00:00:00
I don't know if some of you knew I was an angel investor in some companies. On the count of three, what's my
00:00:06
favorite angel investment of all time? One, two, three. >> Thank you. Give it up. Travis Kalanick.
00:00:21
>> Appreciate you. All right. Wow. Um, on a big news day, Travis is here on a very
00:00:28
big news day. you spent uh wow I guess like seven years just in the lab building last year every year I ask you
00:00:37
hey you want to come to the summit you want to say no it's like I'm going to
00:00:41
just chill I'm building next year hey you know just it's always available
00:00:45
>> you understand I'm stealth >> yeah stealth I'm stealth nobody knows
00:00:49
where I am nobody knows what I'm doing the employees are not allowed to put the
00:00:52
name of the company on their LinkedIn >> thousands of employees that weren't
00:00:57
allowed to put the company name on LinkedIn I mean, incredible. And I'm like, "Okay." And
00:01:02
>> their parents thought they worked for the CIA. >> Yeah. And then he's like, "And by the
00:01:05
way, Jake Al, you can invest. You can't announce it and you have to sign an you
00:01:09
can't mention you're an investor." It's like, "Okay, no problem. I'm just happy
00:01:12
to be on the cap table." >> Is he like kind of like secret saying what he wasn't supposed to say,
00:01:17
>> right? Now he's doing that just happened. >> Well, you know, you're out now. It Let's
00:01:23
go. >> You're out. It's out. You're You came out of stealth today.
00:01:26
>> Um, >> it's so funny. Okay. >> It's so great. You came out of stealth.
00:01:30
Well, you you talked a little bit. You came to Allins last year. Is that fair? You say you're coming out of stealth
00:01:34
today. Is that right? >> Well, look, let let's just start with what that meant for our employees
00:01:39
because again, imagine if you're at a multi,000 person company and every single employee has stealth on their
00:01:48
LinkedIn, including salespeople, okay? Including recruiters. Like it was they they were they were
00:01:58
living life on hard mode. It >> was kind of fun too, right? I mean >> I mean yeah it was like kind of cool
00:02:03
what the what's what is this? Why are there why is this massive density of stealth
00:02:08
>> right >> startup people in Los Angeles? What is happening over there?
00:02:13
>> Yeah. >> Yeah. >> Also technically the name of the company in different countries was very generic
00:02:20
names of companies. I mean everything was designed to be stealth, >> right?
00:02:26
>> So we operate in 30 countries. In the US the kitchens product is known as cloud
00:02:33
kitchens. In Korea it's Kitchen Valley. In the Middle East it's Nama. In
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Latin America, parts of Latin America it's Cinaas. I mean you get the idea. You can't even
00:02:52
remember all the names and all the code words. >> Think about it. >> To think it through. But
00:02:56
>> we have four in China, you know, it's like all over the place. Yeah.
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>> But things have gone really well and you've been a little inquisitive. So
00:03:03
tell us about the branding today that you're announcing and then maybe some of
00:03:07
the acquisitions and evolution of the company. You're not just renting kitchen
00:03:12
space. >> Those who I mean know how I thought about things in the Uber day, a lot of
00:03:17
this stuff's not surprising. I I would often talk about digitizing the physical
00:03:21
world. I think I even did it all at summit. The quick version of this, I'll try to do it quickly, but it's like uh
00:03:28
we know the bits world, the computer world, the one that Michael Dell essentially invented for us. CPU,
00:03:34
storage, network. These are three core computing resources. When you go to computer science class your first day,
00:03:39
three core computer resources. CPU manipulates the bits. Storage stores the bits. Network moves bits from point A to
00:03:45
point B. But if you're digitizing the physical world, you're treating atoms
00:03:49
like bits. You're building an atomsbased computer. And I'll explain what I mean to say. I
00:03:55
know this is a little little out there. CPU manipulates bits. What manipulates atoms? Manufacturing. Storage stores
00:04:01
bits. What stores atoms? Real estate. Network moves bits from point A to point B. What moves atoms? That's
00:04:07
transportation or logistics. So you have these three core computing resources in
00:04:12
an atomsbased computer. The name of my company was very obtuse and purposely designed to be as boring as hell was
00:04:20
called City Storage Systems. So that's digitized real estate in an atomsbased computer. Our first computer
00:04:29
being a food computer. What does that mean? Manufacturing real estate and logistics for food.
00:04:36
And so you start to get there and the idea the the mission was infrastructure for better food. The idea was, can you
00:04:42
get a meal that's prepared and delivered to you so efficient that it starts to
00:04:47
approach the the the cost of going to the grocery store? If you can do that, you do to the kitchen what Uber did to
00:04:54
the car. But in the Uber day, the roads were there, the cars are unused. You just had to put an app in the app store.
00:05:01
Wasn't that easy, but kind of that easy. In this world, you can't do this on a
00:05:06
restaurant. restaurant doesn't have. When I left Uber, 13% of all San Francisco miles were Uber miles.
00:05:15
You can't get and that was 10 nine years ago. You can't get there on food on
00:05:21
restaurants. They they have like 20% capacity. Uber Eats and Door Dash fill it, but the infrastructure to do high
00:05:28
capacity, highcale sort of industrial production is just not there. And the logistics just not there. It
00:05:35
just doesn't work. That's why on e-commerce you go through Amazon big ass
00:05:39
warehouses with awesome logistics. You've got to do the same thing when food when food goes to e-commerce. That
00:05:46
was a lot. Okay. So bottom line is >> it's awesome. We do this food computation stuff. We're doing more
00:05:54
computers now. And so the name of the company is called atoms and it's let's
00:05:59
say the mission uh is um is uh physical automation to transform industries and move the world. And so we have our food
00:06:10
computer I talked about. Then we do we're doing mining. >> Mining as in
00:06:15
>> mining data mining. >> We're talking about atoms guys. >> Yeah.
00:06:18
>> So well of course you do some mining data mine too but the point is is physical mining. So automation of mines
00:06:27
and uh the mission there is uh more productive minds to power earth's industries. Right? So it's got
00:06:36
this industrial atoms vibe to it. And then on the transport side, it's uh wheelbase for robots because if you're
00:06:45
doing specialized robots, not humanoids, specialized robots, you need to be able to move and act in
00:06:53
the physical world. But the minute you're moving, you got to have a wheelbase. So, it's just part of the
00:06:59
equation. And a lot of people go, look at Tesla, it's great. Look at uh look at
00:07:05
Whimo. Awesome. They're cruising around Austin, of course. But there's so many
00:07:09
things that move. It's not just a ride sharing thing. Um, and so, um, obviously
00:07:15
including mining equipment that's doing its thing. So you guys, that's the
00:07:18
general sort of idea. And we acquired a company on the mining stuff, a company called Pronto or it's about to close.
00:07:27
It's we're we're inches from closing is the way to put it. >> What were they doing? What was their
00:07:31
business? Pronto >> automating mining equipment. >> Were they based?
00:07:35
>> Uh, they're based in San Francisco. So, you and I were starting to talk about
00:07:38
this backstage, but there's some folks I talked to in the mining industry who
00:07:42
mentioned, you know, like the the big issue with mining number one is just surveying, like finding the the
00:07:47
locations, right? Is there an advantage to be created there? Cuz I know there's
00:07:50
a couple startups that are trying to be really smart about selecting locations to get the targets out of the ground.
00:07:55
>> Yeah. >> And then the other one is like, well, can you go deep? Because pretty much
00:07:59
anywhere on Earth, you can get whatever you want if you're willing to go deep
00:08:02
enough, but the cost is is distance squared, right? So the energy cost is like how deep are you going to the to to
00:08:09
the second power. So it becomes you know geometrically more expensive to go deeper but the deeper you go you're the
00:08:16
more you're able to kind of not worry about getting the right location. So does automation unlock that capacity?
00:08:23
>> Automation definitely does. I mean, but you have I mean, also it's like, man,
00:08:27
does Boring Company have some good stuff going? >> Like I hope we we're like we're doing
00:08:32
the mining thing like and Boring Goes makes, you know, some good tunnels for for cars to do the thing. But like
00:08:39
there's some kind of boring mechanism, automated tunneling to do some of this.
00:08:44
But to be honest, there's there's, you know, they have this this thing is like
00:08:47
rare earths. I don't know why they put plural rare earths, isn't it? Rar's
00:08:52
earth. I don't know. But the >> but rare rare >> rare earth. >> Yeah. But it's not rare.
