The IPO Comeback: Why Tech Giants Are Finally Going Public | All-In Liquidity IPO Panel

- The AI-IPO of the year so far.

- That company is to re-risk. - Through the systems founder and CEO and development. - We are participating in something extraordinary. - On everything we do, we are the fastest bar none. - Well Marshall, is the co-founder and CEO.

- Oh, I had a blast. - Space and AI are really a match made in heaven. They're getting married in fact. - Just like Google figured out how to index the internet and make it searchable.

We are indexing the earth and making it searchable. - He's got his glasses, the famous red glasses, Brad Gersoners here, founder and CEO of a similar capital, a leading tech investment firm.

“- I believe that the wave is the biggest wave”

in the history of technology will be incredibly beneficial for America. I'm rooting for all of them because I'm rooting for America. - Ladies and gentlemen, please welcome

Brad Gersoner, Will Marshall and Andrew Feldman.

(upbeat music) - That's time I saw you were in Davos? - Yes, we were in Davos. - Cause they're trouble. - That they're trouble?

- Another J-Cell, do you know that little Davos you know? - I was pre-IPO, we're chopping it up. - It's Davos. - We're in Davos. - We're in Davos.

- Well, no, listen, I was everybody in those stories. I'm supposed to go on my yearly Japan ski trip. - Sachs calls me. - With Tucker. - Yeah, well anyway, we don't drop that name,

but I'll pick it up for you to put it over here. So, I can't sell on Tucker. I can't excuse him because Sachs calls me and says, listen, "Potus needs you,

"the world's greatest moderator in Davos."

- Yeah. - But you'll probably know. - I said Sachs, "Potus in Davos." - So, I said when he says in three days, I say, "You got it."

- I go and it gives me a badge and it's like the special green badge and they buzz you through the security. And I look at the monitor and it says, "Jace and McCabe, Calacanis,

"with Donald J. Trump." - Oh, wow, how did you feel? I don't know if it was hilarious. So then I went and we did a great interview there and we did like six or seven of these great

all-in interviews and it was fun. - Let's start this because the two of you guys run two of the most interesting and consequential, newly public companies in the stock market. Andrew Falmond is a founder and CEO

of three bristful marshals of founder and CEO planet labs, but you are also the insight and a gateway for all of us to understand these two big trends. One is in AI silicon. The other one is in space data centers.

“I think it would be a really interesting thing too.”

- And then merging. - And emerging. - Yeah. But let's just take one step back. You just heard the class conversation

about being public going public early. Let's just talk about that 'cause I'm just very curious. How's it been? It's been three weeks or so for you. It's been about a year and a half or two years for you.

- It's more fresh for you. - Was it everything that you thought it would be? - Well, what's clear so far as I need to upgrade my name drop game. I mean, that was a tour to force.

- Yeah. - But by the way, you were in Davos with Jake Owl. - I was there, but that. - Tour to force. Look, I think you do all this work.

And I think it's really difficult to overestimate the amount of garbage that's involved in going public, the number of meetings where you look on the Zoom and there are 130 attendees and the amount of times you review these documents

and the commas move and just know values at it. You go there and you have this enormous event. And the next morning you've sold no more stuff. Your engineering projects have made no progress since the day you weren't public.

And you go back to work. And you have some new constituents

“that you have to address and communicate with.”

But the core parts of your business, you have more money in the bank, but not a damn thing changes. In the important parts of your business, if you need new supply or if your relationships

with your vendors are bad, they're still bad, if they're good, they're still good. And so I think what we've seen is your employees have a party, everybody's really excited. Put your head back down, you're high five

and you go back to work. - Can I just give a little context and then when you hear from Will? You know, if I can, Andrew, you know, we were investors in Serebris. I was on the board a year earlier

where we were trying to go public. And you know, aside from just being a warrior who weathered a decade worth of storms that would have taken out any normal human being,

was a particularly challenging one.

