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Today is Tuesday, June 3rd, 2025.
4:55
We are live from the TBPN Ultra Dome. Still gets me, John.
5:01
The temple of technology, the fortress of finance, the capital of capital. Uh we have a great show.
5:07
We're going through a bunch of stuff.
5:08
We're covering CO2's public market updates.
5:11
We're going through uh some news about Nike, some news about Nvidia earnings.
5:17
We're going through We have We have a couple great guests today.
5:21
Um and we're going to take you through the timeline, of course.
5:23
Um of course, we also have a new gong cam, which I think we should show off right now.
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Jordy, why don't you give it a hit? Let's do it. Let's do it.
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Let's Let's check it out.
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The production team has been cooking. Check it out.
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We doing We have the cam. Oh, yeah. We have the cam.
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The horizontal cam is really really something. Really something. There we go. Yeah.
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I didn't realize that it would be horizontal. Oh, it's great.
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But it really is just about It's extremely chaotic.
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You want to see the vibration gong up close for sure.
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Yeah, you can see it swinging. Swinging.
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with easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place. Go to ramp. com.
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Let's give it up for ramp. com.
6:13
Uh I wanted to cover this yesterday.
6:13
We didn't quite have enough time.
6:16
Um but uh Mary Maker dropped the internet trends report.
6:20
Code two Philant fired back did not fire back. Uh very different take.
6:27
They're going deck for deck, John.
6:28
They're going deck for deck.
6:30
The code deck is a little tighter.
6:30
uh they use Sam Alman's face instead of uh instead of referring to OpenAI as just leading LLM company, they they actually come out and say what OpenAI is doing.
6:42
Um and uh but but it's a great read through.
6:44
I gave it I I gave it a full read through this morning and I thought it would be fun to go through on the show.
6:48
And so this is from mastersinvest.
6:50
com I guess is the account uh says Tiger Cub Philont Coto's public market updates.
6:56
It's too early to tell, but it's surprising how bad sentiment is compared to economic hard data.
7:00
And so, uh, it's a good read this Google. It's crazy.
7:05
You can be Philip Leaf Font and still be a Tiger Cup. Yeah, I know. Still a cub. Still a cub.
7:10
I mean, Tiger Global is itself a Tiger Cub because they spun out of Tiger Management, Julian Robertson's fund, which is very fun.
7:18
Uh, still using the Tiger name.
7:21
Imagine if uh Tyler Cosgrove, our chief intern, spins out and just launches TB Global. TB TB Global. Wow, he fully sent it.
7:32
Uh don't get any ideas, Tyler. Yeah. Yeah.
7:35
Uh anyway, this is an interesting fact that they kick it off with 2025 was the worst start to the year through April 21st. Whoa. Very depressing news. You hate to see it.
7:49
You hate to see it, John.
7:49
But it's really it's really remarkable how how quickly the year just turned from the Trump pump to the Trump dump.
7:56
And it got real rough there for a second.
7:59
So in the first in in the first uh what three and a half months, four months of the year, uh there was an 18% draw down.
8:09
Uh and that's compared to 2022 when the market drew down 16%.
8:12
2022 when the market drew down 16%. 20 uh 2001 started the dotcom crisis 12% in in 2000 10% uh but then they go on to uh and man 1998 was a banger year up 21% that's the the start of the do boom it's interesting because it feels like we're
8:31
in the midst of like the AI boom and yet we had like one of the roughest starts to the year in terms of the market um probably healthy in some way yeah so that maybe Trump just you know the the 4D chess was hey things are getting a little overheated. Let's let retail get
8:44
Let's let retail get another opportunity to buy the dip before we go on.
8:48
You know, I mean, I hate to I I hate to somewhat agree with you.
8:54
I mean, there was there was I I do think there was this there was this sentiment that people were so bearish a couple months ago. Yeah.
9:02
That it felt like retail was going to look really silly for buying the dip because retail over the past 5 years has just been trained always buy the dip. Always buy the dip.
9:13
Uh and it and it's played out generally well. Yeah. Um and so far Yeah. So good.
9:19
But and so that's the I mean I mean that is the interesting narrative here is like is this a crisis or a correction and um and is this really like the the like the end of the of the of the AI boom?
9:30
Is this the end of all the fun?
9:32
Is the party over or is this just like some slight turmoil?
9:34
So, uh, CO2 does a great job of kind of giving examples of crises and corrections and how they kind of, uh, they bucket together.
9:45
Uh, and so, uh, for crisises, for crises, they they highlight in recent memory, uh, the dotcom crash, the global financial crisis, and COVID, they put kind of in half crisis, half correction.
9:59
And this was the question that we uh that we were talking about with the tariff uh the tariff draw down was is this something that's out of the government's control? Can they pull it?
10:10
And if they pull back from the brink, it winds up looking more like a quick down and up versus something that's, you know, it's almost more of a a reaction. Exactly. Versus a Yeah. Yeah. Yeah. Yeah.
10:21
and and so and so it's a little bit uh so because it's kind of manufactured by the administration they can they can by definition pull back from the edge and that leads to uh this falling more in the correction category potentially but that's the question that CO2 uh centers in on during this uh in this presentation.
10:39
So uh for cris for crisis the first crisis that they highlight is uh the 2000.
10:43
com crisis which was incredibly long and so the draw down for the dot uh crash was 133 weeks so over two years of the market sliding downwards and then the and then the recovery to get back to where they were took 242 weeks. Insane. Yeah.
11:01
Uh the global financial crisis was similarly long a 74 week draw down.
11:06
So a little bit faster on the way down. Gen Z. Yeah.
11:11
Or even young millennials have not experienced a draw down like that like the global financial crisis. Yeah. Really? Really? Ever? Right.
11:17
We have like the the entire the the the new generation of investors has only experienced sort of kangaroo market, right? Exactly.
11:25
Up and down and up and down and up and down and up and down. Yeah.
11:29
And so COVID was similarly a crisis very very significant but the draw down was only five weeks but it was the craziest five weeks where there were circuit breakers breaking on the on the exchanges and there was a constant like oh the market's down another 5% and then the market's down another 5% or 7%.
11:46
Uh and so those five weeks were were miserable but then the recovery happened very very quickly only 21 weeks to recover and get back to the previous high essentially.
11:57
So um with uh and then they also highlight the the peak to trough for the S&P 500.
12:01
So the you can think of the dotcom crisis as like a 49 50% draw down.
12:06
Uh the global financial crisis was even worse at 57%.
12:09
You're thinking about like you just bought all you own is S&P 500 index and you're down almost 60% of like your wealth all the money that you've had invested very very rough.
12:21
And there were also commensurate earnings reductions in the dot and the 2008 crisis.
12:25
So companies actually started making less money.
12:27
So it wasn't just speculative and this happened and this happened in CO too. com 42% in '08. Yes. Exactly.
12:32
And so significant impact and that's the difference between a crisis and a correction.
12:39
Uh like obviously corrections are shorter but they also don't hit earnings as much because companies don't have enough time to really react and and and drastically change their um their strategies.
12:53
actually lay people off, actually cut back on spending, actually, you know, retool the business.
13:00
Sort of temporarily, you know, unsustainable and then they got pulled back to the point of still meaningful. Yeah.
13:07
But potentially less of a of a broad market impact.
13:10
And so then the fifth uh the fifth uh indicator that uh CO2 identifies here is the the weeks of elevated volatility in the VIX.
13:17
And so the dotcom crisis had 41 weeks of higher volatility.
13:23
The global financial crisis had 49 weeks of of elevated volatility.
13:29
Uh COVID had 26 weeks where the market was in turmoil essentially with elevated VIX.
13:34
Um but then you go to the other corrections that they highlight.
13:36
Black Monday, Gulf War, uh long-term capital management failure in Asia crisis, sovereign debt crisis in 2011, the POW pivot in 2018, and the inflation uh interest rate hike in 2022.
13:49
Uh now that the the the call it inflation, we call it the end of the Zer era in Silicon Valley.
13:57
We call it the SVB crisis.
13:57
Um but it but that really was what was happening.
14:01
happening. there was there was too much money printed during the the the COVID relief era that led to some inflation and that and that resulted in higher interest rates which of course blew up Silicon Valley and a bunch of and literally blew up Silicon Valley Bank um and and and the inflation correction uh
14:17
they don't put it in the crisis bucket but it does have similar obviously the the um SVB crisis wasn't directly because of you know overinvestment in venture but venture got so ahead of its skis in 2021 and early 2022 that uh and that and and in some ways like the the failure of the bank was was this that symbol symbolic, right? Even though a lot of their issues
14:43
Even though a lot of their issues was that they had a bunch of really long-term Yeah.
14:47
loans that that were um you know priced well below what was mismanaged balance sheet.
14:54
Um so yeah that inflation crisis just to compare it to it is funny that Silicon Valley Bank could not imagine effectively their balance sheet said we cannot imagine a world with rates higher than 3%.
15:06
And then it just rocketed. Yeah.
15:09
I mean I talked to I talked to people in the public markets who who had the similar sentiment that interest rates would never go up because if they did the the government debt would be so unsustainable.
15:19
Um and yet interest rates had to go up at a certain point because inflation was a was a was a tougher pill to swallow and so the Fed had to take their medicine and raise interest rates uh which caused that correction.
15:29
Now that that correction was pretty long 40we draw down 66- week recovery.
15:32
40we draw down 66- week recovery. 2022 was a rough year for sure and the market drew down 25% but CO2 still puts us in the correction category not this crisis crisis category yeah the crisis just to give you some insight into 08 specifically Apple went from $194 a
15:50
share to $85 a share 56% decline in Apple fell 55% 680 Alphabet was 685 to 300 and those companies weren't even particularly indexed on housing it was just that the housing market collapsed and when people lose their homes or their mortgages spike in in payments, they stop buying iPhones. And so it
16:09
And so it really was just this broad economic sell-off and and economic crisis.
16:15
Whereas the inflation issue, yes, we saw a 25% draw down in the S&P peak to trough, but the earning earning reduction was only 1% that during throughout that crisis, which is pretty remarkable because firms were still able and maybe that's a function of inflation, but firms were still able to um this was like the the the other term that was coined by Kylo Scandlin, who we should have on the show, um was the vibe session.
16:39
This idea that the market was was in turmoil.
16:41
Everyone was talking about how bad things were, but daytoday unemployment wasn't spiking.
16:46
It didn't have all of the trappings of like the global financial crisis, even though it felt very doom and gloom at the time.
16:52
And there was a question about can we get to a soft landing?
16:54
Can we pull back from inflation?
16:55
We kind of wound up doing that.
16:57
Um, but it was still a very tumultuous time.
16:59
And so the big question is like where do tariffs sit?
17:01
Like are we in correction or crisis territory?
17:06
What how long will this last? What is the draw down?
17:08
already we're at 19% off of highs or or you know uh we we we were in the beginning of the of the of the tariff uh correction.
17:17
Just to give you some insight back into venture in 2008. Mhm.
17:23
In 2008, venture firms raised 25 billion. Mhm.
17:26
2009 people were were saying basically whoaif only raised 15 billion in uh 2009.
17:36
Uh which then obviously last year was was over 76 billion. So very very low. Yeah.
17:43
Um and so uh CO2 goes on to kind of try and define the difference between crisis and correction a little bit more.
17:51
So crisis the draw down the duration of the draw down's long.
17:53
Uh the magnitude is going to be more than 35% whereas a correction it might be less than 25%.
17:57
Uh earnings cuts are going to be more than 20% with an average of of 35% earnings cuts and corrections are less than 10%.
18:08
uh capitulation peak VIX is uh more than a year for the crisis but just a few months for a correction and the sentiment bearish in both in both cases. Boo.
18:18
Um so the question is great sound effect.
18:23
Uh is will we look back on 2025 as a crisis or a correction?
18:27
And we've talked to a lot of people when the tariffs were happening who were telling us that this is an absolute disaster. This is a crisis.
18:35
this is a permanent change in the dollar, permanent change in the the global economic order.
18:38
Um and things looked really really bad as they were selling off.
18:44
Um we we were we I mean we saw whole day is where the market traded down 5% but we have obviously built back up and so um CO2 mentions here that 2025 may qualify as a correction.
18:56
So they're tracking the S&P 500 since liberation day.
18:58
The tariffs came in on April 2nd, uh just the day after April Fool's Day. It's rough rough timing.
19:06
Everybody says, "Was this a social media post?" Yeah, seriously.
19:10
Meant to go out a day earlier.
19:10
Uh and so they highlight two key moments here. Is there a market put?
19:15
Government announces a 90-day pause on tariffs.
19:17
That was uh the actual the market bottom on April 8th.
19:23
And then on April 11th, the regional Fed president says there may be scenarios in which the Federal Reserve would need to add temporary liquidity, saying that if the tariff situation continues to worsen, if companies are really suffering, um we might need to stimulate the economy through temporary temporary always temporary.
19:43
Um and so the big question is on earnings per share on corporate earnings because that is one of the biggest differences between a correction and a crisis.
19:50
in a crisis, the economy truly stagnates.
19:53
And we've seen that over the the the first 15 months on average of a of a true crisis in in CO2's definition, uh earnings per share dropped by 35%.
20:07
Um in corrections, it's more like 3%.
20:10
And so we are now about halfway.
20:12
We're about eight months into this crisis as they're tracking it.
20:14
And um uh and 2025 is at just just 5% off of earnings.
20:21
So, not really tracking with the average.
20:22
Doesn't mean that we couldn't see things fall, but that's where they're seeing that.
20:25
And then also the VIX spike was brief.
20:27
Um the uh the the volatility peaked um and and has since fallen from 52 to 23.
20:35
Um and if you're trying to track any of this or you're trying to uh get in on the action, head over public.
20:42
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They got multiasset investing, industryleading yields, and they're trusted by millions folks.
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had to serious investing to to check it out.
20:51
Um and public let's see um so the question is where are we today?
20:59
Uh 48 days in there's a severe year-to- date draw down which we saw 19% peaked trough uh in the last 24 days.
21:07
Rapid stabilization stabilization. We love that.
21:09
We love rapid stabilizations.
21:11
Uh so we're up 14% since year-to- date low in the S&P.
21:14
So the question is, are we are we on the verge of a breakout or is this a false start and we'll retest the lows?
21:20
And so they introduced the the CO2 hard truth index, a great coinage.
21:26
Love to see a coinage index.
21:28
And uh this is economic hard data divided by sentiment.
21:31
I would actually name this the Lefont truth index. Truth index. Just the truth. Just the truth. Purely truth.
21:38
And I I mean th this is a good this is a good kind of more quantitative way to look at what Kylo Scan was talking about with the the vibe session because you can open up the cover of the Financial Times and see a bunch of doom and gloom and and and the sentiment can be very bad even among consumers but when Christmas comes around sentiment is good for the news business.
22:00
It really is unfortunately. Yeah.
22:02
And so the question is is you know what is the strength of the consumer's balance sheet?
22:06
what how is the strength and and the true health of the American consumer and what's the state of the of the job market.
22:12
So they they they they identify CO2 identifies a few different metrics that they're tracking tracking.
22:19
So lagging data like job market and inflation leading indicators like consumer spending orders bookings and permits and then bleeding edge uh indicators like proprietary coaching data available on a daily basis because of course they're they're tracking all this stuff very closely.
22:32
Uh then on the sentiment side, they're looking at business sentiment.
22:35
Are businesses investing in growth or delaying capital and hiring plans?
22:39
Are is capex increasing at important companies?
22:43
Investors, are investors optimistic about future returns.
22:44
So there are polls that go out to investors just to ask them about their sentiments.
22:48
And then if you aggregate all of those, you might get a picture of how the sentiment in the stock market is doing.
22:53
And then you can decide if that is if if if the if the investor sentiment is out of step with the economic hard data.
22:58
And then of course consumer sentiment.
23:00
You can look at consumer spending or uh and saving rates.
23:06
And so in terms of sentiment, it's not looking good.
23:07
25-year sentiment indicators are at peak negativity across every sector.
23:12
So investors, businesses, and consumers, everybody is bearish. Everyone's blackpilled.
23:17
And I'm a contrarian, John. No, it's funny.
23:21
I was having a conversation with a uh buddy of mine.
23:23
I won't I won't name it, but he started a a uh a uh widely used unicorn. Okay.
23:27
And we were grabbing lunch last week and the restaurant was just absolutely packed. Middle of the day. Yeah.
23:39
It felt like it was and it was a restaurant that both of us go to routinely and we're like, we haven't seen this place this packed. Yeah. In a very long time.
23:48
And it felt like the roaring 20s. Roaring.
23:51
dropped in there and granted that's in Los Angeles on the coast. People are wealthy. Yeah.
24:00
But it still felt, you know, it in that environment if you asked everybody individually, how do you feel about the economy right now?
24:09
Whether they're a business owner, investor, or consumer, everybody would have been like, h like it feels shaky, yet their actions are saying something else, which is that the consumer is actually decently strong. Right. Yeah. Yeah. Yeah. Yeah. Yeah.
24:21
It it is it is very interesting.
24:24
Um and I mean it comes back I mean we're going to get into this but it comes back to that idea of like the picking up pennies in front of the steamroller that is AI. Yeah.
24:30
So there can be like all these crazy things that are happening that make so much tariffs were initially happening.
24:38
It was like, hey, is this a distraction from just winning in AI?
24:40
And uh, you know, Jensen is obviously conflicted, right?
24:47
Like every every CEO, he's heavily, you know, he's basically an index of of AI progress.
24:51
But, um, you know, in in many ways like if we are entering a new type of industrial revolution in intelligence. Yeah.
25:00
And uh, you know, probably that's the only thing that that matters is to really Yeah.
25:08
I mean we should probably cover this when we go through Nvidia earnings but the like as soon as the tariffs hit and Nvidia was hit very hard I remember there was there was this massive draw down in Nvidia specifically uh and there was you know huge questions about Nvidia's China business and and just overall GPU demand deepseek and Jeban's paradox stuff he was very much saying
25:30
like no like things are going to continue to grow like we're going to be fine and uh and the big question is like is Was was that ever cope or was he just actually right the whole time or did he more importantly execute very strategically in a tumultuous time to outmaneuver something that could have actually been pretty bad for his business? And so I'm sure we'll go into
25:49
And so I'm sure we'll go into that uh during the Nvidia segment.
25:51
But if you're speaking of widely used unicorns, you got to get on Figma. Figma. com.
25:57
Think bigger, build faster.
26:00
Figma helps design and development teams build great products together.
26:02
Um, it is a tool we use all day longing as you know. We love Bigma.
26:08
Uh, anyway, there are some more consumer data points that CO2 calls out here. One from Visa.
26:12
All spend bans remain resilient and consistent with past quarters.
26:16
Overall discretionary and non-discretionary spend remain strong.
26:20
We have not seen any signs of overall consumer spending weakening, says Visa on April 29th. What was that? Pump it up. That's Ben. That's Ben. Okay. Pipe down, Ben.
26:32
Capital One also says spend trends were largely stable through the end of Q1.
26:35
Bank of America says consumers are still spending money.
26:40
American Express says we're we're seeing our customers act as if they have act as if as they have acted in the past.
26:47
What's happened with the stock market or consumer confidence hasn't been associated with our card member spend.
26:53
They continue to spend and they're not spending off what's in the market.
26:55
And so um consumers consumers continue to spend.
27:01
And so there's this the like the vibe session narrative is still going strong which is very interesting. Yeah.
27:05
I mean it's interesting because obviously we're seeing exceptional growth in AI but we're also seeing pretty exceptional growth in the core inf business infrastructure.
27:15
So ramp, other companies in the payroll space like Rippling, things like that are seeing tremendous growth as well.
27:21
And I just, you know, and and AI is also a factor in that.
27:28
But so CO2 actually cohu actually uh charted this hard truth index and they and they track econ they track uh sentiment as the blue line here and then they track green and green hard data.
27:42
And so, uh, the Evercore company sales report.
27:45
And so, these should track very closely like like the the sentiment should match the hard data, but from 2021, 2022, 2023, sentiment was lagging the hard data, which was very very positive.
28:03
And then more more recently, uh, sentiment has taken a massive spike down at negative 1.
28:08
4 where the hard data is basically neutral at negative. 3.
28:11
And so, yeah, again, we're seeing more quantitative analysis of the Vibe session and it just doesn't seem to be going anywhere.
28:20
And I and I do wonder why we're seeing, you know, this this data goes back 25 years and the dislocations are pretty pretty rare.
28:28
You can see there's it feels like there's a little bit more more o there there there's sometimes a little bit of more more oscillation where the hard data is a little bit more aggressive than the sentiment.
28:40
sentiment. Actually during the dot boom sentiment was more neutral even though the hard data was worse and same thing in same thing in the uh in in in the in the global financial crisis after everybody's everybody's like you know spraying champagne in each other's faces meanwhile and the economists are like
28:55
this is terrible like you you were valuing companies with $5 million of revenue at 10 billion what what were you thinking everyone's like it's fine it's fine well now now we're seeing the opposite um and so to recap K2 sums it up says this does not seem like a crisis is yet more like a sharp correction. It's too early to tell, but it's
29:12
It's too early to tell, but it's surprising how bad sentiment is compared to hard economic data and someone it must be wrong between Wall Street and Main Street.
29:20
And so this is this is the question that we're trying to trying to dig into.
29:24
So sentiment sentiment alone they say is not enough of a buy signal.
29:28
When business sentiment is below the 10th percentile, the S&P 500 has top 20% one-year return 35% of the time.
29:35
uh 8% of the time when business sentiment is below the 10th percentile, the S&P 500 has a bottom 20% one-year return.
29:42
And and and you don't know 57% of the time, more than half the time, you just don't know. You just don't know.
29:51
So, uh based on history, they're looking at uh next 12 months price to earnings of the S&P 500.
29:58
And uh the market still looks expensive, but of course, a lot of that is driven by tech companies uh that that are growing very quickly.
30:05
are growing very quickly. Uh we talked about this interesting data point that something like the Mag 7 grew revenue in Q1 at something like 30% annualized where the rest of the of the Fortune 500 the the the 293 that aren't magnificent apparently uh they grew at like 8% less
30:23
magnificent the less magnificent and so uh uh I mean the uh the interesting thing here is that tech has seen a notable multiple reduction and so uh if you you can track the price to earnings multiple of all the tech companies which here are in uh uh where which one is which. Uh so the tech companies are in
30:43
Uh so the tech companies are in blue and the non- tech companies are in purple and the tech companies you know you go back to the dotcom boom they were trading at incredible priced to earnings multiples up in up at 45x on average.