00:09:01
>> It's uncommon mineral guys. It's not rare. It's what you have to do to the
00:09:04
land is aggressive. And what's rare is the is is where the where are the places
00:09:10
they'll let you do it that you can also sort of get people to. >> When you automate, you can go to a lot
00:09:17
of places. Uh well, first is all the mines that exist are way more productive. Um and the second is you can
00:09:25
then sort of justify going to places you wouldn't have been able to go before
00:09:29
because um you don't have as much of a labor footprint or a safety issue or a
00:09:34
whole bunch of other things that then >> So if it's inhospitable, if it's
00:09:38
regulated, if it's like I don't want to live there, it's the end of the earth.
00:09:42
>> Yeah. >> You can send robots and have people monitoring them remotely. Yeah.
00:09:48
>> And this is like a a future that feels like a little bit like science fiction.
00:09:54
>> Look, we're here in Austin. You got to do the shout out to Tesla and all the
00:09:58
things cuz I like to sort of break down the physical AI stack includes not just like, oh yeah,
00:10:06
computation and I've got to have physical AI models and I got to all the things you sort of think of. What about
00:10:12
land development? That should be in that stack. What about chemistry? that needs
00:10:17
to be in the stack. Manufacturing needs to be in the stack. When you look at the
00:10:20
stack, you're like, damn, Tesla's got this. They are they are the Google of
00:10:27
this era. Which is what I mean by that is in the 2000s, if you were doing a startup in the 2000s, the first question
00:10:33
you would get is uh why isn't why isn't Google going to kill you or why isn't
00:10:38
Google just going to do it? >> Why Google? >> They're not going to know that they
00:10:41
killed you. >> And before that, Microsoft. >> And before that was Microsoft late 90s.
00:10:45
Uber had a time 2010. >> What if Uber puts that in the app? >> Come on. It's like, dude, this is Uber.
00:10:50
I'm like, but you know, I think in the physical AI space, that's a that's sort
00:10:54
of a Tesla thing. Um, but there's so many things to do. You got to shoot your shot. You got to
00:11:00
do some stuff. >> And rumors that um, hey, you might not be done with self-driving, something
00:11:06
that you were very early on. How do you think about what you're seeing in the
00:11:10
playing field of self-driving? Because my lord, you know, Whimo's making great
00:11:15
progress. Tesla's making great progress. >> Pick a winner. Like pick a winner
00:11:18
between Tesla, Tesla, Whimo, Uber, >> or or like Uber. Uber Uber seems to be
00:11:24
building a network of stuff. >> Yeah. I mean, the number of >> pick a winner.
00:11:28
>> The number of players is crazy now, right? Like >> Yeah. Look, there's I think there's more
00:11:33
noise. There's more bark than there is bite right now. Um, look, I think Whimo
00:11:39
obviously is ahead. the existence proof is there. Their issue is manufacturing and scale um and urgency and fierceness
00:11:49
like let's >> come on. Let's go. >> Yeah. >> You know, Uber had an autonomy project
00:11:56
back in the day. So, and they have a different strategy these days. I haven't
00:11:59
been there for a while. So, but the but the point is is that you so you got Whimo, then you've got Tesla
00:12:05
fundamentals, science, hard mode times 100. And the question is, do they get there in what time
00:12:17
scale? If if they and like honestly everybody's like, could happen tomorrow, could
00:12:22
happen in 5 years. And I think that it's like when does the chat GPT moment happen for vision is
00:12:30
basically the thing. Let's call it vision without other sensors. So super inspiring, but like what's the timeline
00:12:37
on it? >> Yeah. >> Um those are the bas this is basically the and then there's a lot of other
00:12:41
little guys that don't really have the stuff I believe yet. >> There's nobody standing out just yet of
00:12:48
of the others. Do you think we're at a point now like obviously now that you're
00:12:53
getting into more of these kind of autonomous systems that move around like do we have these vision language action
00:13:00
models tuned and ready for prime time? There's there's been a conversation like
00:13:05
who's going to have the Android the operating system for vision language action where I can use my voice tell it
00:13:12
to do something and it knows what I'm saying and then it identifies the objects and does the thing in the
00:13:16
physical world. Do those models exist today or there still work? And is that like a Google OS or like where does that
00:13:23
OS come from? >> Look, I think there's a there this is an area of a lot of energy, a mix of
00:13:29
research and implementation. I think there's a lot of hope and interesting stuff. I mean the high level is we all
00:13:35
remember what happened when you used chat GPT 3.5 and you're like holy. >> Yeah, it's legit.
00:13:43
>> Whoa. And then it went to four and you're like, okay, like some stuff just
00:13:47
changed. The world just changed and I can sort of connect some dots and getting real.
00:13:54
Is it about to happen? Is it about to happen for physical AI? And that's what
00:13:59
this is about. Yeah. >> And the fun part about it is machine learning, deep learning, this kind of
00:14:04
thing for many years, decades was like inscrutable. I don't know what the thing
00:14:08
is thinking. It just spits out an answer and I know it's correct. Well, now you
00:14:11
can have a conversation with it, right? Like imagine if it's driving your car
00:14:17
and there's different agents and one's just driving, the other's like, "Yo,
00:14:21
look out over there." >> Yeah. >> It's like, "Oh, just like how we roll."
00:14:26
Like somebody does that, you're like, you're like, "Honey, that's like 200
00:14:30
meters away. We're going to be >> okay." Yeah. >> Jason and I don't call each other honey,
00:14:34
but I got you. Yeah. >> Like, >> sweetie, >> you know. Yeah. >> Okay. So anyways, so that was odd,
00:14:41
wasn't it? Okay. Okay. Okay. I didn't mean it that way. I didn't mean it.
00:14:45
>> Yeah. You know, I meant it. Okay. >> Language is a beautiful compression
00:14:50
mechanism that humans use 100 watts of energy like and you put that in the scheme of
00:15:00
things of like AI training, AI energy, the power plants that are built to do the thing that isn't even at human
00:15:07
strength yet. Okay. The Whimo machine takes a hundred times more energy to drive a Whimo than a human does to drive
00:15:18
a Whimo. So, so language we there are still things that humans are great at and that
00:15:26
unbeat like the goat. We're still the goat at certain things. Language is this
00:15:30
epic compression. And um we need to find ways to compress cuz like when you think about how how we
00:15:36
first started looking at the physical world is we saw everything. And you know what guys and this is sort of obvious
00:15:43
like it doesn't matter what the cloud is doing if I'm driving. But like the car doesn't know that. It's
00:15:50
pulling in every freaking data point and processing everything. And it's it's you
00:15:54
know look they've been about sort of carving out the things that don't matter
00:15:57
and things like this. There's ultra awesome versions of this and you can imagine how you can use
00:16:02
language or things that look like language to communicate either amongst agents or sort of safety systems with a
00:16:09
driving system to sort of get very efficient answers and to identify safety issues very efficiently.
00:16:18
>> People don't know that you've moved to Texas as of most people don't know but
00:16:23
it's it's out there. >> Yeah. You moved here in December, so now you're a resident of Austin.
00:16:29
>> Yeah, I was I Thank you. >> It's very exciting for me. We've been
00:16:34
getting to play some back gammon. >> Back gamon cards. It's >> cards. We're having a good time.
00:16:38
>> So, I've had a place on Lake Austin since 2021. And uh I go there. I'm an avid water
00:16:46
skier. Like, >> you're impressive at water skiing, I have to say. Like,
00:16:51
>> so I've had a place in Austin for 5 years. freaking love it. It's my weekend. I
00:16:56
would go 15 weekends a year. >> What do you think's going to happen in
00:16:59
California? >> It's pretty messed up. Look, I I grew up in Cali. Uh like I grew up in Los
00:17:04
Angeles. Uh my parents were born and bred in Los Angeles, which basically makes them the founders of LA. Okay. But
00:17:14
um so I have a lot of heart like my whole family, everything, you know? It's
00:17:18
pretty >> it's pretty it's I don't want >> a lot of us feel that way. I don't want
00:17:22
to get the violin out, but it just But it's heartbreaking. >> The plot totally It's just a place you
00:17:27
grew up. It's your home, you know, >> when you have to leave. >> Uh but it's getting weird out there
00:17:34
and uh it feels like it's getting weirder and at some point that's it's
00:17:40
just too weird. >> It's too weird. Do you think everyone's going to leave?
