After [music] saying he was out, now

Bill Maris is returning to the investing

world. The founding CEO of Google

Ventures has raised [music] $150 million

for his new fund called Section 32.

>> With a smaller fund, I have the

advantage to be very selective in the

companies that I invest in, the people

that I hire. We're going to invest for a

financial return. Any other metric is

impossible to measure and therefore

won't succeed.

>> Think of the change that [music] has

happened just in the last 100 years and

what's about to happen in the next 100

years with the advent of AI. The world's

going to change by orders of magnitude.

>> Thank you very much for that warm

welcome. I am Bill Maris. I'm the

founder of Section 32. Prior to that, I

was the founder and CEO of Google

Ventures. I was also Google's Vice

President of Special Projects where I

incubated Waymo and Google X, Calico,

and many other

projects as well. And before that, I

founded a web hosting and data center

company,

which we're going to talk a little bit

about.

And

today I think I'm going to talk to you

about a few of the lessons I've learned

on these interesting experiences I've

had in life. So, we'll start We're going

to have four lessons I'm going to talk

about and we're going to go back to 1997

to start when I was a fresh college

graduate. I had a degree in

neuroscience.

And I found myself on Wall Street.

Somehow managed to land a job there, but

I was miserable having to wear a suit

and trudge to work in the heat, but one

good thing came of that, which was I

looked in the closet of the office one

day and I saw a server. And I asked,

"Well, what is this

thing beneath our jackets?" And they

said, "Well, that's where our email and

websites

live." And And as can happen to many of

us, I I had a moment where I felt like I

was bathed in the light of inspiration

and and I thought

I thought

I think I've glimpsed the future.

Uh I I I I think I can maybe make a

business out of this because

if you can have our website and email in

your closet, how many websites and

emails could I put in my closet? So, I

immediately quit my job

I because I I had I had kind of glimpsed

through a keyhole and through that

keyhole I thought I saw the internet and

I saw a data center and it looked

something like this or maybe when I say

data center

you think of a something like this or

something like this, but in 1997

the state-of-the-art data center looked

almost exactly like this.

We had three servers,

a small, medium, and large. Uh

business grew, we eventually had five

servers

and this isn't a data center at all.

This was my apartment where I founded

the company

with credit cards

and the servers lived in one room.

The work happened in the other room

and we get very hot in that room

and this was in Vermont. So, I opened

the windows and then we get very cold.

So cold in fact

that by noon if you had a glass of water

on your desk it would ice over.

You may think though

this isn't so bad, but but actually this

was also my apartment as well. This was

the bed

and you may look at that and think well

you've got a mattress and a nice pillow

and then look at that nice blanket, but

this is a rug I got from Home Depot to

keep myself warm on those nights and one

day

there was a thunderstorm.

The roof started to leak

and I knew I needed to do something

because water and computers and servers

don't mix well. So, so I called the

landlord and said

the roof's leaking. The landlord said,

well, that happens sometimes.

But I knew that I needed to do

something. So, when you don't know what

to do, you go to Home Depot. I got a

bucket of tar and a mop, and I went up

on the roof,

and there was lightning, and there was

rain, and I went up there and I I tarred

the roof.

And I did not glimpse the future in that

case because I didn't know when you're

tarring the roof that you should start

at the far corner and work towards the

door rather than

the reverse, and I tarred myself into a

corner, but the choice that I faced was

either

the servers get electrocuted, or perhaps

I get electrocuted, but as an

entrepreneur, I was willing to take that

risk, which, you know, news flash, I

survived. Uh my shoes, though, are still

stuck on that roof uh in Vermont, which

takes me uh to uh

lesson two, which is

to see the future, sometimes you need to

be a little bit insane.

Uh

it may appear to those around you that

you were tarring the roof in the

thunderstorm,

and to that point, I'm going to share a

few slides here that a friend named

Stewart Butterfield was kind enough to

share with me.

And here's the inauguration 1989,

>> [snorts]

>> and

there's someone taking a picture.