30:55
Uh and then postcoid there was a dislocation again where tech was pulling away but got up into the 20s and 30s but is still trading at at 24x earnings where the non- tech companies are at 18x.
31:11
So there's still this there's still this spread.
31:13
So during COVID there was an 8x spread.
31:14
AI had a 9x spread and the current spread is 6x.
31:20
And so uh AI is not the the subcategory but like the trend that kicked off in 2024 when the when the AI trade got really really heated up.
31:28
Uh and so uh some tech franchise names uh you know the we keep coming back to this but Google is actually down 3% over the last year.
31:40
So again despite being you know one of the greatest AI innovators just not getting any credit should be a massive beneficiary even even this year.
31:49
But of course, the the stock has traded up a bunch.
31:50
Um, and so some tech franchise names look more reasonable today. Reddit is down 49%.
31:54
Tesla's down 40% off of the 52- week high. Uh, ARM is down 34%. Um, Shopify is down 23%.
32:04
Nvidia is down 23% off the peak. Amazon 22%, MetaF 19%.
32:07
And so there are still some some tech companies that are are lagging their all-time highs.
32:12
Um, and it's always interesting to kind of go to the the the the public filter for what are the kind of power law super dominant tech companies that are still in founder mode, still led by founders and uh and and and investigate those businesses and see if they do have if they are set up for the next for the next wave.
32:33
for the next for the next wave. um they could be good uh they could be opportunities especially if they're getting beaten up for kind of some macro trend that they will that you would expect a tech founder to be able to um dig their way out of the hole like what
32:48
happened in COVID and like what happened during the um during the the the Powell pivot uh and and the interest rates uh like when interest rates went up Shopify Palunteer um who else uh I mean a lot of these tech companies got absolutely beaten And the ones that really emerged, a lot of them were founder led. A lot of
33:07
A lot of them were were willing to not really change course or if they needed to change course, they did it quicker than the other companies.
33:13
And so, uh, they include a quote from Charlie Munger here all the way back from 1998.
33:17
Uh, Charlie says, "Forget what you know about buying fair businesses at wonderful prices.
33:25
Instead, buy wonderful businesses at fair prices."
33:27
And so, the question is, is the glass half full or empty? Half full?
33:32
You know the the bull case here AI is exploding clearing order inbound.
33:38
Macro is he macro will heal it will heal will heal itself.
33:40
Uh the half empty the value investor they say there's a recession on the horizon.
33:45
They say there's tariffs.
33:46
Uh Berkshire Hathaway has a $350 billion cash pile.
33:49
Lots of things that look not great.
33:52
Um and so what is CO2's view?
33:55
They believe that tokens are more important than tariffs.
34:00
And this is the this is the AI being more important than so launching a cryptocoin.
34:05
No, no, no, don't even joke about that. Yeah.
34:08
Don't we don't joke about that.
34:10
That's the one thing we we will never joke about.
34:12
It's taken out to pump fun about it with you. Yeah.
34:15
In fact, just to clear the just to clear the view, let's tell you about Vanta.
34:20
Automate compliance, manage risk, prove trust continuously.
34:22
Uh the the the opposite of a of a of a fly by night memecoin.
34:27
One of the most reliable businesses in the game.
34:29
Vantis trust management platform.
34:31
Takes the manual work out of your security and compliance process and replaces it with continuous automation.
34:36
Whether you're pursuing your first framework or managing a complex program, some of the best businesses in the world use including ramp. Yeah. Duallingingo intercom. Very cool. Mral. Really?
34:48
The French prominent French AI company. I love it.
34:50
We got to we got to get someone from astral on. Iceland Air.
34:54
We haven't talked to them yet.
34:54
People never think about Iceland Air being on the cutting edge of Have you been to Iceland? I have. You have. Was it nice? Uh I had to go there. I I once was in Africa. Okay.
35:05
And I I was in college and I had $400 in my account. Okay.
35:08
And I had to get back to America.
35:11
So you went through Iceland and I and I charted the most heinous route from like from Morocco to London to through Iceland back to San Francisco and I made it back.
35:26
What's the bullcase for Iceland?
35:27
And the and the the flight uh that was going to and from Iceland was uh it the the chairs didn't were were like bench seats and like almost made of plastic. Okay.
35:41
And it was like a really really long flight like a bus. Uh but I made it home. Made it home.
35:45
I feel like the bullcase for Iceland Air is probably Greenland becoming a state or protectorate or something.
35:51
Many people go there and then Iceland Air probably is going to be the one to get you there at least in the short term. Totally.
35:58
They're going to have a direct flight from uh where will people be going to Greenland from? Probably Park City.
36:05
Anyway, straight from CO2 goes uh goes into OpenAI and they're digging into this thesis that tokens are more important than uh tariffs.
36:13
And so they ask what just happened at OpenAI, the number of monthly active users, MAUs, post launch.
36:20
And so uh uh the they're tracking the number of months post launch for all of these companies.
36:26
Uh you can see Twitter now X uh over 96 months they grew to 288 million uh uh active users monthly active users.
36:35
Um Instagram's over a billion, Facebook's over a billion, Tik Tok's over a billion over that 96month launch period.
36:42
And you can see that these these these social networks, they grow exponentially, but it it it's it looks like a complete grind compared to what OpenAI is putting up.
36:54
And of course that's because OpenAI can travel so much faster because they can leverage the virality of the social internet and everyone already has phones and internet whereas uh for something like Instagram many people didn't even have iPhones yet.
37:06
And um and uh and of course Instagram launched exclusively on the iPhone and took them a while to launch an Android phone and I imagine that 36 month bump is probably them launching on Android or maybe desktop who knows.
37:20
Um but OpenAI launched deep research and operator just uh 24ish months after they launched the original product and they jumped from 400 400 million users to 800 million users.
37:33
Uh and this of course is based on a quote from Sam Alman who says uh the users doubled in just weeks.
37:37
And so it's a little bit of like they're creating this graph somewhat speculatively.
37:44
They're not exactly sure all the numbers.
37:45
They're trying to work backwards.
37:46
Um and and there are of course questions about who are those users, where are they, how monetizable are they?
37:52
But all of that stuff is is kind of something that investors will be digging into down the road.
37:56
Right now it's very clear that open is breaking through in a massive way all over the globe honestly.
38:02
Uh and so uh CO2 also highlights the comments of Sachi Nadella for Microsoft uh talking about a major AI inflection.
38:09
Uh Microsoft says we we processed over a hundred trillion tokens this quarter, up fivex year-over-year, including a record 50 trillion tokens last month alone.
38:21
last month alone. So that that that quote just really says like exponential growth in inference and this is going to be very very important for our discussion on Nvidia earnings because uh Jensen previously had revealed the ratio
38:38
between inference and training loads and he hasn't given as much guidance on that now and so there's a big question about uh how fast is the shift actually happening how much demand is there if you can compress these models and deliver a great product with less GPUs. Like if basically you could see
38:55
Like if basically you could see exponential growth in token generation, but if you see exponential savings in the in the amount of GPU cycles it takes to create a token, you see flat GPU adoption and roll out.
39:10
No one's really expecting that.
39:12
Everyone's building tons of these massive AI factories.
39:14
Um, and Jensen did actually go into unpacking the AI factory idea a little bit more, which I which I'm excited to talk about.
39:21
But, um, Jensen continues, "This is from the Microsoft uh, earnings call on April 30th.
39:26
While we continue to bring data center capacity online as planned, demand is growing a bit faster.
39:32
Therefore, we now expect to have some AI capacity constraints beyond June."
39:34
Which is interesting because he was saying, "Oh, like maybe I'm going to be a leaser. Maybe I'm not going to."
39:38
Market clearing order inbound. The market is clear.
39:42
He's excited to be a leaser. Yeah.
39:43
He said, you know, he said earlier this year he was cancelling some projects, but he said he's excited to be a leaser.
39:49
And we saw and and and we saw actual uh capacity constraints at Google in their in their last earnings, remember?
39:56
Um and so it it'll be interesting.
39:58
We see capacity constraints every day with you and Vio. I know.
40:00
I really throwing your phone across the room hitting hitting getting rate limit.
40:06
I need to like set a recurring reminder on my calendar for every night. Yeah.
40:11
because if I miss a day, it's like, oh, I can't get those back because I only get like three a day and I'm paying the max.
40:16
So, the actual the actual best practice is to like set myself a 15minute calendar hold where I, you know, use VO to the max basically, although there's probably a better way to to interface with it over the API or something like that.
40:28
But anyway, um, Satcha goes on to write, "With deep reasoning and agent flows like Cop-lot Studio, customers can build agents that perform more complex tasks and also handle deterministic scenarios."
40:39
Now, there's this interesting debate going on.
40:43
We I don't think we got to it in the timeline, but um, uh, the the the founder of Zapier uh, was Wade Foster, not Mike, who's been on the show.
40:51
Um, Wade was saying like, "We are doing a lot of stuff with agents at Zapier."
40:55
and he kind of mapped out one of his agentic workflows and somebody was kind of chirping at him being like this is just a workflow.
41:03
This isn't this isn't actually like fully this isn't AI because like you defined for example like you would have one agent that processes an inbound form and then another agent that so like let's say that we're doing inbound sales.
41:19
you you have a you have a website and a landing page and then if somebody's interested they fill out a form and say where they're from, what size company they work for, that type of stuff.
41:26
You have a you have one form that processes that and then that hands it off to an agent hydrates and says, "Hey, go scrape their LinkedIn and see who they're who else they're associated with.
41:33
Are we affiliated with them?
41:35
Are we already selling to them?" Kind of like fact that.
41:37
Then you might have a different agent that sits there and triggers, okay, based on what we know about them now that we've hydrated the the account, let's send them an email or let's send them a phone call or let's route it to Steve who's already been talking to somebody else at that company. Yeah. Yeah. Right.
41:49
Um and and then and then on and on and on.
41:52
And so these are these are like workflows, but they're powered by LLMs at every phase.
41:57
But there's this question of like are they agents or are they not?
42:01
It all people people want to chirp at Zapier because they're an established large company that's been operating forever.
42:12
But you would have to apply the same rigor and framework to every company that says they're an AI agent. Yeah. Yeah.
42:18
So, yeah, I I I think people are maybe overly obsessed with the idea of of and and I've certainly fallen into this trap before uh this idea of like end to end learning, oneshotting, this idea that like it is like creating an ensemble approach of different models, different technologies, some business logic, some deterministic logic, some some uh non-deterministic uh AI generating uh tokens to and reasoning tokens to to get you the result. It's all semantics.
42:48
I mean, it does have an impact on like the super long-term future and kind of the way we design these systems, but uh at the end of the day, most businesses just care about resolution results, right? Results.
42:57
And so, we're seeing that at Microsoft, their the Azure revenue, their cloud is accelerating.
43:04
Uh so, Microsoft Azure's revenue growth on a percent year-over-year basis.
43:08
um through uh up in March of 2021, they were growing at 55%.
43:16
That that went down to 25% in March of 2023 and then it grew to 35% in March of 2024.
43:26
It was down at 31% in September and now it's on an up and now it's on an upswing again.
43:33
We're incredibly back is what Saja is saying.
43:36
He also reported in that last earnings call that already 70% of the Fortune 500 is using Microsoft Copilot for a bunch of AI tasks. So 70%. Yeah.
43:47
I mean% we know what they have to do which is again it's kind of it's kind of like Google saying we already have a billion people using AI overviews or whatever the metric is because they're just sort of slotting it in. Yep.
43:59
Because you know I'm sure that 70% of the Fortune 500 already runs on Microsoft Yeah.
44:04
teams or or whatever uh infrastructure they have set up or they run on linear.
44:10
Linear is a purpose-built tool for planning and building products.
44:14
Meet the system for modern software development, streamline issues, projects, and product road maps. Linear for agents. Check out.
44:18
Speaking of, if you're not on agents, linear yet, what are you doing?
44:23
They got cursor, runway, complexity, retool, retool, mercury, ramp, openi, scale, forc cell, arc. Absolute dogs.
44:34
They're absolute dogs over there. It's fantastic.
44:36
They probably wouldn't describe themselves that, but we do. Yeah, we do.
44:39
Uh, so speaking of agents, uh, the reasoning unlock, this is back in the code deck.
44:46
Agents thinking on their own, solving problems creatively. quote from Sam Alman.
44:49
We view this as the beginning of the next phase of AI where you can use these models to do increasingly complex tasks that require a lot of reasoning.
44:58
And so chain of thought reasoning is multi-step trajectory where the model thinks and iterates. It writes code. It searches the web.
45:03
It creates the reports, build tables and all of these uh the model keeps asking does this make sense?
45:09
I should verify the source. Let me edit my work.
45:11
me edit my work. And so um all this this reasoning revolution this agent these agentic workflows uh it feels very much like this narrative of like oh we kind of capped out on the previous thing we need a new buzzword but it's actually showing up in the data and we're seeing it in uh upward revisions to cloud capex
45:29
when you add up Amazon m uh Microsoft Google Meta Oracle and Tesla oh we got the big six and it's a different six it's a different six uh Capex has gone from $213 billion uh to $310 billion a a 70% jump and today the capex forecast is up at 365 billion which is pretty crazy which again Tesla's up here good work getting
45:59
in not a huge contributor to this they're expected capex is going to be around 10 billion yeah it would be interesting to see how Tesla and uh and XAI kind of partner on the capex side build these build these like hypers scale data centers because you're already kind of seeing that take shape with Stargate where it's a separate
46:19
entity and and within Stargate there are also separate entities where who owns the land who owns the the the the power production it doesn't necessarily make sense to always bundle all of those in the same company and so yeah so Oracle's projected capex for 2025 is 16 so between Oracle and Tesla. Yeah. You still have over 300 billion, Yeah.
46:41
You still have over 300 billion, you know, well over $300 billion. Yeah.
46:48
Uh just coming from the core for Amazon, Microsoft, Google, and Meta. Yeah.
46:51
I mean, this is why we refer to the core four as like the hyperscalers truly.
46:54
And and when you look at Amazon, Microsoft, Google, and Meta, you're seeing high double digits of capex in in the billions.
47:04
60 70 80 billion dollars going into capex.
47:06
and that's driving the majority of that 365 billion of overall capex.
47:10
But if AI wasn't real, if there wasn't real demand, it would be extremely hard to justify this level of capex investment.
47:16
And so this is all driven by actual demand for Google Cloud, actual demand for Azure, actual demand for reasoning tokens.
47:24
Actual I mean Meta was in the news this week talking about how building they want to ultimately create the ads that they run. Yeah.
47:32
Well, speaking of ads, let's run an ad for Numeral. Numeralhq. com. Sales tax on autopilot.
47:37
Spend less than five minutes per month on sales tax compliance.
47:41
There is a fantastic company that runs on numeral. Lucy. Lucy.
47:44
Yeah, my company runs on Luc on on numeral.
47:48
Uh anyway, going back to CO2, they say tokens are greater greater greater than tariffs.
47:54
Exclamation point exclamation point. I love it.
47:56
This deck is, you know, obviously built by a crossover fund, hedge fund, like very successful, like very serious on Wall Street. Personality.
48:04
I Yeah, I see them as, yes, they they are a major player in venture, but they're also a major player on Wall Street.
48:09
I see them as like a respected institution, and yet they're having some fun with the deck, and most importantly, they're clear.
48:14
It's very clear, digestible, not too much jargon.
48:16
Yes, there are some very small bullet points or footnotes that I haven't been reading, but in general, done a great job of summarizing these things.
48:23
So they have three to three takeaways from a market perspective.
48:26
We remain vigilant but have confidence in the AI trend.
48:30
Completely agree remain remaining flexible tracking bleeding edge data carefully.
48:35
AI could be such a gamecher.
48:38
We need to capture this trend. I think it's spot on. Spot on.
48:39
And so that's their conclusion.
48:43
My only uh I know they can't give uh you know investment advice here but uh I wish they took a slightly firmer stance and said AI will be a gamecher if we need to capture this trend.
48:53
they they they sort of, you know, leave some ambiguity there.
48:57
But uh but yeah, I think that that's, you know, drawing it back to earlier stage venture that feels like, you know, people are doing rounds that they feel are quote unquote overpriced that they're a little bit uncomfortable. Yep.
49:09
With valuations or the amount of investment that's being made at at um oftent times, you know, with just a a deck in a team.
49:17
But at the same time it you know they they nobody can afford to miss AI. Yeah.
49:23
Like if you come out of the next five years and you don't have you know multiple bangers don't expect to to be a uh you know serious fund over the long run. Yeah.
49:32
So the poly market on the US recession in 2025 is down at 30%.
49:37
Still a little bit higher.
49:40
like wouldn't be that crazy if it did wind up happening.
49:43
But in general, that's that's looking pretty positive.
49:47
On uh on Liberation Day, it was at 42% on April 1st, the day before tariffs.
49:54
So, it was already climbing.
49:54
I think people were expecting something to happen.
49:57
Um it was very low at the start of the year. February of 2025. This was down at 22%.
50:05
spiked all the way up to 66% post trade war was kind of hovering around 50 60% more likely than not to happen recession and it's since been dropping and dropping and basically every day uh for the past few weeks it's dropped and is
50:20
now around 30% but we got to get it to zero folks we got to get it to zero it's a team effort over here in the American economy let's make it happen just you know next time you're frustrated with the economy don't be thinking what what's the economy going to do for me? Ask yourself what you can do. Don't take
50:36
Ask yourself what you can do.
50:36
Don't take it don't take your frustration or your consumer sentiment out on the economy.
50:42
It's okay if somebody calls you up, hey, I'm from Pew Research. How you feeling?
50:46
You can you can tell them the truth.
50:46
You can tell them you're not feeling good.
50:48
But when it comes time to do some Christmas shopping, just go all out. Just go all out. Just get on bezel.
50:52
Just buy the most expensive watch you can possibly afford. Do it.
50:56
You're contributing to GDP. Yeah.
50:58
I mean, your bezel concierge is available now to source you any watch on the planet.
51:02
And what could help build the American economy more than fantastic luxury watches available on demand at getbesszel. com.
51:11
Anyway, uh the other side of this narrative going even yes uh going even broader is there's now questions about the the the US debt.
51:20
And so Wall Street has been sounding the alarm on the US debt.
51:25
This time it's worth listening says the Wall Street Journal.
51:29
Uh Jamie Diamond says you are going to see a crack in the bond market and he has plenty of company here.
51:34
So I wanted to give a little bit of a review of this because even Elon Musk has been talking about the the struggles of the government and how some of his optimism around writing the budget and um and creating a a budget surplus uh did not come to fruition like he was hoping for.
51:54
So the big question is is the US going broke? It's not possible.
51:56
Joe Weisenthal, we print dollars. We're good.
52:00
We have a dollar machine.
52:00
We have a dollar machine. Um, yeah.
52:02
The the the other element, this this went out right as we were about to go live, but Elon posted at 10:31 about an hour ago.
52:10
I'm sorry, but I just can't stand it anymore.
52:15
This massive, outrageous, pork fililled congress congressional spending bill is a disgusting abomination.
52:20
Shame on those who voted for it. You know you did wrong. You know it. Wow. So, not mincing words. It's rough.
52:29
Um and breaking breaking rank from he's not he's not an employee government employee anymore citizen and he can he can voice his opinion however he wants.
52:40
Um I think the bigger question is like uh this yes like this this might be depressing to Elon.
52:49
might not be the outcome he wanted.
52:51
But in many ways, this is business as usual.
52:52
And and so how can the US economy steer its way through and how can markets react and how can companies build through what is continues to be a poor build spending package uh as it has been for decades, right?
53:10
And I think the answer we're going to come back to again is just is just continue to dominate on the frontier of technology, continue to win in AI and space and all the companies that Elon is already working on.
53:19
So um Elon is kind of refocusing on the thing that actually shared he had already shared something like a week ago that he said I'm not convinced we can solve our problems politically. Yes. Through the government. Yes.
53:32
We need to just grow GDP. Exactly.
53:34
And so if GDP does start growing at 5 10% because of all the technology that folks are working on building right now, well then that probably actually does start solving the the budget deficit unless we just find ways to spend more pork. Who knows?
53:48
Hopefully hopefully pork fil hold it in.
53:50
So uh featuring an an illustrated Uncle Sam with pockets turned inside out.
53:55
That was the cover story of America's most influential news magazine in March of 1972.
53:59
Sounding the alarm about a debt crisis has been great for companies shilling gold coins and flashy financial products, but has made smart, sincere people look silly when nothing happened.
54:10
Financial markets equivalent of Y2K.
54:11
So why are several people suddenly worried?
54:14
Uh because the math is getting daunting with interest on the debt blowing past $1 trillion annually and Washington acting recklessly.
54:23
Even people who have issued past warnings deserve a second or third or fourth hearing.
54:28
and they link to something which I'm sure is someone who has uh warned many many times.
54:32
So, hedge fund manager Ray Dalio does have something to sell.
54:36
His book, How Countries Go Broke, out Tuesday. Yeah.
54:39
So, he launched this this morning. Oh, cool. It's available now.
54:41
Let's let's invite him on the show.
54:43
It'd be great to have him. Yeah.
54:44
Uh but the world's 172nd richest person is hardly staking his reputation on royalties and his arguments are compelling.
54:52
Again, Ray Dalio, I actually did a I made a YouTube video about like like when is a like how how would you quantitatively define kind of a like a fake guru, someone who talks about business but doesn't actually uh like like what is the difference between like an entrepreneur or an investor that just get talks or writes a book versus media is their only thing?
55:15
and and Dalio you can kind of like yes he has he has incentives around his business but uh he does not make the majority of his money from his book and so you could you could like the optimistic case is that his book is is is less about just selling copies. Yeah.
55:35
It's more about actually like sharing his worldview or or or trying to influence like his broader business.
55:43
even even maybe like hiring at Bridgewwater could be more of a more of a needle mover for him than just selling copies.
55:49
So, I think it's worth worth investigating.