00:17:44
>> I mean, it started with Elon and it was like >> we don't want Elon here and then he's
00:17:49
like message received, >> right? And then it kind of worked its way down the tech industry and in the
00:17:55
kind of it, you know, world of people building businesses and whatnot. And now it's kind of gotten so broad in terms of
00:18:03
the >> Joe Rogan comedy, music, New Yorkers, restaurant tours. I mean, this place is
00:18:10
>> I'm not even talking about this. I'm just talking about everyone leaving LA
00:18:13
or sorry leaving California is almost like working down this path of >> look my the rest of my team's like we're
00:18:21
when are we moving you know they're like >> and how are you dealing with that? So
00:18:25
that was the question was like >> got to buy homes on the lake. >> There are literally dozens of startup
00:18:29
CEOs of call it successful or growing companies that I talked to who were like >> dude I want to leave but I got employees
00:18:37
here. I got an office here. I got a facility here. build stuff here. How am I going to leave?
00:18:42
>> Yeah, I totally get it. It's a real thing. So, look, I think like most
00:18:47
things, uh, sort of when it's time and it feels painful to do something, sometimes it's actually not as bad as
00:18:55
you think and you just got to make the move and lead and do it. Um, and so, uh, that's kind of what that's kind of the
00:19:04
process, the almost like a morning process I went through and that's just what it is. is and you're setting up a
00:19:09
team here. >> Yeah, of course. Uh and I got that office right on the lake.
00:19:15
>> Did you get that? >> Uh it's we are negotiating. No, it's all
00:19:19
good. No, no, it's all good. We're negotiating right now. >> But I'm going to jet ski to work.
00:19:23
>> No, literally we is it true story. Last year we're like driving up the thing and
00:19:28
I was like, "Wow, I wonder who owns that." He's like, "I will." And I was
00:19:33
like, "Did you look at It's like I looked at that and I was like, "That's a
00:19:37
that would be a nice one." But the the truth is, you know, and I had a couple
00:19:41
people move here a couple years ago and they all had the same reaction. Oh my god, I'm living in a place that's twice
00:19:47
as big for half as much. The people here are dope. The food is dope. Everybody here is got this sense that we're
00:19:54
building the future. And it's just fun and world positive. And you know, for
00:19:59
me, I got to live New York, LA, San Francisco. I did three of the great cities in this country. This one feels
00:20:05
the most like home to me, >> which is a very strange feeling to me, but it feels like everybody here wants
00:20:10
to build the future and it's very diverse, you know, like all these different industries and people pursuing
00:20:16
stuff. I I think this is the future. >> Yeah. Here's the thing. Like you go to
00:20:19
San Francisco and I still have a little nostalgia when I go to San Francisco just having built Uber there and the
00:20:26
whole thing. Um, I still get the, you know, the butterflies just I, you know, but it does have something magical. You,
00:20:33
you just can't take it away. And then you look at all of these bike lanes and
00:20:38
these bus lanes that never have a bus or a bike in them >> and cost $400 million to build one mile
00:20:45
>> and it's literally it's sort of like this subconscious desire to choke the city
00:20:51
off. Now remember, I look at things through roads. That's how I think. So I'm just like obviously the city is
00:20:58
totally busted. >> Yeah. >> No, they they literally took Market Street and they're like, "What would be
00:21:04
the optimal way to this up and virtue signal at the same time?" And they're
00:21:08
like, "Yeah, buses." And it's like, "Nobody's on the bus. Nobody takes the
00:21:13
bus. It's a beautiful small town. San Francisco. That whole street is empty and painted red."
00:21:19
>> So, okay. So, we all [ __ ] and complain non-stop on our chat. >> When are you leaving?
00:21:25
>> I'm number one. I get it. But, when are you leaving? >> Okay. Well,
00:21:28
>> on the chat, you're the best, by the way. I'm like, >> okay. So, let me just,
00:21:30
>> by the way, there's couple glasses of wine in >> public facing Freedberg
00:21:35
>> and he's like, you know, I think there's a better way to do. And then there's
00:21:38
like Darth Friedberg in group chat. He's like, these people, these morons are
00:21:44
they're destroying societ. He is like Darth Friedberg in group chat. Am I lying?
00:21:51
>> Am I lying? Is he the most >> correct? Especially after a couple glasses of wine.
00:21:56
>> Yeah. When I start drinking fall and he takes pictures, he's like, "Fourth
00:22:00
beverage." And we're like, "Oh, it's worth staying up on the group chat."
00:22:04
>> Yeah. And then I'm like, I'll go and attack this congressman on Twitter,
00:22:07
which I realized. >> And then you go delete the tweet. >> Yeah. >> Don't delete the tweet.
00:22:11
>> Yeah. I delete the tweets. Okay. know there's a group of people trying to
00:22:16
raise $500 million to create like a tech/ business coalition to go to Sacramento, which arguably is something
00:22:24
that everyone's left and avoided doing forever cuz no one wants to spend time
00:22:28
in freaking Sacramento fighting politicians, but it's almost like we're all falling off a cliff. It's time to do
00:22:33
something. Do you think there's a realistic path packed? Do you think the people can actually get their together
00:22:38
that even if 500 million came in, there's a way to kind of turn around the state, fix some of the policies? You
00:22:43
think it's too late? >> I don't think that. But look, I would go I look, anybody who's doing anything to
00:22:48
fix things, I'm like, hell yeah, let's do something. The issue is we all grew
00:22:53
up in the tech world, which was like a libertarian place where you stay out of politics and
00:23:01
>> that kind was that kind of vibe. It was just everybody was like that. >> Leave me alone. when I want to make
00:23:06
stuff. >> Yeah. I just I'm not I don't do that. And that's obviously this not a thing
00:23:11
anymore in California. I think the the ballot initiatives are very powerful and there's very clean ways to get something
00:23:18
on the ballot love that. I think that your DAS who have decided we do not enforce crime at all anymore. That's
00:23:28
like a sweet spot. Like I believe that I sort of have this apherism. Truth and justice are the immune system for
00:23:36
society. When when the immune system is suppressed, all the social ills flare up.
00:23:47
So look for the places where truth and justice are being deteriorated, are being degraded, and say, how do we get
00:23:54
at that? Because if you get at that, everything else downstream will be better. So that's kind of how I look at things
00:24:02
and how I also determine whether the world's getting better or worse. When I
00:24:06
say weird, I'm talking about truth and justice. That's what I mean when I say,
00:24:11
"Oh man, it's getting weird. It's getting weirder," which means it's
00:24:13
weird. I'm just talking about truth and justice. >> Well, I mean, and you look at the
00:24:17
homeless industrial complex, you look at Chesuine, which the all-in pod sacks, myself, and the pod, like we we
00:24:24
literally led the recall of him. And then you had the same thing going on in LA where they were just like if somebody
00:24:31
>> Gasone >> Yeah, Gasone. I mean, we basically lost the script. You're running the city for
00:24:36
the criminals. It literally is like a Batman movie. It's like Bane. >> I mean, you want to arrest the
00:24:42
criminals. >> Look, >> I was born in the darkness. I mean, these guys are lunatics.
00:24:49
>> Yeah. Look, I I know police officers in Los Angeles who are no longer police
00:24:54
officers, and these are lifelong guys who protect and serve. That's in their
00:24:58
bloods or DNA. They want to protect people. They want the bad guys to be dealt with. And they they almost have
00:25:06
PTSD from what it is like to want to serve and see bad things happening and not being
00:25:14
allowed to stop it. >> Yeah. Nobody's got their back and they're not allowed to do their job.
00:25:18
It's It's crazy. And I It's getting weird. >> Okay. Hey, I want to just go back to AI.
00:25:23
>> Sorry for the darkness. >> No, no, no. I think it's good. >> I was trying to induce I'm trying to
00:25:27
induce dark free. >> Well, I brought it up. I mean, someone bring me a tequila. I'll get going.
00:25:33
>> Yeah, let's do it. Can we get a couple tequilas? >> It was funny. I went on this podcast
00:25:36
yesterday and the guy and the f the guy was like the first hour was middle of the road. I was talking about tech and
00:25:40
science and then like politics came up. He's like, so socialism and he said like
00:25:44
you lost it and then you were like he's like the energy went 10x and Yeah. So, it'll come out in a couple
00:25:50
weeks, but I was like, it it got me going. Okay. I want to talk about physical AI one more time.
