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[Music] We came to feel the new [Music] [Music] [Music] [Music] Market clearing order inbound. [Music] 5. You're watching TVPN.
4:52
Today is Friday, June 6th, 2025.
4:52
We are live from the TVPN Ultra Dome, the temple of technology, the fortress of finance, the capital of capital.
5:01
Uh, we have an exciting show for you today, folks.
5:07
We're going to be continuing to react to the Trump Elon breakup.
5:09
I haven't seen a ton of new news, but we'll cover anything that's popped up most recently.
5:16
There's no facts, but there are vibes.
5:18
Yeah, there are there are definitely vibes. Plenty of them.
5:22
Uh, but I wanted to give a little recap on what's happening uh what happened this week on TBPN because we are launching a new product.
5:30
Every week we will be doing a uh a recap video uh uh trying to boil down the 15 hours that we produce into something that's you know 1 hour, two hours, something like that. Yeah. More digestible TVPN.
5:43
Uh and so uh this week what were the top stories?
5:48
What were the most interesting things that we learned?
5:49
One interview the the the Ukraine drone attack that was huge.
5:55
uh Operation Spiderweb, a whole ton of of uh drones were smuggled into Russia uh in uh shipping containers.
6:02
They emerged and uh went out and attacked bombers.
6:08
We had Saurin Monroe Anderson from Nuros on the show to uh to break that down for us.
6:14
We also talked to Connor Love at Lightseed who does a lot of in uh defense tech investing.
6:16
And of course, a couple weeks ago, we had Eric Prince on the show, the founder of Blackwater, and he had kind of predicted that the uh Ukrainian military was perhaps underrated and and we might be seeing like something like this in the future.
6:31
And so uh that was interesting to see to see play out.
6:33
So we will take you through those kind of interviews, recap some of those.
6:36
Then obviously we had the absolute meltdown between President Donald Trump and Elon Musk.
6:40
uh that unfolded on X and Truth Social.
6:42
The two uh leaders dueling dueling social platform. Exactly.
6:48
Uh and although it's a highly political story, there are big business implications.
6:54
You talking about what's going to happen in space between NASA, uh Boeing, different launch providers. Yeah.
7:00
The implications for Tesla, SpaceX, Neurolink, even the Boring Company, right?
7:06
Many of Elon's businesses are heavily regulated. Yep.
7:08
And uh the potential impacts are substantial. Yeah.
7:14
Then we also uh had had uh some earlier stage founders on the show.
7:17
Uh Roy from Cluey came on and went pretty viral. Put on a show.
7:22
You're surrounded by journalists. Hold your position.
7:24
Cli is a uh is a is a service help you cheat on everything.
7:29
Um we got to actually try the app.
7:31
Someone was asking was was pushing us to try it and see how good the product is.
7:35
Um, but regardless of the product, he's also a phenomenal marketer and he came on and put on an absolute show and he's printing apparently. Yeah, he's doing great.
7:44
He can't spend all the money that they're bringing in.
7:48
And so we'll give you an update on Roy and see where that business is.
7:51
And then Keon uh from Nucleus came on and to launch Nucleus Embryo uh which he calls the first ever genetic optimization software that helps parents give their children the best possible start in life.
8:04
Quite a lot of controversy there on the timeline this week.
8:06
A lot of people hate it, a lot of people love it.
8:08
Um, and we'll let you kind of decide for yourselves.
8:13
And then we had a whole bunch of AI experts on the show from Google, OpenAI, and anthropic got to the front leading edge of the debates around AI AI, LLM. Poor John.
8:23
Yesterday, you were fighting as long as you could.
8:26
You didn't want to talk about uh drama. You got dragged into it.
8:32
Uh, but we did get some great coverage from Mark Chen at OpenAI as well as Schol over at Anthropic.
8:38
Yeah, it was a lot of fun.
8:40
Uh, anyway, let's go into ramp. Time is money. Save both.
8:44
Easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place.
8:47
Um, no, let's go into the secondary reaction to the Trump Elon uh meltdown.
8:53
There's first we can call out Tesla's up 5% today. Okay.
8:58
After being down, they they were down 17 or they closed down 12.
9:00
Uh, I mean they're down 12 and a half% over the past five days.
9:05
So, still not a great week. Okay.
9:08
Just hovering on that hovering under that one trillion dollar market cap. Got it. Um, but could be worse.
9:15
And, uh, there's, you know, the timeline is still filled with Trump Elon Post, Jason Calacanis from the All-In podcast.
9:21
It's a must listen episode this week.
9:24
This is this is what they were built for.
9:26
Um, he posts just a dejected meme.
9:29
Although, I don't even know.
9:29
Is this for Mountain Head?
9:30
Is this a screen screenshot from Mountain Head?
9:32
This uh this post by JCAL um uh with the Yes.
9:38
How that I think is the character that JCL most uh sort of sees himself and that is the uh the friend in the group that um it's funny.
9:46
So this friend in the group has like a meditation app and one of the other characters acquires it for two billion to get him into the billion dollar club.
9:55
Wait, it is the Jay Kellen investor in Colin.
9:57
That's hilarious based on them. Wow, that's awesome. Congrats to them.
10:01
Um, Fred Delicious says, "Reminder that this all started with him carrying a sink."
10:08
Shows Elon carrying the sink into X and then one thing led to another.
10:10
I got to say, he looks younger and happier in that photo than we've seen him in a while.
10:16
It was It was Politics will wear on you. Definitely ages.
10:18
You've seen those photos of like Barack Obama before and after.
10:22
It's like eight years and he's like gone cray brutal.
10:25
Uh this was this was a fascinating this was genuinely a fascinating disc when we were live yesterday we were covering in light of the president's statement about the cancellation of my government contract SpaceX will begin decommissioning its Dragon spacecraft immediately.
10:38
We had Delian re react to that.
10:40
Um and uh some random tiny account that just looks like I guess they're verified so it's a real account.
10:48
Says this is a shame this back and forth.
10:50
You're both better than this.
10:52
Cool off and take a step back for a couple days.
10:55
Uh Elon says, "Good advice."
10:55
Okay, we won't decommission Dragon.
10:58
It's so great that he's just reacting this.
11:00
I mean, the funniest thing about all of this is that um you know, it was like it was like this is the only new story.
11:06
Like you have to react to this.
11:09
This is the most important thing.
11:10
And I was like, "Oh, like we get the Financial Times every day.
11:13
Like if this is a business story, like it should be on the cover, right? It's not."
11:18
The top the top the top story in the financial times today is Trump and uh Cinping dial down rhetoric and agree to new round of trade talks.
11:26
US president says meeting will be soon state invitations extended.
11:30
Investors remain cautious and and then also there's a story in here from the failed startup builder AI owes cash to intelligence firm and litigation lawyers.
11:39
And so um you know the the global economy marches on while uh yeah I mean there was something else the kings of drama in in I mean the fact that uh somebody was calling this I I forget the account but they said we effectively had the political equivalent of a tactical nuke yesterday and the S&P is up almost 2% over the past 5 days for it.
12:04
Let's give it up for the stock market.
12:08
Two uh individuals coming on, two guests coming on to talk about we didn't even talk about our white suits.
12:14
The circle IPO circle IPO has been tremendous success but uh you know very very excited IPO window is open at least if you're a pure play stablecoin company.
12:26
I believe circle is now valued at about a third of Coinbase. Yep.
12:31
which is um fascinating considering that a large amount of uh Circle's revenue actually goes to to Coinbase.
12:40
Um but that's uh great for Circle and the whole team and good for the market.
12:46
And I'm very excited to talk with uh Jeremy in a little bit.
12:52
And if you're designing the next product to that you plan on taking public, go to figma.
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com, think bigger, build faster.
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13:01
Uh Simone says, "Deeply hope someone remembered to put Luke Ferdor on a chopper out of Saigon."
13:09
Let's hear for Luke scroll respector.
13:12
You know, he's going to be on to something bigger and better soon.
13:13
Out of the swamp into the valley at this point.
13:18
I think he could do 100 on 500 out the gates.
13:22
Like I think he could get that round done.
13:24
I think he could get that round.
13:26
He's like somehow like I don't know too humble to do. No, I know.
13:29
He's a humble humble guy. But he really could.
13:32
All that matters is that he could. So it'd be amazing.
13:34
Um, and so there's a couple poly markets that we should pull up.
13:38
I I have a screenshot here, but I'd like you to pull up the bigger news.
13:41
We got to give it up to the market team.
13:43
Poly market is the official prediction market of X. Very exciting.
13:48
We had heard something like this was in the works, but I didn't.
13:49
It went back and forth because there was a Koshi rumor and then it wound up.
13:52
No, it wasn't a Koshi rumor.
13:54
Khi preemptively announced that they were and then X retracted it and X from the main account said we are not partnering with Khi. Okay.
14:04
And then a week later they announced this big partnership with with Poly Market.
14:07
So congratulations to the Poly Market team.
14:09
I'm super excited to see how this gets integrated into the product.
14:13
So I want you to pull up will Elon Musk on unfollow Donald Trump before July?
14:18
That's an interesting market.
14:20
Also, there's a market on will there be a reconciliation by the end of the week, I think.
14:24
And then the other interesting one is um does this make it more likely that Elon becomes stays CEO of Tesla or less likely?
14:32
I saw the market spiking yesterday to above 20%.
14:37
Seems like he might have more time on his hands to focus on Tesla.
14:38
So, we'll see how that one goes.
14:40
So, pull up some of those poly markets and I'll read some more posts.
14:42
Um uh there's a whole bunch of silly posts in here.
14:46
Elon Musk rushing home to have a generational crash out in the and somebody put a cybert truck I guess in GTA or something. That's fun.
14:52
Uh who gets custody of Joe Rogan?
14:54
I think he's the perfect moderator for all.
14:57
I mean there were so many of these extremely viral.
15:02
Uh you had who gets custody of David Sax who gets JD Vance of JD Vance.
15:07
Who gets uh JD Vance actually came out yesterday, you know, was pretty clearly picked aside.
15:12
Um which I think is is good, right?
15:15
you should probably yeah, you know, side with the guy that you're in the White House with and then work behind the scenes to kind of massage things hopefully, improve the uh improve the relationship.
15:25
Uh I mean that the the coverage of this has just been fascinating to me.
15:29
So the Wall Street Journal has an entire entire article dedicated to just one post quote quote.
15:36
Okay, so yeah, thank you guys.
15:36
Uh let's let's look through some of these poly markets.
15:40
Uh, will Elon Musk create a new political party by uh December 31st? 24%. I wonder.
15:47
I mean, he could put up the same amount of capital as some of the major parties, right?
15:53
But when was the last time America had a third party?
15:58
Like, it seems unfathomable.
16:00
And also, I was talking to somebody about this who had one of my friends was predicting that the Elon Musk and Trump relationship would sour.
16:07
And I was like, I don't know, maybe it'll wind down soft.
16:10
I was kind of I was a soft landing guy.
16:12
I look really stupid in hindsight.
16:14
Uh but uh but he was but he uh but I was I was wondering like just in terms of like not necessarily political capital, but like popularity like who's more popular, Trump or Elon? I think Trump, right?
16:27
Wild wildly more popular.
16:30
Wildly more popular just generally, right?
16:32
And they do polling on these things.
16:34
Um because yes, you have the tech people that like Elon, but that's a much smaller segment of the market than I think there were a lot of folks like one of the weird things about the election was that like you would have like a tech guy voting alongside uh like you know like a a MAGA supporter from 2016 who who skeptical of Elon.
16:56
Trump is a very successful social media entrepreneur, right?
16:57
He has a billion dollar multi-billion dollar social media app.
17:01
He has two and a half billion in Bitcoin treasury in that company now I think.
17:05
Um I mean yeah you you you called this morning or or texted I don't even remember at this point but you're you you know your big question was you know who's more AGI pill and you had you know a pretty clear answer.
17:19
You said that um your thesis Yeah.
17:21
if if I can if I can um spell it out is that Trump uh is not concerned with the deficit because he read AI 2027. He's a fast takeoff guy. Yeah.
17:34
And in his mind, he's like with uh you know, AGI, you know, just right a quarter away.
17:40
Uh it's very likely that the the 2028 deficit and the federal sort of debt broadly just immaterial. Yeah. Immaterial.
17:48
And you just play it out, right?
17:50
So So yes, there's a huge increase in in spending and there's not a commensurate increase in massive in tax returns, right?
17:57
And so the government is going to be spending more money than it's making and that's going to result in in a budget deficit and over time that grows and grows and grows and we're going to be spending trillions of dollars on interest.
18:09
But if you truly believe in AGI in super intelligence, yeah, you're going to see 10% of electricity being used on AI.
18:19
you're going to see an incredible amount of economic value created by these AGIS and the government will be able to tax that like any other income like the rest of the economy that will drive you know Sachi Nadella said hey I'm waiting for GDP to grow 10% a year y if that happens if you believe that happens if you're
18:36
AGI pled you don't need to worry about the deficit and so I think Trump's a stargate guy right he is he's big announced stargate right and so I think what this reveals is that potentially Trump is more agel than Elon it's very possible You wouldn't expect that to have been the result of this dust up, but I think that's what we learned. Totally. I think Totally.
18:54
I think that's definitely a big takeaway.
18:57
Definitely a big takeaway. Wild times.
19:01
Uh the the Wall Street Journal has a whole has a whole write up, but we've covered most of this.
19:04
Uh once allies, they had a public flaring out after Musk criticized Trump's legislative agenda.
19:10
Musk attack attacked Trump, alleging his name appears in the Epstein files and suggesting he should be impeached.
19:16
Trump responded by threatening to cut off government contracts to Musk's companies.
19:20
Um, just six days ago, senior Trump aids swallowed their irritation with Elon Musk and planned a chummy Oval Office sendoff to him.
19:28
They briefed the president on allegations of Musk's drug use.
19:32
So, Trump should be ready to defend the billionaire if reporters raised the issue at his goodbye event.
19:36
As late as Wednesday evening, Trump played down any conflicts with Musk in a meeting with Republican senators.
19:42
According to people familiar with his remarks, even though the billionaire had spent the past few days disparaging the president's legislative agenda over the weekend after Trump dumped Musk's ally as the head of NASA.
19:54
So that feels like maybe one of the turning points in this whole the whole kurfuffle.
19:58
Um the president made it clear that he wasn't planning a high-profile confrontation with his former adviser.
20:05
According to a person who talked to the president, that goodwill disappeared on Thursday, 13 minutes into an Oval Office meeting with German Chancellor Frederick Ms.
20:13
The poor German chancellor just sitting there and being like, "Wait, like this is supposed to be about Germany.
20:20
I I I'm here to pitch Germany and now you're talking to me about now now you're talking to me about Elon Musk drama."
20:27
Like I just want to talk I just want to talk about German stuff cars.
20:32
Mercedes or how are we going to sell more Mercedes in America? Yeah. Let's keep it focused.
20:37
Let's not put the attention on Tesla.
20:38
Let's talk about the TYON.
20:41
How are we getting more of those over here?
20:45
How we how we getting EQs over here? Yeah. Yeah.
20:47
Anyway, Trump laid out his frustrations at the Musk, marking the start of a whirlwind day in which two of the world's most powerful men went from f friends to foes.
20:55
By Thursday night, Trump had publicly toyed with cutting off government contracts to Musk's companies, said the billionaire went crazy and suggested that he is suff suffering from Trump derangement syndrome.
21:07
Uh, it is it is it was very hard as an ex user to actually understand what Trump was saying because the the the the truth social screenshots were so easy to fake and and the community notes was like a little bit slower.
21:19
Uh, and so uh it was always hard to understand.
21:22
you kind of had to read for it and and kind of read through the lines and understand, okay, this is clearly a joke.
21:27
Um, but uh Elon Musk kind of closed it out by saying whatever, keep the EV solar incentive cuts in the bill, even though no oil and gas subsidies are touched.
21:35
Very unfair, but ditch the mountain of disgusting pork in the bill.
21:39
The in the entire history of civilization, there has never been legislation that both big and uh that both big and beautiful. Everyone knows this.
21:49
You either get a big and ugly bill or a slim and beautiful bill.
21:53
Slim and beautiful is the way.
21:53
And so Elon's kind of closing it out with like what he wants to do.
21:57
Adapting Donald's posting style there. Yeah. Yeah.
22:01
I do I do wonder like like how how big of a deal is the is the is the government spending thing?
22:10
Like we've we've just been hearing rattling about these like the deficit hawks have been pushing on this for decades.
22:17
Like going back to like the Bitcoin people, right?
22:19
Like like when did Michael Sailor start talking about this?
22:23
Like and so it's a little bit of like uh whenever I hear tech people say this, it's always like a little bit of like boy who cried wolf.
22:29
I I get I get convinced very easily by Joe Wisthal saying like we issue debt in dollars, we print dollars.
22:35
Like we could inflate the debt away.
22:36
There's like a million ways out of this and like America's still the number one economy.
22:41
And I'm just kind of like okay.
22:41
But this chart is deeply concerning.
22:44
It's the kind of chart you want to see in an investor update. Yep.
22:48
Not, you know, tracking uh debt, right? It's it's exponential. Uh and yeah, it's rough.
22:57
Anyway, um anyway, let's tell you about Vanta.
23:01
Automate compliance, manage risk, improve trust continuously.
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Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program.
23:12
Um, the Wall Street Journal goes on to write, "The Trump Musk blowup was long predicted.
23:20
Even people close to both men privately believed that their relationship was destined to implode, but the fast-paced ratat escalation still came as a shock to a White House that has grown used to curveballs."
23:30
And a president who often defended Musk as his aids grew frustrated.
23:34
White House officials and other allies of the president spent the day refreshing their social media feeds, watching as the situation escalated, and texting Musk's post to each other.
23:42
It was a matter of time before all this shattered because two giant egos can't be there together, said Mark Short, who is chief of staff to vice president Mike Pence.
23:51
It's hard to imagine uh seeing it collapse as fast as this, but you can't be surprised by this.
23:55
Mike Pence went the only the only person that that had the truly perfect call on it was a guy working analyst.
24:04
I got in trouble once before for calling a 24year-old a kid and I believe he's exactly 24. Oh no.
24:11
So, um, I mean, wise beyond his years.
24:14
He's clearly has the chops of a grizzled 60-year-old political analyst.
24:17
And so, congrats to him for the perfect call. The perfect call.
24:21
You didn't see it yesterday.
24:23
Uh, uh, I think it's working.
24:27
The account is working analyst on X.
24:29
And, um, they crushed it.
24:29
John Production is asking you to move that out of your screen, by the way. Um, um, thank you guys.
24:36
and uh he basically called back in October of last year that that uh the partnership would result in the largest Twitter battle in history.
24:46
Uh and yesterday was it was a very chaotic crazy day on X. It it certainly was.
24:52
It's very entertaining times.
24:56
Uh the Fiser has reverberated inside the White House.
25:00
Musk's top aid, longtime Trump adviser Katie Miller, left the White House with him last week, according to people familiar with the matter and now works with Musk.
25:07
Miller, who held um uh who held special government employee designation, was with Musk at almost all times in the White House.
25:14
She didn't respond to requests for comment.
25:16
Her husband, Steven Miller, is one of Trump's most loyal invisible aids.
25:18
He has defended Trump's legislative agenda and from Musk's broadsides in recent days, and Musk unfollowed him on X this week.
25:25
Um, the Millers have spent had spent extensive time with Musk, even outside the White House.
25:30
The public clash between Musk and Trump also jeopardizes the Department of Government Efficiency.
25:34
The billionaire's trademark cost cutting effort, Doge affiliated staff, some of whom were responsible for pushing out thousands of federal workers texted one another on Thursday about whether they would be fired next.
25:45
According to administration officials, the blowup Thursday caught top White House aids offguard.
25:50
Shortly before noon, Trump sat down in the Oval Office with MS to chat about predictable topics.
25:56
The NATO alliance, the war in Ukraine.
25:58
There really is so much else going on, too. It's absolute chaos.
26:00
Uh, it took about 13 minutes for the president to unload about his billionaire benefactor, expressing irritation that Musk had been critical of his legislative agenda as too costly. It started gently.
26:12
"I've always liked Elon," said Trump when asked about Musk's criticism of his big, beautiful bill.
26:18
I'd rather have Elon criticize me than the bill.
26:20
But before long, Trump ratch ratcheted up his rhetoric.
26:22
Elon and I had a great relationship.
26:24
I don't know if we will anymore, Trump said.
26:26
And yeah, there's this interesting take that like I can see them recovering.
26:34
It's bad right now, but they've dialed it back.
26:36
I'm glad uh I'm glad they've both at least dialed back the posting today.
26:40
Yesterday you could basically refresh and see one of them firing, but today is the uh 81st anniversary of D-Day of the landing.
26:49
Um and and we got a fantastic poster from Anderol.
26:52
Uh we should share a picture once we take a good one, but they sent us one and so thank you to the Anderol team for sending that over.
26:59
Um anyway, let's tell you about linear.
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Is that a Is that a golden retriever I hear?
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Nothing makes me bark like efficient product management and product planning.
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And that's what you get out of linear. I love linear. It's great. Yeah.
27:22
When John's using linear, this is all you hear. This is getting crazy. It's amazing.
27:32
There are some posts from Donald Trump here.
27:34
Elon, this these are from Truth Social and they've been posted in the Wall Street Journal, so I believe that they're real.
27:38
I I'm very skeptical of the screenshots I see.
27:41
I was actually pretty disappointed with people just just making uh I guess I shouldn't be too disappointed with fake news, but it's nothing new.
27:50
Yeah, nothing really new, but um but yeah, it's it's good.
27:55
Um Elon was wearing thin. I asked him to leave.
27:58
I took away his EV mandate that forced everyone to buy electric cars that nobody else wanted, that he knew for months I was going to do. And he just went crazy.
28:05
The easiest way to save money in our budget, billions and billions of dollars, is to terminate Elon's governmental subsidies and contracts.
28:13
I always I was always surprised that Biden didn't do that.
28:15
Is there an EV mandate that forced everyone to buy electric cars?
28:20
Like I don't remember that ever being a thing.
28:26
I mean, I thought it was just subsidies and you would just get like $7,500 if you bought an electric car, but I don't remember there ever being a mandate.
28:34
Maybe maybe there's a bunch of state and local subsidies at the city level across a bunch of the different companies.
28:38
But I guess there's like EPA stuff where automakers need to have a blended MPG across their entire fleet.
28:46
And so you see that that funny there's that like Aston Martin car that they So I can give a quick breakdown of the different companies.
28:54
So, with SpaceX, they have 10 different NASA awards, a bunch of DoD uh launch and then lander awards through 2031.
29:03
There's $22 billion roughly under contract.
29:07
Trump could put pressure on uh the Pentagon, NASA to kind of slow roll things, right?
29:13
There's there's a bunch of or, you know, push push them to give contracts to rivals like Blue Origin, ULA, etc. Yeah.
29:20
Uh Tesla, they have clean car credits.
29:23
Um apparently it's about 1.
29:27
2 billion a year in potential lost EV tax credits.
29:30
Trump's saying that like uh like I always was surprised that Biden didn't do it.
29:36
I thought that Biden was like very much in the process of doing it.
29:40
And so uh part of the reason why Tesla stock like moon so much after the election was that there was the expectation that those wouldn't be cancelled.
29:47
But yeah, like that that that was that was in the plan before. Yeah.
29:52
Um, Starlink already has up to three billion in rural broadband subsidies. Oh, really?
29:57
That that that are kind of pending.
30:00
Um, uh, and then, uh, this is smaller, but both Neurolink and the Boring Company obviously are in high regulated uh, yeah, FDA and then Department of Transportation and then a bunch of other um, so you don't exactly want enemies in the in the White House.
30:16
It's like basically Elon has more exposure than anyone on Earth to a hostile government, right? Yeah. Yeah. Yeah.
30:24
Um which is why I just I I seriously hope um it doesn't matter if you like either of them.
30:29
Uh you know, I I hope they can work it out.
30:34
Uh because I would hate to be sitting here doing moments of silence for any of these companies or their shareholders. Or their shareholders. That's right. For sure.
30:43
Um, Trump was taken aback by Musk's escalation.
30:46
According to his adviserss, Trump told advisers he didn't believe he was harsh about Musk in the Oval Office and he was surprised at how aggressive Musk became.
30:54
Trump's aids spent some time Thursday trying to figure out m what Musk's goal was.
30:59
The president told advisers Musk was just being a child according to White House aid.
31:05
A according to a White House aid around the same time Trump walked into a White House meeting with the Federal Fraternal Order of Police and made remarks.
31:12
He ignored reporters questions and didn't and didn't mention Musk.
31:16
White House staff huddled with Trump in the early evening.
31:18
Um, yeah, I remember that that I I remember seeing a clip of he's he's there to celebrate the police department and they're immediately asking him about about Elon and uh he has to move on.
31:29
Uh, as of late Thursday, the shiny red Tesla that Trump purchased during a high-profile photo op with Musk was still in its parking lot just yards from the Oval Office.
31:38
White House aids joked Thursday evening that they hadn't decided what to do with the vehicle.
31:42
So interesting to see where that goes. What a saga. What a sag. Wild. Back to work. Back to build.
31:50
It's time to build, baby.
31:52
I will remember yesterday forever because we were live sitting exactly like this.
32:00
And I could tell you had no real idea of what was going on.
32:03
And I was coordinating with like 50 different people, the production team, other people were texting me, I'm too agi.
32:08
We were getting angry messages.
32:11
I'm so ag I I care about being like, I do not care about AI. And I'm like, I do. I do.
32:19
I actually just want to talk to and shut up.
32:23
Uh but um AGI is it this is the situation of the of the the the steamroller and these guys are now now it's Elon and Trump picking up pieces of legislation in front of the steamroller that is artificial intelligence. Yeah.
