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learn more, visit P S You and.

2:21

I know I am. I come over some.

2:23

Bill is a general partner of Bench More

2:25

Capital and Michael is the head of To

2:27

Sleep Research for Counterpoint Global. While. They

2:29

are longtime friends with one another. I'd never heard them

2:31

appear somewhere together, so was a real treat to be

2:34

able to do this with the two of them. There.

2:36

To the leading minds in their fields

2:38

and we combine their decades of experience

2:41

into one wide ranging conversation. We.

2:43

Discuss the different kinds of increasing returns

2:45

to scale the issue of regulatory capture

2:47

a I and hardware plus a lot

2:49

more pleasing to a this Great conversation

2:51

with overly and Michael mother some. Guys,

2:55

today's conversation is going to be an excuse to

2:58

do something that I personally want to hear for

3:00

a long time which just the two of you

3:02

and your longstanding friendship and mutual interest in markets

3:04

business investing just as your you talked to get

3:07

out of the have ever heard you at least

3:09

on the record discuss a bunch of interesting ideas

3:11

and I'm going to be my role as during

3:13

some things up and then what are you guys?

3:16

Go. I. Thought I would start with

3:18

maybe the most obvious places because it's

3:20

on everyone's mind. The both thought a

3:22

lot about it. Maybe Michael? Okay, get

3:24

you to starts. What are your thoughts

3:26

on Artificial intelligence? Were recording this on

3:29

April fifteenth in Twenty Twenty four to

3:31

scare people contact since assault cheating so

3:33

fast. The. Seems like the most important

3:35

thing maybe that's happened in a long

3:37

time, but also quite hard to parse

3:39

as an investor. What? Are your thoughts? Were

3:41

you thinking about. I want to take

3:43

it over to Build Luxury. Know a lot

3:46

more about our staff topic than I do

3:48

with Best You. My kids are very involved

3:50

in this from a professional point of these

3:52

white try to glean some from them as

3:54

well as I watched him do they're saying

3:56

for saw this is off see very profound,

3:58

very important. I don't understand all the details

4:01

of how the technology were, but I think

4:03

the most important question is an investor stepping

4:05

back is going back. Using Clay Christians and

4:07

Language of Disruptive Innovation vs. Sustaining Innovation. So.

4:10

Sustaining innovation using Christians and language

4:12

is something that is really different.

4:14

To be very mature, to be

4:16

radical, but it's within the same.

4:18

What? He called died Network. It's basically

4:20

helps the incumbents become better what they

4:23

do. And. Then a disruptive innovation is

4:25

something is a new business model that allows

4:27

new companies are sort of break in and

4:29

I see disrupt the more traditional and comments.

4:32

Took as I look at this the question

4:34

is to this has helped the strongest stronger

4:36

and by way things like you see some

4:38

of the big ai players also doing things

4:41

like. Cloud. Computing, so

4:43

they're big in multiple facets of

4:45

this. Vs. Does is allow

4:47

new businesses to start up and emerge

4:49

and disrupt a traditional guys. So.

4:51

Does at least now. Looks like some the big

4:53

guys have the pole position. Microsoft.

4:56

And Amazon and Google and Med

4:58

on so forth would you say

5:00

though? We're. I think there's

5:02

a number of. Observations. You can

5:04

make from a very high level. That.

5:06

Are important if you're thinking about a lens

5:09

or a framework for investing in a i

5:11

one of them you just mentioned which is.

5:14

This. Appears highly choreographed.

5:16

The. Windows open up huge doors

5:19

for innovators and start ups

5:21

are usually not choreograph. You.

5:24

Don't have the whole world saying look, this

5:26

is where we're going. And yet

5:28

here you do. And I think one

5:30

of the reasons why people are discussing

5:32

what you just said, which is could

5:34

the incumbents have some kind of advantages.

5:37

It was so highly choreographed and give

5:39

credit to open a I and some

5:41

of the platform players who created a

5:44

P eyes and made it very easy

5:46

and leaned in and went after these

5:48

people. So that's one. Thing.

5:50

That has happened here is there's no

5:52

one that's kind of asleep at the

5:54

wheel like people accused Microsoft being on

5:57

mobile. Which. Is where you see a

5:59

lot of opening. Though that may take

6:01

away some of the. Opportunities

6:03

that. The. Second thing I would say

6:05

is. You. Have to separate our

6:07

lives from Ai Ai. As this trend

6:09

it's been gone on for. Twenty.

6:12

Years there's some amazing stuff happening.

6:14

The example of Tesla switching to

6:16

a full A I approach for

6:18

their self driving is really like

6:21

a compelling thing, but it doesn't.

6:23

Involve Allah, Lambs and a lot

6:25

of what we'd gotten excited about

6:28

our our lands. They have. Some.

6:30

Remarkable things that they can

6:32

do specifically around. Writing. Code,

6:34

But they also have some limitations

6:37

because they're mostly about tax. And

6:39

there's a lot of. People I find.

6:42

On. Podcast on other things

6:44

where they're just reading this

6:46

expectation and alums an Ai

6:48

that I think aren't gonna

6:51

quickly outpace what's reasonable on

6:53

what's likely in the short

6:55

term. When. People say stuff

6:57

like maybe my computer when it's either

6:59

will just find a cure for cancer.

7:02

That's. Come out of the mouth

7:04

recently are pretty high level person

7:06

at one these foundation a model

7:08

companies and that's not gonna happen

7:10

anytime soon and so keep in

7:12

these things in context I think

7:14

is really really important if you

7:16

are playing roselle and understanding where

7:18

they're super power for all around

7:20

Language: A lot of the early

7:22

big wins have to do with.

7:24

Analysis and or writing have lots

7:26

and lots of tax. And

7:29

their remarkable, unbelievable death.

7:32

Bill. How would you think about an

7:34

investment in a foundational model company like

7:36

if you think about this way buds?

7:38

New. Entrants that seemed of caption lots

7:40

of I just in terms like they're valuations

7:43

that needs who recognized and tropic open a

7:45

i'm a strong cetera lama of it's a

7:47

smoke Some of the difference in see some

7:49

decent or model companies the market caps or

7:52

the guy way since I should say are

7:54

huge and some cases how would you approach

7:56

like of you saw marginal one tomorrow How

7:58

do you think about. It's

8:01

already. A. Vault to a point

8:03

it's very similar to wear who were

8:05

left in door-ended up where there's just

8:08

so much money moving around. That.

8:10

I really don't even think about it as a

8:12

startup market anymore. Or. We should

8:15

have been having this conversation for five years

8:17

ago. He wanted to be accurate

8:19

nine consensus In a way around these.

8:22

Part. Of it ties into the big

8:24

guys being interested in what they're doing

8:26

with their own balance seek to reinforce

8:29

this which I consider to be remarkably

8:31

dangerous. an unhealthy. The. Having an

8:33

eye Market Cap so like. The. Same

8:35

market cats represent discounted

8:37

future expectations. So. In

8:39

some ways you set yourself up.

8:41

There's amount of money that's being

8:44

handed to the experts that are

8:46

hired by these companies. and all

8:48

that three and four. So now

8:50

the expectation of large secondary payments.

8:52

This isn't pro baseball level money

8:54

at this point which are fair

8:56

to them on that the blanks.

8:58

but it's beyond what you would

9:00

consider to be a start up

9:02

world. One. Quick things. I.

9:04

Do. Think. That the

9:06

initial versions these models are

9:09

structurally slot around. providing.

9:12

Personal. Memory and allowing someone

9:14

to become dependent on one of

9:16

these things. Narrow approaches like rag

9:18

and things they don't really seem

9:20

to get there from my point

9:22

of view. but if someone did

9:25

this correctly, I. Think that can

9:27

really change the game. So if someone had

9:29

a foundational model where they figured out. How.

9:31

To scale. Of the ability

9:34

to return for each individual are a

9:36

small local model that people are come

9:38

out. Apple may have contacts for your

9:40

state of your phone. Any of that

9:42

stuff could create a wildly new direction

9:45

that we have today. Maybe.

9:47

A dumb an obvious question? The key just click

9:49

moron. Why the sorts of things that that would

9:51

unlock the get you so excited? Always.

9:53

Like to reference the movie her

9:55

this thing that walks around and

9:57

has all of your previous now.

10:00

The Edge knows every email you wrote,

10:02

knows every conversation I've ever had with

10:04

Patrick beforehand. So. I'm walking in

10:06

I could say remind me the last five

10:08

times I met with Patrick and to start

10:11

spinning stuff back at me. And

10:13

the alums today are really

10:15

more like a advanced Wikipedia

10:17

that's the can also code.

10:19

when did has sucked in.

10:21

The world's information, but it hasn't really

10:24

sucked in your information. And it doesn't

10:26

suck in your marginal information. And

10:28

it would be cost prohibitive today. But I

10:30

noticed all of the foundational guys see this

10:33

opportunity and I do think it will be

10:35

the game changer if someone can get it

10:37

right. Michael. We've talked

10:39

a lot in the past about the

10:41

way that new technology waves get installed

10:43

in bed and then ten a normalized

10:46

in an overall ecosystem. Everyone's in the

10:48

sort of everything everywhere all at once.

10:50

mowed right now with a i just

10:52

expecting it's gonna do everything and immediately

10:54

which I see a won't can you.

10:57

Lend. That historical perspective antenna how these things

10:59

tend to play out in the abstract in

11:01

a way that might apply to a I,

11:03

too, I. Like to thank you say

11:05

in the abstract ones. I don't know how much

11:07

about what's going on but when history would tell

11:09

us is at as New Technologies com in. Companies

11:12

typically have some sort of a

11:14

workflow and the new technology will

11:16

come in and help productivity and

11:18

efficiency for that company. But. They

11:20

don't completely reorient their workflows initially,

11:23

so the first generation is. it

11:25

amplifies but kind of in different

11:27

spots. and then as time goes

11:29

on, You. Rearrange your business around

11:32

that core technology that allows you to

11:34

really. Unlock the different

11:36

productivity potentials. Go. Back to electric

11:38

engines back in the day but the most

11:40

recent example would be the internet were first

11:42

wave was just sort of adding on to

11:44

something were to happen and then he had

11:46

a whole wave of copies that were internet

11:48

first and completely reoriented. Were. Probably early

11:50

in this phase we're compete or think in every

11:52

company's talking about this obviously. see this for example

11:55

on conference call. Mentions. And so

11:57

forth. Perjury to com. He's probably fully integrated. listen

11:59

to what they're doing. It's gonna take some period

12:01

of time to have that happen are built. You

12:04

agree with that if you see that in own

12:06

business as you work on. The I

12:08

do think if you. Listen. And at

12:10

the margin there are people that are

12:12

like oh yes things amazing it can

12:14

code and then people that have been

12:17

around at you talk to engineering layers

12:19

been around in a lot longer. The

12:21

debugging taking longer than it did before.

12:24

His. Writing code at our stance and

12:26

I gotta go fully understand the code.

12:29

I. Think people extrapolate and

12:31

a level. That has

12:33

put us now in this medal

12:35

land where of course there's amazing

12:38

things happening. Of course it's unbelievable

12:40

was possible but the expectations of

12:42

gun took place another one a

12:44

year frequently especially from the most

12:46

will com a I optimist sir

12:48

talking about universal basic income and

12:51

productivity gains forever. it's gonna be

12:53

so awesome. Will just sit around

12:55

and during my guys all day

12:57

long or something and. I

12:59

just think that So impossible, So wrong.

13:02

Free space on the stuff you and

13:04

I talked about over the years. Michael.

13:07

Most. Notably, the competition is ever

13:09

present. Just because you get again

13:11

doesn't mean. You. Get to hold

13:13

on to it forever. But. Why

13:16

do you think that existing big

13:18

companies have done such an arguably

13:20

awesome job of ceasing this thing

13:22

down this time around like it

13:24

seems like universally. All. The

13:27

next technology companies are. So.

13:29

All over this that the leadership is like doing

13:31

what it's supposed to in it makes me wonder

13:33

like what is a disruptive innovation even mean like

13:36

of these guys had been running these companies are

13:38

normal came with that have been disruptive or sustaining.

13:40

There's. A backdrop to that question.

