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

Hey, 2026 could be an all-time record for IPOs.

The AI IPO of the year so far. That company is Cerebras.

Cerebras Systems founder and CEO Andrew Feldman. We are participating in something extraordinary. On everything we do, we are the fastest bar none. Will Marshall is the co-founder and CEO of Planet Labs.

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 such cool. He's got his glasses, the famous red glasses. Brad Gerstner's here, founder and CEO of Altimeter 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 Gerstner, Will Marshall, and Andrew Feldman.

Nice to see you, man.

Hey, last time I saw you, we were in Davos. Yes, we were in Davos.

Another name drop, another J. Cal. Do you know that little Davos?

Yeah, we're just, you know, it was pre-IPO, we're chopping it up.

It's Davos. We're in Davos, hanging out at Davos.

Well, no, it Listen, everybody knows the story. I'm supposed to go on my yearly Japan ski trip. Sachs calls me.

With Tucker?

Yeah, well anyway, don't drop that name, but I'll pick it up for you, put it over here. Anyway, so I cancel on Tucker, I cancel the ski trip because Sachs calls me and says, listen, POTUS needs you, the world's greatest moderator, in Davos.

No problem.

Tucker, Sachs, POTUS, and Davos.

So I said, when? He says, in 3 days. I say, you got it. I go and they give me a badge and it's like the special green badge and they buzz you through the security. And I look at the monitor, it says Jason McCabe Kalacanis with Donald J. Trump.

Oh, wow. How did you feel?

I thought it was hilarious.

So then I went and we did a great interview there and we did like 6 or 7 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 Feldman is the founder and CEO of Cerebras. Will Marshall is the founder and CEO of 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 to— and they're emerging and emerging. Yeah, um, but let's just take one step back. Uh, you just heard the last conversation about being public, going public early. Let's just talk about that because I'm just very curious. How's it been? It's been 3 weeks or so for you. It's been about a year and a half or 2 years for you. Uh, it's more fresh. Was it everything that you thought it would be?

Like, what's clear so far is I need to upgrade my name drop game. I mean, that was a tour de force.

Yeah, but by the way, you were, you were in Davos with Jay Kal.

I was, I was But that, um, uh, look, I, I think you do all this work, and I, I think it's really difficult to, to overestimate the amount of garbage that's involved in, in going public. The number of meetings where you, you look on the, the Zoom and there are 130 attendees, and the amount of times you review these documents and the commas move and, and just no values added. 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, um, you have some new constituents that you have to, to, 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 still— 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, and you put your head back down, you high-five, and you go back to work.

Can I just give a little context and then I want to hear from Will, you know, if I can, Andrew. You know, we were investors in Cerebras. 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, the path to going public for Cerebras was a particularly challenging one. One of their investors was the UAE. So there was questions about CFIUS, 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 9 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 2 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's just one of these people, let's get back to work and build shit.

But my just add-on question to that is, from an employee morale perspective, like distraction perspective, et cetera, has the last 3 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. I mean, that's really the right way to get timing right. I think first, we've been at this for more than a decade, and we brought everybody who'd been with the company more than 9 years to share, and we brought their families. And first, I learned that engineers own ties. I didn't actually know that. 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 quinceañera or something. And then you had these sort of the children of immigrants. One of our leaders, her father, Chinese immigrant, said, "I thought it would've happened faster." Yeah. Right? But I think we are sort of by nature sort of in the trenches people. And so we love solving hard problems. And so when we had this excitement, everybody went and they were so excited and we had a party.

And I think it gave external validation. And then everybody turned around and said, Now what are we— now back to work.

And, and so I, I think, um, and so you, you started off kind of bang right out of the gates. Will, 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 $5 a share to $50 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 one of the first space stocks, and I think people just had no idea. No idea what was going on in space, how it was changing everything. And they were just like, what the heck is that? And, and but, but, you know, I have similar opinions. I mean, in the end, you've just got to get on with executing the business. Going public gives you access to liquidity for early shareholders, whether that's the 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 customers. And for us, we work with biggest agricultural customers, big governments, 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 are 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, 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.

It's legitimizing that.

And, you know, you know where the stock is at any one day. You know, we're not focused on that day to day. We're focused on how we build long-term value for our shareholders. Right. And, you know, the market is, I think, started to really understand where space is going, why it is changing the world. You know, 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 that's sort of integrated in your lives. You may not realize it, but it's just booming now. There's a—

there's a—

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-Anduril success. Like you probably would have been bucketed into Anduril as a military tech company. So is that framing what's driving a lot of—

I think it's a bit more nuanced than that. I mean, firstly, for the audience's benefit, what Planet does, we have satellites doing Earth imaging. We have the largest Earth imaging fleet, about 200 satellites. They image the entire Earth every day. So think of it like the Google satellite layer on Google Maps that you can look at, except it's today's date rather than 3 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, 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 it's trained upon.

