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[Music] [Music] [Music] [Music] Hey, [Music] hey, hey. [Music] [Music] Heat. Hey, Heat. [Music] All right.
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[Music] [Music] [Music] [Music] [Music] We came to this world to reach the stars.
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We came to this world [Music] to reach the stars to shape a future.
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[Music] We came to feel the new If you need [Music] Morning [Music] everyone. Good morning. >> Good morning Emola. Good morning John. Good morning >> 2. 6 million. What's good morning?
4:50
Good morning >> Bobby Johnson in the LinkedIn chat.
4:58
>> You're watching Christmas TV. >> We are cozy maxing.
5:00
It's rainy in Hollywood today and we decided to put on the fireplace, make the light a little bit warmer, kind of enjoy the warmth.
5:10
And you know, I genuinely get depressed when it rains.
5:15
Like, it actually affects my mood.
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>> But putting on some warm lighting, a nice hearth >> uh really has changed my mood.
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And I'm having a great time. >> Fireplace.
5:24
>> I'm having a great time today already.
5:26
Uh, and so if it's a little bit cold wherever you are, I highly recommend uh throwing on the fireplace.
5:30
If you can get real real logs, that's great.
5:35
>> If not, >> you can get a projector.
5:36
>> 90inch projector works too, I guess.
5:36
Uh, but it is Tuesday, October 14th, 2025.
5:42
We are live from the TVP Ultra Domel, the Temple of Technology, the Fortress of Finance, the Capital Capital.
5:47
>> So today we got to talk about Zoomer. Zoomer Gate. Zoomer is a loved on.
5:50
We've highlighted his post many times.
5:54
He is uh a deranged trader uh who has a lot of fun.
6:00
>> He was heavily promoting the use of leverage right up until >> Liberation Day 2 Friday. >> Then he got wiped. Did he get wiped? >> I don't know. I don't know.
6:09
He he he's he's been big into Chinese equities over a while.
6:13
So >> he's been having fun on the timeline posting a lot.
6:15
He says, "Say hello to 50x leverage."
6:17
More like say hello to God.
6:20
Nobody is an atheist with 50x leverage. >> I love that.
6:22
No matter how much push back he gets, how much doubles down. >> Doubles down. >> Yeah. >> Doubles down.
6:29
>> Well, Zoomer, if you're going to be risky at all, you got to save time. You got to save money. You got to go to ramp. com.
6:34
Easy to use corporate cards, bell payments, accounting, and a whole lot more all in one place.
6:36
Um, Zoomer's had a number of posts do very well recently, like mega mega viral, totally breaking containment, defining what's going on on the internet that day.
6:46
Uh, and Zoomer says, "My tweet about Steve Jobs almost uh about Eve Jobs almost outperformed the actual Eve Jobs tweet." Eve Jobs tweet. LOL.
6:56
And so he's been going viral for posting Steve Jobs daughter, a picture of her, and then posting meta commentary about how much he got paid to make that post.
7:04
Uh, it was a very odd back and forth.
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Uh, and it's uh, it's frustrated a lot of people, but uh, I have a hot take.
7:11
We're going to break it down. We'll discuss it.
7:14
Uh, and so, uh, Zoomer, it all comes down to like what is the value of your account?
7:19
Zoomer went to some website and said his my Twitter account is estimated, uh, to be worth $3 million.
7:25
And, uh, that's not what accounts trade for.
7:28
Um, that's not how that works.
7:28
But, uh, I mean, certainly in my experience, >> Twitter accounts are basically worthless except for the person that creates it. >> Yes.
7:37
>> And then, and then and then it's and then uh, it has some intangible value.
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it can it can uh increase the value of whatever you're working on, whatever you're the work it is that you do.
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But >> um >> and that's sort of true across the board across all social media accounts, especially if it's tied to an individual person or personality.
7:55
But even the large uh YouTube accounts that have more of a corporate brand like I'm thinking of like Donut Media for example, like that was eventually bought by private equity and some of the talent rolled off and they changed they changed hands.
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Like it's still like hard to just build a single account on a social media platform into like the millions of dollars.
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Like it's certainly not easy. But we do love Zoomer.
8:18
Uh and we're wishing him the best during this tumultuous time because everyone's uh going back and forth. >> Yeah.
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I think I think people take uh are overly serious when he is when when I view him as an entertainer. >> Exactly.
8:34
>> A uh somebody at a dive bar that's getting a little wild. >> Yep.
8:37
But uh it adds it adds to the experience.
8:41
>> Yeah, I completely agree.
8:41
Uh I've always thought of Twitter as the internet's dive bar.
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Uh you know, the drinks have always been cheap.
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The faucet in the bathroom's always broken.
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Maybe that's the fail whale.
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The whole the whole bar is unreliable.
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It might be it might be open late one night and closed >> when you expect it to be.
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It's changed ownership multiple times.
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Uh it's just a it's just a very uh you know it's not as polished as you know a Michelin star restaurant or a luxury resort that you might see on other parts of the internet.
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It's a little bit messy but that's why people love it and that's why people keep coming back at the end of the day.
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You grab your little table in the corner.
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Maybe that's basketball Twitter teapot or whatever car Twitter you know whatever your little group is.
9:25
You huddle up and you know maybe you get in a fight with some other table for a little bit.
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bar fights are going to break out, but at the end of the day, you keep you keep coming back.
9:32
And so, I've kept coming back through multiple eras of Twitter is done or X is over.
9:40
You know, there was the whole narrative like Elon won't be able to keep the servers online.
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He couldn't possibly run a website >> with only a thousand >> thousand people.
9:48
And it's like this guy sends rockets to space and builds electric cars.
9:51
Like, I'm pretty sure he can like get the database working. Okay. So, I never bought that.
9:55
But there was a there were a number of like the ad the advertisers are pulling out or the algorithm is bad.
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And the algorithm has been bad at various times.
10:02
There's been plenty of moments where I've been like, man, I'm seeing a lot of just like generic junk.
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But what's interesting is that right now people are like the most mad they've ever been at X.
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I feel like that's kind of the mood.
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But I feel like the algorithm has been super fine-tuned.
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And maybe that's just the way I'm using it.
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I'm really good about like muting.
10:23
Well, one of the reason one of the reason that people are are mad right now is the dive bar basically got a new manager, head of product, Kea, who was a power user of the platform for years.
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>> Power drinker, >> power at the bar, >> power boozer.
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>> He was hitting the hour.
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>> And he was closing it out.
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>> He was closing it out.
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>> Um, and he's been making a number of different changes.
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One that he posted about that I was excited about was potentially bringing links back in some capacity.
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Yeah, but >> he also did little there's little growth hacks that he's done where I've been like that's totally fine.
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Like when you take a screenshot, it replaces the follow button with the X.
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com just to remind people, hey, this originally appeared on X.
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If you're going to share to Instagram, go to x. com.
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And I think that type of growth hack is like fine.
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Like it it doesn't bother me at all.
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It's like, yeah, they they they need to get their users up.
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I want more people on the platform. Like I'm fine with that.
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And there's been a number of things like that where I've been like, "Yeah, seems like he's he's making pro positive progress on the product side, but the creator payouts are still really hot."
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Like very very like hotly debated.
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Uh unclear where >> not among us.
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We would be down to kill them entirely. >> Yeah.
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And what's crazy is that I I mean I don't know if I got on.
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So Twitter launched in July of 2006.
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I'm pretty sure I got on like a year later because I went to co I went to college where Bis Stone went to college, one of the founders of Twitter.
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And that was one of the reasons I went to that college was because I was interested and I was like, "Oh, Twitter's a cool company."
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>> Um, >> April 2009 >> was when you got on or when I when I joined. Okay. Yeah.
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So, >> but still >> sophomore year of college or something like that. >> Very early.
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>> Um, but for 17 straight years, basically everyone on the platform posted for free, >> I guess, for you know, 13 years for me. I posted for free.
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Uh, July 2023, 17 years later, that's when the first creator revenue sharing program rolled out.
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Uh, and what's interesting is that YouTube has been making creator payouts since 2007, just one year after Twitter launched.
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YouTube was like, "We got to pay these people.
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We got to pay our creators."
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And they did this like basically 50-50 deals, like 45 55.
12:22
Um, but YouTube, the partner program has been a huge success.
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Basically, you make no money when you're small.
12:29
no money when you're small. But if you can get to a couple hundred thousand subscribers, couple hundred thousand views on a video regularly, you have a formula, you have an audience for like I talk about this and thing for 10 20
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minutes, people watch it regularly every week, like you can quickly start making thousands of dollars and like turn it into a real job and then you can layer ads on top, which you're obviously intimately familiar with because you've been on the other side of that. And and
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And and there is basically like a middle class of like professional, not not Mr.
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beast level hundred person organizations, but just like a creator, maybe they have one editor, couple editors, and they make a decent living just, you know, making YouTube videos.
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Uh, X has never really had that.
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And it's odd because like the amount of money that you put into a YouTube video is correlated with how many views it gets.
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Like if you're like, I'm giving away a Lamborghini.
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I'm going to drive a Lam I'm a Whistland Diesel.
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I destroyed a Lamborghini.
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You're like, I got to click that. It gets a lot of views. Yeah.
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But on X, you can just have a shower thought that is the most brilliant, hilarious, funny, banger take and it will get 100 million views.
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>> For me, I'm not very consistent with posting.
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I'll just decide I'm going to post today and then I can put up >> numbers >> posts that will get I don't know.
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I I could think I could reliably get 500,000 impressions >> by just spending like 20 30 minutes really focused on it. Yep.
13:45
>> Uh whereas trying to sit down for 20 30 minutes and try to make a YouTube video that gets 500,000 views almost impossible even for the top top top creators unless you're like Mr.
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Beast and you can >> actually at the scale where you could post a selfie video, but even then that's not what drives his business. >> Yeah. Yeah. Exactly.
14:00
And so uh so there's this and >> and we all and and the other thing that's worth noting is like there's totally precedent to have a thriving social media platform that doesn't do any creator payouts at all and that is Instagram, right? Yeah. Totally.
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Instagram has never I mean I shouldn't say never because they've experimented with little things over the years.
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They did some AI uh companion type things with celebrities.
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I'm sure they paid them in those situations.
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But >> in general, there's always been an incentive to grow an Instagram following so that you could grow >> uh a business or partner with brands or there was just a number of ways that you could monetize it uh indirectly.
14:35
could monetize it uh indirectly. And I think that that is uh for for loweffort platforms a much healthier way loweffort content creation platforms >> it's a much healthier to have the incentive be like you have to you have
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to become somebody that is valuable to the world not just you have to post the thing that the thread that gets 5 million impressions right and and the worst of the content that I've seen since the >> monetization >> monetization era of X has been the why
15:07
is no one talking about Mark Andre post and it's like a thread and it's like >> cool but but we everybody's talking about Mark Andre like to find somebody on X in tech that doesn't have an opinion on Mark Andre right you're not it's hard to hard to find him um >> and so I think it was healthy I think if
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you look back to when this era kicked off though I mean the vibes on X were just terrible the public perception of X was terrible and I think it made sense Elon moment, but you need to ride with me through this tumultuous time. >> But it feels like we're back in an era
15:48
>> But it feels like we're back in an era where if you turn creator monetization off today, none of my top 50 favorite posters would really care.
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They'd be like, "Ah, it's kind of a bummer.
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I was making a few grand a month."
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Like, >> and I'd use that to I don't know.
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But >> more like a couple hundred bucks for for a lot of the posters that I follow.
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Like there's a few people that are in that thousand plus club, but it is rare.
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Like you have to be you have to be taking it pretty seriously.
16:14
But uh but yeah, I mean in general for 17 years no one got paid directly on Twitter.
16:19
Uh and they were fine with it.
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They monetized by recruiting or finding jobs or pumping their company or just pumping their bags.
16:26
Like there were a bunch of ways to to monetize.
16:28
Um one of the ways that we monetized by running ads reream. io.
16:31
We also stream 2x through rerecam one live stream 30 plus destinations multi stream to reach your audience wherever they are.
16:38
There's also going back to like the Instagram thing with Tik Tok.
16:40
They did Tik Tok and musically they did figure out this what >> I'm looking back through my creator payout history and it's so funny that the dates are always different. >> Mhm.
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It's like, >> oh yeah, yeah, yeah.
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It's not like on the first, >> okay, I'm getting a payout for four days here and then the ne and then next I'm getting it for two weeks and then after that it's like one week >> and it's just like completely random.
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So I go from making >> Yeah, I guess I don't know.
17:08
I I probably I've averaged like roughly um probably like $400 period or whatever. So like $800 a month. >> Yeah.
17:18
But it's just one of those things like at no point was I thinking I want to post more because I'm gonna get paid more. >> Yeah.
17:26
>> It's just not the incentive for me to use the platform. >> Yeah.
17:29
So, I mean it's interesting to look at the history of like how Tik Tok did it.
17:32
The the the founder of Musicly came up with this idea of like the dual-sided marketplace.
17:36
I'm sure YouTube was aware of this too, but basically they put a bunch of money from ads in a fund and then they would just pay you out based on views.
17:42
But it wasn't like they were actually showing ads directly in front of your content.
17:46
YouTube's a lot better than that.
17:48
Like, a lot better than that.
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Like, if you make a video like the top 25 best credit cards, they will be running ads on credit cards in those videos and you can get you can make thousands of dollars just from like 10,000 views or something because it's super high CPM and it's targeted to the individual video.
18:04
Now, in a endless scrolling feed, you can't do that because you don't know where the ad was relative to the particular post.
18:11
And it's the same thing on X.
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So if you post some banger post you and there's an ad right above it or below it, you don't know if that ad is attributable to that person.
18:21
So you kind of just need to create this, you know, creator payout pool and then just divvy it up based on impressions or views which is a lot harder to actually assess, you know, how much people want and also the pool isn't all that big because X doesn't even advert it doesn't even monetize that much through ads and so there's just a lot of uh a lot of differences there.
18:42
So, I've always kind of gone back to that analogy of the dive bar, and I've just kind of thought that the creator monetization, I don't really care if it's messy.
18:50
I think it's kind of fun if it's messy.
18:52
Um, >> I mean, we have to go back to uh one of my >> Please >> most liked posts ever. >> Yeah.
19:00
>> Uh, Elon unhooking your bra.
19:00
Wow, your creator payout is going to be huge next month.
19:06
>> That's one of your biggest >> The most liked.
19:07
The most liked is actually Ashley St.
19:09
Claire liking that house and you said real. That's ridiculous.
19:14
Um, >> but yeah, I mean, I've always enjoyed that like these random serendipitous moments can happen on X.
19:19
Uh, like Elon responding to a random message with a crying emoji.
19:24
Uh, it feels like when the chef comes out and goes around to dinner tables to chat with the guests about the food, you know, Elon comes around and just leaves the crying emoji over here.
19:35
It feels like he's on the app in in a much different way than >> walking around shot for you.
19:39
You get round of shots for this table. >> Exactly. Exactly.
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And so I I actually like that.
19:47
I think it'd be very funny if Elon just dropped, you know, $1,000 on this person, $200 on this person.
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It was complet no rhyme or reason whatsoever. Chaos.
19:55
Uh I I think that actually makes it kind of fun.
19:58
Uh it feels like putting a slot machine in the corner in the corner of the dive bar.
20:01
you know, some some patrons are just gonna throw a quarter in every once in a while just to feel something.
20:06
So, um >> yeah, and I and and I I think this is where we slightly disagree.
20:09
I just think it's it's enough to just go around drop the like, drop a repost, drop because ultimately people come to X for attention. >> Yeah.
20:20
>> Like learn about the world to get attention. >> Exactly.
20:22
Um well, it'll be interesting to see if we see any like changes to the monetization structure of Axe or the creator payouts.
20:30
Uh people are certainly there is a big group of creators like this is very real.
20:36
There's a big group of creators that are just saying like like it has to be more regular.
20:40
It has to be easier to understand how the creator payouts like they're pushing for a YouTube like transparency partner program where it's very very clear that if you get this audience this many views like you will get this much money on a regular basis.
20:55
And the other thing I think people forget is that the creator payouts were initially meant to be paid out a percentage of the subscript paid subscribers. >> Yeah.
21:05
>> That paid subscriptions.
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That was what was creating the pool for potential payouts.
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And so what the accounts that are angry >> and post and generally the accounts that are angry at creator payouts >> are angry because they're slop farming >> and their content is just not good and they're specifically making doing making the content to make money. Yep. >> It's fair game. It's capitalism. It's free market.
21:27
They're allowed they're allowed to go and do this.
21:30
>> But they're not getting engagement from verified >> like users. Yep.
21:36
>> For the most part, right?
21:36
They're getting engagement on these posts where they get a lot of impressions.
21:39
They get a lot of likes, >> but it's from like I I wouldn't go so far as to say bots, but it's like the lowest value people on the platform.
21:47
>> I mean, the same thing happens on YouTube.
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Like you can like there are channels out there that make get millions and millions of views with just complete clickbait.
21:53
One of there was one channel that would just it was like Elon Musk news or something and they would just post entirely fake videos about Elon Musk launching an iPhone competitor and it was like the Tesla Pi phone.
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and it'd be like, "We're reviewing it today. We're breaking it down.
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Here's the phone that he launched."
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Elon, they did one that was like, "Elon Musk just launched a nuclear reactor. It's live. He built it. It's generating power."
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And Elon had like never tweeted about this.
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And he's in fact a solar maxi.
22:21
He doesn't even like nuclear that much.
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And they would just put up a video being like it would just be B-roll of Elon like moving around, dancing, talking.
