Bill Maris: How Google Could Crush AI Competitors, Why Small Funds Win, and AI's Atari Stage

The founding CEO of Google Ventures has raised $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 an investment financial return. Any other metric is impossible to measure and therefore wants to see. Think of the change that 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 is going to change by words 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 GoogleX, Calico, and many other projects as well. Before that, I founded a web hosting at Data Center Company, which we're going to talk a little

“bit about. 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 at a degree at neuroscience. I found myself on Wall Street, somehow managed to land a job there,

but I was miserable having to wear a suit and tries 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 what is this thing beneath our jackets and they said, well, that's where our email and websites live and as can happen to many of us, I had a moment where I felt like I was bathed in the light of inspiration and I thought, I think I've glimpsed the future. 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 because I had glimpsed through a keyhole and through the 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 something like this or something like this. But in 1997, a state-of-the-art data center looked almost exactly like this. We had three servers, a small medium and large business group, we eventually had five servers and this

isn't a data center, 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 my noon, if you had a glass of water in your desk, it would ice over. You may think though, this isn't so bad 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 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 leaking the landlord said well that happens sometimes but I knew that I needed to do something.

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 tar 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 tard 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, new flash I survived my shoes though are still stuck on that roof in Vermont which takes me to lesson two which is to see the future sometimes you need to be a little bit insane. It may appear to those around you that you are tarring the roof in a thunder storm

and to that point I'm going to share a few slides here that a friend named Stuart Butterfield was kind enough to share with me and here's the inauguration 1989 and there's someone taking a picture. That

there taking a picture and then let's go just four years later 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 our 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 two his friends I'm sure seemed insane who also did glimpse the future and we like closely this gentleman decided to I don't know live stream or record the inauguration

is laptop he knew something that those around him didn't know which is one of the things that I've

“always looked for on 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 a Google and a challenge was given to me the challenge was Google needs a vendor fund we were starting to make some investments we didn't

have a coherent strategy there were no budgets I had to figure out what to do so I first found a

friend rich minor is the co-founder of Android and he became my partner in crime as we conceptualized what what could Google ventures be 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 you to see what we what we could learn we came up with the 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 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 science fiction it is it's 100 years away if it's ever going to happen let's stick to machine learning by the way when you say AI it freaks people out so stop freaking people out 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 to determine what the ideal fund size would be and people were excited here's a headline from tech crunch at the time and and people at 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 2019 2018 top quartile VC returns look like this and top desk I look like this using publicly available information I'm not sharing any non-public proprietary Google information we would estimate Google ventures returns at about four point one X and I adhered more closely to the strategy and the investments that I led and the investments that I led turned out like this which takes me to less than 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 and 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

bunches free and the massages are a plenty and so forth but after the idea you know sunk in I advice sharing it to raises much money as possible you know that's the right way to run it fun 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 do 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 desk aisle

and to the extent there is DPI to measure that's the only measure as far as I'm concerned in venture that counts as DPI which takes me to lesson four that this would 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 that you can have more

employees it's distracting you cannot give the attention to founders that I would like to give it there are many reasons for this and if we look at top desk aisle performance of DPI fund smaller

than 750 million average return of 4.76 and funds larger than a billion 2.42X funds below 750 million

across that time period represented 95% of top desk aisle 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 we'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 75% off venture loses money

and there is persistence of performance of the top quartile so if you need 5 billion to get your

“money back and and if you want to be in this business for a 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 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 times 3x is 210 billion which exceeds the total venture back them in an IPO exit value in most years this year may be an exception but 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 bills for lessons for today I hope that there's 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 we'll build when he started Google Ventures I was the first ex-Google company you invested in that's correct and how did he go

“climate court a billion dollars it's a month ago what was your multiple what was the return”

oh I don't know it was actually good for you guys it was quite good yeah you guys were in the BMS yeah and we went billion dollars was a lot of money then that back then that was a good deal that would have been nowadays how would have been this round now it's like an A round yeah that would have been A round now we're going to do it again with a hollow now we're going to do it again with a hollow 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 billion to 100 and 100 to a trillion

“trillion to whatever 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 three extra terms 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 ongoing trend other than

this one moment this weird moment in time with these multi kind of trillion dollar exits that are coming one that there would be kind of observation one two 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 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 an observation that a a a bit of an objection to companies that wrap themselves up in public benefit language and then keep the value creation 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 what would humanity needs as money so if 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 percent 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 yeah what does well well if you're a company and you can go to Google and Gemini

and you can pay 80 percent less for that basically identical product why wouldn't you do that

what if you don't say that you've fallen that might happen if I were Google that's what I do