00:25:54
>> Yeah. >> So, one of now that now that you're doing this, I saw a presentation the
00:25:58
other day. Someone showed like a video of a squirrel jumping from one tree to another tree. And they're like a tenth
00:26:03
of a watt or something like like the the biology is tuned and it's so perfect in
00:26:09
terms of its efficiency of energy utilization to do physical things. And we're taking these like big things of
00:26:15
metal and motors and like actuators and if you add up or you compound all of the
00:26:21
inefficiencies in the system, it's like 1,200 watts to get the robot to walk 4
00:26:26
foot. Like like break apart not just the software but the hardware layer and where are we at in evolving things like
00:26:35
actuators and the materials and everything else that's going to make physical AI work and scale. Oh, look, a
00:26:42
lot with the questions you're asking are going down humanoid lane, which is like
00:26:48
this thing and and everybody talks about how do you do the hand? It's almost like
00:26:51
Terminator 2 type obsession with the hand, which is fair. Like, it's a very critical part of it. I mean, look at the
00:26:58
I like to look at the Achilles the quote unquote Achilles tendon of any of these
00:27:01
machines and you're like, that's where the action is. This this there's a
00:27:06
couple other places. Um, look, I'm in the nonhumanoid space. I mean, but mechanical engineers have been
00:27:14
dealing with actuators and, you know, all the sort of electromechanical sort of interactions that make machines do
00:27:22
certain things, but like I'm in the food machine space, so I can tell you how to
00:27:27
open a paper bag and put a put a a bowl in a paper bag without tearing the paper
00:27:34
bag. But I am less into the I forget the name pero. They're they're the the
00:27:41
senses to understand awareness and touch. Um I'm not in that game. Um so when you're mining you're like you're
00:27:51
not like you know you know >> you're not threating >> you're not playing tennis. Um certain
00:27:58
things may be equivalent to tennis. So, look, the bottom line is we're seeing
00:28:01
obviously all you have to do is go online and look at where the humanoids are going over time and how much better
00:28:08
they're getting. Um, it's wild and it's happening so freaking fast. But any
00:28:15
humanoid demo starts with dancing and martial arts. >> Yeah. >> And we're sort of down specialized robot
00:28:25
lane, which is gainfully employed robots. >> Yeah. So, I know I didn't totally answer
00:28:30
the question, the technology piece, but >> I just like do you agree that there's
00:28:34
probably like a big opportunity for venture money and like research to go into material science extra? Yeah,
00:28:40
>> for sure. >> Sure. Because if the physical AI stack manipulation and all of the related
00:28:47
things around it >> is massive. >> And so if you get the software working,
00:28:52
it's almost like the hardware has to catch up. Yes, >> we got a lot of
00:28:56
>> investor. >> Well, actually was it's good that you bring this up. You know, one of the
00:29:00
things you pioneered um at Uber was um capital as a weapon and you were very thoughtful about hey if we can take this
00:29:10
capital off the table then that's going to let's call it what it is. It's going
00:29:14
to be an advantage versus the competitors and these other competitors couldn't get that capital. That's now I
00:29:20
think people have seen that playbook and they're like hm Samman's like that was
00:29:24
smart let me try and it's at a different scale now that you've come out of
00:29:28
stealth >> now that you've got and and people are starting to understand just starting
00:29:33
today how big your vision is >> capital as a weapon this is I guess in your plan yeah
00:29:39
>> well I mean here's the thing right so capital as a strategic weapon for its
00:29:44
own sake is not a thing but when it is actually a strategic weapon And then it is a thing. And what I mean by that is
00:29:50
like in the Uber world early days if you didn't have capital didn't matter how
00:29:56
good your app was because MASA is going to put a billion dollars into your competitor and you're going to lose 20%
00:30:01
market share tomorrow. So a critical competency in fact your worldass competencies one of them has to be
00:30:08
raising capital and you need to do it better than everybody else and if you don't you are going to lose.
00:30:13
>> Let me ask one follow up to that. Sorry you go ahead. Um but the Middle East
00:30:16
>> Yeah. I've heard theories the last couple days that big capital seekers are
00:30:21
kind of right now because of what's going on in the Middle East with the Iran war. Dubai, Qatar, Saudis are kind
00:30:29
of going to close up the capital flowing to the US right now. And is that real? I
00:30:34
mean, do you think that's a real threat? So look, our Middle East business was
00:30:36
supposed to go public in January and the Saudi market was went down 20% over like
00:30:45
a two-month period and that was like a massive damper on the situation. Now part of it's part of that was because
00:30:53
the oil prices had gone down so dramatically >> and if you went into KSA, you went to
00:30:59
the kingdom, everybody's like, we need we need oil prices to go up. uh you know
00:31:05
that's the other side of the equation. So I don't know what h like I don't I'm
00:31:09
not in the market raising money right at this moment and this is a twoe old thing
00:31:14
that I you know look I see the news just like everybody else and I'm not out
00:31:18
there calling while a war is going on and saying hey guys you got some money. Um, so I don't know exactly what's going
00:31:25
to happen. But if you are an optimist and you're like, "Okay, this isn't this
00:31:29
is not going on forever." Just like the tariffs, it was the end of the world and then it
00:31:35
wasn't very quickly. >> If you're an optimist about this situation and it won't be the end of the
00:31:40
world, maybe even a better world, then we get to a better place. And I think >> progress, abundance, the golden age
00:31:49
happens. And a lot of it is about all the things that are happening in AI in physical AI and and and just the
00:31:57
productivity gains that are coming in very massive ways. Yeah. >> Yeah. And I mean it it was shock shock
00:32:03
and awe and then hey now we've got a steady state and let's hope that's what
00:32:07
happens in Iran is that we can depose these evil dictators, replace it with something a little more stable.
00:32:14
>> And related to this before we wrap, they're going to China. There's big
00:32:17
trade deal being negotiated. What do you hope comes out of this Chinese thing? >> And what did you learn in China?
00:32:22
>> What would Yeah. What would you learn? And and what do you think would be great
00:32:25
for America? Like what would you like to see and be like, man, that's going to
00:32:27
set us all up. No more. >> Look, here's the thing. If you go to China right now and you go and just take
00:32:32
a tour of the manufacturing that's going on there, just the manufacturing base,
00:32:38
the cities, especially if you've gone to China for a couple decades in a row,
00:32:43
you're like, damn. Yeah. You So, let's just do two things. You go to Shenzen,
00:32:49
which before felt like Kansas City, but 50 years ago and really humid, which I guess Kansas City sometimes, but you go
00:32:59
there now and it's like oneupping Singapore, right? Or so that's the city view.
00:33:06
You're just experiencing a very awesome. You're like, this is advanced and you
00:33:12
just get the vibe and it's everywhere. And then you go and you start seeing the
00:33:16
manufacturing base and you see what like Xiai is doing or any of the other there's so many scrappy guys, badass
00:33:24
guys everywhere and you're like f >> they're hungry. >> So does anybody remember the 2008
00:33:32
Olympics in Beijing? Anybody? Does anybody This is a little bit you're down a rabbit hole. Does anybody remember the
00:33:38
opening ceremony? >> And you're like these mofos are taking over. At least that's what they want to
00:33:45
do. That shit's happening. So, I don't have any issue or this is not negativity for me. I'm like, these
00:33:53
guys are killing it. The best idea is winning. They're fiercely They're fiercely going after truth and progress
00:34:00
and they're making [ __ ] happen. Let's step up our game. Okay. But we can also
00:34:05
have a friendly game. Like, we don't have to like be like the Detroit Pistons
00:34:09
in the '90s, you know? >> Yes. We can we there there's a way >> go into the stands.
00:34:14
>> Yeah. Yeah. You know, there's a way to do this, right? And there's a way to do
00:34:18
it like adults. I hope that's where we would end up. Um I have a employee who
00:34:24
because we we we for for a long time we're the largest build kitchen builders
00:34:29
in China. I have an employee in China has an American wife. Okay. They both live in China. They're both from China
00:34:38
originally. Okay. but want him to it would be great for him to work here on some things I'm doing. It's very hard to
00:34:46
make that happen right now. Now, that's selfish like I like maybe selfish like
00:34:51
I'm like there's a person I've been working with for over a decade. I'd love
00:34:54
to continue here. Maybe there's other bigger picture items that I'm not dealing with. I'm not the geopolitical
00:35:01
guy, but I'd love for there to be sort of good relations and good like like if you have
00:35:11
a significant other in who is an American citizen like do we have to make that hard as an example
00:35:18
>> some normaly would >> something you know I'm just saying now I
00:35:21
agree like >> there are ways to do immigration properly like we effed it up super bad
00:35:28
don't to get me started. But there's also there's good migration too. Like a
00:35:33
lot of great innovators all over the place came from other places for their own version of the
00:35:40
American dream. God bless >> Freeberg. >> And we don't have to that doesn't have
00:35:45
to be a negative thing. And so I'd like to see more of that. And um yeah, China's China's wild. So let's uh let's
00:35:53
keep our eye on the ball and let's let's give them a run for their money, too.
00:35:56
>> Give it up for TK. All right. Well done, brother. Thank you. That was good. Good to see you,
00:36:02
brother. Wow. Michael Dell. My lord. Texas native. >> Michael. >> Yes. Born born born in Houston.