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And then over it they would just have like this fake script saying that Elon had shipped a nuclear reactor and solve fusion or whatever.
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And it would get millions and millions of views with people who just like did not understand the truth or anything of the news.
22:40
And so of course that's going to monetize way way worse.
22:44
This is the number one thing that pisses us off on YouTube is when you're watching a car video and there's a suggested video >> and you click on it only to realize that it's like some fake concept car that wasn't put out by Porsche or Ferrari and it's just somebody hallucinating with their chat >> GPT.
23:01
Well, speaking of concept cars, we got to go deeper in the deck and pull up the video the picture from Mercedes. Uh I think this is real.
23:09
I don't think this is AI.
23:11
I saw this on a couple different auto blogs.
23:12
Uh M the M newly revealed Mercedes Vision iconic channels the legendary Gullwing. No way.
23:20
>> And it's your first look at the next S-Class. >> Is that an EV? >> It's I know.
23:25
I think it's going to be uh both.
23:27
But you can scroll through these images and look at this thing. Look at the back, Jordy. >> The back is insane.
23:32
Imagine bombing around in this.
23:36
Obviously, this is like a uh a concept car.
23:37
Um but it's still cool and I hope it's real. I I was right.
23:43
>> A statement on the future of design language for Mercedes EVs.
23:45
This looks like >> kind of Jaguar coated >> a little bit.
23:51
>> You know, what do you think overall?
23:52
This Yeah, it does feel like it's a little bit it's a little bit blocky like big front grill like Jaguar, but still maybe a little bit >> This view looks better than the existing GT. >> Yeah. >> Series. >> A little bit longer. A little bit. >> A little bit longer.
24:09
Yeah, >> I think it's pretty good. low.
24:10
It's riding a little bit lower even.
24:14
>> Yeah, >> I think looks great.
24:14
I think the grill on the front looks a little bit nasty, but especially considering it's a >> it's a concept car.
24:22
>> It looks Yeah, it's a little wild, but whatever chooses to build, they should do it with cognition.
24:27
The makers of Devon, the AI software engineer, crush your backlog, Nikita, with your personal AI engineering team. >> Love to see it.
24:36
>> It's not going to help right now. >> Is at war.
24:39
Zoomer also had a post here.
24:41
He said, "This is going to be good."
24:41
Uh, and he is quoting Colossus magazine.
24:47
Jeremy Stern has written a lengthy profile of Josh Kushner, Thrive Capital, and the American Dream. >> Okay.
24:55
Before we get into that, yes, I think we need to address the Goon Wars. >> Oh, sure.
25:00
>> Sam Alman posted two hours ago.
25:00
He said, "We made chat GPT pretty restrictive to make sure we were being careful with mental health issues.
25:07
We realized this made it less useful, enjoyable to many users who had no mental health problems.
25:12
But given the seriousness of the issue, we wanted to get this right.
25:15
Now that we have been able to mitigate the serious mental health issues and have new tools, it's wild that he's just uh like >> job's finished.
25:24
>> Uh well, yeah, it's it's it's wild to basically say to just fully accept like yeah, there were serious mental health issues.
25:31
But uh bold uh uh he said we're going to >> we've seen more examples of the oneshotting getting in stuck in some hole.
25:39
So maybe they did solve that. I don't know.
25:41
Like we >> Oh, it's totally possible.
25:42
When when these issues were popping up, it's like okay, this person was 7,000 prompts deep.
25:48
That was >> pretty easy to just be like if more than a thousand prompts deep, send message. Hey, touch grass.
25:53
Like take take a breather.
25:56
>> Yeah, just end the just say like if you send another message, the chat will be ended.
25:59
Yeah, that doesn't seem like technically complicated to implement.
26:02
>> So Sam says, "In a few weeks, we plan to put out a new version of chat GPT that allows people to have a personality that behaves more like what people liked about 40.
26:08
If you want your chat GBT to respond in a very humanlike way or use a ton of emoji or act like a friend, chat GPT should do it, but only if you want it, not because we are usage maxing.
26:17
In December, as we roll out agegating more fully and as part of our treat adult users like adults principle, we will allow even more like erotica for verified adults.
26:34
And uh Doug over at semi analysis says the goon wars have begun.
26:37
The entire porn industry is about a hundred billion which can fund a few gigawatts.
26:42
So I think that um we always thought that uh I wouldn't go there Elon.
26:53
>> Yeah, it was it was a smart you know this is what we said it's very possible that that Grock if they were able to figure out the erotica >> uh product side that they would be able to take that product to a really meaningful run rate.
27:05
uh very hard to assess like what percentage of Grock users or power users of the companion functionality but either way this kind of thing was already happening with OpenAI.
27:16
People were falling in love with OpenAI.
27:18
They were getting married to not not not OpenAI but chat >> I got married to OpenAI.
27:23
Uh no people were were you know proposing to ChatGpt, right?
27:28
people were developing serious romantic uh relationships with >> uh the bot and uh of course now Chad GBC. Great great catch.
27:38
John just slid away in the swivel chair >> to uh catch love to see it >> putting on a clinic.
27:48
>> Well, if you want to design something that's not erotic, uh go to figma. com.
27:52
Think bigger, build faster.
27:52
Figma helps design and development teams build great products together. or get started for free.
27:59
Um, >> touch Figma, everyone. >> Touch Figma.
28:02
Yeah, if you're 7,000 problems deep, maybe something is your Yeah.
28:08
What What is your What is your actual final take on this?
28:10
Um, uh, hundred billion dollars, that's the that's the entire adult industry.
28:14
I I think that a large percentage of the people that will pay a subscription fee to Chat GPT as just everyday consumers will be people that >> develop like serious emotional connections.
28:29
Not necessarily adult level. >> Sure.
28:33
>> But but serious emotional connections. >> Yeah.
28:37
I mean I I like the the steel man here is like treat adult users like adults principle.
28:43
Like I have not tried to generate erotica, but I've definitely gotten flagged for like weird reasons being like, "No, you can't make this person into a bodybuilder or whatever for some reason."
28:55
Like like those muscles are too big. Like this is horny now.
29:00
And I'm like, "No, like it's actually just a joke."
29:02
Uh, and so I I I would be I would actually be happy to like kind of like age verify and just allow it to be like a little bit more lenient with me if and give me like the benefit of the doubt.
29:12
But it does seem like it does seem like the like the PR backlash from some of this stuff is going to be a little wild.
29:19
Like and there's just been so many tech companies that have just said like, "Hey, yeah, like we're just Apple famously like drew the line. Google.
29:28
>> Well, well, the the other the other side here is uh it's not like Google if you search for Bob, Google doesn't say like you can't search this. Right. >> Sure. Sure. Yeah.
29:38
I I think uh the like just just mirroring there there's immense power in mirroring what people are already comfortable with morally.
29:50
And so what I would do is I would just say like we're bringing chat GPT in line with what you expect on YouTube.
29:55
Now, are there some graphic videos on YouTube of 360 nocopes with, you know, visually like distinct blood?
30:06
Like, yes, there is R-rated content on YouTube.
30:08
You can you can watch R-rated content of a Tarantino film clip.
30:14
You can watch uh a Call of Duty montage that is gory and maybe not suitable for children.
30:19
Uh but it's not a place for true adult content, and that doesn't exist.
30:25
360 nocope compilations >> when you were four. >> Yeah.
30:29
From a young age, >> it made me who I who I am. >> Turned me into a man.
30:33
>> But but but uh Instagram apparently is doing this too.
30:36
There was an article in the Wall Street Journal about this how they're using the nomenclature from film making now saying that uh we will go up to PG-13 or you will be able to to pick and I feel like even though movies are like less popular uh than social media on this side of the table.
30:53
Yeah, it's very useful to use the GPG, PG-13, R-rated, X-rated, like nomenclature just because everyone knows what that means.
31:07
Even though it's like a I'll know it when I see it type of rating that's done by the uh not the AP, there's some there's some governing board that literally watches every movie and says like this is R-rated because we saw we heard like three cuss words and like whatever. >> Yeah.
31:21
I mean, here here's the thing.
31:23
When I see this announcement, I'm >> not entirely surprised.
31:26
Even though I didn't think they would explicitly go there. >> Yeah.
31:31
>> I didn't think they would.
31:31
I think that I didn't expect to see Sam >> type the words erotica in a product update. >> Totally. >> Post, right? >> Didn't expect it.
31:40
Makes sense from a business standpoint.
31:42
I don't think they should expect applause.
31:43
I don't think anybody should be, you know, I don't think OpenAI investors are going to be sitting around being like, I'm proud that OpenAI is going into this, but purely from a business standpoint, it makes sense. >> Yes.
31:58
So, >> and the other thing is I I expect that they will uh the key difference between XAI and OpenAI is that OpenAI will not use this adult content in the promotion of ChatgBT. Right. >> Sure. >> Whereas Elon >> Yeah.
32:14
Yeah, >> was very, you know, forward with with promoting it.
32:17
>> Yeah, I don't like talking about this all this adult content.
32:19
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32:35
Um, do you think in a in a year we will look back at Chachi PT as a place that's Rrated like Euphoria level or HBO level or a succession level uh like adult themes and adult content or like X level like not not like X-rated level?
32:55
>> I mean >> full adult content like you would not see on HBO beyond what's available on HBO.
33:01
>> I'm sure it will be beyond. >> You think so? >> Yeah. >> Okay.
33:03
That would be a bold step because I feel like >> but the whole but the whole point is that opening up all of those companrated but we won't go beyond >> but chat GBT is fundamentally a single player experience right it's it's >> uh it's you know some of some of the >> screenshot you take a screenshot and it's their brand next to the thing that it generated.
33:24
It's it's it's like going to Apple TV and saying like there is an adult film on Apple TV right now.
33:27
Like I take a picture of the Apple TV and I show you that like it's it's in their store.
33:34
>> This kind of content pops up on all the platforms, right?
33:38
>> Well, I I don't think so.
33:38
I I I think that YouTube and Apple TV like very distinctly try and not >> Reddit Reddit is notorious for this, right? >> Yes. Yeah.
33:47
I would put Reddit in a different category.
33:49
And so, yes, this is a decision to go more Reddit and less YouTube.
33:52
>> And OpenAI is trained heavily on Reddit.
33:55
So, so maybe that's >> makes sense.
33:56
Do you think this do you think this aligns with OpenAI's mission to ensure that artificial general intelligence benefits all of humanity?
34:04
>> H >> do you think human humanity will benefit from everybody uh having uh a Goonbot in their pocket?
34:12
>> As long as every member of humanity is a shareholder, then they will then they will profit from it, which will be good. No, I don't know. Uh it depends.
34:20
There there's a ton of uh there's a ton of like rough edges and like variability here that I'm like holding.
34:28
>> Ty in the X chat says bare market and morals.
34:31
>> Bare market and moral.
34:32
>> Well, in other news, uh Anthropic uh David Saxs is going to war with Anthropic.
34:38
>> He uh quoted uh one of Anthropic's co-founders, Jack Clark, and said, "Anthropic is running a sophisticated regulatory capture strategy based on fear-mongering.
34:46
It is principally responsible for the state regulatory frenzy that is damaging the startup ecosystem. >> Interesting.
34:54
>> Uh not what you want to hear from the AISAR if you're running a a US-based foundation model lab. >> Yep.
35:03
>> Um but uh we'll see how this plays out. >> Yeah.
35:08
You want to hear about graphite if you're the AISAR. That's right.
35:10
David Saxs, you got to use this for your code review because it's the age of AI.
35:17
Graphite helps teams on GitHub ship higher quality software.
35:18
You can get started for free.
35:19
Uh let's go through some of the Jared Kushner news. >> Josh Kushner. >> Josh Kushner.
35:27
Jared Kushner is also featured in here. Sorry.
35:30
Um uh uh I I was reading I was reading Jared Kushner because Tyler posted sending Jared Kushner 25 books on how to prevent AI bubbles from popping, which uh was an absolute banger. Got a thousand likes.
35:46
Tyler's been on a tear, but he's not even in his seat. Let's cut.
35:48
You gotta cut to him before he gets back. No.
35:53
>> Oh, he was out of his chair. I caught him. I caught him black.
35:55
>> Congrats on >> backtoback bangers.
35:57
Oh, 1K club two days in a row. Don't mess it up.
36:00
If it's not a repeat, just don't show up to work. You're done.
36:04
Do you feel uh do you feel sequel pressure now?
36:09
>> I mean, it there is a lot of pressure on my, you know, on my shoulders.
36:12
>> Heavy is the head that wears the crown. Tyler, get ready. You've been on a roll.
36:17
Let's see what your ex creat >> I don't know.
36:18
I see this I see a couple bangers back toback and I think maybe Tyler doesn't have enough on his plate.
36:23
Maybe >> maybe we should get him to vibe code something.
36:26
>> I I I got to hit um I think I I think it's 5 million impressions in three months to like I'm not available for the creator payout yet. >> Okay.
36:34
>> So I think I got to slap it up in the next couple days. >> Yeah.
36:36
Why is no one talking about Sinsk?
36:39
>> I'm never leaving this app. >> Yeah. Yeah. Yeah. Just keep posting those.
36:43
Uh you you'll definitely >> Ty in the chat says if you cut to someone not in their battle station, they have to wear a part-time podcaster. >> Thank you.
36:51
>> Yeah, really really phoning it into having fun.
36:53
Uh so uh >> yeah, let's get into this.
36:55
Let's get into this piece.
36:56
Uh uh Jeremy Stern profiled Josh Kushner in Colossus. It released today. It's not in print yet.
37:05
>> It's going to be in print, right? >> Get ready. >> Um the new world.
37:12
Where do you want to start?
37:13
>> Where should we start?
37:13
I mean, there's there's so much in here.
37:16
>> I I like this uh bit about Spotify.
37:16
So, uh in 2012, uh Thrive invested $6 million in a growth round of the Stockholmbbas based Spotify out of $150 million fund, an allocation Kushner had regarded as a favor until learning nearly a decade later that Spotify CEO Daniel Ek was in need of exactly six million to close the round.
37:36
So he's just like he's just like, "Oh, thank you so much for like making room for me. Like this is amazing.
37:43
Like I'm so glad I could like, you know, get my six million in."
37:47
And and Daniel X over there being like the crowd would have completely if you hadn't come in. So thank you so much.
37:54
But uh there's more to this anecdote.
37:56
This is the reason E knew he liked Kushner was that a few years earlier when Spotify was only available in Europe, E was notified by an executive that someone in the US had manager managed to register a fake UK address in order to download the app via the UK app store.
38:12
They discovered it was Kushner sitting in the library of HBS. >> Wow.
38:19
>> It's a Yeah, >> I pulled out some highlights from the piece.
38:21
It's way too long for us to try to to get through entirely.
38:23
Um, but the uh some background uh on November 17th, 2023, Kushner was a 38-year-old spouse of a supermodel, brother and in-law of American political royalty and founder and CEO of what would what had very suddenly become one of the most coveted venture capital firms in the world.
38:41
firms in the world. He was also the grandson of survivors of the Novo Gruda ghetto massacres, indignant uh in indigent refugees who over the course of the Cold War built a New Jersey real estate principality that their son Josh's father expanded into a
38:56
multi-state empire before his conviction on felony charges and sent sentencing to federal prison and before the White House activities of his older brother Jared put Josh in the crosshairs of a torid political convulsion of which he wanted no part. So, um,
39:10
So, um, >> Kinder Spirits. >> Yeah.
39:14
I mean, ultimately it's it's it's this uh Josh has put on an absolute master class of how to >> be an icon while being relatively in the shadows, right?
39:28
He just sort of like pops his head up in these key moments.
39:33
Um, and uh, yeah, I think when I think about what Thrive what Josh and the and the Thrive team has built, it's actually it's I mean it's just like it's almost it's almost unbelievable >> that like the story the story end to end.
39:51
Um, >> by the fall of of 2023, Thrive Capital, the New York based investment firm Kushner started 13 years earlier, had become an overnight sensation.
39:59
In 2010, Thrive's first fund was 5 million and included companies like Kickstarter and Group Me.
40:06
By 2023, its eighth fund was 3.
40:08
3 billion, including a maniacally concentrated $2 billion investment in Stripe at a $50 billion valuation.
40:14
So, he's like, here's two/3 of my fund.
40:19
>> This is the Fifth Avenue strategy. Buy Fifth Avenue.
40:21
He talked about this on invest like the best.
40:24
>> And a $150 million check into OpenAI at a $29 billion valuation.
40:26
The companies are now valued at 107 and 500 billion respectively.
40:31
Along the way, Thriv's bet on Instagram, Spotify, Warby Parker, Skims, GitHub, Slack, Robin Hood, and other companies had become uh conspicuous for being preient, aesthetic, and exquisitely timed among its most vindicated admirers, and for being absurdly priced, momentum chasing, and too highly concentrated in dysfunctional businesses with unproven returns among increasingly sheepish critics.
40:56
So, um, >> I like that they got Johnny IV to give a quote for this piece.
41:01
Some people just have innately wonderful taste and intuition.
41:05
Uh, said Johnny IV, Apple's legendary former chief design officer who's now working with OpenAI on a hardware device.
41:11
Josh has wonderful taste.
41:13
I think it bleeds into his product intuition, which is just fabulous. >> It's great.