13:43

That is probably a separate question

13:45

that Michael's been thinking about. It

13:47

is New, which is in Twenty

13:49

Twenty Three, The Magnificent Seven, or

13:52

whatever. We have the largest companies

13:54

on the American Stock Exchange, at

13:56

least outperforming. most of the smaller

13:58

companies from a good And that's unusual in and of

14:01

itself, whether AI is here or not with AI, we

14:05

talked about a little bit, but because everything's

14:07

now cloud based and API based,

14:10

very easy for people to plug this

14:12

stuff in. I think the companies that

14:14

owned the creative productivity apps very quickly

14:17

realized that this was going to be a required feature. So

14:21

Microsoft, all their products, Adobe, those kinds of things, but

14:23

they jumped

14:25

fast to their own, but they jumped fast.

14:27

And maybe it's because people like

14:29

you Patrick talk about innovation and

14:32

learning, you know, for so long that these

14:34

people have gotten their stuff together, but it's

14:37

very clear in this case that that happened.

14:40

What do you think Michael, about that interesting phenomenon? Bill

14:43

pointed out that maybe this is an excuse to have a big

14:45

long talk on increasing returns

14:47

to scale or something, but the dominant players, it's

14:49

not like AT&T from

14:51

when it was the huge percent of

14:53

market cap and it was something huge

14:55

percent of market cap and it was

14:57

slow and stodgy and was definitely nothing

15:00

like Microsoft is today. In

15:02

my venture career, when I first joined the

15:05

number one question someone would ask an

15:07

entrepreneur is what are you going to do when Microsoft enters

15:09

your business? And it went

15:11

from that to a full

15:13

on IBM equivalents where no one

15:16

was afraid of Microsoft. They're

15:18

kind of a really interesting example on

15:20

this question because they're now back in

15:23

full on threat mode. A

15:26

few ideas come to mind on this.

15:28

One is just to echo something Bill

15:30

mentioned a moment ago, looking at the Magnificent

15:32

Seven or whatever you want to call it, some sort of

15:34

leading group of companies, our

15:36

numbers show that the Magnificent Seven

15:38

specifically generated about 45% of

15:41

the economic profit for the US

15:44

stock market. So economic profit, just

15:46

to be clear what that is, it's return on

15:48

capital, less cost of capital spread. So you're earning

15:50

above your cost of capital times

15:52

the invested capital in your business. You're

15:54

earning less than your return on capital. So

15:58

the market caps, you know, I don't know what they got. 25

16:00

or 30 percent and that was

16:03

actually below their economic profit contribution. So

16:05

maybe they don't earn that economic

16:07

profit in the future but just to make a

16:09

point that this is not completely crazy. The

16:12

second thing we've seen is

16:14

that and I'm not sure what we've seen

16:16

is the returns on capital for smaller companies

16:18

used to be bigger or equivalent to larger

16:20

companies and starting around the year 2000 that

16:22

flipped. So

16:25

now larger companies are not only growing

16:27

at pretty decent clips but have very

16:29

high returns on capital. There's

16:31

a very interesting book by Jim Besson called

16:33

The New Goliath where he lays out some

16:35

of the theories as to why this is.

16:37

I'm sure Bill will talk later about things

16:39

like regulation and so forth contributing to this.

16:42

But basically the Besson thesis is that

16:44

these companies had enormous resources that allowed

16:47

them to invest substantially in proprietary software

16:50

which allowed them to enjoy the benefits of

16:52

scale but also do a lot with customization

16:54

and that those technologies did not diffuse throughout

16:57

the economy unlike in past generations technologies tended

16:59

to diffuse. So this has given

17:01

rise to these so-called superstar firms which is

17:03

super interesting. The third thing I'll

17:06

mention is these big guys are spending a lot of

17:08

money and Bill mentioned sort of like what people talked

17:10

about with Microsoft back in the day and I used

17:12

to use Microsoft as an example of my class of

17:14

a company that was spending a lot

17:16

of it on intangible assets and not that

17:18

much on tangibles. So their R&D was a

17:20

lot bigger than their CapEx back in the

17:22

day. Those relationships have all

17:24

changed. And a little fun fact,

17:26

if you just take the top five energy companies

17:29

in the world and the top five technology

17:31

companies, the technology companies are spending

17:34

2x the CapEx as the

17:36

energy companies. And if you told me

17:38

25 years ago or 30 years ago that

17:40

technology companies would be spending twice as much

17:42

on CapEx as core energy companies, I think

17:44

it would have questioned that potential. The

17:47

amount of money these guys are spending is staggering

17:49

and very difficult for new companies to come along

17:51

and keep up with. Bill, I'm

17:53

curious when you put your investor hat on again, one

17:56

Of the original posts that you wrote on Above the

17:58

Crowd I think back in 2000. Three

18:00

years. Was. In search of

18:02

the perfect business model. And it talked

18:04

a lot about increasing marginal utility to

18:06

customers. And so I want to talk

18:08

first about the virtuous version of this.

18:10

As a company scales, it actually is

18:12

better for customers in that layer. Will

18:15

talk about regulatory capture Mrs like the

18:17

other side of a similar idea. a

18:19

similar coins. But why did you write

18:21

that back then? And how does that

18:23

relate to these masses? Seventy Nine Ten

18:25

Technology Businesses today. I'll take

18:27

a short history detour just because.

18:30

We. Did it set this up and talk about how

18:32

we met? But I was. Remarkably.

18:35

Fortunate. To land

18:37

at she first Boston when I

18:39

did primarily says Michael was there

18:41

and so I got to know

18:44

Michael and we became. Dot.

18:46

Partners and would exchange books and

18:48

ideas. and one of the books

18:50

we read back then was complexity

18:52

about the rise of the Santa

18:54

Fans to where we spent time.

18:56

But it also outlined Brian Arthur's

18:58

original thesis on increasing returns. And

19:01

network effects and. Groveling.

19:03

No other. Kind. Of theory

19:05

affected my rent your career more

19:07

than that and trying to find

19:10

companies were this is true and

19:12

the perfect example as you were

19:14

obviously where David Sachs had this

19:16

incredible napkin picture which just showed

19:19

the loop but it's pretty simple

19:21

on it's answered your question which

19:23

is if you have more drivers

19:26

pick up times fall. In.

19:28

It pick up times fox the consumer value

19:30

proposition gets better and so more people want

19:32

to use it and if more people want

19:34

to use it. In. More places.

19:37

The. Availability spreads because driver start

19:39

up enough to meet the needs

19:41

and so you end up with

19:43

more coverage prefer pick up times

19:45

more money for the drivers themselves.

19:47

It's literally a win for all

19:49

sides in the system and those

19:51

are rare as a those are

19:53

rec. When. i push entrepreneurs to

19:55

think about this and it gets your

19:57

increasing a marginal utility but i just

19:59

say, as you penetrate

20:02

a supplier base, one side of

20:04

a marketplace, whatever is

20:06

the value proposition to the other side going

20:09

up. And ideally it would be going up

20:11

exponentially, which is super hard. It's arguable. There

20:13

are levels of increasing returns. Like you could

20:15

come up with some kind of scale or

20:18

index because some of them are more linear

20:20

and some of them can go exponential. But

20:22

I think they're rare. They're so rare. In

20:24

fact, that some people think they don't exist,

20:26

but I'm pretty certain they do. I

20:30

think a framework that really helps also flesh

20:32

all these concepts out is called Value-Based Strategy.

20:35

It's a famous framework by Brandon Berger and

20:37

Stewart. But the way to think about

20:39

it is almost like a linear stick. So at the

20:41

very top would be willingness to pay of the consumer

20:43

and then the price of the good or service and

20:46

then the cost to the company and then

20:48

willingness to sell. Your economic profit as a

20:51

company is difference between price and cost. But

20:53

again, the elements of willingness to pay and willingness

20:55

to supply are very important, willingness to sell very

20:58

important. And just to recast what Bill

21:00

said, because when he explained Uber to me when I

21:02

was first learning about it, this very much

21:04

is the way it came into me. So what

21:06

happens when network effects by

21:08

definition mean the value of the

21:10

good or service increases more people use that good

21:12

or service. So willingness to pay goes

21:14

up. So then you say to yourself, okay, if

21:17

willingness to pay is going up and I

21:19

don't raise the price of the good or service, that's

21:21

more consumer surplus. More consumer

21:23

surplus means happier customers and they stick

21:25

around and it's very powerful. On

21:28

the other hand, if I do need to raise prices because willingness

21:30

to pay has gone up, I have a little bit of headroom

21:32

to do that. In fact, I used to

21:34

think about pricing power as the key issue. I

21:37

no longer believe that's the way to think about it.

21:39

The way to think about it is, am I increasing

21:41

as a company, am I increasing willingness to pay every

21:44

single day? Again, either adding to

21:46

consumer surplus or giving myself future potential pricing

21:48

power if I need it. And

21:50

it also works on the other side, a little bit on the

21:52

willingness to sell on the cost as well. So

21:55

when you start to think about like Charlie Munger's

21:57

idea of a lot of the Palooza effect, you're

21:59

creating value on the demand side, which is

22:02

increasing the least to pay and because

22:04

you get old school economies of scale,

22:06

your costs per unit are coming down.

22:08

So more value for the customer, lower cost

22:10

per unit and you put those two things

22:12

together and that was built sort of exponential.

22:14

Huge value creation happens as a consequence of

22:17

that. I agree with Bill 100% of these

22:19

things are very rare. I think people tend to think

22:21

of them as much more prevalent than they actually are.

22:23

There was actually an interesting academic study where they looked

22:25

at companies seeking to become platform companies

22:28

and by their reckoning, it was less than it

22:30

was like something like one or six or one

22:32

and seven that were able to achieve that. But

22:35

when it happens, it can be very powerful from a

22:37

value creation point of view. People think

22:39

about this a lot related to consumer

22:41

companies, but I stumbled upon something recently

22:44

that thought was pretty cool, which is

22:46

CrowdStrike, which is a huge, wildly

22:49

successful computer security company, but

22:51

they posted a memo four

22:54

years ago titled the CrowdStrike

22:56

security cloud network effect. And

22:59

the way that it worked for them and

23:01

the way that the marginal customer ends up

23:03

with more utility is if

23:05

the threats are shared

23:08

across a network, then if you belong

23:10

to the biggest network, then you get

23:13

the shared learning of everyone in that

23:15

network, which lowers your threat exposure.

23:17

And you wouldn't want to, this is

23:19

always how I think about it. Look at

23:21

the value function to the customer and does

23:23

it go off as the customer count goes

23:25

up? And if you were customer

23:28

in plus 1000 instead of

23:30

in, would you have a better value proposition?

23:32

And in that case, you do. You

23:34

would never want to be in the second or

23:37

third place security network. You'd

23:39

want to be in the largest security

23:41

network. So it can apply in other

23:43

places, but I do think it's rare. What

23:46

would it take for you, Bill, to make

23:48

an investment where you felt like you really

23:50

couldn't see a path to one of these

23:52

stories of increasing returns to scale across

23:55

your career or today? It's rare, not every company can

23:57

have it. There's no big companies that don't have it.

24:00

It happens. There are other dimensions

24:02

of success in venture than just

24:05

increasing returns or network effects. And

24:07

so it could be an early

24:10

go to market advantage that a company has.

24:12

It could be an incredible

24:14

founder where you have

24:16

confidence that those two things might happen

24:18

over time. But I look

24:20

for them in most cases. I'm

24:22

probably overly optimistic about being able

24:24

to create them. Why? I

24:27

think it's such a unfair competitive advantage.

24:29

I think it's just such a great

24:31

way to win. And I

24:34

find when I provoke entrepreneurs, they can

24:36

think in ways they didn't in the

24:38

past, just with some of the dialogue

24:40

we've talked about, but not everyone can

24:42

get there. It's hard. There's so

24:44

many dimensions to corporate success. You

24:47

can't do everything, but I look for it all

24:49

the time, all the time. Michael,

24:51

what role do intangibles play in

24:54

all of this increasing returns to

24:56

scale concepts and literature

24:58

that you've reviewed? I

25:00

think they're really big. I mean, just to

25:02

take a step back, I think that the

25:04

investing world has changed radically in the last

25:06

40 or 50 years, where

25:08

in the 1970s, tangible investments were

25:11

bigger than intangible investments. And today

25:13

that relationship is almost completely flipped

25:15

where intangibles are substantially larger. But

25:18

I think the key question is, can

25:21

we make some links between intangible investments

25:23

or intangible assets and strategy, the stuff

25:25

that we're talking about, there

25:27

are sort of pros and cons on the

25:29

strategy side. What's great about an intangible asset

25:31

is it scales like crazy. You write

25:34

software code, you write, you record

25:36

a great song. The cost

25:38

of incremental distribution asymptotes towards

25:40

zero. So if it's successful, you

25:42

can make enormous amounts of money, which is great.

