00:00:00
All right, everybody. Welcome back to the number one podcast in the world. It's the Allin podcast, episode 274.
00:00:07
Sachs is out today, but we're very lucky to have Gavin Baker from Treaties Management joining us. The spicy takes
00:00:16
must flow. Welcome back to the program. Besty Gavin, >> thanks for having me. Always love it.
00:00:21
>> It's been a huge week in tech. We can start with the SpaceX and OpenAI IPOs.
00:00:26
We've got Andre Karpathy joining Anthropic. Nvidia crushing it. So many different places to go, but I think
00:00:32
we'll start with Andre Carpathy joining Anthropic. Carpathy is only 39 years
00:00:38
old. He's already a legend in the tech industry if you don't know him. I
00:00:41
believe he's also coming to liquidity. Yet, >> he's going to keynote on Monday morning.
00:00:44
>> Oh, fantastic. >> No, Tuesday. Tuesday. Tuesday. Day two. I think he's keing.
00:00:48
>> Okay. As is Gavin. Gavin will be there. Founding member of >> Gavin anchoring day two as
00:00:54
>> excellent. Yeah, this is Gavin's second appearance at >> Look at those two bookmarks. Andre
00:00:58
Carpathy and Gavin Baker. >> Oh, yeah. You know, >> liquidity pulls in the stars.
00:01:03
>> Obviously, Andre was a founding member of OpenAI. He led the self-driving team.
00:01:08
>> Also, hold on. Gavin is going to help us judge the best ideas section as well.
00:01:13
Excellent. >> I don't know if you know that, Gavin, but you're a judge. You're a judge.
00:01:16
>> I'm up for anything, man. I'm easy. >> Yes. Kurpathy also coined the term vibe
00:01:20
coding. He recently built auto research. I think we talked about that here a bit.
00:01:24
That's an open source training tool. It helps AI models improve themselves by
00:01:28
running five-minute experiments. That got over 82,000 stars on GitHub. He did that like as a weekend experiment and
00:01:34
all these civilians started building their own uh recursive LLMs. Really inspiring. And the Andre Karpathy skills
00:01:42
is a tool based on his set of principles for claude code. And somebody just released that. And so that's just pretty
00:01:50
crazy when you think about it. He's going to be in charge of a new pre-training team at Anthropic. The
00:01:55
focus obviously being recursive self-improvement. In other words, they're going to have Claude improve
00:02:01
itself. And they've already talked a little bit about AI improving AI over at
00:02:06
anthropic. What's your take on this? Is this uh super important in 2026? Obviously, Karpathy is super well
00:02:14
respected. is obviously uh you know one of the true talents in the space but hey
00:02:19
we're in we're in a different inning than we were say 10 years ago when he
00:02:22
was at Tesla or five years ago when he co-founded open AI >> you know what's interesting if you go
00:02:27
back to like Google the culture of Google which they got right was the singular technical talents there
00:02:35
they were singled out and they were called Google fellows I don't know if you guys remember this like Ahmed Single
00:02:40
>> Shredar Ramaswami Jeff Dean these guys are stars. And what's interesting is if you track what folks,
00:02:48
particularly Jeff Dean, I guess, now because the other two aren't there anymore, but what they did inside of
00:02:54
Google, it's like wave upon wave, they were at the foot of those waves. What's
00:02:58
interesting about Andre is he's been at the wave upon wave of AI. He was probably the first person that really
00:03:05
commercialized the Richard Sutton bitter lesson essay when he was leading FSD at
00:03:12
Tesla which was really about the brute force computation and I remember him telling me this story I don't know if he
00:03:18
said this publicly or not but where he spent a portion of his time I want to say a quarter of his time labeling data
00:03:24
could you imagine like 201617 like handlabeling video data from Teslas So he did that then he co-founder of open
00:03:33
AI he's a star and he's an exceptional human being and he's super curious and
00:03:38
then what he's done as a kind of a free agent is also quite impressive. So I
00:03:43
think that this is a really important deal. I think he's one of these really
00:03:48
curious people that can be sent off and they'll just go and invent new things.
00:03:54
And I think this idea of recursive self-learning puts these models on a combination of overdrive and
00:04:02
autopilot. And so if you put those two things together, I think that you start to
00:04:08
you can potentially live out this idea that there's an order of magnitude improvement on a yearly basis. So like
00:04:15
this new form of Moore's law. So then the model quality just goes absolutely
00:04:19
parabolically just like this straight up. throwing a bunch of compute at the problem and these things learn really
00:04:25
quick. >> I think is the high order bit there. Gavin, what are you what's your take on
00:04:31
Anthropic's recent success and their massive hiring binge? >> The success is extraordinary. It's
00:04:37
undeniable. I think the fact that they are now they were EBIT positive per the Wall Street Journal in the most recent
00:04:44
quarter is a really important fact for kind of the whole AI narrative because now there's
00:04:52
you know you could talk about circular funding you could talk about ROI and we could go look at the ROIC of the
00:04:57
hyperscalers but if OpenAI and Enthropic are at call it a hundred billion dollars of ARR now
00:05:05
with 80%ish gross margins on inference like the returns are there and then if we add in
00:05:12
and they're growing really fast if we add in Gemini we add in cursor we add in
00:05:16
XAI we add in open source you know it's it's not hard to see 200 300 400 billion
00:05:25
of ARR at the end of this year at high market >> across all of the language models and
00:05:31
you're talking specifically about the private language model companies maybe
00:05:35
not Google which is including But I was excluding you know a lot of the returns to this GPU spend have come
00:05:42
from you know better recommener systems at Facebook and Google Amazon better ad targeting better ad measurement.
00:05:51
>> Sure. So I was excluding that and just narrowing it to LLMs which I think
00:05:56
strictest possible definition and it seems like there's going to be a really
00:06:02
strong ROI this year even excluding what are still some of the most economically
00:06:07
important and profitable use cases for GPUs and AI infrastructure. I do think what Karpathi is working on recursive
00:06:15
self-improvement is really important and unlocking that and continual learning you know maybe the two final frontiers
00:06:24
for for AI and just the idea of recursive self-improvement that the model while it
00:06:31
is training you know during a forward pass has input into its training or another
00:06:39
model has input into the training I think that could be really powerful and I think Chimamoth's statistics of of
00:06:49
you know 10xing every year you know might seem conservative if that comes to pass and then of course
00:06:55
continual learning is the holy grail where the model learns from experiences the way humans do.
00:07:03
>> Yeah. >> And that's something we haven't unlocked yet. And those those those two combined
00:07:08
I think would um they might pull the future forward in a very real way. >> Yeah. And we have right now Enthropic
00:07:15
has a decent lead on everybody else whether it's 3 months or 6 months. Obviously they're probably 6 12 months
00:07:20
ahead of open source. Maybe they're three six nine months ahead of their contemporaries but they have a lead. You
00:07:25
put Cararpathy in there Freedberg. Now you have Karpathy. He does recursive. And at some point, and it may have even
00:07:33
occurred at anthropic, the AI is going to be improving the language model more than the humans in the loop are doing
00:07:45
it. Obviously, they're orchestrating it, Freeberg. But at what point do we think
00:07:50
this, let's call it super recursiveness occurs? When will we cross the recursive
00:07:55
valley? And AI is doing more to build a language model than humans are. I'm not sure when this idea that you
00:08:05
feed the whole model into a context window to train itself and build a new model is going to happen, but I think
00:08:11
there's probably a lot of different architectural paths that could be walked
00:08:14
here. One of which is this idea that you could make much smaller models and then
00:08:19
create networks of smaller models that work together where you ultimately have less energy or less cost per token
00:08:26
produced out of a aggregation of models than you did with one single large model. I've said this probably three or
00:08:32
four times now. There's a lot of work and a lot of opportunity ahead in kind
00:08:37
of rearchitecting models and rearchitecting how models work together to solve problems. My guess is a lot of
00:08:44
leadership that that he can bring to exploring those paths and all it takes is a minor breakthrough and your cost
00:08:51
per token drops in half. That's a tremendous efficiency gain that is seems very much on the horizon because some of
00:08:57
the early papers I think I shared one from MIT a few weeks ago indicate that there's a lot of room to run here in
00:09:04
terms of rearchitecting models and deployment of models. these very small uh models uh the small language models
00:09:11
and then verticalized ones are the future. We've got a company Abocus that's doing it for corporations
00:09:17
crushing it. Everybody's got an interest in doing this. And I don't know if you
00:09:20
saw the news this week uh Chimoth it happened about two weeks ago very quietly Chrome included
00:09:27
Gemini or Google included in their Chrome browser the Gemini Nano model without telling anybody. 4 gigabytes on
00:09:34
your computer and that's the one that does like proof reading, spelling, autocomplete, all that. So now we have
00:09:41
Google covertly installing this on everybody's operating system. >> Hold on, hold on. Covert's a strong
00:09:48
word, so let's not use that word. >> Without telling people, without giving
00:09:51
people a heads up, >> let's say it in a way that we can both agree. We're in the phase now where I think
00:09:58
breathlessly talking about every model improvement is a waste of time. there's
00:10:02
no ROI in it. We are on a path of accelerated learning and we're going to start to see enduser achievements that
00:10:11
were here to for impossible. That should be the focus. So for example, we were able to solve I'm just collectively
00:10:19
saying we in this case it was specifically open AI by the use of a human and this is
00:10:26
important you know a math problem that stood outstanding not been solved for decades and decades
00:10:33
I can tell you in a different example there are drug candidates that are about to enter clinical trials and INDs that
00:10:40
were sitting on the shelf and people didn't think were very viable at So, we're at the phase now where these
00:10:47
things are front and center. They're useful to people. They're increasingly
00:10:51
valuable. I think what we should do now is focus on these end user use cases because the way that you say
00:10:59
it, in my opinion, is part of the problem because it starts to create this boogeyman us versus them thing. And I'm
00:11:06
not saying you're doing it on purpose, but I'm saying this is exactly why I
00:11:10
think so many people are becoming sort of like it's a four-letter word now when
00:11:14
you mention AI because it's presented as this thing. And I think we have to present the other side of it at least so
00:11:20
that people have the data. So I don't think Google's in the business of doing
00:11:24
or shady things. I don't they're not that company. There are other companies
00:11:28
that would referring to your alma mada. >> I'm not going to say which ones. Okay.
00:11:35
But Google is not that company. So I I think that the reason they did it was probably because there's user utility.
00:11:40
And my point is we should focus on the user utility because I think that's the
00:11:43
story worth telling from now on because I think we collectively, the four of us can responsibly tell both sides of the
00:11:49
story in a well balanced way because I think nobody wins if we become bloodites and go back in time.
00:11:55
>> Yeah. >> And I think that if we don't if we're not careful with our words, that's what
00:11:59
will happen. >> Yeah. And by the way, uh obviously not a lite, but this is what you know has been
00:12:06
reported by a lot of folks that people were surprised, shocked when they saw the
00:12:12
size of the model being done in the background and it has triggered some uh people looking at it around privacy and
00:12:19
I do agree that Google is not a bad actor in the space. So probably a speed arrow more than anything I would say.
00:12:28
>> Maybe just add two things. Um there's attorney maxing and then there's
00:12:33
attorney maxed and Google is probably attorney maxed. >> Yes. >> Yeah.
00:12:38
>> And have been for a long time. And the second second thing I would say is I do
00:12:42
think it's incumbent on all of us as Americans who are involved in the technology industry in one way or
00:12:47
another >> to be advocates for a the positive optimistic possibilities that AI
00:12:55
introduces to to everyone in this world because it it is starting to feel or seem like there may be a CCP funded
00:13:05
campaign against AI and data centers in America. And that's very logical for China, but
00:13:13
it is not good for America. And so I just I think it's it we all have responsibility is what I would say.
