker 1: Kaine's John Maynard Keynes was was a great investor. Um,

1103
01:12:29,439 --> 01:12:31,600
Speaker 1: I didn't know him personally. He died when I was

1104
01:12:31,640 --> 01:12:34,160
Speaker 1: three years So I was gonna say what other investors, well,

1105
01:12:34,640 --> 01:12:39,720
Speaker 1: Vogustin John Boglestein was the founding chief investment officer and

1106
01:12:39,800 --> 01:12:43,800
Speaker 1: president of Warburg Pinkas. John was a great investor. He

1107
01:12:43,960 --> 01:12:47,280
Speaker 1: hired me, he gave me my shot at Warburg Pinkas,

1108
01:12:47,840 --> 01:12:52,320
Speaker 1: and he had, as I say, in extraordinary knows from

1109
01:12:52,360 --> 01:12:56,360
Speaker 1: markets and he was he was one of the fundamental contrarians.

1110
01:12:56,880 --> 01:13:00,759
Speaker 1: And so he helped me understand that, you know, being

1111
01:13:00,800 --> 01:13:06,080
Speaker 1: patient looking for where the world isn't looking building new

1112
01:13:06,160 --> 01:13:10,639
Speaker 1: businesses or there's a It actually ties very closely to Kines.

1113
01:13:10,680 --> 01:13:14,240
Speaker 1: There's a wonderful passage in Kiness general theory where he

1114
01:13:14,280 --> 01:13:17,640
Speaker 1: talks about how the value the price of shares in

1115
01:13:17,680 --> 01:13:24,240
Speaker 1: the market has an inevitable impact on investment activity in

1116
01:13:24,240 --> 01:13:27,439
Speaker 1: the real economy. He says, it makes it makes no

1117
01:13:27,479 --> 01:13:29,800
Speaker 1: sense to start a new business if you can buy

1118
01:13:29,800 --> 01:13:32,040
Speaker 1: one on the stock exchange more cheaply than it would

1119
01:13:32,080 --> 01:13:35,280
Speaker 1: cost to start it. Kane's this is the ninety six

1120
01:13:35,320 --> 01:13:39,680
Speaker 1: He saw the LBO business in advance, and then on

1121
01:13:39,960 --> 01:13:41,760
Speaker 1: the other hand, he said, it could it could be

1122
01:13:42,000 --> 01:13:46,759
Speaker 1: worthwhile to take an extravagant amount of money to invest

1123
01:13:46,800 --> 01:13:49,400
Speaker 1: in a startup like b e A if you can

1124
01:13:49,439 --> 01:13:52,040
Speaker 1: float it on the stock exchange for a profit. So

1125
01:13:52,120 --> 01:13:57,439
Speaker 1: this dynamic feedback between what's happening in the stock market

1126
01:13:57,800 --> 01:14:01,400
Speaker 1: and what's happening with real investment from John Maynard Kin's

1127
01:14:01,400 --> 01:14:05,120
Speaker 1: to John Vogelstein and my experience is a seamless web.

1128
01:14:05,520 --> 01:14:08,679
Speaker 1: Those were my mentors. How about books aside from your

1129
01:14:08,720 --> 01:14:11,479
Speaker 1: own book, and I could tell by your writing that

1130
01:14:11,520 --> 01:14:14,639
Speaker 1: you've read quite widely. What what are some of your

1131
01:14:14,680 --> 01:14:21,040
Speaker 1: favorite books, whether they're about investing and venture capital or

1132
01:14:21,080 --> 01:14:25,479
Speaker 1: anything else. Well, of course, the general theory changed my life.