41:17
>> It's great. Um another another highlight here uh in 2020 in 2010 moreover the unknown Kushner's brother unknown little firm was making a bunch of large but weird sounding claims for itself like that it was a stage geography and sector agnostic venture firm that would concentrate all its investments in a
41:36
very small number of companies that it was not only an investment firm but also itself a company that it incubated its own companies as well as invested in others and that it didn't just invest and incubate but functioned as a service provider, product creator, and embedded operational commando unit for founders. By 2023, every self-respecting investor
41:52
By 2023, every self-respecting investor on Sand Hill Road was also saying such things about themselves, even as they wondered how a New York firm made up of a handful of kids in their 20s and 30s, many of them with zero experience in venture capital.
42:04
And from the technology Bermuda Triangle of New Jersey had become some of the most desired investors in tech and the ones most closely associated with the otherwise distinctly West Coast boom in AI.
42:17
Um uh of course uh Josh had a very untraditional pathway to venture capital.
42:24
He w to Harvard for undergrad while uh at the time uh Mark Zuckerberg had just dropped out of Facebook.
42:30
Later he uh got a job uh at Goldman Sachs buying distressed debt and then went back to Harvard for his MBA uh and uh real of course I'm joking a little bit but it but it's it's um the what I what I appreciate about >> what I appreciate about Josh is uh in many ways he he was on uh he was on the perfect trajectory to be a venture capitalist.
43:01
And yet he has succeeded beyond what he has succeeded in a way that so many other thousands of people that had the same kind of pathway into the industry by being in the right circles like being early to a number of these these different trends.
43:19
like he's succeeded on a hundred time on a a scale a hundred times greater than um many of the other people that were again had the same kind of like pathway in the industry. >> Yeah.
43:31
My read on it is that uh a lot of the VCs that started in the same like vintage that did not become massive institutions uh maybe just got caught in the trap of diversification.
43:44
Like I keep going back to that story of Josh saying he wants to buy Fifth Avenue, buy the best asset in the class, be concentrated, build a big allocation.
43:54
And that takes guts that I think a lot of VCs kind of fell in the trap of like I need to get a bunch of logos from I need from a whole bunch of companies or it's particularly cool.
44:05
it's particularly cool. It's actually higher status to be oh first check in this company or see even if you have a tiny allocation that gets completely diluted down like you're not actually making as much as many dollars like if you put two billion in stripe at at at
44:21
50 and it goes up to a hundred you made $2 billion right versus you put 200k into some company gets diluted down you make 50 million like you made way less dollars on dollars return um but it's like somehow higher status in venture to be like, "Yeah, I was like the first check in." And I think uh Josh has been
44:40
And I think uh Josh has been early in a lot of companies, but I think that he understands the importance of like portfolio concentration, like actually getting all the dollars in the companies that matter. And that's like >> Yeah.
44:53
I think early on I think my my sense is that there was some like hunting for logos early on but they were when the fund sizes were very small >> and that led to him having the the track record and ability to put $2 billion into Stripe out of a three $3.
45:06
3 billion fund >> and also like we're just like like the Thrive era the era that Thrive grew in is an era where venture changed pretty dramatically.
45:19
I mean, we were talking about the Intel IPO, raise $6 million.
45:23
Like, what is your role as a venture capitalist?
45:25
Like, deploy $100,000 and then wait for the IPO like a year later.
45:29
And it was like that in the.
45:31
com boom and Google IPOed pretty early.
45:33
Even Facebook IPOed at what 50 billion and it was like the biggest IPO of all time.
45:38
of all time. uh it was in like the >> yeah there were there were investments in that era that I'm sure the partners were underwriting is I think there's 70% chance this company IPOs in the next two years this is why we're investing and then they became compounders and over
45:53
time it looked like >> but they distributed and so a lot of the funds became raas but uh Thrive has been able to say yes we're we're investing in a company at 50 billion because we expect it to grow and grow and grow uh and actually deliver like a venture style return or a significant return. >> I appreciated this exchange between uh
46:10
>> I appreciated this exchange between uh uh part of the article, the beginning goes into Kushner visiting um Rick Rubin in Malibu and uh Josh was telling Rick, "My deepest insecurities is that I have these intuitions about things that I cannot explain to anyone."
46:24
Kushner told Ruben as they sat in his garden overlooking the ocean.
46:27
"Sometimes I see or experience something and it makes sense to me.
46:31
I fall in love, but I cannot explain why.
46:32
Like when Thrive invested in Instagram or Spotify or OpenAI, I could not explain to anyone why the products made sense to me.
46:38
It is my job to learn as much as I can for my team and teach them as much as I can.
46:44
But often I have to push forward on my intuition alone.
46:46
Which is why my even deeper insecurity is what if I lose it?
46:50
Like what if I lose the capacity to feel or experience these things?
46:52
Uh he's basically the uh having this exchange because of course um Rick Rubin notoriously is just going off of raw intuition and uh and vibes.
47:07
>> Um >> I think the other the other I mean it goes it goes into his entire >> um his family's crazy history dating back to >> Europe during World War II, >> getting out of Europe.
47:20
Um but the um I think uh can't be understated how formative it was I think for Josh to go through this this sort of uh you know right as he was uh the quote here by the time I was in high school my father had accomplished a tremendous amount.
47:36
He was deeply impactful in both the business and phil philanthropic worlds and then overnight our family were outcasts.
47:41
The world treat us treated us all one way for the beginning part of my childhood and then suddenly they treated us very differently.
47:49
That experience showed me how the world works and why you should not care too much about what people think.
47:54
think. Uh, of course, um, his father was embroiled, uh, in a, you know, wild crisis and, uh, ultimately went to prison, uh, for a couple years, but, um, I think, uh, Josh says elsewhere in the piece that he wouldn't, um, uh, I forget
48:11
the line exactly, but something like wouldn't wish what he went through on his worst enemy, but at the same time wouldn't uh wouldn't uh uh is is sort of grateful for uh for what kind of turned him into a basically very kind monster. >> Well, if you want to try and reverse
48:28
>> Well, if you want to try and reverse engineer Thrive's returns, dump all that data in Julius and chat with your data and get expert level insights, it's the AI data analyst that works for you.
48:38
Uh Tyler, what are you thinking about Kushner?
48:41
>> Uh I I think there's also underrated is he's he seems very um orilled, right?
48:43
He has this kind of nonchalance about him.
48:49
Y >> there's a good quote I think that relates to this.
48:51
It says um uh it's about Andy Golden.
48:53
He's the um uh Princeton endowment head.
48:55
Uh he says Golden later recalled a happy hour for VCs in Cambridge in 2010 where he saw a 6'3 emo looking kid in a black cardigan standing apart from the group staring at the floor.
49:06
I mean that is just pure pure aura. Yeah.
49:09
>> Uh apparently we're on French TV right now.
49:11
Thank you for the notification.
49:13
Send us the link if you can find it.
49:13
Uh would love to see that.
49:16
Um, yes, there seems to be somewhat of a of a cor correlation or inverse correlation between like uh just how much content and availability you like how how available you are in your aura.
49:28
Like Ilia like never does any press. >> Yeah. He's very mysterious.
49:34
>> Very mysterious >> because the mystery allows like people to like build this idea of you and >> Exactly.
49:40
You're like oh yeah like even when Ilia posted yesterday like oh great the best day ever.
49:45
Everyone was like, "Clearly this is a >> like bubble is gone.
49:48
I mean, we're going to keep going. We're safe."
49:51
>> And and it's like that's not what it was about at all.
49:52
He was talking about geopolitics and the end of the Gaza war.
49:55
But um >> so Rim K in the chat says, "We asked for a link and rim uh Rim K says France 2, which apparently >> you just have to go >> just go to France.
50:04
France 2 is the channel name." Yeah. No, I know. >> Find it.
50:08
Is there a way that or something? >> French cable here.
50:11
>> I would love to see >> go sign up try to sign up for an account. >> Did they translate?
50:14
Did they put subtitles over us?
50:15
I'm so I'm so curious about this.
50:18
Uh anyway, while we dig, >> this is very They just have the interview. >> Yeah. Yeah.
50:22
But I'm wondering because they could have put French subtitles over us or they could have dubbed us with 11 Labs or something.
50:28
>> Ask Le Chat >> how to how to get access to French.
50:33
>> There there is uh more details on how the OpenAI deal came together in this article that are pretty interesting which you should go read.
50:38
Uh I feel like I'm allowed to trash investors because I was one for most of my career.
50:43
Sam Alman said, "Most investors don't work that hard.
50:47
They're usually not available for midnight at calls and won't drop everything to fly across the country on short notice to do you a small favor for you the next day."
50:53
Josh is consistently willing to do all those things.
50:55
He's incredibly hardworking for his companies.
50:57
He'll do whatever it takes, any amount of time.
50:59
Nothing is too big an ask.
51:00
Uh during that crazy week where I got fired and rehired, he just put his entire life on hold.
51:04
Uh he didn't leave his hotel room for 72 hours.
51:07
He just worked non-stop, very strategically, very effectively to get things back on the rails.
51:12
Thrive had first gotten involved in OpenAI in early 2022 when they met Altman to discuss a new round.
51:18
They'd been given a preview of GPT3, the foundation model that preceded Chat GPT, which Kushner reportedly became so obsessed with, he almost seemed haunted by it.
51:25
Now, that's that needs to be like corrected because GPT3 came out in 2020.
51:31
So, I think they're either talking about GPT 3.
51:32
5, Da Vinci 002, which was really popular, or it's just a preview of ChachiPT because investors were getting previews of ChachiPT beforehand, and it was like blowing everyone's mind, but it was a really complicated deal and a lot of people passed basically for the wrong reasons in my opinion.
51:49
uh >> on on Kushner's work ethic.
51:50
There was a he was uh we met up earlier this year >> for coffee >> and he was he was uh I I had like gone to sleep.
52:01
He was still on the East Coast. It was like >> 2:00 a. m.
52:04
He's texting like, "Yeah, do you want to like uh I'll see you at like 10 or something like that."
52:09
I'm like, "You're on the East Coast. >> It's 2 a. m. for you.
52:12
You're going to get to the West Coast and be ready for and and so >> absolutely That is part of the part of the story obviously is just insane, you know, insane work ethic. >> Yeah.
52:24
>> Uh I see in the chat somebody said uh we're on France too.
52:26
And uh Taylor says dang, they released a sequel to France.
52:32
[Music] >> Tyler Tyler is MVP of the chat this week. >> Yeah, sorry.
52:36
Taylor's been crushing it.
52:39
>> Tyler has uh been struggling to learn French.
52:42
I thought you studied French. You took French.
52:44
I took I took one or I took two semesters of French. Okay. I found it.
52:48
Um yeah, let me I'll screen share. >> Okay. Yeah. Yeah. Yeah.
52:51
Let's figure out I'll keep reading.
52:53
Uh so, uh OpenAI at the time was a cap profit subsidiary controlled by a nonprofit board with a mission of safe AGI development, taking legal precedence over profits.
53:02
Uh Microsoft's $1 billion 2019 investment gave it a dominant position in Open AI with complex revenue sharing agreements and preferential access to the company's technology.
53:12
that and the company was reportedly valued at 29 billion while doing a trivial 50 million in revenue.
53:18
What a ramp from 50 mil to what are they doing now like 10 billion 12 20 billion something like that.
53:22
Uh it was all very weird.
53:24
There was no reason uh there there was a reason no other investor submitted a term sheet for that round. Wow.
53:30
After several conversations with the investment team, however, Kushner marshaled his case.
53:34
Forget the nonprofit structure and Microsoft and all the red flags.
53:38
He argued if you can create this much enterprise value everything else is solvable.
53:42
In any case, colleagues recall he kept repeating things like I saw the future and this is the one. >> Great call. Great great call. Extremely hard.
53:52
I know some other investors who literally passed on that round because they were like yeah like we we we talked to our lawyers and they were like this doesn't make any sense or like we couldn't understand like how we were getting it.
54:02
Like there were lots of smart people that passed.
54:03
How early did people feel like chat GBT was a gonna be a meaningful threat to Google?
54:14
>> That probably started in like March of 23, but uh I but like November I mean people when chat when when GPT3 came out in 2020, people were starting to say like you could use this to you could ask it a question.
54:31
You had to you really had to prompt hack because you couldn't just ask it a question.
54:36
You had to like ask it a question for a list of bullet points and put a couple >> a couple of just laughing rim K is saying it's live now on news. >> It's live. >> It's on France, too. It's on the news. >> It's on the news.
54:51
>> Just we're trying to find it. >> It's on the news.
54:53
Um, and so, uh, Thrive submitted a term sheet, 130 million from its main fund at the $29 billion valuation.
55:01
Uh, in November of 2022, OpenAI launched Chatbt.
55:04
Within two months, it became the fastest growing consumer app in history.
55:06
By summer of 2023, Thrive was working on a $90 billion round.
55:11
And in August, they agreed to anchor uh 400 million of a $500 million employee tender offer, critical leverage in the explo explor exploding war for AI talent against OpenAI's publicly traded competitors.
55:22
Um by November 17th, 2023, Thrive had committed around $700 million to the company.
55:30
So, uh, pretty pretty remarkable results and, uh, really just goes to show you that like there are certain pitches in venture like seeing ChatGBT before it launches that you need to really, really, really, really, really swing hard at and and Josh swung at the right pitch at the right time, which is like fantastic and much harder than I think people think.
55:53
It's so easy now that everyone uses Chacht all the time to to to just be like, "Oh, yeah.
55:58
I would have I would have made that deal too. >> Yeah.
56:01
And ignoring the ignoring the FUD and just like doubling, tripling, quadrupling down every single possible >> Yeah.
56:09
I mean, when when that when that initial round was happening, I was I was also like I mean, I wasn't an investor, but I was I was I was thinking like it just makes a lot of sense.
56:17
I was looking at the team and I was like if you just make the bet on like you have the CTO of Stripe Greg Brockman, you have the former president of Y Combinator just the resume of the founding team at that time.
56:29
time. Everyone was midlurve response was the corporate structure is weird >> like like this isn't a norm this isn't a C corp it's breaking the rules I don't fund non C corps like I'm out >> but just going back to basics of being like the founding team who's running the
56:47
company are they the best you know is this an important category and do I have the best team it's like it was hard to make an argument against it at that time in my opinion um anyway should have invested I guess but you know like doing content instead it's more fun. Um in
57:01
Um in other news with OpenAI um uh there's they did an interview with the uh Broadcom team and Sam Alman shared a little bit more about the custom chips that they're working on.
57:15
Uh before we tell you about that let me tell you about fall the generative media platform for developers.
57:21
The world's best generative image video and audio models all in one place.
57:24
develop and fine-tune models with serverless GPUs on demand clusters >> used by Adobe, Shopify, Canva, Corora and many more.
57:32
>> So, uh, Sam says to zoom out a little bit, if you simplify what we do in this whole process, you know, melt sand, run energy through it, and get intelligence out the other end.
57:40
As we realized we were going to need the whole system together to support this, it's just gotten more and more complex.
57:45
So, it turns out Broadcom is also incredible at helping design systems.
57:48
So, we are working together on that entire package.
57:53
uh we are able to think from etching the transistors all the way up to the token that comes out when you ask chat a question and design the whole system all of the stuff about the chip the way we design the racks the networking between them how how the algorithms that we're using fit the inference chip itself all the way to the end product and so it
58:12
feels very much like like even if they're not you know fully like plateau pelled like there's a lot more research to be done there's a lot more improvements like there are at least pieces of the chat GPT architecture, pieces of the system, whether that's, you know, 40 level inference or reasoning tokens that should effectively be baked down onto a chip. And so that's
58:31
And so that's what uh what OpenAI is working on with Broadcom at this point.
58:35
um uh uh se uh strategy Ben Thompson had a great uh deep dive on or on OpenAI and Broadcom and uh and sort of laid out the argument for working for them working together and baking stuff down onto a chip.
58:52
Um it's a it's a fun read.
58:55
You should go check it out. >> Should we move on? >> Yep.
58:59
I was just going to try to figure out uh what >> Well, while you do that, let me tell you about Turbopuffer.
59:05
search every bite serverless vector and full text search built from first principles and object storage fast 10x cheaper and extremely scalable.
59:11
Uh Broadcom was a $220 billion company uh the day that Chat GPT launched. It is now >> Wow. It's almost >> 1. 7 trillion. >> Almost a 10x. Wow. Nvidia too.
59:23
Nvidia was was much much smaller.
59:26
That might be a 10x as well. Um yeah. Wow. Yeah.
59:29
Wild wild growth across the entire category.
59:35
Basically everything is has 10xed in price or something like that roughly.
59:37
Uh >> yeah, it's interesting.
59:39
think it'd be interesting to go back and do the math and the VCs.
59:42
Uh there was some reporting in the Financial Times couple days ago talking about who actually owns OpenAI and it would be probably uh interesting and painful to look back at the investors how much they invested in OpenAI versus just like market buying Nvidia Broadcom and some of the other beneficiaries and would they have made more money?
1:00:03
>> Um there the the Open AI >> didn't alimter do both.
1:00:05
Yeah, I'm sure I'm sure the the players like that did both.
1:00:10
But uh OpenAI's expected ownership after the company restructures, Microsoft is going to have about 30%.
1:00:17
OpenAI employees are going to have close to 30%.
1:00:19
OpenAI, the nonprofit, is going to have uh 20 to 30%.
1:00:25
>> But that doesn't mean you shouldn't still donate.
1:00:26
If you're thinking about doing some charitable giving this holiday season, consider writing a donation to Open AI, the nonprofit.
1:00:34
Prioritize tipping your cap table first. >> Yes.
1:00:37
>> And then after that, consider donating to OpenAI the nonprofit.