00:36:12
>> Well, I missed the the opening. We we jumped to the music, but you started
00:36:16
Dell Computer here in Austin with a thousand bucks >> 42 years ago in my dorm room at Dolby at
00:36:25
UT. uh about 10 days before I finished my freshman semester. >> Amazing. And it's been working out
00:36:35
pretty good. >> Yeah, it's been some bumps in the road, but yeah, it's generally generally
00:36:41
worked out okay. Yeah, we'll have about 140 billion in revenue this year. So,
00:36:47
>> yeah, it's okay. It compounds over time, doesn't it? >> Yeah.
00:36:51
>> Yeah. >> You know, you start small and just keep adding and >> there you That's how it goes. It's just
00:36:56
that easy. >> But why Texas? Like, I think this is an important thing. We're in Austin. Jason
00:37:04
lives here. David Sax lives here now. More people are moving from California to Austin. Why Austin? Why Texas? Why is
00:37:12
it work here? And is it getting better? Is it just always worked? You know, I think Texas has had a
00:37:20
uh, you know, low tax, progrowth, uh, environment for a long time and pro, you know, sort of progressive business
00:37:31
climate. And you know, if you sort of look at the the growth of the Texas economy relative to the rest of the
00:37:38
United States without Texas, you know, Texas just kind of looks like a better version of the US economy.
00:37:46
And uh you know, you now you've got uh Austin is sort of just about in the top
00:37:52
10 cities in in the United States. So you've got uh when that happens, you'll
00:37:59
have four of the 10 largest cities in America in Texas. One out of 10 children born in the United States born in Texas.
00:38:08
Uh more New York Stock Exchange companies in Texas than in New York or anywhere else. And uh you know, you've
00:38:16
got the University of Texas here in Austin, which I always think of as kind of the wellspring for a lot of the
00:38:24
companies that are here. certainly ours and um you know a long history of of uh innovative pioneering spirit and
00:38:36
entrepreneurship and um it's been a fantastic place for us >> and part of this I think Freeberg and
00:38:44
Michael is what's happened in the other great cities or what were once great
00:38:49
cities my hometown New York I got to spend 10 years in LA and the last 12 in um the Bay Area and what's happening
00:38:56
there is incredibly unamerican uh and they're decelerating when compared and I
00:39:03
think maybe the gap maybe and the disparity from these um two locations has gotten greater. Yeah. And you're
00:39:11
seeing a lot more people say life there here in Austin seems a lot better than the life I'm living in New York, LA or
00:39:20
in in the Bay Area. >> Yeah. Well, I've got a lot of new friends and neighbors, you know, that
00:39:24
that have that have that have come. And certainly, I mean, if if you look at the
00:39:27
the the migration statistics, Texas has attracted an enormous number of people and and look, I mean, when you when you
00:39:37
when you look at the environment here and compare it to the other kind of situations that are going on, uh it's
00:39:45
it's it's very attractive. But, you know, it's it's kind of been great for a
00:39:50
long time. So, uh, it's not really new news to us that have been here a while.
00:39:56
>> Yeah. Elon had a great experience when he was building the the Gigafactory over
00:40:01
here. >> They let you do stuff here basically. You know, >> they let him build it
00:40:06
>> which he said was like an incredible experience for him because in California
00:40:10
they didn't let him build, you know, these factories. And in fact, the Tesla
00:40:14
factories that in Fremont was just an old ancient factory that he was able to retrofit. So, uh, there's something
00:40:21
going on here as well with the data centers and and that's actually, I think, very close to what you're working
00:40:25
on at Dell. Maybe you could talk a little bit about the data center boom that's going on in Texas that maybe
00:40:29
people aren't paying attention to. >> Sure. Well, there's, you know, obviously
00:40:34
been enormous buildout of AI infrastructure and that requires, you know, lots of new
00:40:40
data centers, lots of power. Texas, you know, has an enormous uh advantage there
00:40:47
relative to other states. Lot of power, a lot of land, and it's and and you can
00:40:54
build stuff, right? So, there's there's been a massive buildout particularly in
00:40:58
some of the cities in and towns in West Texas where there's not a lot of population and so they're not really too
00:41:05
opposed to having data centers out in the middle of nowhere where there's land
00:41:10
and power. And so um yeah, I mean the the the demand for tokens is enormous. You know,
00:41:18
we've been building these AI data centers not just here in Texas, but around the world. And you know, the
00:41:27
growth in that has been tremendous. You know, we we introduced the the first uh H100 server. It was literally a
00:41:35
couple weeks before Chat GPT was announced. And you know uh the progression of our business in that area
00:41:43
has sort of gone from like 2 billion to 10 billion to 25 billion to this year it'll be like 50 billion. So so
00:41:52
tremendous growth and when when you think about what these models are creating there's this phase change that's
00:42:01
happened in computing right we we we had 60 years of calculating computing. Now we have machines that are thinking and
00:42:08
helping us think. And so the demand for that kind of intelligence and you know the models are amazing but they're also
00:42:16
the worst they'll ever be and they continue to improve. And so we just see uh a lot more demand than supply. And
00:42:26
it's happening not just in the hyperscalers and the cloud service providers. It's happening in 4,000
00:42:34
enterprises where we building these these Dell AI factories. It's happening in sovereign AI, you know, like with
00:42:41
Palunteer and, you know, people want to protect their data but also use AI on it. They want to bring the AI to where
00:42:48
their data is. And you know when this kind of started a few years ago, we had some
00:42:54
really sophisticated uh large companies think of like Fortune 100 and they started you know buying
00:43:02
these AI servers from us and and they kind of knew what they were doing right you know and and uh we said what what
00:43:09
are you doing and and they they were they were kind of taking uh building their own models they were taking open-
00:43:17
source models they were running them some of them were were algorithmic traders or you know derivatives of
00:43:23
machine learning and of course um they needed a lot of help in in doing that cuz it it it was sort of a complicated
00:43:32
thing. So about two years ago, we we put together this product that we we we called the Deli factory and now we've
00:43:42
got 4,000 plus of these and it's kind of running rampant across enterprises.
00:43:49
>> How do you think about the payback time on the investment that's being made? The administration
00:43:56
put in place this accelerated depreciation rule. the cont. >> Yeah, that's very helpful actually.
00:44:02
>> So just for folks to understand that a little bit like if you spend a hundred
00:44:06
billion dollars this year building and data centers and buying infrastructure for those data centers, you get to write
00:44:12
off 100% of that this year. Correct. >> To deduct it. So you don't pay taxes.
00:44:16
You pay way much fewer tax >> and that's in place for 10 years. I think
00:44:20
>> that's a 10ear deal. So it's accelerating the investment. How much is
00:44:25
that helping versus how are you seeing folks rationalize the investment relative to the return they're going to
00:44:32
make and over what time scale? This is still the big question. Is the money really there? The hyperscalers maybe
00:44:37
they're starting to come up but end usage end states are we kind of hey wait
00:44:43
and see we don't know yet or folks are getting 20% ROIC starting in year one
00:44:49
after they've made the investment. You know, I I I can tell you in in our business in in our company, we
00:44:55
definitely see plenty of use cases where the ROI or the improvement in productivity efficiency is 20% or or
00:45:05
greater >> right away. It gets there. >> I mean it, you know, it's not like you
00:45:10
just hit a button and you get 20%. Right? There's there's work required in
00:45:15
thinking through the processes and maybe it's worth a little bit describing that.
00:45:19
So you know when you have a a any company its processes and tools and technology
00:45:26
are a function of what was available at the time it created those things. And so
00:45:31
what you sort of have to do is step back and say all right what's the trajectory
00:45:36
of the improvement of the tools? What outcome are we trying to create? And now let's simplify and standardize the
00:45:45
processes. Get all the tools together. get all the data together and then apply the technology and this really has to be
00:45:55
done in kind of a tops down way. Uh you can't sort of do it spontane in you know
00:46:00
in in silos are not going to spontaneously improve themselves and often that means that you're completely
00:46:07
changing the way the organization works. >> It's like a wholesale rearchitecture.