55:51
Um, Dalio told Bloomberg he gives America America three years, give or take a year, to avert an economic heart attack.
55:58
Peter Orzog, chief executive of investment bank Lazard and former budget director, wrote last week, "Those who bemoaned the uns the unsustainability of deficit spending and debt levels back during his time in government seem to cry wolf a lot.
56:12
Now he's worried too because the wolf is lurking much closer to our door."
56:15
The package, so this is what Elon was alluding to.
56:19
package of tax and spending measures sent to the Senate, now officially called the one big be the one big beautiful bill act could act like budgetary wolf bait.
56:29
It would add around three trillion to debt levels over the next decade compared with existing estimates and 5 trillion if certain temporary features were made permanent according to the nonpartisan committee for responsible federal budget.
56:40
For perspective, the federal interest this fiscal year already will be more than the defense budget and more than Medicaid, disability insurance, and food stamps combined.
56:50
Moreover, the Congressional Budget Office estimates assume that the bond market will not only tolerate a surge in spending, but become more relaxed about it with lower yields.
57:00
Consider if the yield on the 10-year Treasury note stayed at today's level around 4.
57:04
4% 4% for the coming decade.
57:06
Then the CRFB estimates it would add another 1 trillion in interest costs over that period. Wow.
57:11
And what if yields surge instead in a vicious cycle?
57:16
JP Morgan chief and absolute Chad Jamie Diamond warned on Friday of the consequences.
57:21
You're going to see a crack in the bond market. Okay. Yeah. So, yeah. Yeah. It's interesting.
57:25
I feel like I'd like to uh we should try to pull up Yeah.
57:29
what he was saying exactly before and after that because I'm assuming that it adds some important context. Please. Yeah, go pull it up.
57:38
I'm just thinking about like throughout my life there's been whole news cycles around this idea that the defense budget is so massive and it's this massive part of the federal budget overall or Medicare and Medicaid and disability insurance.
57:54
These are these are huge huge costs and they and they drive the majority of the uh of the federal budget.
58:01
And now we're at a point where people would always talk about the defense budget or Medicaid as being maybe wasteful or maybe unoptimized, but at least you're getting something for that.
58:14
You know, like like with those budgets, even if it's even if it's 60% or 50% or 20% less efficient than it could be, um, at least you're getting something.
58:24
With interest, you're literally getting nothing.
58:25
You're just paying the debt and that's it.
58:27
It's like it doesn't even have the opportunity create to create any like value or security or health care for someone like it's pure just just paying back for something that a long time ago after Jamie Diamond said you're going to see a crack in the bond market. Okay.
58:42
He says uh and this is why the journal didn't want to include it because it's he says after stating this quote Diamond emphasized that this bond market fracture is inevitable though he is uncertain whether it will happen in six months or six years.
58:56
He warned regulators directly that you are going to panic, but he himself would not panic and expect JP Morgan Chase to manage through it.
59:02
He also highlighted that current bank regulations restrict banks ability to hold bonds, limiting their capacity to provide liquidity during market disruptions, which could exacerbate the crack in the bond market. So, yep.
59:16
Anyways, he's he's seemingly, you know, frustrated with the uh new spending bill and spending broadly. Yep.
59:22
Uh, the Wall Street Journal continues, "Yet the bond market isn't exactly collapsing, even if 30-year yields recently hit a postcrisis high.
59:32
So, who are you going to believe?
59:33
Millions of fairly relaxed investors or some wealthy pundits?"
59:35
Uh, another hedge fund manager, Paul Tudtor Jones, calls the paradox an economic kayfabe, a term from professional wrestling.
59:42
Let's give it up for professional wrestling.
59:44
We love professional wrestling on this show. Round of applause.
59:47
WWE, if you're listening, I'm ready to get in the ring. Let's do it. Let's do it.
59:52
We We could be the absolute it's heel that everyone hates be like these slick like tech bros the like the tech and then we just get destroyed by like the the Logan Paul. Yeah, Logan Paul. Great.
1:00:06
Uh so so he says those who know that that the numbers aren't sustainable are happy to suspend belief when while the show continues.
1:00:14
Treasury Secretary Scott Basent uh reiterated this past weekend that the US will never default on its debt, but it doesn't have to.
1:00:23
Rapid inflation would accomplish the same thing if the Fed had to ride to the rescue through a measure called fiscal dominance.
1:00:28
Uh what is the tipping point for the bond market to go from mild anxiety bad things something so cool? I know sounds great.
1:00:35
We do have fiscal dominance.
1:00:37
Uh former IMF chief economist Kenneth Rogoff an authority on debt crisis explained in April that they are never a matter a matter of simple arithmetic.
1:00:46
Almost every country default either through outright default or high inflation occurs long before debt calculus forces it to.
1:00:54
Despite Dalia's guesstimate, knowing when doomsayers will be proven right is impossible. Consider Stein's law.
1:01:01
If something cannot go on forever, it will stop.
1:01:05
Contrary to urban legend, that line wasn't uttered by Ben Stein, who played the boring economics teacher in Ferris Beer's day off off, but by his father Herb, an actual economist. Life comes at you fast. Very rough.
1:01:15
Well, if you're losing sleep over the tumult in the public markets and the global economy, you got to get needed sleep.
1:01:23
They have a Pod Five Ultra, 5-year warranty, 30 night risk-free trial, free returns, fast shipping.
1:01:28
Are you are you what I'm going to riff it out? I don't know.
1:01:32
We should I don't know if we should riff it out.
1:01:36
Um John's had a good bit lately that eight sleeps are just so comfortable that they actually they should test them on animals.
1:01:43
Well, recently I've been doing some animal testing at home actually with my eight sleep. So, your own dog? Yes.
1:01:48
So, my dog obviously grumpy because there's now kids around the the house and I think he's getting less attention and also he's just a grumpy old 10-year-old Newfoundland.
1:01:56
Uh but I come home and he's always sleeping on the bed on my bed on my eight sleep and I and I and he's doing it more and I don't know if it's correlation or causation but I think he loves the eight sleep. Yeah.
1:02:07
But he sleeps right in the middle.
1:02:09
So, he's getting like warm on one side, cold on the other side.
1:02:10
He wants to just roll to one side. Yeah. Yeah. Yeah.
1:02:14
So, you know, proudly you can you can change the temperature on either side to perfectly adjust it.
1:02:19
Once he learns to use the app, it's going to be a game. Going to be insane.
1:02:23
You should get him an iPad by the bed, but he just How do you last night? I I got an 87.
1:02:32
I'm not proud of it, but um I was up a little bit late, but I kind of slept in a little bit.
1:02:36
I bet I got crushed on the uh on the regulation. The consistency. Consistency. 82. 82.
1:02:40
Okay, I just I got an 87.
1:02:43
I just need to put up seven straight nights of Okay, let's see. of sleep dominance. Sleep dominance. We'll see you tomorrow. Nvidia earnings.
1:02:50
Uh so, uh from the Wall Street Journal, Nvidia's business is booming despite being shut out of China.
1:02:57
We've been covering this for a while.
1:02:58
Uh Jensen's been running around the globe building AI factories everywhere on an absolute tear.
1:03:05
And most recently, the uh Nvidia shares surged 5% after hours as quarterly revenue surged to a record 44 billion.
1:03:13
Let's hear it for Jensen.
1:03:13
I think you should hit the gong for Jensen. I mean, 44 billion.
1:03:16
Why don't you hit it, John?
1:03:18
I want I want to see you on the Can we get the gong cam pulled up?
1:03:21
Let's get the gong cam pulled up.
1:03:23
Market clearing order inbound. There we go. There we go.
1:03:33
It just keeps ringing, too. Yeah. Yeah.
1:03:35
When we hit the soundboard, it's it's pretty soundboard's in and out in like five seconds, but the gong the real gong remains, you can't you can't beat it. It's the best.
1:03:43
Um, and so Nvidia's business is still booming even with the company effectively shut out of one of the world's largest markets for advanced AI chips.
1:03:51
The chip titan has been on a roller coaster over the past few months after the Trump administration moved to limit sales on chips uh to the Chinese market.
1:03:59
We're having Aaron Gin come on later in the show and he'll break down kind of the uh what's happening most recently uh with Nvidia and chips. He's the GPU whisperer.
1:04:07
Um you of course know him uh if you've been watching the show.
1:04:11
Nvidia, which has emerged as one of the most valuable companies because its chips provide the computing power needed in a global AI arms race, posted another quarter of record-breaking sales on Wednesday. Let's hear it for them.
1:04:22
revenue reached 44 billion for its first fiscal quarter, a 69% increase that was curtailed by Washington's new limit new limits on Chinese chip sales.
1:04:30
The company was unable to ship 2.
1:04:32
5 billion of its H20 processors and projected 8 billion in lost revenue for the current quarter due to the policy.
1:04:40
So you lose a flesh wound, John, you lose 8 billion in revenue, which is high margin revenue, too.
1:04:46
It's this is not we're not talking Amazon here.
1:04:48
and um and you still put up 44 billion and your stock goes up 5%. It's fantastic.
1:04:53
Uh Nvidia's longerterm outlook in China remains a major question mark.
1:04:57
The company admitted on Wednesday that has limited the significant thing here.
1:05:00
Nvidia surpassed Meta in quarterly revenue. Yeah. Wow. That's insane. Insane. Yeah. Um Yeah.
1:05:10
And I mean uh yeah, absolute dominance of the Nvidia CUDA ecosystem.
1:05:16
ecosystem. the number of developers on Nvidia uh has been surging as we saw in Mary Maker's trends report and the company seems very very wellrun at the same time Dylan Patel George hot putting the screws to ARM ARM seems to be uh or AMD seems to be catching up seems to be taking that feedback and trying to solve
1:05:36
some of the problems that have been keeping developers off of that platform even though the cost per flop has been quite good on AMD the ecosystem hasn't been quite there um but obviously everyone there is is, you know, well aware of the opportunity of of of uh taking a little bit of of Nvidia's market share. And so, um, uh, this is an
1:05:52
And so, um, uh, this is an interesting takeaway.
1:05:55
Uh, Nvidia credit its new Blackwell gaming processors, part of the same family as its current lineup of a of AI chips that are seeing red-hot demand.
1:06:03
Blackwell for gaming is a home run.
1:06:05
Nvidia CFO Colette Crest said in an interview uh for the current quarter, Nvidia projected revenue of 45 billion plus or minus 2% compared with analyst view of 45. 84 billion.
1:06:16
The company expects meaningful decrease in data center revenue from China as a result of the H20 ban.
1:06:21
And so uh this is the interesting takeaway from Ben Thompson's post earnings analysis.
1:06:26
Um so he said he he is really focused on the difference between uh the the the transition from training buildouts to inference because training we've seen the scaling law there.
1:06:40
you kind of know, you know, the the race to do get to build a 20k cluster to a 100k cluster.
1:06:44
And that's pretty um it's pretty easy to forecast because uh the CEO of a foundation model company comes out and says we're going to build a 100k cluster and you know they're going to buy that many GPUs, right?
1:06:58
But uh the inference is much more consumer demandbased and and it's always unclear.
1:07:03
These products seem great, but how are they actually going to get installed?
1:07:06
How many tokens are they actually going to be uh generating?
1:07:07
And then and then what is the trade-off within those tokens of reasoning and and heavy test time inference workloads versus uh more more like lower lower volume workloads.
1:07:19
Um and so uh Ben Thompson says last year I expressed concern that inference workloads were not increasing as a proportion of NVIDIA sales.
1:07:27
So he says it's worth noting though that while the company reported that 40% of its chips were used for inference that is the same percentage as last quarter. So keep that in mind.
1:07:34
40% of NVIDIA chips are used for inference. It's 60% training.
1:07:39
I I think that's the breakdown when when he's talking about AI specifically.
1:07:43
Granted, that is a large increase in absolute terms.
1:07:45
Uh by and large, matching Nvidia's and and uh revenue increase.
1:07:49
Um and of course, training large models requires ever more GPUs, but the arrival of meaningful AI workloads will be marked by an increasing percentage of chips being used for inference, assuming, of course, that inference workloads will be run on NVIDIA chips.
1:08:04
NVIDIA chips. And there was always a question of like maybe you train the model on a big NVIDIA cluster and then you bake it down so small that it runs on the iPhone locally or it runs on a CPU or it runs I mean unlikely that that would ever happen but uh but people have been able to distill models down so far
1:08:19
that you can inference them on other on other chips that might be more affordable but that really hasn't happened because of the CUDA CUDA ecosystem and it feels like in general most of the inference has stayed with Nvidia and we see that in the earnings but yeah now you have the TPU and then Meta's Artemis. Yep. And and so Amazon Yep.
1:08:33
And and so Amazon has has uh tranium and inferentia.
1:08:36
So they have a training chip and an inferencing chip and an inference chip.
1:08:41
There's different I think it's inferentia, but um but both of those are are are in-house chips, but um for most companies, they're training and inferencing on NVIDIA.
1:08:50
And so uh on the latest Nvidia earnings call, Jensen Wong and Klet Crest, the CEO and CFO of Nvidia were adamant that workloads for inference were skyrocketing.
1:09:00
And here are a couple quotes that Ben Thompson highlights.
1:09:04
AI workloads have transitioned strongly to inference and AI factory buildouts are driving significant revenue.
1:09:10
This is from Colette Crest.
1:09:12
And so I think we we were we were kind of asking the question of AI factories.
1:09:17
Is that just some buzzword?
1:09:19
Are we is there a distinction there?
1:09:21
And what's and what I'm hearing there is the start of AI factory means more data center.
1:09:28
That's more that's more producing intelligence. Exactly.
1:09:31
It's more inference focused. Yeah. Data center design. Yeah.
1:09:35
Which I think there are specific trade-offs that you would need because you don't necessarily need to run the same code over the entire data center.
1:09:44
You can you can shard it up a little bit more because one inference job can be done on the single rack and so maybe linking all the racks together is not as important potentially.
1:09:52
I don't know enough about how training. You were right.
1:09:56
By the way, a Amazon's in-house AI chips are called AWS Tranium and AWS Inferentia. Let's go.
1:10:01
Let's hear it for my memory. Yeah, still got it. Golden retriever mode. Yeah.
1:10:06
Uh, Colette Crest went on to say, "We are witnessing a sharp jump in inference demand.
1:10:10
OpenAI, Microsoft, and Google are seeing step function leap in token generation, which we saw from that Sachin Nadella quote.
1:10:18
Microsoft processed over 100 trillion tokens in Q1, a five-fold increase over on on a year-over-year basis.
1:10:24
And so she's now quoting Satcha talking about uh token uh token increases.
1:10:28
Uh Wong says reasoning is a is compute intensive requires hundreds to thousands of times more tokens per task than previous oneshot inference.
1:10:38
Obviously the difference between 40 oneshotting something and deep research which sits there generating tokens for 20 minutes. Wildly different.
1:10:46
Reasoning models are driving step function surge and inference demand.
1:10:49
AI scaling laws remain firmly intact not only for training but now inference 2 requires massive scale compute.
1:10:57
Uh Wong goes on and says the first positive surprise is the step function demand in increase in reasoning AI.
1:11:03
I think it's fairly clear now that AI is going through an exponential growth phase and reasoning AI really busted through concerns about hallucination or its ability to resol really resol really solve problems and I think that a lot of people are crossing that barrier in realizing how incredibly a effective agentic AI is and reasoning AI is.
1:11:21
So the number one so number one is inference reasoning and the exponential growth there demand growth.
1:11:28
Um, and so Ben goes on to say that is this is all great news for Nvidia specifically and AI generally, but what was missing was an update on that percentage of chips used number.
1:11:38
It certainly sounds like it's more than 40%, but it would have been nice to receive concrete information that that that number has in fact increased.
1:11:48
And so I don't know how we get that information.
1:11:52
I we we're talking to Dylan Patel on Friday.
1:11:55
we can kind of see if he has a way or a methodology to try and figure that out.
1:11:59
Uh but that does seem like a very very interesting question to ask.
1:12:03
It might be it might just be too soon to really be shifting.
1:12:05
But maybe the plan for the next data center and the order hasn't hit Nvidia yet will be more inference focused and we and we could see a boom in and we could see a shift in that number and maybe it just hasn't shifted yet in in Q1 revenue.
1:12:19
But it's totally possible that Jensen has visibility into Q2, Q3, Q4 orders. Yeah.
1:12:27
And sees that demand is going to go crazy for inference specifically.
1:12:29
We're going to be looking at 10% training, 90% inference.
1:12:34
But he can't say that yet because the orders haven't actually been placed and he's only looking backwards.
1:12:40
So he's trying to kind of like, you know, message that influence is picking up.
1:12:44
You can see a bunch of public data points from Satcha talking about this, but uh but nothing to report on the actual order side just yet. Yeah.
1:12:50
And so he doesn't want to send the message that it's not moving because then people be like, "Well, maybe it'll never move." So I I don't know.
1:12:56
That's my that's my reading on that. Anyway, that's right.
1:12:59
Uh let's go into Nvidia's China argument.
1:13:00
Um, so the upside surprise for investors is that Nvidia is growing just fine without selling to China.
1:13:05
Although, uh, again, although Ben Thompson says, "I'm sure I'm not sure this is a surprise.
1:13:11
Nvidia's sales have not been gated by demand, but by supply for a while."
1:13:14
Were you making this exact statement last year? I got it from Alex Wang. Yeah.
1:13:18
Wang. Yeah. Why do we need to sell to China at all when there is effectively there at Larry Ellison and and Elon Musk are getting dinner with Jensen saying we will buy as many GPUs as you can produce like they are good for the deal like you you you can just
1:13:35
sell to them but of course uh if you're a global company like there isn't there is a shareholder responsibility to have some diversity of revenue and then there's also that interesting argument of is there value to be dependent on Yes, American. Yeah, we I mean I mean
1:13:49
Yeah, we I mean I mean the hypocritical thing here is that we you know I'm I'm sure we have said hey uh you know it's not fair that Tik Tok operates here while Facebook operate while Facebook can't operate there.
1:13:59
Well now what what would we be talking about right now if Facebook was actually in China operating?
1:14:06
Would we be like they shouldn't be like it's it's a powerful tool. It's beneficial. Google is there.
1:14:11
That's a beneficial tool. Why are we helping them?
1:14:14
So, like we're in this weird dynamic where where you can't you can't you can't say both, right?
1:14:18
You can't say it's wrong that it's wrong that that uh companies are banned in China.
1:14:23
American companies are banned in China, but also the ones that aren't banned should like selfban when in fact most most American companies for a long time have.
1:14:30
But this is all part of like the shifting narrative and the shifting geopolitical equation. So, it is unclear.
1:14:34
Ben goes into the timeline.
1:14:37
Uh somebody's quoting a post from the Financial Times.
1:14:39
Jensen saying, "Four years ago, Nvidia had 95% market share in China. Today, it is only 50%."
1:14:46
The CEO said, criticizing the curbs for spurring rivals such as Huawei to develop their own AI products.
1:14:53
Balding's World says, "This has been the story of every CEO that has gone to China.
1:14:57
How do these I'm not going to say that.
1:15:01
How do these guys not get this story yet?
1:15:02
I won't even say I won't call a big tech CEO an idiot. I just won't.
1:15:07
Yeah, it's disrespectful. I can't do it."
1:15:09
Um um anyway, so uh Ben says, "What I believe Balding is referring to is the pattern in which a multinational moves manufacturing to China at the cost of a joint venture or technology transfer only to see their market share competed away by Chinese competitors benefiting from their technology."
1:15:23
This is of course the exact opposite of what is happening to Nvidia.
1:15:27
The company's market share in China is falling because of the US government's export controls, not because of Chinese government policy.
1:15:36
Is that what is that fully true? I think so.
1:15:39
You don't think competition has a fact is is is factoring in there at all? No. No. No.
1:15:44
I mean, because if you look at the cost per flop, uh Huawei Ascend is more expensive on a per cycle basis.
1:15:51
And so, if it was a truly free market, you wouldn't see nearly as much demand for that.
1:15:55
And also, in the same way that demand for GP is uncapped in America, it's uncapped in China.
1:16:00
Like, they want to build a 100,000 cluster right now.
1:16:04
They would if they could.
1:16:04
Yeah, but I'm sure in a supply constrained market that would naturally help other upstarts get market share even if they're selling an inferior product.
1:16:13
But if customers can't access like you'd rather have a Huawei GPU than no GPUs at all, right? Yeah. Yeah. Yeah. Totally.
1:16:21
Moreover, unlike the vast majority of other product categories, one would in fact expect Nvidia to maintain its market share if it were able to compete.
1:16:28
The difference, of course, is software.
1:16:29
Nvidia chips are not just about GPUs, but about the CUDA software layer, which has network effects.
1:16:34
Nvidia not only has the best performing chips on the market, matched at times in pure performance by AMD, they also by far have the largest ecosystem of software and developers, which makes them the first choice for everyone if you can buy them.
1:16:46
Wong's argument is that not only does Nvidia want to sell to China, but the US should want him to sell to China, too, from the call.
1:16:54
This is a tough argument to make, but you know, let's hear him out.
1:16:56
He says, "China's AI moves on with or without US chips.
1:17:01
It has to compete to train and deploy advanced models.
1:17:03
The question is whether China will have AI. It already does."
1:17:08
The question is not whether China or whether or not China will have AI. It already does.
1:17:12
The question is whether one of the world's largest AI markets will run on American platforms.
1:17:17
Shielding Chinese chip makers from US competition only strengthens them broad and weakens America's position.
1:17:22
Export restrictions have spurred China's innovation and scale.
1:17:27
The AI race is not just about chips.
1:17:29
It's about which stack the world runs on.
1:17:31
As that stack grows to include 6G and quantum, US global infrastructure leadership is at stake.
1:17:36
And yeah, it's interesting like is like the the control over Facebook was so strong that because there's network effect but also all of the data is run on Facebook servers that Facebook really has an insane amount of control when you hand over a GPU.
1:17:57
Obviously there are there are some value to the ecosystem and the lock in but you can kind of do whatever you want with it because it's hardware and you're not maintaining the software and gating access.
1:18:08
So there is something there there is something different there but but I but I I do take his point and so uh Ben Thompson goes on to say it's it seems clearly in America's interest for China to have a dependency on US software on a US software platform.