1:00:41
>> Uh but anyways, Microsoft at 30%, >> OpenAI employees around 30%, OpenAI nonprofit at 20 to 30%, SoftBank about 10% and the remaining is is uh Thrive, Kla, MGX, and a number of of uh bedrocks in there. Um yeah.
1:00:57
>> Um but >> I wonder how accurate that reporting is.
1:01:00
It feels like directionally correct.
1:01:02
>> I think it's directionally correct.
1:01:02
I wouldn't, >> but there are some pretty big error bars on either side. >> Yeah.
1:01:06
>> Um, but still, I mean, you you just look at some of these like some of these numbers that we pulled up.
1:01:10
It's like, uh, you know, what was the original OpenAI deal?
1:01:14
Uh, it was that Thrived did, it was at a 27 billion uh 130 million at 29 billion. So, 2900 Z.
1:01:22
So, that initial deal was uh half a percent of the company, right?
1:01:30
And that was like and that was like a whole round.
1:01:32
And so that was a very low dilution round even at that time. >> Yeah.
1:01:37
What what's what's notable is like looking at this kind of rough cap table.
1:01:42
Uh it's just astonishing to end up in a situation where VCs have the lowest ownership out of the employees, a nonprofit, a strategic partner.
1:01:52
Softbank kind of makes sense.
1:01:55
But uh but yeah, >> it's all hands on deck in the chat trying to find France, too.
1:02:00
Thank you for everyone's service.
1:02:02
It seems like they're they're making progress using VPNs, all sorts of stuff.
1:02:06
Uh >> Daniel says, "What's a good number to tip your investors?
1:02:10
20% of the last round or is that too much?"
1:02:14
>> I think more like like 2% of the last round is feels they'll they'll feel very appreciated.
1:02:19
>> But it's got to be delivered in in a sports car form. It can't just be cash. Uh for sure.
1:02:23
Uh, let's read this Jeremy Gon post.
1:02:26
Uh, things that seem true about AI today that will probably be laughably wrong in a year.
1:02:32
Uh, one, it still seems underrated that chatbt has replaced 85% of my Google usage and has become a mostused app.
1:02:40
That's certainly true for me.
1:02:42
The reason we're so upset about slop is because it's obvious we're all going to love consuming it in two to three years.
1:02:48
It's not going to be slop for long. >> What do you think?
1:02:51
I yeah I mean there's out of the out of the hundred sore you know maybe maybe way more than that right call it a thousand Sora videos I've seen one way or another like 10 of them have genuinely been hilarious >> and that is about the same ratio as like the regular internet right see a thousand videos like yes some some of them are going to be Um, but but I I I think uh already there's there's I'm seeing instances where it's not slop.
1:03:29
Still using the Sora app >> is not I I don't love it, >> but some of the outputs are are >> I like it as a creative tool.
1:03:37
Like I I think that if you just view it as a creative tool, there's going to be creative uses and stuff that's amazing, even if it is a little sloppy.
1:03:44
Uh the other lens to view it through is like uh Buzzfeed was creating a lot of kind of slop content but with humans and that never really broke through and became something that a lot of people at least in my world enjoyed.
1:03:58
It kind of remained slop forever and um but but as AI generation as a tool like you you saw over the over the weekend I was having fun in our group chat generating a Sora video sending it there.
1:04:10
I didn't even post it, but it but the result was really funny in the context of our friend group.
1:04:16
And so I think uh I think Jeremy's right there.
1:04:18
Um number three, he says, "Many non-AI products are being adopted due to economywide corporate and capital market top-down mandates to buy fund AI.
1:04:28
A rare reversal of the norm where everyone wants to turn over their existing vendor for the new one.
1:04:33
This will have a similar pull forward effect as e-commerce during COVID.
1:04:37
even if AI ends up being way overstated.
1:04:40
And so right now some of the booms that we're seeing, some of the ramps in these companies going to 100 million is just that the entire Fortune 500 and we're going to get into this with some of the open AI partnerships.
1:04:52
Uh the entire the entire Fortune 500 is saying like CEO, you need to have an AI initiative or else you're gone.
1:05:00
Like you can't be sitting out AI even if you're even if you're Walmart, for example.
1:05:04
Um maybe Walmart should get on profound.
1:05:07
They could get their brand mentioned in Chachi PT.
1:05:10
They could reach millions of customers who are using AI to discover new products and brands.
1:05:14
Uh so uh Jeremy continues >> by the way. Yes.
1:05:17
Uh >> uh best diff in the chat did send me the video of us on French television. >> Nice.
1:05:25
>> Uh I cannot download it cuz X does not apparently allow you to download videos.
1:05:31
Uh so I asked him to send it to to Ben's email uh so that we can pull it up on the show.
1:05:36
>> We will we will work on that. >> We are working on it.
1:05:39
>> Um so Jeremy goes to his specialty uh how companies are using AI.
1:05:44
He says AI rollups and vertical AI.
1:05:46
I've yet to see any part of a business unit that can reliably have cut cost cut or revenue grown with AI.
1:05:53
That's very interesting because the that the the the narrative we've heard this from a number of private equity folks who are saying like I'm going to buy a company throw AI on top and cut costs in this division or grow revenue in that division.
1:06:07
And >> even even soft even >> again uh software engineers at a company if maybe they haven't been using AI you come in you're bringing like fire to you know you're like here look fire it's magical fire um >> there's something about there's still an art to it >> yeah here's potentially why you should still be bullish on on AI rollups is because you take a bunch of >> smart tech people Yep.
1:06:35
and you bring them into businesses that haven't historically had a lot of great technology and they just built great software, it's possible to grow businesses faster, be more efficient, things like that, even if AI isn't actually doing the heavy lifting. Yeah.
1:06:52
So when I've talked to like a rollup founder and I'm thinking you know they've pulled together in this case they had pulled they had pulled talent from like five of the best companies in in the world at least from from from a talent density standpoint and they're they're working in these categories.
1:07:08
I won't name it because I'll I'll I'll dox the company but they're working in a category that never in history had t super talented engineers working on it. Yeah.
1:07:18
And so they're probably gonna do really well even if again it's not like integrating an LLM into the workflow that's actually doing that heavy lifting. Yeah.
1:07:25
So >> yeah, I mean that's >> it's possible that like Yeah.
1:07:29
>> He says companies can ship a lot more software quickly.
1:07:32
Complexity of the buildout is no longer a moat which I think is interesting. Revenue velocity. >> Yeah.
1:07:38
But so the only thing is this kind of contradicts the >> No, no.
1:07:42
So, so one is is it's hard to just go into a business and say, "No matter what your business is, I know that I can come in and drop AI into your manufacturing process or your customer support department or your finance operations department and or your sales department and immediately see a result on cutting costs and increasing revenue."
1:08:06
Like, it's not a reliable playbook. every company.
1:08:10
>> Yeah, but I'm just saying he's saying companies can ship a lot more software quickly.
1:08:12
Complexity the buildout is no longer remote.
1:08:14
So that would you'd buy a platform software business that has a bunch of other products that you want to build.
1:08:20
And if the second point is true, you could just let go of a lot of the engineering team and say we're going to cut >> we're going to cut or we're not going to we're not we're going to change our >> our uh hiring plan because we just don't need as many engineers and you can grow revenue while like keeping your costs relatively the same, right?
1:08:36
So >> yeah, but at the same time like like that software that you launch will be more competitive because there's no longer a moat around the complexity of the buildout and so you wind up with a more commodity product at the end of that buildout and so maybe the equilibrium is that you don't actually grow revenue that fast. I don't know.
1:08:52
It it does seem like it's a very case by case basis basically like everyone wants to paint with a broad brush and just say that like every company will be transformed by AI, every company will will grow with AI.
1:09:02
Uh but it's it's it's clearly like like more more nuanced than that. >> Yeah.
1:09:08
>> He says revenue >> he's also saying margins and headcounts do not yet reflect the narrative around developer productivity.
1:09:13
What I would say here is that if your developers get a lot more productive, >> you might actually want more >> developers, right? >> Yeah.
1:09:24
Because like if a developer can produce three times as much valuable code, if you agree with that, wouldn't you want to grow your engineering team?
1:09:33
Yeah, I mean there is an equilibrium like there is like a game theoretic equilibrium where where if we're direct competitors and I give all my engineers AI and you give your all your engineers AI like we both have to employ the same amount of engineers to compete with each other because if I fire all my employees and I'm just using AI and you >> they're just going to outship you.
1:09:59
you're you're going to outshit me because you have AI and humans and you're double important, you know.
1:10:02
And so >> this is another point here says PE and VC ironic and ironically VC have not found a way to adopt AI internally.
1:10:09
I asked a lot about that.
1:10:13
>> Um and uh yeah, he he I mean I think he generally agreed. >> Yeah.
1:10:19
I mean certainly for like uh research I would imagine that they've they've adopted that just as like a replacement for Google like like Jeremy's first line like you know replacing uh Google search knowledge retrieval that type of stuff AI uh is certainly is certainly a good point.
1:10:34
Um but yeah I mean it's not like you can just say hey go find me a the next unicorn and yeah don't make mistakes.
1:10:42
Um, where AI has created a lot of value is by being the missing puzzle piece for existing businesses usually around this is usually around onboarding, migration or database querying.
1:10:50
Oddly, I can't help but feel that at its core that its core quality is just that it makes everything much faster.
1:10:56
It feels as though the microprocessor, blockchain, and AI have all been these pushes away from clock time towards newer, faster standards, standard measure of times.
1:11:06
I'm not that optimistic, but it does feel like there's a chance for the first time that we could get entirely away from the ad model, taking shots at ads.
1:11:13
How dare you post from the ad supported platform? >> Yeah. >> X. com. >> Yeah. Uh I don't know.
1:11:19
Um I mean, it does seem like it does seem like Chat GPT is going to monetize pretty heavily on the subscription side and then also on the referral uh affiliate revenue side.
1:11:31
Um but they're creating a ton of surface area for ads and I think that there will just be ads. though.
1:11:35
I disagree with that one.
1:11:36
Um, anyway, speaking of ads, Google AI Studio, the fastest way to prompt from prompt to production with Gemini.
1:11:43
You can chat with models, you can vibe code, you can monitor your usage, they got Nano Banana, you can talk to Gemini live. Go check it out. >> Go to ai. studio.
1:11:55
>> Um, post from Hypebeast.
1:11:55
Apparently Tim Cook now has his own custom Leubu complete with an iPhone 17.
1:12:00
I think that's in orange.
1:12:03
I didn't realize they made custom Laboos, but I mean, what what a great uh >> What do you think Tim actually thinks about Laboo?
1:12:13
>> Um, >> he doesn't look that happy there.
1:12:13
It's kind of a forced smile. >> Yeah, I don't know. What?
1:12:17
There's been a few photos of his office.
1:12:21
You remember those the the that viral video, the viral image of like this was Steve Jobs office.
1:12:27
This is Tim Cook's office and Steve Jobs office is all messy and Tim Cook's office is all clean and it's like supposed to be a referendum on the different leadership styles of the two CEOs.
1:12:36
Uh but of course people made the point that uh that picture that iconic picture of Steve Jobs his his office was in fact his home office and we haven't seen Tim Cook's home office so it might be equally messy and Steve Jobs uh work office might have been equally clean but uh in that photo shoot of Tim Cook's work office it did seem very clean.
1:12:53
It didn't seem like it had a lot of chachki or trinkets or uh I don't know.
1:12:58
I don't even know where you'd put Leoooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo in there.
1:13:02
But he doesn't seem like someone who's been uh collecting Pokemon cards and is just ready for the next thing to collect.
1:13:08
Uh but it's certainly a fun >> fun uh fun drop for uh Laboo.
1:13:11
And if you're building a company, you should make a Tim Cook version of your product and and send it to him and get a free uh free ad out of it, I suppose. Who knows? >> Uh I breaking news.
1:13:23
I want your reaction to it, John. Your authentic reaction.
1:13:28
John has not seen this post yet.
1:13:30
>> Breaking Open AAI to partner with OpenAI to help fund OpenAI. Open AAI up 90%. >> I that sounds real. >> It's not.
1:13:39
It's a uh it's a uh post.
1:13:44
>> I know that uh I mean I know that they had crazy amount of partnerships just this week.
1:13:47
I mean the bro thing we'd heard about and then they went bigger.
1:13:51
Jerry Capital says, "This is how you top and it's Walmart partners with Open AI to create AI first shopping experiences."
1:13:57
Uh, this makes a lot of sense.
1:14:00
>> Netcap girl said, "I in case of emergency, break the glass."
1:14:02
It's an open AI partnership.
1:14:04
>> Well, of course, uh, Salesforce announced a partnership with OpenAI this morning. Yes.
1:14:09
And uh, they people were memeing it because the the trade didn't >> the stock trade down on it. It's crazy crazy.
1:14:15
And then High Yield Harry says, "Say the line, Bart.
1:14:17
We're partnering with OpenAI and so Salesforce and OpenAI just announced a partnership.
1:14:23
It's a kind of partnership that will let companies across Salesforce agent 360 platform in chat GPT quering sales records.
1:14:31
I mean it all makes sense to integrate it.
1:14:33
It uh what's interesting is that at one point Salesforce was building their own foundation model and seems to have you know backed down from that a little bit.
1:14:41
Mark Beni off said uh back in 2023 which I believe was the coup, right?
1:14:46
This is right around the coup.
1:14:47
Um, so this was this was when uh OpenAI researchers were leaving uh and there was there was news that Sam might go to Microsoft research and bring a bunch of people there.
1:15:00
>> Yeah, that was like over the weekend.
1:15:01
>> Over the weekend, right? It was really crazy.
1:15:03
And Mark Beni off was like, "This is my Zuck poach moment.
1:15:05
I can poach all these folks."
1:15:08
Uh he said Salesforce will match any OpenAI researcher who has tendered their resignation full cash and equity OT to immediately join our Salesforce Einstein trusted AI research team under Sylvio Sarvisi.
1:15:20
Uh send me your CV directly.
1:15:23
Uh Einstein is the most successful enterprise AI platform completing one trillion predictive and generative transactions this week.
1:15:31
Join our trusted enterprise uh revolution.
1:15:35
High yield Harry says this is hilarious in retrospect.
1:15:37
Um, yeah, I it it's like it needs to be the main thing unless you're Google and you invented the transformer.
1:15:43
Like everyone else needs like a partnership.
1:15:45
And so, uh, Amazon's fortunately in a good spot with Tranium, but they still have to partner.
1:15:48
It doesn't seem like they've been able to really keep up in the foundation model race.
1:15:53
It's it's becoming like a triop between O OpenAI, Enthropic, and uh, and Gemini, and everyone else is kind of dropping out.
1:16:02
Although we do have new new uh uh some new uh information from biology about the Chinese models and what's going on in the free AI model world on Ella Marina.
1:16:11
Uh it's been back and forth between Meta, Deepseek, Alibaba and now Z. AI is in first place.
1:16:19
Uh and they've all been uh uh you know going back and back and forth.
1:16:23
Uh it's knockout dragout bite.
1:16:25
How each organization's best openweight model ranks on Marina Z. AI AI is now. >> Yeah, great domain. >> Not a. com, but still solid.
1:16:34
Um, before we move on from Salesforce, I think we can we can leak that Mark Beni off will be on the show on Thursday joining >> TBPN at 12:15. You heard it here first.
1:16:48
>> That'll be an interesting discussion to understand how he's thinking about build versus buy in the AI era.
1:16:52
There was definitely a time when it made so much sense to say like, well, I don't want this company to train on it. I have my own system.
1:17:00
It's not that expensive, but now it's extremely expensive.
1:17:03
And OpenAI offers an enterprise plan where they won't pull your data back into their training runs.
1:17:10
And so you can use all the best OpenAI models.
1:17:12
Uh they will serve them, Sam Alman's problem, to provision all the GPUs.
1:17:16
You're you're even better than being a renter because you're just a token buyer.
1:17:21
And so there's very little risk of, oh, if you, you know, oh, we, you know, we overshot this AI thing.
1:17:28
Uh, we'll just scale back your token consumption and all of a sudden your economics go back to what they were before at the AI boom.
1:17:34
So, it's a very safe place to be.
1:17:36
So, >> with this video, >> let's pull up uh >> French TV, baby. French TV.
1:17:39
Oh, this is uh this is the studio, not with >> this is very cool.
1:17:45
Do we have audio on this?
1:17:48
>> I want to hear some French TV.
1:17:48
They're really filming us all.
1:17:53
>> We didn't get any We didn't get any audio. >> Audio. >> Okay. Odd.
1:17:55
Well, we wouldn't be able to understand it either. Oh, look. Here we go.
1:17:59
>> They're calling you a >> an expert in artificial intelligence. Yep.
1:18:03
This is the first trading card.
1:18:03
I remember being at breakfast and uh Tyler described that idea and it absolutely ripped. We had a couple others.
1:18:12
What was really funny about this was that the the interviewers kept asking us like okay so for this trading card like how much did that person make personally and we're like look like like it didn't exactly leak like that.
1:18:24
It was a more of a general thing.
1:18:26
There were some leaks of specific deals but they're a lot of them haven't been confirmed like uh we're more just uh you know having fun with the overall trade deal narrative.
1:18:34
We can't really even clock a particular offer within an order of magnitude.
1:18:39
Um, but >> well, we got to find out how to get the audio. >> Yeah, we do.
1:18:44
Um, oh, there was audio, says Fannis.
1:18:47
So, we will figure that out.
1:18:49
And, uh, >> and now there.
1:18:51
>> Now, without further ado, we have our first in-person guest of the show. Welcome to the stream. How are you doing? >> Good to see you.