00:13:22
>> Yeah. Who do you think's doing a poor job at that and responsible for this? Is
00:13:26
it Daario with his constant, hey, everybody's going to lose their job? Who's responsible for this? Is it the
00:13:33
CEOs blaming AI for their layoffs? What's your take on this, Gavin? Look at hold on a second. Everybody is trading
00:13:41
their own book. It makes enormous sense for Daario to try to create the boundary
00:13:46
conditions for a regulatory moat because he will be inside of the tent pissing out. He's big enough now. And if you
00:13:55
notice that a lot of the breathlessness has ramped up and Jason, we've talked
00:14:00
about this. You can annotate successive rounds of fundraising and successive scale with the volume. So, I think that
00:14:08
it's a reasonable business strategy and I think that he's quite clever and I
00:14:12
think that look, if you actually and I and I do this, if you actually just have a Nashbot, a Nash agent inside of Quad
00:14:18
and you ask it what it would do, it would come up with this strategy. And meanwhile, there are other versions of
00:14:23
other counter strategies and counterexloitative strategies. The point is that each CEO has a clear incentive.
00:14:30
They're operating at such a level of scale that they're they're just reading
00:14:35
their own book. >> So it's it's up to us to take a step back and actually see the forest from
00:14:41
the trees. I think Nick, can you find this? There was a clip of Sham Sankar, friend of the pod, fabulous guy, the CTO
00:14:47
of Palunteer, and he was I think he was on Fox News and he said, "Stop breathlessly asking
00:14:53
these model makers what they think. go to the end user and ask the person in the factory that's using the model and
00:15:00
ask him what he or she thinks. Ask what the doctor thinks, ask what the scientist thinks and start to tell those
00:15:06
stories. That's what we should be talking about. >> Yeah. And Gavin, you were I was sort of
00:15:11
asking you your opinion on what's what's who's causing this and then what's the
00:15:16
solution? Like do you do you have folks you think in the industry who are representing it particularly well? we
00:15:22
can point out, hey, Elon has said we're going to move to a world of incredible
00:15:26
abundance and working will be optional. I think that's on the margin a little
00:15:30
scary for people to hear because they hear no job. But he does say, hey, universal basic income is probably going
00:15:36
to have to come into, you know, place. He said that multiple times. You have Daario, according to Chimath talking his
00:15:43
own book, scaring the be Jesus out of people in order to get regulatory capture. What do you think is going on
00:15:50
here and how can we do better as an industry? >> I think Jimoth outlined like a very
00:15:56
viable and positive path forward. We're just, you know, real people who are not,
00:16:02
you know, at the tip of the spear. These are the positive impacts AI's had on my
00:16:06
life. I was at a I was at I was at an event maybe 10 days ago and someone who runs a hedge fund, his daughter was born
00:16:14
with a very rare genetic mutation that effectively would have normally condemned her to a life devoid of joy,
00:16:23
meaning everything the neurons in her brain were not firing. So she wouldn't, you know, who
00:16:31
knows what her life expectancy would have been or what the quality of her life would would have been. and it's
00:16:36
it's a tragic disease. He said he didn't accept that as an answer. He found he did an enormous
00:16:43
amount of research with LLMs and found an existing safe drug on the market that they thought would have a meaningful
00:16:50
impact on his daughter's condition and it did. It took I think the percentage
00:16:56
of times the neurods were firing was 30 or 40% and it took it up to 80 or 90%. And that means that she can live a
00:17:04
normal life. She may not be as smart as she would have been, but she can live a normal life. And he's now figured out
00:17:12
how to use AI, how to to further tailor that drug. And you know, there've been
00:17:16
all sorts of advances in protein design, etc., etc. And he's reasonably confident
00:17:23
he's going to have a drug in months that is a complete cure. And that's just one
00:17:29
person, one dad who was unwilling to accept defeat for his daughter and who changed her life and the life of
00:17:36
everyone else with that disease. And we tell those stories. So I think Elon's
00:17:40
doing a good job. A future where work is optional. I think that sounds great to some people, you know, scary to others.
00:17:47
You know, a 4-day work week, you know, I think is is probably something that sounds sounds good to a lot of people. I
00:17:52
think Jensen is doing a good job of being an effective advocate. And I do think anyone who is trying to drive
00:17:59
reggget I just we need to stay focused on the positives as well. >> Yeah Freeberg what's your take here on
00:18:08
the AI PR crisis if we'll call it that? Uh we had three different commencement
00:18:15
speeches that were booed. Eric Schmidt being one of them, two other ones by maybe less notable folks.
00:18:23
when you hear young people booing AI viferously, why are they doing that, Freeberg? And what's your take on the
00:18:30
overall PR problem and how to turn it around? >> Uh, that's a there's a long answer to that question.
00:18:40
Um, >> it relates in some ways to your concerns about socialism and polarization.
00:18:46
>> The long answer. >> What's the long answer? >> I mean, that's like
00:18:50
like why do people hate technology? the greatest technological why do they >> this technology they love their phones
00:18:58
they love the internet this technology they >> I think that there's like an underlying
00:19:07
view that technology creates leverage for a small group of people which creates power imbalances and nothing
00:19:16
represents that more than AI that a small number of people that control and profit from and benefit from AI are
00:19:26
going to end up getting outsides returns relative to the broader population that
00:19:32
the time to diffusion of the technology because ultimately all technologies like
00:19:37
commoditize and diffuse but the time to diffusion here is such that it's going
00:19:43
to be like extremely asymmetric for society and I think that there is something fundamental about that it's
00:19:49
like you know nuclear bombs I think really created this this moment in people's minds in the mid 20th century
00:19:56
that by the back half of the 20th century gave everyone a high degree of skepticism about technology and science
00:20:01
generally that those who have the knowledge and those who engineer solutions with the knowledge can create
00:20:08
outsized advantages for themselves and it puts the rest of us at risk the rest of the world the rest of the population
00:20:13
at risk and because those questions about when does this benefit me how does it benefit me can't be answered today
00:20:21
the economic benefit that's acrewing to the few today becomes the narrative. It
00:20:26
becomes the story and it becomes this like power system that a few people take from the many. And so there's something
00:20:33
deeply disturbing for the average person about that. They don't understand how it
00:20:38
works, why it works, what it'll do for them, when it will do it, and all that
00:20:41
they're being told is that some people are making trillions of dollars. So I
00:20:45
think that it's pretty obvious why this has got such a backlash. Secondly, I
00:20:49
think that there's a deep amount of external energy that's fueling this anti-technology sentiment in the United
00:20:55
States and has been for decades. I think to Gavin's point, I don't think it's
00:20:58
just China with NOS's today. I think that there is a long history of state actors intervening in media
00:21:07
activities in foreign nations to try and create the sentiment and fuel a sentiment that reduces progress in that
00:21:16
competitive state. I think this goes all the way back to KGB design during the Cold War and it's been refined and honed
00:21:25
and improved over time. This is not just some conspiracy theory. There are plenty
00:21:28
of great books about this. The techniques of what's going on specifically today, I don't know enough.
00:21:33
I don't have any great details on that. But I don't think that there's no
00:21:36
foreign interest in seeing technology advancement slow in competitive nations. The United States
00:21:44
probably does similar things to other nations. And I think that that's probably a key part of this. And then I
00:21:50
think this this like third piece is like when the capernac revolution happened it
00:21:56
was a mind you know like helioentricity was a totally new way of thinking for humans and it was uh deeply disruptive
00:22:03
to the church and it was deeply disruptive to the power centers which were the centers that could tell people
00:22:11
earth is at the center of the universe. We're in control. We're the direct
00:22:14
channel to God. And the idea that the sun is at the center of the solar system and we spin around it and we're a tiny
00:22:19
speck in the universe was very hard for people to grasp. There's something about
00:22:24
AI that's very like not humanentric and it kind of shifts and fs with the ego of
00:22:30
the human. It's it's almost anti-humanist and I think that that's like a deep
00:22:35
psychological current a lot of people and their disdain for this technology. It fuels it. It's not the cause but I
00:22:41
think it fuels it. So I think there's a lot of complicated aspects to this Jal.
00:22:45
You know, I don't think there's like a simple put put Sham on on a podcast and
00:22:48
he'll solve the problems with AI right now. I think that there's a real set of
00:22:52
shifts happening >> and there's a real set of global competition underway
00:22:57
where you know various state actors and interests are competing with each other >> do you think that we should slow down?
00:23:06
>> I don't think you can. >> No, no, no. Do you think we should slow
00:23:09
down? >> No. I I think I was just talking to some people on a Zoom right before this, but
00:23:13
I think after the Manhattan project, the research labs were stood up to maintain
00:23:17
our scientists that worked on the the Manhattan project from effectively leeching back or leaking back to Russia
00:23:25
and Germany and and and other places that that were adversary to the United States.
00:23:30
And they all were against the nuclear bomb. They worked on it because it was necessary for the United States
00:23:36
security. But then when Russia got a hold of the secrets, they were leaked because people were worried that if the
00:23:40
US had all the power, there would be no counterbalance to the power. And so the the nuclear secrets were leaked to
00:23:47
Russia for that purpose. Then when Russia had the nuclear secrets and they began developing hydrogen fusion bombs
00:23:55
and it it was clear that they were going to race ahead, the United States raced ahead with developing nuclear bombs as a
00:24:00
counterbalance to Russia. When the proliferation began, there was no stopping it. it began and you have to
00:24:06
have this balance in the world otherwise you have effectively an asymmetric power
00:24:11
that can do whatever it wants globally. I think there's that moment in the world
00:24:15
right now where if the United States does not advance its AI technology, the availability of it, TBD industry,
00:24:24
taxation, all these all these things that we're talking about doing, there will be someone else that will. And if
00:24:30
someone else does, we can go through what would happen. There's a there's a
00:24:34
complicated game theory on this, but what would happen if China had sufficiently advanced models and
00:24:39
sufficiently advanced scaled deployment of those models relative to the United States? As you do that analysis, you
00:24:45
realize, wait a second, that's probably not a healthy place for the world to be.
00:24:49
It's also probably not a healthy place for the United States to be the only one
00:24:52
with AI. And so I I think what we end up seeing is if we do try and slow down AI, we
00:25:00
kind of lose this moment of balance that's necessary when you have a technology proliferation like we saw
00:25:06
with the arms race after World War II that, you know, we're going to see again
00:25:10
here. >> Chimath, you I think bring up a good point. You know, should we slow it down
00:25:15
or could we slow it down? There actually have been some discussions about ways to
00:25:20
do this. One of them would be, hey, with self-driving, people are scared that all
00:25:24
these cab drivers are going to lose their jobs. Uber drivers, cab drivers, bus drivers, truck drivers. This is, you
00:25:31
know, over 10 million people in the United States driving things for a living. Would you be in favor of some of
00:25:37
the announcements that that will be a paced roll out? It won't happen all at
00:25:43
once. In other words, those people will be giving some amount of job security to
00:25:46
stay behind the wheel with it. Another example that's been given is if you put
00:25:51
Optimus into Amazon factories or the figure robot just did like a week of just sorting packages. I'm sure
00:25:57
everybody saw that video. We'll insert it here. That figure robot sorting things. Hey, if Amazon deploys those,
00:26:02
there'll be a tax on those per hour and we'll tax humanoid robots in some ways
00:26:07
and then use that for say retraining people. Those are two very specific conditions and approaches that people
00:26:14
have been promoting. Do either of those resonate with you in any way? I think it's
00:26:21
interesting that in all of those discussions, I've yet to see an actual survey of only the truck drivers and
00:26:27
only the package sorters. >> The question that I would have is, do the people that do these jobs want these
00:26:33
jobs? And if they do, then there's a reasonable claim to make to keep those jobs the way that they are. If you're
00:26:39
saying this is the job that I do, I love it. I'm able to provide for my family.