That makes sense, probably a film

camera, and

2005, it it's not very different.

There's still someone back there taking

a picture, and then

let's go just 4 years later, to another

inauguration,

and if we look closely, it's quite a bit

different

because now everybody's got a camera.

Everybody's got a camera, and this was

kind of before cameras were mushed into

cell phones. It was kind of around that

time it was starting to happen, but but

that's not the most interesting thing

about this photo because in this crowd

is someone who, to his friends, I'm sure

seemed insane, who also did glimpse the

future. If we look closely,

this gentleman has decided to, I don't

know, live stream, or record the

inauguration on his laptop. Uh

he knew something that those around him

didn't know, which is one of the things

that I've always looked for in

entrepreneurs is they know a secret

about the future that most of us don't

believe.

Let's fast forward to 2007.

I find myself somehow at Google.

Uh and a challenge was given to me.

Uh the challenge was Google needs a

venture fund.

Uh we were starting to make some

investments. Uh we didn't have a

coherent strategy. There were no

budgets. I had to figure out what to do.

Uh so I

first found a friend, Rich Miner, who's

the co-founder of Android,

uh and he became my partner in crime as

we conceptualized what what could Google

Ventures be. Uh we went up and down Sand

Hill Road and we

we talked to

everyone. Anyone that was willing to

talk to us and have a conversation, we

were willing to talk to to see what we

what we could learn.

Uh

we came up with a plan.

Our plan was to obtain all the data of

venture that we could find. And being

Google, you can imagine it was a lot of

data. Historical data, you name it.

Uh

then we decided we would as step two use

AI, but at that time

Google would not let us use the term AI.

And this persisted for many years.

Bill,

AI is science fiction. It is it's a

hundred years away if it's ever going to

happen.

Uh let's stick to machine learning. By

the way, when you say AI, it freaks

people out. So stop freaking So we had

to call it machine learning

and we used machine learning to do two

things: design

the ideal portfolio construction by

running millions and millions of

simulations and back testing and all of

the things you can imagine that data

scientists would do.

And and to determine what the ideal fund

size would be. And people were excited.

Here's a headline from TechCrunch at the

time.

And and people that inside of Google

were also pretty excited. This is one of

the senior execs I later learned had

this to say.

And you know, I I have to admit it

seemed crazy. The plan seemed crazy at

the time, but let's look at how it

turned out. So over this time period

2009 to 2018, top quartile VC returns

looked like this and top decile looked

like this.

Using publicly available information,

I'm not sharing any

non-public proprietary Google

information. We would estimate Google

Ventures returns at about 4.1x.

And I

adhered more closely [snorts] to the

strategy and the investments that I led

and the investments that I led turned

out like this, which takes me to lesson

three, which is don't bet against

computer science. I've seen it

happen many many times and many many

fields. If you apply the right kind of

computer science at the right time to

the right problem,

you will get to the right answers. I

would not bet against it.

Even if it looks like you're tarring the

roof in a thunderstorm. So let's fast

forward to 2017.

I decided to start my own fund. And

again, those around me said, "You're

insane. Why would you do that? You're in

the warm womb of Google. Lunch is free

and the massages are plenty and so

forth." But after the idea, you know,

sunk in, I the advice turned into raise

as much money as possible. You know,

that's the right way to run a fund.

You'll get a big management fee. You'll

be happy. Things are going to work out

really well for you.

And I thought about that relative to

everything I had done up to that point

and I decided to to not take that

advice. And

over the course of my time at Section

32, we've had six funds. We've invested

in companies like CrowdStrike and Cohere

and Coinbase.

And all six of those funds have

averaged

about 400 million in size and all are

performing in their top decile. And to

the extent there is DPI to measure,

that's the only measure as far as I'm

concerned in venture that counts is DPI,

which takes me to lesson four. That this

is this will be heresy to some, but

small funds outperform large funds. This

is simply the math. This is not

an opinion I'm trying to convince you

of, but there are many reasons for this.