1:18:20
Then again, it also seems to be in the in the in in America's interest to have China dependent on Taiwan for chips, but that argument is not winning the day either.
1:18:31
Um, this uh this article goes on and is great and you should subscribe to uh to get the full thing.
1:18:36
Um, anyway, we we should uh go to this uh this Bloomberg piece that uh Ben highlights a little bit.
1:18:43
Um, Nvidia's open ecosystem to rival chipmakers is in global push opening AI ecosystem to these chipmakers. Yeah. So, Nvidia Corp.
1:18:49
Chief Executive Officer Jensen Wong outlined plans to let customers deploy rival chips and data centers built around its technology.
1:18:59
A move that acknowledges the growth of in-house semiconductor deploy development by major clients such as Microsoft and Amazon.
1:19:04
Uh on Monday, Wong kicked off Computex in Taiwan, Asia's biggest electronics forum, dedicating much of his nearly two-hour presentation to celebrating the work of local supply chain partners.
1:19:16
Gong for twohour presentation.
1:19:18
Oh, it sounds crazy the fact that he's going and opening up this conference and giving a two-hour presentation. Pretty awesome.
1:19:23
But then I remember we we come up here and do three times a day. Every day.
1:19:27
You should come do the show with us sometime. Do the whole show. Let's do the whole show.
1:19:32
Imagine imagine ripping some timeline with Jensen. We'll make it happen. It'd be electric.
1:19:37
Uh but his key announcement was the new NVL link fusion system that allows the building of more customized artificial intelligence infrastructure combining NVIDIA's high-speed links with semiconductors from other providers for the first time.
1:19:52
And so this is a little bit of what we're seeing where there's now um chip startups that are building chips for specific uh for specific you know use cases.
1:20:03
So an example would be like etched.
1:20:05
They're bake they're baking the transformer architecture down onto silicon.
1:20:08
But you could even look at um Apple silicon as something that might benefit from the NVL link fusion system potentially.
1:20:16
I don't know if it's saying hey we know you hyperscalers are building your own chips.
1:20:20
We still want you to be dependent on our software even if you're going to ecosystem. Yep.
1:20:24
And so to date Nvidia has only offered complete computer systems built with its own components.
1:20:30
So you buy the all the chips and all the racks and everything wires together very nicely and that is very important for uh data interchange and especially while you're training.
1:20:38
Um this change gives data center customers more flexibility and allows a measure of competition while still keeping Nvidia technology at the center.
1:20:46
NVLink Fusion products will provide customers the option to use their own central processing units with Nvidia's AI chips.
1:20:54
Their CPUs now pair with Nvidia's GPUs or pair Nvidia silicon with another company's AI accelerator.
1:20:59
So you could kind of do the inverse and bring bring up a specific accelerator for a specific use case.
1:21:06
Um Santa Clara uh Californiabased Nvidia.
1:21:09
They love to throw in the location of these companies. It's very funny.
1:21:13
Uh everybody associates Nvidia with Santa Clara.
1:21:16
I guess they're trying to shore up its place at the heart of the AI boom and keep the surge going in the face of concern that spending on data centers isn't sustainable.
1:21:25
isn't sustainable. The company relies heavily on a select group of giant cloud providers known as hyperscalers for much of the revenue and all of those uh hyperscalers are of course um thinking about uh building their own chips because if they're going to be ordering so many the margins are so high why not
1:21:41
just go to uh TSMC directly and so uh this bit of news this is back to Ben Thompson this bit of news from PEX two weeks ago is a reminder that CUDA isn't Nvidia's only moat the company is also dominant in networking particularly the link the ability to link multiple chips together so that they function as a single large chip. The key to this is so
1:21:59
The key to this is so to this so-called scale up capability is NV link and so Nvidia will license its chip to chip C2C technology to enable custom configurations.
1:22:10
For example, Grace Hopper was an Nvidia ARM CPU and an Nvidia Hopper GPU.
1:22:15
Oh, I didn't realize that.
1:22:18
Grace Blackwell is an Nvidia ARM CPU and two Nvidia Blackwell GPUs.
1:22:23
If you don't want that configuration, you're out of luck or at least you were because now you can license Nvidia's COC technology and license seems important there.
1:22:31
Um, to make any number of combinations and it doesn't have to be Nvidia chips that are being combined, although Nvidia is obviously confident that you'll choose their GPUs because yes, they are the best in the business. Uh, fascinating.
1:22:44
Anyway, um we should move on to this Nike story in the information because there's a very very interesting chart again from Ben Thompson that I thought everyone should be thinking about in any of their business.
1:22:55
So, uh the big news is uh this is from the information in May 2020 uh May 21st.
1:23:00
So, it's a little bit of an older article, but Nike announced that they are going to sell on Amazon for the first time since two uh since uh 2019.
1:23:09
So, it's been six years off.
1:23:12
So, uh six years ago all in on D TOC. Yeah.
1:23:15
They really got the DTOC bug.
1:23:17
They did and they said they they read the thought pieces.
1:23:19
They read the newsletters. Cut out the middleman. Yeah.
1:23:23
They they wanted they they were pissed at the middleman. Yep.
1:23:24
They tried to cut him out and now they're making a deal with the middleman.
1:23:29
And so, uh, six years after Nike stopped selling through Amazon in favor of going direct to customers through its own stores and websites, the two companies are getting back together.
1:23:38
I'm sure it was super rough because tons of people probably went to Amazon every day, typed in Nike and just got Nike knockoffs, right?
1:23:45
Because you're just used to buying on Amazon.
1:23:46
Uh, Amazon plans to start selling Nike products with supplies coming directly from the company.
1:23:50
An Amazon spokesperson confirmed Wednesday, winning back one of the world's best known brands as a victory from Amazon uh for Amazon, which has long tried to expand its fashion business by wooing skeptical brands.
1:24:01
Nike's deal with Amazon, meanwhile, comes as the sneaker maker is trying to revive slumping sales.
1:24:06
So, Amazon is going to buy Nike for uh buy from Nike for the first time since 2019.
1:24:11
Um, and this is uh this is all an effort to revive slumping sales.
1:24:16
Now, um uh Nike's revenue is down a ton.
1:24:21
Uh in the most recent quarter, it fell to 11.
1:24:22
3 billion, down 9% from the same period a year earlier, while wholesale revenue fell 7% to 6. 2 billion.
1:24:28
Uh, and so Ben Thompson calls this Nike's disastrous pivot.
1:24:35
Uh, he says there's a lot that has been written by Nike struggles over the last few years.
1:24:39
Um, uh, including a LinkedIn post by former Nike executive uh, and there and and he he outlines three key mistakes here.
1:24:48
The elimination of categories like running, basketball, etc.
1:24:54
A massive dep prioritization of wholesale in favor of direct to consumer sales.
1:24:58
And a shift away from brand market direct sponsor to avoid middlemen and business is rough.
1:25:04
It's like, oh, we're going to have owned we're going to have we're going to have our own retail stores and it's like, okay, well, you have a landlord. Yep.
1:25:12
So, he's your middleman now.
1:25:12
Y and so, uh, yeah, the middle selling online. Okay, welcome. Meet Mark Zuckerberg.
1:25:19
He's gonna be your new middleman.
1:25:19
It's like trying to avoid the middleman is yeah, very difficult, right?
1:25:24
And it's interesting because uh the middleman analogy has actually worked just fine.
1:25:32
And Ben Thompson has this cool chart of the CPG value chain and shows that Proctor and Gamble literally does not cut out the middleman.
1:25:40
In fact, they leverage the middleman and they're and they're doing fine.
1:25:44
So what does Proctor and Gamble do?
1:25:46
They do research and development and they do manufacturing, but they don't handle the middleman.
1:25:50
So they don't handle logistics or retail but they dominate shelf space and with trade marketing and then marketing like brand marketing and so CBG companies like PNG harvested most of the value by integrating research and development, manufacturing, marketing and shelf space, raw materials, retail and logistics were modularized and commoditized.
1:26:10
DTOC companies meanwhile saw research and development as increasingly unnecessary in overserved markets.
1:26:16
As I noted in the context of Dollar Shave Club, razors are a particularly salient example of overserving.
1:26:22
Um, and shelf space on the internet was effectively in infinite.
1:26:27
Their goal was to integrate marketing, retail, and manufacturing.
1:26:29
And so the theoretical, if you scroll down, the the theoretical DTOC value chain is no R&D, just manufacturing, no logistics, but yes, retail.
1:26:40
You don't have shelf space, but you do the marketing.
1:26:42
And so Ben Thompson says the the the problem though is that marketing on the internet was inherent was entirely different than the analog marketing that previously dominated the CBG industry.
1:26:52
They their being good at advertising whether it be coupons in the Sunday paper or television ads during the evening news was mostly a matter of the ability to spend which was itself a matter of scale.
1:27:04
Digital marketing though didn't really work at uh at scale at least relative to TV.
1:27:08
In fact, it only made sense if you could target consumers with advertising and track how it performed.
1:27:14
On the one hand, this was a critical factor for making DTOC companies viable.
1:27:18
The advantage of targeted advertising is that it takes a lot less money relative to to TV to reach customers who are actually interested in your product.
1:27:25
The problem though is that getting good at targeted advertising requires massive amounts of both research and development to build the capability and inventory across a sufficiently large customer base to make the whole effort worthwhile.
1:27:37
In the end, no DTOC company was actually good at marketing.
1:27:39
They outsourced it to Google and Facebook, which both had the inventory and the capability to spend billions necessary to develop sophisticated targeted advertising.
1:27:47
Uh the problem is that in the process of depending on Google and Facebook for marketing, the DTOC companies gave up their planned integration in the value chain and the associated profits to Facebook and Google.
1:27:57
And so the actual DTOC value chain is they're not a manufacturer. They don't do retail. They don't do logistics. They don't do marketing.
1:28:04
instead they just do R&D and adv ad inventory and and and so the actual customer is just completely owned by Facebook and that's why you see a lot of DTOC uh companies that have really really struggled.
1:28:13
Um so the actual integrated players Google and Facebook integrate customers and research and development to dominate marketing DTOC may have online retail operations but that is a modularized and thus commoditized part of the value chain.
1:28:26
Uh and uh oh yeah, he he called out brand list, the the the DTOC kind of like roll up that had a whole bunch of products and uh and he said here's the problem for DTOC companies.
1:28:37
Facebook is really better at finding them customers than anyone else.
1:28:40
That means the best return on investment for acquiring customers is on Facebook where DTOC companies are competing against all the other DTOC companies and the mobile de and the mobile game developers and the incumbent CBG companies and everyone else for user attention.
1:28:54
That means the real winner is Facebook.
1:28:56
While DTOC companies are slowly choked by everinccreasing customer acquisition costs, Facebook is the company that makes the space work.
1:29:03
And so it's only natural that Facebook is harvesting most of the dynamic where Meta is incentivized to uh make uh customer acquisition like basically extract as much of the profit from the ecosystem as possible without putting the companies out of business. Yeah. Right.
1:29:21
And so it's this infinite dance. Yeah.
1:29:23
I mean that that's actually a very simple equation.
1:29:25
It's take all the net profits but not any further. Yeah.
1:29:30
So that the company can continue to go but the equity value is effectively zero.
1:29:34
And this is why when when Sean from Ridge was on the show one or two times ago, we were talking about how uh historically I've seen DTOC brands benefit from net new platforms.
1:29:47
Like a lot of brands exploded from cheap advertising on Tik Tok, right?
1:29:49
if um you know it seems like LLMs are an interesting new acquisition channel, still relatively small channel for a lot of brands, but it's possible when ads hit LLMs that they're cheaper and that that could drive, you know, a a period of of where brands say, "Hey, let's like shift a bunch of spend over here because it's, you know, really efficient." Um but who knows?
1:30:12
Um Facebook is still the best marketing channel in the history of it's the second best.
1:30:18
In fact, the number one obviously ad out of home advertising made easy and measurable.
1:30:24
Say goodbye inbound to the headaches of out of home advertising.
1:30:26
Only adqu combines technology out of home expertise and data to enable efficient seamless ad buying across the globe.
1:30:30
But seriously, like Nike is the king of billboards.
1:30:34
Like yeah, they really are. I mean, they used to be. They used to be. They used to be.
1:30:36
And the billboards were fantastic.
1:30:38
And everyone remembers a Nike billboard.
1:30:40
No one remembers a Nike direct response ad on Instagram. Yeah.
1:30:43
Like I'm sure people clicked on them and I'm sure they drove some sales, but the economic equation just didn't quite work. Yeah.
1:30:48
Well, we walked by some billboards today that are funny.
1:30:51
There is a huge billboard campaign across LA called Just Blood, talking about uh basically it's a campaign to prove that Elizabeth Holmes is innocent.
1:31:04
So, there are effectively uh I think there there's got to be 20 billboards up around LA.
1:31:12
Uh so, I'm interested to follow along with this campaign. If you go to justblood.
1:31:17
com, it's quite a lot of AI generated assets.
1:31:22
Um, and it seems it's kind of an angry website, but I'm interested to dive deeper there.
1:31:27
Going back to some of Nike's errors, the they dep prioritized wholesale.
1:31:34
And then the big one was a shift away from brand marketing to direct response marketing.
1:31:39
So when people think about why they love Nike, maybe sometimes it's about the product, but a big part of it is how the Nike brand has made them feel over time.
1:31:48
And it's really hard to make people emotional through direct response advertising because direct response advertising is like problem solution.
1:31:56
Y it's not about the emotion. Yeah.
1:31:59
And when I think about the moments in my life where I've where I've paid attention to Nike and, you know, been made made to feel anything by Nike, it was these sort of bigger brand campaigns.
1:32:11
And brand marketing does provide a halo effect that can reduce overall customer acquisition costs because if you see some Nike campaign that inspires you or makes you emotional and then you see a direct response ad later, you're more inclined to actually click through.
1:32:27
And so, um, big miss by, uh, John Dano, uh, to just sort of not realize that so much of Nike's dominance was around the brand.
1:32:36
The other thing is like, you know, you look at these upstart players and apparel, things like Vary, Aloe, Lululemon, they're all, you know, we talked about this on the show before, Nike missed wellness, right?
1:32:50
They missed this trend that a huge amount of the population, people, you know, consumers with um a lot of discretionary income stopped seeing themselves as athletes and started seeing themselves as, you know, yogis, people that meditate, people that eat healthy but don't necessarily see themselves as I'm an athlete.
1:33:08
So, big miss um that I I believe they're still trying to actually get tapped into, but yeah.
1:33:16
Well, it seems like they're they're pivoting back to uh the more traditional strategy and probably we'll see some refocusing on brand marketing because they'll just be everywhere and they won't they won't try and cut out the middleman anymore.
1:33:28
Just be everywhere and hopefully we'll see some amazing Nike ads coming up soon.
1:33:32
Anyway, uh we have our first guest of the show, Doug Filipon from Snow Point Adventures joining us.
1:33:38
I'll let you take the intro. I'll be right back.
1:33:39
Uh Doug, how are you doing today?
1:33:43
Um let's bring him in here.
1:33:43
Uh I'll give a little bit of background on Doug in the meantime.
1:33:48
Uh he has a degree from West Point, spent 17 years in the military and then another 17 years at Palunteer uh building the defense business from nothing into a global defense lead.
1:33:57
So we're excited to talk to him about that and uh it'll be very interesting to cover the Ukraine drone attack which we talked a little bit about yesterday.
1:34:06
Um but uh there's a lot more that we can dig into there.
1:34:09
So Doug, how are you doing today? Great. Thanks for having me.
1:34:12
Thanks so much for joining.
1:34:14
Um, I'd love to kick it off with just a little bit of your background first and then we can go into the the the the latest news uh in Ukraine. Yeah. No, that's great. Um, yeah.
1:34:24
So, what Well, I've been on a life journey. I'm uh I've done a lot.
1:34:28
It everything has been hard.
1:34:33
I think just about everything that I've done in my life, people have told me I couldn't do it.
1:34:36
Uh, and I sort of thrive in that world. That's awesome.
1:34:38
That's always the case, right? Yeah.
1:34:40
Well, look, nothing nothing worth doing is, you know, is easy. Um, yeah.
1:34:44
No, I think when I was a young man, I was just um I went to college for just a minute and then I was like, "This is stupid.
1:34:50
I'm in the hamster wheel."
1:34:52
Uh, and I said I wanted to join the army.
1:34:54
I went into the Rangers as a guy and then, you know, got into West Point a little bit later.
1:34:58
Um, while I was there, I studied math.
1:35:00
All my friends made fun of me.
1:35:02
They're like, "What are you going to do with math?"
1:35:06
And, uh, uh, I definitely got the last laugh there. That's amazing.
1:35:10
Were they just saying like like computer nerd type jokes or?
1:35:15
No, it was just like I mean basically you got to remember I'm a little bit older, but I u in the 90s it was like it was before the modern internet era and so forth.
1:35:23
And so um you know computer science was like a hobby more than a real thing.
1:35:27
You know the internet, you know, was just coming out while I was in school.
1:35:30
And so it was um it was just like the idea of like you're going to be a high school math teacher and that's like the that's the end of what math is for.
1:35:38
And so look at my focus was I'm going to go be an army officer.
1:35:42
I'm going to go back in the Rangers and that's going to be my career.
1:35:45
But you know I did six tours in the war and got hurt. Wow.
1:35:47
And so um you know at that point I went back to grad school and then found a job in the very early days of Palunteer.
1:35:55
And literally like the only reason I got hired was they were trying to start their defense business and um they sort of thought that like a a terrace hunter mathematician was a really cool thing. Yeah.
1:36:07
Uh, I sort of found like the the perfect first job. Um, yeah.
1:36:09
How did uh walk me through how you actually met the Palunteer folks?
1:36:14
What was the first day on the job like?
1:36:16
Who was around the table? Was Sean Sangar there? Who else? Yeah. No, it was fascinating.
1:36:21
So, um, so back in the day, it used to be carp, you know, it's like maybe 50 people there, you know, they really had a product.
1:36:26
But the interesting thing, so one of my very best childhood friends, uh, Dan Cervelli, he was one of the best engineers at Palunteer, period.
1:36:33
Um he was like a alternative student.
1:36:36
I say alternative he's like older getting his bachelors when he was like 32 or something. Yeah.
1:36:41
Um, and he was he was interviewing at Facebook and Palunteer and he's like, "Doug, you got to see this.
1:36:47
Uh, you got to come over and uh and then he had just joined."
1:36:50
And so when I saw like the first demo, even though it was all intel-based, um, it was very clear.
1:36:56
I just went back to my time as a commander in the Rangers, it was just I was just I was convinced that if I had this, I could have done everything better.
1:37:05
And I and I really was, you know, a lot of my friends were still going back to the war and getting wounded or killed.
1:37:10
and getting wounded or killed. And so it was just for me it was about purpose you know I think you probably you probably know a lot of palenture people but we're all like in this you know strange family that is Palunteer um everyone is uniquely driven for a sense of purpose
1:37:28
and for me it was like I wanted to do something where I could give back and if I you know if I'm honest if I would have stayed in versus obviously I was hurt so it didn't matter but like I have easily contributed a thousand times what I would have if I just stayed in towards the you know towards towards the mission. So I feel quite proud of that.
1:37:45
So I feel quite proud of that.
1:37:47
So so while you were in the service and you see what Palunteer can do, could you give us a more concrete example of like what you're thinking?
1:37:54
I mean I I often give there there's a little bit of a meme online like what does Palanteer actually do?
1:37:59
And the and the and the example that I often give is like uh think about if there's IEDs all over the place.
1:38:06
Some of those IEDs are going to have C4, some of them are going to have nails.
1:38:09
And if you put those all on a map, you can decide you can start to see clusters of trends just on a map.
1:38:12
And then you can decide, okay, there's a bomb maker in this town.
1:38:16
We should go and investigate that.
1:38:18
Um, that's the most concrete example I've been able to come up with that I've read just from the literature.
1:38:23
But as someone who was there, what what was I mean, that's definitely like the that would be the 2010 version. Sure.
1:38:27
You know, just sort of like, you know, at the core, it's like um they make a software architecture that helps combine a myriad of data systems.
1:38:38
So like all these legacy systems, if you think of the defense world, all these different uh areas, whether it's commercial uh businesses or the military, uh the larger they are, the more that they all look the same.
1:38:50
The military might be the most like complex, but it's all similar in the sense that you have a myriad of legacy technology that's uh built and modeled around information capabilities at a certain time.
1:39:02
And over the course of history, it's like hard to get rid of those old systems.
1:39:05
So if you look at the IT infrastructure of the Department of Defense, it's like you have old mainframes on one end that's modeled certain things, you know, on the edge and then you have like the most exquisite AI sensor that's doing real-time data and computer vision on the other end.
1:39:21
And as a commander, what you're trying to do is um assimilate the real world in real time.
1:39:26
So, it's like you're you're looking at a map.
1:39:28
You're looking at all of your feeds from either videos or satellite footage to understand what's going on, what's changing, and then if you're ever going to go um like to understand what's going on in the real world.
1:39:38
So, you're understanding things and you're making decisions based off that data that you might have to go without Palunteer, you have to go 100 different places.
1:39:45
So that was like the existing paradigm that we were replacing is how do you um if if you an old school analyst or an operator would have to literally go individually search 100 different systems and use an individual tool for each one of those systems that may or may not be good and then they would put all that stuff in their mind and they would write it back on PowerPoint and then that's how and you'd have no legacy search and discovery.
1:40:12
you would be violating all of the like handling of the data.
1:40:14
You lose all this the security of it and it's just like on a flat file and you're emailing around.
1:40:20
I can't tell you like how long that was the paradigm of the military and most corporations.
1:40:25
Can you can you talk about the practical challenges of that?
1:40:28
There's this concept of the fog of war and I imagine you experienced this on your different tours where you have a bunch of data but parsing through it and fully understanding and I can imagine in many ways Palunteer I if you can more quickly and accurately process information from more sources.
1:40:49
you can reduce that sense of of sort of unknowing that that seems to be historically, you know, uh common across every different type of battlefield. Yeah.
1:41:00
No, I mean the short answer is like it will save your life and you can have a successful mission or not.