One of their investors was the UAE, so there was questions about Sifius, you know, in the prior under the Biden administration, challenging to get public. My observation outside looking in is everything was really hard

until it got really easy. Like nine and a half years of really hard and then 12 months, you know, of really easy where everybody wanted to get in, they priced the IPO at 185

which was up, the range was taken up two times.

“Okay, the stock opened at $320 a share I think.”

Today, it's at $230 a share, 50, $60 billion in market cap. For a business like, you know, and Andrew is just one of these people, let's get back to work in build shit.

But my, my just add on question to that is, from an employee morale perspective, like distraction perspective, et cetera, has the last three weeks, you got a lot more capital, you got a lot more profile, presumably it's easier

to sell to enterprise customers today. Net net, if you were advising me if I was in a similar position, would you say go public? - I think the first thing is a lot of people asked us

about how we got the timing right. - Right.

- And I think the answer is by getting it wrong for a decade.

That's really the right way to get timing right. I think first, I, we've been at this for more than a decade and we, we brought everybody who'd been with the company more than nine years to share and we brought their families. And first, I learned that engineers owned ties.

I didn't actually know that (laughs) and they didn't die when they wore them. And second, I was surprised at how big a deal it was for them and their family. They were really proud in a way that sort of their parents

might have heard of it or that somehow this was like, a bar mitzvah or a kinsenera or something. And then you, you had these sort of, the children of immigrants. One of our, one of our leaders, her father,

Chinese immigrants said, I thought it would have happened faster. (laughs) - That's right. - Right.

“- And, but I think we are sort of by nature”

sort of in the, in the trenches people. And so we love solving hard problems and so when, when we had this excitement, everybody won, they were so excited and we had a party and I think it, it gave external validation and then everybody turned around

and said, now what are we now back to work? And so I, I think. - And so you started off kind of bang right out of the gates. Well, you had a little bit different experience in terms of, you know, the entry to the public markets.

But over the last 12 months, your stock has gone from five bucks a share to 50 bucks a share. Some 10x move in the public markets. So talk us through the other side of this where you come public, nobody really notices

until they notice.

- Well, we were on the first space stocks

and I think people just had no idea. - No, no idea. - Earth is going on in space. How it was changing everything and they were just like, what the heck is that and, but you know,

I have similar opinions, I mean, in the end, you've just got to get on with executing the business. The government public gives you access to liquidity

“for early shareholders, whether that's the important early employees”

or early investors and that's great. It gives you cash for the company, that's great. And I do think it helps your business as well because the maturing event gives you more credibility to various customer.

And for us, we work with biggest agricultural customers, big government, civil governments, defense and intelligence, all of those sort of actors. They want to know you're going to be around. - Exactly.

- And not going to disappear. I mean, we have countries that fully dependent on us giving them information. They don't want to just disappear. So they really care that we're going to be around

and being a public company gives you the kind of force in the world that people go, okay, you're here to stay and you have access to capital if you need it and so on. - We're generalizing. And you know, where the stock is at any one day,

we're not focused on that day to day. We're focused on how we build long-term values for our shareholders, right? And the market is, I think, started to really understand where space is going.

Why it is changing the world? People forget how space is part of your everyday life. Every time you use a phone, you're using communications, using satellites or GPS, using satellites or satellite data

in some way or another, it's sort of intricate in your lives. You may not realize it.

- And the story's changed as well. Obviously, with SpaceX going public, but has the framing of planet gone from like a data source for people who need data from space and maps to, hey, this is a tool to accomplish tasks

and military, like post-andreal success. Like, you probably would have been bucketed into androlytes a military tech company. So is that framing what's driving a lot of--

“- Well, I think it's a bit more nuanced than that.”

I mean, firstly, for the audience is benefit. What planet does we have satellites doing earth imaging? We have the largest earth imaging fleet about 200 satellites, the entire earth everyday. So think about the Google satellite layout on Google Maps

that you can look at, except these today's date, rather than three years old. And we have every day going back. So it's a time series analysis of everything going on on the earth.