32:37
Well, uh, in other news, Neysphere, the startup behind, uh, AI coding tool cursor has surpassed 500 million in annualized revenue and has raised 900 million in series funding from Thrive, Excel, Andre, Horitiz.
32:57
Absolutely huge week for cursor.
32:57
Very interesting media roll out here.
32:59
So, well, this round has gotten announced like five times by now. That's true. Okay.
33:06
So, that's why Kate Clark at Bloomberg is writing about the the the revenue instead of the raise because the revenue milestone is the new data point and we already kind of knew about the raise.
33:17
Um, but there were a bunch of stuff.
33:19
I mean, there was this Bloomberg piece.
33:20
Uh, the CEO of Kurser went on Ben Thompson and did an interview that was fantastic and Ben spends half the time just marveling at how young the founder is. Yeah.
33:29
And trying to kind of relate because No, it's so crazy.
33:30
Think about it felt like 6 months ago we were talking and people were saying Sam Alman should be Gen Z, right?
33:38
Like where's where's our sort of Gen Z?
33:41
Where's our Gen Z decorn?
33:43
Where's our Gen Z decacorn?
33:46
I mean, Alex Wang, but but but there just aren't as many and it just it did feel like Gen Z was taking a while to find its footing in the in the private markets.
33:55
uh find find their footing and get to a billion dollar revenue run rate. Let's go.
34:01
That's that that's the expectation in this.
34:03
And that the other data point, the two other data points, they're already being used by more than half of the Fortune 500, including Nvidia, Uber, and Adobe.
34:10
And they say this scale will help us push the frontier of AI coding research.
34:15
So, I want to know what's going on at the other at the other half.
34:21
Like, are the are the other half on windsurf or are the other half like just raw dogging their IDs?
34:27
I mean, they could be using I mean, there's so many options.
34:30
GitHub copilot, but they better be using some somebody uh Swix was saying earlier this week that GitHub Copilot is also at a at a million dollar run rate. Crazy.
34:39
Yeah, that that's a public company if it was if it was out in the market. It's pretty remarkable.
34:45
Um, but yeah, uh, Ben Thompson was talking to the the the cursor CEO and, uh, and they're talking about how he got into software engineering.
34:52
He's like, "Oh, well, like, you know, I was a kid and I wanted to build, uh, I wanted to build video games, specifically mobile games."
34:57
And, uh, and Ben Thompson's like, "This is a huge mark for like how young you are because there's tons of entrepreneurs that got into programming through video games."
35:07
Oh, I was playing, you know, like this was me, right?
35:09
I played Counter Strike Counter. I played Counter-Strike.
35:12
built a PC and then I would like modify the levels and modify the skins and the spray paints and like edit some config files and then eventually like scale up from there.
35:18
No, cursor CEO started with uh started with mobile games and he actually built one that was like really really viral and really successful among software engineers and so uh he's had a story account. Yep. Yeah. Killer.
35:31
What was their what was the activity in their Stripe account when they were in high school?
35:35
Yeah, that's the investment thesis.
35:37
I mean yeah it would have been a good one.
35:39
Uh, who was who was the first investor in cursor? I wonder.
35:41
We gota we gotta figure that out. But Neo was early. Oh yeah, Neo. That's right.
35:45
Um, uh, but Thrive, Excel, Andrew, Horowitz, and DST are all in this series C.
35:51
They raised $900 million.
35:54
David Tish was also super early.
35:56
David Tish, let's hear it.
35:58
Let's give it up for David Tish. Let's go. Round of applause. He wants to hear it.
36:02
He's not going to post about being early as much as the rest, but we we're going to we're going to talk about it. Absolutely. Absolutely.
36:09
And of course, um, Sam Bankman Freed also early into Cursor.
36:16
I thought it was Windsor, but it's cursor. No, it's Curser. Oh my god. Wow. SPF. What a what a picker. What a stock picker.
36:24
I really wonder like So, yeah.
36:26
Uh, FTX had a had a stake had invested I guess 200K. Oh, yeah. We heard about this.
36:34
It had like insane valuation, right?
36:35
insanely low valuation, but it was kind of rumored and the deal might have changed hands a few times or like the stake might have changed. Yeah.
36:41
They invested 200k and they sold the position for 200k. Yeah.
36:43
I wonder how wellated 5x fund, right?
36:49
If that if if you just looked at the FTX private markets like startup investments as a VC fund, like they probably did pretty well. What was the other one? They had a ton. Oh, the Anthropic.
37:00
Yeah, they had a huge stake in Anthropic.
37:01
They were also in Worldcoin. Oh my god. Wow. Damn.
37:06
Should have just should have just raised a fund, not not had to deal with any of the dealing with crypto.
37:10
Should have just gotten out of crypto. Pivoted to crypto to AI. Could have done it. Yeah.
37:16
Or told FTX users, "Do you want to be in part of Sam's slush fund?" Yeah, that was rough.
37:22
Instead of Anyway, I think the story with him is not over.
37:26
We'll see as as it evolves.
37:26
Apparently, he did get in a ton of trouble for that podcast he did from jail.
37:29
Apparently, you can't just podcast from jail.
37:31
Yeah, that that was wild. Crazy. You did that.
37:37
Anyway, um did you see this post?
37:37
Says sales tax on autopilot.
37:40
Spend less than five minutes per month on sales tax compliance. Numeral HQ.
37:43
The golden retriever gets on numeral. That's true.
37:49
Uh you want to go to Will or?
37:52
Yeah, I just thought this was hilarious.
37:54
Will uh obviously of OpenAI fame says, "This was the motivation I needed. Thanks SFO airport."
38:00
It's just it's just like billboard. Win the AGI race.
38:05
Dominate the leaderboard. Win vibes.
38:07
He's just standing seriously in front of it. Made me laugh. Win the AGI race.
38:12
Don't care about the budget.
38:12
Don't care about the pork.
38:14
AGI does not concern itself with pork.
38:16
The lion does not concern himself with deficit spending. Absolutely not. Absolutely not.
38:23
Um, we we can skip this semi- analysis post because of course Dylan Patel from SE semi- analysis is coming on the show today and we will ask him about Jensen's new math rules and have him break it down for us.
38:33
Uh, this is a very fun post.
38:36
But anyway, let's move on to uh, Uber is evaluating stable coins potential for payments.
38:40
uh CEO Darra Koshi says uh yeah I wanted to throw this in here mostly so we'd remember to ask Jeremy about that like all these different massive companies looking to adopt stables. Yeah. Yeah.
38:54
Uh apparently payroll companies should uh might be adopting stable coins for uh for like all of these different wire transfers that they do.
39:05
um both to speed up uh payroll, which is already pretty fast, but there's also a whole bunch of uh uh stable coins that the if you put stable coins inside a payroll company, uh you should be able to earn yield on the on the the the like the the all the dollars that you're holding.
39:26
Now, you don't actually hold that many dollars just from running payroll because it comes out of the company's bank account, goes for like one day into the payroll company's account, and then it goes out to the employees, right? It just gets split up.
39:37
So, there's not actually that much float there.
39:38
But for tax withholdings, there actually is a ton of float because every paycheck you're taking out $1,000 and you're going to send it to the IRS, but you send it to the IRS nine months down the road or six months down the road on average, right?
39:52
Because you're you're you're you're waiting.
39:54
you you only pay taxes once a year.
39:56
So then you know half the year you're like on average sometimes it's you're holding it for 12 months, sometimes you're holding it for one month, but on average that's like six months of cash and it's a lot.
40:04
And so so right now that's that's held in accounts, but um with stable coins you could potentially get more direct exposure to the uh to the underlying treasuries and so there could be some sort of boon for stable coin pro or for both stable coin providers and payroll companies.
40:21
So B2B SAS undefeated, another beneficiary of modern technology.
40:25
Just wait until quantum computing hits.
40:29
Once quantum computing hits, everything changes.
40:33
Every payroll company, especially global payroll companies are, you know, really at the forefront of quantum.
40:39
Oh yeah, this is another thing.
40:41
So what does the Elon Trump desktop tell us about Elon's quantum computing timelines?
40:46
Because as you probably are familiar, quantum computing can break encryption.
40:50
So guess what happens when quantum computers are ubiquitous. Oh, those Epstein files.
40:54
Everyone's gonna have access to them.
40:56
And so and so if he really believed it, quantum stocks should be down tremendously today. Exactly. This is the trade. Stay out of Tesla.
41:04
Stay out of stay out of Rivian and Ford.
41:08
Got to look at the second order.
41:10
Got to look at the second and third order effects.
41:11
What does this tell us about quantum timelines?
41:14
Probably that they're further out than we think because as soon as they crack those, boom.
41:18
Who's the who what's the first what's the first file you're decrypting? The the Epstein files. Obviously. Of course. Of course. Of course.
41:28
I like I like Mike Salon's post about that.
41:31
He's like, I honestly can't believe that we didn't know that already.
41:35
It just felt like internet lore that like of course Trump was in there because there's like pictures.
41:39
But I guess like it's a different thing to be in the files than be in a picture.
41:41
But the pictures seem more damning.
41:42
When I got home yesterday, Yeah.
41:46
Um Sarah was like, "Hey, how was your day?"
41:49
And I was like, "Uh, did you see the news?"
41:52
And she was like, "No, I've just been with the kids like all afternoon.
41:56
Just been bouncing around swim lessons, music class, all that stuff."
41:59
And I was like, "Oh, well, like Elon, you know, accused Trump of like being in the Epstein list."
42:04
And she was like, "Wait, like I thought like there's a bunch of everybody's seen the pictures of like them hanging out like having, you know, Yeah, there's video.
42:14
There's video of them at like a party together and it was just kind of like assumed I thought but you know anyway anything to get the to get the the internet riled up.
42:22
Elon's master master poster he owns it.
42:24
Anyway, uh regardless of your view on quantum computing, you know, you can express your view on it on public. com.
42:31
Investing for those who take it seriously.
42:34
They got multiasset investing industryleading yields.
42:37
They're trusted by millions. Go to public. com. Uh let's go to Nal.
42:41
He says the majority of voters are retired either by age, disability, or make work jobs.
42:49
Paying for mass retirement requires crushing taxes, mass immigration, or rampid inflation.
42:53
The only way out of a risky bet is on techdriven growth. AGI will save us.
42:58
But yes, the make work jobs is interesting.
43:03
The AGI pill lion doesn't concern himself with deficit spending or or or unemployment. True.
43:12
I mean this is one of my questions for most of the the the the truly AGI pelled people.
43:16
I try and formulate it as uh US unemployment over or under 10% by 2030 because the US has rarely had higher than 10% unemployment but AGI seems like something that could do a lot of jobs.
43:32
And so even in the Tyler Cowan model where yes medicine is resistant to AGI, yes like you know farming and and land and plumbing and all these different things are maybe resistant to just like LLM based agents, right?
43:43
But even with that scenario, you should you should experience some some pretty significant dislocation and this is what uh uh that latest Dwaresh debate with Schulto was all about.
43:55
How quickly can white collar work be automated?
43:58
Some people have very aggressive timelines, some people don't.
44:02
But I always try and formulate it in like let's put it in a in concrete something that's measurable 10% by 2030.
44:09
And a lot of the AGI pill people when they go when they really unpack it, they start thinking about like well wait like we're really good at creating fake jobs.
44:18
Like we could just have 10 more TSA type programs and all of a sudden people are you know still employed and it's like yeah my job is pretty chill.
44:25
I I mostly just like watch YouTube and like oversee an AGI that does my job, but I still get my paycheck that way.
44:31
You did a speedrun to leadership census here in college, right?
44:36
This is some incredible Yeah, this was I mean the government's fantastic at this.
44:41
So, uh during the 2008 recession, there was uh a desire to pump money into the economy uh more in the the modern way to do that is basically with UBI and just sending checks to everyone.
44:54
But it wasn't always that way.
44:55
We used to have to come up with an excuse. Schemes. Schemes.
44:57
And so, so this scheme was basically counting counting.
45:02
It was accounting counting scheme.
45:03
It wasn't an accounting scheme.
45:05
It was a just a counting. It was a government.
45:06
It was a count operation. Yes.
45:09
And so the census in 2000, the economy was ripping. It was the dotcom boom.
45:14
And so all the census workers were basically volunteers.
45:17
My mom actually volunteered.
45:19
Went around and asked people in the neighborhood.
45:20
It's actually kind of a nice thing to go meet your neighbors and ask them like, "Hey, like fill out the census form.
45:24
Like we'll be able to get more votes for, you know, the upcoming election."
45:27
Um, and and it's very nice to use people and people are happy to do it.
45:31
Uh, but in 2008, the the economy had just crashed.
45:35
2010, the economy was in in the sham in in in shambles after the after the recession.
45:40
Um, and so they decided to pay everyone like $20 an hour to do a job that people were previously doing for free and throw like way more resources at it to get like better census data.
45:48
But of course you you you can only spend so much and so uh I wound up getting like a management job there and getting paid a ton of money to do like basically nothing.
45:56
You were managing hundreds of people at not quite hundreds but do dozens at and it was it was actually my 21st birthday and I remember going out and being like yeah guys like I can't really like fully take advantage of this and like drink that much tonight because you have a lot of responsibility to go to work tomorrow.
46:14
got to look after your team and and do an orientation for 40 people that range scaled counting operation from 5 years older to me than 50 years older than me.
46:24
Like there was truly no one even close to me like still in school.
46:26
Uh but that's the way the government works.
46:29
Pay a lot of money to have a video of you up in front of all of them talking. It was a wild time. Wild time.
46:34
Learned a lot about the government.
46:37
Anyway, we have uh Patrick Blumenthal in the studio.
46:38
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46:41
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46:58
We can talk about eight too.
47:01
Let's get pod five ultra. Pod five night sleep.
47:05
I had a brutal night's sleep. It's been chaos.
47:06
I think uh I think the two I think the two one-year-olds took the Elon Trump breakup really really hard. Yeah.
47:14
I think the four-year-old as well very very difficult.
47:16
Like it it clearly like he he can't really articulate if he's a Trump guy or an Elon guy, but uh he didn't let that on.
47:26
But it it it was it was a dark moment for him.
47:28
Well, they're all America guys. Exactly. Exactly.
47:30
So it was kind of like in many ways it was an embarrassment. China won. China won.
47:38
The twins first two words. China. China one. Yeah. Yeah. Yeah. They're disappointed. Dada. China one. Yeah.
47:43
But rough night of sleep. I got like a 64. You crushed me.
47:47
I mean, I didn't do much better, John. I got a 73.
47:49
If you want to get on the official matchers of TBPN, go to. com/tbpn.
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48:01
Let's bring in our first guest, Patrick Blumenthal.
48:04
I've been on a podcast with him before.
48:06
We went we were we did Pirate Wire together.
48:08
Good to have you here in the studio. Welcome to the show. Long overdue. How you doing? Thank you so much. Uh break us down.
48:16
Actually, first let's kick it off with an intro. What are you doing? Where are you?
48:19
Are you in America finally?
48:20
Last time I was on a podcast with you, I think you were halfway across the world.
48:24
I am in uh New York City right now. Cool.
48:26
For the illustrious, decadent, incredible New York City Tech Week. Oh, fun. How is it?
48:31
Fun fact, I created New York Tech Week, co-founder right here. Yeah. Yeah.
48:37
Years ago, passed it off to Andre after the first year, but uh but yeah, the very first New York Tech Week was by yours truly.
48:45
One of the biggest still on the domain. Yeah.
48:48
Uh yeah, break it down for us.
48:52
What What What have the best events been?
48:54
Is it mostly VCs, entrepreneurs?
48:56
There a lot of pitching is how are the ads?
48:57
Are there good sponsorships?
49:02
There's a lot of ads and I think the like attendee toe event ratio has like shifted massively compared to previous years.
49:08
I only went to two events by the way.
49:09
So everything that I say take it with a grain of salt.
49:10
I'm actually just in New York and then it happens to be during tech week. Cool.
49:13
Um there's a lot of events, a lot of sponsors virtually for every single industry.
49:18
Like there's a million NATSC events, there's a million interesting tech events.
49:21
It's like virtually every industry. Uh every type of person. What's the reaction?
49:25
You seem a little tired, Patrick.
49:27
Were you up a little late last night?
49:29
I've been up late a lot this week and the previous week and the week before that to be honest.
49:35
New York is an exhausting city.
49:37
It's not quite uh uh the same as San Francisco.
49:40
You sleep more when you're in Ukraine or New York, dude.
49:44
I actually sleep really well in Ukraine.
49:46
I find the food to be so much better, too.
49:47
So, you can like somehow smoke a bunch of cigarettes and drink a lot and still sleep really well. It's a true meme. The meme is real. Nice. Interesting.
49:55
What's the reaction been in at these cocktail parties to the Trump Elon news?
49:59
Uh, that's a good question.
50:02
It came up a lot last night.
50:02
It wasn't actually a tech week party, but um, you know, part of the it was a it was a couple of dissident right events, we might call it that.
50:10
Um, I think I think uh people don't care as much as Twitter to be honest.
50:16
Uh, no one no one really had like any strong takes.
50:18
No one's taking sides, I guess, is the point. Yeah.
50:21
There's just not that much to go on.
50:23
like it's it's it's still like it's like crazy but then in and out in a few minutes but uh certainly something to track.
50:31
Uh but let's move on to the reason we wanted to have you on.
50:32
Uh can you give us your reaction and breakdown to the Ukrainian operation that I believe happened last weekend?
50:38
Uh we covered a little bit on the show, but I'd love to get your take and uh maybe just introduce exactly what happened and then we can go into some of the history and implications. Yeah.
50:48
and implications. Yeah. So at a high level what happened obviously everyone heard about it but um you know specifically um you Russia had a very very big part of its like nuclear triad uh get degraded so they lost like 33% of their kind of air launch cruise missile capacity um it's a bunch of strategic
51:07
bombers that they manufacture during the Soviet Union um completely irreplaceable and so one of the kind of big asymmetric advantages of Russia during the war has been that they can just launch a massive amount of stuff from really far away, like way beyond the range of Ukrainian fighters, Ukrainian air defense systems. Um, they use cruise missiles, which
51:25
Um, they use cruise missiles, which obviously have a uh propulsion on the munition, so it goes much further um than it otherwise would.
51:32
And they also have glide bombs that they've been using for the last uh you know, 3 years of the conflict, which is basically just taking dumb bombs and making them fly much further than they otherwise would.
51:40
Um, and so really all Ukraine has been able to do is destroy the platforms.
51:45
like there's just no way that they're going to shoot down every single cruise missile.
51:49
They're not going to shoot down every single shied and so um this is essentially the best thing they can do is just like go to their airfields and blow things up when they're still on the ground.
51:58
You mentioned the nuclear triad.
52:00
So these bombers that were destroyed were actually capable of carrying and dropping nukes even though that's not directly relevant in this conflict at least not yet.
52:07
They're all nuclear capable or a lot of them. Yeah.
52:08
And so um you know you have ballistic missile submarines, you have strategic bombers, you have ground launch ICBMs um and ideally you want all three because the idea is essentially that you have too many nuclear assets in too many different places that um you know you want essentially deterrence.
52:27
So even if the US were were able to first strike with, you know, hypersonic missiles every single ground silo that uh the the Russian Federation has, they'd still have a bunch of strategic bombers on station, a bunch of submarines on station.
52:43
Um so we would still be screwed basically.
52:45
I It's crazy to think of Russian nuclear submarines like just trolling around the ocean.
52:50
I feel like they've been like so pushed back, so contained, but of course that's obviously Well, that's the point of nuclear submarines.
52:57
you can go down and just hang out for quite a long time.
53:02
Um, how what what do you think the uh is this type of attack a one and done?
53:07
They operated it on cellular networks which was a surprise.
53:10
Do you think that Russia will make changes that make that a lot harder in the future?
53:15
Uh what's your kind of uh reaction there?
53:19
I think the reality is that um Russia is a very poorest country.
53:25
like it's exceptionally easy to get things in and out to their advantage and to their disadvantage.
53:31
Like people don't realize how many Western components are in like every single Russian drone.
53:34
Um like they're still heavily, you know, using Western companies and components for virtually everything.
53:40
Um they get in through a wide variety of ways, but to our advantage, obviously the Ukrainians can do the same thing as they've demonstrated in this case.
53:47
Um I think, you know, the future attacks are going to rhyme.
53:51
They're not going to be exactly the same.
53:52
Like what Russia is probably going to do is improve their uh jamming operations at airfields that uh traditionally have not been subjected to Ukrainian drone strikes.
54:01
Um they're going to change their procedures around daytime operations.
54:05
So generally one-way attack munitions both on the Russian and Ukrainian side happen at night. Mhm.
54:09
Um it's kind of random that like on a Sunday morning basically um you know there were a couple hundred Ukrainian drones sitting on all these airfields.
54:19
It's like quite uncommon. Mhm.
54:19
Um, and we don't know where the failure was on the Russian side.
54:23
Like, were the jammers online and the Ukrainians just knew what frequencies the jammers were working on and so they just operated outside of that?
54:31
Was the Russian jamming guy who just sits there with a big red button just not at his station at the time because he wasn't expecting it?
54:38
Um, there's kind of a lot of open questions around that and I'm sure there's going to be like procedural changes.
54:43
Um, but when you when you kind of step back from the specific attack of like big trucks with garden sheds that are containing all these drones near air bases, um, and you just look at the basic kind of formula there, which is civilian infrastructure near military assets, um, the attack surface is just really wide.
55:03
So like it could be a rail car, it could be a truck, it could be a van, um, it could be a ship in a port, right?
55:06
The military facility doesn't have to be an air base.
55:10
It could be a factory, could be the Kremlin, could be any logistics depot, could be a base.
55:14
Um, and so when you multiply all that complexity basically across the 11 time zones that Russia has territory with hundreds of critical facilities, it's it's it's kind of unstoppable to be honest.
55:25
Yeah, that's interesting.
55:27
How are um how are you thinking of investing in drones as a category?
55:32
You've been on the ground in Ukraine.
55:34
You've seen, I'm sure, a lot of the stuff that they're doing, which is evolving constantly.
55:37
I'm sure you've met a lot of the American uh drone startups and obviously, you know, there's a huge range of players from Nuros to uh you know, Anderoll to, you know, counter drone uh startups like uh ACS.
55:50
Uh but how are how are you looking at the category and and um where where do you think it's investable?
55:59
So I think um Ukraine is interesting specifically and then I'll I'll answer your question.
56:05
Ukraine's interesting specifically because you have a lot of like consolidation around the same exact ideas.
56:09
So like I've seen a lot of the drone factories spread out around Ukraine.
56:13
They're all making generally the same stuff within FPVs at least.
56:15
And like you have different components like oh this FPV we're going to use fiber cable for it because this area is jammed.
56:22
Um but at a high level every FPV in Ukraine is like exceptionally attractable.
56:27
It's like 3D printed, very cheap components from China or now some sometimes domestically produced, but like very very cheap.
56:33
Those are not really what I think of as venturebackable.
56:37
Um, you also have all obviously all the added unique risks of their factory might get blown up by a cruise missile.
56:43
The founders in many case are also active duty soldiers.
56:45
So you have to kind of underwrite the additional risk of them getting killed on the front.
56:50
Um, not to be so morbid, but it's true.
56:52
but it's true. in the US ecosystem more like a traditional startup obviously like there are no founders who active duty in the US um there isn't exactly the same set of risks and they're much more focused on selling to kind of the creme creme customer the DoD so the capabilities are just much more
57:10
exquisite um and so there's a lot of stuff to bite off because the US similar to you know Russia operating in 11 time zones the US operates in every time zone because we have bases literally all over the world and so every single climate every single uh potential adversary like Iran, China, North Korea, Russia, etc. They demand different solutions uh in
57:28
They demand different solutions uh in each theater, they demand different solutions for different operations uh during different times of the day, different weather, like all these different things.
57:38
Um and so the reality is that there's actually a lot to invest in.
57:41
Um, specifically with drones and counter drone stuff, um, I think the future of like the integrated air defense system, like you know, we think of as like the Iron Dome, it's going to be much more heterogeneous, right?
57:52
So like Israel now has like five or six different types of missiles they use. They're testing lasers.
57:58
They're testing a kind of other couple stuff, but it's like a much more stationary and static type of system.
58:03
The integrated air defense system of the future is going to be like three or 400 different things.
58:10
like this is going to jam this one thing, this is going to intercept this one thing, this, you know, is just hitting an FPV, so it can be a small gun like in the case of ACS.
58:17
Um, and then other things, you know, you need uh ballistic missiles to destroy other ballistic missiles.
58:24
So, you basically are going to have this system like a command and control system that senses all these different things and then essentially triages.
58:32
What is uh Russia doing on the FPV drone side?
58:35
We've heard that Ukraine is producing I think millions a year now.
58:40
It seems like really really mega scale.
58:42
Has Russia been able to match that at all or do they take a different tact?
58:45
I don't know where the official numbers are to be honest, but I would be surprised if Russia was producing less to be honest.
58:52
I mean I think certainly within the same order of magnitude.
58:55
Um obviously there's very poor fidelity on the Russian side.
58:58
But one thing that you can just look at um and this isn't just FPV drones, this is just drones broadly.
59:05
One of the things that you can look at is like how many Shaheds are attacking uh Ukraine every single night. Sure. It's in the hundreds.
59:10
Like they're literally just lobbing hundreds of Shahed drones at Ukraine every single night of the week.
59:14
Um and so I don't know if you guys saw, but they did their quoteunquote retaliation last night.
59:18
It was basically like any other night.
59:21
They just lobbed a bunch of drones at Ukraine.
59:24
Um you know, the Russian economy now is like literally entirely a war economy.
