Hey, 2026 could be an all-time [music]

record for IPOs.

>> The AI IPO of the year so far. That

company is Cerebras.

>> Cerebras Systems founder and CEO Andrew

Bubman. We are participating [music] in

something extraordinary on everything we

do. We are the fastest bar none.

>> Well, Marshall is the co-founder and CEO

of Planet [music] Labs.

>> Space and AI are really um 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. [music] He's

got his glasses, the famous red glasses.

Brad Gersner is here, founder and CEO of

Autoimmet [music] Capital, a leading

tech investment firm.

>> I believe that the wave is the biggest

wave in the history of technology,

[music] 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

Gersonner, Will Marshall, and Andrew

Feldman.

[music]

>> On the couch, we switch on the couch.

>> Nice to see you, my friend.

>> Hey, [music] big boy.

>> Nice to see you.

>> Last last time I saw you, we were in

Davos.

>> Yes,

>> we were in Davos causing another drop.

Another JL. Do you hear that little

Davos?

>> We were just, you know, it was preipo.

We're chopping it up

>> with Davos.

>> We're in Davos.

>> Hanging out at Davos.

>> Well, no. Listen, I was Everybody knows

the story. I'm supposed to go on my

yearly Japan ski trip. Sax calls me

>> with Tucker.

>> Yeah. Well, anyway, we don't drop that

name, but [laughter] I'll pick it up for

you. Put it over here.

>> Tucker. Anyway, so I cancel on Tucker. I

cancel because Sax calls me. He says,

"Listen, Pus needs you, the world's

greatest moderator in Davos." I said,

"No problem."

>> I said, "Saxs, 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 and

it says Jason McCabe Calacanis with

Donald J. Trump.

>> Oh wow. How did you feel?

>> I thought it was hilarious. [laughter]

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 uh the two of

you guys run two of the most interesting

and consequential newly public companies

in the stock market. Andrew Feland is

the founder and CEO of Cerebrus. 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 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 cuz 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 two years for you. Uh

>> it's more fresh.

>> Was it Was it everything that you

thought it would be? Like

>> what's clear so far is I need to upgrade

my namerop game. I mean that that was a

tour to force. [laughter]

>> But by the way, you were you were in

Davos with

>> J. I was I was there but that um uh

>> tour [laughter] to force

uh look I 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 value 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 you have some new constituents that

that you have to to to address and

communicate with, but the core parts of

your business, you have more money in

the bank. Um but not a damn thing

changes in the important parts of your

business. um 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

and so I I think what what we've seen is

um you 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

>> can I can I just give a little context

and then I want to hear from Will. You

know, if if I can, Andrew, you know, we

were investors in Cerebrus. I was on the

board a year earlier where we were

trying to go public. Um, 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 CPHAS, you

know, in 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 n 9 and a half

years of really hard and then 12 months

you know of of 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 bucks a share,

5060 billion dollars in market cap for a

business like you know and andrew is

just one of these people. Let's let's

get back to work and build But my

my just add-on question to that is from

an employee morale perspective like

distraction perspective etc. 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 I I think the first thing is a lot of

people asked us about how we got the

timing right.

>> Right.

>> And I I think the answer is by getting

it wrong for a decade. I mean that's

really the right way to get timing

right. Um I I think um first I we we

we've been at this for for more than a

decade and and we we brought everybody

who'd been with the company more than

nine years to share and we brought their

families. [snorts] And first I learned

that engineers owned ties. I didn't

actually know that. [laughter] Um 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

they were really proud in a way that

sort of their parents [clears throat]

might have heard of it or uh that that

somehow this was like a a bar mitzvah or

kinera or something.

>> Um

>> and then you you had these sort of the

the children of immigrants, one of our

uh one of our leaders, her father,

Chinese immigrants said, "I thought it

would have happened faster."