That's useful for farmers, it's useful for energy companies, it's useful for civil governments, for flooding and fires, it's useful for security applications, like you're getting at, and it's a wide variety of use cases. I think that where we're seeing this is that AI is now

enabling the-- it's basically reducing the barrier

to entry so that more people can get access to this, right? And, you know, there's a lot more to say on that, but AI is only as good as the data. - What can I do? - What percentage is military? I'm curious.

“- So, what percentage of revenue customer is about?”

- 60% of our revenue today, security is part of the initial thing that we said we would do at the gate, but it's true, there's a big a fraction today than perhaps we would have guessed. But the needs of the geopolitical situation right now,

demand what we're doing, you know, just as an example, what this does is enable them to see threats around the corner. - Yes. - And then, you know, give them weeks or months of vans warning of things,

and then that enables them to more likely do things that stop conflict. So, we believe this is, you know, really better for the world. - Are you ready to be perceived as a military company? - Not really, but I wouldn't say we're limited

to being perceived like that, right? We are helping farmers, we are helping, you know, energy companies, civil governments, we work with NASA, we work with what have you. And so, it's a bigger, it's a bigger play than that,

but back to the space piece of it, what has changed, obviously, rocket loss have come down about four or five X over the last 10 years, which has helped tremendously. But the thing that people don't know

that is actually perhaps more important is that we've had a miniaturization of satellites

so that the same satellite that used to cost a billion dollars

on way 20 tons, now costs a few kilograms or a few tens or hundreds of kilograms, and can do just as much stuff, if not more. It's the same as the sort of mainframe computer to desktop revolution for space

and it's unlocking, just like mainframes to desktop, unlock loads of applications. This is unlocking loads of applications, and it's, so both go in combo, the launch cost coming down and this.

- Let's build on this. - Let's build on this.

“- So I think I'd like first to you maybe take a few minutes”

and then I wanna talk to Andrew the same question. Both of you guys are at the foot of what are probably huge secular trends in technology. How I would frame this is we are rebuilding the data processing infrastructure

that has existed on the earth in the sky. And first you do the satellites, but I would love for you to explain space space data centers because I think everybody's hearing about that. Are they really viable, what are they,

how will they work, et cetera? And then Andrew, this is the rebirth of silicon. We're gonna find the next version of Moore's Law, which I think is more time-bounded, not transistor, density-bounded.

We now hear a lot about domain-specific architectures. We hear, I mean, your chip was just a complete transformation in terms of the design principles that, you know, I could grow up, we took a very different approach and videos taken a very different approach.

You took a big piece of shape dye and said, fuck it, y'all, oh, this is it, and you were right, just explain where we're going in silicon. So maybe we'll you start and then Andrew you start. - I mean, what we're seeing firstly in space

is all these new applications based on data and AI. So, you know, we're collecting vastly more data about the planet and with SpaceX and Starlink and OneWeb, they're transporting far more data around the planet. As you say, we're sort of changing the nature of data

using satellites and that's basically doing what was once the province of government's only in giving everyone else access to satellite capabilities.

And that's gonna, I mean, I estimate there's 75 to 100 billion

on market just on earth observation that's kind of data we collect and AI on top of that unleashing all that applications.

to earth imagery data unlocking agriculture, you know,

energy, servo government applications, permitting, you name it, this is gonna make everything more efficient. And then where we're going is indeed space is, we did a study with our partners at Google about eight or nine years ago, looking at what are the costs of data centers

on the ground, what are the costs that it would take to put them in space? And when might it make sense to do it non-touristually? And we figured out that when launch costs come down to about $200, $300 a kilogram, it would be cheaper, just simply cheaper

to put the data centers in space. Now we're about $1,000 a kilogram just over that in right today, but that's come down about 10x in the last 10 years. On the current trajectory with Starship in particular, I would expect the launch costs come down there in two or three years.

