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Today is Monday, April 14th, 2025.
4:45
We are live from the temple of technology, the fortress of finance, the capital of capital.
4:50
It's great to be back, John.
4:52
It is fantastic to be back.
4:54
I hope you had a great weekend.
4:55
I wanted to ask you something, Jordy.
4:57
Have you heard the story of the three wells? No.
5:01
Well, well, well, well, well, well. You got me. Well, well, well.
5:05
Uh, that was u Anyway, moving on. A very fatherly joke.
5:11
Uh, we have some breaking news.
5:11
Uh Ray Fiends, the actor, you might know him from Voldemort, from Harry Potter.
5:20
Uh he's been in a bunch of fantastic movies.
5:22
Uh The English Patient, Red Dragon, Grand Budapest Hotel, uh Schindler's List. Well, guess what? He's jacked.
5:29
And we got a photo of it here. Let's hear for Red. It's fantastic news. You love to hear it. 10 million views.
5:36
He's looking absolutely diced.
5:36
He is What What were people doing to community? 62.
5:41
He's 62 and he doesn't look day over 42 in my opinion. He looks great.
5:47
Anyway, we got some uh big company announcement today.
5:50
General Matter has launched the latest Founders Fund.
5:54
Such an unhinged way to start the show. Why not? It's good news.
6:00
This is important to the community.
6:00
This is what people want to know.
6:02
This is why they come to the show. This is exactly right.
6:05
They want to know about the latest and j the latest and greatest jacked 62year-old storied Oscar winning actor and they also want to know about the latest founders fund incubation which of course is general matter which which is number two on our list of top stories. Yeah.
6:20
After Ray's being jacked getting really diced. Uh yeah.
6:24
Uh but um I mean Scott Nolan looks great. I he looks very young.
6:29
I wouldn't be surprised if he looks better than Ray Fiend does when he's 62. Right.
6:32
But uh if you haven't been following General Matter is the latest incubation out of Founders Fund following in the footsteps of Palunteer Andural Varta and now General Matter.
6:45
Uh they are enriching uranium for the United States and they have their blog post here, their manifesto that went out this morning.
6:51
We will revive nuclear fuel production in America.
6:55
We choose to do this not because it is easy and not because it is hard but because it needs doing.
6:59
Nothing g gets made if fuel isn't made.
7:04
America's ambitions from manufacturing to AI all require nuclear.
7:05
It is the only source of energy that is reliable, scalable, and clean.
7:09
It's not only our future, but our present, powering most of almost half of our clean energy and about roughly 20% of our grid today.
7:16
Uh very underdised that we haven't had the nuclear renaissance and nuclear uh nuclear power plant buildouts at the big scale have like completely plateaued because of a bunch of regulation.
7:29
Everyone kind of knows that story.
7:29
But we're still generating 20% of our grid energy from nuclear. It's crazy. Um but the UN Yeah.
7:35
Isn't it interesting to think about 100 years out in the future, 200 or 300, we'll look back at the sort of um at nuclear energy as this sort of potentially this magical source of energy that we discovered and then decided uh actually like it's not so great and then realized like 40 50 years later, oh yeah, it's actually it's actually amazing. It's actually amazing.
7:58
We we should do more of it. Yeah. Yeah. that uh uh who is it?
7:59
Uh at Radiant, they they have some t-shirt merch.
8:02
It's a SMR manufacturer for small nuclear reactors.
8:06
Uh that's like it's like find the magic rocks out of the ground, uh let them heat up and then turn that into steam and then like that's how you get energy.
8:15
And it's just like this amazing gift that we've uh kind of looked past for the last couple years, but it's coming back.
8:19
Uh the US is currently forced to look abroad for our nuclear fuel.
8:23
Despite pioneering the technology, we've since outsourced enrichment to allies, competitors, and adversaries.
8:26
We didn't just give up the lead.
8:28
We're no longer even in the game.
8:30
And there's some really weird places where modern nuclear companies are getting like de like decommission nuclear submarines.
8:39
They take the the the fuel out of that because there's still a little bit left and then they refine it down and then they can use it like the supply chain for nuclear fuel has been really really decimated.
8:49
And Scott's kind of the expert in this.
8:50
We'll have him on the show soon to break it all down for us. Um I did an interview.
8:54
The language in here is amazing too.
8:56
The raw material is embedded in the bedrock beneath our feet.
9:00
America's future is written in stone. That's great.
9:02
Uh, we are turning our potential into power and exceptional talent is needed.
9:06
They've made some amazing progress.
9:08
Scott's been thinking about this for I think like two years or so, but he's been thinking broadly about what he would do at Founders Fund and whether or not he would incubate something for about 12 years.
9:16
Um, and uh, he finally found something that was the right fit.
9:21
There was no one building in this space.
9:23
And he's also made a bunch of investments in nuclear companies.
9:26
Um, y and I mean consistently it seemed like he said there was like a weak point in many of their presentations around where they were going to get fuel.
9:36
It was like, oh wow, super talented team, incredible group of engineers.
9:39
They're build they're going to build a reactor in Radiant's case like Doug is going to build that reactor.
9:45
But then there was kind of a question mark about like okay if this really starts scaling like you are very quickly going to be out of fuel and what's your plan and and every company in the nuclear space would say oh well like we'll figure it out when we get there or like maybe we'll uh we'll keep buying it from Russia.
10:00
It's like that's a good problem to have.
10:01
Yeah, it is a good problem to have.
10:03
So So it didn't stop the the underwriting of the investments, but Scott recognized that if the trend's real and it is uh there's going to be a need for this company and no one else was building it.
10:12
So that's why he's uh starting to refine nuclear fuel, which is amazing.
10:16
And they are also recruiting.
10:18
There's a uh recruitment post poster that's gone up at uh college campuses across the country.
10:23
Uh Jacob Rintto, friend of the show, uh f uh found one of these posters and solved it very quickly.
10:29
Uh it says, "Lost the US lead in nuclear enrichment, not seen for decades. Help us bring it home. Please text."
10:36
And there's a formula here. Uh yeah.
10:38
And these were all over the Stanford campus.
10:40
Yeah, I I think I think a few different campuses have seen them.
10:44
Um, but if you can figure it out, uh, give them a text.
10:46
Uh, I I I I took a look at it.
10:49
I thought it was pretty easy, actually.
10:50
I thought they could have done something a little bit harder.
10:53
I was able to kind of just do it in my head, but, uh, for most people, they'll need to kind of incorporate tutored by Scott Woo, right? Yeah. Yeah. Exactly. Yeah.
11:01
This is definitely something that I can just do in my head and just fire it off the text.
11:03
Uh, say, "Hey, step it up on the next one.
11:05
Make it a little bit harder."
11:07
Uh, but you're not really going to You're not really going to get the kind of quality you're looking for. Exactly. Easy to do in your head. Yeah, exactly. As a podcaster. Yeah, exactly. Exactly.
11:15
Uh but congrats to the team over at General Matter.
11:18
Uh very exciting and cool to see this like evolution of like the Palunteer, Anderl, Varda, General Matter.
11:24
Uh there's this Founders Fund is this interesting company or this interesting fund that when they incubate stuff, it's it's usually stuff that no one's thinking about doing.
11:34
And there's always been this question about like, well, surely they're going to run out of ideas.
11:38
like surely there's not another like really big hard tech company that no one's thought to build, you know, and yet like no one thought of this beforehand.
11:46
And so, uh, it's it's been it's been and I'm sure this will inspire other people to get into the nuclear fuel business.
11:53
But, uh, yeah, it's way too late. Yeah. Yeah. Yeah. Yeah.
11:58
Uh, if you're moving now based on this announcement, you're screwed. You're screwed.
12:04
Anyway, we'll we'll dig it.
12:07
We'll dig more in that this week and have Scott on the show.
12:10
I I actually want to do a whole energy day where we have Scott and a bunch of the other nuclear founders on.
12:15
Maybe bring Casey Hammer back to talk about solar because interestingly Casey and Scott kind of butt head on the future of energy. Casey's the solar maxi. Scott's the goat. The goat debate.
12:26
What is the goat energy source?
12:26
Is it is it uh is it uh fision that we do here with nuclear fuel like uranium or is it fusion from the sun? Because sun's free.
12:36
That's what the solar maxes would tell It's free.
12:37
Don't even have to dig it up out of the ground.
12:39
Just rains down on the earth. Yeah. Just catch it.
12:40
Uh but obviously there are a lot of drawbacks to solar and there are drawbacks to nuclear as well.
12:46
So we'll let them we'll let them fight it out in the debate. I'd like to have both. I'd like to have both. I I I posted about this.
12:52
I think the future of energy is underground nuclear reactors with wind uh with uh windmills on top that have solar panels on the windmills. Just collect it all. Why not? Why not?
13:05
Like why do you not put solar panels on top of every nuclear reactor?
13:09
There's no reason not to. Just do it. Yeah. Yeah.
13:11
Make the smoke stack out of solar.
13:13
I was thinking the future of energy was like a like basically like a sombrero or like a large hat that has a small nuclear reactor stored in it with a windmill on it.
13:21
Also like the kid like the kids cap. Yeah. Exactly.
13:24
Kids cap and it flies too.
13:26
So if you want to get from point A to point B, you would wear that.
13:30
You would the guy who doesn't wear AirPods is going to is going to put a nuclear reactor on his head. Yes.
13:35
Yeah, I I I for sure believe that, Jordan. For sure. For sure. Yeah.
13:37
Uh anyway, uh let's move on to some DGEN news actually with a great clip from Ray Dalio talking about I'm worried about something worse than a recession.
13:47
We have something that is much more profound.
13:51
We have a breaking down of the monetary order.
13:53
I want to give you a quick update on what happened over the weekend with tariffs and how the market is reacting.
13:58
Ray Dalio obviously runs uh Bridgewwater, huge hedge fund, and he had a one minute clip on Meet the Press breaking down his thoughts on the current uh tariff chaos and what's going on in the global economy.
14:10
Let's play that clip and we'll react to it.
14:11
Whether it goes slightly there, we always have those things.
14:15
We have something that's much more profound.
14:17
We have a breaking down of the monetary order.
14:20
We are going to change the monetary order because we cannot spend the amounts of money.
14:25
cannot spend the amounts of money. So we have that problem and when we talk about the dollar and we talk about tariffs we have that we are having a profound changes in our domestic order how ruling is existing and we're having profound changes in the world order such times
14:43
are very much like the 1930s I've studied history and this repeats over and over again so if you take tariffs if you take debt if you take the rising power challenging existing power if you take those factors and look at the PA factors that those changes in the orders the systems are very very disruptive. How that's handled could produce
15:05
How that's handled could produce something that is much worse than a recession.
15:11
I say America's built different and we're fine actually. Sorry, Ry.
15:13
Yeah, little bit of a black pill.
15:16
But he's been he's been on this train for a while. Yeah.
15:19
So he's written about rise and fall of empires for a long time and he has been kind of not like bullish on China but just saying that like all the trends lead to China really giving the United States a run for its money.
15:33
And so I mean you could call it warning signs, you could call it just kind of cynical calling balls and strikes, but he has been worried about this for a long time.
15:42
And I mean it's important to listen when someone like Ray Dalio's uh commenting on something like this.
15:46
Uh it it it has been a chaotic time and it has been a time where it feels like it's it's potentially high-risisk high reward.
15:56
If it plays out and America becomes more dominant than ever with artificial intelligence, manufacturing, reshoring, robotics, automation, all those things could be really good.
16:03
Um but if the dollar loses its dominance and we lose trade and all of a sudden become isolationist, uh that could be a lot worse. Yeah.
16:12
a little little too early to say to call that uh the entire monetary order of the world is being completely you know torn down.
16:23
But yeah, and this is what we were talking about with Tracy Aloway from OddLotss about uh the basis trade just that typically when the when when the stock market in America sells off, you see uh interest rates fall because there's a flight to quality and there's nothing seen as more high quality than American government debt.
16:44
But that hasn't happened this time.
16:46
And that's very very worrying because typically, you know, you should see people flooding into American government debt, but uh a few people have put it like we're trading like a developing nation now, which is not the way you want to be trading.
17:00
You want people to be buying those bonds, but we'll see where it's going.
17:04
Obviously, a lot of this could be rolled back.
17:05
We saw Trump roll back a lot of tariff stuff over the weekend.
17:10
And um again, you know, his fingers on the button.
17:14
He can change the rules at any time.
17:16
If he rolls everything back, maybe it goes back to completely normal.
17:19
Uh you know, this could play out in a million different ways.
17:23
And so, uh it's it it really is like too soon to call almost every single time.
17:28
So, uh the Wall Street Journal editorial board summarized it.
17:30
Uh his custom office, uh Trump's customs office announced tariff rate exceptions on electronics on Friday that he renounced on Sunday.
17:38
So, President Trump is taking exception to the idea that his administration is offering exceptions to his punishing tariffs. That's the story.
17:45
After a confusing weekend that offers more lessons in the arbitrary nature of Trump trade policy, late Friday, the CBP, the Customs and Border Protection Department, issued a notice listing that products will be exempt exempt from Mr.
18:00
Trump's so-called reciprocal tariffs that can run as high as 145% on goods from China.
18:04
The exclusions apply to smartphones, laptops, hard drives, computer processors, basically everything in tech, which got hammered super hard and is obviously super dependent on China. So, you carve that out.
18:14
All of a sudden, it's like, okay, what are we actually doing here?
18:16
Just like t-shirts and sneakers and T-Mu stuff.
18:19
Um, but uh and of course everyone everyone's reaction my reaction was, "Wow, Tim cooked."
18:25
Like Tim really just destroyed this with Apple. Yeah.
18:30
Everyone's everyone's reaction was, "Oh, Tim cooked."
18:32
Basically, it's like, you know, he set up Apple in this very precarious position and then all of a sudden he gets a he gets a rate break and and it looks very good for Apple.
18:41
But there's there's more to the story.
18:43
So, the CBP notice takes the tariff rate on those products down considerably.
18:47
Barons, it calculates that the exceptions cover 385 billion on 2024 imports.
18:52
That includes a 100 billion from China or 23% of US imports from that country.
18:56
The tariff rate falls to 20% on the newly exempted Chinese exports.
19:00
The press spent Saturday reporting this without caval from the White House.
19:04
So, so oftentimes when there's like a leak, it goes out, the press reports it and the and the and the White House the same day will be like, "No, no, no.
19:10
That that was the Walter Bloomberg leak." Right. Yeah.
19:11
Um, but uh the Wall Street Journal weighed in with an editorial on Saturday afternoon noting that this meant a big reprieve for powerful tech companies, though not for smaller manufacturers.
19:21
So, if you're just some small American manufacturer of size gongs and you make them in China, uh, well, too bad for you.
19:28
You got to get in the iPhone game.
19:31
Um, because the iPhone is now exempt, but the size gong market has been unchanged. Uh, Mr.
19:38
Lutnik hasn't been the most reliable voice on the administration's plan.
19:40
So, that was taken with some caution. Finally, Mr.
19:43
Trump jumped in late afternoon.
19:44
Nobody is getting off the hook for the unfair trade balances and non-monetary non-monetary tariff barriers that other countries have used against us, especially not China by far, which treats us the worst.
19:55
He wrote, "There was no tariff exemption announced Friday.
20:00
These products are subject to the existing 20% fentinel tariffs and they are moving into a different tariff bucket." Mr.
20:06
Trump blamed the press for reporting the exemptions that his own CBP had announced, albeit in stealth fashion, at uh 10:36 p. m.
20:13
Friday, and he announced that his administration is taking a look at semiconductors and the whole electronic supply chain for potential tariffs.
20:22
And can you give me a public.
20:25
com update on what Apple has been doing over the last day or two uh or the weekend?
20:30
Because I'd love to know how the market is reacting to this back.
20:33
Yeah, I mean Apple is up 13% on the last week. That's good. So, we love to see it. Unsurprising.
20:39
Only down 2% in the last month, which is wow.
20:42
Given all the chaos, that's crazy.
20:45
I mean, I get that there's like this back and forth battle that's going on, but to end up right where you started is pretty pretty good.
20:54
Tim Cook and he's earning his paycheck as Ben Thompson wrote. Um, who knows? Perhaps Mr.
20:59
Trump didn't like the reporting that tech giants like Apple and it shrewd and capable CEO Tim Cook were getting exceptions.
21:05
Other winners in the CPB notice would be Dell Technologies Michael Dell, Jensen Wong of Nvidia, and the executives and shareholders of Hwlet Packard and TSMC.
21:13
This is no wrap on them since their job is to look out for the best interests of shareholders and that means getting tariff carveouts if they can.
21:17
Some of the companies may not have sought exemptions though the opacity of the process for getting one is the beltway swamp's dream.
21:27
These CBP exemptions would be good news for consumers who were otherwise facing much higher prices uh for smartphones that are a staple of modern life.
21:34
How would you like a $2,400 iPhone?
21:37
I think they should make a $2400 iPhone.
21:39
They should make a goldplated one that's like 10k for sure.
21:43
I mean, they're being goods at this point.
21:44
You don't need to upgrade your iPhone.
21:46
You just swap the battery out and you're platinum iPhone. I'm surprised.
21:52
It truly is fascinating that that phones haven't gone that far.
21:55
Well, Apple tried it with the watch.
21:57
They had the Apple Watch edition that was goldplated.
21:59
It was $10,000 where the normal Apple Watch is like 300.
22:03
And it didn't sell well, of course, because you buy a $80,000 Protect Philippe.
22:09
It's going to still tell the time just as well in a hundred years.
22:13
That's not true for the Apple Watch version one that's going to be out of date and not even be able to talk to the server because all the code changed. Yeah.
22:20
But people buy something that's $5,000 from Balenciaga that's out of style in a year.
22:25
It's not about the style.
22:27
It's about the functionality.
22:28
Like the watch might not tell time in a few years. No, I know.
22:30
But so much luxury goods are about signaling purchasing power. Yep. Maybe that's the move.
22:36
Maybe we should all buy Apple watch editions that just are completely broken and bricked. Yeah.
22:40
And just be like, "Oh, can you tell me the time?" No. No.
22:43
Does that Does that Does that do your text messages on there? No. No. Nothing.
22:47
It's been bricked for six years because it's a 10-y old watch that cost 10 grand.
22:51
But I'm flexing on you nevertheless.
22:52
But there's better ways to flex.
22:54
If you want to watch, go to getbzzle. com. Just do it. Just do it. Um perhaps Mr.
23:01
Trump doesn't like the exceptions that are or doesn't like that exceptions are a tacit admission that tariffs will make American companies less globally competitive, especially in the artificial intelligence race.
23:10
That explains the exemptions for ASML's chipmaking equipment and Nvidia's graphics processing units. Mr.
23:14
Trump first makes US companies less competitive.
23:19
Then he and his administration pick exceptions worthy of help to remain competitive.
23:22
Politicians not success in the marketplace pick business winners and losers.
23:27
So not very free market oriented, says the Wall Street Journal.
23:32
Exemptions would also undermine the administration's legal justification that his tariffs are needed to meet a national emergency.
23:38
Imports of glassware and umbrellas from China are an emergency, but imports of electronics aren't.
23:43
All of this exposes the political nature of tariffs.
23:45
Some industries benefit and others don't.
23:46
Too bad if you make shoes, clothing, or thousands of other consumer products that must pay the tariffs but lack political or market clout.
23:54
We don't discuss politics, but Zack Weinberg, who was on the show Friday, had a post on Saturday that said, "We have now entered the socialism phase of Trump, where the government decides which industry you can have and which you can't.
24:07
Congrats to all the free market small government voters who have been tricked into voting for Donald Bernie Sanders. Donald Bernie Sanders.
24:14
Next up, more government price controls, lobby lobbying by corporate interests for exemptions and probably some taxpayer money going into harmed industries like farmers supply shortages and all the horrible things we actively hate about socialism.
24:26
So um aggressive um but uh that was specifically in response to the electronics news.
24:36
Yeah, it's uh it's rough.
24:36
It was first reported uh in Bloomberg, but we don't need to go through the Bloomberg article because it's kind of the same thing.
24:43
But as these percentages get more complex, businesses have to pay a percentage of their revenue on various things.
24:50
What should they do, John?
24:50
They should head over to Numeral HQ and organize their sales tax.
24:54
Put their sales tax on autopilot. Put on autopilot.
24:58
Spend less than 5 minutes per month on sales tax compliance.
25:00
Thousands of other fantastic companies are already using numeral to put their sales tax compliance on autopilot and you should too. Yeah.
25:10
Uh so there's an interesting dynamic here where the the the big tech companies are going back and forth on the tariff stuff. there.
25:16
You know, I think that regardless of where the final tariff number lands, Apple, Nvidia, these companies have gotten the message that at the very least, if they don't seriously consider reshoring or seriously consider getting out of China, like Trump's just going to make it chaotic for them, and that's not good.
25:37
He might not put them out of business.
25:39
He might not actually charge them 100% tariff, but it's not going to be fun.
25:43
There's going to be lots of meetings about how to do things and Apple's going to have to put, you know, iPhones on 747s and stuff and like you're going to be getting a lot of calls from shareholders. Totally. Totally.