25:45

The problem is those same products are

25:47

very much at risk for obsolescence. If

25:50

you are no longer the most popular song or your

25:52

code is not the newest code, it's

25:54

worth very little, arguably zero.

25:57

Intangibles are easy to steal. Though

26:00

if you come up with a great. Product.

26:03

There are mechanisms to patents and so for the

26:05

try to protected by for the most part

26:07

people can replicate what you're doing and so that

26:09

makes it very difficult for you to sustain

26:11

and access return. If. Other people can

26:13

mimic what you're going. And then

26:15

the last thing that can be very

26:18

bullish I think is something we might

26:20

talk more about which is untenable. Investments

26:22

assets are subject to. Pretty.

26:24

Quick manipulation and recon venetian to

26:26

come up with new solutions. So.

26:29

Really, if you boil innovation down to

26:31

it's core, it's almost always the recommendation

26:33

of existing building blocks and allows the

26:35

link today or intangible building. Com.

26:38

Digital building blocks of we can manipulate.

26:41

And a faster more fact away them he could

26:43

before so they're sort of the attend will investment

26:45

first documenting that it's much bigger than it used

26:47

to be in and second, thinking about what are

26:49

the specific strategic implications. There. Are positives

26:51

in the com and then there are negatives in the com

26:54

And then where do we both know? I

26:56

can maybe talk about. The. Research you've

26:58

done on this notion of recover nation of

27:00

Ideas which is one of a subset. Of

27:03

different kinds of increasing returns to scale.

27:05

I'll just list them off this because

27:07

it my provokes discussion amongst the three

27:09

of Us vs. economies of scale. the

27:11

second as international trade a syringe. learning

27:13

by doing. Before. This network effect

27:15

stricken talked about their and and this

27:17

idea you just mentioned recover Nation of

27:19

Ideas he be say a bit more.

27:22

I love these five categories of increasing

27:24

returns sometimes within a company, sometimes across

27:26

an ecosystem. Say. Will Mark like about

27:28

re combination of ideas and I'm curious how Bill

27:30

As see map Latin practices. Just

27:32

to state the obvious, this is an idea been

27:35

around for long time. Paul Romer won the Nobel

27:37

Prize for his work in this area. When.

27:39

You think about economics. The classic way of thinking

27:41

about this is some sort of production function. So

27:43

you have input of some sort, usually labor and

27:45

capital, and then you're some sort of output. And.

27:48

What economists observe for very, very long

27:50

time was it output was greater than

27:52

the input would suggest, And so. rubber

27:55

sol wrote about as many years goes

27:57

called solos residual people knew that there's

27:59

this thing called technology in quotation marks

28:01

that was contributing to being able to

28:03

manipulate the inputs in some way that

28:05

allowed for greater output. So productivity effectively.

28:08

The early framework, there was an acknowledgement that was

28:10

the case, but those were almost always exogenous to

28:12

the model. The model was still about labor and

28:14

capital. Okay. And so what

28:16

Romer came along and figured out was we can

28:18

make this endogenous, we can build it into the

28:20

framework. This idea of recombination of

28:23

ideas is over time, we can

28:25

figure out how to manipulate the inputs in

28:28

such a way that allows us to have greater outputs.

28:30

So that's the core idea of endogenous growth

28:33

theory. So again, a

28:35

long intellectual tradition, I learned about this actually

28:37

from a very different point of view. I

28:40

learned about it originally from the Santa Fe

28:42

Institute and John Holland. John Holland was a

28:44

professor at University of Michigan. He's

28:46

purported to be the first person in

28:49

the United States to get a PhD in computer science, interestingly,

28:51

and was a professor of computer

28:53

science, psychology, and engineering at Michigan.

28:55

So this guy was extraordinary and

28:58

clearly one of the intellectual founders of the

29:00

Santa Fe Institute. And he developed an idea

29:02

called genetic algorithms. And the idea is

29:04

pretty simply, you have a problem you're trying to solve and you have

29:07

some sort of fitness function to figure out how close you are. You

29:09

throw out a bunch of computer programs, for

29:12

instance, code, and you just test

29:14

to see how fit they are in solving

29:16

the problem. Then what you do is you

29:18

breed, literally breed the top programs, let them

29:20

have a series of progeny, right, that of

29:22

the same original length, and see

29:24

what their functions are. And then you breed them again

29:26

and breed them again. So it's just like breeding up

29:28

an animal or something like that. You breed it toward

29:31

improving your fitness function and solving your problem. I

29:33

know Bill probably talked about this, but Matt

29:35

Ridley's got this much more memorable phrase like

29:38

ideas having sex. This idea of recombining ideas

29:40

in such a way to get to some sort of objective

29:43

goal, solve a specific problem.

29:46

That's really, I think, at the core of a lot of

29:48

what this stuff is about. Now Going

29:50

back to Romer's, I mean, what Romer emphasizes, these

29:53

will be slightly technical terms with this idea of

29:55

rival versus non-rival good. So A rival good is

29:57

a good that one person can use at a

29:59

time. So. The pen in

30:01

your hand or whatever you're on your back

30:03

and a non rival good is a good

30:05

that many people can you simultaneously. And

30:07

then the second question is can we keep

30:09

other people from using him and asked intersex

30:12

A rival goods are easy to exclude from

30:14

other people from using. I'm typically property rights

30:16

but not rival goods are very difficult to

30:18

have exclude ability. If it's out there are

30:20

recipe or instruction. At heart excluded

30:22

from a rumor came along as sad

30:24

as that some non rival goods can

30:27

be partially excludable. Which. Means you

30:29

can have the benefits of an intangible assets, but

30:31

you can read some of the economic benefits from

30:33

that the that sort of the egg inside so.

30:36

There. Are things that impede the three combination of

30:38

ideas? But you want to be optimistic about the

30:40

world? This is really a foundation

30:42

to do the right because as saying

30:44

like whatever problems face us, we have

30:46

more tools and toolbox, more building blocks

30:49

to solve it. And because we have

30:51

digital technologies allows us to do things

30:53

search space much faster than we could

30:55

before. And has we can come up with

30:57

solutions fast we could be. If you want

30:59

to be an optimist, that's certainly one where you could

31:01

argue that. What? Is this

31:03

looks like in the Wild Bill when you're engaged

31:05

with people that are the recombine nurse of the

31:08

idea is trying to build something novel. A new.

31:11

Id talk about this with them. They even

31:13

think about it as such. Are they just

31:15

saying look, Mother's Mobile and their Cps? someone

31:17

to build hoover? How's your experience of this

31:19

narrow world? Some. Of it,

31:21

Chris might fall under that phrase best

31:23

practice. And so there are

31:25

discussions. Are there more discussions and ever

31:27

because of podcast and whatnot? And somebody

31:30

is talking about their Viral Roesler and

31:32

how that works and they come up

31:34

with a framework and of model and

31:36

they share that they put it in

31:38

a powerpoint and and other people are

31:41

using that kind of thing and a

31:43

more. Concrete form. This is

31:45

open source writ large, and

31:47

I think open source is

31:49

one of the most compelling.

31:52

Innovations or human prosperity

31:54

that we've ever had.

31:56

Because and Michael's framework.

31:58

There's nothing. They prohibit

32:00

someone else from using it once you

32:03

used it, and it has zero marginal

32:05

costs. And. So you can do

32:07

amazing things. Maybe you could argue why

32:09

the reasons why the big companies are

32:12

succeeding is because. Open. Source:

32:14

There's no patent protection for the

32:16

smaller. Company. And so they

32:18

can all take advantage of this stuff more

32:20

quickly. And I do believe. The

32:22

most large companies have shifted over

32:24

the past ten years towards an

32:26

open source first. Technology.

32:29

Staff were they used to be an I

32:31

B M shopper, A-shop or wherever and I

32:33

think that's great for everyone involved. My

32:35

an open source is kind of.

32:37

There's this phrase used in economics

32:40

was a micro perfect competition or

32:42

pure competition? Blaze. Through a

32:44

pure competition as to get rid of

32:46

pans and whatnot is just wide open,

32:49

free for all would see be great

32:51

for consumers. Yeah so anywhere adding open

32:53

source is probably the most. The Moscow

32:55

example of his ideas they can just

32:58

be borrowed and really starts with the

33:00

farmer that learns how to plow field

33:02

and tell someone were to get seeds

33:04

and that example works pretty easily and

33:07

people's brain. but when the take it

33:09

forward to where we are today and

33:11

those things are still going on. It's

33:14

really cool and I agree with my thoughts.

33:16

A reason to be optimistic. I often wonder.

33:19

Could. We use open source in

33:21

the nuclear manufactured. Are there

33:23

some areas where we're stuck from an

33:25

innovation stand point where he might be

33:27

better off. Ah, been autonomous vehicles

33:30

just a little bit history and this discuss

33:32

back to work I learned this from gym

33:34

Best since book on open source. I did

33:37

not know this but about a century ago

33:39

the automobile manufacturers together breed an open source

33:41

consortium to work on various technologies and so

33:43

the when the sensory she tells in book

33:46

is in Nineteen Forty General Motors team of

33:48

the automatic transmission how they did as and

33:50

pads and stuff like that. But for the

33:53

most part it was very easy for others

33:55

to send to reverse engineer what they're doing

33:57

and to roll out the automatic transmission. Is

33:59

within. A decade every manufacturer

34:01

had. Offered. An automatic

34:04

transmission. And this is ten years

34:06

with a war in the middle rights of

34:08

those extraordinary so that technologies diffused and I

34:10

think the argument that person is made it.

34:12

A lot of big companies today are investing

34:14

sued sums of money on proprietors have one

34:17

as a Huge sums of money. Two hundred

34:19

billion. Two hundred Fifty billion dollars per year.

34:21

On. Proprietary software and they're

34:23

not sharing with anybody else. Which

34:26

is really interesting so the sensors

34:28

to capture economic rent. Sometimes open

34:31

source is not healthy for yourself.

34:33

To. Very interesting tension and I'm would bill

34:35

I'm adding more. This be better than

34:38

the last of it for overall innovation.

34:40

but it's interesting this tension between companies.

34:42

Why do it and not winded. There's.

34:45

A really instinct trend. It started proud

34:47

of Android, but. Where. Companies

34:49

that find themselves behind the eight

34:51

ball. From offensive standpoint,

34:54

launch Open Source is a

34:56

defensive strategy. google. Did

34:58

it with Android. Against the I

35:00

phone and it's hard to go back

35:02

to that moment time when Apple launched

35:04

only on a T T, but all

35:06

the handset manufacturers all. The. Carriers were

35:09

very, very concerned about Apple and

35:11

they were very open to the

35:13

side. Yes, have an open source

35:15

solution to combat that. They.

35:17

Did it again. In the cloud

35:19

space where Amazon was run away

35:22

with things with eight of us

35:24

and Google created this technology called

35:26

Cooper Net is it allowed you

35:28

to have portability between clouds Open

35:30

source. He got the Linux foundation

35:32

of all got I B, M,

35:34

and others to join along and

35:36

says you're playing defense rather than

35:38

all sense, but you're fighting. Pseudo

35:41

monopolies if you will. So this is

35:43

super interesting. As a new math initiative

35:46

that matter and Amazon I think one

35:48

other working on. To combat Google

35:50

which is in obe source data play. They.

35:53

On Android that I guess fastening mechanics were built a

35:55

said so I mean I was. Are you have his

35:57

idea of trying to increase willingness to pay more way

35:59

to. That is it. You have a complimentary

36:01

good or service, so compliment. The idea in economics

36:04

is it's that costs. Your compliment goes down as

36:06

I have. your good or service goes up. A

36:08

So Hot Dogs and the store gives away

36:11

the bugs for free Friday the guy the

36:13

hot dogs go up. So in a

36:15

sense always think about what google dead wood

36:17

Android as thinking like what was their good

36:19

or service they're trying to sell moser compliment

36:21

and rice of for them. Essentially they're like

36:23

we're in a giveaway the compliment swimming or

36:25

com and basically free which allows the willingness

36:27

to pay to go off for what we

36:29

care about which is advertising. Suicide.