59:28
Like I don't know what it would look like as you know, defense as a percentage of GDP.
59:33
Yeah, that's that's one of the big issues with peace, at least uh on the Russian side, is what happens to the economy if you no longer need to be producing, you know, huge volumes of tanks and drones and missiles and all these other things. It's so depressing.
59:50
So many great mathematicians there.
59:52
They should just be building hyperscaled data centers and racing for AGI.
59:57
You know, they have the talent and they're focused on, you know, kinetic warfare. death.
1:00:02
It's fighting fighting the last war.
1:00:04
Um Well, that's why we got to end the war so that we can do joint AGI development with Russia. Exactly. Exactly. War. Yeah.
1:00:10
Or maybe just more brain drain.
1:00:12
I wonder if there are more Russian scientists that are leaving because of uh how crazy the war effort is and if that'll make it easier to recruit, you know, brilliant scientists.
1:00:23
There's a lot of people just hiding too, mostly on the Ukrainian side because Ukraine obviously has the draft, but a lot of Russian scientists left in the first few days of the war through like Georgia and Armenia and now they're just like refugees.
1:00:33
And then a lot of Ukrainians within AI and tech.
1:00:35
Um, obviously a tremendous amount of them have joined the military and they're now developing drones, but there's still a lot of Ukrainians are just like hiding in their houses basically and their wives just do all their errands for them.
1:00:47
Like they're they're not allowed to leave the house cuz they're going to get conscripted. Yeah.
1:00:50
Um, so their wife gets groceries and everything.
1:00:52
Can you talk to me about what is actually involved in visiting Ukraine right now?
1:00:58
Is this something where you need to fly to a different country and take a train in?
1:01:01
Is the airspace dangerous? Do you need a visa?
1:01:04
What does the State Department think about visiting Ukraine right now?
1:01:08
If anyone in the audience is considering going, uh, what's the what's the vibe on the ground? Where do you stay?
1:01:13
How do you actually get connected?
1:01:15
Can you walk me through your experience visiting Ukraine?
1:01:17
Yeah, it just it kind of depends on what you want to do.
1:01:20
So, um I don't know how specific I should be about my next trip, but um the more east you go, the more difficult things become obviously in both in terms of getting approvals, but also just like transportation and then also your risk tolerance would have to go way up.
1:01:33
So, like you know, hypothetically, if I go to Harkke, um which is very close to the Russian border, it's basically on the Russian border.
1:01:41
um the risk considerations are just very different um in terms of what to expect every night from Russian strikes, what to expect in the context of the war, like there is always some kind of an offensive going on around Hardke um and so you do have to be careful.
1:01:54
Um you know what I would say is that um I obviously have a high risk tolerance.
1:02:00
What I would say is um it's not as dangerous as people think statistically. Mhm.
1:02:04
So like you know um the likelihood that you're going to get killed even in a drone strike when like if you're in if you're in Kev let's say or Kev and they're striking it hundreds of times per night.
1:02:15
These are big cities you know so the likelihood that you actually get hit by anything is pretty low.
1:02:18
Um in terms of getting in in the country you have to fly in through Poland basically.
1:02:23
So you go into Poland and then you drive into Ukraine and it's a big country so it's like 14 hours from Poland to to Kev. Yeah.
1:02:31
I mean, we've heard I mean, we saw during the global war on terror, like there were plenty of journalists that made it in and out.
1:02:36
Obviously, it's extremely dangerous, but it is it is doable if you're if you're careful enough.
1:02:41
Uh, can you talk about the public relations strategy around the Ukraine attack on Russia?
1:02:46
I found it interesting that we were getting like highfidelity video, really detailed analysis. It felt party video. Exactly.
1:02:55
And and the sentiment in the early war was very much like support Ukraine.
1:02:58
Then there was recently some push back about are we spending too much on this?
1:03:02
Is this is this even our war to be fighting?
1:03:05
And that was a kind of political football that went back and forth both on the left and the right in some ways.
1:03:10
Uh this makes this feels like um it like it feels like the takeaway is that the Ukrainians are innovative and they're and they're adapting and they're not letting down and so maybe it's not time to back down in supporting of them. Is that deliberate?
1:03:26
Where do you think this goes from here in terms of support from America?
1:03:29
I think there's like different groups of people that the Ukrainians want to kind of attract or get attention from these kinds of attacks.
1:03:37
And the reason why they're so public about it, including posting footage, is that they're trying to basically convince the rest of the world that they're worth supporting in a very pragmatic way.
1:03:45
It's like, forget about the fact that Russia started the war, that Ukrainians are being killed, any any of that's kind of irrelevant.
1:03:51
any of that's kind of irrelevant. The main calculus is hey yes we are you know 1/5if the population of Russia we have a much smaller economy um you know we have manpower issues all these things are true you know Russia historically you don't want to fight a land war against over an extended period of time we do
1:04:09
these operations the Ukrainians do these operations because it's a way of showing that they've essentially found asymmetric ways to offset it and that if you send them money if you send them weapons if you provide intelligence support they're going to keep finding new ways to So it's just them basically showing every 6 months. We're going to find a
1:04:25
We're going to find a new way to reinvent ourselves and keep Russians on their feet basically. Very cool.
1:04:31
Well, good luck on your next trip.
1:04:33
Stay safe out there and enjoy the rest of New York Tech Week. Appreciate it. I will. Thank you guys so much. Be safe. We'll talk to you soon. Great talking to you. Bye.
1:04:40
Uh next up we have Jeremy from Circle IPO on the horizon. I'm so excited for this.
1:04:47
I I'm I'm still learning about quiet periods and when folks can talk, but uh we certainly not in a quiet nailed this one and we're so excited to have Jeremy on the show. Welcome to TBPN. How are you doing? How are you feeling? Congratulations to you. Congratulations. Thank you. Thank you. Uh I'm I'm feeling good.
1:05:04
It's it's been a it's been a a really intense couple weeks and um obviously uh a really exhilarating last couple days.
1:05:11
Um did you get any sleep last night? I did. I did.
1:05:16
I I managed to my my family was able to join me great for the uh for the ceremonies here in New York and got dinner with my family and got some rest. Yeah.
1:05:26
Uh we we talked to Brian Armstrong about uh the initial roll out of the circle partnership years ago.
1:05:32
This has been uh a classic overnight success very clearly.
1:05:37
Probably your overnight success. Yes. Yeah.
1:05:38
But uh overnight success.
1:05:40
We love an overnight success on this show.
1:05:42
uh but can you give us a little bit of the the the history and the story you told about the company when you were taking Circle Public? Yeah, absolutely.
1:05:52
I mean, look, you know, my my background had, you know, prior to this been building internet software platforms and infrastructure from like programming language, developer tools, digital media platforms.
1:06:05
And I was always interested in sort of how the open internet and open networks could could change the way different parts of society work.
1:06:11
That was what animated me.
1:06:13
And in 2012 I got deeply into the technology behind crypto.
1:06:18
in 2013 really formulated this idea that um you know it would become possible to build a protocol for dollars on the internet where you could issue a what I thought of as a full reserve dollar digital currency that could be made accessible in a protocol like HTTP.
1:06:37
So you could have a a protocol for dollars on the internet and I believe that we could do that on these blockchain networks which were super nent at the time and there was no legal framework for any of this and it was like you know totally crazy.
1:06:46
Um but we believe we could do it and um you know I think the the the the belief was that over time these networks would become scalable, the infrastructure would work.
1:06:57
We could come up with laws and regulations and that once we achieve that that basically the storage and transmission of value would become like a commodity free service on the internet and money velocity would explode.
1:07:07
And then in particular, um, I was really excited at the founding of this idea of programmable money and smart contracts, which was like ideas on napkins at the time.
1:07:19
Um, and that ultimately not only would you just sort of have this explosive way to and and lowcost way to move value around, but actually the utility of money could increase dramatically and that you could actually rebuild the financial system into a internet financial system, which is how we founded the company, a circle internet financial um, originally.
1:07:36
and and so um you know we've just been pursuing that and and now like it's actually happening like the infrastructure works.
1:07:44
There's laws and regulations.
1:07:46
We have these full reserve digital dollars that have like central banks and credential regulators looking at them and and the technology is sort of starting to kind of go into the background. It's no longer crypto.
1:07:56
It's stable coins and it's digital currency.
1:08:01
And so um and we've you know we've built I think right now a really interesting business uh to to to bring that.
1:08:05
And so that's sort of the origin of it.
1:08:07
And so kind of um it's been you know it's been a long road for sure. Congratulations.
1:08:12
I have like 12 more questions.
1:08:14
I know we we don't have a we don't have a ton of time.
1:08:18
Um I you know I I want to get into you know some of kind of two angles.
1:08:20
How you're thinking about partnerships on a go forward basis with institutions and partnerships with you know other large you know public companies.
1:08:30
It seems, you know, we saw Uber in the last 24 hours in the headline talking about, you know, exploring stable.
1:08:35
Talking about payroll companies potentially and and I feel like this gives every, you know, I uh my last company was a fintech company.
1:08:42
We enabled us uh stable coin investing with USDC and uh so I've been a big, you know, believer for a long time.
1:08:50
But you know you guys being public now, the market reaction to it, it feels like it gives every single institution in the world permission to say, "Hey, let's adopt this technology in a meaningful way."
1:09:01
And so it truly feels like you guys are on day this is I hope so day zero. Yeah.
1:09:05
I mean, look, I think I think this is like a mainstream moment for the adoption of this technology.
1:09:11
We're classically crossing the chasm, right?
1:09:13
from early adopters to like mainstream acceptance, the technology usability, the laws and regulations and and you know having a publicly traded company like this I think it really does matter to trust, transparency, compliance, governance, things that really matter when when other major companies want to figure out who to build with.
1:09:29
But you know at the core of our business our whole model is we're a market neutral infrastructure company.
1:09:36
We're like a platform that people can build on top of.
1:09:38
We have banks and neo banks and payments companies and and fintexs and exchanges custodians like every type of institution we work with already and they face us as a mar market neutral platform and that's really really important.
1:09:54
We're not competing for end users.
1:09:55
We're not competing for businesses.
1:09:57
We want to let other people build on top of both the kind of public utility that we put out on the internet like our public protocols and like the the kind of market infrastructure of the money issuance side of it.
1:10:06
money issuance side of it. And so it's now it's definitely getting to a point where um yeah I think major public companies um commerce firms internet firms financial institutions of of all types really can you know build on this now it works it's it's it's it's liquid
1:10:25
you can connect to it around the world and and we have the ability through innovations like CPN a recent product that we launched to abstract away from an enduser perspective a lot of the things that are are you tend to be barriers to entry and and and make it work compliantly as well. So, it is a
1:10:40
So, it is a really I think significant moment and I do think that um you know lots of mainstream companies can now really feel like they can do this and there's a and there's a great platform company to work with.
1:10:54
I'm wondering about other real world assets on change pro programmable money.
1:10:59
A lot of the conversation around I want something that's low cost, high speed, programmable, and stable supply.
1:11:07
That makes me think gold, stable gold coins basically.
1:11:10
Uh I'm sure you've gotten this question before, but why didn't the market evolve that way?
1:11:13
Or even uh that original like 1999 Peter Teal talk about you're going to be able to transfer $1 worth of S&P 500 to someone else.
1:11:24
And uh there seems to be some demand for that type of stuff, but we the market didn't just break that way. Okay.
1:11:29
And so what's actually going on? Yeah.
1:11:30
Well, I mean look, I mean the the dollar itself has has extraordinary network effects.
1:11:34
Like 65% of trade is settled there. Sure.
1:11:36
And and frankly like a huge a huge driver in in our business right now is demand for digital dollars around the world.
1:11:42
People, households, firms want to hold these safe full reserve digital dollar instruments that have the utility of the internet.
1:11:50
It's like when people woke up and said, "Hey, I can use WhatsApp and I can communicate with others.
1:11:53
I don't have to pay my carrier these SMS fees."
1:11:56
And it's over-the-top internet money.
1:11:58
And so people have figured that out and um and people want dollars.
1:12:01
Um even though there's a sell America trade or whatever you want to talk about or there's a fiscal cliff or whatever it is like all these things that are there, people still want a unit of account and they want the power of the internet as a medium of exchange and and relative to almost every other fiat currency, the dollar still remains super preferred.
1:12:21
And so I think that's that's certainly going to be the case for uh for a while.
1:12:25
And um and so I think that's there, but the programmability piece is the really exciting next step, right?
1:12:31
You know, how can you intermediate financial arrangements, commercial arrangements, labor arrangements, arrangements between AI agents, like all of these things that can be machine mediated with provable code, you know, tamper resistant provable code on the internet, which is what smart contracts give us.
1:12:48
We're just starting to see the unlocks there.
1:12:50
Um, and it's going to be an entrepreneur and developer driven phenomenon for sure. That's amazing.
1:12:56
You you mentioned AI agents.
1:12:57
Uh, Ben Thompson was reacting to the uh the MCP standard and the lack of a payments layer in there at least in this version of the specification.
1:13:06
Uh, is there is do we need a v2? Is this something?
1:13:12
Well, you know, you know, it's it's a great question.
1:13:13
We're working with all kinds of teams on aentic payments.
1:13:17
And I'll tell you, you know, we worked on a new um a new uh standard.
1:13:21
Actually, it's reusing an old standard.
1:13:23
Uh we worked on it with Coinbase and a couple of others, which is X42, which is essentially an un it was a it was a protocol extension of HTTP, which was originally a protocol extension to support payments native to HTTP, and no one ever did anything with it.
1:13:38
And so it is essentially the payment request like uh feature of HTTP.
1:13:40
So that's been reincarnated and where stablecoin is the payload.
1:13:46
And so now you actually have built into HTTP an extension which is a stablecoin payload.
1:13:54
And so it's like literally designed for AI agents. Yeah.
1:13:56
Uh that need to basically you know handle these and and it kind of abstracts away what chain you'd use underneath.
1:14:03
And so it's it's pretty cool and we're pushing it into our dev products.
1:14:06
So host Coinbase and others.
1:14:08
And so I think actually like that was part of like you know early on Mark Andreasen complained I was about to say yeah I mean that's the famous thing hey we had this thing there no one did anything with it.
1:14:19
Well now we have something to put in there and now we have the demand which is like machines that talk to each other and so um it's it's interesting how a lot of these things kind of come together at the same time. Yeah.
1:14:29
Do you have a view on uh that idea of micro payments on the web?
1:14:35
It just feels like we have microtransactions that happen across APIs.
1:14:39
They just get bundled and reconciled at the end of the month.
1:14:43
There's still a ton of value in in stable coins.
1:14:44
I'm not saying that like, oh, the narrative is bust because that might not be the endgame.
1:14:47
But we saw this with Bitcoin where people were saying, oh, there's four different ways that this could break privacy blah blah blah.
1:14:54
It wound up in having a very strong narrative.
1:14:56
It it kind of narrowed down the focus, but it's still a wildly successful technology.
1:14:59
Well, I mean, look at at a high level, right?
1:15:01
We think about the the TAM here as legal electronic money.
1:15:06
And then narrowing that down a little bit, you have cash and non-inter non-interestbearing demand deposits, which globally is like $60 trillion of the money supply.
1:15:15
And so if you can have a digital cash instrument that has the superpowers of the internet and and the like that can basically move and transact at almost no cost, there's an enormous amount to to grow into.
1:15:26
Now the other part of the TAM is all of the different utilities that we have for storing it, moving it around and those are being reconstituted on chain and so you you start to think about like okay you know crossber payments is one that we talk about a lot and we're seeing a lot happen there.
1:15:43
The kind of point I like to make is like when's the last time you sent a crossber email and sort of like well that doesn't make any sense.
1:15:51
We're we're like we're entering that era with money, right?
1:15:53
Where basically like stablecoin money and that could be a business that's got a $10,000 payment to buy something from someone in Asia to, you know, get product in Latin America.
1:16:05
It could be an investment, right?
1:16:07
I want to make a $10,000 investment in a startup in in in an emerging market or in the US or it could be and as we see today like the biggest electronic trading firms in the world are moving hundreds of millions of dollar transactions over blockchains using USDC to settle bilateral trades.
1:16:26
The exact same transaction is being used to do buy a 25% digital a 25 cent digital object in a web 3 game.
1:16:31
And it's the same, right?
1:16:34
Just like if I send you an email with a picture of my breakfast and you send me an email with a CIA dossier.
1:16:40
It's it's it's the same payload.
1:16:41
It's whatever it is 25 byt or you know a bite of data or whatever.
1:16:44
You know, it's the same thing.
1:16:45
And so, you know, that's the cool thing about this. Very very scalable.
1:16:49
And so you don't need like streaming payments or micro payments as like a like killer use case.
1:16:57
you just need to be able to support all these different kinds of of of value exchange just in an internet native architecture.
1:17:03
Can you talk a little bit about the the geopolitical environments internationally that are most receptive to stable coin adoption?
1:17:09
You could see demand for crypto products track or correlate with authoritarianism.
1:17:16
But then you have the push back of a lot of authoritarian countries might want to ban or restrict or make something illegal.
1:17:24
So, so will we see more count almost counterintuitively or like as a second order effect, will we see more stable coin adoption adoption in more democratic countries first? Yeah.
1:17:32
Well, what's interesting is the the demand for for stablecoin money is very global and and we do see it for example in in in um countries where there's weak regimes or the banking system isn't as adequate or there's not as as effective access to dollar banking. Sure.
1:17:49
dollar banking. Sure. Um, and and so that's a that's a valuable thing for the people and businesses in those markets, but but it is sort of this again this over-the-top phenomenon like you know WhatsApp came over the top and like all of a sudden everyone was a Facebook
1:18:03
customer and then dealing with Facebook for whatever issues in in your country or you know the Arab Springs were an example of like hey everybody could like share media with each other and like whoa we just lost control uh you know of things and so I do think there are geopolitical dimensions to this. I think
1:18:18
I think we're in the very early.
1:18:19
But then you guys have have partnerships in Japan that allow you to launch USDC there, which is that's our philosophy, right?
1:18:27
Is if a government is going to have rules around, you know, stable coins in their in their society, you know, we we want to make sure that like those rules are are fair obviously and and and we want, you know, that stable coins that are allowed to be used to be held to really high standards, right?
1:18:42
high standards of trust and transparency and compliance and governance and and things like that. So that's important.
1:18:49
And what we're now seeing is in markets where stable coins have exploded, Korea, Brazil, Turkey, South Africa, Kenya, um like all of those governments are working on stable coin rules right now.
1:19:02
And you know, so I I think it's it's a it's a space where that's intersecting and and so yeah, we've dealt with this in the history of the internet, right?
1:19:10
It was when the internet started like you needed a broadcast license to have a radio show in Italy, right?
1:19:14
It was like a or there were national monopolies that were the only entities that could actually do radio shows in Italy.
1:19:20
Well, now here we are, right?
1:19:22
now here we are, right? So I think there are these kind of transformations and society ultimately votes you know on on what they want to adopt but it is still a political economic negotiation and monetary sovereignty is not something
1:19:37
that the internet has really faced off against uh you know uh in a big way but you know people talk about bitcoin as doing that like as this non-s sovereign store value but then when you have kind of exportable digital fiat then it it it it does become a slightly different issue. Can you talk uh quickly about the
1:19:53
Can you talk uh quickly about the competitive dynamics on a go forward basis?
1:19:58
This IPO was massively successful.
1:20:02
It seems like they're at at right now from my point of view infinite uh excitement for for Circle and USC.
1:20:09
That's obviously going to inspire a lot of different groups whether it's early stage startups to other institutions to uh compete and and I can imagine myself why you guys will continue to dominate.
1:20:20
But I'd be curious to hear from you.
1:20:20
I mean, look, I think um the way we think about our business is that we've built um a stablecoin network and it's an internet scale platform and network utility and we take very much like an internet platform mentality.
1:20:36
We want to build open public infrastructure.
1:20:38
We want developers to build on it and developers build applications that integrate it to it which adds utility which then expands interoperability and so you create these really great classic developer flywheel effects and that's what we've done and we've done that with liquidity as well like it's got to be available the digital dollars etc.
1:20:53
available the digital dollars etc. So this is a um you know it's a business that has network effects and um and and and those are I think strong network effects and then it's it's a business that there are these very significant
1:21:06
hurdles we've had to work on for 10 years to become licensed to become regulated to become supervised to become trusted to integrate into these different government regimes and and and and the like and and that that's a lot of work and it's definitely work other people can do. So I have no doubt that
1:21:21
people can do. So I have no doubt that given the TAMs that we're talking about that there are going to be a lot of great you know companies and the what I've sort of said is I think this is a winner take most not a winner take all market and you sort of see that in the market structure a little bit today and
1:21:35
I expect that market structure to persist and I think 3 to 5 years from now within that you know set that market structure there's probably a couple players that don't exist yet but will exist and will be double digit players right so it's just hard to know exactly you know who that's going to be. But I I
1:21:51
But I I think at the end of the day like we want to build things that are useful for end users, for developers, for businesses and and and and provide that and and keep innovating.
1:22:01
We're a productled company, a technology-led company.
1:22:03
So we want to just keep doing that.
1:22:05
And as long as we do that, I think we can we can continue to grow and thrive.
1:22:08
Yeah, you guys are in an incredible position.
1:22:12
Personally, John bought a car uh this week and uh were the dealer able to accept stables, he probably it would probably be getting delivered today. It'll be Monday.
1:22:25
I look forward to people internationally with stable coins years ago.
1:22:28
It was fantastic experience. It was in Argentina.
1:22:30
I have one last question.
1:22:31
Once once you once you've had stables, you'll never go back, right?
1:22:34
It's like, oh wait, I can't believe this. Yeah.
1:22:36
I I have one last question then and then we'll let you go.
1:22:38
Sorry for going too long, but uh I I I want to understand the shape of your business, I'll give you some examples.
1:22:44
There's the the Silicon Valley muscle, there's the there's the Washington DC muscle, and there's the the Wall Street muscle.
1:22:50
And when I think about the Bitcoin project originally, it was almost entirely technology, no regulation, no financial work.
1:22:59
uh the Grayscale Bitcoin uh ETF was uh very little technology, almost all lobbying and regulation and Wall Street financial.
1:23:07
Are you a perfect blend of all three?
1:23:09
Is there is there some focus?
1:23:11
Has it shifted over time?
1:23:13
Are you out of the woods on the DC stuff and you now it's just finance from here on out?
1:23:17
Well, I mean, look, I mean, um, you know, the best way to look at a company is to look at its opex and within its opex, you know, the largest piece of it is labor and so when you look at the labor opex of circle, like approximately 45% is product and engineering.
1:23:33
engineering. So we are we are very technologydriven and that is leadership from amazing uh you know engineering and product leaders mostly out of Silicon Valley mostly based in Silicon Valley and um and so that's that's by far the biggest because we're operating this infrastructure and platforms and
1:23:50
software and and the like and then the second biggest which is you know maybe 20% is what I'll broadly call like our control functions and so that's like risk governance compliance you know uh you know financial controls because we're like this digital currency, you know, market infrastructure, right? So,
1:24:06
So, the control piece is really really key. Yep.
1:24:10
And then and then you have like Yes.
1:24:13
We have we have a a a legal policy and regulatory team that is much larger than a tech company. Yeah.
1:24:17
And and and and is expanding because we're now needing to work with and collaborate with governments world. Yeah.
1:24:23
So, so that part doesn't slow down.
1:24:26
I think as this as this scales like the work the work that we need to do with governments only increases the control infrastructure the product and engineering should kind of kind of chug along.
1:24:38
Um but um yeah that's that's yeah I I think about the compounding advantage of yeah you you can compete with us just you know get uh you know hire a team that can interact with every government on earth.
1:24:50
It's perfectly regulated and and perfectly well.
1:24:51
Well, you know what though?
1:24:53
I I I say this which is like, you know, I I've done the Yemen's work of like legal bills for like a decade.
1:25:00
Uh and so like you know, everyone gets to ride on top of all the legal and regular it so easy algorithm had no legal bills.
1:25:07
Well, thank you so much for coming on. Congratulations.
1:25:12
Excited for you and the team.
1:25:13
Classic 10ear overnight success. Love to see it.
1:25:17
Have a great rest of your day. We'll talk to you later. Awesome. Cheers, Jeremy. Come back on soon.
1:25:22
We have Anastasios from LM Arena.
1:25:24
We're going to get to the bottom of what the best LM is. What the best LLM is.
1:25:29
Welcome to the stream, Anastasios. How are you doing? Pretty good. How are you? I'm great. Uh, congratulations. Uh, you have news.
1:25:36
Can you first introduce the company, uh, the news and, uh, and, uh, everything that's going on in your world? Sure.
1:25:43
So, Ella Marina is an open platform for evaluating AI via human preference.
1:25:49
Um, what it is is you can go to the website lamarina.
1:25:52
ai and you can type in your prompt and what you'll see is responses from two anonymous LLMs.
1:26:00
Uh, and the LLM are, you know, some of the best Gemini from Google and Chad GPT from OpenAI and Claude from Anthropic.
1:26:09
And they're sort of randomly sampled from a pool.
1:26:10
And not only do you see the responses, but you can also battle them against one another to see which ones sort of win for your vote.
1:26:15
Um, and then if you choose, you can vote for the one that won.
1:26:20
And then we use that data in order to construct leaderboards.
1:26:22
So we have a leaderboard of, you know, the performance overall, but also in subcategories like math, coding, instruction following, creative writing and so on. Yeah.
1:26:30
Uh, and we sort of see it as like the people's voice on AI progress, right?
1:26:33
Because you can go there, you can express your opinion.
1:26:35
A lot of the tasks AI is doing is subjective.
1:26:38
Um and by doing so you can sort of guide the field. Yeah.
1:26:40
So you raised money recently. Is that correct?