25:52
Asking what you're doing. Have you seen this? Yeah.
25:56
Have you seen Have you seen this, Jensen? I'm a shareholder. Hey.
25:58
Uh but uh but but they're starting to take notice.
26:02
And so uh Brad Gersonner shares a post from Nvidia that Nvidia Blackwell chips have started production at TSMC's plants in Phoenix, Arizona.
26:10
Nvidia is building supercomputer manufacturing plants in Texas with Foxcon in Houston and Winstron in Dallas.
26:16
And so mass production at both plants is expected to ramp up.
26:21
And so there's another article in the Wall Street Journal about this.
26:24
Um, and uh, there's a very interesting book I'm trying to get the author on from it's called Foxcon, and it's all about the timeline of Foxcon getting into the United States.
26:32
And he tells the story of a particular Foxcon plant in, I believe, Wisconsin that didn't go well, and he kind of puts the whole project in the truth zone.
26:41
It's very interesting read.
26:42
Um, trying to get in touch with him, but he doesn't really have like a internet presence whatsoever.
26:46
Um but uh we're trying to get more folks who have dug into uh the supply chain from the from the journalistic and from the academic perspective on the show to explain that to us.
26:57
But um let's read through this Wall Street Journal article.
27:00
Uh Nvidia said it would start producing AI supercomputers that will be in manufactured entirely in the United States.
27:06
And the funny thing about that is like why are they using the term supercomputer?
27:10
Like because they could just say hey we're going to produce a bunch of chips.
27:13
Wait, wasn't wasn't Bloomberg also using the terminology Gigafactories. Gigaf gigafactories. Gigafactories. AI gig factories.
27:20
Now it's AI supercomputers.
27:22
You could just say, "Hey, we're going to print out a ton of A100s or H100s and then yeah, companies will wire them together and when they wire them together, you could call that a supercomput, but this supercomputer plant." Yeah.
27:35
Which is just which is almost just in incorrect to call it a supercomputer plant.
27:40
Well, I I just don't think of I don't think of Nvidia as building the supercomputer.
27:45
I think of Gro I think of XAI building the supercomputer with a bunch of Nvidia chips.
27:53
And the Nvidia GPUs when they are wired together, they become the supercomputer.
27:58
But you don't really use the term supercomputer for a single chip or a single GPU unit.
28:02
Although this could be a shift and and maybe Nvidia is building a data center.
28:07
I I think of supercomputer as a data center basically.
28:10
Uh this will be the first time that AI supercomputers, which are used to power data centers that solely process artificial intelligence, will be made completely in the United States.
28:18
The move comes after Trump administration officials said over the weekend that they are conducting a trade investigation into semiconductors, chip and chip enabled electronics.
28:24
We'll see new tariffs within a month or two, they said.
28:27
So this is all part of like the 90-day pause.
28:28
Uh you know, we're pulling back from the brink and renegotiating everything.
28:33
Um and so in that interim, Nvidia is clearly striking deals and also doing a ton of PR. Yeah.
28:38
and saying, "Hey, how do we get in front of the Trump administration?"
28:42
Obviously, we can get on the phone with them, tell them our plans, but it's going to read a lot harder.
28:47
Fox News, I mean, probably.
28:50
I wouldn't be surprised if it happens, but also placing a story like this in the Wall Street Journal, this is going to be shared within the Trump administration and they're going to read this and say, "Hey, Nvidia not only told us that they that they have this deal, they went to the press and they and they put it on the on the on the record that they are going to be uh investing very heavily."
29:08
And so Nvidia said it had commissioned more than 1 million square feet of manufacturing space to build and test its Blackwell chips in Arizona and AI supercomputers in Texas.
29:16
Companies working with Foxcon uh on a plant in Houston and Taiwan's Winstrong on a plant in Dallas.
29:23
Mass production at both sites is expected to increase in the next 12 to 15 months.
29:29
The recent flurry of reciprocal tariffs, particularly those targeted at China, have sent tech sector heavyweights scrambling to a to assess how their supply chains might be affected and shifted in the new sky-high if the new sky-high rates aren't adjusted downward through negotiations.
29:44
Uh comments from President's Trump team now uh appear to now be focusing on increasing US semiself-sufficiency uh which is a related but different goal than implementing tariffs to close persistent trade gaps.
29:58
Bank of America analysts said in a research note uh Nvidia said it plans to produce up to 500 billion of AI infrastructure in the US within the next four years.
30:06
Nvidia shares were up uh in early trading amid a broad rally for tech stocks.
30:10
So clearly just making exactly enough for Stargate.
30:14
Yeah, the Stargate can be an Americanmade data center. I love it. Just like Trump wanted. That's great.
30:21
When he went and at the White House, he announced the project.
30:24
I mean, it is like the the idea of like reshoring the full semiconductor supply chain sounds super daunting, but the early reports from TSFC's FAB in Arizona have been very promising and it's kind of been a narrative violation because everyone was saying like, it's never going to work.
30:41
And like apparently the the fab at TSMC in Taiwan is so precise that if if the if like the tide water is is slightly higher that will mean there's more moisture in the soil which produces more salt and people will track the salt into the building and then that will throw off the yield.
31:01
Stuff like that is like insane.
31:03
like that like the tiniest little earthquake over here can like completely destroy the system.
31:07
It's like it's so fragile and and and people kind of bought that and then they also bought that like hey how you use an ASML machine is not in chat like this is a uh this is a mastery uh like a but at the same time if you're moving production to the United States even if the yields are lower Yep.
31:27
it still makes sense to do from a business standpoint if there's a potential scenario in the next few years that Taiwan is invaded and and all of your production is shut down. Yeah.
31:35
And there might be incentives that that offset the cost. Yeah.
31:38
And and it's and again it's uh with with TSMC specifically like it's not a wage arbitrage play at all.
31:44
Like the people that work at TSMC are very highly paid.
31:48
So uh there there's no need where it's like oh like America doesn't have enough like people that are willing to work for $3 an hour.
31:53
Like that's not a problem in semis.
31:55
Um it's more skills anyway.
31:55
Uh so um shares of Nvidia were up amid a broad rally for tech stocks.
32:02
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32:08
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32:09
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32:10
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32:12
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32:17
And let's move on to what's happening with Apple with these tariffs.
32:21
So, the iPhone maker just received some reprieve from tariffs, but is still heavily reliant on the Chinese Chinese manufacturing economy. It helped build. Yeah.
32:29
So, we were talking about this.
32:31
Planes filled with iPhones have been leaving the Chennai airport in southern India for months.
32:35
A lastditch effort by Apple to delay a tariff calamity.
32:38
When President Trump last week ignited a trade war, it was clear that Apple could be hit hardest.
32:45
And for more than a week, it looked like time was running out for the world's largest company.
32:50
Then late Friday night, the company got some reprieve from the White House when the White House exempted iPhones, computers, and other electronics from its reciprocal tariffs.
32:57
Trump had targeted China, where Apple overwhelmingly makes its devices, slapping the world's second largest economy with 54% tariffs that swelled to 145% amid tit fortat retaliation.
33:08
The lower figure threatened to cut deeply into Apple's big profit margin from China made devices sold in the US.
33:14
The higher future uh the higher figure could have obliterated it.
33:20
It is unclear how long that relief might last.
33:22
Um, Apple shares are down 11% since the announcement and now they're like back to where they went, which is crazy. Yeah.
33:30
No longer fully accurate.
33:30
Um, but yeah, the the interesting thing we we were talking about this before the show. Yeah.
33:36
Uh, around you know, whether or not um, you know, what was the real um, sort of incentive for them to put all the iPhones on the 747s and fly them and make this sort of big show out of it.
33:51
And I think it was just the sort of pragmatic thing to do.
33:52
And then you said something that was interesting, which is that Apple always uses planes, almost always. Yeah.
33:58
There's reports that uh a lot of iPhones fly to America in the belly of 747s, usually passenger planes where there's just only so much luggage.
34:10
And most people don't even want to check bags these days.
34:12
They want to keep their bag up here and in in in the pressurized cabin.
34:16
And so there's usually extra space.
34:18
Uh, but it's expensive to throw your your products on there, but if you're Apple, you're fine.
34:22
And so, yeah, they've been doing that for a while.
34:24
They've always had that infrastructure built up.
34:26
But this is hilarious because the how many iPhones can fit in a 747 is like the classic like McKenzie interview question and it's always like when would I ever need to do that calculation?
34:36
Like I get that this is like an abstract Apple supply chain. Yeah.
34:40
And it's like, oh, this is actually extremely important to get right.
34:44
Um, and also it's it's funny because you hear like five 747s full of of iPhones.
34:50
It's like, you know, hundreds of thousands of iPhones or something and it's like it turns out that's like what they sell in like two or three weeks.
34:57
And so, uh, it's not like they moved so many that they're like out of the woods.
35:01
Oh yeah, we got six months of inventory out of the country.
35:04
It's like, uh, we might have saved like billions, but we make billions every single day.
35:07
And so it's one of those things where someone in the supply chain uh group saved the company a ton of money, but they are not out of the woods at all.
35:16
And so they they've been moving stuff around.
35:18
But this is what Tim Cook is known for.
35:20
Like in fact, he you could all of the all of the questions about like like oh Apple is no longer this like super Steve Jobs design product driven.
35:33
They're falling behind on Apple intelligence. Siri's not great.
35:37
Like Tim Cook doesn't seem to be leading into like this VR future really.
35:39
There's always this question of like would Tim T would Steve Jobs have shipped the Apple Vision Pro in that state like Tim Cook did but maybe Steve Jobs wouldn't.
35:47
Well like which is a bigger problem right now?
35:52
supply chain or like being a year or two behind on VR which no one really has working like this is an extreme bullcase for like for like Tim Cook is the right person to be at the helm right now because I'm I'm still using an iPhone. Yeah.
36:07
Even though Siri is not great yet and they haven't released new products that have delighted and I didn't keep my Apple Vision Pro, but uh but keeping the price of these computers in half through amazing supply chain negotiations and amazing management of the Trump tariff policy, like that is where Tim Cook will earn his pay and and validate that like he really should be at the top of this company.
36:32
and any any claims about like, oh, they're not moving fast enough.
36:36
This is game seven for Tim Cook. Yep. Game seven. Job's not finished. Job's not finished.
36:41
Um, and so certainly not.
36:43
Uh, people are saying that if this doesn't go according to plan, American iPhone could cost $3,500.
36:49
Uh, it would be interesting to see what what what that did to the market.
36:52
I don't think people would shift that much to Android because a lot of Android phones are made in China as well.
36:57
Uh, the bigger issue would just be people would just buy a lot less phones.
37:01
Like there are plenty of people that are on annual refresh cycles uh that would just switch to to every two years or every three years.
37:07
Um because at $3,500 like is it really worth it for like a slightly better camera or like one extra button on the side?
37:14
Like the the the improvements are so incremental uh once you triple the price you're you're you're getting into a place where uh you know you're just not going to drive upgrades.
37:24
So uh it took China 40 years to build a complex manufacturing supply chain uh says a professor at ASU um who previously worked ah for Apple in China. Uh we used to have that.
37:35
It's a disaster that we let it go.
37:37
And this is the interesting story of Apple and China.
37:42
Apple both helped China accelerate advanced manufacturing.
37:44
But on the flip side, the iPhone would not be as popular if China hadn't existed to help the iPhone scale.
37:52
Like in the early days of the iPhone rollout, it was such a popular device that they would never miss earnings because they were completely supply constrained and so they would just they would just go to their supply chain and say exactly how many iPhones can you make?
38:04
Okay, we will that's our forecast. Yeah.
38:06
And now with with with VR headsets, it's like the the the demand and supply is like wildly disconnected and now they're missing earnings much more not like missing but like it's much harder to forecast.
38:15
Uh so one one reason Apple is so closely tied to China's electronic supply chain is that the company helped build it.
38:21
It began working with Chinese suppliers more than two decades ago and increased production there in 20 in 2004 as a new hit product the iPod was taking off.
38:29
It had help from a friendly government and Apple in turn trained suppliers to meet its exacting standards. Yeah.
38:36
In time, Apple helped build an ecosystem of more than 1,000 suppliers in China.
38:40
The iPhone maker taught them how to operate more efficiently, so they competed with one another, driving down Apple's costs.
38:48
Apple manufacturing partner Foxcon built a compound so large in uh Jungju is that uh that is known as iPhone City.
38:58
Combining low cost with premium price devices means Apple's share of profits for all smart smartphone production globally can top 80% even when its share of device shipments is below 20% according to Counterpoint Research.
39:11
Other countries don't offer the same promise as a manufacturing hub.
39:12
Guthrie found when he studied alternatives for Apple.
39:16
India has lots of work workers but bureaucracy can make it more difficult to move quickly.
39:20
Apple suppliers in India have focused on two southern Indian states that have more streamlined processes.
39:26
Apple supplier Foxcon has has its main India factories near Chennai.
39:32
Indian officials hope the new tariffs on China would help the country take on more of the Apple supply chain beyond final assembly, but such an effort would take years.
39:40
Yeah, there there's another uh there's another flip side of this which is like there's some scar tissue at Apple from a previous manufacturing effort uh that Ben Thompson highlighted as strategy.
39:53
Um he said uh Steve Jobs in his first tenure at Apple was deeply committed to manufacturing including building a futuristic factory in Fremont for the Mac.
40:05
So he was all in on American manufacturing.
40:07
Uh I think this was back in the 80s maybe the 90s.
40:09
Uh it this merely cost the company millions.
40:12
Um his attempt to do the same for Next all but drove the company out of business.
40:17
So he left, he went to Next and was like, "Of course, we're going to have like the most futuristic gigafactory like what Tesla does now."
40:24
Um but but building your own manufacturing is extremely high stakes because if you if you don't build enough, it's very diff it's very different than being really good at designing totally products. Totally. And innovating.
40:37
Uh so we almost went out of business at at Next.
40:39
Uh what Apple needed and eventually found in China under Tim Cook was scalability.
40:42
Apple would focus its integration chops on getting the product right and trust contract manufacturers to achieve the flexibility of meeting demand.
40:50
And the flexibility of meeting demand in China is insane.
40:53
is insane. I I heard some stat that there are 1 million migrant workers who uh travel to iPhone city for what's what's called the push where there's a new iPhone coming out and they know that everyone's going to upgrade right around
41:08
the holidays because the iPhone drops in like September, October and then it and then people buy it October, November, December and then there's like a steady flow of them but the vast majority of the sales happen in that Q4 period. So
41:19
So you got to manufacture them all, right?
41:22
Then so there's a million people that literally like live in the countryside, come in and just assemble iPhones like 18 hours a day for like 3 weeks or like grand three months. Yeah, grand.
41:32
Uh and then and then they leave and and America just has nowhere near that amount of like labor flexibility and neither does India. Neither does Vietnam.
41:42
Estimate is that America has six million unemployed people. Yeah.
41:47
So, so the idea that you're gonna get a large percentage of those people to only in one city. Yeah.
41:54
And and like we don't have cities that are set up for that.
41:56
Like when the Super Bowl happens, everything grinds to a halt.
42:00
When the Olympics happens, like it's a calamity in America.
42:01
Whereas China's like, "Oh yeah, like uh we have we have a million apartments sitting right there vacant because we built them up over the last 20 years.
42:08
Sure, they all look like Soviet block, like cinder block.
42:13
We had Coachella over the weekend. Oh, yeah. 125,000 people.
42:15
turns into a bit of a nightmare. It's a nightmare. Yeah.
42:18
I mean, just getting in and out of Black Rock City for uh for Burning Man is a disaster.
42:24
Uh but China's like really built up this infrastructure to allow they have a lot of empty.
42:29
They have a lot of empty apartments for sure. Comes in handy.
42:30
And so, uh this more broadly is an important addition to the capability discussion above.
42:36
Manufacturing has changed from being a point of integration with a product to being a horizontal horizontal scalable services offering.
42:42
developing the customer service chops necessary for such a business would be a significant cultural change for a US manufacturing base.
42:50
Allah Intel Intel's struggle to become a foundry.
42:53
To that end, one benefit of a war over Taiwan is that it would be so terrible for tech companies that there really isn't much benefit in planning for it.
43:01
planning for it. the hedging cost which would entail building out those scalable horizontal p service providers which for economic reasons must serve more than one company or product would be so astronomical that it probably wouldn't be economical to do anything other than deepen the status quo and so if you
43:15
think about Apple's approach to the vision pro like that was an incredibly expensive product that could have been it was extremely hard to forecast because remember during the rollout like there was all this like uh there was all this like energy around like oh wow they solved it like VR's finally here. Everyone's going to get this. Sure, it's
43:32
Everyone's going to get this.
43:32
Sure, it's a little expensive, but everyone's going to have it.
43:34
And then the first week of Apple Vision Pro on Axe was like, "This is incredible. I've seen the future. I've seen the future. It's here.
43:42
Everyone's got to have this."
43:42
And I think people were right in that they saw the future.
43:47
The form factor wasn't quite there yet. Yeah.
43:50
Uh yeah, they glimpsed it.
43:50
And so, how do you forecast demand if you need to build out a massive manufacturing plant for Apple Vision Pros?
43:57
If you get it wrong on the low side, you're not going to be capturing all the value while you're out of stock for years.
44:03
And if you build out a massive automated facility, you're going to sell, you know, uh, and then demand comes in weak week.
44:11
You have all this capex that you're not going to repeat like like, you know, be able to reap the reward from and it's just going to be a disaster.
44:16
Whereas, I'm sure Apple was pretty much unaffected by the Apple Vision Pro kind of being a flop because they just went to their contract manufacturer and they were like, "Yeah, like we're not going to make that many of them."
44:26
They're like, "Okay, like that kind of sucks for us, but like we we take the risk with you because we love working with Apple as well." Yeah.
44:31
The real pain there was was a failed product launch around something that not necessarily failed.
44:38
Like you can argue that it that it was Yeah. that it was fine.
44:43
It was a demonstration of the technology and Apple will continue to invest.
44:47
whether or not that's really that true, but uh yeah, when you're selling 233 million iPhones a year, you can launch a new product and have it not do super well and you're going to be okay. Yeah.
44:57
And so uh Tim Cook used to yap about this, but he's kept his mouth shut over the last decade, but if you go back to CBS 60 Minutes in 2015, he said the US over time began to stop having as many vocational kind of skills.
45:12
You can make every you can take every tool and die maker in the United States and probably put them in a room that we're currently sitting in.
45:20
In China, you would have to you would have to have multiple football fields.
45:24
And I think that's so true because you ask the average person like and they're like, "What's a tool and die maker?"
45:29
Like, I don't even know what job that is.
45:31
That doesn't mean anything to me.
45:32
Um, just put the fries in the bag, bro.
45:35
That's what we're good at in America.
45:37
Uh we we we do some vocational stuff, but it's not even a it's not a vocation.
45:42
Like putting fries in the bag is not something you need to go to a trade school for.
45:44
Uh we do like extremely low skill and then extremely high skill like oh you have to you have to understand like PhD level philosophy for this job or whatever uh or like you know legal or business or finance or medical or any of this stuff.
45:57
Um but it is also the low-skilled workers whom Apple needs.
46:02
In China, there isn't only a massive supply of them available, but under the country's mobile labor labor system, which we discussed, uh they work for only a few months.
46:09
This army deploys to help Apple increase production volumes ahead of the US uh holiday system, then retreats when volumes fall.
46:17
And so, uh it's uh it's interesting to see how Apple's navigating this.
46:20
We'll see where it lands, but if Apple wants to control costs through a time like this, they should go to ramp. com. Time is money. Save both.
46:28
use corporate cards, bill payments, accounting, and a whole lot more all in one place. Go to ramp. com.
46:34
No idea where that came from, but we do have Ara Kurasian uh economist over at RAMP coming in later to talk about what they're seeing across the RAMP business corporation platform uh in terms of you know various you know economic data points.
46:50
So well excited to dive in there.
46:52
Should we go through the Texas lottery scandal in the next 17 minutes? This was a fun story. This is a fun story.
46:58
So, uh, Gambling 911, who I did not follow before this, says, "This Texas lottery scandal is so convoluted.
47:06
Mark our words, this will be made into a Netflix docker film in the not too distant future.
47:09
At heart of the scheme, the Joker.
47:11
NCO lotteryies were targeted by these groups."
47:14
And so, the Wall Street Journal has a whole deep dive on a secretive gambler called the Joker who took down the Texas Lottery.
47:20
This has happened in the past, but this is maybe the most dramatic telling of it. And so, yeah. high level.
47:26
This is a story about groups of people that realize there are opportunities to game lotteryies in order to have, you know, outsized chances of winning.
47:37
Basically, they recognize that if they can go post up somewhere and print millions of tickets in a few days, they can uh, you know, have a really good chance at winning a lot of money.
47:46
So, so the the man's name is Bernard Marelli and he had a plan in his mind. He is in part.
47:51
He and his partners would buy nearly every possible number in a coming drawing. There were 25.
47:58
8 million potential number combinations.
48:00
The tickets were a dollar a piece and the jackpot was heading to 95 million.