36:32

On Mobile. In. The sense there is

36:34

a very interesting strategy in the context have

36:36

a willingness to pay increase of i have

36:38

your good or service get your compliment drive

36:40

it is here on this case they just

36:42

bought something gave it away everybody thought circle

36:44

of this works out. Song. Consumer

36:47

surplus and value creation. It seems clear

36:49

that like if we shared as a

36:51

species more probably we would get more

36:53

and move faster. Companies and

36:56

individuals are more selfish than that. They're

36:58

trying to create an capture value. And

37:01

has lots of ways of doing that. Some

37:03

do it very virtuous sleep with the are

37:05

increasing marginal returns, the Cosco model sharing back

37:07

scale economy things like best others do it

37:09

more nefarious li and believe in in touch.

37:11

Lot about regulatory capture recently which I love

37:13

to explore as a group here but I'm

37:15

also just curious for how you feel your

37:17

way to the right lines. You never and

37:19

will say a drug patton makes sense because

37:22

without that incentive he or and he wouldn't

37:24

happen and there needs to be some period

37:26

The you can earn gray returns if you're

37:28

the one that discovers a novel new drug

37:30

or something. Like that, Whereas, like Epic Health

37:32

or something like Snooze fine, literally everyone will

37:34

bitch about it except for the people that

37:36

probably own Epic Health. Which. I think

37:38

it's been pretty good to Bans Are you

37:40

for this soup of incentives and what's best

37:43

for companies and drives are Indian innovation vs

37:45

what's good for humanity. Like get the big

37:47

question butts and a thought of ads I

37:49

feel comfortable asking. I'd. Probably push

37:52

back on the drug comment. I

37:54

don't know that seventeen years makes

37:56

any sense whatsoever and why that

37:58

industry get protected down to a

38:01

very minute detail of innovation. whereas

38:03

it's very hard data software patton

38:05

like a we wrote software patterns

38:07

way we write drug patents. The.

38:10

Software industry would slowed or

38:12

Hall and. The. Other thing is

38:14

I'm it just takes something like linux which has

38:16

been around for twenty years now, but. The.

38:18

Number of companies that invested billions

38:20

of dollars in our Indian Lennox

38:23

this saddle. And so just the

38:25

argument that no one alves unless

38:27

you can put a hard at

38:29

night has been proven false. Companies

38:31

do and best. For for the

38:33

defense of reasons that I talked about so

38:35

I'm not in that market, but I'd like

38:38

to see some kind of reform actually. And

38:40

the drug market in a seventeen. too long

38:42

and they're notorious. Based. On what

38:44

I've read, forks making small changes

38:46

and then reapplying the patents. So

38:49

like intentionally drawing out these windows.

38:51

Say. Everything you've learned about regulatory capture

38:54

in the crusade you been on to

38:56

try to get people more aware that

38:58

each that that fitness is this out

39:00

of widely watched one on. Yeah.

39:04

I mean, I mentioned this in a

39:06

speech by George Stigler Won a Nobel

39:08

Prize. A direct Chicago Me was the

39:10

one that. Really? Should. Be

39:12

mentioned this the one that feared the south

39:14

but. My. Were think this prom

39:16

gets worse as the country ages if

39:19

you look at it from a great

39:21

macro standpoint. The more people

39:23

hang around Washington for a very long

39:25

period of time, they just learn how

39:28

to influence it. And that's true both

39:30

sides, but the lobbyists sides and that

39:32

senator or congressman side and and in

39:35

some people flip back and forth to

39:37

is particularly scary situation. But you look

39:39

at major pieces of legislation like Dodd

39:42

Frank and others and you see competition

39:44

goes down. nada after they half and

39:46

then the phrase I use his regulation

39:48

is the and friend of the incumbent

39:51

but there's just. Way.

39:53

Too much proximity between the industries

39:55

are being regulated and the people

39:57

there regulating. I'm and there's no.

40:00

An authentic balance to prevent that

40:02

from happening is almost nothing is

40:04

someone told me after my speech

40:06

as should have included a slides

40:08

that showed Boeing said quarter move

40:10

over time is it was in

40:12

Seattle. And. Then it was in Chicago

40:15

for a while. Now it's in Washington Dc.

40:17

There's a lot of talk about buying

40:20

these days and a lack of competition

40:22

and coziness with regulators, and it's a

40:24

really big problem. In. The.

40:27

Industry's it have been around the longest. I

40:29

think it's a massive problem and healthcare

40:31

this a massive from the other problems,

40:33

but there's a massive problem there. Are

40:36

saying it's a pretty big problem

40:38

in finance thing it's prom and

40:40

told com the industry determine regulated

40:42

the longest are captured their tracks.

40:45

Patriotic. Tack on that because Stigler.

40:47

His moments won the Nobel prize for this. The.

40:50

Weird thing about this, there is good regulation.

40:52

And he called the Public Interest Regulation. I

40:54

see you're really trying to make sure that

40:56

things are good for the broad public. And.

40:59

Then there's regulatory capture. I sort of

41:01

the bad regulation. People. Throw

41:03

these on one big bucket. but they're

41:05

actually two very distinct things and I

41:07

very sympathetic to Bills Point that we

41:09

sort of gone away from or keep

41:11

taken or I off the ball. Public

41:13

Interest Regulation was adding muslims who agrees

41:15

a good thing and gone and is

41:17

regulatory capture environments and man would it

41:19

be great to not have money. Not

41:21

in Washington Dc. The mix between companies

41:23

and politics and money seems to really

41:25

distorted a lot of outcomes and so.

41:28

On and hi reverse that because obviously it's a

41:30

whole indication of powered so forth but that would

41:32

seem to be are suits you step and trying

41:34

to get this cleaned up. As old as you.

41:37

It's likely a massive advantage

41:39

for China, where a more

41:41

autocratic government can just decide.

41:44

Okay we're gonna start doing things and new

41:46

way. And. Where we have.

41:49

Just painted on. Layer and layer

41:51

and layer of regulation. And

41:53

we chat. Reverse. Those

41:56

are turn nose off as we start

41:58

to do something. There's been some. And

42:00

I don't think anyone thinks that's because

42:02

the people of Texas care more about

42:05

renewables. People would argue to their

42:07

blue in the face that the California populace is

42:09

way more liberal, way smarter, cares more for the

42:12

planet. And I think we all

42:14

know what it is. It's just bureaucratic

42:16

bullshit red tape that exists in California.

42:19

It's just a way more liberal, way smarter, way smarter.

42:22

And I think we all know what

42:24

it is. It's just bureaucratic bullshit

42:27

red tape that exists in California. They can't get out

42:29

of their own way. But

42:32

you've got some great story about, was it some bridge in Pennsylvania that

42:34

was rebuilt? There

42:36

was a bridge across from Harvard, Harvard University, you know, over

42:38

the River Charles and it took them, it

42:41

was supposed to be like a year long project

42:43

and it cost X and it took them like

42:45

15 years and like five X because of all

42:47

the regulatory stuff. I think that was the Boston

42:49

tunnel project. But

42:53

interestingly, more recently, the I-95 bridge went

42:55

down and they got it

42:58

back up in 12 days. You

43:00

know, this is to me the exact same

43:02

as San Francisco when G visits and all

43:04

of a sudden they clean up this town

43:07

that's been dirty for 25 years. It

43:09

gets cleaned up in two days. And the

43:12

governor, I think in the bridge case,

43:14

people are saying maybe a presidential candidate

43:17

now, when we start celebrating people

43:19

moving bureaucracy out of the way,

43:22

in some ways we're admitting that we've

43:24

painted ourselves into a corner. And rather

43:26

than view that as the exception, how

43:29

do you make that the new reality?

43:31

This is where I think China has

43:33

a massive advantage. They could just clear

43:35

the decks for good for every project

43:37

going forward. Whereas we're now

43:40

making exceptions, maybe with the TSMC

43:43

plant in Arizona. They're begging for

43:45

exceptions to regulation and we grant

43:47

it as part of the winning

43:49

process of getting the bid. We've

43:52

come so far. We're so far over

43:55

the line that we celebrate backing up

43:57

as an exception, but it

43:59

makes it really. hard to think about how would you back

44:01

up permanently. Sometimes

44:03

when companies do layoffs, they do zero based

44:06

budgeting, which is a great term.

44:08

But where you say, just imagine we

44:10

are starting fresh, how would we

44:12

ever create zero based regulation? Start

44:15

over, because we've layered it

44:17

on so much. It's so problematic.

44:20

What did you see happen in the wake

44:23

of the Twitter layoff

44:25

decimation bill amongst the community

44:28

of founders that saw him lay off whatever

44:30

crazy percentage and Twitter didn't break? What impact

44:32

did that have? The story is

44:34

not over yet, because I think we have

44:36

to wait until does it

44:38

reemerge as a successful company. It

44:41

certainly didn't break, which is an interesting

44:43

data point in and of itself stayed

44:46

up. And I think there

44:48

are numerous entrepreneurs and

44:50

venture capitalists who believe

44:52

that that is a proof point that

44:54

many of these systems are over invested

44:57

and there is a level of efficiency

44:59

that you can reach if you're willing

45:01

to put your mind to it. You

45:03

could look at the layoffs that Zuck

45:05

did over the past two or three

45:07

years and apply the same lens

45:09

because they're thriving in the absence

45:11

of that. So yeah,

45:14

now the perspectives on

45:16

Twitter and Elon and all this have

45:18

so much built into them that

45:21

many people, I think, have a

45:23

hard time looking at that example

45:25

as a standalone learning point.

45:27

The two of you are uniquely qualified for

45:30

this next question. Michael, you've studied it empirically.

45:32

Bill, you've been one of the key participants

45:34

in the ecosystem. We know the benefits of

45:36

venture capital that it's been behind the world's

45:39

biggest companies. In many cases, it's an incredible

45:41

fuel for innovation. If you

45:43

had to take the other side of it and

45:45

talk about today's venture capital ecosystem and identify things

45:47

that you don't like as much or that you're

45:49

worried about, what would those things be from the

45:51

inside and from the outside? The

45:54

first thing is just taking a step back and just

45:56

talking about public equities versus

45:58

private equity. private equity having

46:01

two flavors venture and buyout so we'll just

46:03

focus on venture. First thing

46:05

to say is I mean I'm gonna get these

46:07

numbers wrong but roughly speaking the market cap of

46:09

public equity is probably at year-end 50 trillion

46:13

ish. The assets under management

46:15

for a US venture a little over

46:17

a trillion maybe trillion and a half something like

46:19

that and when you

46:22

zoom in on venture and you talk

46:24

about what bill and benchmark did

46:26

over the years the capacity at

46:28

early stage just doesn't seem that big

46:30

to me. I don't know Bill

46:32

you probably know these numbers but your last few

46:34

funds were probably 450 or 500 million dollars

46:38

with an M million versus

46:41

these other funds companies were going on

46:43

raising multiple billions of dollars. So

46:45

I think what happened was in a

46:48

low-rate environment a lot of investors understandably

46:50

had to pursue returns and so they

46:52

moved out on the risk spectrum and

46:54

they said where do we go get

46:56

returns and that's gonna be private. So

46:58

in buyouts you get higher returns because you're

47:00

levering businesses and venture getting because you're buying

47:03

younger companies with higher failure rates this becomes

47:05

sort of this automatic to get excess returns

47:07

or higher returns I need to go out

47:09

there. I think there's been

47:11

much less sensitivity to the actual capacity

47:13

and the actual experiences people get into

47:15

these areas. The other interesting

47:18

thing about venture of course which has been

47:20

extremely well documented is it's one of the

47:22

few asset classes with high persistence which is

47:24

to say the past winners

47:26

tend to be future winners and the past losers

47:28

tend to be well often the losers can't keep

47:30

going but the winners continue to be winners you

47:33

have to get access to these guys and

47:35

that's also extremely difficult to do. Just to

47:37

get that back who knows what normal is

47:39

but certainly US 10 years at four and

47:41

a half four and three quarters we're getting

47:43

back to more in quotes more normal return

47:46

environments in terms of equities and

47:48

other parts of the credit world

47:50

and so perhaps that just turns

47:53

down people's burning desire

47:55

to get into less liquid and perhaps

47:57

riskier areas so those would be the

47:59

ones I would say and then Bill's talked a lot

48:01

about this but venture is fascinating venture

48:04

in particular is fascinating due to the cyclicality

48:06

of it And so a lot

48:08

of it depends on when you get in and

48:10

when you get out and so being sort of

48:12

attuned to that is Age tricky, but also obviously

48:14

seems super important Patrick i'll

48:16

start with i've always felt It's funny because you

48:18

read all these books and you study all these

48:20

industries when I go out and make investments and

48:22

you don't Use them to reflect on your own

48:25

And when I did apply my

48:27

supporters by forces to the venture

48:29

industry, I'd say it sucks It's

48:32

high competition But the big problem and

48:34

this is structural is there's low barriers

48:37

to entry and high barriers to exit

48:39

And so it's very easy to raise

48:41

a fund once you do these

48:43

days you're on the field for 15 years I

48:46

think you think it's gone from 10 to 15 And

48:49

so that money stays in the system you go

48:51

into a period Like we had

48:53

three years ago with zirp and the amount

48:55

of money that's raised is so gargantuan And

48:57

then it has to work itself through the

49:00

system Decimating returns along the

49:02

way just from a supply demand standpoint.