1:41:06
not. I mean the the uh historic vignettes that are like pretty powerful for regular people to understand is like um as the military would plan a mission to go in and out like forget about the real-time stuff that is obviously very relevant of just like knowing what's going on and how strategic things are moving around and if someone's attacking you like you have to have that side of
1:41:26
it which Paler does a lot of but like from a historic perspective once you're planning a mission to be able to understand the full history if you're staring at a piece of dirt or you have like, hey, we we think the bad guys are at this compound or there's a military a legitimate military target that you're going to strike to understand the whole corpus of data that you may know about that for the last 10 years. So to give
1:41:48
that for the last 10 years. So to give an example of like you know the failures of um the Afghan war or Iraq for that matter just using the American experience you can do this just about any war is that you know as units would go in and out of a region you would have
1:42:07
these like learning experiences that would last 3 to six to 12 months and then they would at best they would put all the information that they learned whether it's like say so say I went on a mission I interviewed somebody and I I I took fingerprints I took pictures. I
1:42:19
I would write a little note that say here's the here's the human terrain of this area.
1:42:25
This is what the people care about. Here are the projects.
1:42:27
Y um here's where we did a mission.
1:42:30
You know, they usually do an affforction mission report about it. Yeah.
1:42:33
And you would put on a hard drive and then the new commander would come in and you hand it to them and then they would probably look at it for two seconds and then I mean that's literally how it was done for 20 years. Yeah.
1:42:41
for 20 years. Yeah. and you're just you want you're like how can this with with all of our might and all of our superiority in every way and the money that we're throwing at this why does it suck so bad anyway so that was you know Palanteer's mission was to like
1:42:55
how do we change that paradigm so that you know the interesting thing if I give a one of the compelling things so we did this with the British um you know with with u I don't even know if I'm allowed to say this but think of their most sexy unit the Brits and they were they were going into um a specific area. And what they didn't
1:43:13
And what they didn't realize over the past five years, they had every time they flew a helicopter into a region, you know, they have this host of analysts that are like they work with the helicopter pilots and they do menstruated graphics so they understand the exact perfect helicopter landing zone for the mission. Mhm.
1:43:31
And what they didn't realize was that each new team would come in and they would always do their expert analysis and they'd always pick the same exact place.
1:43:42
And so then all of a sudden when we integrated all this data for them, they saw for the first time, holy cow, every single time for the last 5 years that we've gone into this valley, we always landed in the same place.
1:43:51
So it ends up being like a very easy low tech thing for the enemy to put a bomb at the middle of the HLZ.
1:43:57
And they're like, "Anytime Americans come, just blow up the bomb."
1:44:00
Um, but that's like uh they call that knowledge management which is like that's a little bit old school but it's like that was a very unsolved problem forever.
1:44:08
And then now if you get to like real time what we're doing now it's like okay well now you're taking real time signals intelligence.
1:44:17
You're taking real-time video feeds where you're overlaying what the video of the surveillance aircraft would be looking at and then with the entire corpus of information you would know about the area.
1:44:26
So as soon as you're looking at a piece of ground, you're like 10 10 reports pop up of everything you know about us.
1:44:32
So you immediately have situational awareness that'll help say help you stay alive. That's really important.
1:44:38
Can you tell us the story of uh DIGs and the distributed common ground system like how that played out and like the law to any at any level of detail that you think is appropriate? Yeah. No, no, no.
1:44:49
I mean look that was my personal Vietnam except for I won so it's like it's okay. It's not. Congratulations. Yeah.
1:44:56
Think of a different long war that that somebody won and all and that'll be it.
1:45:00
But it was like 10 years of my life. Wow. 10 years. Yeah. No, it was it was wild.
1:45:04
And I will tell you that there was a lot of times when I just didn't think we win.
1:45:07
I literally flew up to New York one time and and rode in the car with Dr.
1:45:11
Karp and I was like, "Sir, do you still want me to do this?"
1:45:19
you know, because it's like I don't know if there's like any amount of hard work or expertise that is going to allow us to win.
1:45:24
And he had this like great moment of leadership where it was like um if any soldiers are still asking, this is maybe 2012, I forget exactly, but he was like, if any soldiers still want this, it's worth fighting for. It's too important. Mhm.
1:45:39
And you know, it was just that moment of leadership that I needed.
1:45:43
So I got out of the car and um you know and then like just a you know a few maybe the next week I had some massive win on Capitol Hill.
1:45:49
Um but it was I mean look I credit that I mean it's the the reason I started Snowpoint and um like the the modern defense tech landscape exists because Palenter was able to break that paradigm. Mh.
1:46:04
And you know if you think of the new executive orders kind of like really focusing on acquisition reform.
1:46:10
So, you know, it was like an old '9s thing.
1:46:13
Um, the lawsuit was about this, but there's an old '9s, it was called the Federal Acquisition Streamlining Act.
1:46:19
I think it's '94, but it's during the Clinton days.
1:46:21
Um, I don't know how old you guys are, but it's it was basically um there were these scandals about the $400 toilet seat and the $200 hammers.
1:46:30
That sounds cheap by modern standards.
1:46:32
I feel like I every day I see we had the soap dispenser.
1:46:36
There was a soap dispenser that was like 50,000 or something.
1:46:37
No, but it's the same BS. Yeah.
1:46:40
So the interesting thing is so before 1994 and I might be screwing this year up by a year or two but um before then the there was this old term called milspec. Yeah.
1:46:51
And the milspec idea was that the preference of the US government was to buy custom things as the priority.
1:46:57
And so all of those scandals turned it on its head and created this idea where you have a commercial item preference. Mhm.
1:47:07
And so, you know, this is sort of like the when I talk about the invention or say the, you know, the start of the modern defense tech era, it was the winning of the lawsuit, which I think was 2016 or so.
1:47:19
Um, it was the first time since the law had been passed, it had actually been enforced.
1:47:23
So, our our lawsuit was like the precedent setting thing.
1:47:27
And all we were finding out, they have like there's protests all the time, like almost every major contract gets protested.
1:47:33
So that part of it wasn't um unique.
1:47:36
What was what part of that was unique about this was uh we weren't it was a called a pre-awward protest and so normally a protest is like somebody else wins and then Loheed gets pissed at Rathon and then they just argue about who is better and then the court decides.
1:47:52
Um our protest was that um we thought we were getting screwed by the army which we were where they specifically wrote the contract where I had put so much pressure on the army to expose all the flaws of D6.
1:48:04
Like D6 was like simultaneously failing while they spent billions of dollars on it while over half of the army's brigade commanders were requesting urgently Palanteer.
1:48:18
So there's this huge battle where, you know, it was like units would request Palanteer, the army would block it, I would go to Congress, expose it, and then there was just this back and forth and and I was like enemy number one for years.
1:48:29
And this is where all my war fighting skills came into play.
1:48:32
It was like in many ways fighting bureaucrats was just as hard as fighting terrorists.
1:48:38
And so I had that like it was good that I had call you a boardroom general, right? Yeah.
1:48:45
I was on the front lines though.
1:48:47
Uh but anyway yeah so so in this particular case so the lawsuit it was interesting because this is another experience of like you know between Peter Teal and and Karp it was like they trusted me and um I couldn't have done it like it's very unique in the Palunteer world that like they would that uh everyone said we were going to lose period and I think like statistically they weren't wrong.
1:49:08
I think the the the chances of winning these cases are like 3%.
1:49:14
So it was like clear and then if we won it so basically this is so everybody was like you guys are crazy and they were like let Doug just do this and um but it was like we were uniquely driven in the sense that we had the moral high ground. We had all the evidence.
1:49:26
It was it was the perfect setup.
1:49:29
Um but but anyway, long story short is uh we did end up winning and then we won the appeal 3 to zero.
1:49:36
Uh and so it sort of set up this thing where you know at the end of the day we when we won the we didn't get any money.
1:49:41
It was like basically we just burned three million three to five million bucks in the hallway on legal bills. Wow.
1:49:46
Um but then we had to go compete for the original D6 contract.
1:49:48
So it wasn't sure like I was halfway terrified.
1:49:52
We went through all this trouble and then the army would blackball us um which could have happened.
1:49:57
But long story short is that was sort of the the real um legitimate beginning where it was no longer a gorilla campaign for Palanteer where we're just winning enterprise contracts. Yeah.
1:50:08
you know, on the run and then on the merits and it's just, you know, the software is 10 times better.
1:50:11
I mean, it's just it's so impressive uh to watch.
1:50:15
I mean, obviously, I'm officially retired, but it's like I'm in I'm in the mafia for life. Yeah. Yeah.
1:50:19
So, can you can you talk about like the the long-term buildout of the defense business at Palunteer, where it is now, and then where you're seeing opportunities in defense tech, whether on top of Palunteer with their AIP program or just generally outside of the It just seems like the Army is modernizing and the DoD is modernizing generally.
1:50:40
So, uh companies won't need to go through the same 17-year journey necessarily.
1:50:44
No, I mean look, that's the whole reason I started Snowpoint was the idea was like, you know, during my journey, say I did a 100 things right and a thousand things wrong.
1:50:52
It's like, how could I help other companies accelerate through that that cycle and and you know, ultimately help help our whole society.
1:51:00
It's like having everyone succeed including for the services.
1:51:02
Um it's it's a win for everybody.
1:51:05
Long story short, but you know, I think it's like it's interesting um you know because during like early years I was um I got the seed corn in across like SOCOM and JC and then a few initial army units and then that was kind of growing but we were still searching for the elusive program of record and then we went to you know across there's like 17 different countries that we kind of got started in the military business.
1:51:29
I was flying on airplanes everywhere.
1:51:31
Um, and we got the C chord done.
1:51:33
And then there's like NATO is like it was kind of the inside joke of like that's never going anywhere.
1:51:39
And then now, you know, of course, this is 18 years later.
1:51:42
It's like we finally, you know, won this huge contract with NATO.
1:51:45
I'm like, you know, it it's taken forever, but it's it's it's been fascinating to watch.
1:51:50
And I think that like um what I what I had determined, you know, again, this is rewinding a little bit, was like we have to win in the US.
1:52:01
And then once we won in the US, it was sort of like this the dominoes started falling where and this is a deep history with Palanteer.
1:52:06
with Palanteer. uh and I tell a lot of my portfolio companies the same thing is this idea of like exit and crisis is that you know many different companies with a lot of different technology um will they all look similar on paper and so it's like how do you prove it and one
1:52:23
of the like defining things that I believe about Palunteer in particular but a lot of my I hold my portfolio companies to the same standard is this idea that um when there is a moment an exigent moment where it really matters and so in military context that means that like a commander is doing something, people are dying. Um, you Um, you have to win.
1:52:42
Then at that point, all the goes away and you have to have something that actually works. That's that's real.
1:52:50
And um that is something unique in the sense that like Palunteer has never screwed that up.
1:52:55
And um and it was just sort of like knowing that it's like you got to obviously it took us forever, but it's like we're past that.
1:53:03
We were way past that, you know, say by a couple years, but um past that momentum point where um you know, you were always fighting like the biggest barrier to entry was like some loser CIO or CTO inside a corporation or the government saying, "Don't worry about this.
1:53:20
I have this PowerPoint slide and I can build this cheaper, faster, better."
1:53:25
And then all the incentives are wrong and then they would slow roll you and and you wouldn't make anywhere.
1:53:32
And and so the the challenge where we would always say is the the open door was around who cares and are you actually talking to the profit loss owner like where it actually matters where the bottom line matters and in the military that was like the operational commander like if you got buried in the Pentagon where they're talking about programs you can't walk four feet without running into like a $300 million disaster.
1:53:53
They're all in they're all in denial about it and it's like because it like either tests out on paper or they're like it's coming. It's going to be here.
1:54:03
It's going to be so awesome.
1:54:04
Um just don't buy Palance here. It's too expensive.
1:54:07
We're going to do something you know I I mean dude don't even get me started.
1:54:12
We're getting you started.
1:54:14
We're getting you started.
1:54:14
Uh let let's flip to something much more concrete and timely.
1:54:17
Uh what's going on in Ukraine?
1:54:20
What's been your reaction?
1:54:22
And what is the solution or impact with uh to the defense tech ecosystem?
1:54:28
Yeah, you know, it's interesting.
1:54:28
I um I traveled to Ukraine in the very early when when Palanteer was just getting started there in the very early times of the war.
1:54:37
I went to Kev just to see what what was true and what wasn't true as we got kind of started.
1:54:41
And you know, it's fascinating to think there's like a there's a deeper political thing and then there's obviously a military and technology thing about this.
1:54:48
Um, and but it also applies to NATO and like what's, you know, the the defense tech market in Europe versus the United States and what the hell is Europe going to do now that like they have to, you know, do something real and stand up their own capabilities.
1:55:02
Um, I think this is like a fascinating time of like uh accountability and uh and I think it's good.
1:55:11
I think it's good for the world.
1:55:14
Uh I do believe that the world is better when the US is the hedgeimon. I believe that deeply.
1:55:18
It's like we can argue about whether or not we can uh afford it, but I'm like a firm believer in terms of like what I'm doing in the defense tech market, but it's also good for for Palanteer, all the companies.
1:55:30
It's like with less budgets, I mean, I suppose it's it's always good with more budgets, but it's like with less budgets or trimmed budgets, it's like if you need something real and you have like a short timeline, that's the perfect environment. There's no free chicken.
1:55:44
like the the entrepreneurs still have to actually deliver on what they said they're going to do. They have to deliver.
1:55:49
But that's the time when you can really succeed because when it's like you're kind of doing nothing and you're just like talking about these like five-year programs, you the tendency is just to waste money.
1:56:02
So going back to the Ukraine example, um you know, in many ways like Zillinsky single-handedly saved NATO, you know, because it's like Biden's plan was to get him on a helicopter and get out of there.
1:56:13
there. like it was just on the heels of the failures in Afghanistan and then it was like it was clear like enemies of the United States this is your time screw with America as much do whatever you want Biden's not going to do anything so it was a very so it was a very tricky time the fact that he decided to stay and fight you know was
1:56:30
super impressive it definitely saved NATO um and you have to think also initially and this kind of goes to like the deeper problem of like what's how are what's the resolution of this and what can we learn from it and I'll try to go faster here, but um think of this initially is Ukraine stopped Russia by themselves in the beginning. Yeah,
1:56:50
Yeah, that's something to like really pay attention to.
1:56:54
And and there was there was a few scenes early on because I used to model this of like China versus Russia's like the Russia was the real military um and China is like this paper tiger and I kind of like flip-flopped all that in my head now.
1:57:05
But it's like Russia could not have screwed it up more than they did. Mhm.
1:57:09
And um you know there was those scenes of like I was like God if we only had a squadron of A-10s on board we could have like you know I don't know you had this like trail of tears of like it was literally just like the first Iraq war where it was like a you know a 10 or 20 mile convoy of like every military vehicle in Russia was stuck on one road.
1:57:27
I was like please baby Jesus where is an A-10?
1:57:33
That's all we need right now.
1:57:33
But um look, there's there's a a very deep asymmetry with Russia versus um Ukraine.
1:57:46
I think the truth is, you know, I don't have a good filter here, but it's like the truth is that both armies suck, both militaries suck, and they've devolved into some sort of World War I BS thing.
1:57:58
Um, if you look at the numbers, it's like, you know, in terms of pushing pushing back, yeah, this drone attack seemed extremely sophisticated.
1:58:06
This did not seem like it's involved. You're not wrong. You're not wrong.
1:58:10
But but but that is that is uh it's a brilliant move.
1:58:16
Will it have any impact on the course of the outcome of the war? Untold.
1:58:21
It does it also mess up the the peace um Oh, the peace talks. Yeah. Yeah.
1:58:30
strike deep in in Russian territory.
1:58:30
It could be seen as aggression. Yeah.
1:58:32
Look, you can you can talk about this like there it is a it is a massive and uh incredibly loudable tactical victory. Mhm.
1:58:41
Um it's impressive in every possible way.
1:58:44
I I love it, you know, in a lot of way, you know, because you sort of think of the, you know, again, this is a very asymmetric fight.
1:58:49
If you look at like, you know, people, it's like 1.
1:58:50
3 million on the Russian side for active duty, 200,000 on the on the Ukraine side.
1:58:57
but they've just kind of devolved into this like frontline thing.
1:58:58
And so like is is the deep attack gonna actually change um the front lines or the course of the war?
1:59:06
I'm not convinced of that at all.
1:59:08
It definitely the the challenge here is like how do you degrade the ability of of Russia?
1:59:12
Um cuz they they have a huge like production problem like they have they they outnumber if you look at tanks and armor it's like you know 17,000 um but so I you know it's like one of the interesting statistics here is that Russia has like 17,000 tanks but they've lost during the war they've lost 8,000 tanks. Mhm.
1:59:35
The US only has 4,600 tanks just to put it in perspective.
1:59:41
But but it hasn't made Ukraine win, you know, like they're still stuck with this sort of like, hey, how do we do?
1:59:47
So there's this incredible like um but tactically tactically is this return to World War I style almost trench warfare that we're seeing.
1:59:59
Is that a byproduct of new technology coming onto the battlefield that is asymmetric and you know generally both armies don't fully understand how to deal with yet?
2:00:10
Yeah, the interesting thing is like you know if I say to my you know military colleagues it's like um there's a lot to learn from what's going on but don't learn too much because this is a very unique thing in the sense that um Russia in particular but Ukraine as well um have have completely failed to be able to execute a joint combined arms fight. Mhm.
2:00:38
And so this is this is the thing that the United States is uniquely the best in the world at in a sense where like what does that mean?
2:00:45
It means that you integrate space, air, land, sea, artillery all into one like you have a decisive point of the battle.
2:00:54
You have a bunch of shaping efforts to the battle and then you can succeed and you can pour troops into and accomplish something.
2:01:00
The US this is the most complicated thing you can do and it's super expensive.
2:01:05
That's why we have a 800 plus billion dollar budget.
2:01:07
And that's what the US is like a thousand times better at than anyone else in the world.
2:01:13
And what I can tell you is the Russians, the reason that they lost against the Ukrainians by themselves is because they don't know how to do that.
2:01:21
They were treating air force as like artillery. None of it was combined.
2:01:23
They totally failed to like in terms of communications, the ability to communicate and command control, like all of that stuff. Total disaster.
2:01:30
And here we are four years into it or whatever.
2:01:35
It's like what what's the outcome?
2:01:38
Um I'm curious how I'm I'm curious what Russia's early stage defense tech market even looks like.
2:01:46
I imagine it's a lot of it is government directed.
2:01:48
But how are they adapting? Are there private? Well, you see Yeah.
2:01:53
you see Yeah. Like the thing about Russia is like um again they've been very good at um advertising specifically like very low production or one production type things where they're like um exquisite systems or exquisite systems and then they have two of them and then the the the the
2:02:18
majority of their uh stockpiles are Soviet era that's horrible And if you think about it like this, um, think of the Soviet Union back in the day, it's like, and they're still not good at this, is that, or even you go back all the way back to World War II, it's like they've never been good at manufacturing. Like think of how many
2:02:34
Like think of how many cars are made in the Soviet Union or Russia, right?
2:02:38
How many real planes do they make, right?
2:02:40
And so like all that stuff is like they can build one or two off, but they're fully reliant on the West for all this stuff.
2:02:46
They've never been good at what they've been good at is like can we stamp out um thousands of really cheap attraitable systems.
2:02:52
Um and and do tanks fit into that category?
2:02:56
Are they Yeah, but but but they're not fighting with them because then you could argue that like because of the tactics, how relevant are they on the modern battlefield, you know?
2:03:06
And I think Ukraine with like a ridiculous uh underdog approach has been able to use cheap drone war.
2:03:13
Like to be clear here, I think that Ukraine is probably the best in the world at drones.
2:03:17
Uh and they have really at a tactical level.
2:03:20
Again, it's not changing the outcome, but they're at least holding the status quo and they're making millions of them.
2:03:27
Like they they figure out and and they're legitimately good. Yeah.
2:03:29
I mean, it's that part is fascinating to watch.
2:03:32
I just don't know that like um Yeah. the way that we fight.
2:03:37
If you were to put the US, if you take away the nuclear component of this, which always makes it tricky, the reason we have nukes is to make it tricky, right?
2:03:46
So, you don't do these things.
2:03:48
Um, but I'm just not convinced that we would do it this way at all.
2:03:50
And and how quickly would we would we win?
2:03:51
Um, that part's fascinating.
2:03:54
How do you think about counter UAS technology right now?
2:03:58
You have to imagine that Russia is thinking about every and any and every response to make sure this never happens again. Yeah.
2:04:06
And look, I was I was I apologize for being like too bearish about like how much does this matter?
2:04:11
The the attack is like stunning.
2:04:12
It's it's almost it's not quite as good as the Hezbollah beepers, but it's pretty close. It's up there. Okay. Um Hezbollah beepers.
2:04:20
I did my master's thesis on Hezbollah, so that gave me like, you know, specific joy.
2:04:25
But I um you know the the idea that like the uncertainty um and kind of a step back that it would take within Russia.
2:04:35
So now basically now they're searching every single truck.
2:04:39
You know they're like super heightened security.
2:04:41
This has caused mass chaos across Russia.
2:04:42
Now they can't mass those those jets together anymore.
2:04:45
So you have to space them out.
2:04:47
So this has like serious consequences to their like strategic capability, let alone their ability to just go bomb Ukraine.
2:04:53
Do you think that uh do you think that going forward various militaries, Russia in particular, will seek to place uh strategic bombers and aircraft like that in hangers and provide some type of defensive mechanism because the fact that they were just sitting out in the open.
2:05:11
We had No, I I actually think that there's like there's I don't know specifically this.
2:05:16
I'll have to look it up, but there's like there is like it's part of like the um there's a part of a nuclear treaty is that Yeah.
2:05:22
So, so it it mostly got rolled back.
2:05:24
Russia rolled it back at the beginning of the war from what I've seen, but you can imag but you can imagine they would say, "Hey, we're not going to participate anymore."
2:05:32
But they wouldn't necessarily build all the structures necessary to actually adapt. Yeah.
2:05:39
No, I mean, look, all this stuff takes time, too.
2:05:40
I mean, that's the the biggest thing is like, you know, for the a lot of those pl I mean, first of all, they're going to have to do that.
2:05:47
Whether there's a tree that says they have to be in plain sight or not, they're going to have to do that.