Smaller funds you can have more focus.

You have I mean I've I've already

managed a multi-billion dollar fund with

hundreds of employees. It's distracting.

You cannot give the attention to

founders that I would like to give.

It

There There are many reasons for this.

And if we look at

top decile performance of DPI,

um

funds smaller than 750 million average

return of 4.76x and funds larger than a

billion

2.42x.

Funds below 750 million across that time

period represented 95% of top decile

performers with discontinuous return

compression above 750 million.

Why is this? There's a lot of reasons

for this.

You can use your own numbers, but I'll

just do a little thought experiment. If

you have a 500 million dollar fund

and let's say on average these days you

can own 10% of a company,

you need 5 billion dollars of exits to

get your money back. Let's just remind

ourselves that the 75th percentile of

venture loses money

and there is persistence of performance

of the top quartile. So So if you need 5

billion to get your money back and and

if you want to be in this business for

the long term, let's say you set your

your goal at 3x, you you need to return

15 billion dollars of exit value in your

companies. Now if you have a 7 billion

dollar fund and we do the same math

through

you know, you've got to return 210

billion. 7 billion to to 70 * 3x is 210

billion, which uh

exceeds the total venture-backed M&A and

IPO exit value in most years.

Uh

this year may be an exception, but I

that is something I'm looking forward to

talking about when we sit down. For

those of you we've crunched the numbers,

we've done all the math. Those are

Bill's four lessons for today. I hope

that they're somewhat useful. There's a

lot of stories behind all this and I'm

looking forward to talking about them

for a few minutes with the guys. Thanks

so much.

>> You guys are old friends.

>> Yes, we are.

>> We go way back. Well, Bill's when he

started Google Ventures

I was the first ex-Google

company you invested in.

>> That's correct. And

>> How did it go?

>> Climate Corp. A billion-dollar exit to

Monsanto.

>> What was your multiple? What was the

return?

>> Oof, I don't know.

>> It was actually good for you guys.

>> It was quite good, yes.

>> Yeah, you guys were in the B and the

>> Yeah. It was when billion dollars was a

a lot of money then.

>> That back then that was a good deal.

>> That would have been That would have

been the seed round.

>> Like an A round?

>> Yeah, that would have been your A round.

Now we're going to do it again with A

Halo, so

>> Now we're going to do it again with A

Halo. Um so

you know, I just want to juxtapose what

you said with what Thomas shared.

They've got a very large kind of capital

base that they invest and they're

investing significantly in these later

stage rounds of these well-proven

companies where it's, you know, the data

he shared is that you can get

significant multiples to get to that

next phase. You know, you're more likely

to go from a billion to 10 billion and

then you're more likely to go from 10

million to 100 and 100 to a trillion,

trillion to whatever.

Um you know, doesn't that justify an

alternative strategy to what you're

saying of having smaller funds focused

on venture that you can maybe barbell

it, have smaller vehicles focused on

venture, and then very large vehicles

that bet on the sure things that have

that durability and that compounding

advantage, and you can kind of have the

two together both be 3x return.

>> So, my observation on that would be one,

I haven't seen the data science to

support that second conclusion of the

late stage companies that that can be an

an ongoing trend other than this one

moment, this weird moment in time with

these multi kind of trillion-dollar

exits that are coming. That that would

be kind of observation one. Two,

um would be at a certain point and this

is not a negative, it's just an

observation. If you're an RIA and

you're, you know, collecting assets,

that is not venture. You know, venture,

as I practice it at least, is a

different craft where you are making

concentrated bets of your time and

capital on entrepreneurs and helping

them build a business. And there's

nothing wrong with late stage investing.

However, I also have a an observation

that

I I a uh a bit of an objection to

uh companies that wrap themselves up in

public benefit

language and then

uh

keep the value creation uh to themselves

and an elite group of investors through

a big part of the curve and then say,

"Well, we're here to benefit humanity."