00:26:43
Great. That's a very different argument than well you know what Amazon has 35 or
00:26:48
40% churn inside of their warehouses and we should probably ask the question why
00:26:54
is that because if it was such a great job I suspect the churn would be 3 or 4%. So what exactly is it that we want
00:27:02
to protect and have you asked them? And I think that this is just again a bunch of people in the peanut gallery who want
00:27:10
to take a moral high ground and try to make some other group of people feel guilty or feel bad. At no point are we
00:27:17
actually asking the conversation that that we should be having, which is it's
00:27:23
interesting to me that the there was supposed to be an EO an exe a presidential executive order that was
00:27:27
announced today and then it was pulled. It was scrubbed at the last minute. >> Did you guys notice that? And yesterday
00:27:33
what was leaked was everybody that was attending. It was all the big Neolabs CEOs and it was all the big hyperscaler
00:27:39
CEOs >> including friend of the pod Nick Aurora. Shout out to Nick. And then it was
00:27:45
scrubbed an hour ago. Why was it scrubbed? And the president said that there were aspects of the bill that he
00:27:52
didn't agree with. And as far as we can tell, the aspects would have required
00:27:56
some amount of supervision, insight, review from the federal government >> of language models specifically of these
00:28:03
frontier models is what I read. >> Not language models because I think just
00:28:07
of AI because there's going to be many different kinds. They're not always
00:28:09
going to be language models, but of AI. So look, I think Freeberg is is right. We are in a proliferation with China. I
00:28:17
think it's actually good that China is less than nine months behind us. I think it allows us to find a detant
00:28:24
where we have a certain magnitude of capability that they also have and that allows all of us to then seek peace and
00:28:32
abundance and the fact that we are orthogonal societies, we are organized differently increases the probability of
00:28:38
finding peace using the Renee Gerard kind of framework of mimetic theory than if if it was like us and another country
00:28:45
that was exactly similar to us. So I think what we need to do, we probably need KYC. I think that that
00:28:54
should be something that us in China get together and say you don't want it to
00:28:58
get into the hands of people you can't control. You probably already KYC those
00:29:01
models anyway inside of China. You already review those training runs before you allow these models to get
00:29:06
released. We already know that that's happening. >> Yes. >> So we should probably do some sort of
00:29:10
KYC so some crazy person doesn't create some biological weapon. I think that
00:29:14
those are like some reasonable ground rules. But otherwise, Freeberg is right. You have to take a a little bit of a
00:29:19
deterministic view here, which is that we are in this existential race and we need to get to the place where each of
00:29:26
us, meaning us in China, can look each other in the eye and say, "All right,
00:29:29
weapons down, so to speak." >> Gavin, I'm going to hold you to answer
00:29:33
two questions. One, should we run Frontier models? Because that's specifically what was mentioned in the
00:29:40
leak about the EO Frontier models, the powerful ones. Should they be run through some sort of testing before
00:29:45
they're released? And should there be some regulatory framework for that? That's my first question to you. Yes or
00:29:50
no question. And then you can explain your answer. >> Jeez. Like I just think it's such a
00:29:57
complicated topic. It feels we're a little early for that. I don't love the idea of the United States um
00:30:08
doing it and no one else doing it. I like I think in a world where we hold hands with China
00:30:17
I think that's that's much more palatable and we are aligned and we trust each other and have kind of
00:30:23
verification uh capabilities I do think yeah let me then rephrase it should China and the US
00:30:31
come up with a simple battery of things that have to be tested before these go out including boweapons
00:30:38
terrorism and and that genre of in that vertical of just really known dangerous things just like the FDA might test for
00:30:46
poisons or contaminants in a food or a drug. Would you be in favor of that? I'm
00:30:50
curious. >> So, a few things like the one one thing that's great about America is there is
00:30:57
or one thing that's just we have other forms of regulation. >> Self-regulation. Sure. We have self one
00:31:05
we have self-regulation also we have the courts and if an AI model company behaves irresponsibly
00:31:13
they know that there are ways that people who have been harmed can seek recourse
00:31:19
and so we already have a system that encourages responsible behavior on the part of the model makers. That's a great
00:31:28
point because OpenAI is being sued right now by a kid who who killed themselves after talking to OpenAI's model. So
00:31:34
you're you're correct in that. Yes. After the fact. Yeah. >> And we will see we'll soon we'll see
00:31:37
more of that. I just you know to me once you give something give a power to the government.
00:31:45
>> It's almost never taken back and it tends to grow >> and it's kind of a one-way a one-way
00:31:51
path. >> Oneway ratchet. Yeah. >> Yeah. Second question then. Chimath was
00:31:56
saying, "Hey, nobody listens to the, you know, these cab drivers or maybe the um
00:32:00
people sorting the packages. Do they want the jobs or not?" Actually, the UK,
00:32:04
there was just a 60-minute special and UK and also Boston and New York are pretty adamant that they want humans to
00:32:11
stay and they want to ban self-driving in those locations or severely limited or maybe limit it in some way to let
00:32:18
those people keep their jobs. How do you feel about that possibility? Is that something you think society should be
00:32:24
open to some gradual licensing? >> They're going to get sued for wrongful
00:32:28
death. When somebody runs over somebody else and you could have implemented a solution that has a zero death rate,
00:32:33
that's very different from package sorting. >> Okay. >> Go talk to the package sorters is what I
00:32:38
say. Go talk to the people inside the Amazon warehouse. Ask them what they would rather do at Amazon. Ask them.
00:32:44
>> Yeah. Sure. But Gavin, what are what are your thoughts here on either one of
00:32:47
those examples here? I think going to a city where you can't get in a Whimo or a
00:32:51
cyber cab is going to feel barbaric and unsafe until you >> agree. Strongly agree.
00:32:57
>> I don't know if you remember, but the early days of Uber, sometimes you go to
00:33:01
a city where there was no Uber. >> Yeah. It'd be incredibly frustrating.
00:33:04
>> Well, I'm not going to come back until they have Uber. It's so inconvenient.
00:33:08
And I think so whatever individual municipalities decide, I do think one Chimas's point is really powerful.
00:33:16
There's 50,000 automotive deaths per year in the United States if I recall correctly and a million globally and you
00:33:24
know that's not tolerable and there will for sure be wrongful death lawsuits and
00:33:28
then just from a convenience and quality of life perspective I just don't think
00:33:32
it's going to persist and that's another great thing about America is you know
00:33:37
you have this patchwork of different states and municipalities and each one doing things in a different way and I'm
00:33:43
not suggesting that's good for AI But it does tend to you know has historically the curly effect aside led
00:33:53
to you know I think more positive outcomes where cities and states compete you the curly effect being it is
00:34:00
>> yeah this is a really important point you're making Gavin with flock safety as
00:34:05
but one example we had a an AI there's an AI tool called flax safety it's
00:34:09
cameras that use AI monitor people who are committing crimes there's a privacy
00:34:13
issue around it is bottom up. You just do it by town. It's not top down. And
00:34:17
states can regulate it. Same thing will probably happen with self-driving. And states will probably have some say in
00:34:23
how AI is deployed, even if maybe some centralized governments don't want to do
00:34:28
that. I really think this only comes down to >> the block safety thing. I think it's so
00:34:32
good, Jason. Crime is now a choice. >> Yeah. >> You know, I think the the Cambridge City
00:34:37
Council voted >> to turn off gunshot detectors two days ago. >> And >> wait, which city did that? What you mean
00:34:44
about Harvard? >> Cambridge Cambridge Cambridge. That's the place where Harvard is.
00:34:48
>> That's a place where Harvard is. >> So the geniuses coming out of Harvard in
00:34:51
that town decided gunshot detection >> shouldn't occur. We you don't want
00:34:58
gunshot detection. >> It's wild because you know there's there's a theory that it disadvantages
00:35:03
you know that it might lead to an illegal migrant shooting a gun being apprehended and we don't want that.
00:35:10
>> Got it. and A16Z had a great essay on flock. We can really really solve crime and
00:35:19
it's just a choice and different states and municipalities will make different
00:35:22
choices to be pro-rime or anti-rime and I'm sure they don't cast it as pro-
00:35:27
crime. There's an, you know, some sort of, you know, moral or ethical reason
00:35:32
they're making that choice. But people will vote with their feet over time and
00:35:36
then voters will vote with their votes and we'll see what works. >> Have you guys been to Vegas recently? My
00:35:42
wife and I went to visit Vegas and we spent the the afternoon with Ben Horowitz and his wife Felicia. She has
00:35:49
done this incredible job with the Las Vegas Police Department. It is one of the most impressive things I've ever
00:35:54
seen. And to your point, crime is an option and they've said no. So what happens there is they have
00:36:00
gunshot detection. They have drones that get deployed off the roof of the police
00:36:04
building. We were sitting inside of mission control where you see it happening, Jason. If something happens,
00:36:10
they have eyes on site within minutes. They can track offenders and bad guys all the way to wherever they're hiding.
00:36:17
And you walk out of it and you feel incredibly safe, like they're really on top of it. And when you understand the
00:36:23
level of investment, it's not it doesn't take billions of dollars. >> It's dimminimous compared to the cost.
00:36:29
It's dimminimous. It's >> especially when compared to the cost of the crime occurring.
00:36:33
>> Exactly. If you gave the Las Vegas Police Department 30 $40 million a year, it would be the
00:36:39
safest city in America and that's all it would take. >> Yep. Exactly. And the for the privacy
00:36:44
concerns, Freeberg, there are very simple solutions to this. I I am a privacy advocate myself. Of course, we
00:36:49
all want some level of privacy. I I had the Flock CEO in this week in startups twice in the past 10 years. He's very
00:36:55
considered. And the way they do it with Flock is they allow you to have a rolling database and I think there's a
00:37:02
maximum you can save the license plates for and they don't do facial recognition. I I don't see why not but
00:37:07
let's put that aside. You can only keep it for 2 or 3 years and then they insist
00:37:11
on having an audit trail in it. So there are all little things you can do on the
00:37:14
back end to protect privacy with audit trails etc. We got a lot more to get to in the docket. I just want to just give
00:37:19
my final thoughts on what we're talking about here in terms of the AI problem
00:37:24
and the PR problem. I think we have to recognize that the layoffs that are occurring in big tech and in a lot of
00:37:32
these places are not just the bloating issue anymore. And I'm just going to point to two factors that I think are
00:37:38
scaring the be Jesus out of people. And we just have to admit that this is occurring as opposed to we've been
00:37:43
debating it here. Is it occurring? Is this just cover? and are we AI washing? The first one I want to give you an
00:37:48
example of is Matthew Prince who's the CEO of Cloudflare. Incredible company,
00:37:53
public company. Two weeks ago, I laid off more than 20% of my workforce. I didn't do it because CloudFare is
00:37:58
struggling. We posted record revenue growth, have strong free cash flow, and are adding an unprecedented number of
00:38:04
customers, yada yada yada. And he says basically he's getting rid of measurers.
00:38:09
Measurers are the people who manage people and who measure data. and he just says, "We're getting rid of all those
00:38:15
people. They're unnecessary because of AI, and we'll be adding to people in
00:38:19
other positions." At the same time, Zuckerberg did another round of layoffs,
00:38:24
and they were done in a way that people felt was not considered and a bit um what's the word?