1:26:44
Yeah, we raised 100 million. Wow.
1:26:44
Uh in a round that was uh Yeah. Thank you so much.
1:26:48
Um it just speaks to the strength of our community uh and our duty to continue to improve the product for them. Yeah. So now Yeah.
1:26:56
What is the business model?
1:26:59
Because I think people might not be so familiar.
1:27:00
Uh there's a lot of benchmarks out there but you're actually building a huge business around this. Absolutely.
1:27:06
The business model is to help you know one of the biggest problems that we see with AIdriven software today is people just don't know how to build it reliably.
1:27:14
They don't know how to pick the right model that to use for them.
1:27:19
They don't know how to build like an agentic system with multiple subcomponents in such a way that they're going to be able to ensemble it together into a piece of software that's like reliable and performant.
1:27:28
And it's hard even to define what these words mean because a lot of the job of AI is to interact with humans. Mhm.
1:27:34
And so when you're interacting with humans, you know, a lot of the responses people give are subjective.
1:27:38
So how do you make sure that you are using your models in a way that like ends up satisfying your users, ends up uh making your product better and better?
1:27:46
You know, we're hoping to be able to address that problem because we have such a big community, millions of people coming to the site and giving their preferences and we have a whole competition landscape of all the different models against each other on all sorts of diverse tasks, not just in tech, but also in, you know, medicine and real estate and school and so on. Yeah.
1:28:02
So talk to me about the death of bench of traditional benchmarking and the rise of big model smell.
1:28:06
Have you been able to quantify the unquantifiable yet? Sure.
1:28:11
So I wouldn't really describe it as the death of traditional benchmarking.
1:28:16
I would just say that um benchmarking is entering a new age where there are different types of benchmarks that are needed.
1:28:23
So what does a traditional benchmark do just zooming out?
1:28:27
What you do is you say hey here's like a particular vertical that I want to evaluate.
1:28:30
Let's say I want to evaluate image classification.
1:28:32
Well, then I'm going to collect a bunch of images.
1:28:35
I'm going to classify them and then I'm going to basically give models a test.
1:28:39
I'm going to grade them based on how well they do on like a held out set of classified images.
1:28:43
So, what is the problem with this in the current day and age?
1:28:47
Well, these days, the way people are using AI is like so broad that you could never like annotate all of it with data sets.
1:28:56
Like you could collect a data set, it's it's going to evaluate that thing, but not everything.
1:28:59
And you could collect 20 and that's going to, you know, evaluate 20 things.
1:29:02
But really there's like a million different things that you should be evaluating.
1:29:05
And you know, arguably even every individual has their own point of view on like, you know, all these subjective tasks.
1:29:12
And so that's why things like Alamarina come in as sort of a different orthogonal signal.
1:29:18
Yeah, maybe it's still useful to say how well is my model doing on image classification or multiple choice question answering.
1:29:22
But maybe I also want to know, you know, whether people like this model, why they like this model, whether they're using it in the ways that I intend it to be used, which and which parts of the space is it good and bad.
1:29:34
And our perspective is those are the questions that we can answer by gathering a massive data set of human preferences and then going backward basically inverting the problem and saying let's mine that data for all the analytics that we can get so that we can tell you which model's best for you and for your use case and that's where I think the power is in this sort of new age of benchmarks. What about humor?
1:29:53
Uh can we expect uh any type of uh benchmarking from LM Arena around uh just making the user laugh? That's a great idea.
1:30:04
We should have a leaderboard for that. Absolutely.
1:30:06
I think I think that that's I I think that that's like a a potential trap that humanity can fall into is is LMS get so good that you just refresh the button and laugh over and over and over and over and then and then you know all productivity is lost and it's just the laugh button, you know.
1:30:23
Hey, if you're if you're making people happy, you know, making people laugh, that's not a bad thing. Yeah.
1:30:26
Sometimes I I also scroll YouTube like looking at my favorite comedians and I think they're they provide me value. Totally.
1:30:33
Yeah, I have I have a post here I want I want your reaction to.
1:30:35
I said, "Now that AI can beat every every intelligence test, we need new evals for the other human traits.
1:30:43
Specifically, I'd like to quantify courage, fortitude, gallantry, mirth, equinimity, yearning, stout-heartedness, gravitas, panache.
1:30:53
This would help me pick what LLM to use.
1:30:55
How close are we to be able to being able to uh quantify courage in an LLM? I love that so much. We need your vision. Yeah.
1:31:03
I don't know how close we are to courage.
1:31:04
Maybe we need them to we need to up the stakes compete in a real arena where they have some risk.
1:31:08
We have some chips on the table, you know. Yeah. Yeah.
1:31:11
Our our intern said, uh, you could probably do this using control vectors.
1:31:16
And I said, uh, I don't want to put the courage mask over the shog.
1:31:18
I want to understand the base level of courageousness for the shog as a whole.
1:31:26
Is that still a So, we went back and forth on that.
1:31:27
We're getting we're getting biblical here. I love it. Yeah.
1:31:31
How how where where where are you guys going to be?
1:31:32
You obviously raised $100 million.
1:31:34
Where where are you going to be investing?
1:31:36
What what are the kind of some things coming down the pipeline that that you're excited about?
1:31:39
Well, the majority of our effort these days is going towards taking the platform that we already have and making it a lot better for our community.
1:31:45
Basically inviting more people in because as you can imagine, how does our platform work?
1:31:50
Like people come to the platform.
1:31:50
At this point, millions, but we're hoping tens of millions or more of people will come to the platform and vote for the ads they like best.
1:31:57
And then we take those votes and turn them into a number, right?
1:32:01
So what's the most important ingredient here is getting people into the platform and loving the platform to play with all these different AIs and like ranking them and toying with them and and so on and so forth.
1:32:09
And we want to build great product features for them so that they continue to continue to love it and come.
1:32:16
So just investing in Elmarina.
1:32:18
ai, that's like where we're really targeting a lot of our energy.
1:32:19
Uh we have Dylan Patel coming on next.
1:32:21
He recently dropped the AI mandate of heaven tier list.
1:32:25
He's got Open AI up at the top.
1:32:28
Uh followed by Anthropic, Deepc, Google, XAI down at B tier.
1:32:30
Uh Meta and Apple are struggling a little bit lower down in Dtier and L tier.
1:32:36
Uh does that track with you?
1:32:39
What have you been most excited about in the recent developments out of the foundation model labs?
1:32:45
Uh what what what uh what do you think's like underrated right now in in uh amongst the various foundation models?
1:32:53
Well, I think uh in general the thing that excites me most is that there's a lot of competition these days and there's also a lot of new modalities that are coming out.
1:33:03
So like you know all the time we're seeing that the models are improving improving improving and the pace is not slowing down.
1:33:08
and the pace is not slowing down. These things are getting way way better and there's a lot of the most brilliant people in the world that are just here like in the crucible developing like the best AI models and then we're going beyond text right it's going from text to people are now doing audio and people
1:33:25
are doing video and I don't know there was a you know a big video model release you know last week with V3 that was huge um and are are you already doing uh tests against the different video models because right now I mean I' I've put the same prompt into Sora and VO3 and it wasn't even close at this point. Obviously, the next iteration will be
1:33:43
Obviously, the next iteration will be maybe more competitive, but it feels like we're we're kind of too early to do those types of evaluations where people would just immediately identify a V3 video.
1:33:54
But then there are some other labs out there like Runway that are doing cool stuff in video and maybe it's harder to tell than people think.
1:33:59
So, we have an sort of initial cut of a video arena that we're going to continue improving that was built by some uh awesome graduate students at Berkeley like Yeah.
1:34:08
So, we have that we're going to continue building it.
1:34:11
Um, but you know, I think one benefit of some of these strategies like arenas is that they can actually provide kind of a a touchstone for the field to come together and say, "Hey, here's here's what we're going to try to improve. Let's go."
1:34:25
And then maybe it would motivate some labs to actually continue to like build better and better video models because they want to, you know, they want to be winning the game. Mhm.
1:34:36
Um what uh what has been your take on the the the llama journey?
1:34:41
Uh there was some accusations of like benchmark hacking.
1:34:46
A lot of people have been saying well it's you know like never been against Zuck.
1:34:50
He he he has a he has a capital cannon and a huge incentive to stay in the game.
1:34:56
Uh and so we could be seeing some exciting things out of uh meta in the coming weeks or even coming months.
1:35:03
I mean, all this stuff moves so fast.
1:35:05
The leaderboards are are constantly shifting.
1:35:06
What's your reaction been there?
1:35:08
So, I would just say that um we should all be gunning for Meta.
1:35:14
We should all be rooting for them because they're releasing open models. Yeah.
1:35:19
And so it I think open models are really great for the ecosystem.
1:35:22
So I think I and everyone else should want them to succeed.
1:35:26
Now, you know, there was a little bit of weirdness in the last release. I think it's okay.
1:35:30
you know, they have a big group of really talented people.
1:35:34
They're going to move on.
1:35:35
And you know, the models they released, they're good. They're getting better.
1:35:38
Um, and I hope the trend continues for them. Yeah.
1:35:41
How is this AI safety debate shifted recently?
1:35:43
It feels like Meta almost could have had a little bit of an out by, you know, years in years past when a model wasn't performing uh up to standard.
1:35:51
You could never really tell if the Foundation Labs were uh really worried about safety or they just didn't want to release the product yet.
1:36:00
it was an easy kind of out.
1:36:02
We didn't see them take that this time.
1:36:04
We didn't see them say, "Hey, we're we're we're delaying because of of uh of safety concerns."
1:36:08
Uh has that kind of melted away from the discourse in your community or do you think that there's a world where what you're building could be used to evaluate safety because there's so many different dimensions of safety now?
1:36:21
I completely agree and we definitely want to make safety a priority in evaluations.
1:36:25
We have a red team arena now that, you know, has been out for a little while and it's still, you know, it's still a bit of a prototype, but we're going to keep working on it.
1:36:32
Um, and I think it's really critical.
1:36:35
I don't know about like, you know, the initial question about, you know, whether or not that's used as an excuse or not.
1:36:40
That's kind of I don't know that might be above my pay grade.
1:36:43
I don't hear a lot of those internal conversations, but I certainly think that like, uh, subjective evaluations are going to be important for safety. Jordy, anything else? No, this is great. I'm excited. Yeah.
1:36:53
Thanks so much for coming on.
1:36:55
Congratulations on the milestone. Excited.
1:36:56
Great to meet the two of you and keep in touch. Yeah. Yeah.
1:37:00
Come back on again soon when you have news. See you guys later. Bye. Cheers.
1:37:02
Uh really quickly while we have our I feel like humanity has a duty to everybody should be required. It should be forced.
1:37:11
You got to go on Marina daily, five minutes a day.
1:37:13
Every every person on earth. What do you got, John? Uh we got bezel. Get bezel. com.
1:37:18
Your bezel concierge is available now to source you any watch on the planet. Seriously, any watch.
1:37:24
And our next guest is here, Dylan Patel from Semi analysis. We'll bring him in.
1:37:28
Welcome to the show, Dylan. How you doing? Boom. What's going on, dude?
1:37:33
This live audience is fantastic.
1:37:38
Uh, we actually do have a bit of a live audience.
1:37:39
We have four people in the studio today.
1:37:41
Uh, but we also have a soundboard going, a giant gong.
1:37:43
If you want to drop a big If you have any big numbers to throw out, we'll hit this gong.
1:37:48
Why don't you just hit it, John?
1:37:50
Dylan's been on a generational run.
1:37:50
Just give us a big number.
1:37:52
Hit it for semi analysis. There we go. Got the Gogg cam. The go cam. It's so loud. I'm sorry. Uh, what's happening? Great to meet you.
1:38:06
It's it's it's fantastic.
1:38:06
I'm having a fantastic day. That's awesome.
1:38:08
I I really enjoyed your China Talk episode, the the update to the AI lab tier list.
1:38:15
Uh, I wanted to I asked I asked some folks about that.
1:38:17
Um, I have I have some follow-up questions, so maybe that would be a good place to start.
1:38:21
Um, uh, OpenAI, I mean, it sounds like they're they're they're not backing down from bigger and bigger training runs.
1:38:28
Uh, but can you give me a little bit more insight into what it means to do a big training run now because they're still pre-training like the RL stuff is scaling up?
1:38:39
Like what is the shape of the next big run, if that's even the right term to use in this era? Yeah.
1:38:43
So there's there's efficiency gains on multiple layers, right?
1:38:49
So pre-training uh you're not you're not simply just going to scale it larger and larger uh as your only avenue of spending resources, but you are constantly getting efficiency gains, right?
1:39:00
Something that lets your model be 10% more efficient to run or train uh but but involves changing the algorithm.
1:39:06
So, people are still doing pre-training constantly, but they're not, you know, OpenAI's uh Orion or GPD4.
1:39:10
5 was a run so large that they literally can't scale it up any larger until like end of this year when Stargate starts being operational, right?
1:39:21
They literally just don't have a cluster that's bigger.
1:39:22
Um, so, so it's primarily them evolving their uh model architecture, continuing to get efficiency gains, right?
1:39:29
Uh so for example, GPT 4.
1:39:31
1 was an efficiency gain over 40 and they're going to do another one of these sort of uh efficiency gain step up in model size somewhat but not as far as 4. 5.
1:39:40
So that's on the pre-training side but all the eyes are on the reinforcement learning side, right?
1:39:46
That's where they're doing all these crazy things or cool things, right?
1:39:50
Whether it be, you know, 03 specifically for uh just regular uh reasoning and 04 is coming out soon enough.
1:39:56
um or it's deep research or it's uh multi- aent systems.
1:40:02
There's tons of work they're doing spending training uh compute um on on training larger and larger models uh in terms of more compute spent on RL, not necessarily model size, right?
1:40:12
Because your model size is baked in at pre-training. Yeah.
1:40:15
Uh w with Stargate coming online is like is there really no other way around that?
1:40:22
Like I feel like AWS is really big.
1:40:24
There's like other big clusters out there.
1:40:26
Can they just not get access to those or they do they truly not exist and will Stargate be like first of its kind?
1:40:31
You know, I think it's it's funny that my little like autistic obsession became the most political thing in the world, right?
1:40:37
Um and so like you know, you have you have you know obviously US, China, now Middle East, like there's all these geopolitics here, but but of course like the politics are between the companies too, right?
1:40:49
So there's the whole like OpenAI, Microsoft breakup, right?
1:40:51
There's a reason Stargate is not in Wisconsin, right?
1:40:54
Microsoft had a huge data center they're building in Wisconsin.
1:40:56
That's where it was going to be.
1:40:57
Uh but now Stargate is in, you know, Texas and it's not being done by Microsoft because OpenAI and Microsoft had all these politics, right?
1:41:05
A lot of which were really well reported but a lot of which have been sort of silent.
1:41:09
Um but you know and it's like okay well is Amazon going to give OpenAI compute? Absolutely not. Right?
1:41:16
Is is like Google going to give OpenAI compute? No way. Right?
1:41:18
U you know it's like it's like there's companies getting bought by OpenAI.
1:41:22
the deal hasn't even closed and they're cutting and cutting off access, right?
1:41:28
You know, sort of with the whole wind surf thing.
1:41:30
So, it's like, you know, it's like these things are so political and and and and little nerdy autistic boys don't know what to do with politics. Yeah. Yeah.
1:41:37
How much of that dynamic is driven by just like true AGI pilling at the top level of the hyperscalers versus just this is potentially a multi- trillion dollar? Yeah.
1:41:48
This is potentially multi-t trillion dollar outcome and like we need to have a player.
1:41:51
we need to cut off a competitor.
1:41:53
Um, what is there a dynamic there?
1:41:55
I mean, I don't think those things are mutually exclusive, right?
1:41:59
Like whether you're like truly agi pill like open aanthropic type people where you know you want for the benefit of humanity or you're like you're like Andy Jasse or like like Satcha Adella or you know whoever it is, right?
1:42:11
You're you're you're uh you're uh you know, whoever you are at the hyperscalers, you know, at the end of the day it's profit is AGI, right?
1:42:19
If you have AGI, you hope you could profit off of it, right?
1:42:21
The the the people at the labs would like be like, "Well, I don't know if AGI would let us profit off of it."
1:42:26
Um, but but in the meantime, as we're building towards AGI, that is a, you know, trillion dollar, 10 trillion dollar, multi- trillion dollar thing that you're you you have under your control. Yeah.
1:42:35
Do you think we'll be able to tax the profits of AGI even if we can't reap them?
1:42:41
Because I was looking at the Trump Elon breakup and I was wondering, what does this say about their AGI timelines?
1:42:47
Because if you really pill lion does not concern himself with deficits. Yeah.
1:42:50
If you believe AGI 2027 or AI 2027, like the budget deficit doesn't matter, right?
1:42:58
Like we're going to be printing 20% GDP growth, we'll be able to pay back trillions of interest in just a couple years.
1:43:05
Um, so I I think it's I think it's quite funny.
1:43:07
Um, you know, this this opening, sorry, this Elon and Trump sort of drama like you know who's you know who's like sitting there like, "Yes, yes, I know who Sam is. Yes, let's go.
1:43:16
Cuz he's like, you know, like for a long time Elon was like, I'm not going to allow OpenAI to become a nonprofit or become a for-profit, right?
1:43:25
And he's suing them, right?
1:43:27
And and part of his like I'm sure part of his calculus for like going all in on Trump and you know, saying he loves him more than uh a man can love any other man like you know, you know, four months ago was like him thinking he could, you know, convince Trump and the IRS to not let them convert. Right?
1:43:43
Now, like it's like very obvious like what's the impediment like they're going to get going to be able to convert.
1:43:49
At the same time, Trump was always a Stargate guy. He's a big Stargate guy.
1:43:52
He announced the project, right?
1:43:54
Trump is Trump is a big number guy, right?
1:44:00
You get the hundred billion and he's like, "Hell yes, hell yeah."
1:44:01
Because this is this is what it's about, right? Yeah. Yeah.
1:44:05
Wait, uh before we move on from the OpenAI uh the next big run, uh how real is the narrative of like they're going to pull ideas from Deepseek?
1:44:14
The I think it was like FP8 was one of the innovations.
1:44:16
There were a bunch of other innovations.
1:44:17
Uh some of those were specific to the restrictions of chips, but it felt like some of them might be generalizable to just more efficient training runs.
1:44:25
Are there real learnings for the American labs that aren't GPU poor, GPU restricted from DeepSeek?
1:44:33
Um, so I think I think there's certain things that uh, DeepSeek did that the rest of the industry had already done in terms of like the OpenAIs, right?
1:44:39
FP8 training was one of them, right?
1:44:41
Open AAI has been doing FPA training since at least 2023 um, perhaps earlier, right?
1:44:47
Now, on the flip side, there are certain things that like uh, Deepseek did that were a bit beyond what the labs had done, right?
1:44:53
And so, one of those things is like how sparse a model is, right?
1:44:55
is like how sparse a model is, right? um you know you have a mixture of experts model u you have you have so many experts in the model but you don't activate all of them for every forward pass of the user right um and so uh GPD4 was 16 experts two of them active right
1:45:10
so that's a 1:8 ratio um GPD4 ended up being like a 1:32 ratio but DeepSeek actually went even further they were 1 to 64 uh I wouldn't say that that's something that like the labs weren't planning to do but definitely Deepseek did leaprog a little bit right went a little bit further uh as far as publicly
1:45:28
available models and I know I know uh Google's models aren't as sparse as um as as open ais right and so everyone is headed that direction but deepseek definitely went a little bit further so I think it's like I think some of the more interesting stuff that deepseek did was around sort of like you know making
1:45:44
it open what the reinforcement learning verifiable reward paradigm is making it open um how how to do really efficient inference systems right um these are the sort of things that I think deepseek did that a lot of people can learn from um and also there their their there are special uh attention mechanisms. There's
1:45:59
There's some interesting work there.
1:46:01
Um even as far back as midl last year when Deepseek released a paper, everyone was like, "Wow, this Deep Seek company has really good uh research, right?"
1:46:08
So, it's I think I think there's things people can learn, but also there's a lot that like the labs had already done.
1:46:13
Uh they just weren't like maybe they didn't go as far or they did it, but it wasn't like they were passing on all the cost savings to the user, right?
1:46:20
Because they like to have margins. Yeah.
1:46:21
How much of the deepseek narrative around like it happened because China banned highfrequency trading is real and should we ban high frequency trading in America if we want to pull AGI timelines forward?
1:46:37
Th this is this is great.
1:46:37
Um I think like like some of the most cracked people I know at Anthropic and OpenAI are ex like quants, right?
1:46:44
uh like Enthropic's best performance engineer who like writes all of the like per like you know improves the performance of their whether it's tranium or TPU or GPUs.
1:46:54
He's he's from Jane Street, right?
1:46:57
And it's like they're missionaries.
1:46:57
The there's still mercenaries over in the high frequency trading bucket with a few laws we could move those mercenaries over.
1:47:05
I'm not saying we should do it.
1:47:07
I'm just say I want to know your take. You there? Yeah.
1:47:12
I think I think um I think I think that the um with with you know with the mercenaries right it's like well the labs can just pay more money right and they do they're luring over the people they want with these crazy um salaries I think we're kind of going back and forth on the uh can you hear us okay we good yeah I can hear you okay perfect um uh let's uh maybe let's move on to Google.
1:47:42
Um, uh, what was your reaction to, uh, the Google IO news?
1:47:47
And, um, and I mean, you put them in a tier.
1:47:51
Um, they have this, uh, incredible V3 model.
1:47:54
How much of that is due to the cornered resource of YouTube?
1:48:00
Is that a durable advantage?
1:48:00
We kind of saw the open web get scraped by every single LLM uh, foundation model company.
1:48:07
We saw all the code in GitHub kind of get exfiltrated one way or another.
1:48:11
uh is is that something that is going to be a sustainable advantage for them at least in video generation?
1:48:21
Um so so to some extent it's like everyone trains on YouTube right um like every company takes makes you takes YouTube into makes it into transcripts trains on it or even takes the videos and trains on it right every video model company is ripping stuff from YouTube uh this is like very well understood and
1:48:37
known but you know there's there's limitations on how much you can steal from YouTube right I think my favorite sort of clip of all time one of my favorite clips of all time is like when someone's like hey Mera did open I train on YouTube and she's just like if you don't You know the bee. You You know the beep.
1:48:51
Yeah, there's definitely some data that got out, but but but there's the scale of data like with YouTube, it feels like just in if you were to tokenize it and then compare it to GitHub's tokens like you're looking at orders of magnitude and that seems important in terms of just right.
1:49:03
I I don't think you can just rip all of YouTube like that, right?
1:49:07
Like they have they have protections against that, right?
1:49:10
Sure, you can get engineer ways around like pulling some videos, but like YouTube gets 500 hours of video uploaded every is it like every minute or something? It's insane. Yeah.
1:49:20
And I mean just the storage costs alone.
1:49:21
Like you would be able to see the storage center for the copied YouTube like from space.
1:49:27
Well, speaking of scraping, I'm curious.
1:49:29
So, so Reddit and Anthropic are in a lawsuit right now around Enthropic scraping Reddit.
1:49:34
Uh I was surprised that they didn't have a deal in place.
1:49:37
Do you think there was, you know, meanwhile Gemini has a deal, OpenAI has a deal with Reddit.
1:49:43
Do you have any insight into why Anthropic would, you know, not even make something happen when clearly it's sort of a valuable and important platform to to train on.
1:49:53
Um, I mean like like the data is the boat, right?
1:49:57
And if if you can get away with using the getting the data without paying for it, then you're going to do that, right?
1:50:02
Um, and I think like, you know, I don't know about the legal ease, but like isn't Open Eyes deal with Reddit like hund00 million like a year or something insane? Um, Gemini is like 60.
1:50:14
Yeah, they're like they're both around 100 million a year and that makes up about 20% of Reddit's overall revenue.
1:50:21
But of course, that revenue is super high margin.
1:50:23
70 million 70 million a year. Yeah. From from both. Google is 60. Yeah. Okay. Right.
1:50:29
So, so like if if that's the case, like what is what does that like lend you, right?
1:50:33
Like $70 million a year is is a ton of either, you know, it's it's like 70 researchers, right?
1:50:38
Or it's like it's like thousands of GPUs, right? Right.
1:50:44
So, it's like, you know, which would you rather, you know, like yolo and and just not pay for the data?
1:50:48
Uh and now like Anthropic can probably just like, you know, fight it out in court for a couple years before they finally pay Reddit, right?
1:50:58
And then are they going to have to pay as much as Google and and OpenAI?
1:50:59
Well, that would like seem unfair, right?
1:51:01
So, like they're kind of going to get away with like having not spent the money.
1:51:06
So, maybe that's a good good sort of uh view.
1:51:08
Obviously, there's also the view of like, well, it's not actually like stealing data because it's like training on it, you know, whatever. Yeah. Yeah. Yeah. Totally. That's interesting.
1:51:14
Um on XAI, you put them in B tier.
1:51:16
Uh there's a world where Elon being on the outs with Trump draws more scrutiny to some of his companies like Tesla and uh and SpaceX.
1:51:26
XAI feels like completely off of the political agenda in Washington.
1:51:29
So maybe this is a bullcase for XAI because they have Elon has more time to focus on it if he's not spending less time in Washington.
1:51:38
Uh what's your view that I have a fun anecdote? Right.
1:51:41
So, um I have a buddy who works in like manufacturing optimization uh at Tesla of like specifically how they like press the steel parts and like you know make make the body, right?
1:51:51
Um and he's like, "Dude, I haven't had a meeting with Elon in like 9 months. I'm right?"
1:51:57
Like I just like what am I going to do?
1:51:59
Like he's going to come in.