2:05:50
I mean, so this is like this this attack has caused a strategic impact.
2:05:55
Whether that gets Russia to the uh to the table faster or better or it gets land concessions for Ukraine or it gets them, I'm not convinced of that.
2:06:10
But it definitely is like a very successful thing.
2:06:12
And we also don't know the ramifications.
2:06:13
Like, you know, does this up the Annie?
2:06:15
Does this get us towards World War II? I don't know. That part scares me.
2:06:19
I do want the war to end.
2:06:21
Um, and it definitely gets in in into the Trump like Trump administration is trying to end the war and neither Putin or Zillinsky are like playing ball.
2:06:30
It's like that's kind of the disappointing part of this.
2:06:32
Well, I I mean we have to have you back on.
2:06:34
I feel like we could go all over the world and talk about geopolitics for 4 hours.
2:06:37
So, expect to get another calendar invite because this is a fantastic conversation. Yeah.
2:06:43
Thank you for jumping on. I really appreciate it. Thank you both.
2:06:46
We'll talk to you soon, Doug. Thanks so much. Bye.
2:06:48
Uh, and we have our next guest already in the studio, so we'll bring him in.
2:06:52
We're going to talk we're going to recap some of the Middle East AI deals, talk about uh, geopolitics in AI, some of the chip stuff.
2:07:02
Uh, I still have yet to figure out what the horse means. Why?
2:07:05
I just love horses, John. You just love horses.
2:07:10
I grew up I wasn't a horse guy.
2:07:10
I I have an extreme respect, admiration.
2:07:16
My mom texted me uh after the show last night.
2:07:18
And she said she was watching the show and because you were playing the horse sound, her dog was running around looking for a horse.
2:07:23
So give give the dog some horse.
2:07:26
For all the dogs that are listening, you're now on the hunt for all the dogs.
2:07:29
Anyway, uh welcome to the stream. How are you doing? Doing uh great welcome.
2:07:35
Uh thank you so much for joining.
2:07:38
Would you mind kicking us off with a little bit of introduction on yourself for for everyone who's listening? Great. Yeah.
2:07:42
Uh so Tan Koshik uh I am at Beacon Global Strategies.
2:07:47
We're national security advisory firm.
2:07:49
So basically what I do is uh you know work with US industry on how to be better national security partners to the United States. Great.
2:07:56
Uh and I I I wanted to have you on to to kind of look at a retrospective on what happened in the Middle East.
2:08:02
We saw Jensen Wong go over there.
2:08:04
I think Elon and Sam and Alex Wang and all the big tech CEOs went over.
2:08:08
over. uh what what is your read now that we have a little bit more distance from how those relationships are changing what we should expect what the actual trade deal came how everything netted out basically yeah I think it's it's a
2:08:24
very interesting thing that happened over there because you look at what the Biden administration did in January they they tried to approach AI diffusion uh with like three key strategic objectives they're like we want to prevent offshoring to the Gulf Mhm. M we want to
2:08:37
M we want to prevent these chips being smuggled into China through which is mostly a Southeast Asia problem.
2:08:44
And the third one like we want to prevent remote access where Chinese entities are just using these chips through the cloud.
2:08:52
Like there are hyperscalers trying to build big data centers for Chinese companies and Malaysia and all. Yeah.
2:08:56
Uh using this technology as a tool of economic statecraft I think was a secondary objective not primary.
2:09:02
Whereas I feel like what has happened, what we've seen with the Gulf trip is more of an upside down uh where we're using this technology as a tool of economic state.
2:09:13
We're trying to get concessions like we're going to give you these trips, but we want reciprocal investment in the United States.
2:09:18
We want onetoone investment.
2:09:20
Y and we want certain security conditions.
2:09:22
Now, a lot of that is yet to be cleared out, right?
2:09:25
We haven't finalized, it seems, per media reporting on what the security conditions are, whether they apply to specific entities or whether they apply to the UAE government or the Saudi government as a whole.
2:09:40
Do they get to host Huawei chips or Huawei infrastructure in the same data centers where they're hosting US chips, right?
2:09:48
like there are reasonable concerns that some people have raised and those are things obviously I think the security details will will probably be figuring out uh because uh if you remember Microsoft and G42 did a similar deal at a company level last year in April that
2:10:07
was accompanied by an intergovernmental assurance agreement which required G42 to do certain things like not have Chinese hardware in certain number of years uh just you restrict access for military or intelligence purposes like that deal was really well drafted. There
2:10:21
There were a lot of things that people pointed out that could be done on top.
2:10:26
So I think we'll see how this shapes out in the next coming few weeks how we see the security guarantees coming together.
2:10:35
Uh but overall I think this is in line with what the president has said that we'll give you our technology but what will you give us in return? Mhm.
2:10:46
So that's the theme that I expect to uh continue. Art of the deal. Art of the deal.
2:10:50
How how important is Llama in this emerging geopolitical narrative around AI.
2:10:56
Uh we're hearing that uh these I I've been calling them like kind of jump ball countries.
2:11:03
They're countries that aren't full allies and they kind of could do business with China and that's kind of the geopolitical backdrop for all this.
2:11:10
If they don't do a deal with Nvidia, they're probably going to run Huawei Ascend and Deepseek and Manis on top of that.
2:11:17
Is an open-source stack important to some of these countries? Yeah.
2:11:22
No, I think there are two questions in there.
2:11:26
First, whether China can even export. Mhm.
2:11:29
Which there are actually the the data suggests, you know, China has enough dyes that TSMC shipped to China. Mhm.
2:11:38
TSMC shipped to Huawei in violation of US export controls like about 2.
2:11:41
9 million dies enough to produce a million 910 C's about 900 910bs.
2:11:49
Uh now you know that's that's a lot of GPUs but they also have a lot of domestic demand. Mhm.
2:11:55
So the question becomes like will they be able to meet their domestic demand let alone export? Mhm.
2:12:02
I don't think that they have the capacity to produce it domestically at scale to export.
2:12:07
There was this announcement from Malaysia recently which the minister walked back afterwards where which made for a splashy headline that Ascend data center is coming online in Malaysia.
2:12:18
But if you look at the details, it was 3,000 ascents by 2020. Yeah, it's nothing. So they can't meet that. That's that's one thing. Yeah.
2:12:28
The second thing to your point, right, some of these countries have worked with China a lot. Yeah, of course.
2:12:34
And well, one of the things of bringing countries into our fold is that we have to work with countries that are in China's fold right now. Yeah.
2:12:39
That is a precursor of bringing them into our fold. Yeah.
2:12:43
But you have to be realistic what the risks are and how do we mitigate them.
2:12:48
mitigate them. Some of these countries have been doing joint military exercises in Shen Jang of all places or hosting military bases and Saudi Arabia I believe like a month or two months ago their national telecom champion did a
2:13:03
strategic uh announcement with Huawei and so you have to be realistic and put put in place those mitigation agreements but separately to your point on open source I think we should be flooding the zone with American open source at the expense of Chinese models. Uh I I
2:13:20
Uh I I think we're not paying enough attention to what can happen when a state controlled company to some extent.
2:13:29
There are a lot of PLA ties that deepseek has have been scrubbed from the internet.
2:13:40
Now if the state wanted to there was a great anthropic paper last year u not sure if people remember but on sleeper Asians that can be converted into models y if the Chinese state really wanted to you know us infrastructure or get into your phones why wouldn't they just put in sleeper agents that would activate in a year two years yeah if it runs into critical infrastructure it changes the way it reasons. Exactly.
2:14:09
And so we should be pairing ICTS action, right?
2:14:13
Like we're doing a lot of export controls on American tech not going to China, but where's the import actions on preventing this Chinese tech from coming into the United States or helping other countries deploy American tech? Like look, come on. Let's be real.
2:14:30
Nobody in Kenya is going to pay $200 a month to access advanced AI models.
2:14:35
We should be deploying American stack there.
2:14:40
We should be incentivizing companies with like loan programs from the development finance corporation, XM bank, whatnot.
2:14:46
Yeah, kind of a new AI belt and road strategy.
2:14:51
Something like that makes a ton of sense. Um, yeah.
2:14:52
Do you do you think we'll see something to the to the effect of a stuckset within AI in the next 10 years, 15 years?
2:15:04
I'd be surprised if there are not zero day attacks that have already been exploited.
2:15:09
Yeah, that we don't know yet. Yeah, that makes sense.
2:15:13
Yeah, that makes sense. um might uh there's been a lot of talk in around Nvidia's earnings around the shift from uh training to inference and we saw with Deepseek uh some really really creative engineering around uh distilling models and switching to I think FP8 and floatingoint uh and just a whole bunch of optimizations to to get a really great result out of less significant
2:15:39
hardware and so uh I wonder if there's is there any risk that the uh as pre-training plateaus, we wind up with a scenario where the distillation process continues and inference shifts onto lagging edge semiconductors and all of a
2:15:59
sudden the the the gap between TSMC's leading edge 3 nanometer and China's ability to produce in mass at 7 nanometer even beyond 10 nanometer beyond um that that actually changed the dynamic. Yeah. And I think uh you know Yeah.
2:16:14
And I think uh you know right now we have the lead there.
2:16:18
Uh it's it's possible that that happens.
2:16:24
And the answer I would tell you that many people in the US government would give you is we should not be complacent about it. Mhm. Right.
2:16:31
Uh we should not be providing components to Chinese companies to build semiconductor manufacturing equipment there to produce these semiconductors. Right. Yeah. Wait.
2:16:43
So, so what is your take on on uh the the chip ban and this idea that like you kind of either need to be all in or all out like it's either don't just worry about the chips but also worry about the entire supply chain or is there is there a creative argument that you could potentially make where there is value to the American semiconductor and and I guess western semiconductor stack ASML TSMC uh actually having an a a benefit in China.
2:17:12
It it feels very counterintuitive, but I was just remembering a decade ago, everyone in technology was making the argument that Facebook and Google should be allowed to operate in China, and now we're making the argument that the other tech company should not be allowed to operate in China.
2:17:27
And I I I kind of agreed with both of those, but they do seem at odds.
2:17:31
Walk me through that argument.
2:17:31
Yeah, I think look, uh there are choke point technologies, right, where we do not want uh the PRC to gain access.
2:17:40
There are multiple arguments for why you should not give them but the effectiveness really depends on whether it's a chokeoint technology or not.
2:17:51
ASML's machines when we export controlled uh extreme ultraviolet lithography. Yeah.
2:17:56
Uh then well uh China has not been able to produce anything domestically.
2:18:03
they are still stuck on 7 nanometer uh dual node patterning multiattering right uh and I think that set them back by 7 to 10 years at least. Mhm.
2:18:16
But so export controls are not about the point that they will never develop that technology. Yeah.
2:18:22
It's buying time and space so that we can extend our lead. Sure.
2:18:26
And that is what matters.
2:18:29
matters. So if we say tomorrow decide you know further tools should not go to China or other semiconductors not should not go or as it happened uh EDA software should not be sold we also need like some promote agenda to really extend our lead uh yeah so Huawei Ascend versus Nvidia um is this a quality or quantity battle how like what is the shape of that differentiation I think it's both uh quality
2:19:01
versus yields uh you know they're at about 20% or so uh when producing the dies for a sense so cost yeah it's extremely in you know inefficient and so without state subsidies uh the latest Huawei server that came out it is using technology that Nvidia was using 7 years ago wow right it's putting more GPUs on the same server to come at the same amount of memory and uh interconnect bandwidth and whatnot Yeah. Now, yeah,
2:19:31
Now, yeah, can they have a state controlled economy, they can do a lot of this. Mhm.
2:19:40
It's not sustainable at the end of it. Mhm. Uh so that's one thing.
2:19:42
Uh I I think there are a couple other things with regards to should we be okay for instance if it turns out that some many of these technologies like look to be real China is a an economy that has an or it is a system of government with an explicit civil military fusion strategy. Mhm.
2:20:03
Every research and development project that happens for civilian purposes is and will be used for military purposes. Mhm.
2:20:14
The vice president of research for Shingua said that explicitly like so are we okay with them developing technology that may be used to kill American soldiers or threaten America's allies in the South China Sea or you know take over the Taiwan Strait.
2:20:36
So those are questions that are you know they're very nuanced questions and hard to answer but the normally but in this scenario I would say perhaps not perhaps it's not okay for us to benefit PLA's modernization. Mhm.
2:20:52
So Huawei can do what it is doing right now.
2:20:56
I don't think it can scale.
2:20:58
Uh I think the US export controls to much extent are working.
2:21:05
The question is how do we extend our lead further?
2:21:07
So reviewing this year so far, do you think we're in a better position than we were last year or are we trending in the correct direction?
2:21:17
I guess yeah I think overall we would you know depends on what how do you define the strategy here right the strategy is to win I mean yeah the goal to win the strategy is to stop their development of the technology altogether that's not going to happen right technology races never stay one the Soviets learned that y so the Chinese have learned that too but if the the idea is to maintain gain a lead that they come second, we come first.
2:21:51
Yeah, I think we're going we're headed in the right direction so far.
2:21:56
Now, China has tried to weaponize like to try to mimic what BIS does with export controls through their own export controls, but yeah, their export control system is just like 5 years old.
2:22:07
Their law passed in 2020.
2:22:10
The nuts and bolts rules for dual use items, they did not arrive until December of last year.
2:22:15
So they're very much in an amateur state over there uh with regards to this.
2:22:20
So the US does have a lead on that as well. Very cool.
2:22:26
Well, thank you so much for joining. This was fantastic. Super insightful.
2:22:29
Uh we'll have to have you back and talk talk more soon. Awesome. Take care.
2:22:33
Have a great rest of your day. We'll talk to you soon.
2:22:36
And next up we have Aaron Gin, the GPU whisperer himself to take us further into the the discussion around uh AI chip controls, geopolitics, and all of the uh fun things that go along with that.
2:22:49
Uh Jordy, I'll let you take the intro and I will be right back. Perfect.
2:22:52
Aaron, welcome to the studio. Play some soundboard. Let's go. Let's go. The GPU Whisperers back. It's great to have you. What's happening?
2:23:02
When I come visit you, I'm going to bring you this. Wow.
2:23:08
Is that a new Is that for the gong? No, it's not a gong.
2:23:11
No, it's also not a sexual toy.
2:23:13
So, so it's called a talking stick.
2:23:16
So, in Kenyan culture, I got this in Kenya.
2:23:18
Uh the the basically the person that would represent the tribe would carry this around.
2:23:22
And whenever you show about a tribe, you would you would show them this and they like so like, "Hey, like I'm I'm coming to the the the TVBN tribe.
2:23:30
who should I talk to, right?
2:23:32
And then you find the guy with the talking stick because you know, yeah, you find the guy, right?
2:23:37
And and so yeah, Kenya, if you represent your sort of head of your tribe or head of your family, you carry that around and then and the great thing is like you can uh when you're in tribal meetings, uh if like you know, someone's arguing, you hold the talking, right? And you're like, "Hey." Yeah. Yeah.
2:23:53
So it's like, you know, so we can span two different continents.
2:23:56
You have the gong to represent my Chinese heritage and now you have, you know, something from the African continent.
2:24:02
So, we just got to find something from Europe. I like that.
2:24:03
Maybe maybe we could make it the uh Sam Lesson from Slow was was on the show talking about the potential of the ecane, you know, uh sort of a smart cane device.
2:24:13
Maybe that could be the American equivalent of a of a of a of a talking stick is a is a smart cane that that the leader of an organization carries.
2:24:20
Definitely something in there.
2:24:22
Uh what's on your mind this week?
2:24:24
I know you've been busy uh publishing uh also scaling Hydrohost.
2:24:27
What's what's going on in your world?
2:24:30
I so Nvidia released its numbers.
2:24:34
I I frankly was surprised they still beat the expectations uh despite having a lot of regulatory headwinds for at least a quarter.
2:24:43
And of course, like as you all have covered, those rules changed.
2:24:45
And now we're back to sort of October 2023 rules, which still had restrictions, but it was a little bit more friendly to some of the countries that were trying to uh form deeper relationships with aka Europe.
2:25:01
So like previously, half of Europe was on you're on the crap list, you're a bad boy.
2:25:04
Uh basically, Switzerland. Yeah. Yeah. Yeah.
2:25:09
Switzerland was bad, Austria's bad, Greenland's bad. We can buy the country. We can't sell them GPUs.
2:25:11
and Pexico as well which assembles 90% of all of our GPUs. Uh so that's all gone.
2:25:15
So a new uh era has or say returned to the old era which is 223 and we have this kind of new thing which I've talked about previously on the show which is this sovereign AI with America uh being deployed into regions.
2:25:31
deployed into regions. The biggest one was the G42, Saudi Arabia uh to build out GPU capacity within regions and and this will I think in the next coming years Americans will see gradually over the course of time how important both
2:25:47
this infrastructure is to the world but also how we ourselves will most likely become a default exporter like like Boeing like a default exporter of this technology not necessarily like we're always using it but the rest of the world is using it and they deeply rely on infrastructure. That's the trajectory
2:26:02
That's the trajectory this this this is is heading.
2:26:04
And and what what was surprising from the Nvidia numbers uh which like I know that uh John uh mentioned was that uh they Jensen has jumped more head first into politics under Biden.
2:26:20
He was very, you know, hands off.
2:26:23
He's just like, I don't support this stuff.
2:26:25
But now, you know, he's meeting Trump and Maril Lago.
2:26:26
He's uh a basically proactively advocating both at conferences and in earnings calls a actual posture about how the world should work and how the world should operate according to uh you know Nvidia preferences.
2:26:41
But but Americans then Americans then accept that like Nvidia is our champion.
2:26:44
They are a national champion. If they lose, we lose.
2:26:49
Like we're tied together at the hip and if they go down, we go down with them. there's not like AMDs.
2:26:53
Well, it it makes sense that he's getting involved with politics when uh in you know or geopolitics when uh Nvidia is valued at the GDP of the United Kingdom.
2:27:05
Yeah, I was thinking about that.
2:27:06
about that. It it is in many ways just a function of the size and scale of that company because you don't see the same uh yeah you're not seeing the same behavior from like the other pieces of the stack like the the the DRAM supplier or the transformer supplier the energy provider I mean to some degree but you
2:27:24
know certainly not getting as much facetime because it's like just a less critical piece of the economy and and the and some of the important things he said in the earnings call was that Nvidia lost 50% of its market share in over the last four years and he mentioned the acceleration of Huawei from 7 nm to 5 nm processes. Uh
2:27:40
Uh so when we as Americans think about GPUs and export controls, we're we're we're kind of battling two different metaphysical complexes that we don't fully accept or understand.
2:27:54
We have one which is generally uh was part of the Trump train back in 2016.
2:28:02
China hawk, they're a threat.
2:28:05
They're taking our stuff, you know, they're they're breaking into Jord's house, stealing his watches, you know, they're they're following John, trying to take a couple inches off his high height right now.
2:28:13
Like Chinese are everywhere. They're in universities.
2:28:15
They're taking our research.
2:28:15
That was like Trump Trump 1.
2:28:17
0, Trump 45, we got to be aggressive.
2:28:20
And he changed America's view on China.
2:28:21
He him alone, like he was the lone Republican on stage.
2:28:25
And in fact, Rubio and Rand were saying that he's saber rattling and the whole stage was like, "No, they're going to engage them."
2:28:33
But then there's this new version which has co-opted itself into which is part of the uh accelerated altruist people mixed with anti-trade mixed with protectionism who took that laundered it and are using it as justification to be China hawk.
2:28:52
And this is goes to my most recent piece which was which we journal which is that America has to be an AI exporter under I'm like OG China Hawk.
2:28:59
I'm like we gotta win with commerce the dollar free trade sell to many people as possible like Boeing as many Boeing airplanes in the world because it's a point of leverage.
2:29:11
It's a point of us being able to spread human rights, freedom, western values and not have to have bombs attached to it on the airplane. Right?
2:29:19
could be passengers rather than bombsh and this other wing which is small but very loud.
2:29:23
They've they've they've co-opted themselves into the altruistic, you know, basically these deceleration people kind of tra uh like protectionism anti-rade unions and China hawk people.
2:29:36
They're the like abandon Taiwan, don't sell to anybody.
2:29:39
We if giving it to the Gulf region means giving it to China, which is bizarre.
2:29:43
It's 12-hour flight away.
2:29:46
I don't I don't understand that.
2:29:47
And it's also insulting to the Saudis or like like they they actually will use it.
2:29:51
It's them saying the Jerusalem of China.
2:29:53
It's it's like it's all this complex kind of vagaries around patriotism like after that earnings call people call Jensen unpatriotic.
2:30:02
Well, you got hook profits, you know, above patriotism, right?
2:30:04
And it's this really bizarre like world that the these people live in where they think that like well if we just don't sell them it, there's no harm, right? They can just wait.
2:30:15
They can just wait for us.
2:30:15
wait. They can just wait for us. when Huawei is like please do and and the the customers in China uh that that were part of the information they they had this on the the publication the the customers of GPUs in China they said that like by the export controls they created the market for Huawei and so we
2:30:34
we only have two options as as a country we either win or we lose like that's it there's no in between there's none of this like we we'll just choke you off right we'll just hold you on the inside you can you can see this is using a non technology example is when we've done
2:30:48
this with food aid when we've done this with other semiconductors like when the first semiconductors came out we shifted to India and China China all of them produced their own industry and in fact there's a famous there's a famous episode between I think it was Johnson and Gandhi whenever she was prime minister when when Johnson was like hey
2:31:07
India you got to back us on Vietnam otherwise we're going to gradually send this food a there's a massive famine going on and and Gandhi she said publicly I will never depend on America ever again and after that she spent all of her money invested in agriculture improvements that became self- sovereign. So this is not a weird
2:31:23
sovereign. So this is not a weird abstraction of well well this is only unique to this situation when they have the engineering horsepower they cover 90% of all rare earth mineral production not ownership but just production they build they have their own boundary program it's already active we don't
2:31:40
have one and it's the focal point of all the accessory parts of a of a server like fans cables things like that and we're like well we'll just choke you off and just wait whenever we want to give it to you it's like no like why would they ever do that they they just build their own and they show They can. So in
2:31:52
So in that world, the Gulf Stargates, we should have a South America Stargate, we have European Stargate, we do in Africa.