00:38:34
>> Dystopian. >> Dystopian. Thank you, sir. Uh he did him in a in a pretty dystopian way. Here's
00:38:40
Zuckerberg for 30 seconds. In general, the average intelligence of the people who are at this company is significantly
00:38:47
higher than the average set of people that you can get to do tasks if you're
00:38:51
working through the contract um through through these contractors. So if we're
00:38:56
trying to teach the models coding for example, then having people internally u build tools that or or solve tasks that
00:39:05
um that help teach the model how to code we think is going to dramatically increase our model's coding ability
00:39:10
faster than what others in the industry have the capability to do who don't have
00:39:14
thousands and thousands of extremely strong engineers at their company. >> Okay. So what Zuckerberg did at the same
00:39:21
time concurrently he told everybody we're laying off these 8,000 people. A lot of those people are incredibly
00:39:26
talented. Some of them are on H-1B visas. Creates all kinds of chaos for them in their
00:39:30
personal lives and obviously they're having record profits there as well. At the same time he was laying off those
00:39:36
8,000 people. This is after tens of thousands of layoffs before which were obviously because of bloating. He said
00:39:41
we're putting recording software on every single person in the company's
00:39:44
computers to study and train our model. And people were like, "Oh," and previous
00:39:49
people said, "I built during the AI hackathons they had months ago, I built
00:39:55
all this AI tools to make my job uh more efficient." And then Zuckerberg laid me
00:40:00
off. So the now p the perception people have now, and it's quite correct, I think, is the most you can hope for here
00:40:07
is you keep this job for some amount of time and train your way out of it, and hopefully there's some more work for
00:40:12
you, but they're studying you. And Zuckerberg just said it plainly there. Hey, we're going to study everybody here
00:40:17
and that's going to lead to more replacements. This is scaring the Jesus out of people and we need to have an
00:40:22
answer for it. Yeah. >> I thought the Matthew Prince note was horrible. >> Okay, explain.
00:40:28
>> This was like from the PR school of retards. >> Okay, here we go.
00:40:34
>> You could not have written a worse memo. It's like you reduce humans to a label
00:40:40
called the measurer and then you're like, I'm going to lay off all the measurers.
00:40:45
I mean, I just think that part of this, again, I'll go back to the and maybe the Sham
00:40:52
Sankar quote that I'm thinking about should be extended beyond the model makers. Can you just play this for one
00:40:58
second and I'll tell you why I think this is too >> and then we'll go on to the S1 from
00:41:02
SpaceX. >> We're listening too much to the inventors of AI. I know that's
00:41:05
appealing. They're geniuses. They're smart. We need to be listening to the
00:41:08
frontline factory workers who are using AI saying, "Wow, I was able to add a
00:41:12
third shift. I was able to hire more workers or the ICU nurse who says I have more time to spend with my patients. I'm
00:41:17
able to ensure they don't code during a shift change. >> So look, my my point is like the first
00:41:22
part of what he said applies here, which is who cares what Matthew Prince thinks.
00:41:26
Because the reality is that if this is the way that you're going to message something as critical as this, I think
00:41:32
you did a horrible job. And now you label these people and you put a scarlet letter on their back. So now when they
00:41:36
try to get a different job, they're like, "Oh, you're one of the Cloudflare
00:41:39
measurers." How does that help anybody? It didn't needed to be done this way.
00:41:43
There's enough of these tech CEOs that are now public. You can hear them. You
00:41:48
can understand them. And I think what we're learning is, man, they're really
00:41:53
good at one thing and they're not necessarily as good at all the other things.
00:41:56
>> Yeah. Uh, okay. >> And so I would say shut the up, get behind the keyboard, just do your
00:42:03
job. And if you need to manage something, just manage it, but don't write these misses. You're terrible at
00:42:08
it. All of you. You're all terrible. You suck at this. >> All right. Uh,
00:42:14
>> end of my TED talk. Thank you for coming to my TED talk. >> Thanks for coming to Shamat's 18minute
00:42:18
TED talk and we'll we'll uh keep moving on. >> Sorry. And sorry, when everybody gets
00:42:23
upset, this will be why. >> Yes. I mean, I I do think the Zuckerberg this and Jack saying, you know, hey,
00:42:29
we're going to have half as many people. Everybody reports directly to me. This
00:42:32
is all building this fear in society. And I think people are rightfully scared. If the people building it tell
00:42:38
you, be scared. your job's going away. >> Wait till the next regulatory filing comes out from these
00:42:44
companies and they authorize a massive share buyback and an increase in their dividend.
00:42:49
>> Yeah. And their cash pile grows. >> All I'm saying is there's a right way to
00:42:53
do this, make these decisions, and then there's a wrong way to do it, which is
00:42:56
to message it in the way that they're doing it. >> So, whoever is running PR and comms and
00:43:01
approves and reviews these things >> are really at their job. They don't understand the moment.
00:43:08
>> Oh, some breaking news here. It looks like Anthropic has hired three more
00:43:13
people. Here we go. Let's see. >> Oh, here we go. Personal job news from
00:43:16
Sam Alman. He'll be joining Anthropic. I see. That's pretty good. >> Who else is joining Anthropic? Let's
00:43:21
see. We checked everybody's socials. >> Oh, Tucker. Tucker Carlson also joining
00:43:27
Anthropic. He'll be doing their PR and podcast from Anthropic headquarters. And
00:43:31
who else? Oh, Shamas looking good. Well, it looks like you put 5 lbs on and using
00:43:37
this. First of all, this is not this is not what I look like. And um >> did you get 5 lbs?
00:43:44
>> Looks like Are you not wear Are you not wearing underwear? >> He's no underwear and he's wearing his
00:43:49
khakis, but I think it's just he's trying to not show off those scrawny those scrawny squints. Those those
00:43:54
little slats he calls legs. He's covering them up now. >> Uh hold on. I'm gonna send I don't want
00:43:58
to leg shame you. >> I I I knew that this was going to come up. I'm going to send Nick an updated
00:44:02
picture of my legs. And you you can deal with this. >> You can photoshop your legs all you
00:44:07
want. >> I didn't I didn't photoshop. >> You look like an ostrich, brother. Those
00:44:10
are not a day working on it. >> They may not be photoshopping, but he may have been leg maxing.
00:44:17
>> He could be legs. What are you doing? >> First of all, first of all, I'm 6'2, you
00:44:25
goons. Okay, so >> gosh legs. >> All you little people, you know, Jason,
00:44:29
you're 5 foot all. So, you know, your ability >> I've had a good day when my platforms.
00:44:33
Yeah. >> Your ability to have legs is is different cuz like my muscle mass won't
00:44:37
show on my legs >> the way it shows on your leg. >> Oh, I don't think you're helping. I look
00:44:42
at you know what he's doing there, Freeberg. You see it, right? Look at how scrawny the calves are. And then look at
00:44:47
how he's doing a >> That's a push-up bra for your quads. >> Oh my gosh.
00:44:51
>> That's the equivalent of a push-up bra. He has those Bonsu balls. He put Bosu
00:44:55
balls under his hammies to You did it. You're using fillets to >> I did my legs and I flex. Okay, you know
00:45:01
what? Move on. This >> I was just say I think we should give credit where credit is due.
00:45:06
>> Yeah, >> Jamoth's legs. >> Better has been doing a lot of work on
00:45:10
his legs. >> Thank you. >> It's better. I'll I'll give him better,
00:45:14
but I do think that he's pumping them up here. Okay, let's keep going here. All
00:45:18
right, topic two. SpaceX just filed their S1 on Wednesday. They are aiming to raise 75 billion at a 1.75 trillion
00:45:27
with the T valuation. This will be the largest IPO ever by more than double Saudis Ramco $29 billion IPO a couple
00:45:35
years ago. Listing is expected mid June likely June 12th. Ticker will be SPCX. We got a lot of interesting information
00:45:43
in the S1 tearown. Obviously SpaceX has three main business units. Starlink is the money printer right now, but there
00:45:52
is a second one that's emerging. Starlink did 11.4 billion in revenue last year on 50% growth with 4.4 billion
00:46:00
in operating income. Over 10 million people are now subscribing to Starlink. That business could easily be hundreds
00:46:08
of millions of paying subscribers. So that that's uh a lot of growth potentially there. The space business is
00:46:15
but 4 billion in revenue. It's growing 17% growth, which would still be strong
00:46:18
growth, uh, but had 650 million in operating losses. AI did 3.2 billion in revenue. That's more than double
00:46:25
year-over-year growth, but it had 6.4 billion in operating losses. SpaceX had 20 billion in capex spend
00:46:32
last year. Over 60% was for the AI compute buildout, and obviously they were trailing anthropic and open AI and
00:46:39
Gemini in terms of XAI uh, playing catch-up. and he did a big reboot of that as we saw on the Twitter. But
00:46:47
here's the big one. EWS, Elon Web Services as we call it here on the all-in pod has exploded. Anthropic is
00:46:56
paying SpaceX, wait for it, 1.25 billion a month to rent out Colossus 1 and parts
00:47:01
of Colossus 2. It's a $45 billion deal over three years, 15 billion a year. In
00:47:08
other words, they added a Starlink in terms of revenue to the party. Plus, if they buy Curser, that's going to add
00:47:14
another two or three billion. >> Not if I already told you they already bought.
00:47:17
>> Okay, I'm just trying to, you know, dot the eyes and T's here. Uh, but when they
00:47:21
buy uh Curser, that adds two or three billion. That's not in the S1. >> That's also growing and doubling.
00:47:28
>> Yeah, that's probably growing 2x year over year. And who knows how much faster
00:47:32
it will grow. Poly Market 71% chance SpaceX closes its first day of trading with a market cap above two trillion.
00:47:40
Thank you to our partner Poly Market. I'll stop here. Gavin, uh you've been
00:47:45
involved in the company for a long time. Jimoth, you uh I think were a big investor in the satellite company that
00:47:51
became part of Starlink, which is the revenue driver there. So, you both have uh a lot to say about this. Gavin, your
00:47:58
take on the S1 and I think specifically Elon Web Services. Well, I think what's
00:48:03
important about um Elon Web Services does make me laugh, but 15 billion that means the AI business right there is
00:48:11
going to quadruple. It it has already effectively quadrupled. I think what's important about that is
00:48:17
there's a stat in it that for I think the their first data center was 122 days. For the second one, it took them
00:48:24
91 days. The third one was I think 66 days. They build data centers dramatically faster than anyone else at
00:48:33
a lower cost. And now that you have a clear offtake partner and I would expect partner to
00:48:42
become partners, there is no reason they can't start stamping these data centers out really
00:48:49
fast. And having watched Jensen for a long time, it is important to Jensen that his
00:48:55
GPUs be used. And so GPUs will be allocated to who can plug them in, turn them on, and start converting electrons
00:49:04
into tokens. And so I think this business can grow dramatically faster than I think, you
00:49:12
know, maybe what anyone could have contemplated three, you know, three three months ago. But 15 billion from
00:49:19
anthropic is is extraordinary. >> Important note, it can be cancelled by either party with 90 days notice. just
00:49:26
want to make sure we also have that in there. So that means Elon might want his compute back or Anthropic may find
00:49:32
another solution. So they do both have an out >> and I think that's that's a you know I
00:49:37
think that's that's that's probably an important provision. Yeah. >> For everyone but I think the other thing
00:49:42
that came out this week which was not in the S1 Nick can you throw up the para frontier and maybe don't you know
00:49:47
include the email and the names and everything but the composer 2.5 stat. I think this is really extraordinary. So
00:49:54
cursor's composer 2.5 model came out this week and I mean this is parto dominant and this is just you know three
00:50:05
four weeks of doing reinforcement learning on Colossus 2 with cursor's data and cursor has we will never know
00:50:16
but but cursor allegedly has more tokens of coding data than exist on the public
00:50:22
internet And that is a stat from I think more than a year ago. So I'd imagine
00:50:27
it's grown significantly. And I think cursor and anthropic probably have the most proprietary
00:50:35
tokens of coding data. And what this this jump from composer 2 to composer 2.5 showed us is that when you do an
00:50:44
appropriate amount of reinforcement learning using Nate data let alone injecting it into the pre-training of a
00:50:50
new base model because composer 2.5 is the same base model as composer 2 which is Kimmy K.25
00:50:59
>> like this is amazing. This is three or four weeks and it is paro dominant. the
00:51:03
paro front here. >> If you draw a curve of the blue dots, you can see composer 2.5 is literally
00:51:15
well outside the paro frontier. And that's after 3 weeks. And what's going
00:51:19
to happen next is you're going to have a new base model with a cursor model in
00:51:24
it. >> Yeah. >> Then the cursor model RL using the biggest coherent uh compute cluster in
00:51:32
the world. And I think this is I think this may >> it's significant. Yeah,
00:51:38
>> it's extremely significant for XAI and Cursor >> and Cursor was dead in the water in
00:51:45
terms of access to compute and they were falling very far behind Codeex, Google, Anthropic and then Elon let them
00:51:55
on Colossus and boom, instantly their models are growing faster and this could be we could be sitting here a year from
00:52:03
now and they're the dominant player and could we sitting here, Gavin, in a year
00:52:09
and Elon is selling compute to Google and Open AI. Is that a possibility or not?