49:04

I don't know how to fix that

49:06

You'd have to rewrite the

49:09

standard gplp agreement. I think

49:11

i'll spend more time thinking about that

49:13

later But it is structurally flawed. I

49:16

think from a cyclicality standpoint The other

49:18

thing that's happened that ties into all

49:20

the stuff we've been talking about about

49:22

the big companies doing better these days

49:24

But the number of public companies has

49:27

shrunk dramatically and michael's written about this

49:29

but we've gone I think

49:31

almost half. Is that right? Michael? Yeah

49:34

down 46 percent You have

49:36

to ask why that is I

49:38

personally don't think it's healthy because a

49:40

minute that happens and everyone realizes that

49:42

there's Less companies going

49:45

public and companies staying private longer than

49:47

the sec I think

49:49

in a well-intentioned way goes. Oh my god,

49:51

the average investor is missing out on this

49:53

asset class We have to fix this but

49:56

what they want to do to fix it is then some

49:58

kind of institutionalized And

50:00

then you start doing things like you start

50:02

trying to create an alternative public

50:05

market. You start putting rules in place in

50:07

the private market that in essence,

50:09

just recreate the public markets. And this may

50:11

tie into what we've talked about with

50:13

regulatory capture and bureaucracy.

50:16

And so, you know, I think, you know, I think you're

50:18

going to have to be able to, you know, you're going

50:20

to have to be able to do that. And

50:22

I think that's a really good question. I think, you

50:24

know, I think, you know, I think, you know, I

50:26

think, you know, the law of

50:28

capitalism is very emulator. where

50:35

I think Wall Street is becoming a big company.

50:39

The big banks have no interest in

50:42

a small IPO. Years ago. There

50:44

were these banks called the four horsemen, which were

50:46

banks that just specialized in small IPOs in Silicon

50:48

Valley, leverage

50:51

them to the hill, and you just had

50:53

more companies getting public sooner. But

50:56

I would rather the SCC try and understand why that's not a

50:58

big deal or saying you got to have a billion in revenue.

51:00

If all that's true, this game's

51:02

a very different game than it used to

51:04

be. And it has less of the American

51:07

spirit. Anyone can do it. Anyone can start

51:09

a company that can go public. If you

51:11

have to get to a billion in revenue,

51:13

it's just a totally different

51:15

game. Hey Patrick, can I just

51:17

take a moment to say why I love Bill so much?

51:19

It is a little moment of appreciation here. So

51:23

first of all, obviously he's extraordinarily

51:25

smart and curious. And as a lifelong

51:27

learner, so those are all incredibly great

51:30

qualities. Obviously I knew him when

51:32

he came out of school, business school and was

51:34

a sell side analyst and was a great sell

51:36

side. It was not a good one, but a

51:38

great one in part because he embraced and I

51:40

think utilized really effectively some of the core tools

51:42

to think about the value of businesses. So

51:45

things like returns on a vested capital and

51:47

orders five forces to sort of be rigorous

51:49

and think about things strategically, understanding

51:51

the basic unit of analysis of how companies

51:53

make money. And so there are

51:55

a few analysts that do that, not

51:58

that many in public markets, but when you get into

52:00

venture, it seems to be a

52:02

lot looser around the edges in terms of how people

52:04

think about business. And one thing I've always loved about

52:06

Bill is you can always talk to him and they

52:08

can always bring things back to some of these core

52:11

principles and reminds people

52:13

and reminds his entrepreneurs, reminds his

52:15

investors that these really core principles are

52:17

really important. When talking about universality of

52:19

investing, what are we here to do?

52:21

Buy something for less than what it's worth. I just really

52:24

appreciate the fact that he's consistently

52:26

and thoughtfully and obviously very

52:28

successfully applied a lot of these

52:30

ideas over multiple decades, multiple cycles

52:32

to the benefit. And he shared a lot of

52:35

his thinking along the way with the rest of

52:37

us. So just a little moment of appreciation. I

52:40

don't know if Bill remembers this, but the first

52:42

time I ever had lunch with him and Sam

52:44

Hinkie in the Midge Park offices many years ago,

52:46

I had all these questions kind of like the

52:48

ones I'm asking today. I didn't get to ask

52:50

one. We spent the whole time talking about how

52:52

one company that he was working with was allocating

52:55

its capital, not just theoretical but applied. I could

52:57

second the notion. The idea of capital allocation is,

53:00

I guess it's the whole ballgame, right? Like it's what

53:02

we're talking about. That's the topic of our conversation. And

53:04

we've had this cool period where for, I

53:06

don't know, 10 years, we had zero interest rates

53:09

that should affect capital allocation, how you

53:11

raise capital, cost of capital, all of

53:13

these things. And there's like a should

53:16

versus did gap between what

53:18

companies maybe should have done theoretically

53:20

under those circumstances. Bill, you

53:22

worked with lots of them. Michael, you studied lots of

53:24

them and what they did do. And I'm

53:26

just curious, it seems like a real world experiment that

53:28

was run for a bad reason, the

53:30

global financial crisis at its start, but probably one

53:33

we can learn a lot from. So what did

53:35

we learn in that period of like should versus

53:37

did and capital allocation into

53:39

the businesses? I'm happy to

53:41

take a first look at this because we looked at

53:43

this for public markets and maybe Bill can talk about

53:45

from his vantage point. We talked about this

53:48

period of sort of easy money from 2009, Patrick, as you pointed

53:50

out, right after the

53:52

financial crisis through 2021. And of

53:54

course, a little amplified in 2020 with COVID

53:57

and central banks around the world coordinating their

53:59

behaviors. So if you said, well, interest rates are going

54:01

to be a lot lower, and they were, by the way, cost

54:04

of capital was markedly lower, you'd probably

54:06

expect three things to happen. One

54:08

would, companies would invest more because your cost,

54:11

capital, your hurdle rate just went down. If

54:13

you have a ranking of projects, more things get funded.

54:16

Second, you'd probably expect companies to hold

54:18

less cash because cash is earning lower

54:20

returns, not a much benefit to that.

54:23

And third, you might expect them to take on more

54:25

debt because interest expense are lower, you could keep the

54:27

same coverage ratios and have more debt and so forth.

54:30

And so we examined what companies actually

54:32

did in that 13-year period versus the prior

54:34

13-year period, which by the way, included the

54:36

dot-com boom and bust and so forth. And

54:39

what we found was almost the exact opposite.

54:42

Investments were actually down, the one

54:44

exception being intangibles, but overall investments

54:46

down. Cash balances actually

54:49

up for companies, again, led by many

54:51

of the large companies. And

54:53

then finally, leverage levels actually on

54:55

average went down, didn't go up, which is

54:57

interesting. So that's sort of the interesting questions

54:59

like why did that happen? The

55:02

other thing is talking about capital allocation, there's

55:04

just a wonderful research by John Graham at

55:06

Duke University. He gave the

55:08

2022 presidential address for the

55:10

American Finance Association, which was written up in

55:12

a paper that came out in the summer of

55:15

2022, surveying CFOs over 33 decades to

55:18

find out what they actually do. And one

55:20

of the big, fascinating takeaways was companies

55:22

actually don't even use the cost of capital. They know what

55:24

it is, they know what their cost of capital is, but

55:26

they use a hurdle rate that's roughly twice as high as

55:28

their cost of capital and it doesn't really change. And

55:31

it's roughly 15%. And

55:33

so it doesn't matter if rates go up or down

55:35

every day, they don't really care. They either use 15%

55:37

discount rate or hurdle rate to accept projects, which is

55:40

interesting. And then they're very, very sticky with things like

55:42

their capital structure decisions and so forth. The

55:45

last thing I mentioned is the one thing that actually did take

55:47

up in the dessert period

55:49

was buybacks. And it's very

55:51

interesting because often you hear people say, oh,

55:53

buybacks, companies would do them. Like

55:56

buybacks are done for the best motivation would be our

55:58

stocks undervalued and we're trying to signal that we think

56:00

it's undervalued. In reality, companies buy

56:02

back their stock largely because it offsets

56:05

dilution from stock based comp. And

56:07

second, given those low interest rates and where

56:09

multiples were, it was actually a creative added

56:11

to earnings per share. And by the

56:14

way, buybacks are not guaranteed to be a

56:16

creative to earnings because you're either foregoing interest

56:18

income from your cash or you're assuming interest

56:20

expense from debt that you raise. And

56:23

it's the relationship between that interest expense and

56:25

the inverse your P multiple centroids, the math

56:27

of it. So what happened was we

56:30

were in a period where buybacks were wildly and

56:32

across the board pretty much positive to earnings. And

56:35

we are now in a world where they are

56:37

essentially neutral. The EPS gains from

56:39

buyback that gig is largely over again, different

56:41

companies in different sets of circumstances. So I

56:43

just sort of throw that one out there

56:45

is this sort of funny takeaway from what

56:48

you would expect companies to do and what

56:50

they actually did is because their behaviors are

56:52

actually markedly different than what the textbooks tell

56:54

us they should be. What did

56:56

you see from the inside, Bill? Like how good

56:58

on average are founders who

57:00

are often the successful ones great at

57:02

building a product? How good are they

57:04

at allocating capital, which is the

57:06

luxury they earn if they're successful at that first

57:09

thing? I mean, I think the

57:12

thing that we live through with the

57:14

zero interest rate period, you go

57:16

back to when we're reading Brian

57:18

Arthur's work in the Santa Fe Institute

57:20

and we're reading so much other stuff.

57:23

So many other great thinkers and there's

57:25

all these types of game theory dynamics

57:27

and whatnot. And I don't remember

57:30

when it was, but it was way before the

57:32

zerk period actually happened. I said

57:34

to Michael one time, what if there

57:36

were multiple players in an increasing returns

57:38

game and they knew what

57:40

the outcome was going to look like? How

57:42

would it affect their behavior? And

57:45

it's actually an interesting conundrum. And

57:47

I think for the

57:49

early part of let's say the

57:51

internet era, most people didn't

57:53

think that way. And so maybe Bezos

57:56

was the only one thinking that way in

57:58

his case. So he's Florida. So man, I think,

58:01

everybody knows what wins because hear your mind

58:05

of what you've had. Absolutely. And

58:08

that that's exactly what the

58:28

holistic I

59:59

don't think there is any way to have a

1:00:01

point of view there that's interesting because

1:00:04

the answer I want to go back

1:00:06

to is there seems to always be

1:00:08

innovation. And if it

1:00:10

were so easy to predict exactly where

1:00:12

it was, then we'd all just go

1:00:14

be the best venture capitals this we

1:00:17

could, but they pop up in weird

1:00:19

places and new technologies. It's a combinatorial

1:00:21

effect of what's happening. Clearly, the experimentation

1:00:23

with AI is where so much of

1:00:25

that's happening right now. So every time

1:00:28

I've read, oh, it's all over, no

1:00:30

one's innovating. I don't believe that. There's

1:00:32

always something new coming around the corner.

1:00:35

One way to think about that maybe would be what are the problems

1:00:37

that need to be solved that haven't been solved yet. And

1:00:40

those problems, that's a shifting set as the world

1:00:42

changes. One huge one, which

1:00:45

we could point to right away is energy, energy

1:00:47

usage. So Bill's talked a lot about this with

1:00:49

nuclear and other things. So there's an example where

1:00:51

you definitely could see innovation, how that ties in

1:00:53

a lot of things we've already talked about. So

1:00:55

part of the way I might think about that

1:00:57

are, are there things that aren't good now? Are

1:00:59

there problems that need to be solved? And do

1:01:01

we now have the pieces and tools to put

1:01:03

it together in such a way to solve these problems?