1133
01:14:25,520 --> 01:14:29,480
Speaker 1: It's why I went to Cambridge. It remains an enormous

1134
01:14:29,600 --> 01:14:34,680
Speaker 1: UH reservoir of insight and understanding about people making economic

1135
01:14:34,720 --> 01:14:38,680
Speaker 1: and financial decisions. Hi Minsky's book UH it's got a

1136
01:14:38,800 --> 01:14:44,439
Speaker 1: terrible title, Stabilizing an Unstable Economy, But boy, if if

1137
01:14:44,479 --> 01:14:47,000
Speaker 1: you if you'd read it before two thousand and eight.

1138
01:14:47,080 --> 01:14:49,840
Speaker 1: And by the way, and Tim Geitner's memoir, my partner,

1139
01:14:49,920 --> 01:14:53,519
Speaker 1: Tim Geitner, who's president at Warburg broncas now he talks

1140
01:14:53,560 --> 01:14:57,479
Speaker 1: about how, having been immersed in the in the Asian

1141
01:14:57,560 --> 01:15:02,000
Speaker 1: financial crisis of the late nineties, he read Minsky. So

1142
01:15:02,080 --> 01:15:05,840
Speaker 1: he was prepared intellectually for two thousand and eight in

1143
01:15:05,880 --> 01:15:09,520
Speaker 1: a way that most policymakers were not. Uh. So Minsky's

1144
01:15:09,560 --> 01:15:14,160
Speaker 1: work tremendously important. The There are two books that I've

1145
01:15:14,160 --> 01:15:17,280
Speaker 1: read recently that I would recommend to everyone. UH. They're

1146
01:15:17,280 --> 01:15:21,160
Speaker 1: not they're not directly economics books. One is UH. It's

1147
01:15:21,160 --> 01:15:25,320
Speaker 1: a book by a young historian called Jonathan Levy. It's

1148
01:15:25,360 --> 01:15:30,040
Speaker 1: called Freaks of Fortune. Freaks of Fortune. It came out

1149
01:15:30,160 --> 01:15:35,920
Speaker 1: last year, and it's about how during the nineteenth century

1150
01:15:36,040 --> 01:15:40,920
Speaker 1: in the United States we involved evolved a whole array

1151
01:15:41,200 --> 01:15:46,160
Speaker 1: of new institutions for dealing with the risks and uncertainties

1152
01:15:46,479 --> 01:15:52,440
Speaker 1: of an industrializing economy, adopting British patterns of maritime insurance

1153
01:15:52,840 --> 01:15:59,160
Speaker 1: to insurance of UH for railroads UH and right through

1154
01:15:59,280 --> 01:16:03,800
Speaker 1: the creation of credit unions sharing financial risk. It's a

1155
01:16:03,840 --> 01:16:07,920
Speaker 1: tremendous book I really recommended very strongly. And the second one,

1156
01:16:08,080 --> 01:16:11,599
Speaker 1: the second the second is a book that I literally

1157
01:16:11,640 --> 01:16:17,160
Speaker 1: just finished reading yesterday. It's called Liberty and Coercion. Liberty

1158
01:16:17,520 --> 01:16:21,799
Speaker 1: and Coercion. It's written by a historian named Gary Gerstel

1159
01:16:21,920 --> 01:16:25,880
Speaker 1: g E. R. S. T. L E. He just moved

1160
01:16:26,000 --> 01:16:29,519
Speaker 1: from the United States to Cambridge, England as the Paul

1161
01:16:29,560 --> 01:16:35,880
Speaker 1: Mellon Professor of American History. It's an extraordinary exploration of

1162
01:16:36,000 --> 01:16:45,120
Speaker 1: the dynamic, contradictory intersection between the federal government, whose powers

1163
01:16:45,200 --> 01:16:51,240
Speaker 1: were enumerated listed in the Constitution, and the state governments,

1164
01:16:51,280 --> 01:16:55,559
Speaker 1: which inherited the more or less unlimited power of the

1165
01:16:55,600 --> 01:17:00,719
Speaker 1: British police power the British state. So that even while

1166
01:17:00,800 --> 01:17:04,320
Speaker 1: the federal government is limited by the by the Um

1167
01:17:06,320 --> 01:17:09,000
Speaker 1: and the Constitution and the Bill of Rights, the states

1168
01:17:09,040 --> 01:17:12,240
Speaker 1: could tell you whether you can own another human being,

1169
01:17:13,080 --> 01:17:18,519
Speaker 1: who you were allowed to marry, whether you could own

1170
01:17:18,520 --> 01:17:23,200
Speaker 1: a home. The power of the state was effectively limitless.