48:04
If nobody else picked the winning numbers, the profit would be nearly 60 million. Martin Elliot. Yeah.
48:10
It's something I didn't really realize.
48:11
I'm not a big not a big lottery ticket guy, but I didn't realize that two people could pick the same number. They can.
48:16
And so you can pick the same number and uh and and and what happens is the winners just have to split the proceeds.
48:24
So they actively are trying to pick numbers that aren't tickets that will be split because a lot of people just do 1 2 3 4 5 6.
48:30
So you don't want to pick that number, you know, interesting.
48:32
And so they fly to the US with a few trusted lieutenants.
48:37
This guy is a London banker turned book maker.
48:40
Uh, and they set up shop in a defunct dentist's office, a warehouse, and two other spots in Texas.
48:47
The crew worked out a way to get official ticket printing terminals. This is the crazy thing.
48:52
Apparently, if you're really really into lottery, you can just figure out a way to actually just get your own machine.
48:57
Yeah, you are going to have to bring in your own paper if you're printing a high volume.
49:02
Well, I I've been doing this with Poly Market.
49:05
I had Poly Market set up like a like an on premise installation of the Poly Market code that runs I run my own chain, my own decentralized Yeah.
49:12
on my own Blackwell, my own data center, my AI supercomputer so that I have access to my own Poly Market because I'm just hooked. Hooked.
49:20
So trucks hauled in dozens of them and reams of paper over three days.
49:25
The machines manned by a desperate bunch of associates and some of their children screeched away nearly around the clock spitting out hundred hundred or more tickets every second.
49:35
Texas politicians later liken the operation to a sweat shop.
49:37
And so to be clear like they they basically spin up these systems which is like almost what you can imagine is like a disaster response type situation where it's like they have a warehouse, they have a bunch of folders and they're just like filing they're printing the tickets, filing them.
49:53
There's actually there's actually a phrase for exactly what this is.
49:55
Uh it's do things that don't scale. Yeah.
50:00
Paul Graham talked about this. Yeah. Yeah. Exactly.
50:01
So I don't know if it was in the context. They're going found.
50:03
But yeah, this is called going founder mode on the Texas lottery. The Texas lottery.
50:09
So trying to pull off the gambit required deep pockets and a knack for staying under the radar.
50:12
Both hallmarks of the secret Tasmanian gambler who bankrolled the operation.
50:16
Born uh Zelko Ranojak, he he was nicknamed the Joker for his ability to pull off capers at far-flung casinos and racetracks.
50:24
Adding to his mystique, he changed his name to John Wilson several decad the most generic name of all time.
50:32
Hey, I need something that that flies under the radar.
50:36
And then you read it in a story about him changing his name to John Wilson and you're like, okay.
50:40
Like he just like picked he's like, what is like the take the two most common name? Yeah. Over the years, John.
50:48
Him and his partners have won several hundreds of millions of dollars by applying Wall Street style analytics to betting opportunities around the world.
50:56
Like card counters at a blackjack table.
50:58
They use data and math to hunt for situations ripe for flipping the house edge in their favor.
51:01
Then they throw piles of money at it, betting an estimated10 billion dollar annually.
51:07
Wow, that's a lot of money.
51:07
The Texas Lottery Play, one of their most ambitious operations ever, paid off spectacularly with a 57. 8 million jackpot win.
51:16
That in turn build their activities.
51:19
I guess they they must be doing a if they're doing 10 billion and this 57 million win where they bet 25 million.
51:28
It must be that they're doing a lot of traditional sports betting markets slight edges 51%. Yeah. More more programmatic. Yeah.
51:35
I mean you see this with like hedge funds where oh they traded a billion dollars a day and it's like what makes Yeah.
51:40
What makes this story fascinating is it was like a boots on the ground operation.
51:44
They sent like Delta Force in to just gamble. Yeah.
51:46
So earlier this month, the state lieutenants governor the state's lieutenant governor Dan Patrick called the cruise win the biggest theft from the people of Texas in the history of Texas in response to written questions addressed to the to the to the joker.
52:02
Glenn Gellbend, a New Jersey lawyer who represents the limited partnership that claimed the Texas prize said all applicable laws, rules, and regulations were followed.
52:09
Dan Patrick of Texas states lieutenant governor is calling this the biggest theft from the people of Texas in the history of Texas.
52:15
That said, it does seem like the Joker and his crew have a good argument that they didn't break the law. Yep.
52:22
They're saying it's a theft because they gamed the system. Exactly.
52:26
But it's not necessarily illegal. Yep. Yeah.
52:28
And this has actually happened before.
52:31
Uh, I remember a a professor at Nor Eastern um figured out the math behind breaking a lottery like this and then he published a paper on it, but he never actually went and implemented the strategy, but kind of proved it and then and then the lottery changed to kind of harden against this type of attack.
52:46
It's kind of like a 51% attack on Bitcoin, honestly.
52:50
Uh, so lottery hunters and pro gamblers have a good reason not to court the limelight.
52:55
Publicity can draw the attention of tax authorities, encourage bookies and lotteryies to tighten rules, or worst of all, inspire copycats who might make a run at the next big jackpot and split the prize.
53:04
A group of Princeton University graduates incorporated under the name Black Swan Capital has won millions in recent years playing scratchoff tickets and other lottery games in various states.
53:13
This is a different group running the same playbook where they go and set up shop.
53:18
It it it's really funny to think about your let's say somebody's running, you know, convenience store and just all of a sudden this like college kid comes to you and they say, "Hey, so I'm going to be buying 500,000 lottery tickets in the next 24 hours for Also, imagine you're just like an average Joemo and you're just like, yeah, like I just like every once in a while when I'm getting gas, I pick up a I pick up a scratch off ticket.
53:44
I just hope that I'm going to win one day.
53:45
And then you find out that there's basically a hedge fund on the other side of the trade dumping $50 million against you.
53:51
And you're not just playing against the house, but you're trading against the house.
53:55
And like a very mature financial organization uh run by Princeton University graduates. That is rough.
54:02
Lottery officials and others who have tracked their tactics say they appear to calculate when the math is is most in their favor using publicly available information such as how many prizes are in a game and how many remain unclaimed.
54:12
When the odds are right, they swoop in, hoping to win back more money than they spend.
54:15
One Black Swan team member collected a $5 million win in Missouri in 2019.
54:19
Another one 10 million in North Carolina in 2022.
54:22
In Maryland, a Black Swan team used lottery machines in four liquor stores for four days to win a $2. 6 million prize.
54:28
And this idea, so this is interesting.
54:30
So, Black Swaners used to appear in lottery marketing promotions, smiling and holding ceremonial checks. Interesting.
54:37
But in recent years, they've mostly stayed quiet, obviously. Yeah.
54:38
You can imagine the first few wins they were they were down to get, you know, the comically large check and then they realized like this is putting a massive, you know, we're basically marketing our own operation here. Marketing alpha.
54:50
I remember somebody at Caltech did this maybe like 20 or 30 years ago with the McDonald's uh Monopoly prizes. Do you remember those?
55:00
You you get the fries and it comes with two different Monopoly stickers.
55:03
you peel them off and the way the McDonald's monopoly worked there was like a million-dollar prize and if you uh almost everyone would get would get Boardwalk but Parkplace was extremely rare that was like a one in10 million chance to get it.
55:18
Uh but if you got both of them boardwalk and Parkplace you would win a million dollar prize.
55:22
And so what they figured out was that because this was not a lottery, it was a giveaway legally, they had to allow anyone to enter uh without no purchase necessary.
55:35
And so what the Caltech people figured out was that they had access to modern printing infrastructure that would allow them to mail in millions of Yeah. submissions.
55:44
Hi, I just would like a an entry into your lottery.
55:51
uh it's not a lottery so I don't need to pay to be entered.
55:53
don't need to pay to be entered. Uh just put me down for one ticket a million times and they won and then it became this big thing and they were dropping off like truckloads of papers being like each one gets me one entry and no one expected that they would do this because
56:08
the math on like the the the postage stamps should be higher but they figured out they could drop them off and they found all these arbitrageages and then eventually one and then and then they changed the rules probably and said like okay max like 10 entries per person or something. Um anyway, like all lotto
56:20
Um anyway, like all lotto retailers, so uh the the team actually recruited one such seller, struggling struggling startup lottery.
56:27
com to help with the logistics of buying and printing the millions of tickets.
56:31
Like all lotto retailers, uh lottery.
56:32
com collects a 5% sales commission, which is unfortunately, we'll find out, only on the cost of the ticket, not on the proceeds. Okay.
56:42
So, the Texas Lottery Commission allowed dozens of the terminals that print tickets to be delivered to the four workshops set up by the team.
56:50
That April 19th, the commission announced that there had been no winner in that day's drawing.
56:53
The next drawing with an even larger pot would be three days later.
56:56
On Saturday, the group sprang into action.
56:58
The printing operation ran day and night.
57:01
The team had converted each number combination into a QR code.
57:03
QR uh crew number crew members scan the codes into terminals using their phones then scrambled to organize all the tickets in boxes such that they could easily locate the winning numbers.
57:13
Yeah, imagine you win and you're like we know we have the number in one of these 200 million tickets in this warehouse.
57:19
Um got to get the game called for picking six numbers from 1 to 54.
57:24
For a pro gambler, some sets of numbers such as 1 2 3 4 5 six aren't worth picking because so many other players choose them which would split the pool.
57:32
Uh, the operation bought 99. 3% of the possibilities.
57:35
Money moved from lottery money moved to lottery.
57:38
com from the Joker's account held under the name John Wilson in the aisle of man, a tax a tax haven off the UK coast.
57:45
Taking a sec, by the way, is of man. Yeah, it's great.
57:50
Yeah, we should go uh we should go on a vacation there.
57:52
Maybe Wander should book a should book a wander out there. Yeah, of man.
57:55
Uh taking auditous route via an escrow account at a Detroit law firm.
58:00
According to people familiar with transfers, the crew hit the jackpot that Saturday.
58:04
One of their tickets was the sole winner.
58:06
About two months later, the lottery commission revealed that the prize had been claimed by a limited partnership called Rook TX with and the winner had elected to remain anonymous, the commission said.
58:14
Which actually makes sense that you want to allow people to be anonymous because if you force them to take a picture with a big check, that's just like a hey, come kidnap me moment, right? Yeah. Or just shake me down.
58:28
Hey, I got a business idea.
58:30
I'm starting a foundation model.
58:33
Do you want to put some money in? That type of thing.
58:35
There's a lot of that going on in Silicon Valley right now.
58:37
Starting a nonprofit foundation model.
58:40
Uh the secret, however, didn't stay secret for long.
58:42
The state officials were outraged when they learned how the operation went down.
58:45
State Senator Bob Hall blamed the Texas Lottery Commission, saying the incident signaled the possibility of an organized crime ring being embedded in the Texas government.
58:53
They think they got an insider. Greg Abbott was true.
58:55
No, ordered the Texas Rangers to investigate, saying the state's residents deserve a lottery that is fair and transparent for everyone. I agree with that.
59:04
They probably should have the California Rangers. Really? Yeah.
59:07
Texas really lucked out with that one. What do we have?
59:11
Stadies or highway patrol or something? CHP. Highway patrol. That's about it.
59:15
I guess we have sheriffs, right? Or sheriffs are federal. I don't really know.
59:19
State lottery directors say they are seeing more organized efforts to buy lottery tickets in bulk, but that the groups are largely operating legally and transparently.
59:27
Uh, state lotteryies like the one in Texas are in a sweet spot for the pros.
59:31
The jackpot the jackpots are big enough to be worth shooting for and the number of possible combinations minimizes the risk of multiple winners.
59:37
Multi-state games such as the Powerball often have far bigger pots, but there are so many combinations that buying them all would be unwieldly and cost too much.
59:45
just wait until they find out about artificial intelligence.
59:49
Maybe they're going to figure out a way to go for the Powerball.
59:51
Some hedge fund is going to get into that.
59:53
Citadel is going to be like, "Yeah, we have a new Powerball desk that's spinning up." Yeah.
59:57
Just we Yeah, we we we hit print here and there's a thousand factories.
1:00:03
We have We have lottery ticket printing fac Gigafactories. Yeah. Just just Oh, yeah.
1:00:07
It actually makes uh the Tesla Model 3 line look like, you know, a uh like this could mean a bull market in the printer space for sure. For sure. Um yeah.
1:00:18
And so uh another example in Oklahoma, the Black Swan Swan team recently made a play at a scratchoff game with a $5 million prize on the line.
1:00:26
They set up at a hotel and spent three weeks scratching off tickets.
1:00:28
So insane, but left the state without getting the top prize. Must be brutal.
1:00:34
Yeah, because with the scratch like they can't they can't like print them themselves and so they're so much harder to organize.
1:00:38
They actually have to scratch them all off.
1:00:40
I bet they had some really pro They weren't using a coin.
1:00:42
They probably had some like uh you know deicer like machine scratching. But that's wild. That is insane.
1:00:48
Uh honestly good take from John Martin, Maryland lottery director.
1:00:53
He said on a podcast, "How is this any different from an investment group buying stocks to gain an advantage over time in the marketplace?" I don't know that it is.
1:01:02
You can take a holier than thou attitude and say, "Well, if it's not right, it's not fair."
1:01:07
But again, it's not illegal, and it's probably not a bad business strategy, which I think is uh generally uh the right take here. Yeah. Well, what a fun story.
1:01:17
You love to see these like little little gambits.
1:01:20
We'll see if it we'll see if it is considered cheating.
1:01:24
I'm sure it will be uh hotly debated in the courts and then ultimately um boiled down into you know new sets of rules but uh it's it's it's it's hard to know like should you put a max number per person should you do oh you know something about per split it per entity because a lot of people just casually will have like you know handshake deals with their friends who are like oh we all buy lottery tickets and if any of us win we'll split it.
1:01:51
Yeah, that's just like a common thing and how are you gonna make that illegal?
1:01:55
Um, so considered cheating.
1:01:57
Once the teams on the ground in Texas had their printing their ticket printing operation in full swing, lottery.
1:02:03
com executive Greg Pototts texted an associates, "Things are going great."
1:02:07
Uh, thanks to the mass buying, the size of the jackpot was soaring.
1:02:09
The Texas Lotto Commission put out a news release saying it was the biggest since 2010.
1:02:14
Lotto Texas fever is sweeping across the Lonear State. had said. It's so funny.
1:02:19
If you're running the Texas Lottery, you're just like, "Wow."
1:02:21
Like, there's just all this demand for our lottery tickets and it's from this one our ad campaign this this quarter must have been fantastic.
1:02:28
Like whoever whoever wrote the copy for that billboard, they need a promotion.
1:02:32
And it turns out it's just some hedge fund that came in and is just like decimating your whole plan. So brutal.
1:02:38
Uh, Don Nettles, a self-appointed watchdog who has published the Texas Lottery Report since soon after the lotteryy's inception in 1992, headed out to stores in Dallas and Garland.
1:02:50
She didn't see any evidence of lottery fever and figured a pro gambling outfit was vacuuming up tickets.
1:02:55
Nettles bought several dozen tickets in a longot bid to split the winnings.
1:02:59
I like how Don Nettles is just like I'm the watchdog. But look, fun is fun.
1:03:08
I gota I got to be in the game.
1:03:08
I I I I got to feel the rush somehow. What if I win?
1:03:11
And and if you know that they're buying, she's saying the same thing that a lottery buyer says. I said, "Come on, God.
1:03:18
Let me hold the winning ticket so we split it and they don't come out with a profit." Called.
1:03:22
So she's like, she's the watchdog, but she's actually acting like a watchdog. Yeah.
1:03:28
She's betting against the hedge fun.
1:03:29
She's like, "If I could take 50% of their winnings and just bankrupt them, that would be so satisfying."
1:03:33
It'd be more satisfying than just actually winning.
1:03:35
And so this is this is some interesting um background.
1:03:37
So that Saturday the commission announced the winning numbers 3518 2930 and 52.
1:03:42
Within hours Marelli's crew had located the winning ticket in a file box in one of their four workplace workspaces.
1:03:50
So it took them hours to actually find if they had the ticket. Yeah, which is crazy.
1:03:54
An associate snapped a photo of a smiling Marentelli holding up the winner flanked by team members in boxes. Um, and lottery.
1:04:04
com ended up making just $264,000 on its commission on this. It's not that much.
1:04:12
Uh, which seems low given how big the winnings are.
1:04:15
But again, that's, you know, that commission uh for lottery.
1:04:19
com is based on, you know, what 5% of basically the the cost of of purchasing the uh tickets.
1:04:25
But this is the big uh the big debate point.
1:04:27
Uh, Texas Lottery Commission Executive uh, Director Ryan Mindell, a deputy at the time, said the mass buying had compromised public perception about fairness.
1:04:38
He said the request for ticket terminals had been approved by a junior employee and complied with policy.
1:04:42
The lottery commission and Texas Rangers continue to look into the episode.
1:04:48
Lottery officials and state lawmakers have taken steps to prevent a repeat.
1:04:52
Yet, progamblers, it appears, haven't lost interest.
1:04:55
And so, yeah, I mean, if everyone if everyone finds out that they're being that they're playing against hedge funds, basically, they're they're not going to be as likely to actually play.
1:05:04
Um, what I'm interested in to know is like I think that this could be a net positive for the state of Texas in a weird way, right?
1:05:13
Because Texas makes uh you still have to pay taxes on it.
1:05:17
And so, um, the money that goes in is the money that goes out minus taxes.
1:05:22
And so uh and and the and the critique of of the lottery was that it's a tax on lower income folks who buy lottery tickets.
1:05:31
And so if instead you're just you're just letting I mean you're still taking money out of the people who are more likely to lose than ever.
1:05:40
But yeah, but something like this potentially compresses the the basically the margin that Yeah. Who who knows? No. No.
1:05:50
I I I think it I think the net effect is just higher tax receipts for Texas.
1:05:54
And and yes, uh the average lottery player is less likely to win, but it doesn't mean that the the the the citizens of Texas who are gambling are losing more money than ever.
1:06:07
They're losing the same amount of money.
1:06:08
They're just guaranteed to lose it.
1:06:10
Um but uh yeah, and it's interesting.
1:06:12
one one fix basically a patch that they pushed out.
1:06:15
The Texas Lottery Commission got wind of the effort and thwarted it by pushing out a software update that limited the number of tickets a terminal could sell in a day.
1:06:24
So they're basically saying like you're not going to be able to buy, you know, 25 million.
1:06:28
Well, we have Tyler Cowan here on the show.
1:06:31
So, welcome to the studio, Tyler. Good to see you. How are you doing? Good.
1:06:36
My video is blocked when I tried to start it. Oh, odd. I'm sorry for this. No problem.
1:06:41
We can just do audio for now and maybe Okay.
1:06:43
I have used the video lately. It may be on your side. Maybe.
1:06:48
Um well, we'll troubleshoot it.
1:06:50
Let's just talk uh like it's phone call. Okay, great.
1:06:52
Um I wanted to start with uh artificial intelligence.
1:06:55
Uh there's a there's a new release from OpenAI today, but it's mostly about uh programming and a new code model, but uh can you give us an update on how you're using uh just any AI tools really and what your experience has been?
1:07:11
Well, I use AI tools for everything.
1:07:14
That was almost an understatement. Yeah.
1:07:17
So, I just took a trip to an event in southern Utah and I used uh strong AI to plan the whole thing, the whole route, where I would visit, where I would stop, where we would eat.
1:07:28
Uh it worked wonderfully.
1:07:30
Uh there were not hallucinations.
1:07:31
But more typically, if I'm reading a book, uh most of the books I read are history books.
1:07:36
So, I want background on things that I don't know the full story for.
1:07:40
And uh then what I'll do is just keep on asking the AI.
1:07:45
So instead of reading say seven books on a topic, I'll read maybe two and spend the rest of the time uh asking the AIs.
1:07:53
So that's a very different approach. Yeah.
1:07:54
But you get very good customized answers and you can keep on asking.
1:07:56
Uh it's right in front of you.
1:08:00
You don't have to wait for the book to come.
1:08:01
At the margin is cheaper than ordering more books.
1:08:05
So it's changed my whole life.
1:08:05
Do you think the future is not ordering the book at all and just talking to the AI?
1:08:12
Because a lot of these books are so baked into the LLMs, you could just you could just hear about a book and then say, "Hey, tell me about the first chapter."
1:08:20
And then it'll kind of spit out the basic or using memory functionality, you can say, "Tell me the tell me the things that you think I'll actually care about." Oh, yeah. From this book. Yeah.
1:08:31
How do you Well, you're saying the future.
1:08:33
I would say it's the present.
1:08:34
Yeah, I guess you're right.
1:08:36
Now, you might want one or two books to get you started on your questions.
1:08:38
I'm not even sure you will need that at some point, but I don't think my status quo practice is to have no books, but it's to have radically fewer books.
1:08:51
Um, what about kind of the uh the post education piece of reading these books?
1:08:58
Are you are you doing any uh interactions with AI to uh kind of like take notes and memorize things or or kind of collect your takeaways while you're reading and learning new new topics?
1:09:12
No, I've never really taken notes on things with or without AI.