1:01:06

What about the physical world? I mean, energy makes

1:01:09

me think about it. It's been one of

1:01:11

these cliches that it's a bad idea to

1:01:13

invest in anything that is hard and you

1:01:15

can touch because it's just a much harder

1:01:17

business to build. But obviously, there's great examples

1:01:19

of companies like that, Tesla and

1:01:21

others that are fantastic, huge companies now.

1:01:24

Bill, what do you think about the

1:01:26

physical world, whether it be energy or

1:01:28

robotics or other new applications of technology

1:01:30

that aren't just pure software all

1:01:32

the time, everywhere, and start to touch the real

1:01:34

world again? I agree with

1:01:37

you about the general principle that venture

1:01:39

capitalists got away from these

1:01:41

categories is simply they

1:01:43

don't bend like software does. So

1:01:45

the amount of exponential growth, it

1:01:48

ties into what we're

1:01:50

talking about ideas having sex, the ability

1:01:52

for software to replicate with zero

1:01:54

marginal cost, and to have low

1:01:57

capital costs, it just makes sense that

1:01:59

that would be tied to a higher

1:02:02

return on your investment dollar. And

1:02:04

the other problems that have existed material

1:02:07

science typically didn't follow

1:02:10

the same innovation path that say Moore's

1:02:12

law did. And so this happened

1:02:14

in solar. There were a lot of shots

1:02:16

on goal and Silicon Valley didn't pay off.

1:02:19

And there's been improvement. It's just been

1:02:21

more linear. And then regulatory plays a

1:02:23

big role. So it's energy,

1:02:26

your ability to get the government to hand

1:02:28

you money may matter

1:02:30

way more than what you accomplish in

1:02:33

the R and D lab. And are

1:02:35

the founder set up to

1:02:37

navigate those waters or not. And just cause

1:02:39

Elon did it, I'm not sure that means

1:02:41

everyone can do it, which is another

1:02:44

problem. It's pretty heroic. What he's

1:02:46

achieved, not just there, but space

1:02:48

X. The good news is, I

1:02:50

guess, for the global populace is

1:02:52

there are plenty of venture capitalists who are

1:02:55

standing up today and pounding the table and

1:02:57

say they do hard tech. And

1:02:59

so we're going to see investment. I

1:03:01

hope they don't get stuck in

1:03:03

the regulatory morass, especially around energy

1:03:05

and those kinds of things. It's

1:03:08

fascinating that it's called Silicon Valley. Like it

1:03:10

started with something that was physical and

1:03:13

then went so pure software for so long and now

1:03:15

we're coming back around. Yeah, it's

1:03:17

hard though. I mean, we used to

1:03:19

do a bunch of semiconductor investments and

1:03:21

it got to the point where it's

1:03:23

50 million per Silicon to first

1:03:25

tape out for your alpha

1:03:27

chip or whatever. And that's a lot

1:03:30

more like some of these biotech plays.

1:03:32

In a TSMC world, if you can't

1:03:35

get in their schedule, you're

1:03:37

toast and Nvidia's got

1:03:39

a lot of power in that and keeping

1:03:41

you. So it's just hard to

1:03:43

harder world to play in with those

1:03:45

dynamics. Whereas with software, no one can stop

1:03:48

me from writing software tomorrow. I

1:03:50

want to go back to the increasing returns

1:03:52

to scale and the notion of learning by

1:03:55

doing Michael, can you outline this idea, which

1:03:57

sounds self-explanatory, but I think is really nuanced

1:03:59

and. an important point of

1:04:01

around increasing returns. Canaro

1:04:03

won the Nobel Prize for his

1:04:06

work on equilibrium markets and general

1:04:08

theory of equilibrium. Canaro was

1:04:10

also interestingly a very early participant at seminars

1:04:12

at Santa Fe Institute. So now withstanding he

1:04:15

was sort of a general equilibrium guy. He

1:04:17

actually was one of the early guys sort

1:04:19

of encouraging work in

1:04:21

complex systems. And as a

1:04:23

side note, I'll just mention that he was in

1:04:26

his 90s at the time, but we were just sort

1:04:28

of standing around having a coffee and he was really

1:04:30

proud of the general equilibrium theory work. He

1:04:32

goes, but it kind of got us, our whole

1:04:34

profession off the track of understanding complex systems as

1:04:36

really vital to markets and economy. So I thought

1:04:39

that was kind of an interesting observation. The

1:04:41

reason I bring up Canaro is that

1:04:43

notwithstanding his Nobel Prize, I think his

1:04:45

most cited paper is actually about learning

1:04:47

by doing, which is 1962. And

1:04:49

the idea is pretty straightforward is the more you do

1:04:52

something, the better you get at it and you become

1:04:54

more productive. And so why

1:04:56

is this important for all of us now? Let's

1:04:58

just think about different industries. Bill

1:05:00

mentioned a moment ago solar. Solar is a

1:05:02

fascinating one. If you do, you have more

1:05:04

solar facilities, increase your output, your

1:05:06

costs can go down. So the classic formulation is

1:05:09

something called Wright's law named after this

1:05:11

guy, T.P. Wright. And

1:05:14

Wright's law says that for every doubling

1:05:16

of cumulative output, your

1:05:18

cost per unit goes down by 20%. He

1:05:21

wrote that paper back in the 1930s, 90 years ago, roughly speaking.

1:05:25

And it turns out, by the way, lithium

1:05:27

batteries for automobiles, perfect Wright's

1:05:29

law. Cost per solar unit, almost

1:05:32

perfect for Wright's law. And in fact,

1:05:34

a number of scientists at Santa Fe

1:05:36

Institute tested 60 different technologies to see

1:05:38

which model best predicted the actual cost

1:05:40

dynamics. The most famous one being,

1:05:42

of course, Moore's law. And they

1:05:45

found that Wright's law actually was the most

1:05:47

effective model explaining all this. And

1:05:49

the more you do with something, the better you get at it. Learning

1:05:51

by doing is a pretty big deal. And

1:05:53

you think about, again, electric vehicles, Tesla, and

1:05:55

Tesla's cost per unit advantage. Well, they're just

1:05:57

so far out of everybody in cumulative. of

1:06:00

output that their cost per unit is lower.

1:06:02

It's one of those wide increasing returns because if

1:06:04

you're ahead of the pack, you continue to expand

1:06:07

that lead versus giving it up. So

1:06:09

that's the basic idea. Bill, let's

1:06:11

apply that to your time as an

1:06:13

investor. If you had to consider your

1:06:15

skill today, you've done a lot of

1:06:17

investing versus your skill, let's say

1:06:19

in 2003 or something or 2004, 20

1:06:22

years ago, where do you think you

1:06:24

of today would most trounce you of 2004? It's

1:06:28

funny, man. My initial reaction is that

1:06:31

there's not much in venture, precisely

1:06:33

because the world changes and

1:06:35

it's so dynamic, both

1:06:38

from the new technologies that are

1:06:40

coming, but also the

1:06:42

competitive nature of venture is

1:06:44

changing constantly. Different people try

1:06:47

different forms and it's just

1:06:49

so dynamic. And Benchmark

1:06:51

always favored bringing on new young

1:06:53

partners. And we found that there's

1:06:56

a point at which they start to wildly

1:06:58

outperform the old guy. So I have the

1:07:00

opposite reaction. I'm not sure what there is.

1:07:02

The stuff that you learn that

1:07:05

you need to know, you can learn pretty

1:07:07

quickly and then you got to be on

1:07:09

the field. It's a crazy game. It's fun

1:07:11

because it's so dynamic, but it's ever changing.

1:07:14

All right. So, Bill, can I ask you a follow up

1:07:16

question to that? Because we wrote a report late last year

1:07:18

about the topic of pattern recognition and

1:07:21

a lot of investors say they like pattern recognition. And it

1:07:23

turns out the group of

1:07:25

investors who seem most enthusiastic about pattern

1:07:27

recognition are venture capitalists. And

1:07:29

the premise is this idea of its

1:07:31

intuitive expertise. You have this flash, like

1:07:33

I've seen this before based on my

1:07:35

expertise and that expertise comes

1:07:37

from being around. So to

1:07:40

Patrick's question, if you're around 20 years

1:07:42

more than your younger version of yourself,

1:07:44

do you not have more patterns that you've

1:07:46

seen and a sense and ability to anticipate

1:07:48

what's going to happen? Or is it a

1:07:51

sufficiently changing world, as you point out,

1:07:53

that you can't rely on those patterns?

1:07:56

I think the patterns have a half

1:07:59

life. not a the

1:08:50

only one of matters missing the

1:08:52

big one is all of the

1:08:54

game getting the negative right is

1:08:56

of little value it's so

1:08:58

a symmetric so anyway there is some

1:09:01

i don't wanna say there's none when

1:09:03

you put it at 30 years i'm

1:09:05

just not convinced that the

1:09:07

guy that's been adventure capitals from

1:09:09

30 years has these massive competitors

1:09:11

and i don't think there's much

1:09:13

data that supports that and another

1:09:15

thing that happens is

1:09:17

you just become cynical you become rich

1:09:21

i think it i think it i think

1:09:23

it i do maybe both maybe both maybe

1:09:25

both maybe both what

1:09:29

about this incredible stat that people have cited

1:09:32

but michael i know i saw you revisit

1:09:34

recently and it's obviously like the whole idea

1:09:36

of venture is predicated on this parallel idea

1:09:38

that's like a very venture concept but then when

1:09:41

you zoom out and look at all of markets

1:09:43

you see this crazy idea

1:09:45

that a tiny percent of companies

1:09:48

not just represent all the market cap

1:09:51

but also like even outperform basic things like

1:09:53

t-bills or something like this i'm

1:09:55

just curious for you both to react

1:09:57

to this strange feature of markets This

1:10:00

seems to always kind of be the case and

1:10:02

what its implications are for like how we should think about

1:10:05

investing in general. Well Patrick maybe I'll

1:10:07

kick off and just give the basic stats on

1:10:09

this. This is work done by Hendrick Bessenbinder, Arizona

1:10:11

State, which is really interesting. It's got some limitations.

1:10:13

I don't think people should run too hard with

1:10:15

it. But the basic setup is he looked

1:10:17

at all public companies since 1926 and what he found

1:10:19

was just under 60%. So

1:10:23

just got to let that number sit in your head, 60%. Built

1:10:26

to earn treasury bill rates. So

1:10:30

by his reckoning, they destroyed $9 trillion

1:10:32

of wealth. The

1:10:34

other little over 40% did create value. They

1:10:36

earned above treasury bill rates and they created

1:10:39

an aggregate $64 trillion of wealth.

1:10:42

These numbers are through 2022 by the way. And so

1:10:44

64.9 is $55 trillion of aggregate wealth

1:10:46

creation US market in the last call

1:10:49

century or so. But what's

1:10:51

fascinating to your point Patrick, and this is

1:10:53

sort of the venture capital-esque statistic is that

1:10:55

2% of those companies created

1:10:58

50 trillion of the 55 trillion. So

1:11:01

2% of the companies were 90% of value. You

1:11:03

can even go down a bit. The handful

1:11:06

of companies were actually a fairly substantial percentage,

1:11:08

including Apple and so forth. So

1:11:10

obviously venture, the average bill ethic said

1:11:13

it's expanding out. But let's say the average venture fund

1:11:15

is 10 years, but we have data on the

1:11:17

return for 30,000 venture

1:11:19

investments over the last quarter century or so. And

1:11:22

yes, 55% or 60% lose money. It's

1:11:24

actually not dissimilar at all. And then

1:11:26

you get some that make money and then you got your

1:11:28

right tails that pull up the whole portfolio. So as Bill

1:11:31

mentioned that you need to capture the extreme events to make

1:11:33

the whole portfolio go. So one

1:11:35

is looking at a century. Another is looking

1:11:37

at it's called a decade, but you're getting

1:11:39

sort of the same essential, almost like a

1:11:41

fractal pattern. The other thing to say is

1:11:43

interesting is that Best & Bind

1:11:45

are also collaborated with some folks, academics

1:11:47

and looked at the same markets outside the United

1:11:50

States. So they looked at an aggregate of 64,000

1:11:52

companies, including developing and developed

1:11:54

markets around the world. Same

1:11:57

basic patterns held true. Really

1:11:59

is interesting. So as an investor, obviously, you say

1:12:01

to yourself, if this is the pattern, you know,

1:12:03

I'm sure Bill and his colleagues think a lot

1:12:05

about this, but if this is a pattern, how

1:12:07

should we behave? That becomes the interesting question. Should

1:12:10

we try to identify those companies? Do we want to

1:12:12

make sure that we own those that the kind of

1:12:14

errors we make, we have to own the guy, the

1:12:17

companies are going to create all the value. Even

1:12:19

if we own some of the bad ones, it doesn't really make

1:12:21

a difference if we own the good ones, it's going to make

1:12:23

up for it all day and then some. If

1:12:26

we were to be a fly on the wall

1:12:28

in a Monday all day benchmark partner discussion with

1:12:30

this topic in mind, what sorts of things does

1:12:33

that then constantly bring up amongst

1:12:35

you and your partners as you're considering an investment?