1171
01:17:23,920 --> 01:17:27,200
Speaker 1: And this conflict that of course exploded in the Civil War.

1172
01:17:28,240 --> 01:17:33,759
Speaker 1: Then after the Civil Rights amendments, the States struck back

1173
01:17:34,520 --> 01:17:39,960
Speaker 1: and segregation was entirely a function of state law. Then

1174
01:17:40,320 --> 01:17:44,480
Speaker 1: with the Great with the New Deal and the Great Society,

1175
01:17:44,560 --> 01:17:49,639
Speaker 1: the thirty years of the exertion of federal authority over

1176
01:17:49,680 --> 01:17:54,000
Speaker 1: the states, and then now the counter thrust against it

1177
01:17:54,680 --> 01:17:58,720
Speaker 1: under the Robert's Court. So this is an extraordinary Very

1178
01:17:58,760 --> 01:18:01,200
Speaker 1: little attention has been paid to what goes on at

1179
01:18:01,280 --> 01:18:05,920
Speaker 1: state level in the US, but for citizens and non

1180
01:18:05,960 --> 01:18:09,160
Speaker 1: citizens in America is what happens at the state level

1181
01:18:09,360 --> 01:18:11,280
Speaker 1: is at least as important at the federal It's a

1182
01:18:11,320 --> 01:18:13,639
Speaker 1: great book. It's amazing when you step back and look

1183
01:18:13,680 --> 01:18:17,680
Speaker 1: at things through a longer timeframe, how these phases and

1184
01:18:18,240 --> 01:18:21,920
Speaker 1: faints and counterfeits become so obvious that you don't see

1185
01:18:21,920 --> 01:18:24,280
Speaker 1: in the day to day operation. It's true for markets,

1186
01:18:24,320 --> 01:18:27,040
Speaker 1: it's true for history. If there's one thing that I

1187
01:18:27,120 --> 01:18:30,120
Speaker 1: feel that I've had an unfair advantage of because of

1188
01:18:30,680 --> 01:18:35,920
Speaker 1: the education I had, it's being able to bring to

1189
01:18:36,400 --> 01:18:39,920
Speaker 1: the immediate situation, whether it's a dot com bubble in

1190
01:18:39,960 --> 01:18:42,880
Speaker 1: two thousand and eight, or whether it's the global financial

1191
01:18:42,920 --> 01:18:45,680
Speaker 1: crisis two thousands, of the global financial crisis in two

1192
01:18:45,720 --> 01:18:49,840
Speaker 1: thousand and eight, it's a longer term historical perspective that

1193
01:18:49,960 --> 01:18:53,360
Speaker 1: crosses over from economics to politics and backing. So so

1194
01:18:53,520 --> 01:18:56,400
Speaker 1: let me digress from my questions and ask something I

1195
01:18:56,439 --> 01:18:59,720
Speaker 1: did not want to skip. So, Cambridge a couple of

1196
01:18:59,800 --> 01:19:03,880
Speaker 1: years ago just celebrated its eight hundred year I think

1197
01:19:03,880 --> 01:19:08,160
Speaker 1: it was twelve or six and twelve o nine. Um,

1198
01:19:08,240 --> 01:19:11,640
Speaker 1: so it's been around a couple of years. You're not

1199
01:19:11,800 --> 01:19:14,920
Speaker 1: only a member of the uh CO, chair of the