2:32:00
We have to own footprint.
2:32:00
Otherwise, Huawei will just go out, sell it cheap gear, own the footprint, own this rare, you know, data center space is not prolific anymore.
2:32:08
Own that and then all the government data in those regions will be running on Huawei stuff, which is which is which which will hurt our natural security interest. Yeah.
2:32:16
What about actually selling to the Chinese directly?
2:32:21
Like should we be building a Chinese star gate?
2:32:24
There's this like weird like thread we've been pulling on.
2:32:28
China gate doesn't have a great rim to it.
2:32:32
But but I mean I I I I know it is different, but I want to kind of unpack all the different ways it's different.
2:32:38
Um because for years uh tech was beating the drum of uh Google should be able to operate in China.
2:32:44
Uh Facebook should be able to operate in China.
2:32:46
This would be a net win for the United States if we could operate there.
2:32:50
GPUs are different because it's more in the supply chain and there's different things you can do with it.
2:32:55
We might be powering adversarial dual use technology.
2:32:56
Um but uh is there is there a world where these two situations are more similar than they are different?
2:33:05
Yeah, the the dual use argument is an argument in vacuum.
2:33:10
It's it's an argument from ignorance.
2:33:10
We don't have an example of what this dual use could be.
2:33:12
And there was a response to Jensen in some article I read somewhere where like they could use AI for missile targeting.
2:33:18
They're like they don't need AI to do missile tech.
2:33:21
They have perfectly fine missile techn technology to to target.
2:33:24
What about uh wait what about just the the idea that like you know large language models chat models they increase productivity and so you know if you give a if you give a soldier on a base chat GPT they will be able to inventory the rations faster and that will increase military productivity. Oh heavens, right?
2:33:46
Like it it say so like one is that by us not entering in the Chinese market we created a Tik Tok problem. Yeah. We created an Alibaba.
2:33:55
We created like like maybe it's because I unpack that because I feel like we we definitely tried to enter the social media market in China.
2:34:06
We were blocked and then I I don't understand how we created that problem.
2:34:09
Well, it's because like we wanted to enter on our own terms. Oh, sure. So So like Yeah.
2:34:12
Like I'm not saying we have to do business with them always.
2:34:14
Like that's that's not what I'm saying.
2:34:15
I don't want to sell F35s.
2:34:17
don't want to sell F35s. I almost have 22s like logical like things when we sell uh trip 7 it should logically have our GPS technology removed anything that's aligned with like kind of our connectivity sure like we would do that today that's fine they they but when you
2:34:32
when it comes to actual like core platforms GPUs is not just the card because just because um you know you own a a a G63 Mercedes doesn't mean I can build one like there's this like misunderstanding of like Jensen is pursuing a 3 nm 2 nmter sort of direction of this company. They don't
2:34:51
They don't have the ability to do that.
2:34:53
And just because I own a cheap wagon doesn't mean I know how to build one.
2:34:56
Doesn't mean I can build one.
2:34:58
And there's a disconnect between there.
2:35:00
So one is that we should restrict anything that is on the supply chain level.
2:35:05
I'm totally cool with that.
2:35:06
If we want to target foundry equipment, if we want to target data center equipment, totally cool with that.
2:35:11
Problem with that, we don't build any of that stuff. Other countries do. Yeah.
2:35:14
But I mean we have American IP so we actually do have a point of leverage over ASML equipment if I'm if I remember that correctly. Yeah. Yeah.
2:35:20
Foreign director role right. So so so yeah.
2:35:21
So it's a stretch because like Japan can still do what it wants like it doesn't it doesn't have America has limit limit like the regrame. Yeah.
2:35:33
The regular frame of the commerce is limited to its ability to to basically tax authority.
2:35:37
So if you have money in America then they could do something.
2:35:40
But if you don't have money in America and you say foreign direct rule in Japan, it does like like they're like, "Okay, that's nice.
2:35:45
Thank you for your memo." Like it.
2:35:46
So I But but again, it goes to like how we treated GPUs that if we want to create a point of leverage between the Dutch and Japanese over over foundry equipment, we should probably not cut half of the Dutch economy off from GPUs, which is what we did.
2:35:59
So So if we want to be allied with them, we should realize what's important, what's not important.
2:36:04
To me, supply chain production is important, not consumption.
2:36:08
consumption. consumption is not very important mainly because there's another risk factor which is significantly more important which is like is it worse for the world if Huawei is everywhere or is it better for the world that Nvidia is everywhere and and and when you we're
2:36:22
talking about the dual use question it's like they don't even think about that well if we if we don't actually engage them on our own platforms we finance their current platforms and we encourage them to do that they will still do it like I I I I think we have to understand that it's a both and a framework in China. I if we if we sell them a fighter
2:36:39
I if we if we sell them a fighter jet, they'll buy the fighter jet and make their own fighter jet.
2:36:44
But but the point is that they is to starve and to use like doesn't starve the local economy as much as possible and to create dependency on us.
2:36:52
The more dependency on us like it's less likely to war.
2:36:55
Also, we can maybe gain leverage on like other trade issues like you know cheap goods, fentanyl, Taiwan.
2:36:59
there's a whole other layer of additional things and just saying dual use which which which again we don't know what that means.
2:37:08
People just say it and they we don't I don't know what it means and as well you can still do it with Huawei.
2:37:12
So like like what does it matter?
2:37:13
like it's this kind of vague bigies around it without understanding the clear differentiation between production consumption, title ownership, cloud consumption and building all those are comingled around Nvidia when each of those are distinct different things um that shouldn't be coming because then you can you give us an update on on uh the Biden administration in January was focused on remote access.
2:37:37
Is that a widescale problem today?
2:37:40
You can imagine it's a lot easier to access GPUs remotely in another country if you want to train a model than it is to smuggle them in across different borders and things like that.
2:37:53
Yeah, the January uh controls assumed two things and ended up being 100% wrong.
2:37:58
One, how close was Huawei?
2:38:01
They assumed like five years, totally wrong.
2:38:03
It was like basically 12 months.
2:38:04
The other one is that LM are remote and they're not.
2:38:06
So like what does it matter?
2:38:08
They like like if DeepSync is the number four, right?
2:38:11
because mainly because it's open source that that's the main reason uh and and it became a brand name and so people know it.
2:38:16
Uh but there's lots of alternatives to to DeepSeek.
2:38:18
There's lots of different reasoning models.
2:38:22
There's lots of foundational models and multimodal models. So it's not a mode. So what does it matter?
2:38:26
Like they make their okay, we make another model.
2:38:28
Like it's not an innate just use a different model.
2:38:32
So So they're we're not going to prevent them from making models.
2:38:34
They they're going to do what they're going to do.
2:38:37
The question is whether or not we're going to be better.
2:38:38
So, it's it's like if you're like racing a car, uh I'm going to F1 race in Canada the uh next week. Nice.
2:38:44
If the F1 driver was staring at the guardrail, is he going to win?
2:38:49
And that's what we're doing.
2:38:49
We're like looking at it. Like, oh my god. Right.
2:38:52
Like, are we looking at the finish line? Are we looking to win?
2:38:54
Because if we win, it doesn't matter because we choke off the local industry.
2:38:57
We we become the global dominant player and then they become KMAC, which is the Chinese version of the airline, the the alternative to Boeing and Airbus.
2:39:05
It's going to be decades before they get anywhere with that airline.
2:39:09
And and that's because Airbus won, Boeing won, and market penetration is a moat.
2:39:14
And we we we we not everything that happens in China is just because they copied us or they stole or they stole something like like they're legitimately good at engineering.
2:39:26
And this is what the point that Jens's been making is that when half of all AI researchers are Chinese, y we can't just be like, you know, can't see it, can't see it, like like we got to engage with it because because at least it's better that it's on our platforms.
2:39:40
And if if the federal government wants to spy on that, like why not?
2:39:42
Like it's like we can't even appreciate the as asymmetric style of that of like imagine if we sold them the video stuff.
2:39:48
It would just spied on it.
2:39:49
Like it's like like let's do what they do to us.
2:39:50
But instead we're like oh right like dual use like oh military, right?
2:39:54
It's a it's it's bizarre to me.
2:39:58
Um, what's been your reaction to the Russia Ukraine development?
2:39:59
I've always been struck by the fact that Russia has produced so many incredible mathematicians and yet seems so irrelevant in the AI conversation.
2:40:09
Uh, any chance that that changes?
2:40:13
Uh, you know, you talk about dual use, seems like they can barely, you know, deal with any technology over there.
2:40:21
Yeah, they make a few drones, but like they're they're years behind the AI race.
2:40:24
We're certainly not testing the limits of artificial intelligence on the battlefield over there.
2:40:30
The uh let me tell you this that uh so with our with our company being international, we've come across all sorts of characters.
2:40:37
So in Riad, I met a Russian who Russian broader caucuses.
2:40:45
So he he speaks Russian but not really Russian who runs data centers in the region.
2:40:48
And he was telling me that about like what Russia is doing.
2:40:53
And he said that like don't underestimate them being quiet doesn't mean they're not doing something.
2:40:57
And and this goes to the the Stargate thing and proliferation is like when somebody does something bad with this, which is going to happen.
2:41:06
It's without a doubt it's going to happen.
2:41:08
The the Ukrainian attack on Russian planes wasn't AI.
2:41:09
It's just fancy remotes and there's no evidence that had a model that was I don't even know why you would need a model.
2:41:16
model. didn't look at the plane and like yeah like it was a it was a very bizarre way of kind of reading that situation was very clearly like remote controlled but um the the uh if when someone does something bad with this technology which is inevitable the world will be very woken
2:41:36
up to how one the powerful this technology is but two how lazy they've been on some of these things that we're we're talking about where it matters if we're everywhere Because if if we're everywhere and let's say something someone does something bad with us, what does that mean? That means
2:41:50
That means that we have the ability to project influence now across the hundred comp countries that are have our infrastructure that that could be everything from utilizing infrastructure in a way to bring along allies to counter something.
2:42:03
Uh but as well as creates a new type of NATO, a new type of framework which is the defense of the next century there.
2:42:10
There is China will pursue it's almost like a known quantity. China's been China.
2:42:16
There's very little things we can actually can do to impact the directory of 1.
2:42:19
3 million people outside of the natural entropy of China itself.
2:42:24
China has imploded seven times in its whole basically 6,000 years of history.
2:42:29
So uh yeah exactly sure please. Right.
2:42:33
So, so communism is just the next iteration of whatever revolution, theQing dynasty, the Shan dynasty, the Shan dynasty, uh the Mongols, right?
2:42:43
All those were different iterations of the same millions of people die, build a new regime, billion people die, build a new dream.
2:42:50
The the ability of us externally being able to influence it is is very limited.
2:42:55
Uh unless we do what we did to Japan and South Korea, which is we totally obliterated other tower society, we built bases there.
2:43:02
We gave them democracy and we gave them markets.
2:43:04
Then you can influence and they can be a part of the order but they don't want to do that.
2:43:10
So China's going to China.
2:43:10
Well what we have to do is we do best which is win trade commerce be the best make give us invest as much money as possible into Nvidia products.
2:43:19
I what their with their recent announcement I I sell in competit but they had this uh basically Nvidia link as a platform.
2:43:26
It's the best way to understand it.
2:43:28
Yeah break that down for us.
2:43:29
So yeah, so because all of this new GPUs are coming out like the gro drones, Huawei, the one of the most valuable parts of Nvidia's infrastructure is its interconnect and interconnect is both software defined and hardware defined. Nvidia is the king.
2:43:44
Like on the GPU level, Huawei is getting closer and closer as is AMD, but from an interconnect level, Jensen's in the stratosphere.
2:43:52
The key is so far beyond.
2:43:53
beyond. So as an effort to keep them in the CUDA system which is this most significant software mode he's releasing in link as platform to where you can plug in other GPUs and you can work through Nvidia fabric as John just said the commerce is going to foreign direct rule the asset of that thing so it's
2:44:10
probably not going to make it into China and that actually has a legitimate claim like you know we made this software reproduce it and it goes versus Japan is a little much looser claim and so I don't think it's going to make it in China but that's the premise is that he's trying to protect Check the CUDA mode. The CUDA mode is the mode of
2:44:24
The CUDA mode is the mode of NVIDIA.
2:44:26
And if Huawei continues to accelerate, open source framework accelerates, Nvidia's mode declines, which means more Y web product uh basically gets released into the wild.
2:44:36
More models are defined by YW.
2:44:36
I is that Envy link um uh licensing more relevant to uh international companies that want to combine different CPUs and GPUs together or is it more relevant to just maintaining dominance in the American market? Yeah.
2:44:54
With hyperscalers that are developing their own chips, things like that. Yeah. Yeah.
2:44:58
The pitch is to hyperscalers, but the actual target is is China.
2:45:03
Yeah, I'd say that that is the that's the but I mean but I mean you're predicting that it won't make it to China.
2:45:09
So why why even like pitch that if it's it has a very low shot of actually getting through.
2:45:13
I mean they they have 75% margins so they can do lots of things that don't go anywhere and and and also they they view that the two risks to Jensen just as putting on Jensen hat. I'm not an investor.
2:45:26
I'm not talking my own book.
2:45:28
I'm not I'm not I'm not talking my own book.
2:45:30
So the the uh is public cloud with their GPUs which goes to this ambient link platform in Huawei. Those are the two risks.
2:45:37
So he's targeting to both but the issue with the uh what public cloud's doing is that they are trying to delever from them as much as possible which is why most of the future deployments I suspect and public go to core.
2:45:50
Cory's like a third party just reseller into cloud.
2:45:52
But his real angle is to Huawei gear where they do not have the ability to build this interconnect via the Huawei products.
2:46:00
Uh cloud matrix is closest and it's still pretty far behind as well.
2:46:05
You look at the networking expense like in terms of the margins in their in the the public reporting they're it's still growing in revenue like significantly on networking side but they're not making very much money.
2:46:16
It's because they view networking as the moat.
2:46:17
as the moat. So they're really just trying to push something into the Chinese market so they can retain that CUDA advantage because they they do think that China is accelerating on the most important models which are the open source models that that if Nvidia sees the more and more open source accelerates the farther and farther it
2:46:37
gets ahead the more that it's going to basically cannibalize uh Nvidia's footprint because if only selling to closed source models that again limits their ability to sell widely and to keep our platforms and America has real like that I'm not just talking about individ like that's our national champion so so it's it's
2:46:55
like locked it's like a Boeing it's like it is our expression into the world of what the future should be and the ability to are our or have like or have our values built into technology which is privacy security western values freedom freedom of thought freedom of information on the internet uh and so I I'm I'm fine with the the product idea I
2:47:12
I don't think it's a risk really much to anything um but most likely commerce will restrict because if they're already restricting boundary equipment, which I which I generally agree with because it's boundary equipment cost $100 million in the side of the house, like you can regulate that. Uh we we export control
2:47:26
Uh we we export control airplanes.
2:47:28
Well, yes, because you you have to put ownership or you fly it over there.
2:47:32
That's not something you can go buy at Best Buy and put in your backpack.
2:47:35
Like it and I mean Nathan Nathan Fielder was able to buy an airplane uh recently for a show.
2:47:38
Um I want to switch switch gears for a second.
2:47:44
Uh there was some news this morning that Meta is partnering with nuclear energy company constellation energy to power uh some of its AI uh I guess AI factories data centers for the next 20 years uh post these new executive orders on nuclear energy.
2:48:01
Do you expect to see a lot more uh deals between hyperscalers or foundation model companies and various nuclear players? Uh unfortunately not.
2:48:12
I I I'm a big fan of fusion.
2:48:15
I'm a realist when it comes to politics.
2:48:16
I'm conservative through and through.
2:48:18
Adam Smith, you know, Milton Friedman, Thomas Soul, like the they're my heroes, but I'm a realist when it comes to DC because DC is is ideology is an excuse for decisions that are self- serving. It's the way DC works.
2:48:29
Nuclear I I love the technology.
2:48:32
I think it's immensely safe.
2:48:32
I don't believe in this irrational phobia related to it.
2:48:36
it has, you know, the the third party or the existential causes of the, you know, pollution or whatever of the energy is put in a barrel, put underground. It's like so amazing.
2:48:44
But and even that the recycle making recycle like 98% of it now.
2:48:49
Uh but power generation uh is very different than energy.
2:48:56
America's really good at energy is really bad at power because power is a federalized decision.
2:49:00
And I just don't see a significant amount of willingness to change about that.
2:49:04
to change about that. I hear lots of talk but the talk is also a little bit like Doge which is the operational mandate of Doge is discretionary and even that it has to have the difference of the secretary it doesn't have a lot of power you have to have mandatory spending have congress do something
2:49:23
because it's the way it works same thing with power is like department of energy can't just say do it right like like the state because it's federalized that that's the whole point of freedom is that if the state says no they're going to say no it's not going to happen so maybe on federal lands by Indian lands. That stuff makes sense. That stuff makes sense.
2:49:38
But but it's I think it's extremely unlikely.
2:49:41
I think it's more likely the like Stargate is essentially a sovereign power infrastructure where they're buying natural gas turbines which is we have a significant amount of natural gas.
2:49:51
They build it in deregulated energy environments and they attach to the data center.
2:49:55
I think that that's more likely because that doesn't require 10 years of approval and you know people who have degrees who never done anything in the world showing up and telling you how to do business.
2:50:03
like it doesn't require any of those things. It's it's natural gas.
2:50:06
It's it's fine and and their pipes are everywhere.
2:50:09
So, what we hear on the eastern level is much more of a trajectory towards natural gas and that nuclear entertaining.
2:50:16
There's not want this stuff to happen. I'm just a realist.
2:50:20
I think it's it's you shouldn't bet on it.
2:50:22
And many of those contracts you see, they're more like if you like dig into it because the Amazon, the Microsofts, the Facebooks of the world, they know the regulatory hurdles of doing this stuff is years.
2:50:32
And so they're basically using the announcement as a means.
2:50:35
They're trying to press through the regulatory cycle uh and to get stuff done.
2:50:39
Well, just to give you some more insight, this deal in particular is for uh a a power plant called the Clinton Clean Energy Center.
2:50:50
So, it's from a different era, right?
2:50:51
It's not a it's not a it's it's taking an asset that we've already had and then doing a net new deal.
2:50:56
It's not as exciting as, hey, some, you know, new nuclear company just signed a 20-year deal with with Meta.
2:51:02
So, the approval of putting servers in the building or putting it around the building like that's not something that's going to be, you know, they're Yes. Exactly.
2:51:12
Like the It's uh the fear around nuclear is is unfounded, but it's still real.
2:51:18
It's it's real and and and this is democracy.
2:51:20
Like you don't get everything you want and and if people don't want in their backyard, they don't and it is what it is.
2:51:26
So like uh but yeah, but I'm pro those things.
2:51:28
I'm pro clean fusion uh like low heat like coal nuclear reactors.
2:51:35
I think all those are super cool technologies that we should embrace.
2:51:37
Yeah, this thing is is interesting because the the reactor at this site was going through a decommissioning process.
2:51:43
So they're effectively bringing it back online. Oh, great.
2:51:47
Similar one to the deal that uh Constellation did with Microsoft in Pennsylvania with the three-mile island plant last year.
2:51:53
So, um, so yeah, at least at the very least it's great to see plants that are clean and functioning, staying online, and serving a purpose.
2:52:03
Anyway, thanks so much for stopping by. This was fantastic. We'll talk to you soon. Always a pleasure. Yeah. See you, man. Cheers. We'll talk to you soon.
2:52:10
Uh, let's close it out with some timeline.
2:52:12
Uh, there's news about Perplexity.
2:52:15
Apple is reportedly planning to adopt Perplexity as an alternative to Google search on the iPhone as well as a replacement for chatbt integration with Siri.
2:52:22
This is kind of rumor mill at this point, but uh apparently Perplexi is also in talks with Samsung uh could become uh a default installed uh search provider on Samsung Galaxy phones and Android phones. Arvin's cooking. Arvin's cooking. Yeah, it's interesting.
2:52:37
It's like the obviously the product is not like completely broken through, but sponsored an F1 team. Maybe maybe it's not.
2:52:45
Didn't they do a Super Bowl ad or No, they just did a really cinematic ad, but uh they've definitely been been out there sponsoring stuff and sponsored Ferrari. Ferrari? Really? No way. Just fully sent it. That's amazing. Tim Cook saw that.
2:52:58
He goes, "Okay, let's talk. Let's talk. Time to talk." Um, yeah.
2:53:03
I mean, certainly smart to break through.
2:53:04
And I mean, a lot of these a lot of these companies like win on these default installs.
2:53:08
It's always tough when there's another company that's like going viral and just growing like crazy, like Chachi PT.
2:53:13
But, you got to get creative and figure out where the value is and who's hurting.
2:53:17
and uh Apple and Samsung seem like they're at the top of the list for uh needing a partner to really keep up with uh with Chat GPT in some ways.
2:53:25
Um anyway, we should tell you about f uh wander. Find your happy place. Find your happy place.
2:53:31
Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, and 24/7 concier service.
2:53:38
It's a vacation home better, folks.
2:53:40
Figure out plans for summer. Yep. Book a home on Wander. Yeah. and uh report back.
2:53:46
Uh we also have some cool probably AI images from if Tesla was made in the 1980s.
2:53:54
I don't know how I found this.
2:53:54
It only has five likes and 220 views. But I really like this.
2:53:58
I thought it was a cool design.
2:53:59
Looks kind of like an Aston Martin bulldog or there's a lot of Aston Martin in there.
2:54:04
But yeah, I hope I hope with Elon spending more time at Tesla, we get some crazier designs.
2:54:08
I want to see a convertible.
2:54:10
I want to see something competiz SUV.
2:54:13
competiz SUV. the Cyurban the Cybert truck converted into an SUV that I mean we've talked about this a a sedan with the aesthetics of the Cybert truck would super cool rip the cyberon the the the the huracan version of the cybert truck
2:54:30
like the new roadster with the cybert truck aesthetics I mean I still think the cybert truck aesthetics are really cool but it's just it's just like not everyone needs a full-size truck you never see somebody with a cybert truck using it as a truck I've never seen anything in the ever. Also, we're in LA,
2:54:43
Also, we're in LA, so most of the Cybert trucks are influencer based.