00:52:18
>> Well, I think it's much easier to see him selling compute to Google and I
00:52:22
think already there have already been posts about that. >> Yeah. >> And for sure Google is going to want to
00:52:28
be part of orbital compute. >> You know, it's very funny. The only people who are skeptical of orbital
00:52:35
compute are those people who are not involved in in data centers or space. Google, Anthropic, Amazon, Nvidia,
00:52:45
they are all very convinced that orbital compute is going to be reality and obviously SpaceX is extraordinarily well
00:52:50
positioned for that. But I do think that Composer 2.5 data point is really powerful.
00:52:55
>> Keep an eye on it. >> Yeah. >> And then the other thing that's come out
00:52:58
is Grock build. So, what Grock lacked that a lot of other models had, and I do think it's important to remember that
00:53:06
the newest version of Grock 4.3 is on the paro frontier for all frontier models. And you're either on the
00:53:11
frontier or you're not. And the the companies on the frontier are XAI with one build of Grock 4.3, which is a 500
00:53:21
billion parameter model, Google 3.1 Pro, and then OpenAI Anthropic. And that's
00:53:26
it. Those are the companies on the frontier. and the four horsemen. >> Google today each have one dot on the
00:53:32
paralo frontier and obviously you want as many dots as possible but Grock lacked a harness. So Claude had cla
00:53:42
OpenAI had codecs and now with Grock build there is a harness that is available to to Grock and you know as
00:53:50
I'm as I'm sure a downloadable app to translate into English that has integrations to all your favorite stuff
00:53:57
whether it's notion, Gmail, Slack, etc. And if you don't have that it's just
00:54:02
like using a a basic chatbot from year ago. So now they have their downloadable. in market and they are
00:54:07
cooking with oil on it and they're playing catch-up, but they're moving fast
00:54:10
>> and and it's it's more than just an app. It's it's a runtime. It's an
00:54:14
environment. It manages state. It manages memory. >> It makes these models dramatically more
00:54:21
useful to the extent that I think the people at the frontier all agree that the harness is essentially as important
00:54:28
as the model especially in an agentic world and the harness and the model need to be developed together. So the release
00:54:34
of gro build and the pace at which they're iterating is I think also really encouraging. So now you have cursor you
00:54:41
have the cursor data you have a clear existence proof that the cursor data is really important because composer 2.5 is
00:54:48
now paro dominant and the most selected model on cursor and that's also important because you know these evals
00:54:55
don't capture everything. You know, this is why people on X talk about the vibes
00:55:01
>> and the vibes on Cursor 2.5 are also really good. >> They're immaculate.
00:55:05
>> Together, >> yeah, >> with Grock build, I think these are really important developments.
00:55:10
>> Yeah, they're there was Elon was incredibly frustrated by the state of
00:55:15
affairs at XAI. He was very public about that and he's less frustrated now and
00:55:19
he's shipping a lot faster and so I think that says something and he has been very focused on it. Freeberg, your
00:55:28
thoughts on the SpaceX IPO and what this collection of companies might look like
00:55:34
a year or two from now, especially if, like many people believe, Tesla and SpaceX merge. What do you think of
00:55:44
dollar sign El N as an entity and what impact it might have as if those two were put together?
00:55:51
The market cap would put them in the fourth largest company in the world. We can revisit our earlier conversation
00:55:56
about an anti-tech, anti- AI, anti- progress world and society ahead. And if there is an effort, a concerted effort,
00:56:06
an organized effort by governments to stop or block access to information, restrict freedom of speech, restrict
00:56:14
freedom of purchasing or buying things, to control more things. And I think there's a trend line in this direction
00:56:22
right now globally. The internet has always been louded at this kind of system that provides an open alternative
00:56:29
to physical commerce that you could create digital commerce, digital uh information, digital media that you
00:56:36
could share and um it's almost this digital representation of society. But the internet has to sit physically
00:56:42
somewhere. And the assault on data center builds outs in the United States right now, I think, may indicate the
00:56:50
importance of having an alternative internet from the ground layer up. If you have a communication network that
00:56:57
isn't restricted and controlled by a government on Earth, it's almost like a backup for
00:57:08
civilization, but it's a backup for progress. And I don't own any SpaceX
00:57:12
shares and I'm not trying to sell the book of SpaceX, but I think that there's
00:57:17
like an important aspect of can you create a system that's not under the control of governments as a way to
00:57:24
ensure humanity's progress to ensure civilizational continuity if things go south, if things aren't good, if things
00:57:31
are restricted, and if you know fundamental forms of tyranny start to restrict speech, restrict commerce,
00:57:37
restrict information flow and whatnot. And I think having like a space-based communication network, space-based data
00:57:45
centers, and space-based communication back down to earth wireless, I think it's generally a good thing.
00:57:53
It's good to have a backup. >> Yeah. So, put all the economics aside and the multiples and the valuations and
00:57:58
whatnot. And whether it's SpaceX or not, I think the idea that you could have
00:58:02
data centers store information, transmit information, route information, and access information through space-based
00:58:08
systems that can't be controlled, manipulated, or destroyed by governments is is important. And I I just I like
00:58:16
that. Yeah. If you most people don't remember this, but when Elon was starting SpaceX, the original idea when
00:58:24
he was running around with ADO and they were looking at some rockets and getting
00:58:28
carriage from Russian rockets was to back up the biosphere. And he came back from that trip and I remember talking to
00:58:34
him about it and he said, "I think I just have to make my own rockets because
00:58:37
that's actually where the problem is and it would be easier just to make my own
00:58:40
rocket to back up the biosphere." He wanted to put geodomes like geodessic domes in space with all
00:58:47
the plants and wildlife and and creatures. Uh and what incredible vision and then it you know there was the
00:58:54
necessity of actually getting that up into space and that's that's the unknown
00:58:58
origin story. I will say this chimat the idea of putting a data centers in space
00:59:05
seems completely doable even though there are a bunch of people who are saying it's not when you compare it to
00:59:11
what happened with SpaceX um with Starlink which people said also wouldn't work and now he's got 10,000 Starlinks
00:59:17
up there. The difference between a Starlink satellite and a data center satellite is really not that different.
00:59:24
And um >> no they're they're pretty different. Well, conceptually, yeah, of course
00:59:29
they're physically different, but conceptually, Elon put 10,000 Starlinks up. Is he capable of putting 10,000?
00:59:37
>> No. Look, the size rockets the size is much bigger, Jason. The foils are much
00:59:41
bigger. The wings are much bigger, >> but it's Yeah, my point is it's not
00:59:45
different if he has the new Starship because that's 10 times bigger. Yeah, >> you can't just scale like this. That
00:59:51
being said, it's technically possible. I think he will be the first one to figure
00:59:56
it out. But I'll just take a much more pedestrian take, which is okay, you're
01:00:01
sitting here and if I'm asking myself, Jimoth, how do I underwrite SpaceX at 2
01:00:06
trillion? Here's the basic math that I would do. Well, last year it did 181 19
01:00:11
billion. It'll probably do 25 to 30 this year. Okay. So, I'm buying this thing at
01:00:18
a fairly costly premium, right? So, what am I buying? Well, I'm buying probably the most
01:00:28
important internet infrastructure project that's happened since the internet itself. That's going to scale
01:00:33
to hundreds of millions of users. And the reason that's going to scale to hundreds of millions of users is it's
01:00:37
just very useful and it's just going to become cheaper and cheaper and cheaper.
01:00:41
So, that's number one. I'm buying a delivery infrastructure, but I think over time
01:00:48
GDP plus 10, GDP plus 15 kind of a grower. So good business, valuable business, but it's the underlying
01:00:55
platform that allows everything else to happen. And then I'm buying an AI business,
01:00:59
which will be at the top level the apps, but at the bottom layer all the compute
01:01:04
capability. And I think when you scale that out, like why is Colossus so valuable to
01:01:12
Enthropic? Maybe that's like a good question to ask. It's because if you look at who's
01:01:17
actually capable of delivering a gigawatt data center, these guys are the closest, like an actual gigawatt. And
01:01:25
and the reason is is that this stuff is very complicated and very very hard. I think you've probably heard this famous
01:01:31
story where Jensen was like, "Yeah, he was the one that figured out this one
01:01:35
thing that we that nobody else could figure out so that you could strip a bunch of racks and drive a bunch of east
01:01:40
west traffic and make the whole thing work together." So I suspect what happens is next year
01:01:46
it's probably 40 45 billion and then the year after that it probably doubles
01:01:51
again. So now I'm buying it at 20 times revenue. And you would say well why can
01:01:55
you buy a company like this on revenue versus earnings and cash flow. And I think the reason is because what
01:02:01
the revenue does is it gives him the operating leverage to go and invest in all of these other businesses that
01:02:08
ultimately consolidate his differentiation and his competitive mode because what he creates is a
01:02:15
capital mode that then accelerates a technology mode that then accelerates an execution and a learning mode. And that
01:02:22
flywheel when it starts to spin very quickly and you would say, "Hey, hold on
01:02:26
a second. It's probably spinning quickly now." I would say we're at the beginning
01:02:30
of the beginning because he's again he still has all these disperate assets. I
01:02:35
still don't like the fact that Tesla's over here. And as I've told you that
01:02:39
will get merged in. And now you have this incredible corpus of physical capability,
01:02:47
movement of all kinds, X, Y, and Z, right? You have learning capability, you have infrastructure, you have all the
01:02:55
connectivity. That thing will look very cheap, I think, in a few years. and he has this
01:03:01
one thing that nobody else if you look at the big CEOs who steps on stage where you're always
01:03:09
curious okay what has he got up his sleeve you know the Steve Jobs oh and one more thing this is the only guy at
01:03:16
the scale of civilizational out of left field he's he's the guy whether you like him
01:03:24
or you hate him he's the guy and there's a premium that is welld deserved that
01:03:28
comes with that so if If you had to pick an underwriting case, Jason, I would flex the revenue and realize that
01:03:34
terrestrial data centers alone are a hundred or $200 billion of revenue by 2030 2032 just and that means just
01:03:42
building it. So already you're buying it at 20 times revenue just for that business. Everything else is the
01:03:47
Colossus on the ground base. No, no, forget space for a second. It's like Colossus 3, Colossus 4.
01:03:55
>> It pencils out with that. Yes. >> Getting a name plate 1 gawatt. It is
01:04:00
freaking hard, man. Getting a gigawatt name plate working is almost. And then, by the way, there's
01:04:07
all the stuff that he can do on land that he's the best position to do. I'll
01:04:10
give you one example. There's a great push that Jensen's making, which he
01:04:14
needs a partner, and I think Elon becomes a natural partner to do DC to DC. Forget all this DC to AC to DC
01:04:19
nonsense that goes inside of a data center. All the laws, heiness, all >> explain what that is in English. Yeah.