1200
01:19:15,000 --> 01:19:18,400
Speaker 1: eight hundred campaign for the University of Cambridge, but you

1201
01:19:18,520 --> 01:19:24,000
Speaker 1: funded an endowment for research in finance at Cambridge as

1202
01:19:24,000 --> 01:19:31,160
Speaker 1: well as creating a um U k US connection for

1203
01:19:31,160 --> 01:19:34,240
Speaker 1: for research on both sides of the Atlantic. Tell us

1204
01:19:34,280 --> 01:19:37,920
Speaker 1: what you want to accomplish with that that endowment and

1205
01:19:37,920 --> 01:19:41,000
Speaker 1: and what the impact of that has been. Well, when

1206
01:19:41,000 --> 01:19:43,719
Speaker 1: I went to Cambridge on a Marshall scholarship in nineteen

1207
01:19:43,800 --> 01:19:47,479
Speaker 1: sixty five, just exactly fifty years ago, the four years

1208
01:19:47,479 --> 01:19:50,519
Speaker 1: I was there just changed my life um and and

1209
01:19:50,520 --> 01:19:55,840
Speaker 1: and getting reconnected with Cambridge as I did UH in

1210
01:19:55,960 --> 01:19:59,920
Speaker 1: the in the nineties, in particular at a time when

1211
01:20:00,040 --> 01:20:03,519
Speaker 1: and a major change was going on in Britain and

1212
01:20:03,560 --> 01:20:07,240
Speaker 1: had already been going on in the US from the

1213
01:20:07,320 --> 01:20:10,679
Speaker 1: end of World War Two through the nineteen eighties into

1214
01:20:10,680 --> 01:20:14,599
Speaker 1: the nineteen nineties, Cambridge and the other great British universities Oxford.

1215
01:20:14,600 --> 01:20:18,559
Speaker 1: Of course we're essentially funded by the government. They were

1216
01:20:18,760 --> 01:20:24,880
Speaker 1: essentially national institutions. But just as the state universities in

1217
01:20:24,880 --> 01:20:28,439
Speaker 1: America in effect over the course of fifty years, have

1218
01:20:28,560 --> 01:20:32,680
Speaker 1: been privatized, so that state legislatures are responsible for less

1219
01:20:32,720 --> 01:20:35,680
Speaker 1: than ten percent and declining, and probably most of that

1220
01:20:35,720 --> 01:20:39,439
Speaker 1: goes for the football coaches salary, most of that for

1221
01:20:39,479 --> 01:20:42,320
Speaker 1: the worst, say the least. Um. So this idea of

1222
01:20:42,360 --> 01:20:45,040
Speaker 1: the of the university, of a national or a state

1223
01:20:45,080 --> 01:20:50,160
Speaker 1: university is a public good was being dismantled. Cambridge, with

1224
01:20:50,280 --> 01:20:54,000
Speaker 1: this incredible history, you know, from Newton to Darwin to

1225
01:20:54,360 --> 01:20:58,280
Speaker 1: Krick and Watson to Keynes, the the you know, probably

1226
01:20:58,640 --> 01:21:03,439
Speaker 1: the source of more original thinking that changed the world

1227
01:21:03,560 --> 01:21:11,040
Speaker 1: over the last five years. UM, Cambridge was discovering that it, too,

1228
01:21:11,080 --> 01:21:14,280
Speaker 1: like the American universities, was going to have to depend

1229
01:21:14,560 --> 01:21:19,360
Speaker 1: on private philanthropy to supplement, if not replace, the money

1230
01:21:19,400 --> 01:21:23,120
Speaker 1: that had been coming from the government. So I got

1231
01:21:23,120 --> 01:21:26,360
Speaker 1: involved as as an American and knew something about philanthropy.