00:46:12
>> It's a it's a reimagining of the way a company works. And you know, I mean, the
00:46:17
way I described this to our team about 3 years ago is, you know, uh, we were going to have a
00:46:24
new competitor 5 years from now, that would be two years from now, you know, that was in every business that we're in
00:46:30
except they were going to be faster and more innovative and more successful and lower cost and they were going to put us
00:46:37
out of business. And the only way we were going to prevent that is is we're going to become that company. And here's
00:46:42
how we're going to do it. And you know, it excited some people, it scared some
00:46:47
people. And but I actually believe that that's what's going to happen. And and so we've
00:46:54
been dramatically changing our business. I would say the biggest benefit by far is speed. We're much faster at being
00:47:03
able to apply innovations. And so, you know, you look at our at our infrastructure business last quarter
00:47:09
grew 73%. Well, that's kind of unusual for a business of this size. >> And uh you know, this quarter we guided
00:47:21
that it would grow even faster, like 100%. So, >> you've lived through a couple of
00:47:25
paradigm shifts here. The PC revolution obviously you led that. Um and then you of course had you know client server,
00:47:32
the network revolution, online uh internet cloud, mobile. >> Yeah. So each one of those we saw
00:47:40
massive disruption. We were talking in in the green room about hey we used to have a typing pool. There was a mail
00:47:45
room. All these things got abstracted away by the PC andorked PC revolution. Um but it took a decade or two and this
00:47:54
one's happening a lot faster. Yeah. >> Yeah. This one I think it's it's like um
00:47:59
you know a quarter is like a year maybe it's five times faster or something like
00:48:04
that. But but back to your question, I I I would say maybe 10 or 15% of large companies have really figured this out
00:48:12
and the rest of them are kind of fumbling around. And you know, there's a tendency when when you hear about a new
00:48:18
technology to like, oh, let's just let's just go do it. You know, show the boss,
00:48:22
hey, we did AI. You know, >> the board said we got to do AI. We got to do AI, guys.
00:48:27
>> We need AI. Are you proud of me, boss? You know, >> um and >> look at what I made. Exactly. And I also
00:48:35
think you know there's an important point about about uh this which is >> you know the barrier to technology
00:48:42
adoption is is not technology it's culture and leadership and courage right and and so
00:48:51
>> willingness to change and >> and you know if you if you're in a
00:48:55
business that you don't think is changing very much or you know hard change is really hard right you you have
00:49:01
to it can be very uncomfortable you're like, well, we're going to stop doing
00:49:04
that. Well, we don't need this anymore. >> Particularly if your bonus is dependent
00:49:08
on not messing things up. But let's go, let's use the internet as an analogy,
00:49:14
which you saw up close. There were businesses that were internet transition successful. They made the transition.
00:49:23
Maybe Macy's.com versus Sears Robuck, right? Like maybe Macy's did a better
00:49:29
job of taking advantage of the internet than Sears. But then there was internet native businesses that seemed to blow
00:49:35
them all out and maybe Amazon's a good example or um CSN stores whatever they
00:49:41
be Wayfair etc. What's the right way to think about this evolution in industries
00:49:47
generally? Are we going to have their businesses are going to transition successfully and those that aren't and
00:49:53
they're going to die? And is this really going to are we going to see AI native
00:49:57
businesses in every industry come in and just disrupt everything? I believe we will and certainly you know when you
00:50:04
talk to the Collison brothers at Stripe they'll tell you that the rate of growth
00:50:10
of the 2025 cohort companies is about four times faster than the 2018 companies and so every year comp the new
00:50:20
batch of companies are growing faster and faster because they're starting with
00:50:23
all these new tools that you know >> because they see all the new companies
00:50:25
on their platform. >> Exactly. And so when when you think about uh an incumbent company, okay,
00:50:33
that already exists, it has, let's say, it's got brands, it's got balance
00:50:37
sheets, it's got, you know, customer relationships, whatever stuff, right? Okay. Um, but that's sort of like those
00:50:45
are expiring value assets. If it doesn't change quickly and get onto the other
00:50:50
side of this, I think it will go out of business. And which is exactly the speech I gave to our team, you know,
00:50:56
three three years ago. And uh I think, you know, you you you you you have to be uh bold and you got to go
00:51:06
make those changes to to not only survive this, but but to but to thrive. And you know, I think about it
00:51:14
is how do we prepare our company to be ready for the 2030s, >> right? Isn't it like it's much more
00:51:20
it's kind of the story line. There's more to do than there ever was. It's
00:51:24
like when the internet arrive kind of came around, Sears doesn't just need to
00:51:28
sell locally. They can sell to the world. >> Well, sure. I mean, this is the point
00:51:35
when when when we have better tools, we can do way more things, right? And and uh you know, when you know, when I hear
00:51:41
people say, "Oh, you know, um maybe we're just going to have all these great
00:51:48
tools and we we won't do more things. we'll just do the same things with fewer
00:51:52
people. It doesn't sound right to me. I I mean, there'll be some of that, but I
00:51:56
think most of it will be we're just going to do a whole lot more things. We're going to solve a lot more
00:52:00
problems. We're going to accelerate scientific discovery. We're we're we're going to invent all
00:52:06
sorts of new things. We're going to solve all sorts of problems that haven't
00:52:09
been solved. >> And you know, that's that's super exciting. >> What do we have wrong on infrastructure?
00:52:16
So the original build cycle looked a lot like everything's in a data center.
00:52:21
Everything's got to sit there. That's where all the intelligence. It'll all be
00:52:25
in these kind of hosted proprietary cloud models. Do you think that it's open source? Is it distributed on the
00:52:31
edge? Where does the intelligence where does the inference sit? And how does that really change or kind of
00:52:37
rearchitect the industry? Do you think >> it's really all the above? I mean it
00:52:41
it's not like there's one answer. I mean certainly if you go to uh any industrial company or natural
00:52:50
resources company advanced manufacturing retail logistics there's tons of inference at the edge and that's growing
00:52:59
very very fast and uh you know we make a lot of that embedded equipment certainly
00:53:06
you know telos are doing that too I mean it's pretty much every every industry
00:53:10
think about wherever data is being created you want the AI I infrastructure and the inference you know close to the
00:53:17
data. Um you know there there there has been this sort of rebalancing as companies have
00:53:25
figured out you know sort of everybody loves the public cloud right until they get the bill right they get the bill
00:53:32
they're like wait this is supposed to save us money yes >> costs quite a bit more. So, you know,
00:53:37
the the the lowest cost token is going to be the one that's generated right where the data is on the device. You're
00:53:44
going to have, you know, tokens being generated on your phone, on your PC, in every embedded piece of equipment. And
00:53:52
and look, we have an interesting perspective on this business because we have 10,000 customers where they embed
00:53:58
our product in their product. This is you know think medical devices, security, all sorts of things in
00:54:05
hospitals and industrial plants and you know any any kind of uh you know uh datadriven activity right requires some
00:54:16
kind of computing network storage infrastructure. >> Yeah. So when you um look at the desktop
00:54:22
where you started, it's coming full circle and this must be at least very interesting or intriguing to you that
00:54:29
you see this open claw movement. Everybody trying to buy the most powerful desktop they can and all these
00:54:35
hobbyists who were your customers who were calling you up and ordering from, you know, Dell, their their bespoke PC.
00:54:43
Now they're >> Dell.com. >> What did I say? Dell.com. Yeah, >> you said ordering from Dell. Calling us
00:54:48
up. They they they order online usually. >> They order online now. Yes. >> We have this thing called the internet.
00:54:53
>> They do. It works out pretty well. Um but this is incredible that they're like
00:54:59
all stacking computers and and running, you know, uh local models. I was just thinking back to how much the first
00:55:07
couple of computers I owned cost $4,000 in 1980. And then the prices came down. You can
00:55:14
buy a Dell for 500 bucks, 800 bucks, like really nice laptops for that price. Um, use the promo code allin. Um, it's
00:55:23
not a sponsor. It's a joke. Um, but do you think there's a world where we're
00:55:27
going to start to see the desktop because people want to protect that data, they want to protect the skills
00:55:34
they're building. They don't want to give it to Sam Alman, put it in a cloud
00:55:37
somewhere. They don't want to give it to Google, whoever it happens to be. Um,
00:55:41
and that the desktop revolution comes back and everybody's got a $10,000 desktop. Is that coming?
00:55:46
>> I don't know if everyone will have $10,000 desktop, but that would be
00:55:49
great. I mean, you know, uh um you know, so we have this Dell uh portal on hugging face and we
00:55:59
have all these open models and we qualified them on every kind of machine we have and you know there's been
00:56:06
enormous progress in the open source models. You know, Google has these Gemma models, GMMA, and they work really,
00:56:13
really well on small machines. You know, OpenAI has their open- source models. You got the Nvidia Neotron models.
00:56:21
You've got, you know, enormous uh ecosystem of open- source that is, you know, thriving and certainly open
00:56:31
claw and, you know, there'll be some good discussion about that. >> How many people have set up OpenClaw?