Well, what humanity needs is money. So,

it would it might be better to go public

sooner because we'll see how these

multi-trillion-dollar IPOs go. However,

if I'm Google and I don't speak for

Google and I decide to arbitrarily cut

the cost of, you know,

tokens to 80%. I'm going to cut them in

What happens to the business models of

Open AI and Anthropic at that point?

>> What happens? Tell us.

>> Actually, what you know, what does

happen?

>> well, if you're a company and you can go

to Google and Gemini and you can pay 80%

less

for that

basically identical product

why wouldn't you do that? And then the

compression and the pressure on those

other businesses goes super critical.

>> What are the chances that the other shoe

has fallen that

>> might happen.

>> If I were Google, that's what I'd do.

>> Walk us through the scenario where

Google decides with their war chest

with their money printing machine, you

know what?

Their margin is my opportunity.

I'm going to give tokens out 20 cents on

the dollar. Every time they lower their

price, I lower our price.

What happens

on the playing field? Walk us through

that.

>> Would that not be the rational thing for

>> It's clear they're going to do it.

>> Well, it may not

>> be a margin though to the

>> They they may be burning investor cash

sort of like an Uber type model, grab

market share,

>> Capital as a weapon, tokens as a weapon.

>> Token as a weapon, grab market share,

grab an install base on consumer and

enterprise. But fundamentally at some

point, you got to have cash generation.

>> So that's 100% possible.

It's 100% probable.

>> Look, I'll just it's been said before, a

trillion for spend commitments

on 60 billion dollars of revenue. And

now you're going to go to the public and

hope that retail is going to pick that

up.

>> Yeah, tell tell us about companies

staying private longer

and how unfair that is to the bottom

half of society who don't get to

participate in it.

>> for those 99% who are mostly not us,

right? So So your 401, you know, those

401ks, those retirement plans to get

into those companies now which are

getting bizarre exceptions to S&P 500

rules that they're all of the rules are

being broken.

Uh the passive funds, the uh ETFs are

going to have to pick them up. And where

do you think we are on that curve of

value creation? Could they go 3x from

here? Sure, but

>> So the

just to say it as plainly as possible,

we're going to force overpriced products

on the 401k holders of America who

didn't get to participate early. This is

your position that this is profoundly

unfair and creates more wealth creation

for the people who don't need it and it

makes the people's retirement accounts

the bag holders.

>> There's a lot of risk in that and my my

my objection is don't say you're doing

this for the benefit of humanity and do

the other thing.

>> Make the public's retirement accounts

the bag holders.

>> Or just say this is how we're running

our business and this isn't for the

benefit of humanity.

>> Bill, do you think that

what happens to venture? I asked Thomas

this question.

When these dollars get distributed,

there's going to be a handful of funds

that have ginormous returns. I mean just

unbelievably excessive. Founders two,

you know, is going to print a hundred

billion dollar return on two hundred

million dollars of invested capital.

But that's one fund in isolation.

>> Right.

>> Right. And there'll be a few. Your funds

when you were at GV are going to print

an enormous

upside.

And so if you don't look closely though

at beyond the averages, venture's going

to look incredible. If you look past the

averages, you're still going to look

extremely bimodal. A handful of winners

and a ton of losers.

>> How does that play out?

>> one, that's how venture is, right? 75%

of funds lose money. But two, in order

for Founders Fund or pick any fund to

get that hundred billion out, they have

to sell that stock to someone else.

Otherwise it's just on paper. So who's

the buyer for that? Is it is it retail?

Is it

you know, what

you've got to make a a business case in

the public market that can show that

this business is worth a discounted

value of its future cash flows. And so

whether it's SpaceX or Anthropic or so

forth, like can that case be made? We'll

see six months after or so. I know

they're playing with the

with the lockups to kind of drag that

out, but we'll we'll see what the public

market thinks of that.

>> Okay,

so we have we have this one set of

companies

and then there's everything else. What

do you like in the everything else

bucket as a venture investor?