1232
01:21:26,439 --> 01:21:29,520
Speaker 1: After all of your principal alumnus you know about fundraising,

1233
01:21:30,320 --> 01:21:35,519
Speaker 1: UM and and and at the same time, internally, Cambridge

1234
01:21:35,520 --> 01:21:40,400
Speaker 1: was going through some internal reforms towards a greater degree

1235
01:21:40,439 --> 01:21:43,960
Speaker 1: of professionalism in the leadership, the academic leadership, and the

1236
01:21:43,960 --> 01:21:49,679
Speaker 1: governance of the university. So on the one hand, given

1237
01:21:49,720 --> 01:21:54,719
Speaker 1: this deep history of Canes and and my perception somewhat

1238
01:21:54,720 --> 01:21:58,080
Speaker 1: ahead of the time, I have to confess that finance

1239
01:21:58,120 --> 01:22:01,120
Speaker 1: and economics are one discipline in that they what goes

1240
01:22:01,160 --> 01:22:03,640
Speaker 1: on in the stock market, goes on in the real economy,

1241
01:22:03,880 --> 01:22:06,360
Speaker 1: goes on the banking system. All of that needs to

1242
01:22:06,360 --> 01:22:09,160
Speaker 1: be brought together. That's why my wife and I initially

1243
01:22:09,200 --> 01:22:13,000
Speaker 1: funded the Cambridge Endowment for Research in Finance. But it

1244
01:22:13,080 --> 01:22:17,759
Speaker 1: was really joining forces with an extraordinary woman, Alison Richard,

1245
01:22:17,800 --> 01:22:21,160
Speaker 1: had been Provost of Yale. She became Vice Chancellor of

1246
01:22:21,280 --> 01:22:24,759
Speaker 1: Cambridge at the start of the new millennium and we launched.

1247
01:22:25,160 --> 01:22:28,360
Speaker 1: What I said to Alison, we should present this as

1248
01:22:28,520 --> 01:22:32,240
Speaker 1: this is the first fundraising campaign for Cambridge since Henry

1249
01:22:32,240 --> 01:22:35,519
Speaker 1: the eighth knocked off the monasteries. It will not be

1250
01:22:35,560 --> 01:22:39,640
Speaker 1: the last, and it isn't. We completed that campaign. We

1251
01:22:39,760 --> 01:22:42,120
Speaker 1: raised more than a billion pounds. Nobody had done that

1252
01:22:42,160 --> 01:22:46,400
Speaker 1: in Britain ever before. We didn't only raise money we

1253
01:22:46,479 --> 01:22:51,000
Speaker 1: raised consciousness. We raised consciousness among alumni, among leaders of

1254
01:22:51,040 --> 01:22:55,200
Speaker 1: other universities. It has to be some alumni association. You

1255
01:22:55,240 --> 01:22:57,919
Speaker 1: think about all the people have come out of Cambridge,

1256
01:22:57,960 --> 01:23:01,000
Speaker 1: that's that's quite an illustrious list. But they spent two

1257
01:23:01,120 --> 01:23:05,000
Speaker 1: three generations where if you ask somebody about giving some

1258
01:23:05,040 --> 01:23:07,840
Speaker 1: money to Cambridge, the answer would be, hey, I pay

1259
01:23:07,920 --> 01:23:13,000
Speaker 1: my taxes. So building a culture of philanthropy is a

1260
01:23:13,040 --> 01:23:18,680
Speaker 1: generation's long process. That's amazing. Now Cambridge has launched its

1261
01:23:18,680 --> 01:23:24,000
Speaker 1: second campaign two billion pounds double or nothing. They got

1262
01:23:24,040 --> 01:23:26,719
Speaker 1: thirty billion pounds to catch up to Harvard and Yaleen's

1263
01:23:26,760 --> 01:23:29,040
Speaker 1: they do they do that? You would think they had

1264
01:23:29,080 --> 01:23:32,000
Speaker 1: an eight hundred year or year head start. Well, some

1265
01:23:32,160 --> 01:23:35,120
Speaker 1: of the endowments to college endowments go way way back,