1:51:59
So So the thing is like Elon's amazing because he comes in and he's like, "Why are you doing it this way?" Yeah. Why? Why? Why? Do it this way. Yeah. Yeah.
1:52:06
And then and then you have to like either do it that way or come up with a really freaking good reason why not.
1:52:11
And he's just such a first principles thinker.
1:52:13
But now but but for like 9 months it was like well I'm going to continue to drive down the path that I think is best. Yeah.
1:52:18
Ideally you want that rapid iteration, right?
1:52:22
It's like you want him to come and just like get angry at you every day instead of once every nine months. It's actually better.
1:52:27
I mean I mean like it depends, right?
1:52:29
like maybe it's not every day, maybe it's not every week, but like there is a level of like he comes in, he resets all your priors and you like reset your road map kind of.
1:52:36
Um, and like the flip side is like, you know, for the for the employees, it's like, well, I might now have to go back to working like 100 hours a week, whereas like when he was gone, I could work like 40 to 60, right? And it was great.
1:52:47
Um, so so so I know Tesla definitely had a lot of neglect.
1:52:51
Um, uh, I know Neurolink had a little bit.
1:52:54
um XAI uh some but XAI still had like quite a bit of interaction from Elon, but obviously that's just going to grow more.
1:53:01
Um and so I think I think it's probably a good thing that these companies have Elon coming back and devoting all his time and effort.
1:53:10
Uh the flip side is that like XAI does have like a government like facing like sales um as does anthropic as does open AI and now is it like XAI is going to lose out on those sort of government sales but at the end of the day government sales are like pretty small relative to private industry where where do you expect uh most of XAI's revenue to to come from a year from today?
1:53:37
That's that's a great question.
1:53:39
Um I don't think it's consumer right because probably most of their revenue today is like the Twitter subscription right u I guess because XAI is X now right so like the categories that matter it's like consumer developers and then traditional enterprise right is there
1:53:57
like people don't seem to be plugging gro into cursor or windsurf and we haven't seen people vend Grock but it's just so early that maybe they could win in certain you need you anti-woke receipt heat processing or something like Yeah. So, it's just at some at some
1:54:10
So, it's just at some at some point, you know, there there's going to need to be a lot of revenue on the XAI side.
1:54:16
It can't, you know, X, you know, X the everything app can do a lot of work.
1:54:19
Maybe they add payments and things like that. I'm curious.
1:54:20
I I'm curious if you think that um the merger is actually net good for X the social media platform in the long run because my con my concern is that it's actually X the social side of the product that will really suffer over the next few years.
1:54:37
But I'm curious how what your read is.
1:54:39
Um I think I think um it was clear before the acquisition that X had a lot of debt um and they had they didn't they didn't generate enough profit to pay it off.
1:54:48
generate enough profit to pay it off. Uh so their EBIT was like bad or not EBIT sorry just their earnings period obviously uh before interest in taxes it was fine but they just had so much interest payments um and so that's why that's that's why I think XAI acquired it um it is beneficial right XAI does
1:55:06
get access to a data source that no one else has um and like like like the fastest data source out there right X is way faster than any other data source out there so I think that's that's hugely beneficial um but as Think about like what is the highest value ways of organizing the world's information and acting upon them and it's like today
1:55:26
everyone's sort of highest revenue thing is is code right cursor just hit 500 million ARR right um and and you know you know all these other windsurf just got bought for this crazy amount of money right like is revenue even even copilot at github at at Microsoft and github apparently isn't doing 500 million a year in run rate yeah but like
1:55:45
like code is like where all the money is being made today um and the question is Like I think I think all of the labs sort of like at least open AAI enthropic uh especially anthropic believe that like code agents software agents is where the most money and most progress is going to be made over this next 6 months. Um I think XAI also believes
1:56:01
Um I think XAI also believes this to a large extent but they also believe some other things right um but but you know I think I think automating businesses and helping them become more efficient is going to be where most of the money is made not consumer.
1:56:15
So yeah, I mean I I guess you kind I can maybe guess your answer, but do you think Anthropic needs a dance partner or any dance partners because you could see them going out and getting Pinterest or Snapchat?
1:56:25
I don't know if that would be valuable, but uh they're kind of the one LLM that doesn't have a huge consumer front door to their product.
1:56:32
And maybe that doesn't matter on the revenue side, but maybe it matters on the data side. Yeah.
1:56:40
So I think um I think they're just too AGI pilled to think consumer matters at all, right?
1:56:45
Like they don't care about voice modality, right?
1:56:46
Like they just don't think it matters.
1:56:48
And it's like voice matters a lot, right?
1:56:49
Um at least for like consumer applications, right?
1:56:53
They don't they don't care about like image generation, right?
1:56:55
So it's like do they need a do they need a dance partner?
1:56:59
Uh there's a really good Mexican song called Asia by Solo.
1:57:01
Uh and so like I don't know if you know him, but it's got a freaking trumpet and everything. It's such a good song.
1:57:06
Um, and it's like, no, they're going to they're going to stay they're going to dance alone.
1:57:10
They're going to dance alone.
1:57:11
Are uh staying in the Elonverse, are you worried that cheap robotic arms will take the jobs of humanoid robots?
1:57:20
Um, so so I think like colloquially like everyone just talks a lot about humanoids. Um, humanoid robotics.
1:57:24
Uh, but it's like most of the applications that I think are automatable in the next 2 3 years do not require legs, right?
1:57:34
Like if I go to a warehouse, if I go to a data center, if I go to a factory, the floor is a flat slab of concrete. Yep. Right.
1:57:41
I do not need to spend all this weight and energy and power on legs when I could just throw wheels on it, dude. Like come on.
1:57:48
Um and so like that's that's like one side of it.
1:57:50
And the other side is like human manipulation.
1:57:54
Um it's it's actually funny like AIs are going to be way better at us than like software than they are going to be at like just manipulating, right?
1:58:01
like picking things up, right?
1:58:03
Like it's like it's like hands are freaking incredible.
1:58:08
And no, we we aren't even close to, you know, human level hands on um on on a physical basis, let alone the AI that we have in our brain that's, you know, developed over thousands and millions of years versus, you know, the the sort of language capabilities which have only evolved over the last 5,000, right?
1:58:22
Um, so I think I think um it's going to be hard for humanoid robots to be like take off immediately, but there's tons of applications where um you know humanoid robots will still be able to do basic things, things that are um capable like low low risk of getting it wrong so you can try again.
1:58:40
Uh, and then the other aspect is, you know, what about what about like I cut the cost of a humanoid robot in one/10enth because I have wheels and so I cut weight down dramatically and it's way more efficient and instead of having fully formed hands, I just have like three gripper fingers, right?
1:58:54
And that's all I need for like, you know, data center automation.
1:58:57
I just got to plug in things and take them out, right? Unscrewing things.
1:59:00
Maybe my arm is just a screw and then the other one is like a three-finger, right?
1:59:03
And it's like this is way way cheaper and specialized to the task than a humanoid.
1:59:06
Uh, not that I'm like against humanoids, but as far as like, you know, robot arms, yes, that's part of it, right?
1:59:12
Like a lot of tasks, it could be a stationary robot arm.
1:59:15
Um, but the important thing to consider here is that literally all of this will be made in China and none of it will be made in America. Why is that?
1:59:24
Uh, the supply chain for Chinese robotics is soundboard.
1:59:31
We're very pro from America here.
1:59:33
Yeah, the audience is very America.
1:59:36
Um, it's sad, but it's like, you know, the supply chain here is like China's China makes more robots.
1:59:41
You know, if you go back 5 years ago, China made as many robots as roughly Germany, uh, South Korea, Japan, and the US, right now, China makes more robots than all of them combined, right?
1:59:51
Um, and the cost that they do that at is way lower.
1:59:56
And like, well, the Japanese companies argue that they're that the Chinese robots are Yeah, but like you speedrun up like quality faster than you speedrun down on cost.
2:00:03
Y um and like the same applies to like Germany, although Germany sold some of their best robotics companies to China and all the tech got transferred, but like you know it's like we don't have the manufacturing supply chains to turn, you know, raw goods into motors or into actuators.
2:00:18
Um and if we can, you know, or or when we do, it's like it costs 10x as much. Yeah.
2:00:23
And so it's just like it's it's impossible at least in like some huge industrial policy for the US to compete here.
2:00:30
So I mean it seems like there's almost an analogy there to the semiconductor industry where China has been lagging there for decades but has done a lot to at least catch up to the lagging edge.
2:00:45
Are there any policies that that or investments or industrial policy that China did to at least stay in the game to the degree that they did that we should be stealing from them and doing here for robots and manufacturing 10 five year plans back to back 10 five year plans.
2:01:03
I think the funny thing is that when you look at industrial policy uh the way China does it sometimes is more capitalistic than the way we do it.
2:01:12
Now obviously like you know giving a bunch of money to an industry is not capitalistic but the like the exact policy mechanism of the chips act versus what China does is like so much better right so like China does like oh you just get like x subsidy for
2:01:25
manufacturing a certain amount right like oh it's a company by company deal and this company gets this money for this plant right um or or like hey we're just going to subsidize the land in general for this or hey if you build a fab that is 28 nanometer you don't have taxes for 10 Right. And so stuff like this is what
2:01:41
And so stuff like this is what China's done and that's had them like dramatically increase their uh semiconductor spend.
2:01:47
You have things like the National Railway Company is now making power semiconductors, right?
2:01:52
Because because they make profit and they're like, "Well, if I make fabs, then I can blow all my profits from the uh the the railway in that and then all my all my fab profits will just be profits without tax, right?"
2:02:03
And so now one of their largest railway company is like the third largest power chip company in China and like top 10 in the world and and over the next few years they're going to be top five period right uh across the whole world.
2:02:16
right uh across the whole world. I think like things like this are like interesting industrial policy and probably we can get like the car companies you know and uh various you know like John Deere and like all these like automation like these mechanized things uh to get them to get start
2:02:33
pushing into robotics right cuz like BYD is pushing into robotics and like obviously everyone knows about unit but like you know Xiaomi is making cars and getting into robotics right like all these companies are getting into robotics in China because of industrial policy Um and and they did the same with autos, right? EVs. They went into EVs EVs.
2:02:49
They went into EVs because of industrial policy or they went into semiconductors because of industrial policy.
2:02:54
Like America doesn't have that, right?
2:02:57
Like we just have maybe you know we have the startups who are mostly just buying Chinese equipment and repackaging it and pretending like they make it here.
2:03:04
Like figure um or um you know like well we also we have we have American VCs who put American flags in their offices.
2:03:12
That's got to count for something, you know.
2:03:13
I mean I I'm not saying it's not noble.
2:03:16
It's just like I'm joking.
2:03:17
Um uh on on unitry, what do you think the perception of unitry is in China?
2:03:23
Because if you're if you're a believer in the wheels and the different actuators, it feels like they could be more like China's Boston Dynamics where it's like, oh, bunch of cool videos, but not a lot of actual applications.
2:03:38
But the reaction in America to unitry videos is, oh my god, there's this crazy wave coming.
2:03:44
Um, but but maybe I love that every video of them is just like doing war things.
2:03:52
Like, do you really want to scare the West? Like, totally.
2:03:53
Why don't you just have it like petting bunnies?
2:03:56
Like, you know, trust us, the Chinese robots are not dangerous.
2:03:59
They should be doing that. Yeah.
2:04:01
I was wondering like I I fully expect that there will be one of those like North Korea style military marches with a hundred like a 100 thousand humanoids and it will just be terrifying even if the capabilities aren't actually there for real war fighting just the demonstration.
2:04:15
Did you see the uh humanoid uh marathon in China? Yeah.
2:04:20
But but anyway, so to answer your question, right, um um Uni Tree, yes, we see the like the humanoids, the the robot dogs, but they've actually released a robot dog, but with wheels.
2:04:33
And so it's just like two, it's like sticks and it has wheels.
2:04:36
And they're releasing a humanoid with wheels actually.
2:04:38
Um they just showed it off at this uh conference uh in Singapore that one of the guys on my team was at.
2:04:44
Um and so like um they're they're coming with the mobile manipulators, but also you have to recognize like for the cost that they make in $10,000, Western companies make in like $75,000 or $100,000, right?
2:04:55
So like the quality of hardware they can make.
2:04:59
So that's also like an important consideration. Yeah.
2:05:00
Um you said you said something earlier around all the you know the next value in uh models coming from automating businesses.
2:05:08
is the right framework for that agents.
2:05:10
Is that how you how how someone should conceptualize it or is it an entirely new paradigm um that that's less about you know agent human kind of collaboration and more so just like full autonomy. Yeah.
2:05:26
I mean I mean uh the the dream is always multi- aent systems right many different agents working together and just doing the job.
2:05:31
just doing the job. And then uh but today you know the time horizon for human model interaction has been growing rapidly right initially it was like seconds right um it's getting to minutes or if you use deep research like 30 plus minutes right um and and and this is going to start extending to many places
2:05:49
like code u you know if you use uh cloud code you know the the time interaction is like minutes not not second uh not seconds um and so I think um it's it's and it can even extend to tens of minutes I think I think these agent systems will it'll be it won't be like a hard like hit, right? Like everyone's
2:06:04
Like everyone's expecting sort of like oh we have chat bots now I have agents but really it's going to be like a blended curve of like yeah you know like just like the amount of interaction the human has with the system get becomes less and less and less over time. That's a good framework.
2:06:21
Uh, sorry to move back to China, but uh, Alibaba, Quen, um, what, uh, I I I mean, it seems like they're just pumping out like a million different open source models.
2:06:32
What's the reaction been to the American research labs?
2:06:34
Have we actually learned anything from that?
2:06:36
Um, uh, we've had some folks on the show who've been just generally excited to play with so many different research tools, but, um, but are they trying to commercialize that?
2:06:47
And I guess my big question is like what is the actual chatbt of China right now?
2:06:51
Like what is the what is the consumer front end?
2:06:54
So so on the on the latter point the consumer front end is is is DeepSeek offered through the clouds right?
2:07:01
So some of the cloud companies like Bot Tensen etc offer uh DeepSeek uh the model but through their own platform rather than through DeepS um and some of them will offer it through DeepSseek themselves directly.
2:07:14
Uh but the interesting thing to note here is that we sort of have a very big dichotomy here.
2:07:18
dichotomy here. Part of the reason deepseek costs so much less on inference than you know US models is because the speed of deepseek's models right and there's this curve right of like how how fast does the model respond to you versus how many users you can batch together right so if I have like and
2:07:34
it's a system and I'm only serving one user it's going to be bl screaming fast right but if I'm serving hundreds of users each individual user is going to be slower now the total collective number of tokens I'm generating is much higher but this is interesting because when I use open AAI I I get 100 tokens per second, I get 200 tokens per second, right? Same with Google, same with
2:07:52
Same with Google, same with Enthropic, XAI, etc. , right?
2:07:53
Like you type the query and it goes like maybe twice as fast as you can read, so you can skim it, right?
2:07:59
Uh but if you do that to DeepSeek, it's like 20 tokens a second, right?
2:08:03
And I can read faster than the model outputs.
2:08:05
And that's a conscious decision because they're limited on compute on hey, I want to serve as many users as possible.
2:08:10
And so the chatbot style applications are actually very like bad.
2:08:14
And that's why that's why Chinese uh people tend to use like open router a lot to access like open anthropic models through uh in China even though they're not supposed to or you know accessing you know other companies uh models like through other methods.
2:08:30
So like I wouldn't say that there's truly a one consumer front uh front end.
2:08:35
Rather it's it's that the as soon as DeepS came out the the government started pushing all the companies to offer DeepSeek.
2:08:40
Uh but there there still isn't a good consumer uh experience right in China.
2:08:45
Moonshot is probably the most uh popular one.
2:08:47
Uh but their models aren't that good, right?
2:08:51
So it's like there I don't think it's one out yet. Yeah.
2:08:52
How much of an how much of an issue is uh owning the application layer if you're an u an independent country that doesn't want to rely on American or Chinese foundation models like what we've seen with Mistral and L chat.
2:09:07
There's this world where you spend all this money to build this data center in your country.
2:09:11
You spend all this money to train a model.
2:09:13
Maybe you're not at the frontier but you're you're close.
2:09:15
You're in the game but everyone just by default in your country just goes to chat. com.
2:09:19
And so unless you're willing to ban chatbt and you're not going that far, like you haven't truly won in terms of deploying your model with your view on free speech into your populace. Yeah.
2:09:33
So I think I think that's that's going to be challenging for like there are there are sovereign AI efforts in all these countries, but like you mentioned right uh Lech is not like that successful in France.
2:09:42
Um you know there and and this and and and Mistral is the closest of any like sovereign AI besides China and the US.
2:09:49
So like you know you're going to get all these models but people are just going to use the consumer like you know it's like am I going to use like like like Google models are so popular in India or like perplexity is like ridiculously popular in Indonesia for some reason.
2:10:00
Um like I don't know why but like these are just like frontier models instead of like from American companies rather than like um the the domestic model that could could be made.
2:10:11
Um and so I don't expect any sovereign AI efforts.
2:10:14
So so uh that to like truly succeed on the model level.
2:10:18
I do think that like you know sovereign can mean many things.
2:10:20
It could mean I'm making a bunch of data centers.
2:10:24
It could be mean I'm making a big neocloud company or it could mean like I'm going to make the full stack with the model.
2:10:28
But at any point if it doesn't get economical, you can always just like rent out like most of the cost of the GPUs.
2:10:33
You can just rent them out to someone else, right?
2:10:34
And then like try and recuperate your cost.
2:10:36
But you can't really do that with a foundation model that you've trained that has like mediocre weights, right?
2:10:41
So that is kind of right.
2:10:42
It's like it's like you just you burned all this money and flops on something that's effectively useless because Meta's open source model and Deepseek's open source model and Alibaba's open source models crush you. Yeah. Yeah.
2:10:53
Uh speaking of Meta, uh I'm try I've been trying to work through what's going on there.
2:10:57
There's obviously kind of the dust up around Llama 4 launches, but uh somebody asked me like what is the bull case?
2:11:04
And everyone always says like, oh, recruiting or you know, some beneficial thing or benevolent thing.
2:11:10
But I was wondering if there's a reasonable case to be made that if you try and just project out what Meta's LLM spend would have been on other vendors o in five years, it would have been so big that even if they're constantly on the lagging edge, they're still recouping the investment in training llama just because they will be able to serve it internally.
2:11:33
Is that a reasonable uh like like thesis or is there something else going on there?
2:11:40
Like what what do you think of like the the motivations and and problems with that project?
2:11:43
I mean they have like internal llama models too that are trained on their internal codebase that they can use internally, right?
2:11:48
So that sort of stuff is like something they could just never get elsewhere.
2:11:51
Um but I think it's I think it's a a multiffactor thing, right?
2:11:55
Like uh the bullcase is obviously a personalized AI assistant on my glasses.
2:12:00
Um, and that's just always on my head, always serving me up slop.
2:12:04
Um, but like so truly winning in the consumer use case like like right like truly the real Yeah, that's that seems to be what Meta is actually going for.
2:12:14
Um, but as far as like you know today they roll out WhatsApp uh Instagram and Facebook models uh meta llama models to everyone and they claim they have 500 million monthly active users right which is a lot right now.
2:12:26
Imagine if they didn't offer that, right?
2:12:28
didn't offer that, right? Would people start uh using chat GBT instead and now they're out of that a meta ecosystem and their screen time goes down and they get look at less ads or does like Apple intelligence uh become more powerful and that people go to Apple intelligence for
2:12:43
their AI because that's the that's the AI that's most accessible um and now all of a sudden Meta who already has been screwed by Apple multiple times on advertising is now getting screwed even harder because all of the like like more and more of the data keeps going to Apple and there's no way for Meta to get access to it. It's like there's an
2:12:58
It's like there's an existential threat here too, right?
2:12:59
Um, and so I don't think I think it's like prudent that Meta spends on these models.
2:13:04
I'm also like a lot more bullish on Meta longterm than like most people are.
2:13:09
Um, people are like looking at Llama 4 as like a single point in time of like, "Wow, this really sucks."
2:13:13
Uh, but there's like two models here, right?
2:13:17
There's like Maverick and their Scout.
2:13:19
Um, one of them is really bad and one of them is pretty good, right? What about Behemoth?
2:13:22
Isn't that another Don't they have a third rough name? They didn't release it. name, but uh yeah.
2:13:26
Yeah, it is a weird name cuz it's like very demonic and it's like you're unleashing this demon.
2:13:32
But well, the funny thing is the architecture is super similar to GPT4. Oh, really?
2:13:36
But like Yeah, it's it's like extremely similar.
2:13:39
It was just like a very funny naming scheme because like the behemoth is like the untameable beast and like they couldn't tame it to get it out the door and so like the name really mimics like what what happened with that project.
2:13:51
But um so yeah, I mean what are are are they uh gated by uh scale?
2:13:58
Are there I mean the capex expense seems to be growing but similarly to all the other hyperscalers uh is there anything that's unique about uh meta over the next couple of years that could kind of give them a compounding advantage there and and allow them to kind of come from behind?
2:14:14
I I do think they are still spending less on genai than other hyperscalers.
2:14:18
um note that like 60 70% of their GPU spend is on recommendation systems and like standard business and like nowadays that means like creating genai ads and those have more click-through rate like that's the that's the holy grail for the next 6 months for them.
2:14:31
Um so it's not like there there's no Genai in there but like a lot of it is on their classical business.
2:14:36
Um but generally like they are a player to be reckoned with, right? Like Open has Stargate.
2:14:41
Uh Meta has their Louisiana project.
2:14:43
I don't know if there's a fancy name for it.
2:14:45
Um, and like everyone everyone has like their big projects and so when we get to 26 27 everyone's going to have these gigawatt scale data centers with, you know, close to a million chips, right?
2:14:56
Um, and and the game continues to fight on.
2:14:59
I don't think that like this is a temporary setback for Meta, but they continue to recruit, they continue to have um, you know, good talent.
2:15:06
Um, they'll be reorganized, right?
2:15:08
Like without pain, you don't like get better, right?
2:15:10
So this is this is a learning experience for them.
2:15:13
So uh on meta and and scale they partnered with constellation on this sort of uh basically agreeing to purchase nuclear energy from constellation for the next 20 years.
2:15:23
Uh what what's your updated take on nuclear?
2:15:29
We obviously have these new EOS to help support it yet it still feels pretty far out at least for bringing new energy online.
2:15:36
How how are you thinking about uh the category? Yeah.
2:15:41
So like even even like in general building new nuclear reactors is still going to take a really long time.
2:15:46
Uh and if you're a believer in AI27 or AI 2032 uh whatever the number is uh that's too long of a time scale to matter, right?
2:15:57
Like you know this is this is still in the deficits can be largest possible time frame.
2:16:01
Um I think I think uh with regards to like nuclear that's the case for standard u you know gen 4 reactors.
2:16:08
Uh but when it comes to like SMRs, uh they didn't ease the most important regulation, right, which is that like the concrete containment zone, you know, this containment zone for the SMRs still has to be like monumentally big, right?
2:16:21
Even though it's like a much smaller, much safer thing.
2:16:22
Um and so, uh they didn't ease that regulation.
2:16:25
So, I'm not that bullish on SMRs yet either.
2:16:26
Um and and basically like yes you can sign these deals for nuclear power but that's nuclear power that was already being used by residential and now those residential or like industrial whatever it was just turns to gas.
2:16:38
Or on the flip side right if you look in like Louisiana Meta's data center uses gas right or if you look at Stargate it uses gas.
2:16:44
Or if you look at uh Memphis, Tennessee XAI, it uses gas, right?
2:16:49
Like you know, you look at um you look at Amazon's Indiana facility, project rainer, it uses gas, right?
2:16:56
Like everyone just uses gas and like that's are the ESG commitments that the hyperscalers made in kind of the prior era uh like informing any of like are are they acting as like handcuffs or shackles or like leg weights going into this next energy buildout?
2:17:09
So, so the funny thing is some of them have backed off a little bit like Meta and Microsoft have backed off some.
2:17:15
But the other thing you can do is just like pretend like you're still green.
2:17:19
Um, and so what you do is you do this thing called a PPA, right?
2:17:22
Which is a power purchasing agreement.
2:17:24
So you can set up like solar panels like 100 miles away and they'll generate power only during the day, but that power generated during the day is enough to cover the entire night of the data center as well.
2:17:36
But the actual electrons being consumed are not from the solar panels, right?
2:17:40
The solar panels are just selling it to the grid, but you purchased it and sold it to the grid.
2:17:44
Whereas the power that you're buying from the grid is like coming from a gas plant.
2:17:47
The actual electrons you're consuming are from there.
2:17:49
So then you're pretending to be green because you have this solar PPA backing it up or you have this wind PPA backing it up.
2:17:54
But in terms of actual electrons being consumed and new plants being built, it's gas. Yeah.
2:18:00
Uh let's talk about I think this has their their their regulatory ESG stuff is like malleable enough that this is allowed.
2:18:08
They're working through it.
2:18:09
Um let's talk about some of the other sci-fi concepts for energy generation.
2:18:12
Uh people are starting to talk about uh data centers in space.
2:18:14
Uh people are talking about data centers in the middle of the ocean with tidal energy.
2:18:20
Basically go where the energy is basically free or you get something for free.
2:18:23
Maybe you get cooling for free or land for free.
2:18:25
Uh is any of that relevant to what you've been uh focused on?
2:18:29
Um, so Microsoft's tried putting a data center in in in the water before uh for cooling, right?
2:18:33
Um, and that didn't that didn't work.
2:18:36
Um, and it's the same reason why space data centers won't work anytime soon. Okay.
2:18:40
Um, and as far as title energy, tidal energy is like interesting.
2:18:45
I think it could work, but like, you know, it's a bit of ways.