What percentage is military? I'm curious. Sorry, what percentage of revenue customer base?

About 60% of our revenue today. Yeah. Security is part of the initial thing that we said we would do. Out of the gate, but it's true there's a bigger 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 advance 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 reticent 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 costs have come down. About 4 or 5x over the last 10 years, which has helped tremendously. But a 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 $1 billion and weigh 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 desktops unlock loads of applications. This is unlocking loads of applications and it's so both go in combo, the launch costs coming down and this.

Let's, let's build on this. So I think I'd like first you maybe take a few minutes and then I want to 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-based data centers because I think everybody's hearing about that. Are they really viable? What are they? How will they work, etc.? And then, Andrew, this is the rebirth of silicon. We're going to 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, like at Groq, we took a very different approach. NVIDIA has taken a very different approach. You took a big pizza-shaped die and said, fuck it, YOLO, this is it. And you were right. Just explain where we're going in silicon.

So maybe, Will, you start and then Andrew, you start.

I mean, what we're seeing firstly in space is, 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 governments only and giving everyone else access to satellite capabilities. And that's going to I mean, I estimate there's a $75 to $100 billion market just on Earth observation. This kind of data we collect and AI on top of that, unleashing all that application. So that's the near-term thing, applying large language models to Earth imagery data, unlocking agriculture, you know, energy, civil government applications, permitting, you name it. This is going to make everything more efficient. And then where we're going is indeed space is, is— we did a study with our partners at Google about 8 or 9 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-terrestrially.

And we figured out that when launch costs come down to about $200 to $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 2 to 3 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 is, that helps people understand that is you would naturally use solar panels for doing, uh, the, the data centers are a power problem. 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, you don't want intermittent power. So then you have to have batteries, or you, then you have to have gas, or then you have to have nuclear, and then it gets really expensive. In space, you can put a solar panel in a sun-synchronous dawn-dusk orbit where you are 24/7 looking at the sun.

So you can have a solar panel that collects and gathers 5 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 computing 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 into 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 NVIDIA's— some of NVIDIA's GPUs into space. We're launching Google's TPUs into space on an early test. There's lots of technology to figure out. 3%. Let's have a conversation. But it's an early— it's early days. But I think no question within 10 years, most compute will be put 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. Comms, Earth imaging. This is why we're getting into this.

Do you believe sending data centers to space makes more sense, or is it just the regular—

Can you have him explain the business first and then—

Oh yeah, of course.

Yeah.

So I think there, you know, with all due respect, one or two hard problems still left beyond putting, putting GPUs in space right now. I think we're not super good yet at building the clusters in space necessary for the communication. Between. Between, exactly, between.

We're not good at doing it on the ground.

We're not good at doing it on the ground. We're really not good at doing it in space. I think this is an extraordinarily important and interesting problem and one we should be spending money and attacking. I've got it in a slightly different time frame, but one that certainly will occur. And the hard part is, 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 to experiment, to even get insight into whether I'm right or not, is to get down the cost of the launch vehicles. Then you can start doing experiments and getting it wrong and fixing it and figuring it out. And until then, it was mostly on paper.

So for the foreseeable future, you're gonna be terrestrial. Explain your business and how you made these critical decisions that kind of took you on a different path. And you know, you versus NVIDIA versus AMD and what you think the future of AI silicon looks like.

I think that there were two parts here. Your first question was, around sort of the rise of silicon in general. And I think what AI did, and it's rarely sort of 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 of compute. We could store them and that's about it. We were bad at 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, 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. All right, maybe we could understand it. Rather than storing it and regurgitating it. And what this did is it opened up sort of to 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, terrestrially, 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, in AI compute is as a, as a processor builder, as 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, 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 share to change, right? 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 Nortel and all these companies we've forgotten about couldn't build chips and couldn't do data networking. And, and what you got was Cisco and Juniper and Arista, this collection of new companies. So we knew that, um, this new problem would present an opportunity for massive change.

So we saw that. We, we made two bets. Um, the, 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, they have enjoyed and eaten all the low-hanging fruit. So if you build a GPU, the odds that you're better than NVIDIA, in our view, are 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, that very few others had even attempted, which was to build a very big chip and to put memory right next to compute. And 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 opportunities.

Opportunity. So when OpenAI uses us, we're 15 or 18 times faster than a GPU, right? That means your answers are delivered more quickly. It means your engagement with, with the AI is 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 the, the counterfactual question. How big is the market for slow search today? Right, 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? 3 seconds, 5 seconds? You will not wait for AI. We have to deliver it to you in a, in, in real time. And that's what we saw, that's what we built.

So the panel's on going public. A lot of LPs in the room, they need to get liquid. I'm curious about the journey for your investors. Yeah. Okay. So, well, you guys went public what year?