>> So so I'm going to make an analogy to

the gaming industry. We all I get asked

and we all think about, "Well, what does

the future look like, you know, when

when AI is everywhere?" And and there's

doomers on one side and utopians

>> Zork?

>> on the other. That's Zork. I'm going to

get to that. Just just give me Bear with

me 30 seconds. It's probably not as bad

or as great as everyone says. So, let's

look at the gaming industry. So, I used

to play this game, Zork. There's one

called Planetfall back in the '80s. And

it was very brittle. It was turn

response, turn response. Grab the lamp.

Oh, I didn't It's a lantern. I should

have said lantern. Go north. And and you

wait for the computer to respond. Let's

show the most sophisticated retail

available AI system out there today on

the next slide. And tell me how

different it looks. So, so what what's

happened to the gaming industry from the

'80s to today is going to happen in AI,

but in the next like five years. So,

that will be compressed in terms of how

quickly that change happens. But, we

would all agree games are better today

than they were then. They're photo

realistic. You can like inhabit them.

And they're they're they're moving very

quickly. On the AI side, there'll be

ambient computing. There'll be uh

The problems that Zork had will be

solved for AI. Lack of memory, lack of

consistency, session resets, and and so

forth. How did we get there? You have To

answer your question,

I don't plan on investing in kind of

larger models, right? Just like wasn't

uh better stories that would make better

games. It was controllers and physics

engines and GPUs and and those are the

parts of the AI uh cycle that I'm

interested in, which is which is all the

platforms that need to be built to

>> machinery.

>> You're correct. That is going to make

this reality real in the next five

years. And it's not just bigger models.

I think we're at the Atari command line

stage of of AI. And we're going to get

to the, you know, PlayStation 10 stage

in the next five years.

>> You uh you also used to do a a of stuff

in life sciences.

>> Yeah.

>> Um not as much anymore.

Yeah.

>> My interest in life science, I founded

Calico and been very interested in that

space and we were investors in Flatiron

uh and Veer and lots of other companies.

Uh I'm very interested in that space

because it has a dual benefit of helping

people and also do good, do well.

>> Correct. However, uh the uh the

therapeutic space that requires human

clinical trials is a specialist

investment area that uh

we're not uh spending a lot of time on.

I'm very interested in computational

biology and and and those areas, which

is

>> if you just look on X that there's a

renaissance happening in human health.

I don't know if that's true, whether

it's cures for pancreatic cancer, cancer

vaccines, peptides, obviously. There's

just an explosion and a lot of it seems

to come back to computation.

Um

but this class of winners so far is not

really computationally driven. It was

just really good science 10 years ago.

>> Yeah.

>> And so do you think that we're about to

see this massive

>> I hope so. So I started Calico and and

again it was like fringe science

longevity at the time. And now we're

investors in uh um New Limit, which is

Blake Byers and uh and Brian Armstrong's

company and a number of other companies

in that space, which doesn't seem so

crazy anymore. However, because of the

human biology and the FDA, if you find a

compound and you think you've got

something, that's like 5% of the work.

We there's still all kinds of titrating

and safety testing that needs to go on.

And so I don't think it's going to go

quite as exponential as we would all

like it to. However, if we can achieve a

realistic simulation of a human cell in

silico, then you will see that

accelerate as well. We're not quite

there yet.

>> But generally we're seeing some might

say a flight of capital to India and

China right now. Are you seeing that

that their biotech path to market is

faster if you invest in firms that are

based offshore versus the US.

>> has always um uh

indexed on human safety over speed to

market, and that has cost us in some

ways. However,

some other countries are indexed in the

opposite direction, which costs lives in

that. So, there's a balance there, uh

but there are certainly

there's research going on in China and

other places, experiments in cloning and

all sorts of things that that as far as

I know aren't happening here. Uh so,

yes, and I think the gutting of the CDC

and the NIH and and anti-science

vibe that has now pervades this country

has driven a lot of mind share elsewhere

as funding is drying up for basic

research.