00:56:37
Raise your hand. Oh my lord. That's about what a 20% of the audience here. >> Yeah. So, you know, autonomous agents,
00:56:45
um, big deal. And certainly inside companies, there's going to be a lot more
00:56:50
autonomous agents. There are significant security requirements that need to go with that. We need to we need to be able
00:56:56
to authenticate and validate who these agents are and what they're doing and,
00:57:01
you know, have the right controls and and and that sort of thing. >> Yeah. and uh your take on uh AGI and
00:57:11
when we're going to hit it like do you actually think about super intelligence
00:57:14
and AGI and the the the two sets of problems that could solve there and do you have a personal definition that you
00:57:22
like to use for those when you're talking internally with your team of how things are moving?
00:57:28
>> I I I don't really know Jason. Um, you know, I I think if it feels like with
00:57:34
the latest releases, we were talking about this backstage, uh, you know, the Gemini 3.1,
00:57:42
the Opus 4.6, the OpenAI 5.4, it feels like we sort of u hit some kind of threshold where the just the quality of
00:57:52
the the models are are just tremendous. and and and and you know when I listen to what our teams are able to accomplish
00:57:58
in a day or two weeks that would have taken them you know a few months or nine months time you know it's it's just
00:58:06
amazing the speed of of innovation. >> Yeah. And so it it seems to be continuing and we get
00:58:15
all the reinforcement learning and there's also tons of private dark data that these models haven't been applied
00:58:24
to and that's sort of what's happening with these >> I think the auto research is the that's
00:58:29
the the key with auto research the capacity to take a standard model and then retrain it on your private data and
00:58:36
keep it private and build an advantage for your organization based on the history of your data that no one else
00:58:42
has. That seems to be what a lot of folks are thinking about that have the capacity. But if you were to start a
00:58:48
company today that was not in computing and you were to build a business from the ground up, how would you architect
00:58:54
your people and your organizational principles as an AI kind of first knowing what you know about computing
00:59:02
and where things are headed? Are you hiring people? Are you hiring a bunch of people to run a bunch of agents? How do
00:59:08
you think about architecting a new business today? >> It's a great question. I don't really
00:59:12
spend a lot of time thinking about that. You know, I'm thinking about how do how
00:59:15
do I run >> what the rest of us are thinking about. >> How do I how do I run our company? I
00:59:20
mean, that's hard enough. So, >> yeah, everyone I talk to, that's the
00:59:24
question. They're like, everyone goes to these off sites and they're like, I'm
00:59:28
actually doing this with my management team on Monday. We're doing like a tear
00:59:30
down be like, "Hey, how would we build the business differently today?" Knowing
00:59:34
>> I mean what we've been thinking a lot about is it's sort of this this reimagining
00:59:40
question. Yeah. >> You know, sort of all right, we know the trajectory of the tools. What are the
00:59:46
tools going to be in 27 28 29 and how do we accelerate you know our path to that?
00:59:55
How worried are you about social issues? So AI recently ranked as the most unfavorable term of a list of
01:00:04
terms including president. >> It was somewhere between ISIS, the Democrats, ICE, ISIS, and the Democrats.
01:00:11
>> ICE was better than AI. >> People liked ICE mass agents >> more than they like AI.
01:00:17
>> Yeah. Well, I think I think part of the problem is it's been it's been uh you
01:00:23
know maybe sold as >> as you know it it it sort of presents itself like a human would.
01:00:30
>> Yeah. >> Right. And you know maybe if we called it linear algebra
01:00:35
>> matrix multiplication >> and statistics instead >> matrix multiplier maybe that would be
01:00:40
more friendly. I don't know you know. >> Yeah. >> But do you think do you think we're
01:00:43
going to have No, I think you're right. the positioning is wrong and then we're
01:00:47
not communicating to people, hey, this could help healthare, this could make you live longer, this could help your
01:00:52
kids get educated more, that this could help with housing costs, this could help
01:00:56
with food cost. Messaging aside, I mean, how much do you actually worry >> about disruption or dislocation in
01:01:03
employment, about acceleration of earnings for some people and deceleration for other people in society
01:01:10
that feel left behind? And that starts to fuel more of the kind of social concerns and politicians saying, "Hey,
01:01:18
we got to stop building all the data centers, you know, like that kind of stuff." And and how much are you really
01:01:23
>> I I tend to be, you know, more optimistic and and um you know, I I do I
01:01:30
do think that in all technology cycles, you get sort of these network effects and
01:01:37
uh that's kind of inevitable. But I also think, you know, uh we're going to do
01:01:44
more with the tools. You you do have this acceleration of all sorts of uh great things. I mean, education can
01:01:52
dramatically improve, scientific discovery, healthcare, energy, you know, all sort of the the unsolved problems
01:01:59
can can be accelerated. Ultimately, I think it's it's amplification of of
01:02:04
human potential and capability >> and >> extending the frontier, too. And and and
01:02:09
and by the way, we should also remember that basically what we're talking about
01:02:13
here beyond sort of some of the advanced semiconductors in the you know big data
01:02:18
centers, we're talking about software, right? >> Yeah. >> Right. It's like software that runs on
01:02:24
your computer. So you know if somebody says well we don't we don't want that. It's like how
01:02:30
do you stop software I mean >> yeah how are you going to how you going to stop someone putting an open source
01:02:35
model on their computer at home and asking it for medical advice? You know, New York just passed a law saying AI
01:02:39
models can no longer give >> medical advice. Passed, right? It's being proposed.
01:02:44
>> Oh, proposed. It's being proposed. You can't give legal and health advice.
01:02:47
>> We're anti-s software. It's like, >> yeah. Well, we're also anti books and
01:02:50
advice. So, if you were going to look it up in a book, but were you dropping into
01:02:54
your Bernie Sanders right there? >> That was my Bernie Sanders. >> Michael D. 1% of the 1% that you're
01:03:01
enabling with your data centers. Why are you doing this to the people of our great nation while you give your
01:03:08
money to children in the Invest America accounts? >> Yeah, >> this is a good one you're doing.
01:03:14
>> Yeah. Can we talk about Invest America? >> I think he might have even criticized
01:03:17
that, but but you know, >> well, that's the problem. The billionaires are giving our children
01:03:21
money and they're not asking us permission and then those kids are going to buy things that their parents never
01:03:26
asked for. >> Well, they they don't they don't actually get the money till they're 18
01:03:32
years old. So that's that's >> But what gives you the right to give our
01:03:36
children an education? What is this philanthropy? It makes no sense. No, I mean honestly.
01:03:42
>> Well, I see I see my great friend Brad Gersonner here. >> Brad's here.
01:03:47
>> There he is. >> Brad, come up for this little uh segment here. Sit sit for a second. Let's talk
01:03:51
about America. We got 5 minutes left here. >> So, you know, I heard >> everybody the fifth bestie. Give him a
01:03:55
round. >> I didn't know he's going to be here. >> All right. I
01:04:02
>> how did this go down, Michael? >> I I heard about this idea in 2021 from
01:04:07
Brad >> and I thought, you know, that's a that's just a great idea. That's an awesome
01:04:12
idea. And, you know, I think there were some discussions with the prior administration,
01:04:18
but they didn't uh do do anything about that, unfortunately. And um you know, here we are, you know,
01:04:26
a miracle. you know, uh the the the Invest America Act was was passed and um you know, now we have thousands of
01:04:34
companies that are joining in and matching the government's contribution and u you know, Susan and I made a big
01:04:43
announcement uh giving $250 to 25 million children in uh zip codes where the median income is
01:04:54
>> I mean, Michael, let's just let's pause for a second This is one of the greatest
01:05:01
>> What do you think, Bernie? Do you approve? >> I'm going to go with Jake All this. I
01:05:06
just want to pause on this because it is one of the greatest philanthropic gifts
01:05:10
in the history of humanity. And I I people have just kind of glossed over to it because there's a lot of big numbers
01:05:16
in the world, but we're talking about you. You personally, you and Susan sat
01:05:20
down and said, "We're going to give a number." And that number was five, six,
01:05:25
seven billion dollars or this is >> well it's it's $250 to 25 million children ages 2 to 10 in
01:05:34
zip codes where the median income is $150,000 or lession. It's $6.25 billion.