2:18:46
Um, the main thing on why data centers don't work, whether they're you're sticking them underwater or you're sticking them on a barge in the middle of the ocean or you're sticking them in space, is that GPUs are really really unreliable. Right?
2:18:58
So we we we have we've done a bunch of like testing of GPUs.
2:19:00
Uh we we reviewed 40 different clouds up to you know thousands of GPUs in fact in some cases but hundreds usually um or and and many time it was called cluster max right where we tested like 40 different clouds including like Amazon Google etc.
2:19:17
Everyone's GPUs are unreliable because they're inherently unreliable.
2:19:19
And what happens when a GPU is unreliable?
2:19:22
Sometimes it's as simple as, oh, turn off the server, turn it back on, right?
2:19:27
Sometimes it's unplug an optical fiber, you know, a transceiver and plug it back in, right?
2:19:31
Um, sometimes it's like take the GPU out of the socket, put it back in.
2:19:35
This is like the vast majority of fixes.
2:19:36
I don't know why you need to do this, but like that's that's how tech works, right?
2:19:39
You unplug it, you plug it back in.
2:19:41
And and and like you need people to do that, right?
2:19:43
Um, yes, robots could potentially do it, but we're not there yet.
2:19:47
um the space of a data center like the physical size of it isn't that large.
2:19:51
Um like they're big in an individual basis, but like they're not even covering like a basis point of American uh land even in like a decade, right?
2:20:00
It's like they're very small.
2:20:00
So So like GPUs are really unreliable, which we've sort of proven with like cluster max.
2:20:05
Um and then the other aspect of space data centers that's really dumb is like how does heat get removed, right?
2:20:11
Heat gets removed because like you have atoms contact the heat.
2:20:14
they, you know, whatever's hot, they take the heat away and they're more excited as they leap, right?
2:20:17
You're you're taking cold stuff, you're making it hotter, and you're sending it away, whether it's water or um air, right?
2:20:21
But at the end of the day, you're radiating that heat um out of an evaporation tower or chillers or whatever into the general air around you uh on land.
2:20:31
But in space, there's no medium for you to like like how many particles are hitting your spacecraft and carrying away heat.
2:20:39
And also those particles that are hitting your spacecraft are generally quite excited anyways.
2:20:44
Um, but there's just like very few of them.
2:20:47
And so like there's no way to radiate heat away.
2:20:49
And these things consume tons of power.
2:20:50
So like they're unreliable.
2:20:53
They consume tons of power.
2:20:55
Power is cheaper in space, right?
2:20:56
Solar panels, you can you can have them like constantly having sun, but like it's like you know what about the fact that like you got to radiate the heat away.
2:21:03
radiate the heat away. um like people people try and put like tiny little p uh computer chips in space and satellites and they have a hard time cooling those right so it's it's a it's a problem that I don't think is like feasible something
2:21:15
that's feasible in the next sort of within the deficit spending is okay time frame keep going back to that uh are you bullish at all uh are you bullish at all on new consumer hardware you know dedicated hardware for AI you know Uh Johnny IV joining uh friend.com. You might be com.
2:21:35
You might be calling in from a Rabbit R1 and we don't even know.
2:21:40
Uh are are you excited at all about kind of a third device outside of the phone or the the computer?
2:21:45
Yeah, I think um like the Johnny IV Sam Alman video is so cinematic. It's so good.
2:21:51
I'm excited for the product simply because the video is so good, the quality of it.
2:21:57
Um, but like like I don't know like there's I've seen I've seen that like this Apple device that has like a um it's it's basically an AirPod with a camera, right?
2:22:05
Um and like that that's pretty cool.
2:22:08
Um or like the AR glasses, right, with the cameras on them like the Meta Ray bands.
2:22:12
Um or you know all the other iterations of that.
2:22:15
I I think that a new device is definitely coming.
2:22:17
um with how good AI is getting, it means that the form of human computer interface can change um and it can be more natural and more seamless, right?
2:22:31
It's not going to be typing on a computer in front of a on a desk.
2:22:32
It's not going to be, you know, it's you're still going to have that.
2:22:36
You're still going to have your phone, right?
2:22:37
But really, I think like this like hands-free compute device is coming and and and it's enabled by AI. Now, will Meta win? Will Apple win?
2:22:46
Will OpenAI and Johnny IV win?
2:22:48
Um, yeah, I like I like Friend.
2:22:51
The founder is really cool.
2:22:53
Will they be a runner at all? Right.
2:22:54
Like um it's it's it's a hard space.
2:22:54
Um but I think like there's three companies that like seem to have a shot and it's like Apple, Meta, and maybe OpenAI Johnny IV. Yeah.
2:23:03
And Avi of course coming from behind.
2:23:07
The domain is just we got to give it up for the domain.
2:23:08
The domain is appreciate it.
2:23:11
They spend a fortune is worth every penny.
2:23:13
Uh on Apple uh you put them in L tier.
2:23:16
Uh, if Warren Buffett can learn to love Apple at age 75, can we AGI pill Tim Cook at age 65 or however old he is, is it possible?
2:23:28
What needs to change for Apple to become dominant?
2:23:30
They have so many advantages.
2:23:31
They have tons of lines in humor.
2:23:31
It's the AI that's made me laugh more than any other. That's true.
2:23:36
The the the that the text summaries that go crazily wrong and hallucinate weird things.
2:23:40
Very entertaining product.
2:23:42
Seriously underrated as a consumer product.
2:23:44
But what's your experience?
2:23:45
uh break down what's happening at Apple, what changes you predict, what changes you would recommend.
2:23:51
So, I think um they're clearly not, you know, that AJI pled.
2:23:54
Uh they haven't spent a ton on data centers and things like that.
2:23:59
Now, they do have like hundreds of megawatts going online in the next two years versus like the hyperscalers have gigawatts, right?
2:24:05
So, it's like, you know, it's like, okay, they're still an order magnitude off in like how much they, you know, want to fume.
2:24:12
Um, and then like the flip side is that Apple has started building an accelerator.
2:24:16
They hired some of the best people from Google.
2:24:18
Um, they already had a good chip team anyways cuz their chips for their phones and their Macs were good.
2:24:23
But it's like it's like getting the talent they didn't have.
2:24:25
Uh, they're partnering with certain companies and they're like they hired some of the best people from Google.
2:24:30
Uh, you know, including their like head of rack design, right?
2:24:34
Like uh rack architecture.
2:24:36
So, it's it's Apple's definitely um keeping far enough behind that at any point they could leap into action.
2:24:43
Uh but the challenge is always going to be like how are you going to get people to join this company?
2:24:48
And so this is sort of like my bullcase for like or not my bullcase but like a possible scenario for like thinking machines is that they just get acquired by Apple, right?
2:24:56
Like because at some point Apple will realize, oh god, we need talent and it's like there's no talent out there for us to hire.
2:25:04
when we try and hire, they're like, "No, screw this."
2:25:05
I mean, and Tim Tim barely makes 70.
2:25:07
He doesn't even make 75 million. He makes 74.
2:25:09
6 million, which is like a junior OpenAI researcher if they joined two years ago.
2:25:13
So, it's like, how can they compete?
2:25:15
Uh, that's OpenAI's janitor, bro. Yeah. Uh, is Lisa Sue cooking?
2:25:22
She acquired Bream earlier this week. C.
2:25:25
Can you break down that acquisition?
2:25:27
Uh, was it exciting to you?
2:25:31
What's going on over there? Yeah. Yeah.
2:25:33
So, so they actually acquired uh two companies. Okay.
2:25:35
Um this week they they acquired Brium u which which is more like LLVM compiler people.
2:25:40
Um I think it's more of like an aqua hire.
2:25:43
It's like 10 people or something like that.
2:25:44
I think uh it's not that crazy, but it's it's it's more commitment that they care about acquiring software talent. Yeah.
2:25:52
And what's funny is when they acquire aqua hire a company, the people at that company are getting paid a fair salary, right?
2:25:58
You know, like a like a very good salary.
2:25:59
salary. whereas like sometimes their hiring process they don't pay people enough which is why they don't always get the best talent um which is something that we've sort of uh mentioned but yeah so Bri's like an ML compiler and things like that and then untether is another one which was like making an AI chip um and they aqua hired them as well u mostly for the the the
2:26:18
staff on the hardware side I imagine uh because they just need to move faster uh to be able to uh release chips as fast as Nvidia is because Nvidia is just like clockwork spinning out new chips uh they're trying to go to that yearly cadence and such right So, I think I think Lisa Sue is is waking up to, you know, how important this opportunity is and that she needs to spend a lot more. Um, but note they're still spending a
2:26:37
Um, but note they're still spending a ton of money on um buybacks um when they could be spending.
2:26:43
I mean, so does Nvidia, but like Nvidia is also making like, you know, godly amounts of money.
2:26:48
AMD is making good money and then they could turn around and reinvest that, but they're not reinvesting as much as they should.
2:26:53
Um I think you know these are good aqua hires both untether and uh brim which are like both aqua hires.
2:27:00
They also bought like nodai right a while ago.
2:27:02
Um nodai is where AMD's sort of like god of GPU AI software is an he came from there.
2:27:09
Um like he's the king and and that acquisition was really good because they have like again like really good software talent that they were able to pick up.
2:27:16
Um it's just you know we need them to move faster if we want to take them like you know super seriously.
2:27:21
Um but the right direction.
2:27:21
What do what was your read on the NVIDIA earnings and uh kind of the lack of guidance around the training to inference switch over?
2:27:31
Do you have a better idea of what's going on?
2:27:32
It seemed like they had quoted a 40% number earlier.
2:27:34
They didn't include a new number.
2:27:36
Uh but this seems like an important narrative or maybe it's not around uh the actual workload shift.
2:27:43
And then I want to know if that's like relevant to AMD at all.
2:27:45
Is there an opportunity there? Yeah.
2:27:47
So, I think that Nvidia is going to have a hard time knowing Oh, really?
2:27:53
how much compute is going to inference versus training.
2:27:56
It's actually just like hard for them to know, right?
2:27:58
They don't get to know what workload their customer is running. They can guess.
2:28:01
They have the most data to guess, but like they can guess.
2:28:03
Would people not want to tell Nvidia?
2:28:04
I feel like if you're buying, you know, 100 million H200s, you might just be like, "Yeah, sure.
2:28:10
I'll tell you what I'm doing with them right now." Like, no problem.
2:28:11
I'll fill out your survey. Here's my NPS.
2:28:13
I think I think these companies are very secretive, right?
2:28:17
secretive, right? Like you know people like OpenAI won't tell Nvidia what their model architecture is even though if they just told them what their model architecture is Nvidia could optimize their next generation chip to it way better right and so Nvidia just has to
2:28:29
guess right and like hope that they know what openi is doing but they don't right like um they they have a good idea right and so like I think I think that's one aspect of it the other aspect is that the lines between training and inference are blurring right in the days of pre-training your cluster would be
2:28:44
training training training and then you deploy inference clusters but Now uh with uh reinforcement learning with verifiable rewards one interesting thing is that you know traffic is not usual right it's like it oscillates um and actually on the weekends chat app chat GPT is used very little relative to
2:29:01
weekday um during work and school hours chat GPT usage is huge during night it's not really right except for when like Giblly slop like is like trending that's the only time you have like usage uh you know higher during non- peak hours which is like work day, right? Um, and so
2:29:17
Um, and so what's interesting is that these clusters have lower utilization, but now I can turn around and start using these clusters at night.
2:29:25
For example, I can spin down a percentage of them and I can turn them to reinforcement learning with verifiable rewards.
2:29:30
I can generate a bunch of data, verify it, see if it's good or not.
2:29:34
You know, whether it's math problems, coding, or some other reinforcement learning uh paradigm like computer use, I can do it and then I can throw I can I can keep that data.
2:29:41
throw I can I can keep that data. And if I ever need to switch over to uh back to inference as usage is picking up I just like okay stop you know no more of that here's you know put the normal model on there and start doing inference and that can take like a minute or less right
2:29:55
like so it's like there is there is a blurring of lines of what is training versus inference um and then and then the other aspect is like can AMD get in there right um what's interesting is that you know AMD has generally taken this approach of like hey we're like 80% of the cost and we're the same performance, right? That's that's sort
2:30:14
That's that's sort of where MI300 sort of shakes out.
2:30:15
Some scenarios it's higher, some scenarios it's lower, but we're like 80% of the cost.
2:30:21
Um, now when you look at this new generation of GPUs they're launching, I think next week u Mi355, it's it's two/ird of the cost of Nvidia's Blackwell.
2:30:30
Um, but performance-wise, is it 2/3 or is it is it less, right? Or is it more, right?
2:30:36
And so this is going to be a challenge.
2:30:38
It's going to be it's going to rely a lot on their software.
2:30:39
Uh Meta is really excited about it, but like not too many other customers are.
2:30:43
And so the question is like can AMD get in there.
2:30:45
Um they're targeting inference mostly.
2:30:48
Um but Nvidia is moving the game really fast, right?
2:30:52
They're coming up with these new software libraries that uh don't just like it's not just CUDA, right?
2:30:56
It's like they're building the entire inference engine, right?
2:30:59
And AMD can't plug into that. It's called Dynamo.
2:31:00
So what Nvidia is doing around Dynamo is really locking AMD out from inference at the non-hyperscalers and labs because it just doesn't make sense for anyone else to try and replicate the software that Nvidia is giving away for free on Nvidia GPUs. Mhm.
2:31:13
What do you hope to see out of companies like Prime Intellect over the next one to two years?
2:31:18
Uh I I believe you're uh an investor in Prime Intellect. Is that correct?
2:31:24
Intellect. Is that correct? But but uh so uh I'm sure a little bit conflicted but uh but yeah talk yeah I mean I invested in the seed but like to be clear like our I'm pretty impartial right like we had this cluster max review and we didn't give them the best review even though I invested in them personally right so it's like you know
2:31:42
this is I think but I think what they're doing I'm really excited about right AI is super centralized right um and and this is the only path I see forward mostly for c is like that AI continues to be more centralized there's fewer and fewer players they have more and more control over our data, over automation of the entire world's economy. You know,
2:31:58
You know, this is this is potentially quite scary for someone who likes decentralized power systems and like capitalism and such is that centralization begets, you know, tyranny.
2:32:09
Um, and not not that I'm like being that dogmatic, but like their like their technology is mostly a technology reason, right?
2:32:15
They had cool demos around decentralized training.
2:32:16
Uh, they've trained models in a decentralized way.
2:32:20
They've done reinforcement learning with verifiable rewards now in a decentralized way.
2:32:23
I'm very excited about the research they're doing there.
2:32:26
And they're open sourcing everything, right?
2:32:28
Uh which is the cool thing, right?
2:32:29
You can just go look at what they open source.
2:32:31
You don't have to like trust, you know, anything.
2:32:33
It's like they they have some pretty good software.
2:32:36
Uh I'm I'm hopeful that there's a path to all AI and power not just continually being centralized until we, you know, are like enslaved by the machine god.
2:32:46
Except if except if semi analysis were to centralize it.
2:32:48
I feel like you know that rule people should be able to trust you.
2:32:52
You know benevolent sort of dictator world leader.
2:32:54
I could I could see that.
2:32:57
Call me the leewanu of AI for sure.
2:32:59
Um uh I I wanted to go more into uh the those like Studio Giblly moments when when people say quick quick fire off.
2:33:09
Would you hire somebody with a Studio Gibli profile picture or is that a negative signal? No, that's good.
2:33:13
in in our Slack, someone has a Studio Giblly profile. Okay. Yeah. Okay. I like it.
2:33:19
But and his public his public profiles are also a Studio Giblly. Okay. Wow. That's good.
2:33:24
Uh but you know, whenever there's like these big meme moments like they everyone says the GPUs are on fire.
2:33:29
Obviously, they're not literally on fire, but what is breaking?
2:33:34
Because is it is it that there's actually more unplugging and plugging it back in in the data center?
2:33:38
Like like when when we see Studio Gibble go out and like you know the queries are clearly failing.
2:33:43
Uh what's what what is it?
2:33:46
What do you think is happening internally?
2:33:47
Is it just too much load?
2:33:50
Because I feel like the chips are under incredible load during training, right?
2:33:53
So like that can't like they're used full times, but but why are we seeing um so much failure during these like spikes?
2:33:59
What like what's actually going on there?
2:34:01
With training, we know what's happening, right?
2:34:03
We're saying, hey, in this iteration, you're going to process this many tokens.
2:34:06
You're going to update the weights.
2:34:08
You're going to exchange them all.
2:34:09
Okay, here's more data for you to train on, right?
2:34:10
and you just keep iterating, you know, many many times, you know, every 15 seconds or 30 seconds or 60 seconds, you update the weights and you do it again.
2:34:17
Um, and you know how much data you're sending with inference, you know, you have these clusters and it's like it's that curve again, right?
2:34:22
Uh, if I just have one user, it happens really fast, great user experience.
2:34:26
If I have tons and tons of users, happens really slow.
2:34:27
Um, and while I am serving more users and I'm getting more output, each individual's user experience is worse.
2:34:34
user experience is worse. But at some point it gets so bad that you either run out of memory or hey a GPU does break now all of a sudden you're dropping uh requests constantly right so not only does the user experience get bad because it goes from fast to super super slow u
2:34:49
right like look at how fast Giblly is processed now right it's like crazy fast compared to what it was initially um but also like when something bad does happen you can't just be like oh take all these requests route them to these other GPUs right it's oh all these queries fail right? Like, oh, like I got I got more
2:35:04
Like, oh, like I got I got more requests than I'm able to handle.
2:35:07
Well, these users, I'm just not going to let I'm just not going to start processing their requests.
2:35:11
I'm say, uh, sorry, it doesn't work. Right?
2:35:12
And so, that's sort of when the GPUs are on fire, that's what happens. Right?
2:35:16
Now, also, um, I think I think it's mostly it's mostly that dynamic of like you add add that incremental user and things break or if something breaks, all those users now have their stuff broken.
2:35:30
Well, thank you so much for coming on.
2:35:32
Everyone in the audience should go to semianalysis.
2:35:33
com if you're not already subscribed.
2:35:35
Uh and uh we would love to talk to you again.
2:35:39
This was fantastic conversation. Super fun. A million. A billion. A trillion. I want to go. A billion.
2:35:44
Hey, add a add a Yeah, hit the size.
2:35:48
Go um add a add a new plan on semi analysis.
2:35:51
Uh 5 million a year and uh we'll we'll ask some of our VC buddies that just have a bit too much.
2:35:57
We will shame them into Oh, you're not on the pro plan yet. Yeah.
2:36:00
The the max the presidential the presidential plan.
2:36:04
You're on semi analysis ultra max. Wow.
2:36:08
You must not be serious about artificial intelligence. Oh.
2:36:10
Oh, you're not you don't really invest in AI, but Oh, you're not about the AI thing.
2:36:13
You're you're more just more of a tourist. I get it. Yeah. More of a tourist. Yeah. Yeah. You're B2B SAS guy. Yeah. It's cool. It's cool. It's great.
2:36:20
I'm sure you make a good living.
2:36:21
Sure you make a good living.
2:36:22
But anyway, this is fantastic.
2:36:25
We'll talk Thank you guys for having me on. Super fun. We'll talk to you later. soon. Bye. That was a lot of fun. All right.
2:36:32
Uh, you're going to love this, John.
2:36:34
I think you were too locked in.
2:36:35
We're going to have um Blake from Supersonic calling in at 2:15, 45 minutes to talk about the new EO. Oh. Oh, is it political?
2:36:42
You know, I can't you I can't pay attention to politics when I'm talking to an AI person.
2:36:48
You know, I just get too too locked in.
2:36:50
But that is fantastic news. Very exciting. I see your post.
2:36:52
Blake will be joining TVPN live at 2:15 PM PST to discuss the new Supersonic EO.
2:36:57
very excited to talk to him.
2:36:59
Uh and uh we have Dana Settle from Greycraft coming in the studio. How are you doing, Dana? Good to see you.
2:37:05
Hi, great to see you, too. What's going on?
2:37:08
Uh thanks so much for joining. Very exciting times.
2:37:10
Uh the IPO window is is is squeaking open and it's open more every day.
2:37:16
We talked to the founder of Circle today. Uh very good showing.
2:37:21
Would love to talk to you about that, what's going on in the markets, what you're investing in today.
2:37:26
But would you mind uh introducing yourself for the audience members?
2:37:28
For anybody that's been living under a rock. Yeah.
2:37:31
Living under a data center as you like to say. Yeah. Thank you. Yeah.
2:37:33
Dana Subtle, co-founder, managing partner at Gay Croft.
2:37:37
Um been a venture capitalist for uh a very long time.
2:37:40
Started out in 1998 on Sand Hill Road. So, wow. Seen a few cycles. Yeah.
2:37:47
What What was the first uh what was the first big deal that you kind of really really tracked or invested in or followed?
2:37:53
Like were you were you tracking like Yeah.
2:37:55
What what deal allowed you the right to be a VC for more than maybe four years, right?
2:38:02
Because it's you know the first four years it's kind of like you can make some bets but eventually you know there needs to be story.
2:38:08
Yeah it's a it's a good question.
2:38:12
Um so you know when I first started in venture we were investing in all kinds of things but more you know it was like networking equipment and semiconductors and storage and you know sort of that was building the the um last you know the really the first generation of the internet and so some of the companies um from that era were are are no longer exist.
2:38:32
They're actually bought by much larger networking equipment you know companies etc.
2:38:38
But a similar dynamic you know where we would invest uh um I didn't wasn't expecting this question so I'm basing it on the name of the company but literally it was like you know from oh god optical equipment company and it was you know in like 18 months sold for $2 billion. Yeah. Wow. Wow. There we go. That's amazing. Yeah.
2:38:59
To be clear though I was, you know, I was the number two on it. Course. Of course. Yeah. But that's great.
2:39:05
Uh it is fascinating how much the networking equipment space has kind of come back into focus with the AI boom.
2:39:10
We talked to Kevin Wheel over at OpenAI.
2:39:12
He's on the board of Cisco now, right? Yeah.
2:39:14
Uh and and so and we've talked to another founder who is working on uh optical cabling in the in the data center because as we scale up these models and so everything old is new again.
2:39:24
Um but what is most new for you?
2:39:26
Uh what have you been focused on?
2:39:28
What's been uh what's been in the news in the last couple weeks? Um yeah.
2:39:32
Well, I mean, in terms of what's new and what we're investing in is certainly in all of the, you know, sort of AI, everything from infrastructure up through applications.
2:39:41
Um, so that's not nothing terribly surprising there.
2:39:43
But it is interesting to really look back to the history, you know, sort of history of the internet and see how much things are repeating um right now in terms of what's being built.
2:39:52
Um, the other thing that we uh do is we actually have a sustainability fund.
2:39:57
Um, and we've done that in partnership with some strategic partners.
2:40:01
partners. So Coca-Cola and eight of their largest bottlers um globally and what's been so interesting about that is we are there's such a huge intersection essentially between AI and sustainability people don't really think about it but you know if you look at
2:40:16
energy consumption doubling by 2050 I mean something's something's got to give and oil and gas right now but I think that's where we see a lot of a lot of opportunity not just in renewables but actually in like the you know software ware and hardware for sort of reimagining how all of that's consumed. Yeah, you imagine that all the
2:40:34
Yeah, you imagine that all the hyperscalers are going to need to kind of re-evaluate their ESG mandates.
2:40:39
There's already a lot of companies in the space like Crusoe Energy started by flaring natural gas plants there.
2:40:43
There was wasted energy and uh there's obviously a ton of news in in solar and nuclear and all all sorts of stuff.
2:40:50
The energy landscape has been um fantastic.
2:40:55
Um would you mind taking us through the the latest IPO experience? How was that?
2:40:59
Uh I'd love to hear that story uh kind of from start to finish because uh it we like there's so many VCs that have been in the game for a long time and not actually been through that process because uh the companies love staying private. Well, other reasons too. Plenty of other reasons.
2:41:14
There's a lot of there's been a lot of pressure to stay private, right?
2:41:17
Well, it's really interesting. I mean, I don't know.
2:41:20
That's like a whole other tangent and I'm kind of obsessed with it because it is really interesting if you look at, you know, the what the public markets are today which I is really interesting.
2:41:29
It's just really different.
2:41:29
Um it's almost going back to potentially what it what it used to be, you know, where it was like smaller IPOs and it was um actually, you know, access to growth opportunities to more retail investors.
2:41:43
Um so uh so anyway but but our most recent IPO is a company called Mountain and it's a pretty amazing story incredible founder serial entrepreneur technical background and um really you know he essentially started the business I mean we invested actually in 2011 so this gives you a little bit of a sense of overnight success overnight success um overnight success we have a soundboard here like It's every founder we talked to.
2:42:13
I mean, we talked to the circle founder and it was the same thing.
2:42:15
He's like, "Yeah, I've been doing this for a decade."
2:42:16
And, you know, today actually, well, it's funny to see Jeremy Lair, you know, talking about, I mean, I remember when he had a video search startup in the last, you know, generation.
2:42:27
And so, it's really interesting to see these, you know, things sort of come full circle. Incredible entrepreneur. No pun intended. Yes. Sorry.
2:42:34
But anyway, back to the story of Mountain.
2:42:37
Back to the story of Mountain.
2:42:38
So, uh, so Mountain Mark Douglas, um, you know, really again, incredible founder.
2:42:43
Um, he had started, um, one type of an adtech business essentially, um, back in sort of the display days.
2:42:50
And when we first invested, just to give a sense, it was a $4 million series B. Wow. No way.
2:42:53
Think about like what that means today.
2:42:58
Now it's like four billion.
2:43:00
It's a series that's around for ants. It's around for ants.
2:43:04
But, you know, it needed a capital and it worked. Yeah.