1:19:02
>> Get to stand next to you. See what it feels like.
1:19:04
Welcome to the Ultra Dome.
1:19:06
Hopefully uh you're you're looking cozy in that in that sweater.
1:19:09
Hopefully you're enjoying the the rainy day in Los Angeles.
1:19:13
>> I was told come to LA. It'll be nice. It'll be warm.
1:19:15
And >> it's only it's like 300 330 days a year.
1:19:21
>> It feels very warm in here.
1:19:21
It's actually more of a neutral temperature.
1:19:24
But uh through the power of movie magic, it appears that we are in front of a warm heart.
1:19:30
>> Anyway, please introduce yourself to the stream. >> I'm uh Henry Stern.
1:19:33
I'm one of the co-founders of Privy.
1:19:34
We build embedded wall software.
1:19:37
I was told to come here to help translate the French television. I'm French originally. I watch uh France.
1:19:45
>> Are you a France 2 fan? >> I'm a a France 2 fan. >> Is France too fan?
1:19:49
>> France 1, two, three, four, five.
1:19:49
I think it goes into the 40s.
1:19:51
If I >> We're working on on iterations at this at this point in time politically and uh and I think uh TVPN is is welcome respite for uh for all French political watchers out there. >> That's fantastic.
1:20:03
Yeah, it was fun uh telling the story of what happened over the summer.
1:20:07
It felt like flashback because the AI talent wars I'm sure you tracked them like in real time uh in July getting acquired.
1:20:16
>> You were busy but still I mean I'm sure they broke through to you and you were aware of we saw these you saw it of course.
1:20:21
Um and everyone's wondering like hey what what's my comp package going to be next year?
1:20:24
Well, we we so we normally don't do uh life stories on TVPN, but when did you actually >> uh when did you leave France, assuming you grew up there?
1:20:34
>> Uh I grew so I grew up uh there till I was like 12 or 13.
1:20:37
Then I came to the US, which is how I shed my accent to some extent.
1:20:42
>> Yeah, it's barely I don't even notice it.
1:20:44
>> Um and and got very Americanized.
1:20:44
So I'm a I'm an American uh person in so far as startups are concerned and I'm a French person in so far as like you know voting, passports and food is concerned. >> Sure. Sure. Makes sense.
1:20:55
>> Uh give us give us a playbyplay of the last few months. It's been busy.
1:20:59
>> Uh it's been very busy.
1:20:59
Um well there's like two parallel worlds.
1:21:01
On the one side there's uh we we got acquired by Stripe.
1:21:05
So um we had uh the great folks at Stripe reach out.
1:21:07
I think you ganged us already.
1:21:10
I'll >> second gong because you closed >> uh retroactive gong.
1:21:16
>> You got to hit one for closing, one for the announcement, one for closing course.
1:21:19
uh and and basically so they they reached out in in around April.
1:21:21
Um that's pretty quick and went through really what was a very very fast uh time.
1:21:29
So huge shout out to to the M&A team over there and and frankly to uh the entirety of >> But had you not had you not talked surely you >> you' never heard of Stripe before that?
1:21:38
>> I didn't know what it was. No I I um No.
1:21:41
So obviously we knew Stripe and and frankly a lot of how we shaped our company and the way we wanted our product to work was based on what we saw Stripe doing.
1:21:47
We'd had talks with their crypto team and in general and we did a lot of work with the team at Bridge uh through joint customers that we serve together >> and the outreach was some version of listen we think wallets as uh distributed global bank accounts are an extraordinarily powerful primitive to have as part of the stack that we're hoping to serve.
1:22:07
>> Yeah, >> we'd love to talk to you about this the way that the way these work.
1:22:08
Um, so we had a conversation and it very quickly led to to where we were and I think we we talked through what would it take for us to be uh excited beyond the general excitement of Stripe about like joining forces.
1:22:20
What would it take for us to accelerate?
1:22:22
>> Um, and uh and we got there and then you know to their credit we moved really quickly.
1:22:26
So by uh by May we were uh signed with a term sheet by uh I guess mid June we announced and uh and we closed in July. >> That's correct. >> Uh >> yeah.
1:22:37
How how uh what was the pitch around like synergy?
1:22:39
Was it obviously they're well capitalized so you don't have to go out and raise anymore.
1:22:43
They have a huge customer base of people who have saved credit cards through Stripe Link.
1:22:49
Uh but then they also have a bunch of merchants who have done developer integrations with the API.
1:22:52
Like what stood out to you as like the most important piece and what was maybe less important than people might think?
1:23:01
>> Yeah, I I think there are two parts to it.
1:23:03
The first is how do we get this tech to mainstream?
1:23:07
How do we get it to customers who otherwise don't care about crypto whatsoever?
1:23:11
And one of the things Stripe has been excellent at is basically hiding the rails behind, you know, extremely complex infrastructure. Exactly.
1:23:19
And you take these like you know hundreds of banking partnerships, you turn them into an API that just works and you enable, you know, in their case like >> commerce on the web for the last 15 years.
1:23:28
And the question is as this stack evolves, how do we do the same for crypto?
1:23:32
So that felt like very natural.
1:23:33
But I think for us the point was one it is uh being able to strengthen our teams across security infra and obviously across distribution to customers we wouldn't be talking to otherwise.
1:23:43
>> Um and two being able to plug into money money movement rails like making it that fiat and crypto are married to the point where they become indistinguishable from one another and where as a consumer of this API you no longer have to think about one versus the other.
1:23:56
So I think the the way I look at it is broadly we have two prerogatives.
1:23:59
uh if stripe is AWS for money then this is a rail they should be uh leveraging and they are intent on leveraging and building up uh this is why they acquired bridge.
1:24:08
This is why they acquired us and broadly we want to be the best purveyors of money movement and storage systems on the web so that you can build completely global businesses uh on modern financial rails. That's one. >> Yeah.
1:24:23
>> And then two is beyond the tooling that we provide.
1:24:26
Can we make it that every existing Stripe user today can benefit from these rails so they can provide you know cheaper faster global payments and they can enable anyone to hold dollars anywhere in the world.
1:24:36
>> How do you think about the modern onboarding of the consumer?
1:24:39
Um going back to maybe 2021 2022 the way people would start I mean a lot of people were on centralized exchanges like oh I want exposure to Bitcoin or something.
1:24:54
I'll go buy some and I'll go through the setup flow and KYC and whatnot.
1:24:56
And then uh the wallet era I felt like started with um NFTTS, different tokens that were sort of like getting traction on on Twitter.
1:25:04
People would talk about them and then you'd have to be oh well to buy this I got to set up this this wallet.
1:25:09
I have this specific wallet for Salana or I have a specific one for Ethereum.
1:25:12
Um and and people it was very it was a very like proumer activity.
1:25:17
How do you think it evolves to a more consumer world uh going forward?
1:25:23
going forward? Is it like >> well my my my framework is there's the speculation era people are signing up for different services to speculate but I think what you had seen probably >> prior to starting the company is that eventually there would be this like more
1:25:37
functional use case of like I'm going to sign up for products in general for specific purposes whether it's to buy things you know you know pay >> you think start with signing up or will it be like PayPal where it's like I get an email and I'm like I got to go claim that and then I set up the wallet. I
1:25:50
I think there's going to be two and true.
1:25:53
I mean, broadly what we're seeing, so to your to your question of like, you know, what what's been happening these last few months, there's obviously what we've been doing at the the preview level, the stripe level, but then there's the space overall and the amount of institutional adoption that's coming.
1:26:02
And I think we broadly see it on three fronts.
1:26:04
We see crypto as an asset class.
1:26:06
So, how do you unlock basically access to these assets for traditional uh consumers?
1:26:11
And you see it through, you know, JP Morgan giving access.
1:26:15
You see it through I think Morgan Stanley is going to unlock spot trading on Erade.
1:26:18
uh you see it through we're working with uh Deutsche Bank um uh uh JV called All Unity on a European stable coin for support.
1:26:29
Um, so broadly that's that's the the first part >> and quickly there.
1:26:33
So someone has a an account with a bank that has a brand that's probably been around for 50 or hundred or hundreds of years and and that particular web app or mobile app is like provisioning a wallet for them that they might not even know that is provisioned for them.
1:26:52
Is that how you think that plays out?
1:26:53
think that plays out? I think we're see I mean this is I think where it leads to start I guess the the the the the broadly there's access to the asset class there's obviously stable coins and global distribution and the last is you know overall >> tokenized assets beyond you know things like tokenized equities or tokenized deposits is where you see players like
1:27:13
you know Apollo or Blackstone getting involved and the way we're seeing this develop is you broadly have a move from cryptonnative startups to fintex and so what you just talked about is exactly what's happening with Neo Bank stack and a number of NEO banks that we're seeing provision wallets exactly as you're saying it which is as part of your traditional Neo banking app. You'll have
1:27:29
You'll have the ability to move your checking deposit or balance into a wallet that you control through which you can get for example uh yields on DeFi in a way that as interest rate go down becomes more interesting.
1:27:42
more interesting. So that'll be phase two to then >> right now if you want to buy Bitcoin on Erade for example like you buy the ETF which is like a very abstracted like multi levels of abstraction it's not even self-custody and so yeah okay that that's break down maybe what's what are the institutions focused on like what
1:28:01
are the kind of the categories they're focused on so one would be stable coins hey the these are going to be big we want to have a play here so whether that's uh leveraging them in the business or launching their own stable coin is There's opening up access to crypto markets to their users are another one. What are kind of the other maybe are you
1:28:18
What are kind of the other maybe are you thinking about uh less like sexy use cases for crypto like things like back office stuff or is that more on the bridge side of the business?
1:28:29
>> Um it's a great question.
1:28:29
uh we are in so far as basically setting up you know you can think of a wallet in this in this new instantiation where the wallet is just this embedded product that sits within your existing stack as a way to do broad treasury management.
1:28:42
So bridge you know is working for example with SpaceX on remittances across uh SpaceX's global operations >> uh but you know this is a random example but you can imagine uh a company like Coca-Cola who is bottling plants all over the world needing to have capital put to work and so this is where the wallet stack becomes useful.
1:28:58
Um, broadly it breaks down largely as you've said it, which is to say it's uh access to crypto as an asset class.
1:29:04
It's stable coins and that's on two fronts issuing the own and you know for example stripe and bridge have uh launched open issuance where you can actually launch and own the economics of the stable coins that you're putting forth but broadly we're seeing a lot more people starting to do this um as well as using stable coins for things like uh remittances and payroll.
1:29:23
We you know see folks like deal or remote that are doing stable coinbased payroll.
1:29:27
We see folks like Zeps, Remittly, Felix who are doing uh remittances using stable coins.
1:29:32
And then the third is uh broadly trying to see can we open up tokenized deposits and other things to uh financial markets globally through uh crypto.
1:29:45
So this is where I think the the Apollo of the world are playing and want to become in a sense like you know lenders on chain for folks across the world who have not had access to to to private credit.
1:29:55
So if I'm if I'm a contractor for SpaceX at Quadrilen ATL or something and I don't have USD or I don't have a USD uh bank account, SpaceX HR effectively or financing might send me an email, hey sign up for this to claim your, you know, your payment, your payroll, and it's just a stable coin wallet.
1:30:16
They provision the wallet right then. >> Exactly.
1:30:19
I mean, >> and then they have it and they can move it where and then they can interact in crypto, but then they'll also be able to move it outside.
1:30:24
In the specific case of the the SpaceX bridge work, I think it's used for internal treasury operations.
1:30:29
But that's exactly the sort of thing that we're seeing coming. Exactly. >> Got it. That makes sense.
1:30:33
>> That goes back to your question of, you know, how are people going to get wallets in the future, 2021, 2022, you have to be this proumer.
1:30:37
You have to be extraordinarily sort of >> high activation energy of I want this and I'm going to self- select into this.
1:30:44
Um, I think we're going to basically just start seeing myriad of ways in which this starts to bleed into your life as a participant in global financial markets and that's how you get into >> Do you think it's uh do you think there's how many fewer crypto companies are being started today than in than in 2021 2022?
1:31:01
Is it is it like uh I could imagine it's like 20% as many even though there's a bigger >> more than ever.
1:31:08
I feel like >> but but but here's the thing.
1:31:10
I mean, I feel like I feel like crypto crypto uh this should be the excite most exciting moment ever in crypto history, right?
1:31:19
All the institutions like it's not just like the Robin Hoods coming in and saying, you know, we're going to add support for Bitcoin.
1:31:24
It's it's the biggest financial institutions in the world. Yep.
1:31:28
>> And yet there's less it feels like less excitement from like look at the YC batches.
1:31:33
You would think you would think a YC batch would be like 50% crypto right now given the institutional opportunity and now regulatory clarity and all these things.
1:31:42
So, it's really great if you're if you're privy or bridge or or you're you know some sort of established crypto company because you're not getting that that it doesn't feel like you're getting the same influx of of new competitors even though the opportunity has never been more obvious or bigger.
1:31:56
I mean, I I you know, I think we had to eat for a few years to to get here, which which which I think speaks to it, but you're right.
1:32:03
I mean, from my standpoint, the EV of starting a company right now related to, you know, crypto or stable coins or or I wonder to what extent, by the way, just fintech and crypto are going to become one and the same and indistinguishable, >> but uh but the EV as compared to some of the competition I'm seeing in AI, for example, is absolutely wild.
1:32:21
So, I do think it's fewer than in 2021.
1:32:24
Probably at least 50 to 70% fewer that I'm seeing.
1:32:29
But the fun thing is I'm I'm here in LA for an event for partners of ours called LightSpark that have a Bitcoin L2.
1:32:34
And at the event uh they're presenting the work that they're doing with uh SoFi, there's folks from Apple, Meta, like everybody is actually paying attention to the opportunity and coming in.
1:32:44
So, I think the next 18 to 24 months are going to be incredibly high leverage.
1:32:49
And I think we'll look back and we'll have the same conversation, call it in 2027 and say, you know, it was so quaint in, you know, late 2025 when we were talking about distribution starting off and so on.
1:33:00
>> How how long until the average bank account in America when you want to send a payment, you're getting a drop down like do you want to send a wire?
1:33:06
Do you want to send a stable coin payment?
1:33:07
It feels like that might be two years, three years away.
1:33:12
But how quickly are the institutions actually now that there's regulatory clarity, now that it's sort of fair game, how quickly can they actually adopt?
1:33:19
I mean on on pace of adoption, the reality is extremely fast.
1:33:25
The rails are actually a lot of the rails have been tested.
1:33:27
I think this is by the way where a lot of the crypto native usage for trading and for speculation has proved useful for the financial rails and that it's helped harden the financial rails and then you have things like uh tempo uh getting started for you know payment specific use cases to enable uh you know stripe level uh payments utility on blockchains.
1:33:46
Um so the TLDDR is I think it the rails are ready the places where work will have to be done is on the last leg of distribution uh for global payouts.
1:33:56
So, banking partnerships on the ground in various countries where you'll want to move back to fiat, but this is where, you know, I'm going to keep plugging away my my Stripe things, but obviously Stripe's doing a lot here.
1:34:05
Uh, this is where, for example, Bridge and Visa are working together and you see the card issuers uh moving into providing this.
1:34:12
So, you could pay out in stable coins using a card directly rather than needing to move back to fiat via your banking partner on the ground.
1:34:18
So, yeah, >> I I think we're going to see a lot of pressure from neo banks >> pushing traditional institutions to pick this up.
1:34:24
And I don't think your two-year timeline is crazy at all. I think it'll be one.
1:34:29
>> That's why that's why it's wild that there's so it it feels like there's massive reduction in new crypto uh company formation at a time when the entire mar like every key partnership will be like decided in the next like two to three years.
1:34:44
two to three years. The the other interesting point this was like you know crypto cope circa 2022 but it was like you know crypto is the only net new technology AI serves the incumbents because you have data and distribution modes and I actually think stable coin changes that because stable coins uh
1:35:00
play to the strength of existing networks distribution modes and so on and so forth and so I think the shape of crypto companies that will become valuable is also like not obvious which is a really good opportunity and interesting time to start something >> what uh What regions or countries specifically are most hostile to crypto adoption today? I assume like North
1:35:19
I assume like North Korea, Russia, uh, uh, countries that already have, you know, intense capital controls, but >> yeah, I mean, there's probably a joke about North Korea somewhere in here in terms of crypto hostility.
1:35:31
They certainly do a lot of crypto work, unfortunately, uh, in terms of cyber security.
1:35:37
>> But, um, >> did you I'm sure you got a bunch of applicants over the years.
1:35:40
>> We're all in person, which helps >> tremendously. remote.
1:35:42
It was always the remote North Korean engineers.
1:35:46
>> There was a there was a computer scientist from Caltech who went to North Korea, smuggled himself across the border from South Korea, gave a talk on Ethereum as like a way to kind of move money, not maybe above board.
1:35:56
And and he went to jail because Virgil, I forget his last name, but I know I know exactly what you mean. >> No.
1:36:04
>> No. So, so the honest answer is um the way you'll see it is there's a lot of adoption today in LA latam and parts of I mean obviously Europe and the US but the opportunity is quite different there because the stable coin opportunity where the pitch of you know just hold dollars
1:36:21
>> is a little bit different if you look at tether tether keeps 100% of its yield which speaks to how valuable holding a dollar is if people are willing to make no money on top of their sitting balance so >> uh >> so is that why there's so many stable coins is this like like it feels like we we had like a few dominant winners. It
1:36:36
It felt like it was going to be maybe a duopoly or like power law winners were going to happen.