1266
01:23:35,160 --> 01:23:38,719
Speaker 1: did didn't Cain's actually manage some of the Caine manage

1267
01:23:38,720 --> 01:23:41,920
Speaker 1: the money of King's College, that's right, his college and

1268
01:23:42,240 --> 01:23:45,320
Speaker 1: uh and and by the way, Cambridge now has a

1269
01:23:45,479 --> 01:23:49,640
Speaker 1: very well managed professional endowment fund, which I'm pleased to

1270
01:23:49,680 --> 01:23:52,800
Speaker 1: say over the last year two has done at least

1271
01:23:52,800 --> 01:23:55,760
Speaker 1: as well as Harvard and Yale at Princeton Um. So

1272
01:23:55,920 --> 01:24:00,000
Speaker 1: the money that's given to Cambridge is very well taken

1273
01:24:00,040 --> 01:24:04,560
Speaker 1: can care of. And the breadth of the um donations

1274
01:24:04,680 --> 01:24:09,280
Speaker 1: and the breadth of the professionalism of fundraising at Cambridge

1275
01:24:09,280 --> 01:24:12,920
Speaker 1: in the last fifteen years has been tremendous. It is,

1276
01:24:13,000 --> 01:24:17,920
Speaker 1: it really is a great achievement. Celebrating the emergence of

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01:24:18,040 --> 01:24:22,440
Speaker 1: Cambridge's own revival of post two thousand and eight economics,

1278
01:24:22,680 --> 01:24:26,479
Speaker 1: My wife and I just made another major contribution million

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01:24:26,520 --> 01:24:31,880
Speaker 1: dollars for a professorship in financial economics and a fund

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01:24:31,920 --> 01:24:38,839
Speaker 1: for economics which will guarantee that the pore research funding

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01:24:39,000 --> 01:24:42,519
Speaker 1: is perpetuated. It's an endowment, not spend down money. And

1282
01:24:42,600 --> 01:24:45,439
Speaker 1: that's and that's at Cambridge. That's at Cambridge. So what

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01:24:45,439 --> 01:24:47,599
Speaker 1: do you say to Princeton when they come knock. I've

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01:24:47,760 --> 01:24:50,240
Speaker 1: I've also First of all, of course, Princeton is the

1285
01:24:50,320 --> 01:24:53,360
Speaker 1: richest university in the world per capita. Is that true? Yes,

1286
01:24:53,439 --> 01:24:56,920
Speaker 1: I had no idea. And second, we also, celebrating my

1287
01:24:57,000 --> 01:25:00,200
Speaker 1: fifty three union at Princeton, have funded a pro am

1288
01:25:00,200 --> 01:25:03,200
Speaker 1: in financial economics at Princeton, which I'm delighted to say

1289
01:25:03,280 --> 01:25:07,320
Speaker 1: has has taken root. So given all this education, let's

1290
01:25:07,479 --> 01:25:12,720
Speaker 1: let's talk about the students who are just graduating. The millennials,

1291
01:25:12,760 --> 01:25:16,880
Speaker 1: and soon there's going to be in another generation behind them.

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01:25:16,920 --> 01:25:19,800
Speaker 1: What advice would you give to someone coming out of

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01:25:19,800 --> 01:25:26,120
Speaker 1: school today who's interested in economics and venture capital and finance. What,

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01:25:26,400 --> 01:25:29,320
Speaker 1: Because it's a different world today than when I started,

1295
01:25:29,320 --> 01:25:31,880
Speaker 1: and certainly that from when you started. What sort of

1296
01:25:31,880 --> 01:25:33,880
Speaker 1: advice would you give someone who wants to go into

1297
01:25:33,920 --> 01:25:37,200
Speaker 1: your field. Well, first of all, the world is very,

1298
01:25:37,280 --> 01:25:40,000
Speaker 1: very competitive. It's more more competitive than it was. It's