1:09:14
So, I don't I don't think I'll start now.
1:09:19
Now, as you mentioned before, there is now AI memory.
1:09:21
Yeah, I've only had that a very small number of days.
1:09:24
Uh I'm not sure what I'll use it for.
1:09:26
I'm not sure it will matter for me, but uh we'll see.
1:09:32
It might send things my way I wouldn't have known of otherwise.
1:09:37
So, I do think about what queries I feed into the AI.
1:09:39
I'm not worried about privacy, but I just want to be smart for it so it thinks I'm smart and treats me accordingly. Yeah.
1:09:47
What uh what about deep research?
1:09:50
uh is has that worked its way into your workflow or has kind of the 5 to 10 minute delay been a barrier to adoption?
1:09:58
Uh the delay is no problem for me.
1:10:01
I've been using 01 pro more than deep research because often I just want short answers. Yeah.
1:10:06
Uh I've used deep research quite a bit for my class.
1:10:09
So if I want them to read a paper on something, well I can look on Jtore or I can just have deep research create the paper. Mhm.
1:10:17
and it does that very well.
1:10:21
I think it's still a bit wordy, but it's very impressive and and really quite accurate.
1:10:26
So, it is double or triple checking things.
1:10:28
It hallucinates less say than Google or Wikipedia might.
1:10:31
So, I've been using that. It's gone quite well.
1:10:35
Can you talk a little bit about uh the the workflow with teaching?
1:10:38
You mentioned last time you talked something about uh kind of a a flip to the way you teach where uh you are judging the students on how much they teach you.
1:10:49
Can you kind of reiterate and expand on that idea?
1:10:53
Well, one thing I do in this class, this is a PhD level class in history of economic thought.
1:10:58
I tell my students they need to write their papers using advanced AI and I grade them just on how good the paper is.
1:11:06
They then should explain to me how they used it and I will indeed learn things from that.
1:11:12
But we're already in the world where so many people are using this, how well you can write a paper without AI.
1:11:19
It's not any kind of predictor or useful indicator of how well you're going to do.
1:11:23
So, we just need to start teaching them that skill.
1:11:25
So, I teach them what I know.
1:11:27
I encourage them to provide tips and advice to each other.
1:11:30
You know, we're all new at this, right? It's a new thing.
1:11:34
Uh, and we're all learning as we go along. So far, it's been great.
1:11:37
How are you thinking about um AI and the future of work, job displacement, um, all of that?
1:11:45
Well, you say future, but I would stress the present. Yeah.
1:11:48
I think a lot of companies should hold off on hiring people with particular skills because those people will not be as good as the AI is likely to be, you know, a week or two from now would be the blunt way to put it.
1:12:05
Are there different sets of skills that companies should be hiring for like a certain I don't know if it's like neuroplasticity?
1:12:11
Uh we like to joke about uh a concept of like golden retriever mode being uh friendly and uh focusing more on friendliness than intelligence because intelligence is becoming too cheap to meter.
1:12:22
But being a great co-worker and being a great interface between different parts of the organization and ultimately AI models who provide the intelligence uh potentially is is growing in importance.
1:12:35
What what's your read on that?
1:12:35
I use the word charisma for your friendliness. Yeah.
1:12:40
Uh they also have to inspire the other people and simply being friendly doesn't do that.
1:12:45
You might need a sharper edge.
1:12:47
So a lot of people in VC, I wouldn't say they're unfriendly, but friendly isn't exactly the way you would describe them.
1:12:53
They're they're inspiring first and foremost.
1:12:55
I think also having good taste is very very important.
1:12:58
So someone still has to interpret the products of the AI or you know decide what's a good answer or which model to ask a particular question and that's a question of taste.
1:13:10
So taste and aesthetics have become more important.
1:13:16
What about um I mean is it is it useful to look at the initial roll out of the internet where it felt like wisdom or knowledge became too cheap to meter and that maybe became less important to have someone on your team who just was an encyclopedia of facts because it became so quick to look up everything.
1:13:37
Been through this before, right?
1:13:40
Growing up, yeah, you know, being born in the 90s and then having access to the internet almost as soon as I was very conscious. Yeah.
1:13:50
I was intuitively aware that memorizing sort of facts uh didn't feel like such a valuable skill set in the classroom because you would go home and you'd be doing your homework and you'd obviously be sitting in front of a computer and have access to that information.
1:14:03
Yet, it was still baked into the curriculum pretty intensely.
1:14:07
But you're basically saying what is a curric almost like what does a curriculum look like if intelligence is like well you don't need to focus on wisdom and maybe you don't need to focus on intelligence and maybe it's just purely charisma from now on I don't know Tyler well I'm not sure of all the net effects here but keep in mind the people
1:14:22
who know a lot and understand it that's an important qualifier uh they're now you know a thousand times more productive than before because they're managing these armies of AIs so you you may not need to hire more of them but the ones you hire who are good will be much more important by a lot, not just by a little. So I don't think
1:14:40
So I don't think it's simply substituting away from intelligence.
1:14:45
You want beings who can manage other intelligent entities, humans or AIs and a lot of those people will be very smart. Yeah.
1:14:55
Uh do you think the bicycle for the mind metaphor is uh still apt?
1:14:57
I mean uh bicycles are great but it's better if you're Lance Armstrong, right? Uh sure.
1:15:05
I'm not sure I know the metaphor though.
1:15:07
Uh this was Ste Steve Jobs said uh uh a computer is a bicycle for the mind.
1:15:12
Uh in the sense that uh a human on a bicycle is the most efficient uh energy per uh mile per hour uh device even faster even more energy efficient than a cheetah.
1:15:25
Uh, and so a human by by themselves is uh underperforming relative to a cheetah, but you give the human a bicycle and it's the most energyefficient mode of transportation, I think. Oh, sure.
1:15:37
Yes, that makes sense to me.
1:15:39
So, I think some mix of knowing facts but understanding them, having great taste, and having the initiative to manage an army of AIS and the willingness to do the juggling involved.
1:15:53
It's a very complicated set of traits. Mhm.
1:15:55
But my sense is the people who have those will do just very very well.
1:15:57
Um can you talk about you know you wrote recently around uh American soft power and AI.
1:16:05
If you had to sort of summarize your your takeaway from from the article, you know what what would you share with our audience?
1:16:13
Well, it makes me more optimistic about America that we're the AI leader.
1:16:18
You know, the Chinese models, Deep Seek and Manus, as you probably know, they're based on American AI.
1:16:24
So, as the Chinese government uses AI more and more, it will be more dependent on Western modes of thought, and they can censor the AI on Taiwan, on Tienman Square, but they can't really change how it thinks without making it much stupider.
1:16:41
So, we're taking them over is one way to put it.
1:16:44
Not in the sense of conquering them, but the Francis Fukuyama vision I think will be realized through AIs. Can you expand on that?
1:16:54
Well, the smartest entities in China, you know, already, but more and more as the future arrives will be AIS and those are American again, even if it's Deep Seeker Manus.
1:17:05
So, their smartest entities all of a sudden are American.
1:17:08
How would we feel, you know, if all of our smartest entities were Chinese?
1:17:12
we'd be like, whoa, well, that's the position we're in now. That's a great take. I like that.
1:17:18
Um, you have something, Jody?
1:17:18
How do how do you think of uh tariffs in the trade war in the context of the AI revolution?
1:17:26
We we were joking, not not joking, it's a serious topic, but as these sort of tariffs, you know, were rolling out.
1:17:32
Um, I I was saying this almost feels like in some way, you know, picking up pennies in in front of a steamroller.
1:17:39
Um, and you've said before that you don't sort of believe in in sort of this almost instant massive GDP growth, but it still feels like AI has the potential to transform our, you know, economy by 10,000% and tariffs can have an impact, a very significant impact on a bunch of different factors, but maybe not even necessarily as impactful and maybe the wrong thing to be arguing about as a country.
1:18:09
But I'm I'm curious to get your take on on on it.
1:18:11
The AI race is much more important, but to win that, you want free trade in the inputs for AI, which is quite a few different things.
1:18:22
Now, you might want export controls on China, which we have to some extent.
1:18:24
I'm not sure they're effective, but I don't see any downside to trying them.
1:18:28
Uh, but in the meantime, you want to just take in everything as much as you can, as cheaply as you can, as quickly as possible.
1:18:37
So, I would say it's an extra reason to be skeptical about the tariffs.
1:18:41
You I mean, you said there's there's maybe no downside to trying the export controls.
1:18:45
Are you familiar with Ben Thompson's new argument that uh maybe the downside is that it makes an invasion of Taiwan more likely and in fact keeping the Chinese dependent on Taiwan increases global stability if you take away the trade restrictions.
1:19:02
I don't know that I'm fully in support of that, but that's the argument that he's been making.
1:19:08
I've discussed that with Ben.
1:19:10
I don't think it's impossible that he's right.
1:19:13
It's just very hard to predict that kind of thing.
1:19:16
I'm not sure the expected value calculation falls his way.
1:19:21
Again, I I would gladly admit export controls may not work out well.
1:19:27
It just seems odd not to try the first order policy to slow China down. Mhm.
1:19:29
I suspect whether or not they invade Taiwan on whatever date, uh, they'll just develop quality, you know, chips and lithography themselves and it probably won't matter that much.
1:19:44
Uh, but trying to forecast their their Taiwan decisions, it's just it's very hard to have a good theory of that one way or the other. Yeah.
1:19:51
Uh, how excited are you about American semiconductor production?
1:19:56
We've, you know, there's the the TSMC facility in Arizona seems to be having good results.
1:20:03
Nvidia is talking about, you know, partnering with Foxcon to produce 500 billion dollars of of their new Blackwell chip.
1:20:08
Uh, is all of that, you know, market how how real is that in your mind?
1:20:14
Is that something that, you know, we think that you think the United States can sort of lean on when it comes to the sort of broader AI race?
1:20:23
I read and hear a lot of propaganda on that saying it's going very well.
1:20:25
I don't feel I have trustworthy sources of my own.
1:20:31
As an economist, my view tends to be supply is elastic and if you pay for something, you'll get it.
1:20:36
So, I suppose I'm inclined to believe the propaganda.
1:20:40
Uh but I'm still not sure yet. Makes sense.
1:20:42
Um uh what has been your reaction to uh Ezra Klein's new abundance agenda?
1:20:53
Well, it would be much better for the Democrats and the Democratic Party and indeed all of us if the party became about that and that's Ezra's main goal.
1:21:03
So, in that sense, I'm fully on board. Yeah.
1:21:05
But that said, I think one has to go a lot further.
1:21:07
And I had a podcast with Ezra on my own podcast.
1:21:10
And I'm like, well Ezra, are you willing to fire a lot of these people?
1:21:15
You know, they're in the way.
1:21:17
There's cliocracy plus AGI is coming.
1:21:19
And he and Jennifer Pulka, they both seem like very reticent to me.
1:21:25
When you push them on, okay, I agree, but let's go a bit further here.
1:21:27
Like you can't just be right 10%.
1:21:29
If you're right, and I think you are right.
1:21:31
you know, you're right, 75% or more.
1:21:33
So, let's take this as a good step one and see it through consistently.
1:21:41
Yeah, it seems like one of those uh platforms that's almost directly out of the West Wing where it's inspirational.
1:21:48
It can win, but will it actually work?
1:21:52
And those are two different questions.
1:21:53
And I think he might this might be something that is a message that can win but maybe not change things is is my fear.
1:22:01
But I don't know if you if you feel the same.
1:22:03
Well, I don't know if it can win.
1:22:05
So, I suppose my view of the Democratic party is that it will splinter the way the Republican party has splintered.
1:22:11
So, the Republicans right now to some extent they're unified around the figure of Donald Trump, but intellectually they're all over the map.
1:22:20
That may have upsides, downsides, but I think it's clearly true.
1:22:22
And I suspect the same will happen to the Democrats.
1:22:26
So, the abundance thing will be one faction of 17.
1:22:28
It'll be the one I'm rooting for.
1:22:30
It'll win some partial victories. That'll be nice.
1:22:32
But I don't think it will ever be in charge.
1:22:35
I don't think any of them really will be in charge. Yeah.
1:22:38
Do you think it's more driven by the personality of the particular candidate?
1:22:44
Because uh with the Trump election, you would see a diehard libertarian voting for Trump, you know, in the same in the voting booth next to them is someone who's highly protectionist in favor of tariffs.
1:22:59
And they both kind of wound up rallying around the same person for very different ideological reasons.
1:23:04
My guess is that will happen to the Democrats also.
1:23:08
I mean, Biden was like the anti-personality candidate.
1:23:10
He literally had no personality.
1:23:12
you couldn't go meet with him, you couldn't see him on TV, there wouldn't be a press conference.
1:23:18
It's sort of like I mean he he didn't exist in fact in a way.
1:23:20
Uh and I think they'll rebel against that and way overshoot. Yeah.
1:23:27
Jordy, do you think we need uh more weird uh ideas around AI?
1:23:30
You shared something earlier out of uh Google.
1:23:33
something earlier out of uh Google. uh they're they're using uh Google's uh I think it's their deep mind team is using Google AI to help decode dolphin communication which just feels like it feels like right now there's a lot of attempts on uh which I think are
1:23:48
important of unlocking the power of AI in private equity unlocking unlocking the power of AI for lawyers yet there's this whole other sort of spectrum of of ways that you can apply this technology and I and I personally I would like to see more more you know maybe there's not
1:24:03
immediate commercial opportunities but at the same time uh you know I can imagine US consumers would probably pay $100 a month to be able to communicate with their dog you know so like maybe there are uh sort of exciting commercial opportunities and sort of humanto animal
1:24:19
communication but how do you think about you know needing um sort of newer uh more sort of creative ideas uh as this technology gets broadly adopted strong agree I want to be the first human to do a podcast with a dolphin I feel I already communicate with my dog. He has little more to say than what
1:24:37
He has little more to say than what I get already, which is I want to eat.
1:24:39
I need to, you know, go in the backyard and so on.
1:24:44
Uh but yes, I think the non- elites will come up with a lot of these ideas and they'll be hugely successful. Why?
1:24:52
Why non-elites specifically?
1:24:52
I mean, that example was from Google feels like the most elite people in the world or like the most elite team in AI at least.
1:25:00
I don't know who there had those ideas. Sure.
1:25:03
Uh talking to the animals is a Dr. Dittle thing, right? Is he an elite? I don't know. Yeah.
1:25:08
But I think uh elites feel threatened and indeed will be threatened by AI because it's smarter than they are.
1:25:15
And a lot of non- elites will just be like, how can I make this useful for me? Yeah.
1:25:20
Because they're not expecting to be, you know, the so-called smartest person in the room. Yeah. That's why.
1:25:25
Speaking of that like kind of weird useful AI, how did you process the Studio Gibli moment a few weeks ago?
1:25:32
Well, no elite would have predicted it, but obviously people loved it and just something about it worked.
1:25:40
Uh, I hope it didn't, you know, fry the servers on the cloud computing, but you know, the stuff is still up and running.
1:25:47
And there was something online, I forget the numbers, but some radical upsurge in use of chat GPT in the last few weeks. Sam gave the numbers.
1:25:54
just stunning and we're gonna have a bunch more of these moments in the next year or two.
1:25:59
Do you think there will be a kind of a a cohesive renegotiation around intellectual property that comes out of the AI era? Uh, I hope not.
1:26:11
But, you know, media is in big trouble because you can read a smarter, clearer version of the story on the AI tailored for you.
1:26:19
There is a free rider problem here. Mhm.
1:26:23
Uh I don't know what kind of arrangement we'll come up with.
1:26:27
I don't want government subsidized or government controlled media.
1:26:31
Uh maybe it'll be some weird barbells equilibrium where there's like the New York Times and then there's bloggers and and tweeters and not that much in between. I don't know.
1:26:41
I do think it's a real problem.
1:26:45
But to make the AI companies pay for everything the model reads, that strikes me as a bad idea.
1:26:50
And I would rather win the AI race with China than do that. Yeah.
1:26:55
I mean, Nat Friedman was just uh kind of running the numbers and saying that uh OpenAI has more than enough money to hire every single journalist in America on a full-time salary just to create content that eventually goes into the training and into the models.
1:27:09
Uh which is a very very odd outcome, but financially it could work.
1:27:14
I I don't know if that's actually how it'll play out though.
1:27:17
Yeah, Google has a lot of money.
1:27:19
I'd rather see corporations do it. Sure.
1:27:21
Bloomberg, where I used to work, both has money and does hire a lot of journalists and that's very high quality. Yeah.
1:27:30
So, there's a number of models.
1:27:32
I just prefer to keep the government out of it and not to slow down the AI companies either.
1:27:39
Do you think that AI is broadly priced in yet?
1:27:42
It feels like Nvidia in many ways priced uh priced to perfection.
1:27:45
Uh but it feels like many other industries haven't had maybe the uh and companies haven't had the corrections you might think they would have if they were on the verge of massive disruption. People are asleep.
1:28:04
While the disruption may come slowly, it will come.
1:28:06
And I think there's a lot of places, companies with mid-tier quality software that will end up devastated, you know, within five years.
1:28:16
Not as quickly as some of the crazy people think, but you know, within a time horizon relevant for share prices. Yeah.
1:28:22
Like I I look at people today the hot thing has been buying accounting firms and like buying an accounting firm that does accounting for small businesses that and and you're buying a com a firm for call it eight times earnings and it's like do you believe that in five like the idea is like in like small businesses will be quick to adopt technology that saves them a meaningful amount of money.
1:28:46
So the idea is like can you keep prices high? Yeah.
1:28:50
Grow earnings and introduce technology that basically undercuts you know the existing service offering that you just paid up to get.
1:28:57
Uh I I don't know if that's a that's a good strategy. That's a great example.
1:29:03
You know if you could short nonprofits I'd short most of them too. Savage.
1:29:11
Well, I mean, speaking of the some of the crazy people, uh, did you have a chance to read or read about AI 2027?
1:29:17
And what was your reaction?
1:29:21
Well, I always ask those people, are you short the market?
1:29:23
And I never get a straight answer.
1:29:26
Those are private conversations, but there's one prominent doomster.
1:29:30
His response to me was, well, I don't know how to short the market. I just giggled.
1:29:36
I'm like, ask the AI if you don't think the AI can arrange that for you.
1:29:40
It's probably not very threatening. Yeah.
1:29:42
So, look, any new technology has a lot of dangers.
1:29:45
You shouldn't rule out any scenario.
1:29:48
But what I tell those people is do what the climate change people did.
1:29:52
Take this to peer review, referee journals, make a serious case.
1:29:57
Don't just write, you know, the blog post with 17 different vertically arranged separate points. Yeah.
1:30:05
and see where you get with it.
1:30:05
Uh, the other kind of response I have, it's jokey but also serious.
1:30:10
I say I would rather be an American paperclip than a Chinese paperclip. So, it's coming anyway.
1:30:18
You know, you want to have it on your terms.
1:30:22
There is no pause option.
1:30:22
We got to try to win this thing. Yeah.
1:30:25
How um how do you think about AI adoption?
1:30:31
And I know it sounds like a simple question, but I I feel like this is an interesting technology where every single person that I know and I am in a bubble, right?
1:30:38
I live in I live on the coast.
1:30:40
I work in, you know, tech broadly.
1:30:43
Uh and everybody I know and and even I I was talking the guy who details my car.
1:30:48
I was I was telling him that he should expand into a sort of adjacent category because I wanted it myself.
1:30:53
and and he told me that he spent, you know, the entire ride home uh last week, you know, talking about just talking with chat GPT, right?
1:31:02
Like using it as a sort of like personal tutor on a business opportunity.
1:31:07
So, it's we're in this interesting scenario where uh AI in many ways seems in sort of certain segments seems to have been like, you know, fully adopted like it's being used uh and you know, and now it's just more about the sort of capability unlock right in in all these different use cases.
1:31:24
But I'm curious how you think about sort of okay, everybody's using AI now.
1:31:28
Um, but they're not I mean it's totally brutal.
1:31:32
You've got to get out of your bubble.
1:31:35
Like a lot of people use chat GPT for something trivial. Yeah.
1:31:38
They don't take it seriously.
1:31:40
It's like another app like they used it to name the dogs puppies or something and they have no idea it's going to change their lives.
1:31:49
That's the default mode of every elites. Yeah, that makes sense.
1:31:52
And I was at a prestigious New York event just like two or three months ago with five people, all of whom are well known.
1:31:58
And I used the three-letter phrase AGI.
1:32:00
Not one of them knew what I meant.
1:32:03
I don't mean they didn't understand it in a deep sense. Maybe none of us do.
1:32:07
They didn't even know what I was referring to. That's where we're at. Wow.
1:32:11
Um Yeah, that that that's shocking.
1:32:15
Um how do you think about uh economic growth?
1:32:18
It feels unimaginable that AI would not be the thing to disrupt stagnation and get us at least to three, four, 5% real GDP growth annually.
1:32:34
And yet, it doesn't feel like we've seen it yet.
1:32:36
Even in energy production, I think China's adding 20% energy uh production a year and it's still essentially stagnant in the United States.