“walk us through this 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 may be burning investor cash sort of like an Uber type model grab market share grow 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 that's 100 percent

possible it's a problem I'll just it's been said before a trillion four spend commitments on sixty 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 us about companies staying private longer”

and how unfair that is to the bottom half of society who don't get to participate and speak for those nine nine percent who are mostly not us right so so you're for all you know those 401ks those retirement plans to get into those companies now which are getting bizarre exceptions to S&P 500 rules that all of the rules are being broken the passive funds the 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

three extra here sure but they so the just to say it as plainly as possible we're going to force

over price products on the 401k holders of America who didn't get to participate early this is your position that this is profiting especially creates more wealth creation for the people who don't need it and it makes the people's retire cards the back holder 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 this a public's retirement accounts the back holders or just say this is how

we're running our business and this isn't for the benefit of humanity build 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 to 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 and there'll be a few year 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 ventures going to look incredible if you look past the averages ventures still going to look extremely buy-mobile a handful of winners and a

“ton of losers how does that play up I mean one that's how venture is right seventy five”

percent of funds lose money but two in order for founders fund or it may 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 you you've got to make a business case in the public market that can show that this business is worth this kind of 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 uh uh with the lock-ups to kind of drag that out but we'll see what the public market thinks of that okay bait 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 so I'm going to make an analogy to the gaming industry we all are again asked and we all think about well what is the

future look like you know when when I AI is everywhere and and there's tumors on one side and YouTube is a fork on the other that's the work I'm going to get to that just this is going to be barely thirty 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 planet fall back in the 80s and it was very brittle it was turn response turn response grab the lamp oh 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 their photo

realistic you can like inhabit them and they're they're they're moving very quickly on the AI side

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 it wasn't better stories that would make better games it was controllers and physics engines and GPUs and and those are the parts of the AI cycle that I'm interested in which is which is all the platforms that need to be built machinery you 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”

AI and we're going to get to the you know PlayStation 10 stage in the next five years you you also used to do a lot of stuff in life sciences yeah not as much anymore my interested in life

science I found a calico and been very interested in that space and we were investors in flat iron

and veer and lots of other companies I'm very interested in that space because it is a dual benefit of helping people and also the dual correct however the the therapeutic space that requires human clinical trials is a specialist investment area that we're not spending a lot of time on I'm very interested in computational biology and in those areas which it seems if you just look on X that there's a random sense 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 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 again it was like fringe science longevity at the time and now we're investors in new limit which is Blake buyers and and Brian Armstrong's company and a number of other companies and 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 with 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 the biotech path to market is faster if you invest in firms that are based offshore

fronts the US has always 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 and that so there's a balance there but there's certainly there's research going on in China and other places experiments and cloning and all sorts of things that that as far as I know aren't happening here so

“yes and I think the gutting of the CDC and the NIH and the anti science vibe that has now”

pervades this country has driven a lot of mine share elsewhere as funding is drying up for basic research I mean China's got their own paperclip model now they're recruiting some of the best scientists from Europe and India and they're all emigrating to China to go do work and that used to be a scientific pool that we used to access and we used to recruit we believe we really need the the the neurological reserves here and this business with or brain trust we'd another way to say this

that as well but the the the the the the the pushing out of HMB holder there's so much happening now it is causing it's just easier to go elsewhere that's not good for 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 have successfully tackled 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 because things are moving so much what what areas like that are you focused on investing in I mean here in all biology and health care it's probably the largest term 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

Saxon freeberg before we run out of time if it's possible. Saxon I'm curious your thoughts on the venture capital business I think you did five craft funds or four. Well we've done four venture and two growth. Missuming 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 bills look at this and do you believe in the $500 million fund suite spot or do you

“think you need to become injuries in horror which when you go back to the private sector?”

Well I don't think we need to become injuries in horror widths but you know I look I think fund size determines fund strategy and the size of your fund because you're going to divide your fund size by 20 to 25 names to achieve some portfolio diversification and construction they'll determine your check size and that's sort of determines where you play in the market. The thing that's spinning through my head after Thomas's presentation is you know are you

better off just focusing on you know let's call it what you speak called I don't know late venture

early growth you know you're writing $50 million checks you just kind of wait for the breakout

“stocks as opposed to playing in this really noisy super early stage game 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 1.01x gets to say that they're in the 75th percentile and can raise their next fund and no one at the Stanford and dominant 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 1.01x I'm going to make more money

“than bill with his 500 million dollar fund that returns 3x okay so that's also a strange incentive”

so now let's look at the youngs per nurse 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 or 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 entrepreneurs says well 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 of waiting to sniper at larger companies will be a long term the data would suggest that's not going to work in the long term okay let's thank Bill amazing job great you're still thank