01:05:40
>> I mean and I just want to say something. You know, we live at a time where
01:05:48
>> but they have to sign up to claim the accounts. Yes, >> they they have accounts, but they have
01:05:52
to sign up to claim the accounts. You know, I think we're getting 100,000 plus
01:05:56
kids now a day signing up. >> Yeah. >> First, thanks for having me up. I mean,
01:06:01
what what a national hero and national asset that my friend Michael Dell is, but he understates this
01:06:08
>> because I've been working on this for four years. We've been talking about it
01:06:12
on the All-In Pod. We had a lot of momentum, but behind the scenes, Trump gets elected. Um, and so it's April that
01:06:22
we're in the middle of the tariff strife. April 25, we realize there's only going to be one piece of
01:06:28
legislation that gets passed during Trump's first two years. It'll be the,
01:06:32
you know, this big beautiful bill, the reconciliation bill. And so I I call up Michael and I said, "Michael, we got to
01:06:39
go. We've got five days. We have the it it's drafted in the Senate. We have
01:06:44
bipartisan support, but we have a window and like we ha I have to get in the Oval
01:06:50
Office. We have to get in the Oval Office. And you know, Michael said, you know, what what should the text say? And
01:06:58
you and I had a conversation and you you know uh you know the text to DJT. >> Yes. I I'm not talking out of school.
01:07:06
Listen, Biden, where wherever you sit on the political divide, I will say I've
01:07:10
said this, Trump seeks out ideas from business leaders and he has deep respect for business leaders like Michael Dell.
01:07:18
Like you wherever your politics are, that's just the truth. And the last administration didn't and you know, if
01:07:24
it may have done the same thing >> and and this and I just have to say this, Invest America, it's not a red
01:07:30
idea or a blue idea. It's a red, white, and blue idea, right? It's it's
01:07:34
>> so into the prior conversation when Michael and I first talked about it um
01:07:42
you know it was this is the right thing to do right like we have to reconnect the 70% of people who feel left out and
01:07:50
left behind to the American dream right but this isn't our self-interest this is
01:07:54
about defending the ownership society and capitalism that for 250 years created the greatest
01:08:01
experiment in the history of the world but that's at at risk less than half of people under the age
01:08:06
of 40 have a favorable view of capitalism. So when I talked to you about it the first time, Michael
01:08:11
understood both sides of it. It's the right thing to do and it's the right
01:08:15
thing for the country. And uh so at any rate, Michael Dell, tremendous American I have one just one one punch up the
01:08:26
name invest America Trump accounts. What do you think? >> Were were you considering this in the
01:08:32
context of other philanthropy? I mean, how do you how do you kind of put this together in the spectrum of how you
01:08:37
think about giving back? >> Yeah, great question. So, so you know, we have a foundation that's very focused
01:08:43
on children in urban poverty. That's basically the central focus of the foundation, although folks in uh central
01:08:52
Texas would know that we do a few other things here in our local community. Um, and
01:08:59
you know, when I heard about this idea, one of my thoughts was, "Wow, this is
01:09:03
like a platform for directly giving to the people that we're targeting, right?"
01:09:10
And, you know, we actually thought about doing it just in Texas first. And, um, you know, things have gone pretty well
01:09:19
with the company and all that. So, you know, we thought we just go bigger. And and
01:09:26
what happens, Brad, if you know 10 more Michael Dells show up and and there are dozens of
01:09:33
>> That's not a lot of Michael Dells, let's be honest. But >> there there's a number of folks who
01:09:37
could make an equal size or even greater gift. Um there are people who, you know,
01:09:43
many hands makes for light work. There are a thousand people who can make a gift of significance. What if this
01:09:49
actually becomes a movement and we >> I think I think it actually is becoming
01:09:54
a movement instead of a moment and and and we've you know we've got a lot of
01:09:58
that queued up. Brad, why don't you >> Wait, have you called anybody? Michael,
01:10:02
have you did you call? >> Michael and I chair the Invest America Giving Committee and we're ambitious
01:10:08
guys. >> You're knocking on doors. >> We we've had a few conversations.
01:10:12
>> You're texting people. >> Yeah. >> And so so so just there was a question
01:10:16
earlier. First, it's really important to understand and for you guys to spread
01:10:19
the word. Every child under the age of 18, every child under the age of 18 is eligible to claim their account. Number
01:10:27
one. Number two, you've heard this like, oh, kids born between 25 and 28. No,
01:10:34
this is forever more. The legislation creates this account forever more. Every child born in America starting January
01:10:41
1st, 2027 will automatically get an will get a trump account right at birth stapled to their social security card.
01:10:49
The $1,000 has to be reauthorized every four years. Okay? But the accounts don't. So every kid, this is social
01:10:57
security 2.0. This is the biggest change to the social contract in America in in
01:11:03
50 years. 3.7 million kids a year will get an account that can compound. a 401k from birth. And yes, we're going to have
01:11:11
a lot of announcements, but it's not just billionaires. It's going to be
01:11:16
companies that are donating stock on their IPOs into these accounts. It's going to be wealthy people. It's going
01:11:22
to be states. It's going to be moms and dads. It's going to be corporations. And
01:11:26
the estimate is over 15 years, we can move $5 trillion into the pockets of families that would
01:11:34
have otherwise had zero. $5 trillion, right? And so to me, the leadership that Michael showed not only in helping me
01:11:43
get the meeting that ultimately got this passed into law. And it does take people
01:11:48
like those moments either happen or they don't happen. And if they don't happen,
01:11:53
there's no law. And this doesn't change kids lives. >> By the way, two things on this.
01:11:58
>> If this $5 trillion moved through government programs, it would get incinerated.
01:12:03
>> Exactly. >> That's what we see happen. there's just a million crony structures that take it
01:12:09
away and destroy it. So to give it directly into the accounts is the circumstance. The second thing is it
01:12:14
makes a lot of sense that you guys can I I'll I'll be the lead but can we replace
01:12:20
social security in this country with a defined benefit or defined contribution like this and eventually everyone has a
01:12:27
Trump account or whatever you call it and we don't have to have this fake Ponzi scheme that we call social do we
01:12:34
can do it. Well, they they they have a defined benefit program, but I'm saying
01:12:37
like everyone has an account and they all own a piece of their future. And every time you get a payroll to tax
01:12:41
deduction, instead of it getting inviscerated and destroyed and vaporized, that money actually goes into
01:12:47
an account and you buy a piece of a company and maybe you can direct it. >> Freeberg's getting
01:12:51
>> on July 4th of this year. >> You're getting me wound up. So for all
01:12:54
the there are 4.5 million kids who've claimed their account almost $150,000 a
01:13:00
day will have on the trajectory we're on 10 million by July 4th our 250th anniversary of the country. Every one of
01:13:07
those kids accounts the parents and the kids on July 4th they'll see an app on
01:13:12
their phone that looks a lot like a Robin Hood app that'll see them owning. It'll say you've received your $1,000 or
01:13:19
your $250. you're and it will show a little bit of Nvidia, a little bit of Walmart, a little bit of Dell. We
01:13:25
decompose the S&P 500 which they own into the constituent parts so they can get excited about being an owner in the
01:13:34
upside of America. And when moms and dads doubleclick and Apple pay 510 bucks into the account, right? When they send
01:13:40
their QR codes to their friends on their birthday and now their friends all add to the account or on Christmas or bar
01:13:46
mitzvah and they add to the accounts. When companies add to the accounts, all of this, they see it growing and it
01:13:53
unlocks the human potential. It's not just the money. It's that I'm in the
01:13:59
game. I have a shot. Which to David's point, I think the biggest crime of social security. And we made very clear,
01:14:07
social security is a sacred promise. We we refused and many people tried to get us to to to take on the broader
01:14:14
struggle. And we didn't do it because we knew it it would kill this program. But
01:14:19
but let's be clear about this. Our government requires all of us to give 10% of what we earn into social
01:14:26
security, right? It was the social contract evolution in the industrial revolution that kept kept the country
01:14:32
together. The only problem is it goes into a black hole. Nobody sees it. Nobody knows what's there. But it is
01:14:38
your savings. Now imagine if that same money was required to, you know, government took it away, but it was in
01:14:44
an account with your name on it. You could see it grow. you knew exactly what was there. You could get excited and
01:14:50
say, "Hey, I'm going to add a little bit more to that, right?" And and and you
01:14:53
had a little bit of choice. That to me is uh is the possibility. And I think we will end up there some
01:14:58
>> and and and Brad, thank you for just going to say, you know, Brad Brad also adopted his home state of Indiana.
01:15:11
We have Ray and Barbara Dal Dalio adopted their home state of Connecticut. and many many more to come.
01:15:19
>> And and and look, it's going to be super easy for anybody to add a 100 kids in
01:15:24
your neighborhood, adopt a zip code, adopt a school district, adopt a town. >> It's going to be amazing. Give it up for
01:15:30
one of the great entrepreneurs of our time and an incredible pledge. I'm going all in.
01:15:51
I'm going all in.