2:43:06
and it worked. Yeah. And so and and really you know that market changed pretty dramatically when all of the regulation around cookies etc you know happened and Mark had the foresight to take what was a hundred million plus dollar revenue business super profitable and essentially build an entirely new
2:43:24
business saw that connected television would be the next major ad platform I mean and again seems very obvious now but wasn't definitely wasn't consensus at the time and he essentially just built that out of cash flow from the old business sunset that business and built this one up to now the company that went public uh two weeks. Uh we're talking to
2:43:40
Uh we're talking to the founder of AG1 uh next.
2:43:43
I'm interested to hear your take on celebrity partnership.
2:43:48
There's so many different configurations whether it's just uh the celebrity investing just like any other investor and then maybe they've add some value to co-founding the company incubations.
2:43:59
uh what is your view on the on the role of of celebrities or people that bring differentiated value ad in the startup ecosystem?
2:44:08
Well, I think what you just said is the key which is differentiated value ad.
2:44:11
Um, and you know, in the case of Mountain, we we did partner with Ryan Reynolds and and his marketing agency.
2:44:18
And um, you know, and that was sort of a fortuitous connection, but you know, it really just I I actually was introduced to to Ryan and his team as they were sort of thinking about what to do with their agency.
2:44:29
And it was just in this moment where I was like, "Wow, what you guys are trying to do in terms of really making ads that sort of, you know, move at the at this at the pace of culture, like I have the perfect platform for you."
2:44:41
And you know, really Mark and Ryan just sort of saw eye to eye on on on really how to build this business.
2:44:46
Um, but again, that was so really um authentic to Ryan and his team.
2:44:52
It's just like what they want to do.
2:44:54
They want to make really cool ads that really resonate with people, not to just make ads, but really, you know, to to sort of make them at the pace of culture, and Mountain is the perfect platform for that.
2:45:04
And and that's why I think it's worked so well.
2:45:05
We saw literally I mean the crazy thing is when you think about I think about celebrity or influence as being largely marketing right I mean it's and so if you sort of look for like a dollar for dollar replacement totally mountain's inbound leads went from like 2% to over 60%. Wow that's crazy.
2:45:22
Well, it's also interesting to think in a in a B2B business like Mountain, like somebody like Ryan Reynolds effectively acting as a sales rep and just like messaging a CEO and being like, "Hey, I'd love to set up a demo with you."
2:45:35
And it's like that just that impact alone in terms of bringing spend on the platform.
2:45:41
I mean, we've been joking about this.
2:45:41
We talk about ourselves as like enterprise influencers because all of our sponsors are basically B2B companies for the most part.
2:45:47
And and and and it's just like it's kind of a new era, but it but it's working.
2:45:51
And Ryan's clearly carved out just a very unique position.
2:45:53
It's he's not just somebody you just pay to show up for an ad.
2:45:57
And there are there are celebrities that have built great businesses on that.
2:46:00
Um but he's taking a very different tact.
2:46:02
I'm curious when you made the mountain investment, was there any was there people maybe in in the investment committee or other investors that were friends that sort of were writing off TV at the time digital was exploding.
2:46:15
And now you know looking back it's like TV advertising has exploded. It's continuing to grow.
2:46:20
Even in the US, I think in 20 past sometime past 2030, it'll be well beyond, you know, hundred billion dollars in in uh spend just here in the United States.
2:46:29
So TV advertising is clearly not going away.
2:46:34
But I could imagine 10 years ago a lot of um you know, you know, a a Facebook PM that became an investor would probably have written a memo that said like this market is going to you know, go away or or at least shrink. Yeah.
2:46:48
And and and I I would clarify I mean a couple things.
2:46:50
I think 10 years ago for for sure.
2:46:52
Um I think TV advertising has is changed.
2:46:55
I mean this is largely advertising on connected television, streaming television.
2:47:00
Um so really the distribution has fundamentally changed but um yeah I mean we actually had investments in some companies that you know like 15 years ago that were actually um you know improving the process for television ads and we sold those businesses gratefully and made a profit on them.
2:47:17
So, but um but so when Mark proposed this, I think what was counterintuitive is all of those businesses were subscription.
2:47:25
I mean, the idea was not to have ads in those streaming services, right? Yeah.
2:47:31
And so what's happened in the last 5 years is now all of those streaming models have moved to where the majority of subscribers that are coming on I mean if you look at the public earnings um from you know Netflix and um you know Disney etc.
2:47:44
that the majority of new users are coming onto their ad platforms. Yeah. Yeah.
2:47:48
Uh do do you have I mean I'm sure I'm sure you know investing and being in LA often um like there's probably celebrities that come to you with like hey I want to get into venture.
2:47:59
I want to have exposure one way or another.
2:48:01
Uh and there's so many different models.
2:48:03
Do you have uh any any recommendations uh for all the celebrities that are listening uh for for the the the best way to get to get exposure to tech or or just patterns to avoid so that they don't get over their skis? Yeah.
2:48:18
I mean, look, I think it's like anything like whatever you're truly really curious about and you really want to dig into, I mean, that's where you should spend your time, right?
2:48:25
I mean, I I think if you're just sort of dabbling, I mean, I guess if you want to have in investments um to sort of talk about because you think it's like just in the zeitgeist, then great, like invest in some funds, you know? Exactly.
2:48:37
I was going to say more more just LP. Yeah.
2:48:42
Either LP or like be deeply involved in the company. But yeah, exactly. Yeah.
2:48:44
Or if you just want to, you know, kind of learn about investing like that's a great way to do it.
2:48:48
I think if you want to actually be, you know, direct investing, angel investing, um, you know, I think actually, um, again, just sort of following like your true curiosity and the areas where where also where you can really make an impact.
2:49:00
And that's why I think like with, you know, again, going back to Ryan and his team, I mean, they're amazing marketers.
2:49:05
I mean, like best-in-class.
2:49:07
And so, um, you I think that's where, you know, I would just sort of like encourage any any celebrity to do what they're truly passionate about.
2:49:16
And I think if you you know look at um where things have really worked outside of you know Ryan I mean I think um you know what Gwynneith has done with Goop.
2:49:26
I mean I think it's just these are just very natural to I mean they're they're things and Goop Kitchen which is another you know sort of spin-off from Goop.
2:49:33
I mean it's it's the food side of it and it's again it's just what's so natural to her.
2:49:38
It's what people expect her to be you know sort of recommending and excellent at. Right. Yeah. Yeah. Yeah. Totally.
2:49:44
Um, what about uh what's your how how what are your thoughts around the evolution of LA's ecosystem on a personal level?
2:49:51
I think my last five LA county investments were in the Gundo.
2:49:57
Um, and uh haven't done haven't done much outside of that, but uh I'm curious, are you are you disappointed? Are you uh accepting?
2:50:07
Uh are you still excited?
2:50:11
Do you do you see a lot more growth here?
2:50:13
It seems like San Francisco has certainly sucked a lot of the oxygen out of LA if you want to be I I I had one portfolio company that was you know a consumer AI business that was in LA and just like had to bail like almost within two months uh just because of a talent a $350 billion company popping up in San Francisco will do that but yeah what is your been give us the temperature check on I mean you know look I think um there's No question.
2:50:42
I think there's a sucking sound back to to the Bay Area and you know again it's sort of like early days of any major technological shift.
2:50:50
Um you know I think that's naturally going to happen.
2:50:52
Um it's Silicon Valley you know and so we actually uh opened an office up there for the first time last year.
2:50:59
Um we've hired a new partner up there team up there and we're all spending a lot of time up there.
2:51:05
I I mean for us I mean I love LA.
2:51:07
I moved here I did spend 10 years in Silicon Valley before moving here but I moved here almost 20 years ago.
2:51:14
I think LA is an incredible market and I think having access to this market and really having a deep understanding of a lot of the industries and network here is super valuable.
2:51:21
Um but the talent density from a you know just technology standpoint right now Silicon Valley is just a super important place to have a strong network and so we're you know we're spending time both places.
2:51:34
We've also I mean we are spending time also in you know the gundo and in other and you know on other things um which are certainly um big growth areas in LA.
2:51:44
We also um led an investment that we think is super exciting uh called whatnot um which is LA based company you know fastest growing um largest live streaming shopping you know um platform in the United States.
2:51:58
So, I mean, we think that there'll always be great companies here and continue to be, but there's definitely a AI talent density in in the Bay Area.
2:52:06
I think we were talking when when not exits. Yeah.
2:52:08
When Whatnot exits, it'll be like LA's back. LA's back.
2:52:13
And then people will be like, "Oh, I never lost faith. I never lost faith." Yeah, it's hilarious.
2:52:16
Well, we had Scopley also lastly was fantastic.
2:52:20
That was that's pretty pretty great story.
2:52:22
And continue service Mountain SpaceX. Yeah, there's a couple.
2:52:30
It's not the worst place.
2:52:30
We're doing okay in the country.
2:52:31
Uh, but I I think LA kind of like surprises people when you dig into the numbers as opposed to it's not as loud because Hollywood is the thing.
2:52:41
It's the it's the Hollywood town that happens to be uh above expectations at in tech and hasn't made as much noise about it.
2:52:48
Uh anyway, this has been fantastic.
2:52:50
Thank you so much for hopping on. Super fun.
2:52:52
Congratulations on the on the big win. We'll talk to you soon. Great to see you guys. Bye. Cheers.
2:52:56
Have a Uh any any other breaking news that we need to cover in between our guests? No, we're good. No politics. Yes, we're so back. Let's talk about AG1.
2:53:06
Let's talk about consumer package goods.
2:53:08
Uh let's bring in Cat from AG1. How are you doing, Cat? Good to see you. Welcome to the show. Boom. Welcome.
2:53:16
Jordy, I'm going to let you take the intro.
2:53:19
Thank you so much for joining. Well, it's happening. How are you? I'm great. How are you guys? We're doing great. It's Friday. We wish it was Monday.
2:53:27
We We like podcasting a lot here, so the weekends are always tough, but um how are you busy?
2:53:31
I'm sorry for your wind down. I know.
2:53:33
Monday will be here soon enough. I know. I know.
2:53:37
I'm I'm sure you feel the same way.
2:53:38
Uh why don't why don't you give a quick intro? Uh a brief history.
2:53:40
We don't like to do uh make this, you know, biography, but um but but would love to to have you kind of give your background for the audience. Sure. Uh I'm Cat. I'm the CEO of AG1.
2:53:52
I have spent several decades uh in consumer.
2:53:56
I started opening franchises around the world when I was a teenager and had an incredible opportunities in restaurants, food and beverage and franchising for the first, you know, 20 years of my career.
2:54:11
By the time I was in my early 20s, teenager teenager got to back up.
2:54:16
Uh what what were you doing as a teenager?
2:54:18
Uh you just sort of sprinkled that in there, but uh I'm sure it's a good story.
2:54:23
Yeah, I started working at Hooters restaurants as a hostess when I was 17, putting myself through school.
2:54:31
I'm the oldest of three girls.
2:54:34
We left my dad when I was nine. Helped raise my sisters.
2:54:36
And so restaurants are very common place for young folks who need to work to start to work.
2:54:42
And I grew up in Florida.
2:54:42
And so I used to pick uh my my first real job after soccer soccer refereeing was picking up cigarette butts at a nightclub in the morning.
2:54:51
I would get there at like 6:00 a. m.
2:54:53
and that was that was my job.
2:54:55
So, uh very familiar with the the sort of restaurant grind and and it and it certainly it it allows you to bring it's easy to bring the sort of service culture mentality into startups when you're you know responding to like tickets online.
2:55:09
uh if you got your start in restaurants. Yeah.
2:55:14
I mean that that that closeness, right, that proximity to the transaction, to the customer experience, if you're paying attention, it never leaves your bones and your soul.
2:55:22
And so I stayed in that industry for many years.
2:55:26
I was with Hooters for 15 years.
2:55:27
Um helped grow that business around the world and then moved on to a ROR Capital uh really big private equity firm and restaurants and franchising owned portfolio company called at the time called Focus Brands.
2:55:38
uh took over Cinnabon when I was 30 years old as president to turn it around out of the great recession and then built that business into a billion-dollar global revenue business.
2:55:48
Uh then built a licensing CPG division out of that parent company and eventually ran Focus Brands, the parent company, couple billion, eight brands, 80 countries uh for four and a half years.
2:55:59
So 10 years at Focus total.
2:56:01
And all throughout that time, I was just becoming more passionate personally about nutrition and fitness.
2:56:08
I had kids later in life. I'm 47.
2:56:10
I have a five and sevenyear-old.
2:56:12
My mom had breast cancer when I had my second, my daughter.
2:56:15
And so health became this personal obsession.
2:56:18
And so while I was running these big mass market brands, some of them were sweet treats and fun for you, but some were better for you.
2:56:25
Jamba, Mo, Schlatzky's, Mallisters.
2:56:27
I wanted more, like more bleeding edge of health and nutrition.
2:56:31
So, I started angel investing in better for you businesses quietly on the side.
2:56:36
That eventually coincided with when I left Focus after a 10-year career running those global franchise businesses.
2:56:42
I was introduced to the founder of then called Athletic Greens AG1.
2:56:47
I'd been a customer for a few years and you know, here we are. That was four years ago. Um, amazing.
2:56:52
years ago. Um, amazing. what what was your pro personal process diligencing AG1 given that I'm sure you know you looked at hundreds of businesses run these sort of massive organizations what I guess what were the qualities because I think if I remember correctly the time
2:57:07
you joined AG1 was when almost everybody was writing off direct to consumer as a category broadly they just said it didn't work the economics weren't there you were giving all of your you know uh you would eventually have to pivot to retail and then that was completely changed the business capital and you couldn't really get to scale. Yeah,
2:57:24
Yeah, there were a few things.
2:57:26
One, I did similar diligence to uh some of our investors which is we were customers.
2:57:31
I was a customer for two years and when you have a personal experience with a product and real passion for me it was energy immunity, gut health support.
2:57:38
It made a big difference for me as a as a busy professional mom.
2:57:42
So I was a bit of a fan girl of the product itself.
2:57:44
But that's just one layer.
2:57:47
The second was I actually advised the founder for half a year before I joined.
2:57:53
And so talk about diligence.
2:57:56
I had the opportunity to get inside the business, get close, meet the team, understand product, and as every layer I lifted, what I learned was even better than I could have expected.
2:58:05
And I had a bit of an ego moment where I'm like, "Oh, this company is so much smaller, you know, than the other ones that I've run.
2:58:12
Is is this really what's right and best for me, even though I love it?"
2:58:16
And very quickly I got over that too.
2:58:17
This is actually a brilliant time to jump on a health and nutrition rocket ship that's better than anyone knows and has incredible upside.
2:58:24
So after advising I joined in November of 21.
2:58:29
So what were the first challenges when you came in?
2:58:32
It sounds like a lot of things were going right but there's probably some area that you were focused on.
2:58:39
Yeah there I mean there was a ton going right on the outside.
2:58:41
Everyone said oh you guys are crushing it.
2:58:43
We did this fund raise right 120 billion or 120 million raised at a 1. 3 billion post. Wow.
2:58:49
It was still the end of the frothier era like end of 21 beginning of 22 and the business had done 160 million that year in revenue and bootstrapped up to that point.
2:59:00
So the founder was an incredible capital allocator, incredible subscription business, 90% subscription growing at, you know, multiples not percent. So that's what was good. That's what was great. Fresh round of capital.
2:59:13
the only round of capital we've ever raised uh and a lot of tailwind in the category in the industry and a clear leadership position.
2:59:19
What was wrong is that we had scaled so quickly and we only had one manufacturing plant in New Zealand.
2:59:29
So all of that green powder was being blended in New Zealand and most of our business had grown in the US. Yeah.
2:59:38
And so job one was scale the operations to support growth.
2:59:43
I wanted to launch a few additional products sooner.
2:59:45
I wanted to go into retail sooner.
2:59:47
But we had no business doing anything new until we really built the infrastructure and that was expanding manufacturing to the US which we did immediately to support the US business.
3:00:00
So now New Zealand supports the rest of world other source we own our source source highest quality ingredients globally then blend in those countries and certainly that's helped us in the tariff volatility uh moment and so that was job one.
3:00:15
The second was then it was very clear pretty early on that even though there were there was so much energy and tailwind and growth in the supplement category of wellness and a lot of that was getting hyped up and promoted on podcasts and with influencers and creators and we were certainly a part of early very early in that trend.
3:00:38
We were fortunate that some of our early customers became thought leaders and had famous podcasts.
3:00:44
uh but it was very clear that science was going to be a critical part of marketing for this category where it historically had not been.
3:00:49
So a few years in, first shore up operations, second actually pull back marketing a bit and reinvest millions into double and sometimes triple blind randomized placebo control clinical trials which take years to build a PhD team to scope the trials to conduct to analyze etc.
3:01:10
And uh so those were the first two things s operations supply chain in particular which includes like QA maintain our NSF for sport thirdparty certifications there's a lot of like high quality standard we needed to protect as we move manufacturing and expanded it which was a little scary as
3:01:25
we put our product in the hands of other blending facilities but the team did it beautifully and then make massive industryleading investments that would take an annoying amount of time to be completed and pay off and then use those two things as the foundation once we got them in place to then innovate. So we wrapped up last year 600
3:01:43
So we wrapped up last year 600 million in annual revenue, one product, one channel.
3:01:50
Um yes, John's going to hit the crazy. Congratulations.
3:01:56
Yeah, the scale is just wild. Let the waves be. Yes, we deserve it.
3:02:03
Uh our customers deserve it and that's fantastic.
3:02:05
Uh but it is time uh and it it was time a year ago to make some thoughtful large focused moves outside uh of that single product single channel model.
3:02:18
So just this last week we announced a direct to national partnership with Costco.
3:02:23
So we are now a multi- channelannel company went straight from no retailers to an of the of the largest.
3:02:30
I don't I also I also don't think I don't think people realize how significant winning in Costco is because I've I I'm an investor in a company that expects Costco like in the first I think 18 months to do add 50 million revenue to the business.
3:02:46
It's like extremely significant.
3:02:49
It could easily be into the nine figures.
3:02:51
And so, um, it's it's great if you can just go from, you know, one channel to adding retail as like this individual, you know, yeah, channel that you can really Yeah.
3:03:03
If you're running a small CPG company, our recommendation is just just go into Costco. Just win Costco. It's easy.
3:03:07
It's not for anyone out there with like a $2 million CPG.
3:03:11
curious like how much uh I'm curious if you think like most of the issues in in DTOC and consumer brands broadly are just operational because like when I think of structural versus structural when I think of Yeah.
3:03:28
versus structural where it's like hey you have a good product maybe a good brand and you're just or or or a brand that could be good. Yeah.
3:03:34
Um, and and it's just a a lack of of pure leadership abilities internally because like we're very close with the the the Ridge Wallet team and that's a business that like shouldn't be a multiund million dollar revenue business, right?
3:03:47
It was the the original product was a um you know in the early days the LTV was like the LTV was like the first the value of the first order the first purchase, right?
3:03:59
And so you would have think there's no way this business could could really scale or be massive and and they have against the odds.
3:04:05
Um, but I'm curious as you look at other DTOC businesses, how often are you thinking this could be great, but it's just not like it's actually just like a operational uh um uh lack effectively.
3:04:19
You know, what's interesting indeed to see is I I've seen both ends of the spectrum where something is actually demonstrating outsized growth, but there's not a lot of there there underneath and it's a window of time before they hit their CAC wall. Yep.
3:04:33
and they end up having a lot of unit economic challenges.
3:04:36
And it doesn't mean retail will solve those challenges in particular.
3:04:40
And then you see others that have beautiful products, incredible retention, um but just haven't mastered the art of e-commerce marketing.
3:04:49
And so for for us at least early on, I I think people gave us way too much credit for being amazing DTOC marketers. We were not.
3:04:58
We had a phenomenal product that it didn't matter what type of marketing we use to have people learn about it. Right?
3:05:06
Any marketing is just awareness and trial.
3:05:10
What keeps people ordering months and years.
3:05:13
I've got over 500 customers that have been with us for a decade. Wow. A decade.
3:05:18
They've been drinking AG1.
3:05:18
That is not because a podcaster told them something.
3:05:22
It's not because of a billboard or sponsoring a sports team. It's their experience.
3:05:26
And so I don't think we can remove consistent quality and that compounding resulting both growth from those customers individually but we call it the referral quotient.
3:05:38
Our number one driver of customer acquisition or post-purchase survey.
3:05:42
How did you hear about us?
3:05:42
How did you first hear about us? Friends and family. Number one by a mile. Bigger than podcast.
3:05:47
Bigger than bigger than influencers. Bigger than television. We're fullfunnel.
3:05:51
We're pretty well distributed from a marketing strategy.
3:05:53
I was just listening you guys talk to Dana.
3:05:56
She's amazing and their portfolio is phenomenal and you know whether it's television or community and activations it's all a part of our approach but DTOC really has to have that incredible experience to have its chance.
3:06:09
I mean we were rewarded for our focus, right?
3:06:14
Pretty unusual to get to 600 million with a single product. Yeah.
3:06:16
And we weren't even on Amazon. This is just drinkagg. com. And that's unusual.
3:06:22
Um, and and I do think that might be part of a a challenge for some DTOC businesses is if they don't get traction or they're not seeing that retention or the LTV they want, then they go wide like SKUs and offerings and you get distracted.
3:06:36
But if you can focus and really differentiate then that that traction is there and the unit economics perform to the best that they can as the algorithms change and as the structure of to your point of structure of digital marketing changes.
3:06:52
On the other side, retail, yes, it's a revenue channel, but it's brutal and your product is in the hands of someone else.
3:06:58
And uh but it is marketing, right?
3:07:02
It is eyeball the shelf is a billboard.
3:07:05
And so if you can do it well, I believe it is synergistic with DTOC, not the um maybe predicted or feared cannibalization that some might think going into retail.
3:07:16
I'm glad we didn't go in early. This is our time.
3:07:18
This is the right time for us.
3:07:19
Uh but we have an unusual business and that people stick with uh with AG1 for so long. Yeah.
3:07:25
Do do you have a reaction to the news uh this week or last week that Nike is going back on Amazon?
3:07:33
Sort of a pivot away from their direct to consumer strategy.
3:07:38
I think Nike got a little too inspired by you guys.
3:07:39
I think they try to copy you guys.
3:07:42
They saw you putting up like H1 was the last hold out.
3:07:46
They're the last hold out.
3:07:46
If they're there, all bets are off. Yeah, exactly. Welcome back, Nike.
3:07:50
Yeah, but but no, they they they seriously said, "We're we're pull, you know, we're not going to do Amazon.
3:07:56
We're going to focus on our own Nike.
3:08:00
com and direct response marketing."
3:08:02
And that's the other thing you guys have blended.
3:08:04
You guys do, I'm sure, the vast majority of your budgets around direct response, but when you came on board, suddenly the AG1 brand was aspirational.
3:08:13
It was like, you know, cool. And it was leveled up.
3:08:15
It felt like that's been a critical part of the Nike brand is putting the celebrities front and making the athletes the heroes and that kind of fell by the wayside during the direct response era.
3:08:25
Hopefully, they're getting back to it.
3:08:27
People were talking about Caitlyn Clark has is signed with Nike, but most people don't even know it because the particular shoe that she wears is like a limited release and so they've gone this like very odd strategy.
3:08:36
So, just general lessons from Nike or reactions to the relationship with Amazon there.
3:08:41
I mean, look, it's I it's similar to us and um may we be a Nike one day.
3:08:46
What a phenomenal brand, but they've had their bumps as all scaled companies do.
3:08:50
And um we several years ago, as part of that pullback in that lowerfunnel marketing and investment in human clinical trials to raise the standard in research, we also moved the marketing spend we protected to more upperfunnel, right?
3:09:02
Building brand brought an incredible CMO recently, former CMO of Yeti.
3:09:07
is a a creative genius and really deeply believes in community.
3:09:12
He always says niche to be mass like go to your people be deep be there for them and we're we have a lot more ground game happening now and so that investment in fullfunnel marketing you get a greater return if you're in more places including the world's largest e-commerce retailer being Amazon.
3:09:32
So for us, and I know this was a part of u Nike and even some other brands calculus in either going off or never being on.
3:09:39
For us, there was so much tailwind in organic search and growth.
3:09:43
We didn't need to be there to grow the way we grew and we could barely keep up with the growth that we had.
3:09:47
It got to a point where three things changed for us, and I I can't speak for Nike, but I'm assuming this is a piece of the pie.
3:09:55
of the pie. one um there was a growth of counterfeits and resellers and to protect our brand at scale and you know this isn't a shoe it's something people put in their bodies that's a safety issue that's a brand issue so when part
3:10:10
of our thinking of getting back on was seeing the programs that Amazon in particular transparency and others that they put in place to take down either of those fraudulent products people infringing on IP or you know, unauthorized resellers. That was
3:10:26
That was critical for us.
3:10:28
We would not have come back on in the way that we did as in as big of a way if those programs were not in place for this category in particular. It's about quality.
3:10:37
We added we had to add holograms to our box with with randomized unique numbers on all of our packaging.
3:10:45
We did this pre-Amazon because the you know, it wasn't just Amazon.
3:10:49
Amazon. all the marketplaces there were count I'm talking real counterfeits like weird typos and Grinch green powder dark green powder getting caught by customs and imagine getting a phone call from your general counsel and she's like we just got a call from the feds or customs something that says NS for sport so there's brand you're being a very you know like a a politician about this but when I talk to portfolio companies in
3:11:17
the supplement space about Amazon on it is just their number one uh one of their biggest pain points and and and just a massive source of of frustration around counterfeiting around you know all the sort of issues that you're when we got
3:11:32
back on it was gone gone and um now we're a meaningfully scaled business right so um they've they really this is not being diplomatic I had a ton of risk to my brand and it is now gone on that platform that's Those are the facts. Um,
3:11:47
Um, the other issue was that because the resellers were there, even if it was real product being resold, I couldn't tell you how old it was, the shelf life, the stability.