1:32:46
Um, are you expecting things to change or will it just be a reshuffleling of the deck even though things will be disrupted?
1:32:54
There's not really a net new experience of our economy or or our energy infrastructure.
1:33:02
I think it will improve slowly.
1:33:02
But if you look at our economy, and I'm going to sound like Peter here, like just add up what percent of it is totally non-functional, non-adaptive, bureaucratic.
1:33:14
much of health care, most of government, higher ed, K through 12, nonprofit sector, like that's more than half the economy, right? Yeah.
1:33:22
And at what speed will that respond?
1:33:25
The stuff that responds quickly, which is great, of course, it becomes so cheap, it it's an ever smaller share of GDP.
1:33:33
So, it it's very hard to get the growth rate up by a lot. I think it will happen.
1:33:37
But one way to put it is the better the AI is, the more the human imperfections matter.
1:33:44
We're already at the point where they're going to put out new models.
1:33:46
And most people aren't smart enough to see that they're better. Yeah.
1:33:51
So, I'm all for the new models.
1:33:54
They will ultimately matter, but you need to restructure, rebuild almost every institution for the growth rate to truly accelerate, and that will happen.
1:34:03
But it's a a generational project. Is that a warning sign?
1:34:07
I I mean the the counter to every uh to every AI doomer has always been in my in my mind like we the the cars aren't even driving themselves yet fully.
1:34:19
Like surely the cars will drive themselves for a couple months before the cars are terminators that are killing us all.
1:34:26
Um, and uh, and is that kind of like a like an early warning sign for taking AI more seriously, or should we already be really discussing AGI at every uh, fancy dinner party that you get invited to?
1:34:42
Well, I think we're going to have AGI this coming week, so depends how you define it.
1:34:47
I think driverless cars, as they spread, will have a big impact.
1:34:50
And they're coming to Washington DC this year.
1:34:54
Oh yeah, that's an important city for obvious reasons and I think that will change many people's perceptions.
1:35:02
Yeah, because they do work and they are much safer and there are no associated problems except maybe for the two days a year it snows here.
1:35:09
So yeah, I think that will really matter.
1:35:12
But right now it's what San Francisco and Northern Arizona and one other place. Yeah.
1:35:16
Uh, and the Bay Area people, they are pilled, white pill, black pill, whatever about AI, and no one else is.
1:35:24
New Yorkers are the worst.
1:35:26
I think DC, the national security people are pretty awake. That's that's very good.
1:35:30
Uh, even the staffers can be pretty good.
1:35:34
We're way ahead of New York in DC, but that's not saying much.
1:35:39
How do you uh do do you feel like humanoid robots are are like you know somebody uh you know a Henry Ford alternative saying like I'm going to build a mechanical horse or do you think that humanoid robots can be uh the right uh form factor for uh AI you know embodied sort of AI labor.
1:36:05
Robots still seem far away to me.
1:36:05
I'm not dogmatically convinced they're far away, but I would say they're far enough away that it's difficult to forecast when they'll get here.
1:36:14
So, my thinking is mostly about the smarts in a box more than the robots.
1:36:20
The robots seem to need pretty controlled environments.
1:36:25
Uh, San Francisco streets are that, factories are that, and that's already significant, but just that there's like more robots than people in the world, uh, that seems distant.
1:36:38
um on robots that could have a potentially, you know, faster and greater impact um or at least greater in the short term.
1:36:47
How do you think about uh companies like Zipline that are doing instant delivery via drone?
1:36:51
Uh we had the founder of Zipline on last Friday and it was pretty exciting to think about just reducing congestion on roads by eliminating all these big heavy cars driving around you know a hamburger for 20 miles um you know all day long. I'm all for that.
1:37:10
It's pure gain, but I think those gains are pretty small.
1:37:12
And we could already do congestion pricing as a few places have done and solve that problem as it is.
1:37:19
And most of traffic is not like your Amazon delivery person.
1:37:22
Uh it's a modest share of it.
1:37:26
So again, I'm all for it, but I don't think it will noticeably change life. Yeah. on on the AGI question.
1:37:34
I feel like these definitions uh get wrapped up in benchmarks or or you know IQ tests or human performance.
1:37:41
Um but I've always wondered if it's almost better to think about the impact of AI through an economic lens and say something like AGI is here when AI is doing is producing GDP greater than humans or something along those lines.
1:37:59
Uh, is that a useful framework or am I just thinking about it all wrong?
1:38:03
You know, Satia Nadella said some version of that but with different numbers.
1:38:08
You know, my AGI definition, just to be totally self-centered, is when it's smarter than I am, I call it AGI.
1:38:15
And I think that's coming within the next few days.
1:38:17
So, I get that's not the only definition, but surely it's a meaningful benchmark of some kind. Yeah. Yeah. Yeah. Yeah. It makes sense.
1:38:26
It's just uh the the it's the difference between like fast takeoff, slow takeoff, almost like fast roll out versus slow roll out.
1:38:34
Um we we could have the you know genius intelligence that that's too cheap to meter, but I think people won't care as much until it's actually everywhere having an impact all over the world.
1:38:48
And so, uh, I I think that like once it arrives, it could it could drop just like the passing of the touring test dropped where we just kind of move on with our lives.
1:38:58
I have one very short last question I think is relevant.
1:39:03
Tyler, how much smarter do you think you've become due to AI and and using it, you know, dayto-day, if if at all?
1:39:12
I don't I'm not sure what you mean by smarter.
1:39:15
So, I've been using it lately to learn English medieval history and I know much more about that than I would otherwise.
1:39:23
I mean, more like maybe quality of thinking.
1:39:27
No, I don't think I don't feel that way.
1:39:30
Uh, you know, in chess that's been a factor, but I think maybe it will help some people who are less rational.
1:39:37
Maybe I'm already there and so irrational I don't know it, but I don't feel it's improved the quality of my thinking.
1:39:44
Is that dependent on like discoveries like or or almost like frameworks like if if AI discovers the next you know law of supply and demand that would make every economist smarter, right? I don't think it will.
1:40:00
I think there's a lot of areas we're never going to learn much more.
1:40:04
Not because the AI is weak, just there's only so much to learn. Sure.
1:40:06
But I think there's a lot of people, you see this already, like the AI tells them to calm down or please rethink that email before you send it.
1:40:15
Sure, that's quite significant.
1:40:17
I just don't think I'm in that category at age 63.
1:40:19
Yeah, but yeah, it's helping a lot of people think better. Uh just not me. That makes sense.
1:40:27
Well, thank you so much for hopping on.
1:40:28
We really enjoyed talking to you. Yeah, very insightful.
1:40:30
We'd love to have you back in the future.
1:40:32
This was really enjoyable conversation. My pleasure as always. See you around. Take care. Talk to you soon. Bye. See you.
1:40:40
Next up, AGI this week, folks. AGI this week.
1:40:43
You heard it here from Tyler. Yeah.
1:40:46
I wonder I wonder what is he referring to exactly.
1:40:47
Is this a new OpenAI release? I don't think it's 41. Okay.
1:40:52
Because that was really oriented around 4. 1 because we're at 4. 5.
1:40:54
Anyway, uh let's bring in our next economist.
1:40:59
We're doing a little econ day here.
1:40:59
We got Arazzian from RAMP.
1:41:02
You might have heard of him when we did our personnel news segment. Look in the suit. In the suit. Looking great. Uh great to talk to you. Welcome to the show. How you doing? Thank you guys.
1:41:12
I'm a big fan of the show.
1:41:13
You guys have done such done such a good job. I love the announcement.
1:41:15
So happy to jump into it. Yeah. Yeah.
1:41:17
The idea with those is uh you know, very low TAM, but we want to set the Slack account on fire in whatever company uh get gets one of those messages.
1:41:28
Uh but thanks for joining this the show today.
1:41:32
Uh we want to talk about the release today.
1:41:34
Can you break down uh the announcement, how regularly the these spending reports are, and then we'll go into some of the top takeaways.
1:41:40
Yeah, I mean I'll start by talking about the main question that I get asked a lot is that, you know, what is my job? Why do I do it?
1:41:49
Why does RAMP even have an economist?
1:41:50
I think it confuses a lot of people.
1:41:52
Uh, but I think it really does come from RAMP's product, right?
1:41:55
It's a spend platform, but what RAMP, I think, figured out very effectively is that businesses aren't just looking to spend money.
1:42:04
They're looking for help on how to make decisions, uh, how to spend their money most effectively, what the best businesses are doing. Mhm.
1:42:09
And so features like that are always integrated into RAM's product to help businesses make, you know, those kinds of calls.
1:42:16
But what, you know, the logic of my role is that we can help a lot more businesses make decisions by making a lot more of that data public.
1:42:22
Data both about how businesses are spending money, but also where these economic trends are going and how your business can can operate uh within them.
1:42:30
And so our latest spending report, what we put out this month, gets right at that.
1:42:35
We're looking at trends in AI adoption.
1:42:37
Our main finding is that uh 35.
1:42:39
5% of American businesses have already adopted uh AI to produce goods and services.
1:42:47
That's four and a half times higher than the current US census estimate.
1:42:48
Uh and then we also posted a lot of results about general business spend trends, where businesses are spending more money, where they're pulling back.
1:42:55
But the idea here is really to be able to say something really compelling and new about what's going on in the economy. Yeah.
1:43:03
and trying to respond to the fact that there's not a lot of public data available about where businesses are spending right now.
1:43:08
spending right now. Can you uh just jumping right into the first point, can you talk about how you guys came to the 35 and a half% number because I imagine it's pretty hard to triangulate given that you know some you can get AI in a
1:43:22
non like AI you know product as an example right like you're using Google Workspace and it it sort of like you know pops up a little like you know magic wand icon and you click it and that's like technically using AI Clippy's coming back. We've seen
1:43:35
We've seen Clippy's coming back. We're bullish on Clippy.
1:43:38
We're making a PY market for No, but but but then you know different you know differently it's like a company directly spending money on OpenAI or Grock or Anthropic or any of these other things.
1:43:49
So I I'm curious how how you got there because we've been talking we were just talking with Tyler Cowen.
1:43:52
What is AI adoption right now?
1:43:55
It feels like in in our world it feels like it's 100%. Yep.
1:43:59
But, you know, it's also very different to use OpenAI as like a search engine versus using it to develop software. Yeah. Right. Totally. Yeah.
1:44:08
Well, you guys are getting at the key issue with a lot of these conversations about AI is that nobody's really sure where to draw the line. Yeah.
1:44:14
About what AI is, if it's going to be integrated into every single tool. Yeah.
1:44:17
And that's similarly, I think, what you get with uh the problem of a lot of AI adoption measurements.
1:44:24
The current US census survey, for example, is just a survey question and asking one person at the company, typically the person who answers the phone, uh whether or not they're they're uh using AI to produce goods and services.
1:44:37
And it's kind of a confusing question to answer because you know what does that mean?
1:44:41
Does it mean we're using AI for our manufacturing processes and robots or are we using it to make sure all of our customer service agents have this body of knowledge which was which to answer answer questions?
1:44:51
I mean, by the way, no shade to the Census Bureau.
1:44:55
They produce a lot of really great work.
1:44:57
Uh, and and shout out to them.
1:45:00
They have a lot of really great economists on staff.
1:45:01
But I do think we can do a lot better.
1:45:02
If we're trying to measure AI adoption, we should probably use data sets that measure actual transaction activity.
1:45:09
Yeah, we have access to the contracts that uh businesses are using to engage with the large model companies.
1:45:16
large model companies. we can actually see the size of those contracts, how that adoption is changing and particularly how that's changing in different sectors and that's really where you get a lot of the variability right uh I mean you see adoption rates in our measurement for technology are about 65% in the tech sector and that
1:45:33
even that sounds kind of low you'd think why is there a tech company that hasn't adopted some kind of AI tool but you know when you look at this actual spend data you also have to remind yourself that businesses are much more diverse than we realize there are large and small companies that are still evaluating whether or not AI makes sense for their business. There are companies
1:45:50
There are companies that are still using the free versions.
1:45:54
They're c they're employees at many companies that are using their own free that's not going to be captured in our data set either.
1:45:59
And there's other companies that are spending money with Accenture saying like we want to have an AI strategy, but we're going to give you we'll review the deck in Q4 and then decide if AI is right for us. $200 million.
1:46:09
Have you had uh like venture capitalists reach out to you like hey let me get an early read on the on the spend report. I want to know.
1:46:15
I want to frontr run it because I feel like every time I see the screenshot go out, I'm like, "Okay, there's the next series.
1:46:22
There's the next set of series B's that are going out."
1:46:23
Yeah, we get that question.
1:46:26
I get a message on LinkedIn or Twitter daily.
1:46:29
There are probably people listening who are going to message me now or or I haven't responded to.
1:46:31
The goal is to make this data public. Yeah, of course.
1:46:36
Goal is to make it as available to as many people as possible.
1:46:39
And look, there's the business side of it where we really do want to help businesses make better decisions. Yeah.
1:46:45
But there is also a public service aspect to this kind of work which is look if AI is going to be this transformative technology that's going to change our economy that's going to move over economic indicators that's going to increase labor productivity the
1:46:58
very first place we're going to see that is in AI adoption rates and so if you are a policy maker that is you know building policy that's going to try to move these metrics uh we should probably know what that metric is and I just I don't think 8% is the that's the current US census sentiment. I just don't think
1:47:14
I just don't think that's the right number.
1:47:16
Uh but even so, I think we can add something to the public discourse by showing people, well, there's still a lot of room to grow.
1:47:23
I mean, we have 15% of, no, 18% of restaurants on our platform are also using AI right now.
1:47:29
And that doesn't mean they're using it to serve people, but they're, you know, when we talk to them, they're using it for a lot of back office tasks, which means 82% of restaurants haven't done that yet. Yeah.
1:47:39
Can you re can you restate those high level numbers?
1:47:41
census at 8% and then your estimate was what? 30 uh 35.
1:47:47
5% is our estimate across US businesses.
1:47:49
That's like significantly higher not growth was higher than previous months. Wow.
1:47:54
Saying that we're not at this point yet where AI adoption has plateaued where you know companies have figured out how to implement it yet. Yeah. Yeah.
1:48:03
The other thing I would say is that there what we have observed is there's this sort of learning curve in AI adoption where your first month on an AI platform does not mean that's how you're going to stick to implementing into your operations.
1:48:14
You might be evaluating multiple vendors.
1:48:15
We often see in ramp data that businesses are multihoming AI vendors and using open AI but they're also using anthropic and they're using the more verticalized uh services available to them.
1:48:26
see a lot of experimentalism where they use one model for one month and they switch to a different vendor for another month.
1:48:32
Uh so all of this stuff is still very early. It's still developing. Yeah.
1:48:36
What what is the ramp data showing about the current uh market chaos and tumult around tariffs? Yeah.
1:48:46
I mean we it's a really common question that we've gotten.
1:48:50
Uh look, we haven't seen a significant slowdown in if that was the concern, we haven't seen a sort of slowdown in business spend on ramp data yet.
1:48:57
That's typically what you'll find in both ramp data, but you'll find that in a lot of public and private data sets as well.
1:49:02
Uh I mean last week we did go out and actually talk to a bunch of businesses.
1:49:09
We interviewed 30 businesses in retail and construction and manufacturing to try to figure out how they did feel about tariffs.
1:49:14
Uh, and we found a few main points in our findings.
1:49:17
I think we found first of all, there's a lot of policy uncertainty that businesses are concerned about.
1:49:24
They're not sure how to respond to the tariffs, how to adjust their operations quite yet.
1:49:28
A lot of them are in this sort of wait andsee mode where they're trying to wait for tariff policy to settle before they make significant changes in their spending decisions.
1:49:37
So, that's part of why I think we haven't seen that in our data yet.
1:49:41
though we did talk to several businesses who told us that they were pausing all capital expenditures until they see uh the tariff policies clearly settled.
1:49:48
How that's going to affect our data, I do think we're going to need a couple more months to really find it.
1:49:53
But so far, we haven't seen aggregate changes in business spend in both ramp data and in private data sets, public data sets.
1:50:00
Is there another leading indicator?
1:50:02
I mean AI might be something I know it's like the most important segment to follow in the spending report but at the same time I imagine that a company that's going into a tumultuous financial market that might not be the first place that they cut.
1:50:16
They might actually double down on AI uh and cut back.
1:50:20
But in terms of the type of expenditures that go through uh corporate cards, what's kind of the canary in the coal mine for a recession?
1:50:29
you know, in the in in like the Fed data, we usually look at like credit card delinquencies or uh car loan repayments or something like that.
1:50:37
But are there are there specific categories within corporate spend at American companies that you would expect to track more closely as a leading indicator of recession? Yeah.
1:50:49
And it's definitely going to depend on the sector. Sure.
1:50:51
So, we're going to have some sectors that are a little bit more exposed to tariffs.
1:50:55
They're going to be making those changes a little bit sooner than others. Sure.
1:50:57
Uh I mean I generally start by looking at the largest categories of spend by business and thinking about where you're going to see budgeting or movement there. So advertising is one.
1:51:07
Digital advertising for I think is a really great way of measuring how businesses feel about the economy. Yeah.
1:51:14
And you know we we rely a lot in the public sphere on these CFO surveys or CEO surveys about business expectations.
1:51:20
Uh but if you really want to know how a business feels about their prospects, you should look at their digital ad spend. Yeah, that makes sense.
1:51:28
That is what's going to capture whether or not they see the value in putting ad dollars toward trying to get new customers or increase their revenues.
1:51:38
Uh I mean, we're seeing some changes there.
1:51:41
So, we're seeing as last month, year-over-year, 55% of large businesses uh reduced their ad spending or kept it the same.
1:51:49
Small businesses, however, but that's going to include startups are increasing their ad spend year-over-year.
1:51:54
That's going to be a harder sector to track.
1:51:55
Startups don't always track the overall economy.
1:51:58
They can be a little uh a little skewed in that way.
1:52:02
But it is worth noting that we are seeing some declines in advertising spend which could suggest some some kind of lack.
1:52:09
Yeah, it's just an easy thing to react.
1:52:12
You can go into Facebook for Google and just immediately reduce your budgets and and it's a way to just be a bit more, you know, pragmatic.
1:52:19
I think secretly every entrepreneur thinks, am I really getting my money's worth on those Google brand keyword ads?
1:52:26
Like maybe we should do that hold back test and cut those back this month and then uh see what happens to revenue and then eventually they sneak back in and you're like I want to own my keyword.
1:52:35
Can you can you talk about spend across the different model providers even at a high level?
1:52:41
I know there had been some interesting data on on deepseek specifically um you know earlier this year but can can you dig in there? Yeah.
1:52:51
So open eye is the clear leader in the model companies across business adoption.
1:52:54
More than a quarter of businesses on our platform have an active contract with open AI. That's crazy. Yeah. No.
1:53:01
And they were the first mover and it just shows you sort of if they're sort of become synonymous with AI products and companies. Totally.
1:53:08
And that's not just coming from the chat chat subscriptions.
1:53:11
it's coming from their sort of a API integrations uh down the line too.
1:53:15
Enthropic is a is a is second uh and they are still growing very quickly.
1:53:20
Uh but open is a clear leader in all of the markets that we're tracking.
1:53:24
Uh though we are still seeing a lot of growth in some of the newcomers to the markets too.
1:53:28
XAI has grown very quickly despite only being a couple months old really you know operating.
1:53:32
Uh Gro 3 pushed a lot of their adoption up.
1:53:37
uh you're still seeing some amount of experimentalism, some amount of that learning curve from businesses.
1:53:41
Deepseek had a really big spike in January when it really came to fruition that slowed down a lot the following month.
1:53:47
Uh and uh and XAI has now sort of leaprogged it, but they're still relatively small players. Yeah.
1:53:54
Is it hard to uh understand AI spend with the hyperscalers because you can go to Microsoft and vend you know GPT4 API into your organization but that's probably just going to show up as Azure on your on your ramp bill if you're even billing it to your corporate card.
1:54:10
You might have you'd be surprised I I really have such a lucky job.
1:54:15
I s as for sort of a private sector economist I sit on such a good data set because a lot of those bills they do actually they they produce the line items for API credits and Oh yeah because you get the receipts too it's not just the charge.
1:54:26
too it's not just the charge. Yeah, for deepseek that was originally a challenge because how do you pay deepseek particularly when a lot of the business implementation of deepseek was not necessarily going to go through deepseek
1:54:38
the company totally because of the security concerns with using deepseek and a lot of it was going through sort of these hyperscalers or a lot of the other sort of companies that allow you to integrate an AI model that's that's working on their own local servers. Yeah. But even then we'll see deepseek Yeah.
1:54:49
But even then we'll see deepseek as the line item.
1:54:51
And so we started putting that data out try to get at you know we put an article out last month about whether or not businesses are actually adopting deepseek and high high rates uh so that business can really figure out you know where is this market trending.
1:55:05
I think it's extremely hard to figure out without some data given how quickly uh everything's moving in this industry.
1:55:12
What is your tech stack look like for some of these analysis?
1:55:15
Are you IPython notebooks?
1:55:17
Are you using Julia or Julius?