1:12:37

Like if you were going to heed this truth

1:12:39

and you just said you can't miss the huge

1:12:41

ones and if you go in Sequoia,

1:12:43

they'll all talk about like be the person that finds the

1:12:45

next logo that goes on that wall. This

1:12:47

seems to be like the game that everyone's playing.

1:12:50

What does that feel like tactically every Monday as

1:12:52

you're talking about founders and customers? Like what are

1:12:54

the sorts of questions that forces you to ask

1:12:56

of young companies? So

1:12:59

a couple of different things. One is just to

1:13:02

embrace that attitude. I

1:13:04

think Bruce came back from reading one of

1:13:06

Ridley's book and used the phrase what

1:13:08

could go right at a partner meeting. And

1:13:11

so it's very easy, especially

1:13:13

with a big group, with a

1:13:15

group bigger than about five, it's

1:13:18

very easy to fall

1:13:20

into cynicism as a sport,

1:13:23

to start taking shots at stuff. And

1:13:25

so having this what could go right attitude,

1:13:28

in other words, make the primary part of

1:13:30

the discussion how big could this be rather

1:13:33

than trying to nitpick whether or

1:13:35

not it might fail. And

1:13:37

so that's one. Two, I

1:13:39

think it requires just exhaustive

1:13:42

behavior. You can't stop looking.

1:13:44

How would you know that

1:13:46

you looked under every rock? There's no

1:13:48

way to know that other than to

1:13:50

be exhaustive about it. And

1:13:53

so creating a culture where everyone

1:13:56

feels that responsibility is

1:13:58

important. That's just,

1:14:00

you know, never lose at the finish line.

1:14:03

Never ever, ever lose it finish line. Once

1:14:06

you've made a decision as a firm that it's something you

1:14:08

want to be in, make

1:14:11

it happen. How would you do that? Well,

1:14:14

now you're getting into the secret sauce. Maybe you'd be

1:14:16

like the saffron or like one ingredient. Well,

1:14:20

I mean, you have to have built the right relationships.

1:14:23

You have to call in the right favors

1:14:25

from a refutational standpoint

1:14:28

and the reference calls to the finish

1:14:31

line. Be tiresome.

1:14:33

Don't lose on price. There's the

1:14:35

obvious idea that you want to be non-consensus

1:14:38

and right. How often would that manifest in

1:14:40

the deals that you did that turned out to be great

1:14:42

ones where it wasn't that

1:14:45

competitive when you invested or did the

1:14:47

great ones feel really competitive requiring the

1:14:49

favors called in, et cetera, at

1:14:51

the time of the round itself? I'd say

1:14:53

it's going to be somewhere right in the

1:14:56

middle Patrick, because a lot of the big

1:14:58

returns either have some

1:15:00

momentum, even at a very early

1:15:02

stage, or they

1:15:04

have an individual repeat entrepreneur type situation

1:15:06

where they're highly competitive. So it'd be

1:15:09

very rare for there to be a

1:15:11

hundred percent absence of competition.

1:15:14

And then that become big. It's probably happened

1:15:17

before, but I think that's a rare event.

1:15:19

So it's somewhere in the middle. If it's

1:15:21

a pure jump ball, that's what's

1:15:23

happened with a lot of these late stage rounds

1:15:25

these days. I mean, if you're paying 90 billion

1:15:28

posts for Striper, open AI, you're

1:15:30

probably not looking at the type

1:15:33

of returns Michael was talking about.

1:15:36

What in the world of technology or

1:15:38

just like the landscape today has you

1:15:40

the most interested or excited Michael

1:15:42

may be starting with you that we haven't talked

1:15:45

much yet about today? I would

1:15:47

defer to Bill on this one. I guess probably two

1:15:49

or three big things. One is how is this AI

1:15:51

thing going to unfold? I think Bill made a really

1:15:53

important point just to reiterate distinguishing between

1:15:55

AI, broadly speaking and these large

1:15:57

language models are generative AI, right?

1:16:00

So those are really two distinct things that we should keep

1:16:02

those separated at least a little bit.

1:16:04

That's gonna be an incredibly important area to

1:16:06

understand. I do think that stuff that's related

1:16:08

to physical, the physical world is also gonna

1:16:11

continue to take on significance. We

1:16:13

haven't really been completely overt about this, but

1:16:15

when you think about competitive strategy, really what

1:16:17

you're after is ability to

1:16:20

generate good returns and barriers to entry. You're

1:16:22

getting good returns and it's difficult for someone

1:16:24

to replicate what you're doing or to take

1:16:26

away some of your economics. Those

1:16:29

opportunities obviously do exist in the physical world as

1:16:31

well. So that's probably another area just to straddle

1:16:33

these two things. I think are super important. The

1:16:36

other area, again, not an area of expertise for

1:16:38

me, but it feels like it's really ripe for

1:16:40

a lot of change. And who would

1:16:42

have said this 10 or 15 or 20 years ago is

1:16:44

healthcare. When you think about AI, think

1:16:46

about generative AI, think about what could happen in the

1:16:48

world of healthcare, how much

1:16:50

money goes into it, how poorly

1:16:52

managed it is as an industry,

1:16:54

broadly speaking, the regulatory hurdles. That

1:16:57

just feels like an area too. I don't know how easy

1:16:59

or hard it is to make money, but that's another area

1:17:01

that's got to be right for some change. I

1:17:04

would agree on all those fronts. I asked

1:17:06

about the talk I gave on regulatory

1:17:08

capture. I look at the energy situation

1:17:10

where we know, and it's

1:17:12

not just us, it's us leaning on

1:17:14

the greater minds of our world, the

1:17:16

steep thinkers of the world. We

1:17:19

know that the most

1:17:21

efficient way to create energy is nuclear and

1:17:24

we stepped off of the learning curve that

1:17:26

Michael talked about. And how do you both

1:17:28

get the red tape out of the way

1:17:30

and get back on that learning curve in

1:17:32

a fast way? I mean, it's

1:17:34

awesome that for the first time, the Biden

1:17:36

administration, I think is going to help restart

1:17:39

a plant. But where you want to go

1:17:41

is so much further from

1:17:43

that place. It's great to see us

1:17:46

reach a right rail and come back.

1:17:49

But how do we accelerate in the

1:17:51

other direction? It probably would take

1:17:53

a very active group

1:17:55

of people in Washington that would

1:17:57

want to see that happen, to rewrite

1:17:59

regulations. to potentially incentivize the

1:18:01

best and brightest minds to get

1:18:04

us back on that curve on

1:18:06

healthcare. I totally agree with the

1:18:08

need. I think if you didn't

1:18:10

have the regulatory problem, you have

1:18:12

entrepreneurs could do so much more,

1:18:15

but take a simple construct

1:18:17

like price transparency. Any marketplace

1:18:20

company in the world would obviously want

1:18:22

to expose all pricing so

1:18:25

that people can make good decisions. We can't

1:18:27

even get that. Congress

1:18:30

demanded that the hospital systems disclose their prices

1:18:32

and several of them just sat on their

1:18:34

hands and paid to find, and

1:18:36

these are pretty noteworthy institution and

1:18:38

the press doesn't really take them

1:18:41

down for doing that. It's

1:18:43

going to require such a different mindset

1:18:45

than where we are today. And

1:18:47

I just don't know how you get there. I don't

1:18:50

know how you get out of the trap. So

1:18:52

Patrick, can I mention one thing too, like Bill

1:18:54

mentioned before, zero based thinking, there are two areas

1:18:56

I found fascinating that if you would ask

1:18:58

people in the 1950s, what will the

1:19:00

future of these areas be? I think they would

1:19:02

have said they're very bright. One is

1:19:05

psychedelics, which in the 1950s

1:19:07

were demonstrably helpful for certain people

1:19:09

for things like depression and addiction

1:19:11

and so forth. So the

1:19:13

medicinal, careful medicinal benefits were quite clear and

1:19:16

that they just went wildly out of favor

1:19:18

for a very long time and are now

1:19:20

just getting back into the mainstream

1:19:22

understanding. A lot of people have suffered in between

1:19:24

because of it. And the other is nuclear. From

1:19:27

Martian came down and said, Oh, you guys need

1:19:29

energy, energy is fundamental to everything. What do you

1:19:31

guys got? Can you show them around and they'd

1:19:33

be like, Oh, this is the obvious thing you

1:19:35

guys should be doing lots of. It's

1:19:38

so straightforward and obvious if you took

1:19:40

it from a zero based point of

1:19:42

view, but because of all this regulatory

1:19:44

and emotional and political baggage, look

1:19:47

at Germany now having to reverse

1:19:49

decisions because they're recognizing. Anyway, so

1:19:51

it's fascinating that you get these things that

1:19:53

you're sort of like half century trends take

1:19:55

you have to bend it back around where

1:19:58

if you just said, if I had no prior. knowledge

1:20:00

or understanding, it would be obvious

1:20:02

that these things are beneficial to the world and they're just not

1:20:04

where they should be. I love

1:20:06

the zero based idea applied to ideas. Nuclear

1:20:08

and psychedelics just not mixed together. Two

1:20:12

closing questions for you both. The

1:20:15

first is about working with and

1:20:17

being around what I

1:20:19

don't have a better word for than just genius. And

1:20:21

this is based on a few people that

1:20:23

have passed recently and that you guys have

1:20:25

both had some interactions with one or the

1:20:27

other. One is Danny Keniman. Most people

1:20:30

listening will have read his work and thinking

1:20:32

fast and slow and heard the name a

1:20:34

lot. The other is Cormac McCarthy who Michael

1:20:36

I know you worked with and Bill too

1:20:38

at Santa Fe and I think Michael he

1:20:40

was really close with your wife such a

1:20:42

cool relationship. And Murray Gilman is the third

1:20:45

where you know these are three people that

1:20:47

are probably genius by any definition. I'm curious

1:20:50

about those three but also just what you

1:20:52

both have learned about a certain category of

1:20:54

person like that. What they're like and what

1:20:56

it's like to work with them. Michael

1:20:58

maybe starting with you. I think genius

1:21:00

is a very fair term for all those folks but

1:21:03

they were for me very different experiences. I would probably have

1:21:05

to say if you had to say pick the person you

1:21:07

thought was the smartest person you've ever been around in your

1:21:09

life I would say Murray Gilman. The guy was

1:21:12

just extraordinary and Bill's got a Murray Gilman

1:21:14

story so he'll maybe let him tell his

1:21:16

Murray story but if you said

1:21:18

that you could only pick one person to recreate the

1:21:20

knowledge of humanity I would have

1:21:22

picked Murray. The guy was extraordinary. And

1:21:24

he obviously won the Nobel Prize for

1:21:27

Physics in 1969 leading light in that

1:21:29

area but incredibly interested

1:21:32

in lots of different things. Obviously a

1:21:34

founder of the Santa Fe Institute so

1:21:36

dedicated to understanding various disciplines so just

1:21:38

an extraordinary guy. Cormac McCarthy of

1:21:40

a different ilk obviously he was a writer and

1:21:42

an amazing writer. He didn't like at least with

1:21:44

me didn't like to talk that much about his

1:21:47

writing. He would talk a little bit about it

1:21:49

but not that much. But I think

1:21:51

and Bill maybe you can back me on this. I mean

1:21:53

I think if you walked around the Institute people would say

1:21:55

he was like the smartest guy there even though he wasn't

1:21:57

a scientist. So he would sit in on all the meat.