Elon might say it's next week, but at least realistically, a couple of years.

So we're not far away from it literally just being cheaper.

Then in addition, and the intuition there that helps people understand that is you would naturally use solar panels for doing the data centers there are power problem. And it's a power game. And you would normally use solar panels,

that's the cheapest way to get a watt today by far, but you don't want intimate and power.

“So then you have batteries, or you then you have to have gas,”

or then you have to have nuclear, and then they get really expensive. In space, you can put a solar panel in a sun synchronous, a dawn dusk orbit, where you're 24/7 looking at the sun. So you can have a solar panel that clicks and get us five times

more energy per solar panel than on the ground. And you don't have to have batteries or anything else. So the infrastructure for compute in space is literally just solar panels and the chips, and then the RF signals up and down.

So it's actually really quite simple. It was just a question of when it's going to be cheaper to launch all those solar panels and chips in a space than putting it on the ground. And it turns out that's going to be in a few years.

So we're partnering with Google to launch some of their TPUs into space. We've already launched some of Nvidia's GPUs into space. We're launching Google's TPUs into space on an early test. There's lots of technology.

You want to watch the figure out? Let's have a conversation. But it's an early days, but I think no question within 10 years, most compute will be put in in space, which to give you a sense is a lot of money, like trillions,

and will be bigger than any of the other space businesses today. Come, come, thymaging. This is why we're getting into this game. And thirdly, believe sending data centers to space makes more sense.

Or is it just the regular--

“That can you have to explain the business first, then?”

Oh, yeah, of course. So I think there, with all the viewers, what are two hard problems still left beyond putting GPUs in space right now? Yeah, I think.

We're not super good yet at building the clusters in space. That's a theory for the communication between-- Exactly between-- Yeah, we're not going to do it on the ground. We're not going to do it on the ground.

We're really not going to do it in space. I think it's an extraordinarily important and interesting problem. And one, we should be spending money and attacking. I've got it at a slightly different time frame,

but one that certainly will occur. And the hard part is, is it-- is it one of those problems where the last 10% is 80% of the time? Now self-driving was a problem like that, right? Where the last 10% proved to be a decade's worth of work.

And just now we're over the hump. And we don't know yet.

“But I think the interesting work they're doing at planet”

is really important. And I think the fundamental driver day experiments to even get insight into whether I'm right or not is to get down the cost of launch vehicles. Then you can start doing experiments and getting it wrong

and fixing it and figuring it out. And until then, it was totally on paper. The foreseeable future you're going to be terrestrial, explain your business and how you

made these critical decisions that kind of took you

on a different path. And you versus in video versus AMD and what you think the future of AI silicon looks like. I think there were two parts here. Your first question was around the rise of silicon in general.

And I think what AI did and it's rarely framed this way. But it allowed computers to address a class of problems that before AI computers were bad at. We were bad at images for almost the entire history

We could store them and that's about it.

We were bad at the language. We could store it, but that's about it. We could transform numbers. We were magical with numbers.

“And what AI did starting in about 2015-16”

is it opened the door or the aperture to say, maybe we could use computers on images. All right, maybe we could find insight in images. Maybe not only could we store language, but we could generate it.

Maybe we could understand it rather than storing it and regrigitating it. And what this did is it opened up sort of two compute. Huge areas that were previously foreclosed. And at the same time, we were adding to those areas.

We were taking vastly more images. All right, to restually, in satellites. And what this did is it simultaneously opened up this entire area and allowed compute to attack it. And this is what's underpinning both

Nvidia's growth and sort of all the growth you're hearing about in AI compute as a processor builders, a hardware builder, suddenly our tools could attack more in different parts of knowledge.

And that was sort of the first part to answer your question.

Now, how you do that? There are lots of different strategies. It tons of different ways to skin cats. What we saw in 2015 were several things. First, we saw that AI would be an enormous consumer of compute.