1:55:20
two different people people can make fun of me, but I do a lot of work in a notebook. Yeah. Uh it's great.
1:55:28
I mean, it's it's it's uh skilled skilled very effectively.
1:55:30
But the real goal is to put things out quickly. Yeah.
1:55:34
And so, you know, we have a lot of notebooks that are just outputting directly to our website. Oh, very.
1:55:39
And uh and similarly with the benchmark report that we just released. Yeah.
1:55:44
Uh the goal, I mean, you'll note that it goes all the way through March data.
1:55:47
And so the goal is to really provide people with the earliest available data as soon as possible because particularly in this news environment right now, yeah, things can just become immediately outdated.
1:55:57
Yeah, Jordy, um, how what what is act what is AI adoption look like across different teams?
1:56:07
teams? because I can imagine at some of these larger companies you have an engineering team that's using you know uh Devon or Anthropic or Cursor and then you have you know the marketing team which is using some like app layer company or they're just using open AI to
1:56:25
generate images um how how are you seeing it kind of roll out well AI adoption is generally going to be higher at the large companies than the small companies and we think it's for that specific reason large companies have many more teams many of them using AI products and services, many of them aren't. And then
1:56:39
And then those large teams, those teams at those large companies will then evangelize the products they're using throughout the company and increase the adoption rate that way.
1:56:48
Um, I mean, the model companies are still growing at a very fast rate, but one thing we saw this past month was that the sort of coding platforms, the quote unquote vibe coding platforms, the cursors of the world, the lovable, uh, those are currently growing faster than the model companies themselves.
1:57:04
um seeing growth rates in the 40s right now.
1:57:07
And so uh you know people talk about you know whether or not you know any of this growth is sustainable.
1:57:14
For what it's worth businesses are clearly acquiring value from them. Yeah.
1:57:18
And uh and and the the way these products are developed I think is it's going to be really interesting to see how they get integrated.
1:57:25
I mean canvas also Canva just announced its version of it too. Yeah.
1:57:29
Uh that was also one of our fastest growing vendors last month, but it wasn't because of an AI coding thing.
1:57:34
It was just because it's a really fast growing vendor that's implementing AI across all of its features. Yeah.
1:57:36
Have you gotten push back from any of these companies saying like, "Hey, maybe don't leak our financials or like uh you know, it's like you're sharing too much insight."
1:57:46
Actually, completely anonymous.
1:57:48
So, I don't think it's Yeah, it's anonymous, but again, you're naming like a specific company.
1:57:52
And for most of the companies, it looks amazing and it's like, "Wow, they're growing so fast."
1:57:56
But uh you mean on the you mean on the customer side? Yeah. Yeah. Yeah. Yeah.
1:58:01
Like like you get a you get an email from OpenAI saying like hey like because of secondary is being repric know that we're growing at 30% instead of 40%.
1:58:08
Or this is off and we're actually growing bigger and non-ramp customers and so your data is low. Yeah.
1:58:14
But what's interesting about it is that we've had customers that we reported on reach out to us. Yeah.
1:58:19
For more data on what we're reporting on. You can imagine that.
1:58:25
What's really great about having this data set at RAMP is that in in some ways is you know the most comprehensive data set you can find about overall spending by businesses and so you can say large AI company for example knows how much spending is happening on its platform but they don't necessarily know how much spending is happening with the other AI model companies. Yep.
1:58:46
Desire is really to have some kind of data that estimates that sort of total market view. Yeah.
1:58:51
And the the logic of this role again is that businesses, people, but everyone businesses really make better decisions when they have access to better information.
1:59:02
And and I see my role as trying to put that kind of information out so that companies can make decisions that are right for them and it's available to everybody for that reason.
1:59:14
Are there are there CFOs on RAMP who come to you uh in a less positive light?
1:59:20
Instead of saying, "Oh, what AI model should I be adopting or paying up for?
1:59:25
Instead, they're like, give me the what should I be cutting?
1:59:28
Like, where are the biggest places to save money instead?"
1:59:32
Or, yeah, they're like they're looking at like declines and then they're saying, "Oh, I'm going to target that."
1:59:36
If everyone's if everyone's unsubscribing from, I don't know, Netflix in their organization or something, uh, they're going to try and do that internally to save money. They do.
1:59:44
And that's the fundamental goal of this kind of work is not just to show you what to buy, but it's to show you first of all what to cut, what other businesses are cutting, how can you benchmark your business relative to how others are performing. Yeah.
1:59:55
The goal is that if you have access to this kind of data through RAMP's product, but also through the kind of research that we put out, you might get a better picture about, you know, what it really means to be a high performing business, how to run most efficiently, uh, which vendors to use and select, and which vendors other people in your industry are using, and then which ones they're not using. Yeah.
2:00:17
One thing you pulled out was that Tik Tok's ad platform leads in year-over-year spend growth, signaling advertisers have not been deferred by the prospect of a ban.
2:00:24
My question when I saw this was, is it possible that people are like, "Hey, we think this platform could get banned.
2:00:31
Let's basically try to acquire every poss." Yeah.
2:00:40
And I think what's showing you is why there's going to be such a big bidding war for this kind of platform. Sure. Right.
2:00:46
The ad spend just continues to grow.
2:00:48
Their user base, I imagine, still continues to grow. Yeah.
2:00:50
uh it is really one of those unique platforms that is able to both attract a lot of visitors but also keep them on the platform for a long time.
2:00:59
It's made ads on short form video kind of work well and it's still growing a lot.
2:01:04
I mean I I I'm I'm really interested in seeing how different how how this sort of Tik Tok Tik Tok fight plays out in the business side.
2:01:14
Yeah, makes a lot of sense.
2:01:14
Poly market has the recession at 51%.
2:01:18
What is uh what does your gut tell you as an economist? How we looking?
2:01:23
My real goal here is just to put out data to help make their appropriate guesses.
2:01:29
I mean, I do think there are a lot of headwinds what we're hearing from businesses.
2:01:34
So, I hope those get resolved. Yeah.
2:01:35
But, um hopefully I I I hope people are able to make the decisions that make sense for their businesses based on what we're putting out. Yeah. Makes sense.
2:01:47
Do you have any do you have any uh thoughts on AI can has the potential to be deflationary in some ways?
2:01:54
Let's take like an e-commerce business who, you know, might spend $50,000 a month producing content to make ads.
2:02:02
And then if if suddenly they only need to spend like $5,000 a month because they're able to do one shoot and then just like generate iterations of it or or maybe they're eventually able to, you know, just generate all the advertising content that they need.
2:02:18
in theory they would just take that budget and spend it to acquire more customers or spend it to launch new markets or things like that.
2:02:28
How do you think about um how do you think like long term about you know as AI drives efficiency where those dollars flow right because budget if if budget is being you know sort of reallocated because if AI can do something a lot more you know inexpensively the budget will naturally flow to where it can sort
2:02:47
of generate the highest possible return and that could be as simple as like oh you know we we spend $20,000 a month for this CPA firm with AI we now only need to spend $5,000 a month because they don't need as many people, you know, working on on it or something like that. But then again, you're going to want to
2:03:03
But then again, you're going to want to sort of reallocate that spend to continue to grow the business.
2:03:07
Do you have any do you have any sort of highlevel thoughts on if it's again if it's going to okay, let's just run more ads or or or things like that?
2:03:15
Well, I think that re real reallocation will happen and I think that's the reason why we probably won't see deflationary pressure.
2:03:25
Uh I look I'm of the school of thought that AI will be a very transformative technology.
2:03:30
I think it's going to change a lot of knowledge work.
2:03:33
I think it's going to reduce costs for a lot of businesses.
2:03:34
But at the same time I am also fairly realistic about the fact that many parts of our economy just will never be touched by something like AI.
2:03:42
I mean it will be touched in some ways right like me going to a restaurant I imagine that restaurant will probably have much easier back office automation because of something like AI.
2:03:49
But, you know, me sitting down across from someone at a restaurant is is not a which is a lot of most people's day-to-day spending, right?
2:03:57
It's just going to businesses on your small business street.
2:04:00
You know, most of that is not going to be touched or moved.
2:04:02
And uh so I think we'll see a lot of parts of a lot of parts of the economy continue to grow.
2:04:08
I think knowledge work is going to change a lot.
2:04:09
Uh and I'm bullish about the impact of AI.
2:04:12
Uh but uh you know I I do think much of our day-to-day spending is going to stay fairly similar as consumers at least. Yeah. Yeah.
2:04:24
Uh have you thought about uh any like more niche industry benchmarking?
2:04:32
And I remember uh it was always useful to know how other companies in the same sector, how much are they spending on their legal bills or how much are they spending on e-commerce development and kind of have a rules of the road and when you I I I did some back of the envelope with some rival companies at one point and found that some of the companies were way way overspending.
2:04:50
Um so we should be clearly under that.
2:04:53
I could imagine that type of uh benchmarking being useful just to kind of allocate budgets to say, hey, realistically, you know, the IT budget at a company of this size in this industry really shouldn't be more than like 5% of our costs or operating costs, anything like that.
2:05:10
Have you been able to produce anything like that or are you thinking about that?
2:05:14
We're working on that right now.
2:05:16
I mean, the goal is to be able to see whether or not you're a small construction firm in can Kansas City. Yeah.
2:05:24
And your current cost structure can compare that to other construction firms in Kansas. Yeah.
2:05:28
And and see how you're sort of tracking relative them.
2:05:32
Uh I mean I think that's going to be the real frontier that helps businesses make those kinds of decisions for them. Totally.
2:05:37
Find out where they're overindexed and then when they're under indexed and then to try to track their performance following decisions and just make like a choice.
2:05:45
Like there are times when you want to invest more than your competitors in a certain area, but there's other times when you want to be below them and maybe that's your competitive edge.
2:05:51
Uh well, thanks so much for joining.
2:05:53
This was a fantastic conversation.
2:05:54
Let's make it a quarterly thing. Yeah.
2:05:56
I can't wait for the next one.
2:05:58
And thank you for coming uh coming prepared.
2:06:00
Yeah, you look fantastic.
2:06:02
I know people people always think it's weird to everyone at work is commenting like, "Oh, I can't believe you wore a suit today."
2:06:08
It's like this has been the normal component of men's wear for centuries. It's just only weird.
2:06:13
You work in you work in finance finance. Finance tech. So, dress the part. Great to see you. We'll talk soon. Bye.
2:06:24
Next up, we have And I'm still I'm still thinking about how um Tyler Cowan just came in.
2:06:30
He's like, "AGI is here in two days."
2:06:32
And uh not super bullish on robots, but uh yeah, AGI is here.
2:06:36
AGI is here, but it's not necessarily going to grow the economy as fast as we want, but still here.
2:06:43
It's I mean, it's a good take because it's it's the it's the same as the touring test.
2:06:46
Like, we passed the touring test and it was kind of a nothing burger.
2:06:49
It was like, "Okay, yeah, you can chat now, but you probably still want to watch a live stream, especially when you have the founder of California Forever in the building. Welcome to the stream." Boom. What's going on? Good to be here. Hi guys. Hi. Uh, how you doing today? I'm pretty good. How are you? We're good.
2:07:05
Uh, could you start just by giving us the the high level pitch?
2:07:09
Uh, introduce yourself and the company, the project. How do you refer to it? Sure. Um, Yan Shame.
2:07:13
I founded California Forever almost 10 years ago at this point.
2:07:18
Uh and we are building the next great American city.
2:07:23
Uh and so we own about a 100 square miles of land, grazing land basically just outside of San Francisco, about half an hour east of Napa, halfway between San Francisco and Sacramento.
2:07:32
Uh and what we doing here would have been the least controversial project in California in 1960 when we uh when we still used to build stuff.
2:07:42
uh but somehow today it it's become controversial.
2:07:46
Um but uh now it's really kind of going full steam in the last few months.
2:07:52
So now we have a couple of local cities moving to approve the new city.
2:07:56
And then last week we introduced a proposal to build the Solano shipyard which would be the biggest ship building complex in America to help with uh the ship building crisis that the whole country is trying to solve right now.
2:08:08
I mean that sounds like pretty industrial.
2:08:13
Is is that important to have like an industrial plan and really like jobs growth engine?
2:08:18
Because when I first heard about this, I was like, "Oh, it's like halfway to Napa.
2:08:22
This will be just luxury mansions for people who have a place in Tahoe and also have a place in uh in San Francisco and they'll go out there on the weekends.
2:08:33
Uh but it sounds like you're planning for something much more ambitious than just a retirement community for uh liquid uh liquid tech people." Oh yeah, 100%.
2:08:41
Um, I mean, I really started the company eight years ago when it became clear that we were going to need basically what Silicon Valley used to be.
2:08:50
I mean, you look at you look at what the value used to be all the way through the 80s.
2:08:53
It was primarily hardware, right?
2:08:55
Until 1985, the biggest employer in the valley was Loheed Martin. It wasn't Microsoft. It wasn't Oracle.
2:09:02
Um, and so the focus from the beginning was, yeah, bunch of really high quality housing, great walkable neighborhoods, but also how do you how do you go back to what the valley used to do, which was make planes and microchips and uh, and radios all the way back at the day.
2:09:19
Um, and um, I mean that was 8 years ago, but I think if you look at what's happened in the country and in the world over the last eight years, that's kind of just supercharged that whole effort.
2:09:29
And so when we came out here um and introduced the project about a year and a half ago, we said that we would want to bring particularly advanced manufacturing and aerospace and defense to Solano County.
2:09:38
And um it kind of got lost in a lot of the media coverage, but that's been the that's been the focus since the beginning.
2:09:45
Has the controversy, which is a seemingly silly controversy especially for our audience because the idea that we should just build more housing and advanced manufacturing just seems like should be agreeable with every American.
2:09:57
But uh do you feel like the the controversy has actually maybe been you know beneficial at all and the ability to sort of like attract you know you know independent thinkers people that otherwise you know if it was still the 1960s and everybody was just pro building and new cities maybe it would have been harder to recruit you know just like truly exceptional talent to join the team and the sort of movement.
2:10:20
maybe it wouldn't have been in the 60s.
2:10:22
Maybe it wouldn't have I think about California Forever as somebody who, you know, grew up in the Bay Area and in Sonoma County and, you know, I think about it as like very exciting, very ambitious and like, you know, something like very worthy of of a ton of investment.
2:10:36
But, um, but back in the 60s, it would have been, you know, okay, a lot of people maybe thought that they should create another city or something like that. Oh, 100%.
2:10:43
Um, I mean, it's it's it's a great question.
2:10:46
mean, it's it's it's a great question. I think you're the first person who asked it but uh we've definitely seen it uh which is similar thing that I think you've seen with early Andural and early SpaceX where if the whole world is saying hey this is a dumb idea you can't build a new defense company in 2016 and
2:11:03
you can't build a rocket company in I don't know 2004 2005 we've definitely seen that the people who want to come and work on it are people who really believe um and it shows right it shows in the in in the quality of the talent that you can get and it it is ironic in that if you if you propose this in 1960, there were a ton of these happening all over the country. I mean, Irvine is a
2:11:22
I mean, Irvine is a great example in Southern California, right?
2:11:25
Irvine is a city of 300,000 people.
2:11:28
There's 250,000 jobs on Irvine.
2:11:31
They have more jobs than they have working age residents.
2:11:33
Uh it's one of the safest places in America, some of the best schools.
2:11:37
Um it is different kind of a place.
2:11:39
It's the best-in-class suburban community if you want, but uh not what we're trying to build, but huge success.
2:11:46
that was started in I think 1962 and there was zero controversy about it in the beginning and same thing happened in other parts of the country but it's kind of an old idea that we used to have and then we forgot it as a country and then everyone is shocked that people can't afford to live anywhere because we stop building stuff.
2:12:04
What is the roadmap for actually building a new city?
2:12:05
I mean it sounds like there's a corporation here, you've raised money, there's there's investors and at some point they might want a return on their investment.
2:12:13
Uh like What steps do you have to what steps have you done?
2:12:19
What steps do you still have to realize?
2:12:21
And then it sounds simple to just go and build a city in some ways because it's you know there are companies that their whole job is building houses or building buildings.
2:12:31
There are companies that need buildings to have to live in or people to live in and like all of that makes sense but then there's something that's still really hard. What is that thing? Yeah.
2:12:40
Yeah, I mean it's it's I I describe it as I think someone coined the term complex coordination startup.
2:12:44
There's no breakthrough here, right?
2:12:47
There's no we're not trying to make a rocket fly.
2:12:50
We're not trying to cure cancer.
2:12:50
We know all of the steps.
2:12:52
You just have to put them together really really well and finance it correctly and execute on it.
2:12:57
Um and we do build new cities in America, not in California largely, but we build them in Texas and Arizona.
2:13:02
We just don't call them new cities.
2:13:04
We call them master plant communities. Yeah.
2:13:06
Now the difference is they are largely um they are largely residential and they don't have manufacturing or jobs and so on but we do build them.
2:13:15
Um I kind of compare the company to a biotech company. Mhm.
2:13:20
Which basically has three distinct stages.
2:13:23
The first one is you kind of invent the drug.
2:13:25
The second one is you go through the clinical trials and then you get it approved and then you commercialize it. Right. You sell it.
2:13:31
And for us the three distinct stages was um the first one was to buy the land.
2:13:36
And so I spent seven years very quietly raising money and buying the land.
2:13:40
And in the end we bought about Sorry, one question.
2:13:44
Maybe you're about to say this, but were you piecing together like tons of different properties?
2:13:49
Like imagine there's not a 100 square miles just sitting there like, "Hey, you want to buy this for one price?" Yeah. Yeah.
2:13:55
I wish I wish that would have been easier.
2:13:57
No, we uh it took seven years, 200 individual transactions, 700 individual sellers.
2:14:02
Um and so it was probably it was probably the most successful I think uh land assembly in the history of the country.
2:14:13
Um but yeah it took seven years to put it together. U very long process.
2:14:19
Um and then so that's kind of phase one.
2:14:22
Phase two is what we going through right now which is the planning and the permitting. Yeah.
2:14:26
Uh, and so we're doing both the actual planning of how do you how do you design an incredible new city and and how do you combine the old and the new in the best possible way to create a great quality of life.
2:14:38
Um, and that's going to take us about another two two and a half years and then we are hoping to break ground in 2028.
2:14:45
Um, and from there on it's kind of the third pace in a biotech context if you want which is basically build and and sell.
2:14:53
Uh, and you start out slow and the first year will probably build 500 homes and then the second year you build more.
2:14:59
Um, and eventually you're building thousands of homes every um every year.
2:15:04
Uh, and all of the accompanying uh industrial space and retail and commercial space and so on.
2:15:09
And and really the vision is to build um a city that actually looks pretty old school at least in terms of on the surface.
2:15:15
I mean a place that looks very much like some of the most beloved neighborhoods in America like at a smaller scale.
2:15:24
Charleston, South Carolina or Savannah, Georgia.
2:15:26
And then as the city grows and becomes bigger, Chicago, Brooklyn, Philadelphia, Georgetown.
2:15:31
Yeah, I'm excited to hear that because in in many ways like the the classic thing in in tech is, you know, you know, it's not like you've maybe built like 10 cities before.
2:15:42
And so to come in and say like, oh, we're going to reinvent the city and just completely redesign everything.
2:15:46
And I I I've had this theory for a while that like suburbs are like nice in a lot of ways.
2:15:52
I live in a I live in a small like gated community.
2:15:55
There's like hundred something homes.
2:15:57
It's like generally well-run. I like my neighbors.
2:16:02
I I have friends that don't live in suburbs yet and they like tell me like I just want to live somewhere that's like safe and community oriented and why doesn't this exist? Yeah. Why doesn't this exist?
2:16:11
And I'm like, you know, there's the we we were sort of like, you know, I feel like our, you know, as a sub 30-year-old, my generation was like just against this idea of of suburban living.
2:16:24
Yet, the idea to live like just outside of a major industrial area with like-minded people that has like family values and things like that is actually fantastic.
2:16:35
fantastic. So I guess like how long like did you did you know from the beginning that the sort of like historical concept of a city was like pretty pretty good right like you're talking about like Charleston right like you can it's not like did did Charleston like have it
2:16:52
figured out you know whenever they like created the city or did it sort of naturally evolve into that state and how did your thinking shift at all from the beginning of saying oh we need to completely reinvent this or or the right model already exists and we need to sort of emulate that in some way. Yeah, I was
2:17:06
Yeah, I was pretty much in the camp of we know how to do this, we just need to do it again.
2:17:13
Um so my take is that um there's a tremendous amount of wisdom in how we design cities and I mean we've been building cities for 10,000 years, right? It's not like iPhones.
2:17:24
And so to come in and be like, I'm going to design a better phone.
2:17:27
That's pretty reasonable, right?
2:17:29
We've been building phones for 20 years.
2:17:30
So you can kind of say I I'll I'll do it better.
2:17:31
say I I'll I'll do it better. Also the technology of what you can do has changed and so it opens up new possibilities right same with a car but with a city like you can do some smart things in it but um at the end of the day it's a bunch of buildings and parks and schools and shops and and businesses
2:17:49
and we've been doing it for 10,000 years not in this country but elsewhere um and so I think it's pretty arrogant to come in and say we're going to redo all of this and do it from scratch and I think a lot of the backlash against tech coming in and saying we going to invent and how to do cities comes from that. People just saying what are you talking
2:18:06
People just saying what are you talking about?