3:11:57
So, I still had a quality concern, but the as big of an issue for e-commerce marketing was it was driving my ratings into the ground.
3:12:04
So, our brand ratings on Amazon were awful.
3:12:08
And so, if you would search AG1 on Google, you'd get these great ratings from our site or other sources.
3:12:14
And then Amazon, who stars? Three star. I mean, it's horrific.
3:12:19
And so, as soon as we got back on, resellers are gone, counterfeits are gone.
3:12:23
We have a limited product assortment there.
3:12:26
So, we can be there meaningfully, but keep DTOC is the place for expansive SKUs.
3:12:29
Ratings went through the roof because customers are having a better experience.
3:12:33
So, it's search, it's about search and discovery as well for us.
3:12:37
Um, where is your team getting the most leverage from AI?
3:12:40
There was news this week from Meta talking about wanting to be, you know, basically help advertisers actually generate ads.
3:12:47
Um, Dylan Patel was talking about and and in general, you know, when you talk to brands like the number one thing holding back their growth oftent times and efficiency is creative. Yep. So, it's very exciting.
3:13:01
We're finally there with VO3 where it's not it's at least a drop in replacement for some B-roll or stock footage that you might pull off the shelf.
3:13:08
Uh, so yeah, that's a fascinating question.
3:13:10
It's God the technology is unbelievable. It's it's unreal.
3:13:13
Um for us the first place AI showed up in the business is our customer service and customer happiness.
3:13:20
We partnered with uh with Sierra.
3:13:22
We were very early with them and um I have no affiliation with them otherwise being a happy customer.
3:13:28
and uh they partnered with us to craft what we needed and what we got out of efficiencies we redeployed into human resources for concierge programs for loyalty programs which we were actually very late to develop as a subscription
3:13:42
business so I used there there was a there was a financial benefit there was a speed benefit for like we learned that 50% of our customer inquiries were things we already knew this we just didn't have the solve that Sierra helped us with um 50% were just manag my
3:13:58
account you know like that that stuff can be that's prime for AI so for us AI was first there then we have tools that our team our supply chain team have brought in on um transparency and tracing for ingredient sourcing since we own our sourcing and so it's really
3:14:14
helped us track and monitor and enable all because we have pretty rare high standard specifications of our ingredients and have unusual levels of testing of ingredients and so to manage that through the supply chain has been very manual and so AI has helped us there. Then to your point, marketing,
3:14:30
Then to your point, marketing, um, we have some interesting thoughts on AI.
3:14:36
We are using it for, as you said, digital background, digital B-roll, anything that isn't supposed to be real product and real human because the supplement space has both good actors and not.
3:14:48
We are holding ourselves to a standard of if we're putting a person on camera or if we're showing our product, right or wrong, it's going to be real.
3:15:00
and but everything around it, the enablement, the editing, we are bringing every AI tool we can to make that more creative um and more efficient.
3:15:06
Yeah, we were talking to a food photographer earlier today who was uh very nervous about artificial intelligence uh and AI image generation, but was hoping that some of the rules around the way food is is photographed from the FCC market. Yeah.
3:15:23
And marketed because you've seen those famous pictures of like here's the burger.
3:15:27
when you say the name of the company that does it, but you know, here's the here's the photo and here's the actual burger and they don't look anything alike.
3:15:34
And you can imagine that being a big a big issue even if AI can be used in the in the post process, there's probably still value to uh showing the customer exactly what they're what they're actually getting.
3:15:45
Last question from my side for now.
3:15:47
Do you think that uh do you think that people should be significantly more concerned with the supplements that they choose to put in their bodies?
3:15:55
I I there's this uh obviously in the Silicon Valley, the tech world, people will take any supplement if it's like, hey, this is going to make you 1% more focused today.
3:16:06
They're like, I will buy this from some sketchy website and and take it today and and you know, you keep coming back to this sort of like traceability testing, you know.
3:16:14
Um we seem an issue, too, but there's no creatine in it.
3:16:21
But I mean, if you test supplements, it's like, yeah, you could be supplementing lead and not knowing it, you know, and so, uh, I think that not every supplement company has the same standards, and I don't think people fully appreciate the potential consequences of that today. Yeah.
3:16:34
I, you know, the the very fast answer is yes.
3:16:41
People should be incredibly discerning.
3:16:43
While there are truly so many companies doing the good work, third party certifications, publishing certificates of analysis like us on their site, um all kinds of third party labs, it there still are so many who whether intentionally or not on in the in the mildest form of of the issue, what is on the label is not what's in the product, right?
3:17:07
So if you think you're supplementing with X amount of this ingredient and whether it degrades because of the shelf life and they are blissfully unaware or their manufacturer pulled one over on them and they are unaware.
3:17:17
I would say irresponsible in those cases if you're going to sell a product.
3:17:21
Um that that could be happening and in that case it's just an it you're not getting what you pay for.
3:17:25
On the other side to your point there could be ingredients that you don't want or don't know are in there.
3:17:32
And so what I would encourage people to do whether they're in Silicon Valley or anywhere is recognize this is a huge industry and where there is growth there will be both good and bad actors.
3:17:42
And the great news is there are ways to know who and what to trust.
3:17:47
You got to look for third party certifications.
3:17:48
And don't just take the words that someone types third party certified. What third party? Yeah.
3:17:56
NSF for sport is the gold standard.
3:17:58
They're incredibly expensive and a a pain in our asses because if I change one thing in this formula, it has to go back through their process through shelf life testing to prove what's on the label is what is in that bag. Yeah.
3:18:08
You actually have to go you have to really verify, too.
3:18:12
I I helped start a company in the water filtration space.
3:18:14
And we went through the full NSF certification process.
3:18:19
It costs hundreds of thousands of dollars.
3:18:21
And then we have competitors that will put the NSF badge all over their website and they're like actively getting sued by the NSF or in legal battles, but they just keep it up because it increases conversion rate, but if you go below the surface, it's like there's just nothing. That's right.
3:18:36
I think the other piece to for for people to think about too is this is unfortunate another layer of confusion is you also then have people doing what you just described starting their own labs and then they are testing product with some unknown methodology and then creating viral content around whatever they find and that just makes it harder for the customer to know.
3:18:57
So I would just say that this is not and anything you put in your body should not just be a listen to someone and click and buy and put it in your body.
3:19:05
Go to the website, look at the ingredient section, look at the research section.
3:19:08
Do those uh supplement companies have any research on human beings? Yeah. At all?
3:19:16
And I mean you can imagine, you know, because you've got investments in the industry, having four double blind randomized placeboc control clinical trials u with over a 100 people proving the same outcomes of supporting gut health, 10x gut bacteria, beneficial gut bacteria, covering nutrient gaps in four different populations. That's not cheap.
3:19:36
And um but we have to, right? We're the leader. We don't make claims. We can't substantiate.
3:19:41
I could have done two studies and that's enough to say clinically backed. We did four, right?
3:19:48
We're just we we have to lead because there is so much to be questioned with those in the middle.
3:19:53
And I will offer if anyone is starting a supplement business and if they genuinely want to know how to do this right, I will help them. My team will help them.
3:20:02
It is bad for the industry for people who don't take this stuff seriously. That's amazing.
3:20:05
Well, thank you so much for hopping on this. Fantastic.
3:20:09
Congratulations on the massive revenue numbers, all the progress.
3:20:15
Classic overnight success. We love to see it. Yep.
3:20:16
Come back on next time you have news. This is super fun.
3:20:18
We'd love to talk to you soon. Thank you guys. You're welcome. Great to see you. See you.
3:20:22
We are shifting gears over to the Supersonic world.
3:20:24
We have Blake Schaw from Boom. Supersonic.
3:20:29
Is the speed limit lifted? Are we post speed limit?
3:20:32
I want to go 2,000 mph tomorrow. Smiling. He's smiling.
3:20:39
Something must be good happening. What? What happened today?
3:20:41
We've been live for the last few hours.
3:20:43
So, we got a text message. We got to have you on. Yeah. Nothing nothing big.
3:20:47
We just actually we actually broke the sound barrier today permanently because the band is reversed. No way. That's what Let's go.
3:20:55
John's going to hit the John's going to hit the gong. That's for you, Blake. Congratulations.
3:21:03
We've been hoping for this for a long time.
3:21:05
So So the rules are going to change and you can go supersonic as fast as you want so long as the sound is a gong. Yep. Oh, that's great.
3:21:14
I would happily let gongs ring upon the the fields of America from sea to signing shining sea. I'd love to see it.
3:21:23
Uh I mean I know this news is breaking but uh how did you find out about this?
3:21:28
Was there expectation that this was going to happen?
3:21:30
Who are the folks who have been working on this?
3:21:32
Uh and then break down what actually happened. Yeah.
3:21:36
Well, I mean in a certain sense people have been working on this for decades, you know, since 1973 when it first went in place.
3:21:40
And we've been working on it very intensely since February 10th.
3:21:45
Uh which is when we announced we could do we could fly supersonic without an audible boom.
3:21:50
Y I think it was uh that uh that night I left LA where our test flights were and went to DC.
3:21:58
And by the way it's horrible flight. Much better supersonic.
3:22:01
It was like like left at 11 p. m. Got it at like 4:30 a. m. It's awful.
3:22:05
It should totally be supersonic.
3:22:08
And then by the time I landed I had an invitation to the West Wing.
3:22:11
So um the uh so we you know since then uh what we did what to me felt like a very long frustratingly slow campaign but what everybody tells me in DC is actually supersonic.
3:22:24
Uh so a a bipartisan bill dropped three weeks ago in the House and the Senate um called the Supersonic Aviation Modernization Act which by the way I think we should still pass because that locks in all of today's goodness. Mhm.
3:22:39
Um and uh you know and we just sort of continue to educate people on by the way we don't have to have the boom anymore.
3:22:44
And by the way, not all booms are created equal. Not all are bad.
3:22:48
And uh that's something a lot of people can get excited about.
3:22:51
So I I mean I know a lot of the technology is about uh flying at very specific speeds at specific al altitudes doing all the math to make sure that the boom bounces back into the atmosphere or something like that.
3:23:03
Uh what kind of speeds does that actually work at?
3:23:07
What what are we what what are we expecting because Supersonic goes well past it goes basically infinite, right? Right. Yeah. Exactly.
3:23:14
So So there there's sort of two ways you can kind of attackle sonic boom.
3:23:18
And like one one is what you're just describing.
3:23:20
Make it go away entirely by making it make a U-turn and go up to space.
3:23:24
And the the great thing about that is that there's nothing to argue about whether it's too loud.
3:23:28
Um the the less the less great thing is it only works up to about Mach 1. 3. Okay.
3:23:35
You can go about 50% faster, but you can't go 100% faster or 200% faster.
3:23:38
Uh, put that in terms of like a commercial airliner.
3:23:42
I feel like I fly at like 500 600 miles an hour.
3:23:45
You're talking about like 700 800 maybe. Yeah.
3:23:46
Let's talk about in terms of flight times.
3:23:48
This is so with with a 50% speed up, which is what's achievable routinely.
3:23:52
Uh, you can leave New York at 9:00 a. m.
3:23:55
and be in San Francisco at 9:30 a. m.
3:23:57
So, it's a three and a half hour flight. Okay. Wow.
3:24:01
Which is like that's a W, right? Yeah. That's massive.
3:24:04
Now, you know, if you want to go higher than that, faster than that, uh you have to convince yourself that some some way or other the boom is not a problem. Yeah. Okay.
3:24:11
And uh and I don't think people don't agree about the answer to that.
3:24:14
Uh you know, I I want to get out there, fly the airplane.
3:24:17
I want to hear some real booms.
3:24:18
I've heard a bunch of booms in Mojave, by the way.
3:24:20
We were doing our test flights.
3:24:22
Booms are common place down in the Mojave Desert.
3:24:26
Military makes them all the time.
3:24:26
And there's some that kind of get your attention.
3:24:29
You're like, "Wow, we probably shouldn't do that.
3:24:31
At least not at least not at night time.
3:24:32
That would be at most that's a daytime thing, you know, but there are others that like sound like somebody like dropped a book on the floor and you know and those are, you know, so think of it as like the wake of a boat.
3:24:43
The bigger the boat, the bigger the wake.
3:24:45
The closer the boat, the more the wake you feel. Yeah.
3:24:47
And so if you have a right-sized boat at a sufficiently far away distance, it really ought to be considered a non-issue.
3:24:54
So, uh, so, you know, I think we're still kind of taking in exactly what's the language and the EO.
3:24:58
Um, you know, but my my expectation is that this will be a one-two punch where uh you know, if there's no boom, there's nothing to argue about.
3:25:06
And if there is a boom, there should be a way to sort of demonstrate uh that that it wasn't it was an acceptable one. Yeah. Yes.
3:25:12
Uh specific flight corridors where people are opting in or something like that.
3:25:19
And yeah, I mean that's it's just a quarter the the you'll hear a not if you're in kind of boomful mode that the boom corridor is actually like 50 or 100 miles wide. Oh, very wide.
3:25:29
So I mean you know we can't build a railroad in this country. Yeah. Yeah. Yeah.
3:25:32
Like you know which so the positive thing is like I imagine if when you're traveling over oceans we can you know have a little bit more flexibility. Yeah.
3:25:42
There there has never been a restriction over ocean.
3:25:44
So so that's the fortunately there's nothing to do there.
3:25:47
So, so the way our first airplane overture will do this is it'll fly boomless over land at like plus 50%.
3:25:52
And then and and then when we get to the coastline, you know, you gun the throttles and and then you go to full 2x speed. Yeah. Yeah. Yeah. Yeah.
3:26:01
And I'm sure that the economics change when you can do 1. 3 Mach over land.
3:26:03
Uh because that's just a there's so much more overland air travel generally.
3:26:09
So it's just a bigger market.
3:26:12
So it justifies everything in the investment. It does. Yeah.
3:26:14
And the economics are actually really interesting, you know.
3:26:17
So if you fly sort of lightly supersonic, it's worse for fuel burn, but you can do so many more flights with the same airplane, you save a bunch of money on other things.
3:26:23
And so go so on on overtry going right under the speed of sound and going boomless supersonic is actually the same uh dollars per seat mile. H interesting, right?
3:26:33
Like the fuel slice gets a little bit bigger and the cost side, the cost side like anything, but the revenue is going to be I'd pay 10 times as much to get from Oh yeah. Revenue obviously. I mean, time is money. Save both. Ramp. com. Also, boom. Boom. Supersonic. You can go to both. Time is money. They're both.
3:26:52
Everyone's gonna save you time.
3:26:53
Um, but if the boom comes down, reflects, bounces back up, and I'm in a plane there.
3:26:59
Is that going to break my plane's windows? What What's the risk? So, okay.
3:27:03
So, so a few people asked that question. It's a good question.
3:27:06
The answer is Concord did that for 27 years, and nobody noticed. Oh, interesting.
3:27:11
And and and one time they tried to test it.
3:27:12
We know the pilots that were doing this.
3:27:14
They sort of arranged for like a 747 to be here while Concord's kind of passing overhead and they they had told everybody on the 747 that they might get to hear something and then they didn't hear anything and everybody was super disappointed. Okay.
3:27:28
So, it just doesn't really affect maybe you feel something that feels like turbulence. I don't know.
3:27:31
It's like a It's like a It's a nothing burger, but it's not going to blow the windows out, which is like the worry, of course. No.
3:27:37
I mean, if if that was going to happen, you know, Concord have knocked out every other airplane in the sky. Yeah, of course. Airplanes fly above. Yeah. Airplanes fly below.
3:27:45
So So Conqueror is booming for 27 years over the Atlantic and like nobody got hurt. Yeah. Wild.
3:27:49
Um the way to look at this, by the way, is like the uh like the energy intensity and some of the physics of Sonic Boom are very similar to thunder, right?
3:28:00
So you could be like, "Oh my gosh, like you know, could could boom over the water like disturb the mating habs of like, I don't know, the aquatic spotted owl or something." Sure.
3:28:10
Uh, well, anything that was going to be put out of commission by a sonic boom was long ago put out a commission by a thunderstorm. Sure. Yeah. Sure.
3:28:17
Um, we So, was there anything was there anything to you that was surprising about the EO?
3:28:21
Uh, what what what what what did you maybe not anticipate?
3:28:29
I mean, I had I I admit I haven't read it word for word yet. Yeah.
3:28:32
Uh, I read I read the back partied and I need to like calm down and read it word for word.
3:28:38
Uh there's there's a lot of stuff in it um uh that that appears to sort of like not just say great you should be able to fly supersonic but you know advances R&D and you know there's I don't know I got to read all of it.
3:28:49
I want to say what it says read it. Yeah. Yeah. Yeah.
3:28:51
I'm sure there's a ton of work to be done on like the licensing and approval and and everything that happens with certification.
3:28:56
Some of those things might need to change or speed up.
3:28:59
Some of them might need to stay in place if it's a safety issue of course.
3:29:02
Uh but what's next for the company?
3:29:04
What's the next milestone that you're tracking? uh is let's go.
3:29:08
So we're building our first engine. Okay.
3:29:11
Power the you know and that thing is like 60% uh the parts are in the manufacturing process.
3:29:15
Uh and uh we'll go uh run that bad boy later this year.
3:29:21
You know that the skeptics always say the startup can't build a jet engine from scratch. So we'll find out. Yeah.
3:29:26
And uh then we'll start building the first uh fullscale pre-production prototype overure next year. Very cool.
3:29:32
Uh it'll be roughly three years. Okay.
3:29:35
today to to be back and like there's a bird in the air.
3:29:37
But you know last time that what we flew it looked like a fighter jet. Yeah.
3:29:39
Next time it's that it's the overture which it looks like a it kind of looks like a Concord and a 747 had a baby. Yep. Amazing.
3:29:46
It's got this like little hump up at front.
3:29:49
You know it's you know it's not a double-decker but uh but it's a really unique airplane. Not yet.
3:29:54
We have to get the goldplated 747.
3:29:56
Those are really hot right now.
3:29:58
Lots of people giving them to their friends and so I could imagine uh handing these out to world leaders being pretty effective.
3:30:05
I have I have to ask did you have any did did you get a chance to watch the rehearsal by Nathan Fielder?
3:30:11
Uh you're giving me a blank stare so I assume you're too locked in.
3:30:16
I I I don't I I is this sounds like a pop culture thing of which I'm ignorant. Yeah. Yeah.
3:30:20
Well well the reason it's relevant is because this this sort of comedian Nathan Fielder um uh go you know has this show called The Rehearsal.
3:30:28
He learns how to actually fly a commercial aircraft to demonstrate to the FAA some of the issues they have around safety.
3:30:35
uh specifically on pilot communication.
3:30:38
He he identifies that the vast majority of of of commercial air crashes that have happened over the last few decades have been the result of a a captain making a mistake and the second in command not having the kind of energy or or confidence to stand up to them because they're meeting for the first time.
3:30:58
And so he dissects this in a bunch of hilarious ways.
3:31:02
My main takeaway uh from your answers that is extremely bullish for boom that you have no idea uh there's a certain class of hard techch founder like I I always notice Scott Nolan uh he'll post like he'll repost like their
3:31:15
announcement like four days later because he's like so in the trenches that like I'm like Scott like like you you know you launched three days ago like you should be rep retweeting at least like the post because he's so offline. Um but anyway speak I have one
3:31:26
Um but anyway speak I have one last question about being online.
3:31:28
uh you've been learning from Elon about manufacturing online.
3:31:33
You had an interesting back and forth where you were talking about uh manufacturing parts. I barely followed it.
3:31:39
Can you explain what did you learn from Elon about manufacturing uh and and Yeah. Yeah.
3:31:46
break that interaction down.
3:31:48
So So Elon has this thing he talks about called the idiot index, which is it's a beautiful Elonism, right? Yeah.
3:31:54
Elonism, right? Yeah. uh where it's it's sort of a like you've got a final part and you divide it by the the part cost like say it's a turbine blade it costs uh I don't know a mill a real world example we've got the set of turbine blades costs a million dollars for a set of turbine blades what is the raw
3:32:09
material cost $1,000 what's the index a thousandx like the cost goes up a thousandfold in the manufacturing process and so it's a sort of measure of like what's the what's the money efficiency of the manufacturing process there's another thing that I think is actually even more important that we we call we call the slacker index. Yeah. Yeah.
3:32:29
And the slacker index is how long it takes to get something out of the supply chain divided by how long it actually takes to make it.
3:32:37
Oh, so we're time based, right?
3:32:38
Like so we were getting these t these 3D printed turbine blades for our first jet engine and we go quote them in the stupid old aerospace supply chain and the quote comes back and it's like it's six months and a million dollars. Yep. And I was like, "Wow." Okay. Okay.
3:32:51
Well, how long does it actually take to print the blades? Oh, like 24 hours.
3:32:54
Like, so what's going on the other 179 days? You're like waiting for?
3:32:58
And I was like, oh, it must be that the machine is like really hard to get and they're like only a few. Well, no.
3:33:03
Turns out the machines are off the shelf.
3:33:05
They've got them in inventory.
3:33:07
You can get one in two weeks.
3:33:08
And by the way, do they cost? $2 million.
3:33:11
So, for the price of two engines worth of blades, we were able to buy a 3D printer and print our own blades. Yeah.
3:33:17
And and so what happened, by the way, it compounds from there is if you if engineers can only make a a new blade every six months, they like really work the blade design because they don't want to get it wrong because if they get it wrong, it takes six months to fix it.
3:33:29
But if they print in the one next day, then all of a sudden the rate of iteration goes up and they're an engineering hand ringing and trying to get it right the first time goes away. Yep.
3:33:38
So you want low idiot index and you want low slacker index. I love it. I love it.
3:33:42
Well, hopefully this EO unlocks a lot of that and we can bring down the idiot index, bring down the the uh the slacker index and supersonic flight man definitely had a high idiot index.
3:33:53
So, I'm I'm glad I'm glad that's been uh deep. Well, fantastic.
3:33:57
We are one step closer to a supersonic podcast. I love it. And I cannot wait.
3:34:01
Yeah, I haven't forgotten what you're on. I know. I know. It's happening. It's happening. Well, congratulations. Uh enjoy the weekend.
3:34:10
Hopefully you can advance the technology but also celebrate a little bit.
3:34:13
Uh and we will talk to you soon, Blake.
3:34:15
Thanks so much for hopping on for jumping on. Congratulations. Bye. Bye.
3:34:21
Give a little air horn for supersonic flight. Yeah, I love it.
3:34:22
Uh I can't wait to hop on a boom supersonic.
3:34:25
Take it to an exotic local. Stay at a wander. Find your happy place. Find your happy place.
3:34:33
Book a wander with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, and 24/7 concier service.
3:34:39
It's a vacation home but better folks.
3:34:41
Um, any other posts we need to go through?
3:34:43
We talked about Poly Market partnering with X. That is fantastic news.
3:34:48
Shane Copeland has the news.
3:34:48
He says, "Proud to announce Poly Market's partnership with X and XAI as their official prediction market partner."
3:34:53
I'm very interested to see how this actually integrates.
3:34:57
Obviously, Poly Market's gotten very good at sharing images with with a very catchy image and then the market, not just the like the the Poly Market screenshots have been kind of a staple of X for since the election.
3:35:08
Um, but they've but they've gotten better at that.
3:35:12
I'm wondering if we're going to see the the data actually hydrate live like community notes.
3:35:16
So, you can attach a poly market to a post and it will stay updated. That would be very cool.
3:35:20
Uh, so you could be tracking it on the post.
3:35:24
Uh, it'll all be very interesting uh to see where that goes.
3:35:26
Um, what else should we talk about today before we leave?
3:35:32
I think we covered a lot of it.
3:35:34
Uh, Scott Bellki is coming on the show next week. Very excited for that.
3:35:35
He has a post that uh I was just enjoying because it's about product leadership.
3:35:40
He said, "Underrated characteristic of top product leaders compulsiveness, obsessively capturing decisions, ideas that need to be taken baked that would otherwise be fleeting."
3:35:50
This is how I felt about reading this post.
3:35:54
Incessantly iterating over options in mind, morning till sleep.
3:35:57
This is what the the golden retriever does.
3:35:59
The golden retriever incessantly iterates over options. Should I get the ball? Should I get the snack?
3:36:06
Should I should I roll over? Try and get a belly rub. Golden retriever. High energy. Trying to be efficient.
3:36:13
Not always getting it right, but doing their best.
3:36:14
Worldclass products are crafted via compulsion.
3:36:18
There's no better example than the golden retriever.
3:36:20
Golden Retriever never says, "Nah, I don't want to get the ball today." Yeah. No, never.
3:36:24
So, go out, get that ball, enjoy, be a Golden Retriever this weekend. Fantastic week.
3:36:29
Timeline in turmoil, lots of chaos in tech, but we're still here. Incredible IPO.
3:36:34
We had an incredible IPO. IPO windows open. Yep. Uh, we had some drama.
3:36:39
Some drama on the timeline, but who knows? It's a new week.
3:36:44
We might see completely new things.
3:36:46
and the and the relentless march of techno capitalism and artificial intelligence.
3:36:51
Well, it marches on and uh as always, we're newsmaxing.
3:36:55
Ben is standing behind the camera right now giving us a threatening look.
3:37:00
He says, "Go leave us a fivestar review, Spotify, Apple Podcast.
3:37:05
It does help the show a lot." Thank you.
3:37:07
And we hope you all have a fantastic weekend. We'll see you Monday. See you Monday. Goodbye.
3:37:12
Market clearing order inbound.