>> China's got their own paper clip model

now. They're recruiting some of the best

scientists from Europe and India, and

they're all emigrating to China

>> Yeah.

>> to go do work, and that used to be a

scientific pool that we used to access,

and we used to recruit.

>> And we're losing We really need the the

the neurological reserves here.

Uh and this business with

>> Or brain trust would be another way to

say that, but yeah.

>> well. But the the H-

the the the pushing out of H1B holders

like there's so much happening now that

it's causing it's just easier to go

elsewhere. That's not good for science.

>> What's your view on what's been called

deep tech for the last decade? These

traditionally long investment cycle,

capital intensive, high-risk like Elon

is one of the few entrepreneurs that has

successfully tackled uh deep tech

business model with SpaceX and Tesla. Is

this becoming a more tractable area for

entrepreneurs to activate and for

investors to invest in because of AI

enablement and physics engines and

>> Absolutely, cuz things are moving so

much faster. What

>> like that are you focused on investing

in?

>> I mean human biology and healthcare

that's probably the largest TAM in the

world. So super interested in that. And

then all of the others I I mentioned

that kind of underlay

the AI revolution which are the the

physics engines and the controllers and

the GPUs and the everything that is

going to take to to get us there.

>> I want to

bring I want to bring Sax and Freeburg

before we run out of time if it's

possible. Sax

I'm curious your thoughts on the venture

capital business. I think you've did

five craft funds or four?

>> Well, we've done four venture and two

growth.

>> I'm assuming you're going to be going

back into the venture business. But I'm

curious your take on when you started in

venture and when we started as

entrepreneurs 25 30 years ago, this was

a much different playing field. What are

your plans based on you know sort of

Bill's

um look at this and do you believe in

the $500 million fund sweet spot or do

you think you need to become Andreessen

Horowitz when you go back to the private

sector?

>> Well, I don't I don't think we need to

become Andreessen Horowitz um but um

you know, I I look I think fund size

determines fund strategy.

And the size of your fund cuz you're

going to divide your fund size by 20 to

25 names to achieve some

portfolio diversification and

construction. That'll determine your

check size and that sort of determines

where you play in the market.

The thing that's spinning through my

head after Tom's presentation

is you know, are you better off just

focusing on you know, let's call it what

used to be called I don't know late

venture early growth. You know, you're

writing $50 million checks. You just

kind of wait for the breakouts as

opposed to playing in this really noisy

super early stage game. Well, I think

the problem

with that is we have to look at the

incentive structure of venture. So a

$5 billion venture fund that returns

1.01 X gets to say that they are in the

75th percentile and can raise their next

fund, and no one at the Stanford

endowment is going to get in trouble for

writing that check. They need to put two

or 500 million into a fund multiple

times.

So, so I understand that dynamic. So,

now let's look at the GP dynamic. Well,

if I have a $5 billion fund, I return

1.01 X, I'm going to make more money

than Bill with his $500 million fund

that returns 3 X.

Okay? So, that's also a strange

incentive. So, now let's look at the

entrepreneur side. I am researcher X

from Open AI. I'm going to start a

company.

Bill says, "I'll give you $20 million at

a $100 million valuation. I want to buy

20% of your company."

Giant fund Y, we're friends, it's a

different model, but giant fund Y says,

"Well, we have this giant fund. We need

to put 250 million in."

And then an entrepreneur says, "Well,

but my company's valuation is 100." No,

your valuation is now 4 billion. And

we'll give you 250 million for a percent

of your company.

They're going to take that deal every

day.

Unless you're a seasoned entrepreneur

who has kind of been down the road and

knows the pitfalls of that. And so, the

incentives are broken in all those ways,

and the pendulum will swing back. So, I

don't think just staying late stage and

waiting to snipe her at larger companies

will be a long-term The The data would

suggest that's not going to work in the

long term.

>> Okay, let's thank Bill. Amazing job.

>> Thank you.

Thanks, Bill.

>> [music]

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