2:54:48
Um, semi analysis breaking down Tesla's Optimus.
2:54:50
Speaking of Tesla, ever wondered how those humanoids are dancing in the videos.
2:54:56
Check out Tel Tesla optimists.
2:54:56
Uh, here hitting a smooth shuffle.
2:54:59
Let's dive into one of the methods they may have used in the paper ASAP, aligning simulation and real world physics for learning agile humanoid whole body skills.
2:55:08
The researchers did train the humanoid to perform these actions in simulated environments.
2:55:11
But there's more to this.
2:55:14
So, we've been talking a lot about uh simulation in the context of robotics.
2:55:19
It seems to make a lot of sense that you could model all of those joints in a physics engine, run that in Unreal Engine or something.
2:55:25
I mean, it does look remarkable.
2:55:26
Uh I don't know if you can see that, Jordy, but the uh I mean, the dance is definitely not the Biden walk, right?
2:55:32
Uh so, the pro the problem play it. Let's see it. Yeah. Yeah. Here. Here you go. Uh okay.
2:55:35
What What are you thinking? Conspiracy time, right? No. No. No. It's pretty good, right?
2:55:42
I mean, it's definitely a unitry level. Yeah.
2:55:46
I don't see why they'd be any further behind unit, but obviously there's a lot of I think Gen Z would say the robot low key has aura. Aura. Yeah.
2:55:56
The problem the robot policies like guide books for performing an action trained in simulations often stumble when transferred into a physical robot.
2:56:03
This is called the sim tore gap.
2:56:03
We'll have to talk to more folks in robotics about that.
2:56:08
Uh many complex interactions can occur in real life that are difficult to model.
2:56:11
ASAP decides to train their policy in simulation by using retargeted human motion like Ronaldo's SUI celebrations motions but mapped onto a humanoid so that it can produce the same motions in its own body.
2:56:25
However, to mitigate the issues upon transferring to real life, they then deploy the policy onto the Unitary Robotics G1 humanoid.
2:56:32
This is uh from a from a researcher and train a delta action model.
2:56:36
The model watches and learns what the differences are between the desired simulated motion and the real world.
2:56:43
Uh this delta in particular this jumping motion it's wild is wild wild the the the jumping cuz you you that's using the same effectively the same physics as a human to do that.
2:56:56
and it just feels feels a lot more they do a bunch of simulation, they transfer it to the robot, then the robot does it and messes it up because there's all these like fine details that that that uh that emerge when you're crossing that sim tore gap.
2:57:12
That delta correction is then fed back into the simulator, effectively aligning the virtual simulated world and robot with reality.
2:57:20
The result is significantly improved agility and coordination and now fluid reproduction of famous celebrations.
2:57:27
Uh ASAP is a major leap forward for humanoid robots, but there still remains some challenges in simulations.
2:57:34
And semi analysis says, "What do you think?"
2:57:36
And so it's interesting because it's basically creating a a a reall life feedback loop for humanoid robotics based on simulated data.
2:57:46
So you go and simulate the robot to get it like 80 or 90% of the way there.
2:57:49
Then you run those simulations on the real robot and let it make a bunch of mistakes and then feed all of that data back in.
2:57:55
So you're generating a lot of robotics data and you can actually have like a a learning loop to improve this.
2:58:01
So uh still unclear how close we are to like fully re fully utilizable fully useful humanoid robotics but it does seem like more and more algorithmic progress is being made.
2:58:13
more and more like AI training strategies are being made uh to really make this stuff uh valuable.
2:58:19
And then of course closer to the the robot games where they're going to have these robots do surfing at Jaws, cliff diving, things like that. Can't wait.
2:58:30
Uh let's tell you about Adio.
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2:58:45
Everyone from Union Square Ventures uses them to Coca-Cola. Wow. That's a big range. Big range. And TBPN, of course. Of course.
2:58:53
Uh when I first opened Adio, I instantly got the feeling that this was the next generation of CRM.
2:58:58
So trying to make money, trying to sell, if you're doing deals, get on AIO.
2:59:04
We also have some uh news.
2:59:04
There's a new company launching.
2:59:06
Amy from Joe Perkins, the AI agent for private market investors.
2:59:10
Stop wasting 30% of your week on busy work.
2:59:12
Amy handles sourcing, diligence, ops, admin, and research 24/7, remembers every interaction, and sharpens over time.
2:59:20
Yeah, this is interesting.
2:59:21
I I have the website pulled up. They do deep diligence.
2:59:23
So, you can imagine some type of deep research product, watch list monitoring, anti-portfolio analysis, which is fun.
2:59:31
basically track track track your passes, memo drafting, exit planning, customer diligence, autosourcing, market mapping, team evals, meeting prepper, pretty extensive. It's cool.
2:59:43
Um, well, the timeline was in turmoil as Megan Nyold kind of sort of anonymously called out Alex Lieberman for co-founding too many companies. Oh, wow.
2:59:54
That was I I saw Megan's You saw that post? I had no idea.
2:59:59
I had no idea who it was either.
3:00:01
And Alex kind of selfdoced himself here and he says, "Someone called me out publicly for co-ounding five businesses." What?
3:00:06
A man can't co-ound five businesses? Come on.
3:00:08
I think I've actually co-ounded maybe four businesses at this time, although I kind of moved on.
3:00:14
I wasn't doing them all at the same time. One at a time. It was one at a time. Yeah.
3:00:16
But uh uh I love the reaction. It makes total sense.
3:00:19
So, I thought I'd explain.
3:00:20
Says Alex Lieberman, the business barista.
3:00:21
He says, "I very much don't recommend people do what I do.
3:00:25
History has proven time and time again that relentless focus on one thing for decades is how you build anything of consequence.
3:00:29
I didn't set out to build a startup studio and co-found five companies.
3:00:32
It was the result of trying to optimize for my two highest order goals post exit.
3:00:36
Be an A+ entrepreneur and an A+ family man.
3:00:38
Read have full control over my schedule and time.
3:00:42
Spend 90% of my time in the negative one to one of business.
3:00:45
Early stage businesses make me feel like a kid in a candy store.
3:00:49
I do not work 120 hours a week.
3:00:51
I work about 50 hours a week.
3:00:53
Most mornings I start drinking coffee, walking the dog with my wife.
3:00:56
Most days I finish eating dinner and walking the dog with my wife.
3:00:58
Those moments are sacred for me.
3:00:59
I have an amazing co-founder and CEO for each one each of my businesses.
3:01:03
So he's not the CEO of these businesses.
3:01:05
That would be very very difficult.
3:01:06
Um who I trust deeply and gives me space to focus time.
3:01:10
I view myself as a media company that creates surface area for an array of opportunities.
3:01:13
So yeah, uh little bit of an uncommon decision, but he's certainly enjoying it.
3:01:18
And so you know, hats off to him.
3:01:19
Yeah, I mean I think the thing that matters ultimately having a CEO that is regular founder as incentivized y as a as a traditional founder or over time you'll get cooked by totally a founder a truly founder company to totally totally so so yeah there's there's a big question about like you can be a small angel that owns.
3:01:41
owns.1% of a business you can be a VC who owns 20% of a business and uses the word we when describing the company uh then you can be you know an an incubator or a silent co-founder or you can be the co-founder CEO the founder CEO and and these are kind of a spectrum and everyone kind of plays in different roles but uh you know historically it's it's that serve to to work at kind of
3:02:04
the fringes of those but um there's different models that work for different folks uh this is an interesting trend that I want to dig into kind of the future of Hollywood we've been joking about this but uh there is something interesting with uh what Tony Lash Lashley says Sequoia investing in essence and Mubby and Thrive investing in A24 in the past four years. Pronouncing essence properly, John. Yes.
3:02:23
Pronouncing essence properly, John. Yes.
3:02:26
So, just sense uh and Thrive investing in A24 in the past four years is quite fascinating.
3:02:32
Um and so apparently the Essence investment maybe didn't do so well.
3:02:36
Definitely they're pretty clearly struggling, but the model works and so Sequoa is getting into the independent movie business.
3:02:41
Thrive is already in with A24.
3:02:42
And so uh very very interesting to discuss like the impact of AI on Hollywood and independent movie making as these movies it feels harder and harder to get the the power law outcome in movies the Avengers moment the Avatar moment the Top Gun moment but A24's clearly made a different strategy work and they're breaking through all the time and so uh it's justifying increased investment. Um, yeah.
3:03:06
Uh, another Perplexity news, they they they did the thing that we've been talking about, like you can now travel, search, and book on, uh, on Proplexity.
3:03:15
No scrolling 847 hotels and photos trying to spot a decent gym.
3:03:21
I asked, "Find me a hotel in Amsterdam with a serious gym.
3:03:25
Walkable to conference venue use under €300 per night.
3:03:27
Result, perfect recommendation.
3:03:29
The exact hotel I actually use."
3:03:31
Could you actually click book in the app? I think so.
3:03:33
And so, they're definitely working on it.
3:03:36
And this is like an like an obvious uh uh agentic workflow, but Simon Taylor, let us know.
3:03:42
Were you act did you actually book and did you go through with the booking and was it easier than just going to the website or was it ser merely better search because uh I think people won't be fully satisfied until it's an entirely chatbased workflow and they don't need to do anything and they never get routed to another another website. Yeah.
3:03:58
Um David Sax has a little uh review of Mountain Head.
3:04:00
He says mountain head costume designer Susan Lyall on the all-in pod. It was very good source.
3:04:06
It was a very good source for research for me.
3:04:08
One of the hosts, Chamath Palapatia, went to the inauguration of President Donald Trump and he showed pictures of all the things he wore. I couldn't believe it.
3:04:14
He had a Lauro Piana jacket here and a Bruno brunell Coochinelli there.
3:04:19
He obviously really knew his stuff.
3:04:21
So, I mean, hats off to Very, very cool.
3:04:23
That said, it shouldn't take too much research to understand that capital allocators enjoy Laura Piana and yeah, it's good stuff.
3:04:34
Uh this is an interesting post by uh Ash Sanvi.
3:04:36
Uh uh so Anthropic just went from 1 billion in annualized revenue to three billion in annualized revenue in five months.
3:04:44
Crazy growth at this scale.
3:04:44
And uh Ash says I remember the days when Snowflake doubled at 500 million ARR in a year and people lost their minds.
3:04:51
And yeah, the numbers have gotten so big in the AI race that uh going from 1 to three billion is like what have you done for me lately? Claude, step it up.
3:05:03
But obviously, congrats to everyone at Anthropic.
3:05:05
We're having some anthropic folks on the show this this week. Fantastic.
3:05:08
Extremely impressive, but I don't know why that is super surprising.
3:05:15
It's impressive, but shouldn't be surprising if you're paying attention given the actual technology.
3:05:19
You mean that that just that how useful these tools are? Yeah.
3:05:22
If you just look at trailing trailing open AI, they have less of a they have less significant of a consumer business, but it's still very big in enterprise, loved by developers. Yeah. Yeah.
3:05:37
So, uh what else do we want to go through?
3:05:39
Uh Yashu Benjio has a new uh nonprofit research lab called Law Zero.
3:05:45
Uh Sharon Gaffer has the story in Bloomberg.
3:05:49
She's coming on the show soon.
3:05:50
And I thought this was interesting because I was I was wondering if like has anyone in AI safety actually just tried to use Isaac Azimov's three three laws of robotics to design a safer AI system?
3:06:03
Like it would be very ironic and hilarious if that was the the solution all along was just hardcode in don't hurt humans which is basically what the what the Isaac Azimov three laws of robotics are.
3:06:14
But of course, the the premise of the Azimov movies is and books is that uh even though they try to encode that, it still goes wrong.
3:06:21
Uh so there's still a little of an AI doom scenario, but uh he raised $30 million of it on it.
3:06:27
So congrats to Yosua and hopefully there's some good uh AI research that comes out of it.
3:06:32
And as we've seen, even if you don't believe in the AI doom scenario, the paper clipping, uh there's still a ton of other ways that AI can go wrong and have negative effects.
3:06:41
Even it's just creating overly addictive products or dual use technology.
3:06:45
There's a bunch of interesting the Manurian candidates and the and the sleeper agents that Anthropic discovered or or hypothesized AI stuckset. Yeah.
3:06:52
And so um I think this is worth funding.
3:06:55
I think this is worth uh worth researching, but you have to take it with a grain of salt and you have to realize the the full picture and the full dynamics of of geopolitics and the AI race before you actually go and execute against what uh one of these nonprofits is is saying.
3:07:10
I thought this post from Justine Moore was hilarious.
3:07:12
Have you seen the new Google AI feature? It's on Gemini.
3:07:14
It's literally on AI Studio.
3:07:17
You can probably find it on Google Ultra 1, dude. It's on Flow.
3:07:21
It's a search labs original.
3:07:21
You can find it in Google Docs.
3:07:23
It will appear as a popup when you least expect it.
3:07:29
So ridiculous and so true.
3:07:29
Just put it just put it in the Google search bar if you care so much.
3:07:33
They just want to test their product market fit.
3:07:34
They want to see how hard they can make people work for it and still get adoption.
3:07:37
You know, they're built different. Yeah.
3:07:44
Um we have some some news uh separately. Toma Bravo Oh, yeah.
3:07:47
has announced this morning the completion of fundraising for new buyout funds totaling more than 34 billion fund commitments. Yeah.
3:07:59
Hit the Can we get the gong view, please?
3:08:01
Can we get the gong view? There we go. Nice hit, John. Toma Bravo. Nice hit.
3:08:06
Uh and and notably, uh they softcircled 1.
3:08:09
8 billion out of the 34 billion for Europe. Oh, interesting. So, there we go.
3:08:14
Uh you know, not get ready if you're a if you're a software company over in Europe, you might have a buyout is good but not great. Yeah.
3:08:23
If you're in need of transformation on optimization, get ready. Yeah.
3:08:28
Good to see private equity finally finally raising some real money. Yeah. You love to see it. getting some real size.
3:08:33
Uh, in other news, uh, open evidence, the Sequoia backed AI medical assistant is reportedly raising a hundred million or $3 billion valuation just months after its $75 million series A at 1 billion.
3:08:46
Uh, GV and Kleiner Perkins are in talks to lead the round, though details are still being finalized.
3:08:50
As soon as it's finalized, got to have the CEO on the show.
3:08:53
Some of the investors, it' be interesting.
3:08:55
Uh, I I I am very interested in this like the the the the vertical, it's like vertical SAS, right?
3:09:01
uh the niche verticalization of the platform uh layer.
3:09:03
Everyone's agreeing with like value acrruel at the application layer.
3:09:06
The question is like how many applications will there be, right?
3:09:11
Will there be five or 10 or 50 or 100?
3:09:14
There seem to be a lot of companies getting into the unicorn territory.
3:09:16
How many will make it through and win? Yeah. But it's all exciting.
3:09:20
Also, Chime has just launched their IPO road show.
3:09:22
Dan Primac has the story in Axios.
3:09:24
uh market clearing order inbound a $9.
3:09:28
clearing order inbound a $9.1 billion market cap if it prices in the middle versus the 25 billion market cap valuation VC backed unicorns are maybe are finally done clinging to their zer era valuation seeing this more and more and we cover taking their
3:09:43
medicine calls out I think they bid it up to 12 billion or so during the road show and pops up to 15 billion on IPO day fair value is in the high teens is his point of view yeah uh but we saw this in the information a lot of private companies are, you know, done with their their their venture journeys. They're
3:09:59
They're ready to go out into the market as soon as the IPO window is open just enough to get through.
3:10:06
And so they might take their medicine, they might take a slight down round going when they're going out, but then uh historically that's that hasn't been that bad in letting them actually perform once they get into the market and go public. So good luck to them.
3:10:20
We should have lesson on talk about this next one to discuss this next post from Bakate. Very exotic sounding.
3:10:28
He says, "Cluey intern son or VC scout daughter."
3:10:31
Uh, which is I love that Roy is in the comments immediately.
3:10:34
Let me get back in the comments. We got to have Roy.
3:10:37
We got to have Roy back on to get the update because he and the team seem to just be wilding out right now. It's actually insane.
3:10:44
I see again I I'm starting to feel like a bit of a boomer cuz I see some of their exchanges and this has to be I'm like there's no way this is real.
3:10:54
Like there's no way um uh there's no you know it can't possibly be real.
3:10:59
But I don't think they ended up hiring 50 interns. Yeah.
3:11:01
But it seems like they have a lot.
3:11:03
Got to have them back on uh to break it all down.
3:11:05
We should have all the interns on.
3:11:07
We should have him with all the interns standing behind him and they can just shout answers over each other. loudest intern wins.
3:11:13
He had an interesting So, uh he he had a post that went fairly viral yesterday.
3:11:21
He was quoting somebody who said, "What genuinely pisses me off about younger founders or just new people getting into startups is how obsessed they are with raising." Goes on and on. Roy said that. No, no, no.
3:11:30
Roy quotes that and says, "Hot take founders need to focus more on hype chasing." Okay.
3:11:37
Startups don't live and die by a product being 5% better.
3:11:39
they die because of lack of money or delusion.
3:11:44
Hype chasing helps with both.
3:11:44
I don't know how hype chasing helps.
3:11:47
Yeah, you still got to build a product, but distribution is really important.
3:11:49
And so like you can he said inflated revenue is still user is still revenue.
3:11:52
Users who pay out of curiosity are still users and good engineers who are down to interview after a cool launch.
3:11:58
Video are still good engineers.
3:12:00
Viral moments are not so easy to come by and the potential upside of making the most of them is higher than you think.
3:12:06
I like this because like it's it's it's it's a debatable point.
3:12:10
Roy, you know, his story is clearly going to break one way or the other.
3:12:12
Um it'll either be a breakout success or kind of a shot.
3:12:16
He he had another post that I saw where he said he's paying founding engineers like hundreds of thousands of dollars in cash because he said that he can just raise infinite amount of equity.
3:12:27
Uh which is built different.
3:12:31
He's just built different. Um different. And uh yeah.
3:12:32
Uh I'm I'm just interested to follow on.
3:12:37
I'm rooting for him despite him being controversial. Yeah.
3:12:40
I want to see him succeed.
3:12:40
Uh I think he is he's very good at causing controversy like that.
3:12:46
Even just that the idea of like, oh, we're not giving equity, we're giving all cash.
3:12:49
Like that's a controversial approach and some equity, but he's just like, I value I value equity way more.
3:12:55
I'm just going to pay, you know. Yeah.
3:12:56
But he's selling the equity at high value.
3:12:58
It's like you could do that with the shares.
3:13:00
It's it's very odd, but it's like good bait.
3:13:01
No, I mean if he says my if he believes that his equity is worth a multiple of what?
3:13:08
Yeah, but he's selling it to pay the cash.
3:13:10
He's he's not making money.
3:13:10
He has cash in his bank account today.
3:13:12
He says I'm in a forex in a couple months. Yeah, makes sense.
3:13:18
Anyway, interesting post from Eperis.
3:13:20
We haven't had them on the show yet, but we have to at some point.
3:13:21
Uh so quoting uh defense index unstoppable China can produce 500,000 FPV drones every month and scale up to 700 in wartime which actually feels like roughly the same scale as as Ukraine maybe within an order of magnitude which is um shock it's actually kind of lower than I expected but it's obviously a lot and Eperis says this is not unstoppable. Yeah.
3:13:46
So Ukraine is doing uh just under 400,000 a month right now at their current rate.
3:13:50
But they're doing that basically in a cave with scrap, you know, like China has all of the on, you know, so I imagine uh I imagine China could actually do well beyond this. Yeah.
3:14:03
It's also a weird narrative because like in what scenario like are these FPGV drones can they get over the Taiwan Strait?
3:14:08
Because like I believe they're pretty short range and so it's it's more for like like what is the trench war scenario that would happen over there where these would be super relevant.
3:14:18
Yeah, it's interesting to think about.
3:14:19
They could have basically a bunch of floating docks that the FPV drives it and just boats.
3:14:23
I mean, especially if you can just put them into a shipping container and then move the shipping container.
3:14:28
So, it's like instead of an aircraft carrier, you just have a a shipping like a car.
3:14:33
Interesting thing about um Yeah.
3:14:33
So, so with Eperis, I'm interested to see how Eperis is actually doing against these FPV drones.
3:14:40
Saurin yesterday said he hadn't seen an American electronic warfare.
3:14:44
They could really reliably take down FPV drones.
3:14:46
I'm sure I'm sure Eperis can certain conditions and it should be a part of a broader system. Yeah.
3:14:53
So they say that their their mission is to overcome the asymmet as asymmetric challenges inherent in the future of national security.
3:14:59
Uh and so good luck to them.
3:15:01
You know, we want we we want we want everyone to win here who's working for America.
3:15:04
And uh we should note uh earlier today Chimoth uh was sharing uh an image of a of a I forget what machine this it's not a scale you I think you hold these devices that like an inbody. Yeah.
3:15:19
That that sort of track your body fat.
3:15:21
He says hot girl summer bring it.
3:15:23
She's putting up 11 and a half% body fat. Pretty good. Uh at uh allegedly 6'2.
3:15:31
And uh Delian responded and saying, "Are you trying to get your body fat percentage as low as the IRRa of anyone that invested in your 2021 spaxs?"
3:15:39
Fortunately, that would be I don't think it's possible to go negative uh on the body fat uh front, but uh then Chimath made a very lewd comment.
3:15:48
Uh Delian fires back and said, "Brothers, this conversation is unbecoming of the high technology industry.
3:15:57
I propose we shift the conversation to what really matters, capital.
3:16:01
Would you both like to join TVPN today?
3:16:03
And Chimath uh unfortunately turned it down.
3:16:06
Uh so we didn't get here, but uh maybe in the future, but he's got a he's busy capital allocators.
3:16:13
I like everyone working together to maximize returns at all times.
3:16:15
Yeah, I I think we need to work on our pay-per-view format.
3:16:19
Get the boxing ring set up.
3:16:22
Imagine hitting this Imagine smashing the soundboard as two alligators just duped it out. I mean, yeah. Yeah. No better entertainment. It'd be spicy.
3:16:30
Um, but that'll have to be for another day.
3:16:32
Anyway, thanks for watching.
3:16:35
This has been a fantastic show.