01:04:23
forever just like look you go through a bunch of power transformations to to actually deliver the electrons into the
01:04:30
rack so that as Gavin said you can generate the token on the other end today it's it's very inefficient it's
01:04:36
very costly it requires a lot more power it requires a lot of cooling it requires
01:04:40
complexity and what people have said is wow if we could just do DC toDC like it comes in as DC direct current it goes
01:04:47
right to the rack as DC but it requires a fundamental rearchitecture Jensen needs a design partner and a thought
01:04:54
partner to get that done. >> He's probably the only one. So, I just think there's a lot of reasons where you
01:04:59
can underwrite this to a multiple of revenue plus the X factor which is just the creativity and the the one more
01:05:06
thing. Love it. And then here's two uh charts and I'll have you comment on
01:05:11
these Gavin after it. Here's the rocket sizes just in terms of scale and I most people have not
01:05:19
actually seen a Starship in person. when you see this thing in person and I I've
01:05:23
been inside that rocket. I think you were we were together Gavin when we were in the first build and like inside of
01:05:30
that you can fit 300 people. It's basically like a giant if you thought of a commercial aircraft.
01:05:39
That's what it feels like when you're inside, right? Like a 747 in terms of
01:05:42
the amount of space in it. Especially when you compare the Falcon Heavy, which is their workhorse. Correct, Gavin?
01:05:48
>> Yeah. And Starship's going to get bigger. based on their road map, it's
01:05:51
going to get a lot bigger, >> a lot bigger. And then this one is the most interesting that this started
01:05:56
trending last week. This is cumin of payloads launch 1957 to today. SpaceX is basically about to in just that and and
01:06:05
this is really what exponential growth is about and this is what disruptive technologies are about. Just from 2012
01:06:12
to today, SpaceX is about to dwarf the rest of the world's cumulative payloads
01:06:19
into space. So Gavin, maybe take the other side of it. When do these data centers in space happen? What has to
01:06:29
happen for those to be a reality? When does that hit SpaceX's bottom line? We've heard from Chimoth, hey, here's
01:06:35
all the things that hit the bottom line in the short term and midterm. But I think data centers in space would be a
01:06:40
midterm to long-term play. Three years is what I'm hearing. So t tell us about
01:06:45
that business in relation to the two charts I just shared. >> Well, the one thing I would just say,
01:06:50
well, first all those charts about launch are before Starship was operational and most most of that master
01:06:57
orbit was done by Falcon. >> Yes. >> And Starship the Falcon is reusable. Starship is
01:07:04
designed to be rapidly reusable. And this is a critical difference. Like let's say Blue Origin successfully
01:07:11
solves reusability. They're where SpaceX was 10 years ago. Let's say China solves it 10 years ago.
01:07:19
Rapid re the reusability means that you extensively refurbish the rocket, you know, the engines, everything, the
01:07:27
fairing, it takes a lot of time. you know, maybe you can fly that rocket again in
01:07:33
30 days, 60 days. Rapid reusability means that you can fly the same fly and land the same rocket multiple times per
01:07:41
day. So, if SpaceX and and it's really hard to do rapid reusability. I think it would have been much it would
01:07:50
have been not trivial but much easier to have Starships working if it was just designed to be reusable. Hm.
01:07:57
>> That's not enough for what Elon wants to achieve of, you know, a a moon base, a
01:08:04
colony on the moon, a colony on Mars, mass drivers on the moon. You need rapid reusability and that is why Starship is
01:08:12
such a an engineering challenge and will be such an impressive achievement when they have rapid reusability. But I do
01:08:19
think that master orbit rapid reusability in Starship means if they get >> when do when do you predict they'll have
01:08:26
that rapid reusability into space? You think >> I mean we're going to find out we're
01:08:29
going to find out you know we find out I'm I'm I'm going to be at Starbase
01:08:34
today for the launch. >> Yeah. >> So you know we we we turn over cards and
01:08:38
you know it's important for everyone to remember like let's just let's just say
01:08:43
it's a fireball. SpaceX will still learn from this. Yes, >> they they learn from failure. If you
01:08:50
don't fail, you're not learning. Same way if you're not wrong, you didn't
01:08:53
learn anything in that day. And this is a brand new rocket, a brand new booster,
01:08:58
a lot of new technology. There's a lot of instrumentation on it. So, whatever
01:09:03
happens today, SpaceX is going to learn and rapidly iterate. I don't know when.
01:09:08
I don't want to make a prediction. I would guess a year or two, maybe sooner.
01:09:14
>> I think that's most consensus. A year or two is I think perfect consensus. Yeah,
01:09:17
we'll see. So like the even if everybody else solves reusability, master orbit
01:09:22
from everyone else will quickly asmtote to a very small number. As far as when will orbital compute be a
01:09:32
reality, I would say well it is important to realize there is a working H100 and Nvidia H100 GPU in space today.
01:09:40
>> Yeah. >> Andre Karpathy both trained a model on and used for inference. So this is, you
01:09:47
know, it's it there's a working GPU in space today. >> And Nvidia is making a space designed
01:09:55
version of this, which will be different because the heat sink has to be different. There's a bunch of weight
01:09:59
that you put on it when it's in a data center that you don't need in space. And
01:10:03
you also have to reinforce it for the journey to space because these things are going to shake and break apart. The
01:10:09
data center ones are not made to have that many G's put on them. So, you're
01:10:13
going to need an an industrial an industrial strength one that gets to space that has a different profile.
01:10:19
Yeah, Gavin. >> Well, one of the things that's been so magical about SpaceX is they're very
01:10:23
good at engineering the rocket and the payload that you can use semiconductors that are not designed
01:10:32
>> be in space or satellites in space and those semiconductors are a lot cheaper.
01:10:36
We have a couple my my firm a trades is an investor in a company called Exite Labs that it's a matter of public record
01:10:43
is going to be in essentially every Starlink and the chips were not designed to go to space. They're not radiation
01:10:51
hardened. You know, everyone, you know, SpaceX really liked a lot of the the specifications on the chips and then
01:10:58
it's like, well, we'll see how they do with rad testing and they just, you
01:11:01
know, happened to pass. And so that is one of like one of something that's very
01:11:07
underappreciated I think about space. It's >> one of their specialtities.
01:11:10
>> One of their specialtities. >> Yeah. >> But I think second half of 28 to first
01:11:15
half of 2030 would be my point prediction. >> All right. Let's do Nvidia and then the
01:11:19
the market recap since we have you here Gavin and since Freeberg you wanted to get in on that. Nvidia blew out its
01:11:23
earnings again. Q1 performance is just mindboggling. 81.6 6 billion in revenue, up 85% year-over-year, 20% quarter over
01:11:32
quarter. High growth in the stock market for those people who don't participate.
01:11:36
20% would be a high growth company year-over-year. They did that quarter over quarter. 58 billion of net income
01:11:44
and uh 48 billion in free cash flow. They're doing all this at 75% gross margins.
01:11:50
They're growing massively. And they're obviously the most valuable company in
01:11:55
the world at a $5.3 trillion market cap. Stocks up but 16% year this year with all that growth. That's a magnitude of
01:12:04
that 16%. And um they've announced another 80 billion in additional buybacks on top of
01:12:11
the 100 billion in buybacks uh they did at the start of 2023. So they're buying
01:12:15
back about 4% of the company. They raised the quarterly dividend 25x from 1 cent a share to 25% cents per share and
01:12:23
their CFO said they're going to return 50% of the free cash flow to shareholders.
01:12:29
Never been a company like this. Huh, Freeberg. The the scale of this is just extraordinary.
01:12:36
>> Uhhuh. Yep. Don't don't see it. >> There you have folks. There's your
01:12:40
market report from Freeberg. >> Don't seem so enthused. >> Yeah, it's a mhm. He's got potatoes in
01:12:46
the oven. I have a question for Gavin. He did a really interesting talk with Patrick Oshanaughy and there was this
01:12:52
one thing that I wanted to ask you about because I thought it was so interesting.
01:12:56
You said when you look at the revenue multiples of the chip companies and you look at the revenue multiples of the DRM
01:13:01
companies, both cannot be true. In the context of Nvidia's earnings, can you
01:13:05
just explain maybe in plain language for folks? I just thought it was so fascinating because it explains
01:13:11
>> it explains I think just to set it up >> where is value over the next five years
01:13:15
like I think if you looked at Leo Ashen Brener his fund has gone from like 0 to5
01:13:21
billion overnight and it looks like he's just got massive puts on the chip sector
01:13:24
and he's kind of rotated. So just give us context Gavin where where's the puck
01:13:29
going? >> Well so maybe take the questions in reverse order for Leopold who's clearly
01:13:35
a brilliant man. I think he's a road scholar at like 19 and I think my understanding he's putting up pretty
01:13:41
extraordinary numbers. I've yet to meet him. He actually shares an office in San
01:13:45
Francisco with a friend of mine. So I think I'll probably meet him sometime soon. But it's got to for that 13F that
01:13:51
he filed was at the end of the first quarter when you know I would say we were in the you know the the thick of
01:13:59
geopolitical fears and I think you saw a lot of puts on a lot of 13Fs and I don't
01:14:05
know that those puts are still there. >> Okay. >> You know I think a lot of people wanted
01:14:09
to be hedged for Ron and you know now I think it's a little more clear. So I
01:14:14
wouldn't read I wouldn't read Leopold's 13F as being super negative on on SIM
01:14:21
>> chips. Okay, >> on chips. Second thing I think cross-sectionally if you look at the
01:14:26
valuations for all these AI DS they just they can't all be accurate. You have
01:14:31
memory makers at you know three to five times PE. You have Nvidia at a really low PE. you actually have um you know
01:14:42
some other accelerator companies at reasonable multiples and then you have everything else everything in power
01:14:47
everything in cooling and when I say power I don't mean utilities the IPS are
01:14:51
actually quite reasonably valued but power cooling even probably some of some of the optical names
01:15:00
these are discounting very different things if the multiples on the power cooling optical names are correct Nvidia
01:15:10
memory, they're going up a lot. If the multiples on Nvidia and memory are are
01:15:15
correct, everything else is probably going to underperform. The AI market is cross-sectionally inefficient right now,
01:15:22
which is what I was trying to say. As far as the Nvidia quarter, I do um they went to a new reporting structure, data
01:15:28
center and AI and then with no data center and edge and then within a within AI they have hyperscalers and then I
01:15:36
think they call it AI clouds >> AI clouds >> industrial and enterprise. What I
01:15:40
believe is if we were to make a true applesto apples comparison and Broadcom, you know, there's a
01:15:47
narrative that Nvidia is losing share to the TPU and Broadcom guided for 143% year-over-year growth in their AI
01:15:56
semiconductor revenue in the quarter that they will report. Um, that's comparable to the one Nvidia just
01:16:01
reported. I think if you were to and I just I so wish they had reported slightly differently. I wish they' done
01:16:10
hyperscalers, AI clouds and then industrial and enterprise because I think the segment that is comparable is
01:16:18
the sum of hyperscalers plus AI clouds stripping out China because Bracomob just did not have the China business
01:16:26
that Nvidia did. And I think on that basis, in other words, in within the western AI world, within data centers
01:16:34
that need being built, whether they're being built by Coree, XAI, Amazon, Google,
01:16:39
>> Nvidia's AI business is growing faster than Broadcom's and faster than a lot of other companies
01:16:47
that are, you know, seen as part of this AS6 share gate story. And you know, I think Jitson has become
01:16:55
you can you can hear it increasingly frustrated and rightfully so with two things.