1:22:00

Oh, even I used to have

1:22:02

conferences in Santa Fe for business, you know,

1:22:04

investors in the 1990s and someone say,

1:22:06

where Mac has asked if he can sit

1:22:08

in and I'm like, yeah, absolutely. So he would

1:22:10

come and sit in like business presentations. So the

1:22:12

guy was extraordinary and he could

1:22:15

talk about any topic and was an extraordinary

1:22:17

storyteller. And then when you read

1:22:19

his stuff, I mean, it's almost like someone says, if you

1:22:22

know, I go over to Bill's house, he says, I've got a $3,000 bottle of

1:22:24

wine because that's how he rolls. I'd

1:22:26

be like, I'm not good enough. I

1:22:29

don't have the quality of a palate

1:22:31

that's refined enough to appreciate how good

1:22:33

this wine is. That's a little bit

1:22:35

how much like I feel when I read Cormac, I think it's

1:22:37

almost too good for me. I need to slow

1:22:39

down or have someone walk me through it. Danny

1:22:41

Kahneman is another guy and I met him probably close

1:22:43

to 20 years ago. First of

1:22:45

all, just an extraordinary person in the sense that

1:22:48

he made extraordinary contributions to

1:22:50

understanding how people behave was

1:22:53

incredibly measured, thoughtful. He was like

1:22:55

sitting down with your very wise

1:22:57

grandfather. There was a

1:22:59

recent tribute that was put out about him and

1:23:01

one of the common threads was the fact that

1:23:03

he actually not only was willing

1:23:05

to be proven wrong, he actually sought

1:23:08

views that were different than his own and was

1:23:10

almost happy to be proven wrong about something. And

1:23:13

his take was, if there's a

1:23:15

truth out there and I now

1:23:17

no longer harbor a false belief, I'm

1:23:20

stepping closer to the truth. And

1:23:22

boy, what an inspirational way to

1:23:24

lead your life every day, say,

1:23:26

if I believe something that's not

1:23:28

what it should be, I'm going to step toward understanding

1:23:31

the world in a better way. And

1:23:33

that requires an enormous amount of mental energy

1:23:35

and an enormous amount of mental flexibility. But

1:23:38

he above all has embodied that. And

1:23:40

that's leaving aside Patrick, as you pointed out, reading

1:23:42

fast and thinking fast and slow, like all the

1:23:45

lessons in there that people really

1:23:47

should internalize, investing business and it doesn't

1:23:49

matter. Like in your life, these are

1:23:51

really, really our concepts. Go

1:23:54

with your Murray Gell-Mun story. So

1:23:56

by the way, before I tell that story, since

1:23:58

Michael was so kind. to offer thoughts

1:24:01

about myself, I would say one of

1:24:03

the most amazing things about Michael is

1:24:05

his ability to synthesize. And so Michael

1:24:08

can go read a book

1:24:10

that's too dense for most of us to

1:24:12

make it through or go to a lecture

1:24:14

from a professor that most of

1:24:16

us, you know, couldn't stay awake through and

1:24:18

come away with the three tidbits that we

1:24:20

should all know. And I think

1:24:22

part of what lands in Michael's

1:24:24

books is this ability to synthesize

1:24:27

from some of the smartest people

1:24:29

on the planet. And that then

1:24:31

gives us the opportunity to be

1:24:34

proximate to them. We were visiting

1:24:36

Santa Fe a long, long time

1:24:38

ago. I'm going to guess late 90s. Yeah,

1:24:40

late 90s. That sounds right. 99,000. So

1:24:43

I'm hopefully 30 at the

1:24:45

oldest. By that point, we had read the book

1:24:47

and we knew who all these people were. And

1:24:50

somehow I find myself at a breakfast table

1:24:52

with only like four or five people, but

1:24:54

one of them's Murray Gell-Man. And it's not

1:24:56

like an organized breakfast. It's like people grabbed

1:24:59

a burrito and sat down next to each

1:25:01

other. And someone asked Murray

1:25:03

what he's spending time on. And he says

1:25:05

quantum computing. And they say, how's

1:25:07

it going? And he says, well, we're struggling

1:25:10

because we can't measure the

1:25:12

state of the system without messing

1:25:15

up the system. And through what

1:25:17

I will only describe as either

1:25:19

egoism or ignorance, I blurted without

1:25:21

thinking. So this was whatever

1:25:23

that is, system one versus system two,

1:25:26

the phrase Heisenberg strikes again,

1:25:29

to which Murray's face turned

1:25:31

bright red, his head

1:25:34

spun on his neck.

1:25:36

And he looked right at me and

1:25:38

said, what did you say? Like in

1:25:40

the sternest, meanest tone possibly. And

1:25:42

I went, I

1:25:45

felt like the smallest human on the planet

1:25:47

at that moment in time. So it turns

1:25:49

out that the thing

1:25:51

he's describing is the observer effect, which

1:25:53

I now well know. And

1:25:56

even on the Wikipedia page for the

1:25:58

Heisenberg uncertainty principle, these These things are

1:26:00

often confused and it's highlighted, but this

1:26:02

was a pet peeve for him, people

1:26:04

that confused the observer effect

1:26:07

with the uncertainty principle and he let me

1:26:09

know it. What

1:26:13

about working with Genius Bill? Like is

1:26:15

Genius, is that a useful concept? Are

1:26:18

the people that you seek out

1:26:20

geniuses, does that matter? Is that a

1:26:22

stupid word to you? What do you think? I

1:26:25

would probably say that

1:26:27

the more interesting thing which Michael talked about

1:26:29

are these people that are just kind of

1:26:31

truth seekers that are just always open for

1:26:33

discussion and always trying to get to the

1:26:36

next place. They bring a

1:26:38

very different mentality to the table. Michael

1:26:40

and I spent a lot of time in the

1:26:42

past couple of years with Jeffrey West and just

1:26:44

your ability to sit down

1:26:46

with them and say, okay, you just said

1:26:49

this, but my mental model conflicts with it

1:26:51

in this way. Can you tell me and

1:26:53

like for that to be intriguing to them

1:26:56

and to be them to be open minded

1:26:58

to wanting to explain that and

1:27:00

to try and figure that out together

1:27:02

makes the relationship at least from our

1:27:05

side so powerful, which is part of

1:27:07

why we spend time there. There

1:27:09

are other people who just wouldn't have time for

1:27:12

you and just say, get out of here. But

1:27:14

I think if you have that plastic

1:27:16

mind, we're always looking to

1:27:18

learn. It's really powerful. You

1:27:21

can walk away with something from a conversation.

1:27:23

The other party may not even know they

1:27:26

conferred anything to you. I

1:27:28

also say Bill gave another brilliant

1:27:30

talk, Running Down a Dream. One

1:27:32

of the things I took away from that,

1:27:34

he features a number of people who are

1:27:37

extremely distinguishing their fields, Bob Dylan and Bobby

1:27:39

Knight and Danny Meyer. But I

1:27:41

think the point I took away, Bill, hopefully

1:27:43

that was the message is that these guys

1:27:45

worked incredibly hard at mastering

1:27:47

their craft and put

1:27:49

in lots and lots of hours, lots of

1:27:51

passion, lots of sweat. So what you see

1:27:53

now is the output of

1:27:55

all that work without perhaps fully recognizing

1:27:57

how much they put into it. and

1:28:00

how where they are today was formed by

1:28:02

all that effort. And by the way, lots

1:28:04

of diverse influences. It wasn't just one influence,

1:28:06

but lots of diverse influences which they took

1:28:08

and made into their own to some degree.

1:28:10

So I think that's another really powerful lesson.

1:28:13

We talk a lot at the Santa Fe Institute like

1:28:15

why being exposed to diverse ideas can really be helpful.

1:28:18

And again, it's not because you want to take the

1:28:20

best of those ideas and use

1:28:22

the tools that are helpful for you as you

1:28:24

sort out your day and solve your problems.

1:28:26

That talk is obviously for old people and

1:28:28

certainly for young people is really, really powerful

1:28:30

and it underscores by the way also the

1:28:33

importance of hard work and there's no substitute

1:28:35

for hard work. Michael

1:28:37

was the second guest on this show

1:28:39

way back when and I think

1:28:42

this is our sixth maybe something like that. I think

1:28:44

you two are actually the two most frequent guests. So

1:28:46

it's so cool to finally do this with both of

1:28:48

you together. We used to call it

1:28:50

the Mobison bump on my team because every time

1:28:52

he would come on, the audience would like double

1:28:54

and then stay that way. And so

1:28:56

I owe a huge amount of my success and then the same

1:28:58

thing started happening with you. You both

1:29:00

seem to have what seems like a

1:29:02

felt obligation to do a lot of

1:29:04

teaching, not just doing

1:29:06

but teaching, synthesizing, giving back, putting

1:29:09

things in a way that people

1:29:11

can consume them. And

1:29:13

I wonder what you would say

1:29:15

to others that have that capacity, that

1:29:17

ability to teach and give back

1:29:19

in that way and the benefits of

1:29:22

it to you. Obviously, there's benefits to everyone that's

1:29:24

listening to this, to everyone that reads your guys's

1:29:26

stuff that has learned from you along the way.

1:29:29

Maybe just as a point of inspiration, say a bit

1:29:31

about why it can also be a nice

1:29:33

selfish thing in some ways and can make your

1:29:35

life return better because you've both done a lot

1:29:38

of it. It happened to

1:29:40

me anecdotally because I became a

1:29:42

self-signed analyst and that's your job

1:29:44

to publish what your thesis is.

1:29:46

And so it was a necessity.

1:29:48

I didn't do it for the sake of it.

1:29:50

Very quickly thereafter, I learned

1:29:53

that the broader my distribution was,

1:29:55

the more power came back

1:29:57

to me to your point. And

1:30:00

then later, I think in venture capital, I learned

1:30:02

that having a reputation as a

1:30:05

thought leader was very helpful in

1:30:07

closing the deal back to your earlier

1:30:09

question about winning and being able to

1:30:11

help. And so the reputational

1:30:14

benefit access, we talked about being able

1:30:16

to sit down with geniuses and talk

1:30:18

to them. Getting that access

1:30:20

is partially tied to reputation. And

1:30:23

so that's another benefit along

1:30:25

the way somewhere. I learned that I just

1:30:27

think better when I write, you've

1:30:29

heard this from others, but putting things down in

1:30:31

a structured way and having to defend

1:30:34

an argument ties back

1:30:36

into Bezos' six page letter kind of

1:30:38

thing. Like it just causes you to

1:30:40

think better. There's some consequences. Like you

1:30:42

write everything down, you're going to get

1:30:44

some stuff wrong. And then people 15

1:30:46

years later will say, see, so

1:30:49

that comes with it. And then as

1:30:51

I've gotten older, the giving back

1:30:54

part is really, really rewarding.

1:30:56

If someone comes up to you and says,

1:30:58

Hey, that really helped change my life, my

1:31:00

direction. That's pretty powerful. Yeah.

1:31:03

I don't have much to add to that. I mean,

1:31:05

I've been incredibly blessed that basically my career has evolved

1:31:07

to the point where a lot

1:31:09

of what I get to do is to learn

1:31:11

and to share those ideas with others and hopefully

1:31:13

to make them more effective what they're doing. So

1:31:15

that's amazing. I would echo

1:31:18

what Bill said is that I find

1:31:20

that teaching and writing and their book

1:31:22

can be very related, really

1:31:24

compel thinking. I often think I understand

1:31:26

something until I really go to write

1:31:28

it down. Patrick, that

1:31:30

increasing returns is a good example where

1:31:33

I was familiar with all those ideas and it kicked

1:31:35

them around and talked about them for

1:31:37

a long time, but really hadn't gone deeply into each

1:31:40

of those things. And just spending time to do that

1:31:42

allowed me to understand the links between

1:31:44

them, understand them in a deeper way.

1:31:47

So writing them down, your thinking

1:31:49

and understanding really benefit. Yeah.

1:31:52

Well, it's very cool for me to do

1:31:54

this with you guys. I'm really appreciative of

1:31:56

the time. Michael had such inspiration on my

1:31:58

time as a quant bill. Your inspiration. my

1:32:00

time as a private investor has been enormous. This is

1:32:02

so cool to do with you both. Thank you

1:32:07

for the time. Thank you. Thank you. Thank

1:32:30

you.