All right, and historically, for computer architects, new workloads were the opportunity for shared a change. Share changed when the rise of graphics emerged.

“And you got the dedicated GPU that's how”

Nvidia was born. Share changed when cell phone compute emerged and Intel and AMD who had fabs and the best architects got zero share. And it all moved to ARM, right?

Share changed in the late '90s when nor tell in all these companies we've forgotten about couldn't build chips and couldn't do a data networking. And what you got was Cisco and Juniper and a risk to this collection of new companies.

So we knew that this new problem would present an opportunity for massive change. So we saw that. We made two bets.

The first was dedicated silicon would be the answer.

And the second was it couldn't look like a GPU. And our view as computer architects is if you want to be 20 times better than somebody, right? Your architecture can't look like them, right? It can't.

They have enjoyed and eaten all the low hanging fruit. So if you build a GPU, the odds that you're better than Nvidia and R of your approximately zero, that led us to a fundamentally different architecture. All right?

The hard part here, the hard part is moving data from memory to compute. This is the fundamental problem in AI. And we solved it with a way that very few others had even attempted, which was to build a very big chip

and to put memory right next to compute. By building a big chip, a chip the size of a dinner plate whereas most chips are the size of a postage stamp. We could use a different type of memory. And by using a different type of memory, a memory

that was vastly faster, we opened up all sorts of opportunity. So when open AI uses us, we're 15 or 18 times faster than a GPU, right? That means your answers are delivered more quickly. It means you're engagement with the AI as more enjoyable.

It means you can use the AI to solve harder problems and not wait. And the way to think about this is sort of to ask yourself that the counterfactual questioning. How big is the market for slow search today, right?

Is zero. How big is the market for dial-up? It's zero. How long do you wait for a website to resolve before you click away?

Three seconds, five said, you will not wait for AI. We have to deliver it to you in real time.

“And that's what we saw, that's what we built.”

So the panels on going public, a lot of LPs in the room, they need to get liquid. I'm curious about the journey for your investors. OK, so well, you guys went public what year? 2021.

2021, by way of a SPAC, and your VCs were who?

in Capricorn, PDTO's Founders Fund, then we go, Yuri Melner's DS2. OK, so you're the investor's come in.

You go public at $2 billion via a SPAC.

Now, we're four years later. Really, it wasn't until year three or four that 90% of the value was created. OK, so did those early investors capture this? Yeah.

90% moved, did they stay in it? Most of them did. OK, most of them did, which is really smart on that, obviously. I think they should hold on, if I didn't think that. Well, I mean, what would have been self-interest?

“Well, that's what's interesting about this.”

But it really did, and Google hasn't sold a share. They're a larger single investor. Capricorn didn't, until very recently, so they basically most of them stayed really well in, and they got all of that upside and good for them.

And the real thing is, this is so important. Is there a lot of LPs in this room that they're like, when a company goes public-- Yeah, this shares. No, no, no, no.

Give us the given shares. This is a counter-example, right? This happened to us in Mongo 10 years ago.

We invested pre-IPO at a billion dollars.

We distributed the shares, I think, at three or four billion. And then it went to 50 billion over, you know, the course of the next 24 months, and we have people called us who said, well, why didn't you hold on to the shares? And we're like, because you're pounding on us, right?

It's not distributed to the shares. So you're an example.

“No, in your case, Andrew, you have an innovation, right?”

You're just now a public. So all of your investors are still under lock-up, like, like, all timeter. But you guys have innovated with the banks on what I call a dribble lock-up.

So over six months, the shares can be dribbled out according to a bunch of performance hurdles, which SpaceX is going to have a very similar-- Well, when did we start this process of the dribble? The dribble?

[LAUGHTER] Conceal started it years ago, but-- Yes, but we're all of that. With respect to the lock-up, I think this is the most innovative. And I think SpaceX is going to have a very similar innovation.