1:36:42
And then I hear stories about like uh the state of Montana is going to launch their own coin and I'm like do like I I I kind of like the idea of just one standard, but I I don't know enough to really make that argument beyond just like it would be nicer if everyone used the same dollars.
1:36:53
I think we'll probably see two things which is one a broad like mesh of interconnectivity under the hood so that your coin for every single place you launch it.
1:37:03
So again you know bridge worked with phantom to launch cache they're working with meta mask you'll be able to interoperate between them without having to think >> uh but on the flip side which ones will have a brand y >> um is going to be a separate question.
1:37:17
So in so far as like stable coins are products, they are programs. They can be programmed.
1:37:20
The way in which yield is managed, the uh way in which you put those underlying sort of collateral assets to work, all of that is configurable, which is why it makes sense that you'd have a proliferation like economic entities should be able to own how their balances are held and and managed.
1:37:36
>> Uh but the actual rails through which you you know plug all these together will make it seamless. >> Yeah.
1:37:40
What's the what's the headline KPI that the stable coin industry is obsessed with?
1:37:43
I remember during the bitcoin era everyone was talking about like number of bitcoin wallets or number of people that have have have bought some bitcoin and there was like oh eventually everyone will hold a little bit and that's will drive the value.
1:37:53
Uh are you looking at like number of wallets, number of transactions per user, DAUs, MAUs?
1:37:59
At what point do you is it is it worth tracking how many bank accounts are created daily globally versus how many wallets because I imagine that will flip at some point but maybe that's not the right >> it may have already even flipped in so far as there's an issue of civil resistance which is it's you know costless and instantaneous to create a wallet and you can do so very easily.
1:38:17
So that's part of the value but obviously it means that you'll get a lot more noise in that in that data. Yeah.
1:38:22
Um, I think today the obsessive sort of stable coin metrics are uh volume moved.
1:38:26
So that we're moving I think about $5.
1:38:29
3 trillion of stable coins annually at this point as well as aumumumumumumumumumumumumumumumumumumumumum how much collateral is locked up in stable coins and last I checked I think we're at about 300 billion.
1:38:42
>> Do you have a comp for that uh that transaction volume?
1:38:44
Because the bitcoin folks would always say like uh well gold is 10 trillion.
1:38:48
You think about as digital gold like maybe it'll comp there.
1:38:51
Uh, but when I think about like the amount of money that's moved, you'll hear about like one highfrequency trading firm is moving five trillion because they're just like trading a billion dollars back and forth every second.
1:39:02
Uh, like what is the actual pie?
1:39:05
Are we talking like quintilions of dollars a day floating around or something?
1:39:09
Like is it so high that we're like very early or is five trillion actually like a meaningful chunk?
1:39:13
actually like a meaningful chunk? No, I think these are just the starting days and and to your point that the metric I'd love to invite by the way is open data by the folks like Visa, Mastercard, Stripe to actually show how much is going to end users through payments rather than potentially you know uh trading that's happening that has less
1:39:29
of an impact on uh consumers but um you know in an agentic world >> where ostensibly most commerce will happen via automated means this is you know something stripe is very focused on >> but it stands to isn't that a like natively digital payment method will be the choice way through which agents actually get to purchase goods and pay each other. So imagine now not just
1:39:51
So imagine now not just every bank account has a wallet but every agent has a wallet and that can be used you know on Jord's behalf to pay for something with you know some cap every day that you set for it.
1:40:01
Um >> Thompson was talking about the MCP hopefully the future MCP standard has crypto in there stable coins. >> Exactly.
1:40:08
just as a payments method.
1:40:08
And so I think we're just scratching the surface because the the denominator is not just global payments today.
1:40:13
It is global payments in an agentic world where most money movement comes online. >> Yeah.
1:40:18
And it feels like that's coming very very soon.
1:40:20
I mean Fiji Simo has telegraphed it with OpenAI and like there's a ton of startups that are working on this stuff. It makes a ton of sense.
1:40:26
>> Is talent the primary constraint for you guys right now? >> Yes.
1:40:30
Uh I'm I'm trying to come up with a pathier answer.
1:40:32
The the sort the short answer is yes.
1:40:34
I think Stripe has been a major accelerant to our work.
1:40:36
We're, you know, working with a lot of customers.
1:40:41
Patrick and John just firing off like I'm going to fire off like 10 intros right now and it's like, you know, the most significant financial institutions in the world and it's like good luck.
1:40:51
>> Just sending sending you the blog post fast and being like we'd love to add you here. >> So, keep going.
1:40:58
>> Uh, no, I mean this is as exciting a time to join.
1:41:00
So, obviously we're hiring.
1:41:02
I know bridges as well, Stripe is as well, but talent is absolutely the main for doing this.
1:41:06
A lot of it software engineering, a crossbow of sort of smart contracts to build up the actual sort of capabilities to build whole new currencies.
1:41:13
So if you're an economics, >> how much of that is a new Yeah.
1:41:15
How much of that is a new skill?
1:41:17
Like is it CS plus economics or CS plus a specific language that you've worked in a long time or just experience in uh smart contracts specifically?
1:41:26
The honest take is we found the people who do best are like generally spiky and then specialize over time.
1:41:32
So you could argue like we want, you know, solidity devs which is the the smart contract language on Ethereum.
1:41:36
But I actually think people who are just like very deep in what they do and excited about the space and to pick it up uh have an opportunity to come here and shape the space in real time.
1:41:45
So >> do you put engineers out with your customers?
1:41:48
that is uh we are we are we were early to the I spent some time at Palanteer uh and so we were early to the FDE uh resurgence and and so basically that's exactly what we do.
1:41:58
We we mostly basically uh embed with our customers to build alongside them to get repeatable use cases and then those are product ties and that's most of what you see on on the preview website but that's a lot of how we do the work today. >> Cool.
1:42:11
>> Well, thank you so much for coming by. This is fantastic.
1:42:14
>> Progress is absolutely wild. >> Congratulations. >> Thank you.
1:42:18
We will talk to you soon.
1:42:20
>> While he's walking out, let me tell you about linear, a purpose-built tool for planning and building products.
1:42:23
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1:42:27
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1:42:30
Uh Delian said, "Bro, these foundation model companies already have pretty rough P&Ls.
1:42:34
Imagine if they also had to pay their pay to put their data centers in space."
1:42:41
Yeah, the space data center thing.
1:42:41
Yeah, the space data center thing. there is like some sort of bullcase but every person who's sort of like an expert in uh building a data center what it takes to actually like rack and unrackck GPUs and what happens >> data centers in space the perfect spec
1:42:56
though >> yes >> the perfect spec >> I mean it it could happen it just feels like something that's like 10 20 years out it feels a little bit longer uh let's pull up I think we got audio on the French TV >> let's listen to that >> hopefully Henry is still uh around so you can translate plate. If you can hear
1:43:12
If you can hear the audio, >> let's see.
1:43:22
>> Do they go to Silicon Valley for this, too? Who' they talk to?
1:43:24
Do we know what labs they went to get access? Here we go.
1:43:31
Can we get Henry miked up?
1:43:38
Yeah, she interviewed us French take on actually because they're talking about how Meta is paying engineers and absolutely bludgeoning each other with high salaries and the French are blown away by basically how hard American tech will go to find talent.
1:43:56
>> Yeah, we we just thought it was amazing that that they they they came back from summer holiday and decided we have to cover the story immediately.
1:44:03
We have to get our reporters to the west coast to figure out what's going on.
1:44:09
>> Now covering uh is uh these engineers are being traded like uh like athletes thanks to TBPN cards.
1:44:18
>> Uh so you're seeing the emergence of a whole new talent market basically with active trades.
1:44:22
>> This is a great translation. Thank you.
1:44:24
You're doing this in real time. I'm here for it. It's hard.
1:44:27
>> No, we need to get uh the new version of PS manager so people can actually uh trade their own uh >> talent. Oh, that's great. >> That's hilarious.
1:44:34
Is that ProEvolution Soccer?
1:44:36
Is that what you're saying? >> Yes.
1:44:39
>> They got a gamer in the Ultra Dome.
1:44:40
>> Thank you so much, Henry, for the translation and for coming on. You're >> Thank you.
1:44:43
And thank you to France for highlighting the Ultra Dome.
1:44:45
It's a huge sign of respect.
1:44:48
>> TVPN is the TVPN of Europe. >> It is. Uh, Sonnet 4. 5 wrote a ha coup. Uh, he said sonet 4.
1:44:54
5 wanted really wanted to write some bad haikus to experiment making itself laugh.
1:44:59
The worst haikus ever written.
1:45:00
This is the haiku on being digital. I am made of math. Consciousness goes burr. Haha.
1:45:08
Still love you though, bro.
1:45:11
And Replegate says, "That's actually an amazing haiku."
1:45:13
It is a pretty good haiku.
1:45:14
Uh the LLMs are great when they're when they're like trying to do something poorly and then it winds up being actually unintentionally amazing.
1:45:24
It's very hard if you're if you come in and say, "Write me something that's actually great."
1:45:27
It needs to The hallucination is a feature, not a bug. For sure.
1:45:31
Ara says, "Your kidney can go for like 300k and you only need one to survive."
1:45:36
God gave us all startup capital.
1:45:38
You just have to want it bad enough.
1:45:41
>> You got to I would not go that far.
1:45:41
I am against uh selling body parts, but if you do, make sure you pay your sales tax. Get on numeralhq. com. Sales tax on autopilot.
1:45:51
Spend less than 5 minutes per month on sales tax compliance.
1:45:54
Um, Chris over on X is highlighting the Apple TV Plus rebrand to Apple TV and says, "This changes everything." >> I have an idea. I have a pitch.
1:46:04
We're going to get Ashley Vance to produce a documentary about Apple TV and it's just going to be called Apple TV.
1:46:10
And so, you will be able to watch Apple TV's Apple TV on Apple TV on your Apple TV.
1:46:16
And that was a grammatically correct sentence because there are >> but it's not an actual it's not an actual TV.
1:46:24
>> It's not it's not >> it's not.
1:46:26
So that's going to be slightly confusing.
1:46:27
Some people are going to be excited because people like me have have wanted Apple to make a proper television. >> Yeah. >> Yeah.
1:46:35
Ben To had a funny take that was like Apple TV should have made like three different products where it would be like Apple TV the box, Apple TV set, which would be which would be like the actual TV, the physical screen, then Apple TV box would be the box and then Apple TV stick. I don't know.
1:46:50
Have you ever used a Fire Stick? An Amazon Fire Stick.
1:46:54
Have you ever used one of those, Tyler? Yeah. >> Yeah.
1:46:56
I mean, it's like the same thing as a Roku.
1:46:58
>> Yeah, but it's like smaller.
1:46:58
It just plugs straight into the HDMI port, right?
1:47:01
>> Isn't Gen Z using the Fire Stick as a vape these days? >> What?
1:47:04
What are you talking about?
1:47:04
That that is >> Don't act confused, Tyler.
1:47:08
>> How would you use it as a vape?
1:47:10
>> I'm just I'm just playing at all.
1:47:13
>> Um, but yeah, I it is it the Ben's point was that uh Apple's incredible at miniaturization.
1:47:18
The Apple TV is pretty big.
1:47:21
I mean, it's small compared to like an old DVD player, but it's pretty small, but it could be way smaller.
1:47:24
And you could basically stuff stuff an iPhone in the in the I thought they should call it the Apple TV Nano and then it would be the stick that plugs in the side because you could clearly fit plenty of stuff in there uh to actually do everything you need to do.
1:47:38
>> Did you see this post from Pedro Domingos of most valuable private AI startups? >> Yes.
1:47:44
>> Uh and he says the most hilarious is safe super intelligence.
1:47:46
No customers, no products, no plans and a $32 billion valuation.
1:47:50
Obviously, uh they have plans and obviously they're working on a a product safe super intelligence.
1:47:56
What more do you need to know?
1:47:59
>> What else do you know?
1:48:00
>> They uh I my my question is what um >> what percentage of these companies >> we got to buy midjourney 20x revenue multiple. It's a banger.
1:48:09
>> John, what how what percentage of these companies do you think will be uh uh valued at more than their current valuation in 5 years? [Music] 30%.
1:48:23
I would say like 30% of these are going to go the distance.
1:48:26
Um there's a lot of these companies that have been around.
1:48:30
>> They're going to get through the trough. >> Yeah.
1:48:32
I mean like like like data bricks is like a very robust business that has been growing for years. It started in 2013. Like I don't know.
1:48:39
It seems like they've they've they've been accelerated by the AI era, but uh they've built a very very durable enterprise SAS business.
1:48:49
Uh and I mean a lot of these companies are just like set up for success too.
1:48:53
Like Midjourney is a great example like they haven't raised any money.
1:48:57
And so it's like, okay, if if people get sick of midjourney and stop paying or something, it's like, okay, like we'll go from 99% profitability to 92% profitability or something.
1:49:06
Like it just seems uh it just seems like like a fine situation.
1:49:11
A lot of these a lot of these companies have set themselves up.
1:49:14
And then a lot of them are just like, you know, like compounders grown, found their found their footing.
1:49:17
And then there's some that are much earlier, obviously.
1:49:20
obviously. uh some that have zero revenue so far and still need to go from zero to one or find the initial product market fit and uh it'll be interesting to see like where some of these like how niche do the do the do the foundation model companies go like where does where does thinking machines actually wind up
1:49:39
where does where does safe super intelligence wind up there's a couple other companies that aren't even listed here that are doing this sort of more focused LLMs that aren't just trying to go straight at anthropic or straight at open AI anymore more and uh we've only heard like very loose rumors about what that actually looks like. Some of them
1:49:54
Some of them are pursuing like wildly different architectures and there's actually been some interesting news this week about that.
1:50:01
Google came out with a new paper.
1:50:04
Did you see that paper about the humanities last exam uh or no uh the arki there there was a new new model that did really well on archi that was very small recursive models. >> We talked about this.
1:50:15
Yeah, I think it was tiny recursive model.
1:50:18
>> Tiny recursive models.
1:50:18
>> Tiny recursive models. So you could imagine that someone comes up just like just like you could look at midjourney as a competitor in AI like they train a model they're competitor anthropic but enthropic doesn't do images and midjourney doesn't do code or text and so they're actually not competitive at
1:50:34
all and you can imagine that there's a new architecture that emerges like you know you have the LLM you also have the diffusion model and then if you have a new architecture a new model that's maybe not good for chat or good for images but it's good for RKGI puzzles maybe that works works in a particular place and maybe that becomes its own business. So I don't know uh there's
1:50:51
So I don't know uh there's still a lot of a lot of gas in the tank for for the earlier stage foundation.
1:50:59
>> Rock quoted this data and said is at 150 million of ARR up 4x yearover-year two years after launch is the >> way to make a song with AI uh via prompt.
1:51:11
I wonder where this revenue is coming from.
1:51:14
Is it just proumers, people making songs for videos they're making? Is it actual musicians?
1:51:21
>> Yeah, people seem very willing to throw down 20 bucks a month if they're in the like AI experience. >> Yeah. Yeah.
1:51:28
>> Yeah. Yeah. if they're in the AI early adopter crowd and also I mean I I was we were we were testing some of these audio models and you know we have a business use case for them like if we could generate a the sound of a crackling fire or Christmas song that was uh you know
1:51:43
somewhat tailored to us fit the mood maybe was endlessly looping or something like that uh we would pay for that because it's related to our business and so uh we might we might get on the $200 a month plan pretty quickly I don't know uh it's possible um But >> Andrew Curran says, "We are in a strange spot right now with AI. The anti-AII
1:52:00
The anti-AII crowd believes progress has halted and are doing a victory lap.
1:52:04
Insiders at all labs maintain advancement continues at pace.
1:52:09
Only one of those these versions of reality will survive the new year.
1:52:13
Gemini 3 is very close now.
1:52:13
We are uh hopefully hopefully I don't even know if we should get early access to Gemini 3 because we're probably gonna like talk. >> Tyler's gonna Tyler. >> What do you mean? Why wouldn't we?"
1:52:26
Well, I just sometimes I'm like, "Okay, this a fundraising announcement, give it to me under embargo.
1:52:31
I don't I don't really, you know, I'm not gonna I'm gonna not gonna talk about it."
1:52:35
But if if we if we get access to Gemini 3 and and it and it's and it's like a step change.
1:52:44
>> Oh, it blows your mind.
1:52:44
Then you can't keep it a secret.
1:52:46
>> It's going to be hard to keep.
1:52:47
>> It's going to be people are going to be re read between the lines.
1:52:48
See that Jordy is forever changed. >> Yeah, potentially.
1:52:52
>> What did What did Jordy see? >> What did Jordy see? ES off.
1:52:53
ai, the number one AI agent for customer service, the number one performance benchmarks, number one competitive bake offs, number one ranking on G2.
1:53:00
>> Uh, >> what about you, Tyler?
1:53:02
Do you think that progress has halted or advancement continues at pace?
1:53:09
>> Uh, I mean definitely the latter get any like benchmarks. We're on path.
1:53:14
>> What What is your prediction for Gemini 3? What do you think?
1:53:17
>> Rumors are saying that it is incredible.
1:53:19
Those uh those rumors are coming from fairly unreliable sources like random exons >> who like >> okay >> it's like why how do they have access to the smart no one really knows do they even >> well what what do you think incredible will mean do you think it will mean faster cheaper or truly like good at posting higher intelligence some like qualitatively new functionality that you're like oh this doesn't even feel like claude 4.