[laughter]

>> Right. And but I I think um we are sort

of by nature

uh

sort of in the uh in the trenches

people. And so um we we love solving

hard problems. And so when when we had

this excitement, everybody went and they

were so excited and we had a party and

um I I think it it gave external

validation. And then everybody turned

around and said, "Now what are we now

back to work?" And and so I 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 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 one of the first space

stocks and and I think people just had

no idea what earth is 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. uh the going public gives you

access to liquidity uh for early

shareholders whether that's the employ

early employees or early investors and

that's great it gives you cash for the

company that's great and I do think um

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, right? It's

legitimizing

>> and you know, you you know where the

stock is at any one day. You know, we're

not focused on that dayto-day. We're

focused on how we build long-term value

for our shareholders, right? And um you

know the market is I think started to

really understand where space is going,

why it is changing the the 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 um but it's just

booming now there's there's a

>> and the 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 Andrew's

success like you probably would have

been bucketed into Andrew as a military

tech company. So is that framing what's

driving a lot of

>> I think it's a bit more nuance 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 uh satellite lay 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. Um, 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 uh, you know, there's a

lot more to say on that, but AI is only

as good as the data it's trained upon.

percentage is military. I'm curious.

Sorry.

>> What percentage of revenue customer bas

um uh security is part of the initial

thing that we said we would do um out of

the gate, but it's true there's a bigger

fraction today than perhaps we would

have guessed. Um but the needs of the

geopolitical situation right now demand

what we're doing. Um you know, just as

an example, what this does is enable

them to see threats around the corner.

>> Yes. and then uh you know give them

weeks or months advanced 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. I but I wouldn't say we're

limited to being perceived like that,

right? um we we are helping farmers, we

are helping uh you know uh energy

companies, civil governments, we work

with NASA, we work with what have you

and and so um it's a it's a bigger it's

a bigger play than that but back to the

space uh piece of it what has changed

obviously rocket costs have come down

about four or 5x over the last uh 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 a billion dollars and

weigh 20 tons now cost a few kg or a few

tens or hundreds of kg

>> and can do just as much stuff if not

more. It's it's the same as the sort of

mainframe computer to desktop revol

computer 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

cost coming down and this

>> let's build let's build on this. So I

think I I'd like first you maybe take a

few minutes and then I 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

timebounded, 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 Grock

we took a very different approach

Nvidia's taken a very different approach

you took a big pizza shaped die and said

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

we're collecting vastly more data about

the planet. And with SpaceX and Starlink

and One Webb, they're they're

transporting far more data around the

planet. As you say, we're sort of

changing um uh 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 uh satellite

capabilities. And that's going to I I

mean I 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, um energy, civil

government applications, permitting, you

name it. This is going to make

everything more efficient. Um and then

where we're going is indeed space is is

we did a study with uh our partners at

Google about eight or nine years ago uh

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 uh

do it non-aterrestrially.

And we figured out that when launch

costs come down to about $200 to $300 a

kilogram um uh 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.

Uh but that's come down about 10x in the

last 10 years. Um on the current

trajectory with Starship in particular,

I would expect it the launch cost 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 uh 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. Um in

space you can put a solar panel in a

suns synchronous uh dawn dusk orbit

where you're 24/7 looking at the sun. So

you can have a solar panel that collects

and gathers five times more energy per

solar panel than on the ground and you

don't have to have batteries or anything

else. Uh so the infrastructure for

comput 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 into space than putting on the

ground. And it turns out that's going to

be in a few years. So we're partnering

uh with Google to launch some of their

TPUs into space. We've already launched

Nvidia's uh uh 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.

>> Let's have a conversation. Um, but it's

an early it's early days, but I think no

question within 10 years most compute

will be putting in space, which to give

you a sense is a lot of money,

[laughter]

like trillions, and um will be bigger

than any of the other space businesses

today. comes Earth imaging. This is why

we're getting into this.

>> Do you believe 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

they're, you know, with all due respect,

one or two hard problems still left be

beyond putting putting GPUs in in in

space right now. I I think um we we

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 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 the hard part is is it is it one of

those problems where uh 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 uh 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 launch

vehicles. Then you can start doing

experiments and getting it wrong and

fixing it and figuring it out. And until

then it was unpaid.