2:18:08
And uh and then particularly you have these images of steel and and and uh glass and everything is a skyscraper.
2:18:16
It creates this very alineating human environment where people don't really like living there.
2:18:20
Um and so I was pretty and I also came into this after 10 years of living in the old York and the old Cambridge and London and Zurich and Manhattan and the old parts of San Francisco.
2:18:32
And so I was pretty charmed of those places.
2:18:33
Um and so from the beginning that was the idea and I think in particular we are pretty excited about this intermediate people call it now gentle density or missing density where right now what we have in America is you have mostly single family subdivisions and then you have sixtory buildings where you live in a small studio or a onebedroom apartment and if you have kids and you want some space for them to run around in the garden tough luck. Mhm.
2:19:00
And we don't really build anything in the middle.
2:19:03
And I kind of think that the magic happens in the middle.
2:19:07
And that's why those neighborhoods are so charming, right?
2:19:10
Because you can have a rowhouse and you can have a backyard so your toddlers can run around in the backyard, but then the plot sizes are small enough that if you want to walk to a restaurant or your kids to school or to a coffee shop or you just want to go out at 6 p. m.
2:19:23
and walk over five blocks and see your friend and have dinner with them, you can do it.
2:19:28
And that's the sweet spot that we are really excited about.
2:19:29
And and so for us, most of the magic is two to five stories, row houses, small apartment buildings, what's called small parcel fabric.
2:19:39
So every house is a little bit different.
2:19:41
It has that old charm that you see in the marina or in Noi Valley locally in San Francisco.
2:19:46
And we've basically stopped building those neighborhoods.
2:19:50
Um and um I think they are really magical and that's what we mostly going to be building.
2:19:54
mostly going to be building. Can you talk about the potential impact of a single new city with you know specific ideals right you talk about you know when I when I think about you have a 100 square miles you're going to have I don't know how many residents but if you have thousands of homes it's you know be tiny percentage of California's population but could theoretically you
2:20:17
know meaningfully you know impact like a bunch of different metrics can you talk about like what you think success is obvious obviously like a new city that's thriving, has a local economy, a bunch of happy residents, families, people that you know, generations that that grow um you know old there, but what does kind of success look like across you know whatever metrics you're you're sort of thinking about? Yeah, I mean at
2:20:40
Yeah, I mean at at a very micro scale, my personal goal, so we have uh we have a couple of young kids and another one on the way and my personal metric, so we'll we'll move in the first house in the in the in the city.
2:20:52
Um and my wife has given me the goal of the the first one has to go to school in the new city.
2:20:58
Uh she she said preschool.
2:21:00
I think that's going to be a push now, but we we'll we'll try for school.
2:21:03
Um I think success is if kids can walk to school alone.
2:21:07
Um that's a pretty big one.
2:21:10
And I kind of think of kids as they basically indicate the species, right?
2:21:15
Like if you have a city where your kids can walk to school alone, it says a lot about the city.
2:21:19
It says a lot about how close things are.
2:21:20
It says a lot about safety.
2:21:22
It says a lot about kind of neighborhood relations and you feel enough trust in the system that they're not going to get abducted and police works and all all kinds of stuff works basically.
2:21:33
So that's it at the very micro level.
2:21:34
very micro level. And then at the very macro level, um I think there's a cultural moment in California where the state is kind of waking up from a few decades of not building very much and um I think when the history of the state gets written in 40 years or 50 years and they talk about this kind of turning
2:21:59
point in cultural attitudes and and how the state kind of went back to what made it work for a century, I I would like California Forever to be a footnote in it and say, well, one of the things that happened in this moment was this project and it kind of galvanized uh and helped rethink the attitudes towards growth in in California. Um and um it very much
2:22:15
Um and um it very much feels that way.
2:22:19
It it feels like at least to me it feels like a bunch of people left during co and they went to other places and then um uh they kind of learned the shortcomings of other places. Let's just say that.
2:22:34
And they they they they realized that when uh uh when nature or the almighty or whatever was creating California, it kind of was creating the planet, it kind of got a uh unfair share of all of the advantages. Yeah. Can you prods?
2:22:48
Can you you know, so growing up in the Bay Area? Yeah.
2:22:52
I watched as San Francisco basically got worse every single year for like as I became an adult basically.
2:22:59
But I but and during COVID I was in Southern California and I had the same thoughts as everyone else you know sort of looking you know they said you can't go to the beach.
2:23:08
So I was like well if I can't you know even go to the beach why am I here and and everything's closed down.
2:23:13
I started like everyone else looking at Zillow and things like that and other states.
2:23:18
Decided to stay because I just spent my whole life here and I really believe in California and I want to make it better.
2:23:24
But can you talk about the sort of why California is so great?
2:23:27
Because obviously like I I can imagine if this if if this model city works then you could do other states but you name the company California Forever.
2:23:35
So I imagine you you you would maybe even uh you know try to pursue this model in other places in California even.
2:23:42
But um can you give like can you give the bull case for California at a sort of extremely sort of high level ignoring all the sort of you know last 20 years of politics and anti-growth and and all that. Yeah.
2:23:56
I mean I mean if you're trying to write history, right?
2:24:02
So you you write the history of the world and you write the history of America and then people cross the continent across all of these perilous deserts and most of them die and they get here and they kind of get to this place that just been blessed with geology and climate and all of the all of the stuff.
2:24:19
And um and then obviously the what is it the the the um the weak didn't make it and the the ill we left along the way or something.
2:24:32
So you you get this cer of people who come here who are just basically the the self- selected pioneers and they get to the ocean and then there's nowhere else to go and so they invent Hollywood and then they invent tech and we basically create the two industries that have
2:24:46
defined the 20th century and then unlike with Detroit those industries happen in a complete natural paradise where you can be skiing versus on the beach in 4 hours and then the California values and the California ethos defines the 20th century. And then we screw it up because we can't
2:25:04
And then we screw it up because we can't build stuff. It's ridiculous, right?
2:25:07
Like I grew up in posts Soviet Eastern Europe with this vision of California as this place of optimism and opportunity.
2:25:14
And then after 28 years of my life, I get here in 2013 and people are throwing rocks at Google buses because we can't build enough housing, which we've known how to do for 10,000 years.
2:25:25
And I'm sitting here like, what the [ __ ] is going on?
2:25:29
And then you look at how we designed the housing system.
2:25:31
And if you tried to break up a society and make everyone hate each other, you would design the California housing system.
2:25:39
You would have a fixed housing stock in one of the most desirable places to live in the world, which basically means that you make one person fight against another for housing.
2:25:47
And then you have the dumbest industrial policy in the history of America, which is we invent every company worth anything in the country.
2:25:54
And then we force them to leave the state. It's insane. It is crazy.
2:25:58
It's like we waking up from a bad dream. Yeah.
2:26:00
But I think what happened to your point about CO is people went to other states and then they realized all of the problems there and they came back.
2:26:08
But they came back with a different different attitude.
2:26:11
They came back and they said, "Hey, we've been living here, but we haven't really engaged in politics." Mhm.
2:26:17
But we're going to change that now because we looked at all of the other places in the in in in America and they are pretty nice, but they're not California.
2:26:23
And so we're going to stay, but we're not going to let these um radical ideas just destroy the state.
2:26:31
And I think that's what you've seen in the next couple of years.
2:26:32
And it feels like it's just accelerating.
2:26:33
And um we're pretty excited to kind of be part of finding the new new new middle path where you can show that you can build stuff, but you can also build it with California values, but you have to build it.
2:26:46
You're not that you you are not a progressive if there's no progress in your state and you're not for economic opportunity if the teachers who teach in your school have to work I have to live two hours away and commute four hours every day.
2:26:58
You're just not and we have to reckon with that. Yeah.
2:26:59
Uh how how do you think about fire wildfire prevention and protection?
2:27:06
I'm sure you guys have thought about it a lot.
2:27:08
I I live in Malibu, John lives in Pasadena, so we both went through this.
2:27:12
Um, and it felt like the Palisades should have been in many ways just it should have should have been more defensible than it was.
2:27:23
And there was a lot of reasons that that that happened.
2:27:24
And so I can imagine if you're building a new city from scratch in, you know, Northern California, which is fireprone and just the state has been fire has always been fireprone, right, if you look throughout history.
2:27:34
if you look throughout history. Um, and one thing that was interesting about the Palisades, I was talking with a a friend and he said that there was like a commonality between the homes that didn't burn down and it was like some way that the roof was attached to the
2:27:47
siding of the house and it was just like this one design decision that is like less uh less environmentally friendly like it it doesn't you know maybe hold in um cool air as efficiently or something like I I actually don't know specifics but that was like the common ground between all the homes that didn't burn. So when you get to design a city
2:28:06
So when you get to design a city from scratch, like the layout and everything and then design all the homes from scratch, how do you think about that?
2:28:13
Uh if if the ultimate goal is to prevent, you know, uh fire, you know, destruction from fires and then also make sure the cost of home insurance stays reasonable. Yeah.
2:28:25
So, here's a here's a here's a mind-boggling statistic.
2:28:27
There there isn't a single new neighborhood in California, not one that ever burned down ever.
2:28:37
No new neighborhood, sorry, in the last 20 years, no neighborhood that has been built after roughly 2000 has ever burned down.
2:28:44
When there was a big fire in Mission Vjo down in Southern California, when there was a big fire in Santa Rosa, the new master plant communities, the new neighborhoods have become places of refuge where the firefighters take breaks.
2:28:56
And that's because we've um we've tightened up the building code so much in the last 40 years that these new buildings are borderline impossible to burn down.
2:29:06
Um and so one of the one of the unfortunate consequences of the California building regulations is we've made it so expensive and so frustrating to build new buildings that we keep old buildings around for longer than we should and those buildings burn like nothing.
2:29:22
But um we will do more than that.
2:29:25
We will have the most modern water distribution systems and backups on backups and building materials.
2:29:31
But the reality is even if all we did, what everyone else is doing in new communities, none of them has ever burned down because they are they are so far resilient.
2:29:40
And the second component of it is one of the one of the reasons for why this site is by far the best place in Northern California to build is it has the lowest exposure to natural disasters of any site within 200 miles.
2:29:53
M so the entire we own 68,000 acres at this point is over 100 square miles.
2:29:59
There isn't a single earthquake fault line running through the whole site. It's unheard of.
2:30:06
Normally our engineers tell us you cannot find 3,000 acres in this studio down in LA like today. Yeah.
2:30:11
Our we're on the 10th we're on the 10th floor.
2:30:16
We're on the 10th floor of this building. It started shaking.
2:30:17
You could hear noises from Yeah.
2:30:18
Right before we went live. It was very funny. Uh so so that's one.
2:30:23
And then just on the other two, uh the the whole thing is um surrounded by water or grass, which means you don't have the fire risk the same way because it's the trees that normally have all of the combustible load. Yeah.
2:30:33
And then the whole thing is above um flat plane and sea level rise and so on.
2:30:38
So it's a pretty cool place to build. Yeah.
2:30:39
You're not at the wild the wilderness interface, as you say.
2:30:41
Um I have a question about uh Ezra Klein's abundance.
2:30:46
uh it seems like a dramatic shift in uh potentially like the Democratic platform if he really gets it to take hold. Uh very progrowth now.
2:30:53
He uses the analogy or the story of the California highspeed rail system is instructive for but his whole pitch is is not necessarily uh burn the government down.
2:31:06
We need to be ultra libertarian, let anyone build.
2:31:08
Uh it's much more make the government great again.
2:31:12
uh what has your read on the abundance agenda been?
2:31:15
Uh and just kind of give me your take as much as you've dug into it.
2:31:19
I've been a fan I mean he's been writing about it for a couple of years and uh I've I've discussed with discussed it with Derek Thompson quite a bit and uh I'm a huge fan.
2:31:27
I think that the the the devil is in the details but to me whenever people on both sides of the political spectrum are kind of saying the same thing there's a deep underlying truth at work. Totally.
2:31:37
And there's some differences between what Mark Andre is saying with it's time to build and what Tyler Cowan is saying with kind of state capacity and and with what Ezra is saying.
2:31:46
But they all there's an underlying truth at work that they are all kind of getting at.
2:31:50
And um I think the devil for um abundance is going to be in the details.
2:31:56
Can they actually simplify the regulations enough?
2:31:59
But I do think that California California desperately needs a big win in the built environment.
2:32:04
Everyone knows that we can build apps and phones and drones here, but people have given up on our ability to build something.
2:32:11
I we posted this thread on Twitter about the Solano shipyard that we proposed last week that went pretty viral.
2:32:18
If you look at the comments, it's fascinating.
2:32:22
99% of the comments that are negative are saying, "This is an amazing idea, but California will never let you build it."
2:32:32
that it's literally there's there's like 400 comments that are maybe 200 are negative.
2:32:37
195 of them are basically saying great idea, California will never let you build it.
2:32:41
And to your point, they quote highspeed rail.
2:32:42
And so I think California desperately needs to show that we can build again.
2:32:46
Um and have a have an example for the abundance movement like this is what it looks like.
2:32:52
And I can't think of something bigger and better that could do it than California forever.
2:32:56
Particularly because we put it in the name.
2:32:58
I mean, if California wants to stop being a joke to the rest of the country on our ability to build, we need something that's as big as highspeed rail to reset the conversation.
2:33:07
We're not going to reset the conversation by building a bunch of five-story apartment buildings in San Francisco.
2:33:12
Nobody cares across America.
2:33:14
We need a big um bold statement and I think this could be it.
2:33:18
If you had if you had the ability to step into a particular government role with essentially like complete control for a day or some hypothetical uh and your choice was uh a mayor, a mayor, a governor or the president, uh which one would you choose?
2:33:36
Like where where does the h what what position or what level of abstraction over our government has the highest ability to act as a lever on housing policy?
2:33:46
America tends to focus a lot on the presidency.
2:33:49
Uh but I've always wondered is there an executive order that can fix pol housing policy?
2:33:55
Is there a bill that we should be passing or is it more at the state level or even more at the local level?
2:33:58
So so that's that's part of the challenge.
2:34:01
And I mean called it vetocracy and I think Ezra gets into it in the book.
2:34:06
None of them alone can do it.
2:34:08
I mean if you look at what we need to build um we need local permits, we need state permits and we need federal permits.
2:34:14
Um, and you could get all the local permits you want, but unless you get the state permits, you can't build it.
2:34:20
And conversely, and so we've created this system where you need 25 people to say yes, and if one of them says no, you can't build.
2:34:31
And so I think the goal for people like Ezra and the abundance movement in some sense is going to be reducing the number of people who can say no.
2:34:37
I mean, imagine if you're running a company and to do anything you needed 25 people to say yes. Yeah.
2:34:42
you would never ship anything and none of them and in many cases and the CEO didn't have the power to override your head of sales or your head of product.
2:34:50
You would never ship anything. Yeah. Yeah. Yeah, it makes sense.
2:34:55
Um uh one last question for me.
2:34:57
Um you said that you're not building skyscrapers on day one, but as I think of how a city evolves as it gets bigger and more dense, I actually love skyscrapers.
2:35:09
And I and I and I love the idea of a city getting more and more vertical as it gets more dense, as it's more economically su uh uh successful.
2:35:19
Uh how do you think about setting up zoning or housing policy or even just expectations that you're moving into a quaint suburb or mixeduse environment on day one, but if this goes really well, yeah, we're putting up the 40s story or the 20 or even the 10story uh building.
2:35:37
Is is that just a cultural thing or are there regulations that you want to instill from day one to allow the city to scale or is it more of like a copype strategy and you think we just need 10 of the same uh communities all over the all over the state and that's how we win?
2:35:53
Yeah, I mean it's a great question.
2:35:56
Um I think for a long time we'll be able to replicate it by just growing.
2:35:59
I mean we have 100 square miles.
2:36:01
It's that's twice the size of San Francisco, five times the size of Manhattan.
2:36:06
It's bigger than the city of Seattle or about the size of the city of Atlanta.
2:36:11
And um if you look at um places like Barcelona or Paris or even Chicago, they get to really large populations um just with sixtory buildings.
2:36:21
And there's a lot to lot to say for that.
2:36:23
I think the other part of the question of how do you give people a voice in their neighborhood and what it looks like?
2:36:29
I actually like the the Texas model for this.
2:36:31
So, we try to do this with zoning in California, but that this it's very unclear who control I mean the city council controls the zoning, but like when should it be changed?
2:36:41
And that kind of creates all of these fights that we've been dealing with for the last 10 years of I moved into a single family neighborhood and I don't want any four-story buildings here. Mhm.
2:36:51
I think the way to do it is to have a really permissive zoning code that goes all the way up to five stories from the beginning at least.
2:36:57
And so, for example, in in in the city that we've proposed, um, every parcel can be built up to five stories from day one. Mhm.
2:37:06
Um, but then what you do is you allow home builders and residents to control kind of their block or their neighborhood through covenants. Mhm.
2:37:12
And so that's a private contract that can exist on a few blocks that says when this was built, this was meant to be a lower density neighborhood with buildings going up to three stories.
2:37:22
Um, but that also means that it's clear who has the power to change it, which means 50% of the people or 60% of the people living there can vote and they can lift it.
2:37:32
And that also means that when they do it, they might um they might kind of lose something and that maybe there's a taller building that looks into their backyard, but maybe that property became more valuable because now you can upgrade it and you can build a second another story or another two stories.
2:37:49
And so I think that's a really good way of dealing with it at a at a um neighborhood level that is just much more adaptable to change over time.
2:37:55
Well, when I get there, I'm building down. I'm building four subb.
2:37:57
I'm going to have a bat cave. I'm going down.
2:38:03
Everyone else is going to be sitting five stories up.
2:38:04
I'm going to be five stories down.
2:38:05
It's going to look like a tiny hut on the roof.
2:38:07
How uh are you I don't know.
2:38:11
I don't know if we have more time.
2:38:12
I know we're five minutes over already, but if we have time for one more question, I'm curious if how much you've studied uh HOAs and uh all the you know, my HOA like runs on paper.
2:38:22
So, if you want to pass anything, it's like you need they'll like send you something.
2:38:29
Everybody has to sign it.
2:38:29
Of course, nobody's like and then and then like apply your own postage and like get it back to them and it it's a bunch of silly rules.
2:38:37
So, like building an HOA from the ground up that just effectively, you know, is digital first, uses the internet, like seems pretty seems pretty powerful.
2:38:46
But I'm curious if you've you've spent uh so many I mean it's just like a meme at this point.
2:38:50
So many people like, you know, have a a I'd love to just hear best practices for HOA design.
2:38:58
Like that's an interesting question. Yeah.
2:39:00
And in the context of like an entire city. Yeah. Yeah.
2:39:01
What's the biggest mistake and what's important to get right?
2:39:06
So, it's it's it's an area that we've done some work on. Not a whole lot yet.
2:39:10
I mean, that's kind of a little bit downstream.
2:39:12
We have a couple of years to figure it out.
2:39:13
The question that I've been obsessed about the most is why does everyone hate their HOA? Mhm.
2:39:20
Just at a at a very human level, like it always seems like people hate it.
2:39:23
I Ours is actually fine, but a lot of people hate it.
2:39:26
I wonder whether there's something about the appointment of the HOA board that's part of the problem.
2:39:32
I'll tell you I'll tell you my reason.
2:39:34
Are you the president of the I'm not the president is a in the home building business of my HOA and so if you want to get your plans approved for some reason use him it goes super fast.
2:39:48
So it's it's basically like uh you know mafia but this is what we like.
2:39:51
It's one handwashing the other.
2:39:53
No we don't one hand washes the other. We don't like that.
2:39:57
So that's that's my personal, you know, uh, so my my take on I mean it's and it goes to to this.
2:40:04
I I think there's all kinds of issues with direct democracy that we've tried.
2:40:08
Uh, but I I do wonder whether it could work pretty well with tech at an HOA level, which is a relatively low stakes like vote fraud and whatnot.
2:40:18
like instead of having a three person board, if everyone just had an app and then you hire basically a HOA manager to kind of execute, but you didn't get into the politics of who's on the board and which neighbor they like and so on and it's like, hey, I want to rebuild my house. Here are the plans. Can you guys vote on it? You've got a month.
2:40:36
I wonder whether you could remove a lot of the really complicated social dynamics around it.
2:40:42
Uh, the other the other benefit that I think you're going to have is a lot of neighborhoods have like the challenge is if you're creating a new neighborhood in a new city from scratch, you can get a bunch of like-minded people that are there for similar reasons at the same
2:40:57
relative time, which is very different than somebody that moved into a neighborhood in the 60s, has been retired for 20 years, and their set of priorities is very different than the young family who's coming in today and, you know, maybe paid 10 times more for their house or something like that. And
2:41:11
And that those sort of like competing priorities of somebody who spends all day at home is very different than you know a young a young family who like you know prior is like super oriented around security or you know something else.
2:41:25
Yeah, I think this question. Oh, sorry. Oh, no.