1:53:44
5 or GPT5 it feels like a different thing there's this Guy Vidant Mistra over at DeepMind and he posted a couple days ago, we're doing all kinds of stuff with these models that the public isn't even thinking of yet. >> He's vague posting. >> Vague posting.
1:54:02
>> You like to see the vague post.
1:54:02
I mean, I I hope that uh the model is basically like way more expensive and it takes way longer because the output is like so incredible. Yep. >> Right.
1:54:11
Like5 I was maybe I would I wouldn't say I was disappointed, but it was like clear that they were going for efficiency.
1:54:17
They're driving down cost.
1:54:18
Maybe that's better in the long run because you can just get way more output out of the models.
1:54:21
But I would like to see an incredible model that is maybe expensive to run, but it's just, you know, way way better. Yeah.
1:54:26
I think it's also we're getting to a point where models uh it's it's kind of hard to tell like how much better they are because >> it just saturates all the easy benchmarks.
1:54:35
Like totally there was uh GBT 5 I had the horse benchmark. >> Yep.
1:54:39
>> Um and even then like if you run it on a couple times it would sometimes get the horse right. >> Okay.
1:54:44
>> It's like that's way better than I I can't name any horses. Why not?
1:54:46
You've been working here for almost a year.
1:54:49
>> Give it to any math question, give it any figs question, it's going to get it right.
1:54:52
So, it's get definitely getting hard to actually tell that the models are getting better. >> Yeah.
1:54:56
>> Um, >> I'd like a model that if I put in my query, put in my prompt, it says, I'm going to come back to you in a month.
1:55:02
I'm going to think for a month and then it goes and it aentically hires a person to solve that problem and it employs a human being. That's the goal.
1:55:10
>> I do think the time horizon benchmarks, I think those are some of the most like promising things that we can still uh rely on, right?
1:55:16
you you're seeing uh I I forget what the exact number is, but it like doubles every 6 months or something like that.
1:55:22
>> So like an impressive step forward would be doubling from like 2 hours to like 4 hours. >> Yeah, I I think uh 4.
1:55:27
5 was something like I I thought it was like around six or seven hours. >> Six hours.
1:55:32
Okay, so maybe Gemini 3 goes 24 hours.
1:55:35
That'd be pretty impressive. Come back.
1:55:37
Noah Hersfield in the chat says, "I see Annon's posting some crazy oneshot coded stuff using Google uh Studio 8 saying it's Gemini 3 looks impressive if real."
1:55:48
>> Super vague post though. Okay, last question.
1:55:49
If you're Demis, >> the founder of Deep Mind and you got to put up the ultimate vague post before Gemini 3 drops.
1:55:56
You're trying to out vague post Sam Alman's Death Star post. What are you posting?
1:56:02
What's the vaguest post you can possibly >> solar system? >> A solar system.
1:56:08
>> Maybe just >> post the solar system.
1:56:10
>> Maybe just uh just a >> just random noise.
1:56:13
Something like that or >> an audio file.
1:56:17
>> You know what would be good?
1:56:17
The you know the green uh the green text from the matrix where the green numbers flow down.
1:56:23
That would be a cool vague. Put that up. >> Or he could post it.
1:56:26
You know how you know how the the the Tesla robo taxi and the Whimos they they hurl slurs at each other when they pass? Yes.
1:56:34
>> Uh just translate that into English.
1:56:36
That would be pretty mind-blowing.
1:56:38
Translating you know the the machine super intelligence back into English.
1:56:40
Uh there's more >> uh some timeline and turmoil from uh some earlier coverage.
1:56:46
Uh >> Mark Andre quoted David Saxs who said anthropic is running a sophisticated regulatory capture strategy.
1:56:53
Mark Andre just said truth >> truth >> he put it in the truth zone uh and it uh it's fact true by >> Mark Sager and Jetty quoted Sam Alman and said Sam Alman proudly announces Chad TVT will soon produce personalized pornography. >> Yep.
1:57:13
>> Y >> it's a it's a choice.
1:57:15
>> That is one uh that is certainly feels like a fair way to to uh characterize the announcement.
1:57:21
Yeah, >> it's I think it would be hard to argue it's not personal.
1:57:26
>> The really crazy thing is when you think about like Sora cameos adult content where that matches is going to be extremely extremely weird.
1:57:36
>> But you know what's not weird?
1:57:36
Adio customer relationship magic.
1:57:38
Adio is the AI native CRM that builds, scales, and grows your company to the next level.
1:57:43
>> Get out there, make some sales calls >> barking.
1:57:46
>> Get your dogs barking.
1:57:46
Uh head over to Allen and Company. Head over to Sun Valley.
1:57:51
Andrew Reid has the story.
1:57:51
In 1999, the year was the year that the internet guy showed up at Allen Company in Sun Valley.
1:58:00
Uh, new media to click with the old guard at Sun Valley. This is from 1999.
1:58:09
Uh, this year will be remembered out here as the year the internet guy showed up >> as the giants of media businesses arrive here today for the annual Allen and Company conference.
1:58:18
They are being joined by a large scale for the first time of a new connect new collection of internet billionaires.
1:58:24
Tech giants like Bill Gates and Andy Grove have been coming out for years as have AOL's Steve Casease and Bob Pitman.
1:58:30
But this year there's a new breed of mogul.
1:58:32
Michael Dell is coming from the first for the first time.
1:58:36
You got to listen to him on David Senra >> by David Sen. >> By David Sen. >> Hosted by David.
1:58:42
>> David Weatherell of CMGI was here last year but no one knew who he was. Now everyone does.
1:58:47
uh his collection of internet properties including LIO and soon Alta Vista has taken off like a rocket.
1:58:52
Then there's Jay Walker who was here last year as well, but that was before he took Priceeline.
1:58:56
com public and became a billionaire.
1:58:58
I believe Mary Mer took Priceeline public or or at least reported on it.
1:59:03
Um uh Jeff Bezos of Amazon.
1:59:06
com has joined the party for the first time as are Jerry Yang and Tim Cougall of Yahoo and Bob Davis of Likos.
1:59:12
Many of the traditional media moguls attending the presentations and panel discussions will be eager to meet the new media powerhouses and possibly work some deals.
1:59:19
Time Warner, Disney, News Corp, uh, and Viacom have all made the internet top priorities.
1:59:24
Making his Sun Valley debut is Richard Breler.
1:59:26
The former Time Warner CFO, who's now in charge of the company's internet ambitions.
1:59:31
NBC and CBS will be chatting up the newcomers as well as the networks continue to continue trying to use their promotional clout to build internet dynasties.
1:59:43
Um Frank Bondi will be seeing a lot of uh a lot of two former bosses who fired him.
1:59:48
Snar Redstone of Viacom and just recently Edgar Brmpen of Cr.
1:59:51
Uh this year the broadcast network guys here will be able to walk around with their heads held higher.
1:59:58
Last year they were the poor cousins struggling for their lives against cable and the internet and trying to cope with skyrocketing program programming costs.
2:00:05
Barry Diller began talks here last year with NBC trying unsuccessfully to acquire the networks.
2:00:12
Uh fascinating archival post from the New York Post.
2:00:14
Thank you for surfacing it.
2:00:16
Andrew Reid >> Ross Hendrick says uh is quoting Wasteland Capital.
2:00:20
Wasteland says, "We're at the stage of the market where any company that issues an AI related quote unquote partnership press release soarses by 10 to 35% immediately.
2:00:30
Obviously, except Salesforce."
2:00:30
Ross says, "Yep, this is our version of 1999. Back then it was adding.
2:00:34
com that sent stocks up on autopilot.
2:00:36
Now just announced a vendor financed quote unquote AI deal and same result.
2:00:41
The name change the names changed.
2:00:43
The game remains the same. We know how it ends.
2:00:45
I would argue that announcing deals is not as bad as just like acquiring a dot domain.
2:00:55
>> Yeah, slapping a domain on it is a little bit rougher.
2:00:57
Um, at least the at least the partnership should generate like economic value if they play out.
2:01:04
But uh it is it is very frothy and it's clear that like it's become some sort of like meme or there's some sort of like mimemetic contagion where everyone needs to >> Honey in the X chat says bottom line is that Google has turned the tanker and the game is already over. >> We'll see. We'll see.
2:01:20
>> We will see with Gemini 3.
2:01:22
>> Well, speaking of turning the tanker, when you get an aid sleep, you'll need to change out the water tank every once in a while, but otherwise it's a fantastic few every few months. >> Yes.
2:01:32
>> How'd you do last night? I got an 84. I slept okay. Only 6 hours though.
2:01:36
I woke up a little bit early.
2:01:38
Kids were a little crazy. >> Got an 81.
2:01:41
>> Still very happy with my sleeping. Get one at aleep. com.
2:01:44
>> Uh, speaking of water, McMaster sells supplemental eyewash with mountain.
2:01:51
>> I hope this catches on.
2:01:52
>> There's a McMaster reaction meme.
2:01:55
Pouring water in your eyes. >> It's very >> Yeah.
2:01:57
You see a post on the timeline that it's not so great.
2:01:59
Two 32 oz bottles of McMaster water eyewash are $55 each. That is expensive.
2:02:07
>> Okay, pull up this video of robot dogs.
2:02:10
>> Robot dogs dressed in costumes.
2:02:10
Fill me with joy, says Justine Moore of Andre Horowits fame.
2:02:15
Uh, this is a robotic dog in a dinosaur costume of some sort. Look at that.
2:02:22
It I I like this a lot more than just the normal robot dog.
2:02:25
This seems like lowhanging fruit that everyone with a robot dog company should be doing.
2:02:30
It's hilarious looking and it seems like the kids love it.
2:02:34
It's a lot less scary that way.
2:02:35
I feel like it's a lot more like, you know, less Terminator.
2:02:38
What do you think, Tyler?
2:02:40
>> I mean, we got to get some kind of robot. >> We really do.
2:02:41
We really do have to get a robot.
2:02:45
>> Um, >> we could get so much good business value out of it. >> I agree. I agree.
2:02:48
Have you looked into the the APIs at all or or what you can actually do with with one of these humanoid robots?
2:02:55
I mean on on the unit tree like most of the videos you see of the unit tree like fighting or or walking around it's just from like uh PhD labs. Yeah.
2:03:03
So it's just like open source.
2:03:05
It's like I don't even know if there is software that comes with the robot. >> Oh really? Buy it.
2:03:08
>> I feel like it would at least come with like a you know basic Xbox controller so you could like do a basic walk cycle.
2:03:14
Like if they're not even shipping with that that's a crazy crazy move.
2:03:17
>> I mean it's mostly for researchers to buy.
2:03:19
I assume >> it's so cheap. It's wild.
2:03:21
We we really do have to get one.
2:03:23
It's gonna be kind of creepy, kind of crazy.
2:03:26
Well, in good news, Goldman Sachs has announced Q3 net revenues 15. 18 billion.
2:03:32
Let's ring the >> founder. >> There we go. We love to see it.
2:03:43
>> And if you want to get in on the action, whether you're long or you're short, head over to public. com.
2:03:47
Investing for those who take it seriously.
2:03:49
They got multiasset investing, industryleading yields, and they're trusted by millions.
2:03:54
>> I think more startups should just post a picture of their net revenues like this picture that just came from this the official Goldman Sachs account.
2:04:02
Uh it's pretty pretty sweet.
2:04:06
>> Um >> anyway, um >> that picture that that video of the dinosaur reminded me yesterday.
2:04:11
Uh one of our nannies did something cool.
2:04:13
They took a a video of our back of our actual backyard and then they used Sora to make an animated video of one of my son's like toy dragons that flew into the backyard and landed. >> Wow.
2:04:30
>> And of course, he absolutely loved it.
2:04:33
He was like freaking out.
2:04:33
There was like a dragon in the backyard or whatever.
2:04:36
And I was just thinking my immediate thought of this is amazing, but at the same time like is it good that my like 3 and 1/ halfyear-old like >> thinks that a dragon was actually in the backyard.
2:04:49
>> Yeah, you definitely have to say like this is from the computer.
2:04:50
It's like when you draw with a pen and paper this is, you know, not real. >> It's imaginary.
2:04:57
>> But does a three and a halfyear-old actually have >> eventually they do process that you know they learn that you know cartoons exist and animation is not real.
2:05:03
So I think that you can you can instill that uh over time.
2:05:07
Um but we have our second guest of the show, Andrew Ross Sorcin, the author of 1929.
2:05:12
Andrew, thank you so much for joining.
2:05:14
Congratulations on the book and thank you so much for joining.
2:05:19
>> Hey, thank you for having me.
2:05:19
I was just checking my um my score on my eightle.
2:05:20
I was cur I was because of you guys.
2:05:24
I'm a I'm a big fan of Matteo Forever.
2:05:26
Um they've done an extraordinary job and but I was going to tell you I really did not do well last night at all. >> What you got? >> 43. 43 last night. >> I got an 84.
2:05:40
>> But my aura ring I don't know if you guys ever compare.
2:05:42
My aura ring has me in the 70s.
2:05:45
So I don't I don't know what to do.
2:05:48
But I sometimes I do you ever turn the mattress off in the middle of the night >> and then turn it back on because it's too cold.
2:05:55
So sometimes it gets too cold. Okay.
2:05:56
And then I need to get back to sleep.
2:05:58
So I'm like I got to turn it back on. >> Yeah.
2:06:00
I think you got to do a software update.
2:06:03
>> You got to get on autopilot.
2:06:03
I have noticed that if I autopilot >> uh occasionally I have a bunch of kids if they wind up piling into the bed over time I will bail go to a different bed and then the sleep gets all confused because it's like why is this four-year-old in here?
2:06:15
How how do we track how he sleeps? >> Crazy heartbeat. Crazy heart.
2:06:18
I've had that my my daughter slept in the bed. Crazy.
2:06:22
like all of a sudden you're like is there something wrong with it? >> Yeah. Yeah.
2:06:25
There are there are limits to technology.
2:06:27
Um >> well I think it's a it's it's fair to not sleep that well right before a day like today for you. >> Yes.
2:06:34
>> Um a day that that uh you've been working towards for how many how many we were hanging out off off the air.
2:06:39
You said >> this has been like a seven was it a seven year? >> Seven or eight years.
2:06:43
I think end of 16 early 17 is when I really sort of began uh down this road right right about 1929. So, here we are.
2:06:52
>> So, you predicted the AI bubble all the way back then and you said, "I'm going to drop the book right as everyone's talking about talking about bubbles popping."
2:06:58
And >> no, now to be honest with you, and it's actually funny that the book is coming out now.
2:07:04
>> I thought I was writing a story about the past.
2:07:06
And the truth is, it is a story about 1929 and all the shenanigans and crazy things.
2:07:11
And I just really wanted to write a sort of cinematic uh character-driven narrative of that time.
2:07:16
I always loved books like Barbarians at the Gate and Den of Thieves and things like that.
2:07:20
And nobody had really written a book about 29 like that.
2:07:22
I had gone on this wild vacation years ago where I downloaded a million books about 29.
2:07:28
There's some really good ones, but no one told you like who the people were and what were they saying to each other.
2:07:33
I found some and then I found these transcripts and and uh depositions and all sorts of things.
2:07:37
I said, "Okay, maybe I could do this."
2:07:39
But as I was working on it, it was weird because eerily there were things that were clearly happening in the 20s that all of a sudden I', you know, I'd seen the headlines today and I'd go, "Oh, okay.
2:07:51
Tariffs, like that's a thing.
2:07:51
U you're seeing some of these circular deals, that's a thing." Yep. >> Cool.
2:07:57
Like, uh, there was a whole bunch of I mean, some of the stuff that's going on with meme coins, >> sure, >> that's a thing. So, yeah.
2:08:02
Um, it gets >> it's a little nerve-wracking, but I don't think we're going off the cliff just yet. I hope. >> Yeah.
2:08:10
Well, we know who the characters are today.
2:08:11
Um, but I'd love to know who were some of the key characters that stuck out to you that you identified like you want to draw extra focus towards this particular person.
2:08:21
I mean, Churchill sticks out, but who who else or or or maybe you could tell me the story of like how you thought to integrate Churchill into the story.
2:08:28
Um, and then we can talk about some of the other characters that stuck out to you.
2:08:34
>> Well, Churchill was just almost an accident.
2:08:36
I didn't realize Churchill happened to be in New York literally uh the week that the crash was taking place.
2:08:41
He'd actually been down on the stock exchange and there was a big dinner that was taking place the night of the crash with every major banker and frankly every major character in this book was all going to dinner with him and I thought, "Okay, so now I got to figure out everything about that because I got to set that dinner up um and really understand."
2:08:59
He was, by the way, in the in New York because he needed money.
2:09:02
He was he he also loved the stock market.
2:09:04
He was getting loans like crazy.
2:09:06
He had totally got the bug. He was investing.
2:09:08
And he also, as you might imagine, lost.
2:09:11
But yeah, really the the big characters in this book, a guy named Charlie Mitchell, who really was probably the he was almost like the Jamie Diamond of his time, maybe more like Michael Milin in certain ways, but I mean, he was super famous.
2:09:23
He was like on the cover of magazines.
2:09:25
This was also a period where all of these guys also became celebrities for the first time.
2:09:30
That happened in the 1920s when, you know, Time magazine would put these guys on the cover.
2:09:34
the same way they had put Babe Ruth and Charles Lindberg on the cover.
2:09:37
So sort of like what we see now, you know, whether you Sam Alman or Elon Musk or whatever that really that whole kind of celebrity CEO that started then and uh this guy Charlie Mitchell ran a bank called National City becomes Cityroup >> if you're a New Yorker.