01:17:02
I would say what is the performance of the stock to to >> he's been vocal about that. Like what is
01:17:08
going on here? You're putting up record numbers and we're getting no like uh
01:17:12
credit. >> Yeah, I get it. And and just how can there be a share loss narrative if I am
01:17:18
gaining share? And it is indisputably true that he is growing faster than hypers scale or capex even without these
01:17:25
adjustments. >> Yeah. >> And I think the other thing that's so frustrating to him is these other
01:17:29
>> AS6 >> are not being submitted for benchmarks. They're not in the SIM analysis in
01:17:34
inference max. They're not in ML Perf. And I think the reason they're not being
01:17:39
submitted is they will lose >> and you can't fight shadows. And until we see a clean benchmark
01:17:48
of whether it's GB300's verse TPU V7s or you know very >> versus inferentia. Yeah. Yeah.
01:17:56
>> Versus Yeah. versus Tranium. >> Yeah. >> We're not going to know. And that's why
01:18:00
a lot of these other chips I think Tranium's in a great spot aren't being
01:18:04
submitted. But nonetheless, if India is doing well, once you become the largest company in the world, you kind of you
01:18:10
tend to trade by observation would be in stairst step patterns where you kind of
01:18:15
the multiple compresses compresses compresses because people are skeptical of the size.
01:18:19
>> Then you have a rerating. Yeah. >> And then you rerate. >> New floor is established at a higher
01:18:23
rate. Yeah. >> I think there was one other really important thing in the VA quarter. It's
01:18:28
they said that they thought their CPU business was going to be $20 billion this year.
01:18:32
>> Yeah. Yeah. Yeah. That's extraordinary. It means overnight we're one of the
01:18:35
world's largest CPU manufacturers. >> And I think that is a testament to
01:18:40
Nvidia has a unique position. They're the only company that works with every
01:18:46
lab. And so that puts them in the best position to architect their chips. They call it co-design for where the models
01:18:54
are going. And I think that $20 billion CPU figure is pretty extraordinary. This
01:19:00
is the thing like at the end of this Grock transaction last year my kind of prevailing thought on this is we're
01:19:05
going to move to these domain specific architectures. I thought that was like a a feta complete. We're just now waiting
01:19:11
for which models. But the reality is that that DSA market evolution is actually happening
01:19:18
inside of Nvidia. That's what's so insane to me. That was my takeaway from
01:19:21
the quarter as well which is like holy [ __ ] these guys actually have domain specific architectures because they're
01:19:26
doing these design programs with every this is why back to sort of the you know when he does DC toDC with Elon and
01:19:31
Colossus 3 or whatever it's just it's another game changer for everybody
01:19:35
>> he doesn't he makes nine and then I think the cost at which you can finance
01:19:41
these chips and these useful lives is really important >> you had an incredible insight which is
01:19:45
the amortization schedule for coravee and all these guys they got saved You may want to just explain what that is
01:19:51
and what why you said that. I thought that was a great insight. >> No, thank thank you Jamatha. I
01:19:54
appreciate it. So when core weave and all these neo clouds came public and by the way this goes for the hyperscalers
01:19:59
too. There was a big bare case that hey the these guys are amortizing their GPUs
01:20:03
and CPUs over four, five, six years and that's way too short of a lifespan. The
01:20:08
true lifespan of a GPU is more like two years and therefore you know the profits
01:20:12
of all these businesses are overstated. >> The reality is >> this was Michael Bur who put this out
01:20:17
there. Yes. To be clear. Yeah. Yeah. And you know, thank you, Michael Bur. We need bears. Thank you.
01:20:24
>> Yeah. That's like It's like asking Gerardo about modern music. >> Well, I don't I don't want to cast
01:20:30
dispersions on Michael Barry. He's a He's a brilliant man. But we need bears.
01:20:33
>> Let me Hey, somebody call Vanilla Ice and ask him what he thinks. >> Oh my god. Millie Vanilli, check it out.
01:20:40
>> What a waste of time. What a waste of time. >> Oh, poor. Come on the program anytime.
01:20:45
Go ahead, Kevin. Keep us on track. >> Happy to chat. But now that we've
01:20:49
disagregated inference, we have these different domain specific accelerators. You can mix and match them.
01:20:55
>> And I think the GPU stays in a lot of ways at the center of this constellation
01:20:59
for a while. >> And you can put whether it's a Grock accelerator, whether you know it's a
01:21:05
Cerebrus accelerator in front of old GPUs, use Grock or Cerebrus for decode. And then those older GPUs, they have a
01:21:12
useful life for 10 or 15 years. And this means that you can finance GPUs. I think
01:21:17
Cory's lowest financing, I can't forget if it's six or 7%. >> 6% come down%.
01:21:22
>> And if you can get an assetbacked loan, an asset backed financing >> for GPUs at a lower rate than other
01:21:29
chips. >> No, that that's a profound advantage. >> That quarter single-handedly saved the
01:21:33
Neo Neos clouds this Nvidia. I mean, they single-handedly saved them all. I think they they should all they should
01:21:41
all say an incredible thanks to Jensen because >> I interviewed the CEO of Core Wee,
01:21:46
Michael in Trader. Michael and Trader. Yeah. And he was saying, "Hey, listen.
01:21:50
People have no problem buying and financing these over a six-year period and people are asking for things that
01:21:56
are coming off and that he thinks they're going to have year seven, eight, nine, they'll have some useful life, you
01:22:02
know, uh, in addition to that." So, >> yeah. So, he's like, I I I don't know
01:22:06
what anybody's talking about here. Like this is just not informed analysis was
01:22:11
his point. Like I the game on the field and people are betting with their dollars with him. He has them pay in
01:22:17
advance and sign six-year contracts. If they didn't think it has a six-year lifespan, they wouldn't be signing a
01:22:22
six-year contract. Pretty straightforward. And they can't get enough of them. Okay, let's end on this
01:22:26
market update. Macro picture. Not great. Oil remains elevated. Although there might be a settlement. Every week we
01:22:32
have there is a settlement coming. Maybe this time uh 16th time it's a charm. in
01:22:36
the Iran war is going to wrap up, but we're in week 12 of it and this was supposed to be four to six weeks. So
01:22:41
wars never get resolved quickly. That's one thing we've learned in our lifetimes. Oil is driving inflation
01:22:47
massively higher. Poly market says 99% chance May inflation comes in at 4.2% or higher. Survey of professional forecast
01:22:54
is projecting CPI hits 6%. You heard that right, folks. We weren't just talking about a 3% handle, which we just
01:23:01
hit. Now people are saying four, five, and 6% in Q2. And obviously that's a huge revision and uh the narrative was
01:23:10
hey more Fed rate cuts coming. Now we're talking about Fed rate increases. Inflation is causing obviously bond
01:23:18
yields to rise. 10ear hit 4.6%. You remember we've had Besson on the uh pod multiple times and his goal was to get
01:23:26
that under 4%. Now it's significantly above that number. And also if we go around internationally, Japan's 30-year
01:23:33
is at a high of 5.1%, highest ever recorded. UK yields highest since the great financial crisis. Germany highest
01:23:41
since 2011. And in Korea, retail investors are borrowing borrowing record amounts of money to trade in AI chip
01:23:48
stocks. They also had a incredible run in Korea betting on crypto at the peak. So that's some sort of an interesting
01:23:56
signal. Freedberg, is your alt personality going to come out right now? Are you concerned?
01:24:03
Is Dr. Doom making an appearance here or do you think this is manageable? How concerned are you? What is the point of
01:24:08
being concerned when you have ridden the roller coaster to the top and it is beginning its descent? I I don't know
01:24:14
what there is to be concerned about. The the the force of gravity is inevitable.
01:24:20
>> The roller coaster will roll down. We will throw our hands in the air and we
01:24:24
will scream wee as we go for the ride. Global debt to GDP is 310%. Reserve currency status to the side. The
01:24:36
spending problem at the federal, state, local level. The spending problem at every country to basically keep
01:24:43
economies growing to support existing leverage ultimately creates a cascading effect. it ultimately breaks and uh as
01:24:51
it starts to break you have massive inflation because the value of your underlying um currency collapses and
01:24:59
then you have money printing and all this other sort of stuff which inflates the value of assets which allows you to
01:25:04
keep servicing your debt and the spiral takes off and so we will just uh enjoy the ride. This is the moment you know
01:25:12
30-year Treasury 5.2% 2%. This Japanese yield some argue might, you know, you should talk to more active market
01:25:19
participants than me, but and probably some economists who trade the market, but I would think that this is one of
01:25:25
those things that could be a catalyst for a for a a credit crisis because there's a lot of people that are
01:25:31
in this carry trade and we'll see. You know, this is >> okay. >> This is water leaking out of the bucket.
01:25:38
There it is. >> Oh, there he is. Dr. Dumisier Jam, your thoughts on Dr. Doom's panic attack of the month. Uh
01:25:46
is this uh is this time real? Is this uh the 17th prediction of the next six recessions? What do we got here?
01:25:52
Chimath, are you concerned? How concerned are you about these signals that are flashing?
01:25:58
>> I I think that's exactly what that is, Jason. There are signals that are
01:26:01
flashing. I think there's pockets of the market that still make sense that you
01:26:04
can underwrite if you want to buy businesses that represent the future. And if you can find a few of those and
01:26:11
you can get comfortable with that and you can own it for 10 years, I think you buy those companies.
01:26:18
And generally everything else, I think you should not speculate and you should generally avoid, not just because it's
01:26:24
an up market, but in every market. I've learned this the hard way. We've all
01:26:28
kind of gone through this. As I get older, it's it's just not worth it. the
01:26:32
vicissitudes of the market um don't give me anywhere near the sugar high it used
01:26:37
to on the way up and it makes me feel horrible on the way down. So how I manage myself is I have a few companies
01:26:44
that I really believe in. I have extremely concentrated large holdings in those large for me doesn't mean large
01:26:49
for everybody else and then otherwise I just kind of stick to my eating and keep
01:26:54
my head down. It's a much more rational way to behave. So, how many public >> stocks can you keep in your brain and
01:27:00
still sleep at night holding for the long term? What's the Is there a number
01:27:04
for you? Is it five? Is it 10? Is it >> five? It's five or less. >> Five or less.
01:27:09
>> Five or less. >> And so, what your largest holding right now is what percentage of your net worth
01:27:13
would you say? >> I don't know. >> Or like top two maybe. >> Yeah.
01:27:18
>> Oh, top two. >> Yeah. Like one and two. One is 20, two is 15, or one is 40, two is 20.
01:27:24
>> I don't know. Again, it depends on the day. I don't know. But it's it's
01:27:27
>> just curious. But I think that's I think that's really important.
01:27:30
>> My point is there's no 30 things that I'm tracking. I don't I don't have the
01:27:33
time. I'm not smart enough. There's too much information. There's like four
01:27:37
things that I stay on top of. >> Gavin, you you do this for a living. How many positions do you manage? And what's
01:27:43
your take on some of the flashing signs that are saying, "Hey, slow down." Or
01:27:47
maybe there might be a wreck around the corner here, you know, when they do the checkered flag in the F1 or whatever the
01:27:52
metaphor you want to use is. Well, so one, I I manage more than 100 positions at my firm. Um, and I do that with a
01:28:01
team. We're over 30 people now. So, it's not just me and I work with some some
01:28:06
great people. And then three things can be true. Rates going up is very concerning. What is happening with AI
01:28:14
right now with anthropic growing faster than any country, any company in history
01:28:19
at massive scale >> and certainly any country. >> Absolutely unprecedented. Yes, they're
01:28:24
actually Yeah, they they're now the size of, you know. Yeah. Yeah. They're pull
01:28:29
up where they >> they're bigger than a hundred different countries for sure.
01:28:32
>> Exactly. And keeping really fast >> and now profitable. >> Yeah.
01:28:36
>> Which I think really changes the moment. Yeah. Yeah. How did that happen? Yeah.