2:41:28
I was going to say I think there's actually two really deep truths in what you said.
2:41:30
And the first one is I've heard from a lot of people that's actually what they missed the most about kind of moving into a new subdivision which is often it was a lot of young families and so you had everyone was kind of in the same stage of life and they had kids and it really created a sense of community and that's harder to find.
2:41:46
Then the other one is the other kind of exciting thing that came out of CO was people realizing just how much better your life is if you can live 5 minutes away from your friends or a minute away from your friends.
2:41:57
I mean we lived during CO we moved five doors down from my sister-in-law and we just had the best time.
2:42:02
It was it was incredible.
2:42:04
And um and people came back and they said hey I'm going to try to move in close with my friends.
2:42:08
But it's really hard to do it in practice, right?
2:42:10
You need to solve this issue of you all need to find a home in the same neighborhood and nobody wants to be the first one to jump and and you're driving up the prices.
2:42:21
Um, and then for a lot of the people who want to do it kind of in in in tech, you don't always necessarily want to move in like a new subdivision.
2:42:30
But I think that's going to be a huge part of who moves into the new city is going to be a bunch of people who live right now different parts of the Bay Area and they all kind of like the design aesthetic and will be trying to build and they can get houses on the same block.
2:42:42
I mean, you could you could connect my my my wife and her sisters have the plan of connecting the backyards. Um, that's amazing.
2:42:47
So, uh, I think there's going to be a lot of innovation in this kind of not communal living, but kind of co-l livingiving or living nearby with your friends and family.
2:42:56
That's going to be pretty cool. I love it. Uh, my last question.
2:42:57
Have you played City Skylines? No.
2:43:00
You got to It's a city builder.
2:43:04
It's what you're doing in real life.
2:43:06
He's playing He's doing the real playing the game.
2:43:07
Uh, but it's like the most popular modern version of Sim City.
2:43:12
Uh, I'm sure I'm sure a lot of fans will enjoy it.
2:43:14
They can play along at home.
2:43:16
Uh anyway, thank you so much for coming on the show. Yeah, this was great. I'm so excited.
2:43:22
Thank you for uh I can't wait for the, you know, for you to move into your place.
2:43:27
It's going to be a 15-year overnight success. Exactly. Oh, 100%.
2:43:32
Next time, next time you guys should come up and uh we'll we'll site once. Fantastic. All right. Good to see you. Cheers.
2:43:38
Have a great rest of your day.
2:43:41
Let's move on to the timeline. You threw this in.
2:43:43
We got to talk about this.
2:43:44
China is currently exposing all the European luxury brands with Tik Tok videos confirming that over 80% of the luxury items being bought at ridiculous prices are made in China and only packaged in Europe. Interesting. Uh this Yeah.
2:43:58
I got to basically put this in the truth zone. Okay.
2:44:00
There are a lot of luxury goods brands that make products in China. Sure.
2:44:05
But they were that some of these videos coming out were were basically like Birkin bags or like knockoffs, which is like Yeah.
2:44:13
And and and and I I do believe that this was like basically in a large part fake news.
2:44:21
Going on going on and saying your Hermes bag is made in China is offensive to the generation of artisans that have been handstitching these bags uh in in Europe for a long time.
2:44:35
The goal here is is to get American consumers of luxury goods to falsely believe that their goods are made in China and therefore be anti-tariff or anti- trade war. Is that correct?
2:44:46
Yeah, I think that's the strategy.
2:44:47
I think that's generally the strategy.
2:44:49
What's funny is they could just be like your iPhone is made in China like and that's true and also the whole I think I think the whole idea of I don't think brands should optimize for transparency.
2:44:59
Like nobody wants to find out they paid 20 times more for a product than what it costs to produce.
2:45:06
But at the same time, I think people like when they're making a p purchasing decision, like it's it's they're making it based on the fixed final cost of the item, right?
2:45:17
It's that's that's how they're an analyzing like the sort of value exchange. Um it is interesting.
2:45:22
I um the one thing that China did recently is they basically made knockoffs and dupes legal in the country.
2:45:31
They used to like crack down on it more.
2:45:33
Um, but you can actually go in China and go to entire malls where it looks like a Prada store or it looks like a Northface store except every single product in it is fake.
2:45:44
Um, and like very good quality. That's the thing.
2:45:48
Like they can nail the quality.
2:45:49
It's not going to be the same quality as some you know uh like a you know a dupe Birkin bag won't be the same as as you know an authentic one, but from 20 feet away it'll look like it.
2:45:59
So I don't know if that's true.
2:46:02
I don't know that China can always uh copy things with enough quality.
2:46:05
I was thinking about the disaster that could occur if you tried to buy a fake EightLe and then it ruptured and you drowned to death because you bought a cheap eightle instead of just going toleep.
2:46:17
com/tbpn getting a real eight.
2:46:20
They have a 5-year warranty.
2:46:20
30 night 30 night risk-free trial, free returns, free shipping.
2:46:24
Uh how' you do last night, John?
2:46:26
Go uh off on the I I already checked.
2:46:29
I'm off on the schedule again. I figured it out though.
2:46:31
I have cracked the code and I'm gonna be upping it.
2:46:35
I was at a 90 last night, although it's dropping now. It's a nine. Now it's an 89.
2:46:39
I don't know what happened.
2:46:39
It It does after you wake up. Okay.
2:46:41
Well, I slept pretty well.
2:46:44
740, but my routine was at a 73% and I figured out the algorithm for the routine, and I'm never making that mistake again.
2:46:51
uh you have to it takes the the rolling three-day average of when you go to sleep and you have to be within that band within 30 minutes of your rolling average.
2:47:02
So you can be a night owl and still have put up but it's about consistency.
2:47:09
You got to be consistent specifically 30 minutes within the rolling average.
2:47:12
So now I'm I'm dialing in my rolling average.
2:47:14
I know what that time is.
2:47:16
I'm going to be asleep before the 30.
2:47:17
It is it is funny that people people take the time that they wake up very seriously, yet don't take the time that they go to sleep.
2:47:25
It's the bedtime alarm is more important than the wake up alarm for sure. Yeah.
2:47:28
Uh anyway, in my household, the alarm bells start going off 7 p. m. It's bedtime. It's bedtime.
2:47:37
Nobody sleeps harder than me. It's bedtime. Uh this was interesting. Yeah.
2:47:40
Uh, so I guess apparently some news came out that the White House released a corresponding memo indicating that the exemptions also extend to changes in small parcel shipping duties, Apple, Teimu, Sheen, whatever.
2:47:52
Um, so anyways, this guy Dave is saying, "Wow, so the news over Yeah, the news over the weekend was, hey, for the really critical stuff, you know, we don't want to destroy Apple.
2:48:03
It's one of the greatest American companies.
2:48:05
We don't want to destroy Nvidia.
2:48:06
We're going to create exceptions for those."
2:48:08
But apparently in this one corresponding memo, Timu and Sheen were also included in the exemptions.
2:48:14
Uh, and they've been taking advantage of that deminimus exemption where they don't pay any tariff if they're under a certain weight.
2:48:22
And, uh, Dave here says, "Woo, almost hurt Timu and Sheen's businesses." Uh, which is ridiculous.
2:48:28
Obviously, like that's the easiest category to target because it's it's purely eroding quality American goods with this crazy loophole.
2:48:35
Uh and people have been expecting a dimminimous exemption uh you know tariff or or addressing that loophole for a long time.
2:48:47
Uh we talked to Ryan Peterson at Flexport about that.
2:48:49
Um so it'd be very weird if that sticks around.
2:48:51
That feels like an anomaly or something that might get flipped.
2:48:55
I think shortterm I think it's short relatively short.
2:49:01
I mean a lot pretty much everything.
2:49:02
So they're planning to close it on May 2nd right now.
2:49:06
Everything everything is short-term right now.
2:49:08
Nothing is nothing is written in stone. It's still free game.
2:49:11
Uh if you're trying to buy a couch for $15 Yeah. head over to Teeu. Yeah. Download the app. Yeah.
2:49:17
And uh I mean you can think about all the tariff stuff as like vibe law makingaking.
2:49:22
You just embrace the exponentials.
2:49:24
Let the vibes take over and forget the law even exists.
2:49:29
That's that's the way you do it.
2:49:31
Uh anyway, Kyle Tibbitz over at Wander uh is posting a photo of the Masters.
2:49:36
They ran an ad in the Masters.
2:49:36
I can't imagine a better audience to hit with a Wander commercial. Uh and and very cool.
2:49:44
They're using a little uh a little news bar at the bottom. It's a nice design. I like it.
2:49:48
Let you know as you're watching the the the ad, the.
2:49:50
com, the logo, there's a surprise waiting for you at checkout.
2:49:55
So, head over to Wander and find your happy place.
2:49:57
Find your happy place, book a wonder with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, 24/7 concier service.
2:50:05
We should put all of our ads and publish them as like a sp an artist on Spotify.
2:50:10
People can just listen to them. Totally.
2:50:12
I think the uh the song has been a resounding success. A success. Yes.
2:50:17
Um it's going to worm its way into someone's mind and in 10 years they're going to book a wander and have the Find Your Happy Place jingle play in their name. Play in their name.
2:50:27
We if if if real success looks like you go to wander.
2:50:32
com and just automatically I want to bring back like songs that play when you land on a website automatically. Yes.
2:50:38
So and those trailing mouse moves like the the mouse move the trails and and the colors and really HTML 1. 0 vibes.
2:50:47
Success looks like our face our faces being used as like if you have a question ask us and it's like in the bottom right hand corner.
2:50:54
To me, success looks like going to getbzzle.
2:50:56
com and getting a watch because your bezel concierge is available to help you source any watch on the planet. Seriously, a watch.
2:51:03
Uh, they're recommending the Rolex Date yellow gold. That's the presidential.
2:51:08
They got the GMT Master, the Batman, they got the Date Just Wimbledon.
2:51:12
They got a Submariner on here.
2:51:14
There's lots of great options on Bezel. Go check them out.
2:51:18
Uh, anyway, I I like this post from Will Brown.
2:51:20
underrated underrated poster put putting up some great content.
2:51:23
Uh so he's quoting Paul who says, "So Google Sheets now has an equals AI formula.
2:51:28
You can process data that was impossible before in a spreadsheet.
2:51:33
Gemini understands what's in the cells and returns tailor made answer."
2:51:36
And uh and he quote tweets with E= MC² plus AI.
2:51:39
And do you get that reference, Jordy? I do not.
2:51:44
It's a very funny reference.
2:51:46
Someone posted an extremely cringe LinkedIn thread about how uh AI is so disruptive, you must now consider a new formula called E= MC² plus AI. And it was very viral. It was very funny.
2:52:01
Uh but it is very silly that that Google Sheets just has an equals AI formula because most of the other formulas are like specific mathematical formulas.
2:52:10
Like AI can do a lot of things just like math can do a lot of things but typically uh you know you have a formula for a sum or an average or a vookup that does something specific not just equals AI.
2:52:21
So, uh, the bad naming continues across all AI products.
2:52:24
But it's not all bad news because France, the creator of Arc AGI, former Google employee, uh, just posted, uh, Google quietly released a powerful recommener library, uh, optimized for Jackson TPUs based on caris, which is the library that he created while at Google. It's called RecML.
2:52:43
It has, uh, native support for sparse core, latest, uh, hardware for handling large distributed embeddings.
2:52:50
And so what this means is that if you're just building a, you know, the next Tik Tok clone and you want to do uh recommending of different content across a really large system, they have a pre-baked machine learning system.
2:53:04
And these types of advancements are getting completely drowned out by everything in LLMs.
2:53:08
But just a just a vanilla recommender system is extremely valuable.
2:53:13
Yeah, th this type of system would have probably cost you millions to create even five, six years ago.
2:53:18
Chris Dixon, number one on the Midas list a few years ago.
2:53:23
Coinbase seed or series A investor.
2:53:26
Uh he one of his companies Hunch I believe is Hunch maybe.
2:53:28
Uh he I think he sold it to PayPal or eBay.
2:53:31
Uh and the whole product that he built was a recommener system.
2:53:36
And so this was called collaborative filtering and it's what drives those uh you may also be interested on Amazon.
2:53:42
These are really really critical systems for e-commerce sites for Netflix.
2:53:46
How does it predict what you want to watch next?
2:53:48
This has then been baked into Tik Tok and Instagram reels and and the remember you remember when Netflix like everyone was like oh that's their alpha like they just know how to recommend.
2:53:59
No it's commoditized but but it's exciting now.
2:54:04
It's exciting that that it's available just just via Google and you can uh specifically use sparse core which allows you to embed large distributed embeddings which means uh like when you when you define what makes a post on X
2:54:20
recommendable it's not just here's the text it's here's the text here's the user is their video what's in the video what do the comments say how long did people spend watching this video or how long did people spend reading this post, did they share it? There's so much other
2:54:35
There's so much other data that you could think of like metadata, but all of that gets embedded into uh like a basically a matrix of of what is this about and then that can be recommended based on other things.
2:54:47
And that's why these algorithms are getting so uncanny.
2:54:50
You know, you watch you watch one video about uh I don't know, McLaren F1 and then pretty soon you're seeing 25 more, right?
2:54:56
And it knows that oh, you're interested in McLaren F1.
2:55:00
might also be interested in McLaren P1.
2:55:01
P1 GTR takes you down this different road.
2:55:03
Pretty soon you're learning about Senna watching hours a day of Doug Demiro. Exactly. Exactly.
2:55:08
Uh that's all built on recommener systems and these recommener systems are not defined in a way that it needs to it needs to in understand what a McLaren F1 is in a human readable form.
2:55:19
Any new topic can instantly be baked into the recommener system through these embeddings. So very exciting.
2:55:25
So little shout out to Google for delivering some great software. We love to see it. I love big tech. I love big tech.
2:55:31
Uh let's go to Jeff Lewis.
2:55:31
Uh he says it it's fair to call the US dollar's decline yesterday parabolic.
2:55:38
More important than ever for investors to ask what's growing parabolically amidst macro volatility.
2:55:42
At Bedrock, our our answer is clear. Open AI.
2:55:45
We've concentrated nine figures into OpenAI across multiple flagship funds since early 2021.
2:55:51
And we've never been more bullish.
2:55:53
Yesterday at TED, Sam Alman shared, "10% of the world now uses our systems." A lot. I love it. Uh, crazy. It's great. Uh, yeah.
2:56:02
I mean, I think the number that was floating around was 500 million weekly active users, something like that.
2:56:08
But that's but pacing to potentially get to almost double that by end of year. Yep. Which is crazy.
2:56:14
Yeah, it is funny that I think they might still be eligible for using some of the open-source uh libraries.
2:56:22
Like I'm pretty sure they could technically still use Llama because Llama set the threshold at like 800 million users so that the other services couldn't use it or something like that.
2:56:30
Uh there's all these funny uh like big tech wants to exclude each other, but they are quickly becoming uh definitionally big tech.
2:56:35
And uh yeah, it's consumer consumer tech company, but we'll go more into Chat GPT and OpenAI and what's going on.
2:56:42
Uh Willm writes, "Chacht memes like roast me, create a CIA report, Gibbly Filter, etc. feel very familiar.
2:56:48
a throwback to Buzzfeed quizzes, Facebook personality tests, super intelligence or not, we just want to have fun and see ourselves in new ways.
2:56:57
So, I did one of those when they rolled out memory.
2:57:00
I I prompted it with one of the prompts that was floating around that was like, "Tell me my blind spots." What did it say?
2:57:06
And I was very disappointed with the response.
2:57:10
It just felt like super general astrology style answer where it like could apply could apply to anyone basically.
2:57:18
For me it for me it said it said I knew I knew my supercars really well.
2:57:22
I knew the holy trinity watches really well but I was really really lacking on equestrian and specifically Dr.
2:57:28
history like I don't know who the historical winners are.
2:57:33
leave the studio and you'll you'll spend hours talking to Chad GBT just over over audio just about Dr.
2:57:42
Horse and so it's basically knows like you're not fake which I think is can't fake it till you make it.
2:57:48
I think it's a real blind spot. I think Dr. is going to be huge. Yep.
2:57:51
First we talked about this. It's going to be huge. Dr.
2:57:55
is coming to Los Angeles. It's in the Olympics.
2:57:57
It's in the Olympics and we will be there. We will have a box. We'll have a box.
2:58:00
It'll be half VCs, half tech journalists.
2:58:04
It's going to be the biggest crossover event in history. You heard it here first.
2:58:07
Let's go back to Jeff Lewis.
2:58:08
He says, "Memory transforms chat GPT from merely an unprecedented consumer phenomenon into missionritical infrastructure for individuals, families, enterprises, and society at large." I agree. I think it's very cool.
2:58:21
I did see someone put this stuff in the truth zone.
2:58:24
Well, let's go back to Will Brown.
2:58:26
He says, "Chat GPT memory is the most disappointed I've ever been in an OpenAI feature.
2:58:30
It's unbelievably simple implementation and it doesn't even work.
2:58:35
It's crazy that they released this as a pro feature.
2:58:36
It is significantly worse than the vanilla clawed memory MCP tool. Sorry.
2:58:41
Uh so little bit of back and forth on how good memory is.
2:58:44
I imagine it's less important that it's amazing on day one and more important that it just keeps growing and growing and growing because uh obviously we've seen scale is all you need.
2:58:55
Scale is so important to these systems even if it's not great today.
2:58:59
Yes, it might not know your blind spots today, but let's talk about this in a decade.
2:59:02
Like maybe it has even more.
2:59:04
Are you really confiding in it?
2:59:06
It's probably a wildly different experience if you're using it as your journal every day and documenting your entire life in there versus, you know, just using it as information retrieval, right? Yep.
2:59:16
Will says he's pushing back his timelines. Tyler Cowan disagrees. Well, yeah.
2:59:23
I mean, should is is infinite memory a prerequisite to AGI or is it a separate thing?
2:59:28
uh OpenAI has actually mapped out the step function like the five steps in the layer to kind of their growth path and uh TAN who's been on the show mapped it out.
2:59:39
Uh level one was chat bots real-time predictive responses.
2:59:43
responses. This is 2023 system one thinking that's chat GPT that's GPT40 then you had the reasoners that's level two thinks for longer before responding system two thinking this is late 2024 you had 01 03 03 mini chat GPT search deep research that type of stuff then
2:59:59
agents we get to we get to the third level this is where they are now in 2025 AI that can do work for you independently that's tasks operator deep research and now this code product that they're building uh innovators that's level four develops innovations independently. That's something that we
3:00:14
That's something that we have not seen from any LLM or AI system really, but we're very optimistic about it.
3:00:19
There's been this big question, hey, you have a system that is it has all of the knowledge in the entire world.
3:00:24
Why can't it put two things together and just notice something, right?
3:00:28
That happens all the time.
3:00:29
Like the the like the reason we discover like penicellin or something is just because like there's a guy who knows about all these different things and realizes that, hey, these two things are correlated. Let's dig in there.
3:00:40
And no one's been able to pull an innovation out of these things.
3:00:44
And you even feel it with the the text, the tell me a joke, the the come up with an innovative business strategy.
3:00:48
It'll just be like, oh, like you should start a coffee shop because coffee shops sell coffee and this is way it's good at like stock business planning, not not new ideas.
3:00:59
And so that's where they want to get with level four.
3:01:01
And then level five is organizations.
3:01:03
They want them to think strategically and achieve organizational goals.
3:01:06
Uh we'll see how fast they get there.
3:01:10
Today we uh two more things to cover before we call it for today.
3:01:13
OpenAI co-founder Ilia Siver safe super intelligence uh pulled together the round at 32 billion. You love to see it. Love to see it. Little size for Ilia. Sizegong moment.
3:01:25
And uh we had some other news.
3:01:28
Larry Ellison has started following TVPN. Thank you. So welcome. Welcome to the show.
3:01:33
To the show and the community.
3:01:35
Uh you are in many ways our technology brother but also our technology father. Yes. So a true inspiration.
3:01:42
I mean founder mode for decades, one of the greatest tech companies has played such a role in in so many tech transactions.
3:01:51
He's in the conversation about Tik Tok.
3:01:53
He was a financeier behind Elon's purchase of Twitter.
3:01:59
Fantastic taste in hotels.
3:01:59
He has sensei which is phenomenal. Malibu Racket Club. Yes.
3:02:04
many esteemed institutions big into sailing.
3:02:07
Yes, he's doing it right. To say the least.
3:02:10
Um, today was a fun show. It was a great show. Very optimistic. I'm excited.
3:02:15
Uh, I just keep coming back.
3:02:17
I'm excited to experience AGI later this week. Yeah.
3:02:21
And I enjoyed the 30 minutes.
3:02:21
I thought that was a great pace. 20 minutes, 30 minutes. We start doing the 15s.
3:02:26
They get a little bit too fast-paced.
3:02:28
I like the way we handled it today.
3:02:31
So, thank you for watching. Thank you for listening.
3:02:35
Leave us five stars, Apple Podcast, Spotify, and we will see you tomorrow, folks. Looking forward to it. Have a great day. Have a great Monday. Have a great Monday. Bye. Cheers.