But Andrew, for your investors-- if you were talking to my LPs, right, in the room-- should all timeter be distributed in the shares when they come out of lock? How do you think about your VCs holding onto the shares

kind of post-lock? I think historically, more money's made after I peeled them before.

“I think every single study shows that there's more money”

to be made, both in percentage and in what we care about, which is absolute. Yes. And so the amount of money that it's possible to put to work in most venture companies is very modest.

I mean, there are two or three or five outliers. But for the most part, you can only put a relatively little bit of money to work. By the time we get public, there's a lot more money there. Things are going well.

And the opportunity to make vastly more is after I peeled not before. If I could just add on that, it one interesting question is what's going to happen with SpaceX on this, because a lot of the value is in the future, right?

But I mean, most of the big tech companies

when public get a few billion, not a few trillion.

There's a lot of zeros in between those, right? And you've got all this upside afterwards. Now, for the equivalent lift off, SpaceX would have to be aiming at quadrillion dollar valuations. Now, I know Elon has those sort of ambitions,

but you really have to believe in that to get-- this is kind of the point I'm getting to. Right? We have three mega IPOs that we're talking about that are multi-trillion.

All of that value accrued to private market investors. And it labs is a great example of venture capital in the public markets where the 10X has occurred in the public markets. We're all advocates of these companies coming in public sooner.

Had Andrew had his way, he would have been public 18 months ago, probably, at $10 billion rather than $50 billion. And that five X over the course of last two years would have gone to public market investors. So go ahead.

Way better to be lucky than good. So I think that I hear a lot of people thinking that anthropic open AI and SpaceX are the new normal. I actually think the public markets-- I totally go back in this direction.

And a lot of the companies in our portfolios are now thinking about going public at $1 billion or $3 billion, or $5 billion. We had this period of a decade where in Driesen was really pushing state private forever.

And I see the pendulum swinging back to companies are like, man, I want to be like planet labs and get public and have to play in the big leagues

So here's what I'll say, maybe just like to the two of you guys.

Both of you guys have had enormous pressure, because there's visible competition that's always sort of in your periphery. But I do think that getting public sooner, having the scrutiny of public markets,

having the scrutiny of having to deliver sharpens the focus, it's still sharpens steel. Iron, sharpens iron.

“And I think innovation tends to get better.”

And so the idea that you allow everybody to participate, but you also put yourself in the spotlight to me is where great things happen. - I agree. - And so anyways, I just wanted to say to both of you,

just as we were up,

you guys are in incredible testament to entrepreneurship,

both of you. I mean, we've been talking literally since day one, me and Andrew, because we went in different paths and then we kind of reconversed and then we'll same with you.

- How many have you worked out for you? - Well, it's worked out for both of us, so it's fine. You guys are in incredible testament to entrepreneurship. And I just want to say thank you for everything you guys are doing.

- It's the next few years are gonna be really-- - Well, I see. - Yeah, if I could just spend 30 seconds on the next few years

“because I think it's gonna be so exciting”

with, as I mentioned, AI and space emerging together, we're gonna see a take-off out of applications. I'd say all the cool stuff that we're doing with LLMs now is really based on just a text of the internet being absorbed into these models,

which is incredibly powerful already,

but they don't know shit about the real world. I call them blind, they don't know about that farm field that flood the security situation around the corner. If you give them real world data, then they can answer real world problems.

“And that's gonna open up gazillions of applications”

for these AI models. I call them instead of having large language models, large earth models, or instead of AI planetary intelligence, where you have planetary sense and systems in space, planetary compute systems in space,

and we can disagree or agree on exact timeframe, but I think it's gonna happen. We have, and then that's gonna enable a huge economy, so it's an exciting time in the next few years. - Well, thank you guys very much.

- Well done. (audience applauding) - Okay. (upbeat music) - Thanks buddy. - Thanks buddy.

- Have a good week. - Have a good week. - Great scene, you brought us to that side of the thing.