01:28:40
>> So those things can both be true. And I think we should all remember the tech
01:28:44
bubble happened with you know the 10-year and the 30-year much higher than they are today. And you know the the
01:28:51
Nvidia of of the tech bubble is Cisco and it traded 100 times forward earnings. And you know I think Nvidia is
01:28:57
probably at a low teens multiple of kind of low to mid- teens multiple of real earnings. You know if you that that'd be
01:29:04
a buy side consensus not in a trades number. And then the third thing that I think is true is a straightup formula
01:29:09
being closed. While it's terrible for everyone, it is relatively the best for
01:29:14
America because we are self-sufficient in energy. We are self-sufficient in food. We have become a massive exporter
01:29:21
of oil. We're now the world's largest not only oil and gas producer but oil
01:29:26
and gas exporter. And you know those three things can be true. What do they mean? I think it's probably hard for me
01:29:32
to see with America being the most advantaged by what is going on. >> We're still the best currency. Yes.
01:29:40
>> Still the best economy. We still have the best public marketies and we have
01:29:44
the best private market companies. >> Yeah. >> And we are >> one of the greatest producers of oil in
01:29:51
the world. So we're in good shape despite this international chaos. >> I don't think a dollar crisis is around
01:29:56
the world. Now listen, like if you know the Bundes Bank and was still in charge and you had the Deutsch mark and there
01:30:03
was a currency with better fundamentals, we would be at very high risk probably.
01:30:08
But just because we're the best house in what is globally a you know bad neighborhood of high debt levels and we
01:30:16
have AI in our corner and we have energy self-sufficiency and every day the straight of form was closed I think is
01:30:23
relatively good for the re-industrialization of America like I think you know you have to you
01:30:29
have to all the >> you're saying it's a forcing function it makes us just like co did be more
01:30:35
resilient and yeah more self-reliant. >> Yes. And electricity is a base input to every
01:30:45
manufacturing or industrial process essentially all of them. >> And what we make electricity with in
01:30:50
America overwhelmingly is natural gas. And you can look it up NG1. It is down this year.
01:30:56
>> The input cost for electricity in the rest of the world, you know, lots of
01:31:01
different things, but LG is a very important one. And it's up 100 200%. And so the street of form is absolutely
01:31:09
bad for everyone, but relatively good for America and relatively good for Trump's policy goals.
01:31:16
>> And that's why I think he's in no hurry. Every day the straight is closed and for
01:31:22
whatever he does seem like a relative thinker. Every day the straight of is closed is relatively good for America.
01:31:29
It's terrible for Europe. It is terrible for Asia. >> Japan and China need that oil.
01:31:35
Philippines needs it, India needs it. Yeah. >> Yeah. And so all these things can be
01:31:39
true, but the one thing I do just want to say is rates going up and inflation going up is never good. But we have to
01:31:47
hold what's happening with AI where the fundamentals are getting a lot stronger
01:31:51
in our mind. And then the one thing I would just add is AI has been seasonal. the market's
01:31:57
seasonal, you know, it often, you know, sell in May, go away. >> And AI fundamentals also appear a little
01:32:06
seasonal. >> In the past, that's been because, you know, because college students, they
01:32:11
they use a lot less chat, GPT, and claude in the summer. And generally, people maybe work a little less hard
01:32:17
when the weather's nice. Now, with a JPIC AI, will the fundamentals still be
01:32:21
seasonal? We will see. >> Oh, that's a really interesting point, right? We see that e-commerce apps,
01:32:26
subscriptions, what as investors in a lot of these companies, we would always have these board meetings. Chimoth, oh,
01:32:32
Q3, uh, yeah, people are out gallivanting and they're not playing Candy Crush or buying comm or whatever,
01:32:39
but oh, hey, Uber and Door Dash went up. People are traveling, etc. Okay, final story of the week. We had a 48 hour
01:32:46
jaunt by a bunch of tech CEOs and the president to hang out with she. A lot of high fives, a lot of handshakes, a lot
01:32:56
of great vibes, but coming out of it, we haven't seen anything definitive. Freedberg in terms of policy. This was
01:33:04
supposed to be some big breakthrough. It would have downstream effects on tariffs, on us selling chips to China.
01:33:11
We did see a little movement there. Uh, and the straight of war moves. we would become, you know, wonder twins with she
01:33:17
and Trump reopening it. But nothing really definitive other than some soybeans being sold and some H100s,
01:33:26
A200s getting sold to BYU and some of the top folks. So what do and maybe some planes got sold too. So other than a
01:33:32
little BD, a little business development. Yes. Uh Freyberg, what's the outcome here or was it just a bit
01:33:39
performative in your mind? There was a a question would the administration leave China with a grand deal that made
01:33:49
everyone feel like there's a long range view on a partnership and I don't think
01:33:52
that that's what happened. There were a few announcements obviously around an
01:33:57
intention to continue to work together in a cooperative way and find a path to partnership, an intention to establish
01:34:03
additional trade deals and and you know there were some purchases of aircraft and and some agricultural product
01:34:10
commitments but fundamentally the grand deal the big deal that I would say reduces deescalates tension probably
01:34:18
didn't manifest as some had hoped it would. And I don't think it's any
01:34:21
surprise that Putin is with Shei today. And this is also performative that following the US visit, there's now a
01:34:30
relationship bonding moment happening between China and Russia. So the story continues.
01:34:37
>> You know, there is no happy ending and there is no rainbow colored chapter 3 in
01:34:41
this book. It's going to continue to be a dramatic arc as this rising power continues to challenge the United States
01:34:50
and I think the story continues. >> Were you expecting a happy ending? >> I can't answer that question.
01:34:58
>> I mean to the story of the China visit. Not not I'm not talking about any other
01:35:03
things going on in your life, but >> did seem like some planes and soybeans
01:35:07
got sold, some H100s perhaps, but I mean it wasn't like there was some grand deal
01:35:13
that occurred, but it's nice to see them together, right? I mean, that is nice.
01:35:16
>> I think it was successful. I think there's what you see on the surface and
01:35:19
then there's what happens behind closed doors. And uh without speculating too
01:35:23
much, I think that it was a useful and productive trip. I think the the biggest thing that they probably got alignment
01:35:29
on is just geopolitically the tic-tac-toe of what has to happen next and and I think that there's some amount
01:35:35
of agreement there. I'm just guessing. >> Yeah. And so that guess if I was going
01:35:39
to unpack it, hey, we get uh we have Venezuela, we have Iran and Taiwan. you have
01:35:46
>> I would just say look here's this geopolitical chess board and >> here's what I would say just very
01:35:52
generally like it's just >> I think that there's a that there's a um
01:35:57
a way to divide up the game board in a way that helps them and helps us >> Gavin any thoughts on specifically
01:36:06
Nvidia being able to sell more chips into China material for the company good for America I mean it's obviously a
01:36:15
pretty debatable issue. >> I think I disagree with Chimoth on this. I think Stelling and deprecated Nvidia
01:36:22
GPUs to China lowers the odds of them developing their own alternative ecosystem which would be
01:36:31
a lot power hungrier um because you use optical you bring in optical a lot earlier for scaleup fabrics. I think
01:36:38
there's sound arguments that this is stabilizing for the world and is the best highest probability path for
01:36:49
keeping America ahead in AI and kind of keeping control of AI. And that's almost
01:36:55
a shame we've had to have this debate because now people like me have said this many times in China. If they didn't
01:37:00
understand it, they probably do really understand it. By the way, that's not to
01:37:03
say we shouldn't have had the debate, but um that is what I believe. You know,
01:37:09
reasonable minds can disagree. >> No, wait. What? Where do you think we disagree? I'm not I agree with you.
01:37:14
>> Oh, good. I'm glad we >> No, no, you start you started in agreement on
01:37:18
>> No, no, no. I'm like sell I'm like sell everything to them. No, what I was just
01:37:22
saying is that there was what you see on the surface of what they can speak to the press, but I think the most
01:37:27
important thing was the negotiation of hey, listen, like we're going to do these things. you do these other things
01:37:33
and that's never going to get put out in a multi- you know memoed press release.
01:37:37
That's my point. That's all I'm saying. >> Yeah. And I I would just say listen it
01:37:41
like American China talking is only good. We want to avoid theities trap that has been discussed and China talks
01:37:49
about a lot. They're very aware of it. And >> they brought it up. >> She brought it up by name.
01:37:56
>> Yeah. Hawking is a integral step of avoiding I have to say having a nice
01:38:02
resolution. I do >> from my perspective the the greatest superpower Trump has is his ability to
01:38:08
bond with dictators, monarchs, royal families, Gulf monarchies. He's just great at it. They see eye to eye. They
01:38:17
vibe. He has no problem going to see them. He has no problem inviting him to UFC fights. like this is like if if she
01:38:24
comes to the United States and he's sitting courtside with Dana White, like that's when we know things are going to
01:38:28
be okay. I do think he's probably given him the green light on like, "Hey,
01:38:33
Taiwan's yours. Just let's not have it during my administration. Maybe like we
01:38:38
do a 30-year deal or a 20-year handoff deal." I wouldn't be surprised if
01:38:42
something like that happens >> or a 100-year deal or a 200-year deal. But the one thing I would just say that
01:38:47
I'm sure was communicated is, hey, wars consume a vast amount of oil. You buy
01:38:53
your oil from Iran, Venezuela, and Russia. Russia alone can supply a fraction of what you need. And now it
01:39:02
should be clear to the world, >> two of the three are off the chessboard. >> Yeah. If you two or three are off the
01:39:07
chessboard, if you do something we don't like, Venezuelan oil gone for you. American oil gone. Brazilian oil gone.
01:39:16
And we'll say to all of our good friends in the GCC, we're so sorry, but we have
01:39:20
to close the straight of Formos again. So Iran, all of Middle Eastern oil gone for China. Now you just have Russia. And
01:39:29
good luck fighting a war with just Russian oil against us. Japan, South Korea, >> Australia, UK, France, Germany, the
01:39:41
world. Good luck. Who knows about Europe? But for sure, Japan would be there. For sure. Japan would be there.
01:39:47
>> Oh, and Australia for sure. Korea for sure. Yeah. >> And so, I think it's going to be a more
01:39:51
stable world on the other side of Iran, however it resolves. And I think that's
01:39:58
nothing but good. >> I think that's a good insight. >> I think it's a great insight. All right.
01:40:02
Listen, we missed you, Sachs. Come back soon. Uh, and Gavin Baker, >> shout out to Bestie Gavin. Thank you.
01:40:09
>> Yeah, you're so great. Thanks for coming. Uh, we appreciate it. Hey, and
01:40:13
uh, your father-in-law, what's his name again? >> Jeff Painter. >> Jeff.
01:40:17
>> Jeff Painter, >> we love you. Thank you so much for all the kind words. We'd love to invite you
01:40:22
to come to Liquidity or the Summit. I know you're a big fan of the show. Wanted to give you a shout out here on
01:40:27
the show. Uh, thanks. I used your fandom of the show to leverage Gavin, who was like, I can't make it today. And I was
01:40:35
like, "Tell your father-in-law we're going to get him backstage VIP tickets to the next two events if you
01:40:42
show up today. And if you don't, I'm going to back channel it to him." And
01:40:45
all of a sudden, Gavin made it to the show. >> Love you, boys. A little bit of
01:40:50
pressure. That's my way of the That's my hero straight. >> I'm always there for my father-in-law.
01:40:56
>> Absolutely. All right, everybody. See you next time. Thanks, guys. Great job.
01:41:01
>> Let your winners ride. Rainman David >> and it said we open sourced it to the
01:41:10
fans and they've just gone crazy with it. Love you queen of winners. >> Besties are
01:41:24
my dog taking your driveways. >> Oh man, my appetiter will eat me. We should all just get a room and just have
01:41:33
one big huge orgy cuz they're all just useless. It's like this like sexual
01:41:37
tension that they just need to release somehow. >> Your feet. We need to get Mercury's already.
01:41:54
I'm going all in.