1299
01:25:40,000 --> 01:25:43,680
Speaker 1: more open, there's more access, and that's that's unquestionably a

1300
01:25:43,760 --> 01:25:48,240
Speaker 1: good thing. Um. I I speak a bit as a father,

1301
01:25:48,280 --> 01:25:50,760
Speaker 1: a very proud father of my twenty six year old

1302
01:25:50,760 --> 01:25:55,760
Speaker 1: son who went to Oxford as it happened, the great university,

1303
01:25:56,040 --> 01:25:59,439
Speaker 1: shame to the family. On the contrary, and an Oxford

1304
01:25:59,479 --> 01:26:02,800
Speaker 1: has a wonder full program of philosophy, politics and economics

1305
01:26:02,840 --> 01:26:08,240
Speaker 1: PPE and our son was Sperversity of Pennsylvania. It's so

1306
01:26:08,280 --> 01:26:11,960
Speaker 1: funny you mentioned that that that's its own specific thing.

1307
01:26:12,040 --> 01:26:14,559
Speaker 1: But but that advice would you give him? And what

1308
01:26:14,600 --> 01:26:18,519
Speaker 1: advice would you give other recent graduates? I'd say one

1309
01:26:18,680 --> 01:26:24,599
Speaker 1: one bit of advice is um combining a really open mind,

1310
01:26:24,640 --> 01:26:30,719
Speaker 1: really reading and reading broadly, with a willingness to get

1311
01:26:30,760 --> 01:26:32,840
Speaker 1: down to work. I mean one of the one of

1312
01:26:32,840 --> 01:26:36,439
Speaker 1: the things that just has thrilled my wife and me

1313
01:26:36,520 --> 01:26:40,439
Speaker 1: about our son is that he just loves to get

1314
01:26:40,680 --> 01:26:46,760
Speaker 1: dug into doing real work. Academics, yes, but actually real

1315
01:26:46,840 --> 01:26:53,280
Speaker 1: work out there, um, doing his apprenticeship. Um, So looking

1316
01:26:53,320 --> 01:26:59,240
Speaker 1: for opportunities two whatever the job may be, but learning

1317
01:26:59,400 --> 01:27:04,040
Speaker 1: how too. As Woody Allen said, showing up is half

1318
01:27:04,080 --> 01:27:07,080
Speaker 1: the battle. Showing up on time, doing the job you're

1319
01:27:07,080 --> 01:27:10,439
Speaker 1: asked to do, and then looking for what more there

1320
01:27:10,600 --> 01:27:15,960
Speaker 1: is to be done. That somebody is absolutely but also

1321
01:27:16,120 --> 01:27:20,680
Speaker 1: as I say, reading and thinking about the context in

1322
01:27:20,720 --> 01:27:24,960
Speaker 1: which you're working, not just going down the line. Because

1323
01:27:25,360 --> 01:27:27,840
Speaker 1: the way things have opened up so much, there's so

1324
01:27:27,880 --> 01:27:33,439
Speaker 1: many diverse possible opportunities. UM. But I do respect, I

1325
01:27:33,760 --> 01:27:37,519
Speaker 1: do recognize that it is it is so competitive today

1326
01:27:38,360 --> 01:27:45,439
Speaker 1: that um, there's no there's no guaranteed road. Um. You know,

1327
01:27:46,000 --> 01:27:52,040
Speaker 1: Thomas Edison said, perspiration ten percent inspiration. The perspiration really matters.