>> For 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 know you versus

Nvidia versus AMD and what you think the

future of AI silicon looks like. I I I I

think there were two parts your your

first question was around sort of the

rise of silicon in general and I I think

what AI did and it's 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 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

it simultaneously opened up this entire

area and allowed compute to attack it.

And this is what's underpinning both

Nvidia's growth and 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 and different parts of

knowledge

and and that was sort of the first part

to to 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 '9s

when Nortell and all these companies

we've forgotten about couldn't build

chips and couldn't do uh uh data

networking and and what you got with

Cisco and Juniper and Arist and 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 first was dedicated silicon would be

the answer. 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 it it can't. They have they

have enjoyed and and eaten all the

lowhanging 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 opportunity.

So when OpenAI uses us, we're 15 or 18

times faster than a GPU.

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 counter

factual question. How big is the market

for slow search today?

Right. Right. Is zero. How big is the

market for dialup? It's zero. H 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 spa.

>> Correct.

>> Okay. And your VCs were who?

>> Um Drake Professor Jverson was one of

the earliest Capricorn. Um Peter Te's

founders fund. Then we got uh Yuri

Milner's DST.

>> Okay. So your your investors come in,

you go public at 2 billion via a spa.

>> Now we're four years later. Really, it

wasn't until year three or four that 90%

of the value was created. Okay. So did

those early investors capture this 90%

move? Did they stay in it?

>> Most of them did. Yeah, most of them

did, which is really smart on their

part. Obviously, I think they should

hold on even more. Uh, if I didn't think

that, you should.

>> I'm a little bit self-interested.

>> What's interesting about this is

>> No, but really they did. And and I mean,

Google hasn't sold a share. They're our

largest single investor. Um, uh,

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 I think this is so important

>> 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

>> give us give us the shares. This is a

counter example right? This happened to

us in 10 years ago. We invested

preipo 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 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 to 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 [laughter]

>> concept you started it years ago but

>> yes

>> but u we're all of that with respect to

the lockup I think this is the 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 ILPs right in the room.

Should Alimter 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?

>> Well, I I I think historically more

money's made after IPO than before.

>> Yeah.

>> I 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 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 two or three or

five 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. Hey, if I could just add

on that, one interesting question is

what's going to happen with SpaceX on

this because you know a lot of the value

is is in the future, right? But I mean

most of the big tech companies went

public at a few billion,

>> not a few trillion. Like there's a lot

of zeros in between those, right? And

you got all this upside afterwards. Now,

for the equivalent liftoff, SpaceX would

have to be aiming at quadrillion

valuations. Now, I know Elon has those

sort of ambitions, but you really have

to believe in that uh to get, you know,

>> this is this is kind of the point I'm

getting to, right? We have three mega

IPOs, you know, we keep talking about

that are multi- trillion.

>> Yeah.

>> All of that value acrewed 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 two

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 open AI

and SpaceX are the new normal. I

actually think the public markets may be

shifting back in this direction and a

lot of the companies in our portfolios

are now thinking about going public at a

billion or three billion or 5 billion.

>> We had this period of a decade where

Andrees was really pushing stay private

forever and I see the pendulum swinging

back to companies are like man I want to

be like Planet Labs and get public,

>> right? and and have to play in the big

leagues and do it in the public markets

like

>> 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 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

recon converged and then Will same with

you.

>> I'm happy it worked out for you Jimoth.

>> Well it's worked out for both of us so

it's [laughter] 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 a 30 seconds

on the next few years because I think

it's going to be so exciting with um as

I mentioned AI and space merging

together. We're going to see a take off

our applications. I like to 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

about the real world. I call them

blind to you know they don't know about

that farm field that flood that 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 uh AI models. I

call them instead of having large

language models, large earth models or

uh 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

on exact time frame, 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. [applause]

>> Thanks, guys. Okay. [music]

Thanks, buddy. Appreciate you. Really

appreciate it. Great seeing you,

brother. Congrats.