Uh, 2021.

2021, by way of a SPAC, correct? Okay. And your VCs were who?

Um, Draper Fisher Jervison was one of the earliest. Capricorn. Peter Thiel's Founders Fund. Okay, then we go Uh, Yuri Milner's DST. Okay, so your sort of—

your investors come in, you go public at $2 billion via a SPAC. Now we're 4 years later. Really, it wasn't until year 3 or 4 that 90% of the value was created. Okay, so did those early investors capture this? Yeah, 90% move. Did they stay in it?

Most of them did. Okay. Most of them did, which is really smart on their part, obviously. I think they should hold on even more. If I didn't think that, you should buy me a bottle of wine.

Well, I mean, what's— I'm a little bit self-interested.

What's interesting about this is—

No, but really, they did. And I mean, Google hasn't sold a share. Their largest single investor, Capricorn, didn't until very recently. So basically, most of them stayed really well in. And they got all of that upside. And good for them.

And the reason that this is so important Yeah. Is that there are a lot of LPs in this room who they're like, when a company goes public, give us the shares.

No, no, no.

Yeah, give us, give us the shares. This is a counterexample, right? This happened to us in Mongo 10 years ago. We invested pre-IPO at $1 billion. We distributed the shares, I think, at $3 or $4 billion, and then it went to $50 billion over, you know, the course of the next 24 months. And we had people who 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, to distribute the shares. So you're an example. Now, in your case, Andrew, you have an innovation, right? You're just now, uh, public, so all of your investors are still under lockup like, like Altimeter. But you guys have innovated with the banks on what I call a dribble lockup. So over 6 months, the shares can be dribbled out according to a bunch of performance hurdles, which SpaceX is going to have a very similar—

When did we start this process of the, of the dribble?

The dribble?

Constantly. We started it years ago. But yes, but we're all about age. With respect to the lockup, 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 Altimeter be distributing the shares when they come out of lock? How do you think about, you know, your VCs holding on to the shares kind of post-lock?

I, I think historically more money is made after IPO than before. Yeah, I, I think every single study shows that, uh, there is more money to be made both in percentage and in, in what we care about, which is absolute. Yes. And, and so, uh, the amount of money that it's possible to put to work in most venture companies is very modest. I mean, there are 2 or 3 or 5 outliers, but for the most part, you can only put a relatively little bit of money to work. Um, by the time we get public, there's a lot more money there if things are going well, and the opportunity to make vastly more is after IPO, not before.

If I could just add on that, one interesting question is what's going to happen with SpaceX on this, because a lot of the value is in the future, but most of the big tech companies went public at a few billion, not a few trillion. There's a lot of zeros in between those, and you've got all this upside afterwards. Now, for the equivalent liftoff, SpaceX would have to be aiming at quadrillion-dollar valuations. Now, I know Elon has those ambitions, but you really have to believe in that.— to get, you know—

This is kind of the point I'm getting to. Yeah, right. We have 3 mega IPOs, you know, that we keep talking about that are multi-trillion. Yeah. All of that value accrued to private market investors. Planet 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 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 5x over the course of the last 2 years would have gone to public market investors. So go ahead.

Way better to be lucky than good.

Yeah.

So, so I think that I hear a lot of people thinking that Anthropic, OpenAI, and SpaceX are the new normal. I actually think the public market's maybe shifting back in this direction. And a lot of the companies in our portfolios are now thinking about going public at a billion or $3 billion or $5 billion. We had this period of a decade where Andreessen was really pushing stay private forever. And I see the pendulum swinging back to companies are like, man, I wanna be like Planet Labs and get public, right? And have to play in the big leagues and do it in the public markets like you just did.

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— for sure, steel 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.

Um, and so anyways, I just wanted to say to both of you, um, just as we wrap, you guys are an 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 reconverged. And then Will, same with you.

I'm happy it worked out for you, Chamath.

Well, it's worked out for both of us, so it's fine. Um, you guys are incredible testament to entrepreneurship and, uh, I just want to say thank you for everything you guys are doing. And the next few years are going to be really spicy.

Yeah, if I could just spend 30 seconds on the next few years, because I think it's going to be so exciting with, as I mentioned, AI and space merging together. We're going to see a takeoff of applications. I'd say like all the cool stuff that we're doing on the— with LLMs now is really based on just the 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. You know, 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 going to 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 sensing systems in space, planetary compute systems in space. And we can disagree or agree on that. On exact timeframe, but I think it's going to happen. And, and then that's going to enable a huge economy. So it's an exciting time in the next few years.

Will, Andrew, thank you guys very much.

Well done.

Thanks, guys.

Okay.

Thanks, buddy.

Thank you.

I really appreciate it.

Great seeing you, brother.

Congrats on everything.