1328
01:27:52,080 --> 01:27:56,200
Speaker 1: But but but the informed mind can can confind opportunities

1329
01:27:56,200 --> 01:27:59,400
Speaker 1: for the inspiration too. And and then my final question,

1330
01:27:59,479 --> 01:28:01,920
Speaker 1: and I'm going to change the date on this, what

1331
01:28:02,080 --> 01:28:05,240
Speaker 1: is it that you know about investing today that you

1332
01:28:05,320 --> 01:28:08,640
Speaker 1: wish you knew fifty years or so ago when you

1333
01:28:08,760 --> 01:28:14,320
Speaker 1: left school. That's a very very good question. Um, I

1334
01:28:14,320 --> 01:28:24,000
Speaker 1: think I learned, Um, I think I learned how important? Well,

1335
01:28:24,000 --> 01:28:26,280
Speaker 1: this is something I learned from my mentor at Giles.

1336
01:28:26,320 --> 01:28:29,920
Speaker 1: I used to say, a winner is somebody who knows

1337
01:28:29,960 --> 01:28:34,040
Speaker 1: what to do when he's a loser. What's the backup plan?

1338
01:28:34,520 --> 01:28:39,599
Speaker 1: What's the hedge? What's the cash in the bank that

1339
01:28:39,640 --> 01:28:43,599
Speaker 1: you the the extra resource that you have that lets

1340
01:28:43,720 --> 01:28:48,120
Speaker 1: you survive when the world goes against you. There's a

1341
01:28:48,200 --> 01:28:50,840
Speaker 1: quote that's attributed to Cains. Nobody can ever find in

1342
01:28:50,880 --> 01:28:54,920
Speaker 1: any of his writings that the market can remain wrong

1343
01:28:55,040 --> 01:28:59,720
Speaker 1: longer than you can remain solvent. Um, So I can

1344
01:28:59,760 --> 01:29:02,160
Speaker 1: remain in irrational far longer than the average investor can

1345
01:29:02,200 --> 01:29:05,720
Speaker 1: remain solvent. That's right. And so I would say that

1346
01:29:05,760 --> 01:29:11,120
Speaker 1: it's the it's it's it's thinking in advance about what

1347
01:29:11,160 --> 01:29:13,280
Speaker 1: you're gonna do. What's plan B, what's plans to see?

1348
01:29:13,280 --> 01:29:15,280
Speaker 1: What are you gonna do when the world goes against you?

1349
01:29:15,800 --> 01:29:18,400
Speaker 1: When you plug it in, it doesn't light up? Um,

1350
01:29:18,560 --> 01:29:20,680
Speaker 1: how you going to ride out the heart? Touch? Right?

1351
01:29:21,040 --> 01:29:25,439
Speaker 1: That's right, Bill, Bill, This has been absolutely fascinating. I know,

1352
01:29:25,479 --> 01:29:28,160
Speaker 1: I promised i'd get you out of here fifteen minutes ago,

1353
01:29:28,200 --> 01:29:31,639
Speaker 1: but I just couldn't stop. We've been speaking with Bill Janeway.

1354
01:29:31,680 --> 01:29:35,760
Speaker 1: He is the author of Doing Capitalism in the Innovation Economy,

1355
01:29:36,479 --> 01:29:40,640
Speaker 1: as well as the managing partner at Warburg Pincus and

1356
01:29:40,720 --> 01:29:45,040
Speaker 1: a co founder of the Institute for New Economic Thinking.

1357
01:29:45,600 --> 01:29:49,080
Speaker 1: If you enjoy this conversation, be sure to look up

1358
01:29:49,080 --> 01:29:51,519
Speaker 1: an inch or down an inch on all of our

1359
01:29:51,840 --> 01:29:53,960
Speaker 1: previous on Apple iTunes so you can see all of

1360
01:29:53,960 --> 01:29:57,439
Speaker 1: our previous conversations. I would be remiss if I did

1361
01:29:57,439 --> 01:30:01,679
Speaker 1: not thank my recording engineer Reggie, my producer Charlie Volmer,

1362
01:30:01,800 --> 01:30:05,719
Speaker 1: and my head of research, Michael Batnick. You've been listening

1363
01:30:05,760 --> 01:30:08,439
Speaker 1: to Masters in Business on Bloomberg Radio.