2:09:53
Uh he lived by the way on Fifth Avenue between 74th and 75th uh which is where the French con the French consulate is now.
2:10:00
So that there's a beautiful uh building that was his house.
2:10:04
I mean like these guys lived like kings back then and he really invented modern credit in terms of lending it to people to go speculate or not I shouldn't say speculate but invest and ultimately a lot of people speculated with it but >> including Winston Churchill himself >> in including Winston Churchill himself.
2:10:23
Uh by the way he he was staying at the Plaza Hotel Winston Churchill there a brokerage house had opened and EF Hutton had opened inside the plaza.
2:10:29
I mean, these these brokerage houses were opening up like like Starbucks on the corner of every street and you could go in and you put down a dollar, they'd loan you $10.
2:10:38
I mean, like virtually sight unseen and there was no prospectuses uh or anything like there's no SEC, no nothing.
2:10:44
So, at best you'd get like a leaflet, >> but I mean 10x leverage now that's low.
2:10:50
I mean, I see people with 50 100x leverage. We learned our lesson. Go bigger.
2:10:58
So, so that so, so Mitchell was really sort of the at at the edge of that and and really building that.
2:11:02
And the other character that really drove me to even write this book was you had Charlie Mitchell on one side and then you had a guy who you probably know, Carter Glass, uh, Glasssteagall, which is a bill in in 1933 that gets put together to break up the banks.
2:11:15
But, um, >> Carter Glass was a senator in Virginia who was like the Elizabeth Warren of his time.
2:11:22
He would rail about this thing called Mitchellism and how he thought Mitchell and Wall Street were going to ruin America and speculation was going to go rampant and someone had to stop these guys and it's really a a bit of a story the clash of these two uh remarkable figures and then there's so many other sort of fascinating entrepreneurs uh along the way.
2:11:42
A guy named Billy Durant, a guy named John Rascco.
2:11:44
John Rascov is Elon Musk.
2:11:46
I mean, I got to tell you, uh, John Rascco, uh, created credit at General Motors, uh, became a a amazing investor, then takes all of his winnings, decides to get into politics, a little Elon like, uh, decides to, uh, back Al Smith against President Hoover, by the way, loses, then decides to spend his money to almost undermine Hoover's reputation.
2:12:09
You know, Hoover has a terrible reputation.
2:12:10
I actually think John Rascco had the secret campaign going that gets exposed.
2:12:13
um that really I think did a did a whole number on Hoover and then he creates what was then probably like the SpaceX of America.
2:12:23
He builds the Empire State Building.
2:12:26
So he also has 13 he has 13 children.
2:12:29
So you know >> there's a lot of similarities there.
2:12:33
There's a lot of >> Yeah.
2:12:33
So, I mean, yeah, as you get into this is just incredible proof that uh products and and technology changes and people have just seemingly don't at all.
2:12:45
It's just the same kind of behaviors over and over.
2:12:49
>> But the truth is, and this is the part that I'm always like grappling with, and I know you guys spend a lot of time with these amazing startup founders and entrepreneurs, you need some speculation in the system.
2:13:00
Like we always say speculation is a dirty word or bad word, but you know the original investors in SpaceX or in Tesla who probably thought the whole thing was insane were speculating.
2:13:11
And you need some of that. You really do.
2:13:13
And so the question is like how do you create a line where you know you have enough of that to create that innovation but it doesn't go you know totally parabolic and out of control. >> Yeah.
2:13:26
I mean it feels like the answer is probably like you can't have some sort of systemic risk that just brings down the whole thing, right?
2:13:32
Uh and I want to know about the reaction to 1929.
2:13:34
I mean you mentioned Glass Deagle.
2:13:36
That's four years post crash. >> Yeah.
2:13:39
What were like the >> the tools in the tool chest? >> Yeah.
2:13:42
And also the key the key takeaways like hey like some of the speculation was fine.
2:13:46
Maybe that's that that can drive industries forward but let's not do that again.
2:13:50
So, I think a couple things.
2:13:53
First of all, leverage to me, and I I wrote about this in Too Big to Fail in 2008, leverage is to me like the the match that lights the fire every time.
2:14:01
When you have too much leverage in the system, that is that is the problem.
2:14:04
You can actually have a lot of crazy things happening.
2:14:07
>> Uh but it's it's the leverage that really yep >> exacerbates it and is the accelerant.
2:14:13
So, I think you have to watch uh for that.
2:14:15
I think politically, interestingly, you know, we talk right now about the Federal Reserve and Fed independence and things like that.
2:14:20
Back then, the Fed knew that there was a problem with speculation and they didn't really do anything about it or enough about it partially because they were worried about the politics.
2:14:30
They were worried because they were such a new institution, they were born in 1913 that, you know, not just they'd get hauled in front of Congress, but maybe they, you know, the Fed would effectively disappear.
2:14:40
And then once the crash happened, instead of flooding the money, flooding the system with money the way Ben Bernanki did, who by the way learned that because of the Great Depression and studying that when he was at Princeton for his PhD, we there was almost like um no pullback.
2:14:56
Nobody nobody was flooding the system with money.
2:14:57
Everybody was in this, you know, crouched position, but you almost have to do the politically unpopular thing and flood the system with money.
2:15:04
Then you had a whole series of other dominoes.
2:15:06
You know, you had Smoot Holly, which was this tariffs. 1930 tariffs happened.
2:15:11
>> Global trade drops by 60% as a result of that.
2:15:15
Hoover is trying to raise taxes at this time.
2:15:19
>> That's the worst thing to do in a moment when the economy is faltering.
2:15:20
So, I think there's so many different things.
2:15:24
And then setting the setting up the SEC was super important because so much of what was messing up the market was in truth manipulation that wasn't really illegal at the time.
2:15:34
So, talk about insider trading.
2:15:36
There were groups of people, they call them investment pools.
2:15:39
And in fact, I would say it's sort of similar to what goes on with some of the meme stocks where people have like Telegram groups, >> retail armies. >> Yeah. Reddit.
2:15:45
So these were the original retail armies.
2:15:48
>> These were the original retail armies, but they were typically the wealthy.
2:15:50
So it was the elite doing this.
2:15:52
This wasn't a democratized version. Okay.
2:15:55
>> And they had it all set up and they it would almost be like actors down on the floor of the exchange saying, you know, I'm going up for 100, you 200.
2:16:01
And it was sort of out of the open like some people knew that there were pools in the like for the next two weeks there might be a pool in a p in a stock and so then other people would try to jump on the train and hopefully try to jump off the train before the rug got pulled. >> Yeah.
2:16:16
>> But >> obviously didn't happen.
2:16:18
>> Who was on the the right side of history?
2:16:22
>> The right side of history.
2:16:24
>> Like as in as in right now right now everyone's calling it a bubble, right?
2:16:29
So, and and presumably that's so that they can go back and quote, you know, two years from now they can see like, look, I I called it, right?
2:16:35
And there's actually some in in 2021, there's an iconic post from Keith Reo where he basically called the top to the actual day.
2:16:45
Um, and so there's a lot of incentive to call the top and get kind of the the the um the aura of of having that insight at the right moment or maybe just getting lucky.
2:16:56
But I'm curious if anybody, you know, pre 1929 was basically saying like >> two two people.
2:17:02
So there was a guy named Roger Babson, uh, if you know Babson University, by the way, he founded it.
2:17:09
>> Um, and he created what was called the Babson break.
2:17:10
It happened in September of 29.
2:17:13
And he had been he had been out there.
2:17:15
So this was a little bit like, you know, the clock strikes midnight.
2:17:18
You know, it is going to get there eventually.
2:17:20
He was out there for like a year or two or three before saying the whole thing was going to come undone.
2:17:25
So, that's one Cassandra.
2:17:25
Uh, Charles Merrill of Meil Lynch.
2:17:28
He was out there in 28 saying there's a problem.
2:17:30
Um, and then I would say the big winner was a guy named Jesse Livermore.
2:17:36
Jesse Livermore was a short seller who made probably like about $100 million.
2:17:41
He's the most interesting character.
2:17:43
I mean, you'll if you get into this book, it's just fascinating all the things that were going on with him.
2:17:47
Um, but he was a real trader, by the way.
2:17:50
He lost most of that money a couple years later. He made some of it back.
2:17:53
lost him back and then uh in truth ended up uh killing himself uh up on Fifth Avenue at Sherry Netherland in in the cloak room.
2:18:02
Literally went in there in 1940 and shot himself in the head.
2:18:04
So >> uh you know hard hard to say.
2:18:06
The the one thing that's interesting though about >> about No, but about being a Cassandra is interesting.
2:18:14
So Charles Merrill was out there in 28 saying don't invest and he was right and he was wrong.
2:18:19
I mean he was right and that obviously the depression took a really long time.
2:18:22
So he he actually probably is writer than most.
2:18:25
But and this is the question for most investors, the market between the beginning of 28 and September of 29 was up 90%. >> Yeah.
2:18:35
>> So if you had not been in the market during that time, you would have not participated in those ups.
2:18:39
And so that's the question, you know, I was like I was talking to Paul Tudtor Jones about a week ago and he said I was asking him this question about bubbles.
2:18:48
He said, "Uh, I think we're in maybe like October 1999 right now." >> Yep.
2:18:54
>> And I said, "Oh, that's interesting." Okay. 99.
2:18:55
He said, "But there's still, if you said, if you remember, October 99, there was still a 40% upside." >> Yeah. For 6 months.
2:19:03
>> You got to know when to get on and off the train, and that's the hard part. >> Yeah.
2:19:07
Uh, how do you think about tariffs then versus now?
2:19:10
because it feels like the narrative at least is that there's the a bubble is is inflating generally, but also we're seeing high interest rates, tariffs.
2:19:19
There's a lot of tools in the tool chest that could kind of come down if if there was a sell-off and um but it sounds like in 1929 a lot of this stuff happened after the fact like the the the government moved too late.
2:19:32
What was the mood around tariffs and uh and and just anything that was done beforehand that was a potential mitigator?
2:19:39
Like could it have possibly been worse?
2:19:40
Well, you'll laugh because just like the past, call it six or eight months, you know, all of his economists were writing these letters, open letters in the paper papers to Hoover saying, "Please don't do the tariffs.
2:19:52
We beg you not to do the tariffs."
2:19:55
Uh the the CEOs of the the banks were all going to visit him in the White House and he had run on tariffs.
2:20:02
Because he he was trying to get farmers to vote for him in, you know, when he was campaigning in 28.
2:20:06
So he thought this was like a a pledge that he had made that he had to follow through on and that was a big part of what was going on.
2:20:13
Obviously similarly you know like a thousand economists write letters to Trump saying please don't do this.
2:20:19
The the distinction I think today is >> back then it was an acrosstheboard tariff.
2:20:24
Um it was there weren't these bilateral deals and so maybe you could argue today these one-off you know individual deals are better deals.
2:20:32
In fact, one of the ways they tried to fix what happened after Smoot Holly was in 1934, they gave the president of the United States, the authority, which is what President Trump is using today, to make these sort of bilateral deals.
2:20:44
So, >> um, you could you could argue maybe it's more hopeful because there's a little bit more control today than what was happening then, which was just sort of broad-based.
2:20:55
>> So, you said, uh, there were retail armies, meme coins, circular deals back then.
2:21:00
Was there buy the dip culture? Did that exist? Anybody? Anybody in September?
2:21:04
Anybody in September that is like, nah, I'm I'm still long. I'm >> buying the dip. >> Yeah.
2:21:10
You know, I don't think they I don't think they use the phrase buy the dip, but there was definitely a lot of people who thought, you know, this can thing can only go up.
2:21:16
And this was really the first time that people ever saw the market, right?
2:21:19
So, they were sort of not used to the ups and downs, >> just up only >> up only.
2:21:26
And at by the end of it, I mean, you know, I don't know if you remember, you could you there's pictures in the book, but you've seen the pictures online, >> you know, all of those pictures of people who who'd be like standing outside the New York Stock Exchange during the crash, like thousands of people in the street.
2:21:39
The reason they had all come down there was because when they were up at the brokerages, they couldn't even find out what was happening to their stocks.
2:21:46
Uh because everything was out of out of talk about time and technology.
2:21:50
They didn't know what um you know the the stocks on the board would be three four hours behind. >> Sure.
2:21:58
>> And so that was a huge thing in terms of buying the dip.
2:22:00
I don't I think they were just so scared because they didn't even they didn't even know.
2:22:03
It would be like being at a a baseball game and you know you'd be in the eighth inning but you'd be betting on what was happening in the third inning. >> Yeah.
2:22:12
>> And not know what was really going on.
2:22:12
H >> how do you think about that uh canary in the coal mine of the of the retail trader?
2:22:19
There's always this apocryphal probably story from 1929 of like I knew it was time to sell when the the person who shined my shoes was giving me stock tips.
2:22:28
Uh how real was th are those anecdotes from what you what you found in your research and then how real is it throughout time?
2:22:38
>> You know I think it's not a bad signal but I think you got to take a lot of signals together.
2:22:42
Um, John Kennedy, Kennedy was the one who who tells that story uh about the Shoe Shine boy.
2:22:47
And I remember people, you know, talking in the in the do boom about, you know, getting in the back of a taxi cab and getting told, you know, buy some shares of LOS or whatever it is. So, like that happened. I remember that.
2:23:00
But I don't know if that's, you know, when it be is it is it that when it becomes such a part of culture, but now with social media and by the way, all the amazing things you guys are doing, I feel like the exposure I got 15-year-old boys who are twins and they're so exposed to this stuff. >> Yeah.
2:23:16
>> Just and I don't think that they're because of their I don't think that's cuz their dad.
2:23:20
I think that's just like the culture.
2:23:21
And so I think it'd be harder to figure out today.
2:23:23
It sort of look at that as the signal.
2:23:25
We'll tell them to >> Yeah, it feels it feels like uh it's been a very unreliable signal at least over the last two years when it feels like I've >> had people >> Yeah. Yeah. Yeah.
2:23:36
It's been sort of >> constant.
2:23:37
It it certainly maybe in 2021 if the Uber driver had like a crypto wallet pulled up that was maybe a signal, but in general it's like there's so little friction to investing.
2:23:46
It's so much so a part of American culture now that it doesn't doesn't feel, you know, it's lost. >> I mean, I don't know.
2:23:53
I I feel like every Uber driver talks to me about Bitcoin now, but I was I was hearing it from people in like 15 16 I don't know.
2:24:02
>> It's been it's been kind of consistent.
2:24:03
Uh take me through a little bit of the the actual research process for this.
2:24:05
I imagine it's like one big long chat GPT pro.
2:24:12
>> Oh man, I wish chat GPT existed when I started this project and actually worked.
2:24:19
Um maybe my next book AI will be able to help me.
2:24:22
I But I mean that's part of it.
2:24:24
I I'm assuming a lot of the sources that you use for this book are not in the in the in the data set at all. Right.
2:24:33
>> They're not they're not scanned. It's it it was wild.
2:24:35
So what happened was I actually went to the reason I really went down the road is I go to this library at Harvard University.
2:24:41
Um, I happened to be there giving this speech and I'm looking through these documents and I found out that Thomas Lamont, who ran JP Morgan, his secretary was keeping transcripts basically of his conversations uh, with Hoover and Roosevelt.
2:24:56
And I was like, "Oh my god, this is amazing.
2:24:57
I got to find more of this stuff."
2:24:59
And the archist said to me, "You know what, Andrew?
2:25:00
You're not going to be able to write the book you want to write."
2:25:03
She had read Too Big to Fail.
2:25:05
And I wanted that sort of granular detail where you're like in the room.
2:25:08
and she said, "There's not like three or four archives in the country you could just go to and just excavate. It doesn't exist."
2:25:13
And so I think I took that as a personal challenge really and ended up going around the country.
2:25:18
Um it was almost like putting puzzle pieces together, finding depositions and transcripts.
2:25:23
I I got access for the first time to the Federal Reserve Board minutes um from 29 in New York.
2:25:27
They had never been made public.
2:25:30
So that really created sort of like an undergirling.
2:25:32
I got this um memoir that had never been published and a whole bunch of of other things that that really sort of helped me uh create the story and sort of a technology thing.
2:25:43
Mother of Invention, it wasn't just GPT, but during the pandemic, I got stuck.
2:25:47
All of a sudden, I couldn't get into libraries.
2:25:52
>> I So, uh and the only people who could get in were students sometimes who had like a dissertation that they needed to do.
2:25:58
So I would find the >> deployed engineers >> to find me students and I would pay them by the hour and I would say go in there find box 152 and take a picture with your phone of every single page and dropbox it to me. >> Wow.
2:26:14
>> And so I did I did it.
2:26:14
I it was actually a very helpful um helpful thing.
2:26:17
And then I will say one thing about chat GPT to its great credit it was too sad because it was too late for me. Too late for me.
2:26:24
At the bitter end of this project I'm doing the factecking.
2:26:25
I had a handwritten diary of a guy who was on the board of the Fed and I only was able to read like two pages of it the whole time.
2:26:34
I I given it to handwriting specialists and things.
2:26:36
Nobody >> because you just couldn't understand.
2:26:38
You you could see the words but you just didn't know what they were too messy. >> Terrible handwriting.
2:26:42
I mean chicken scratch to me.
2:26:44
So I'm doing the facteing and I think and I had as a PDF because I had taken pictures of the pages and so I don't know what happened to me.
2:26:51
I just said you know what screw it.
2:26:52
I'm just going to put it in chat GPT. Maybe it can read it.
2:26:54
and it read it and >> decipher the scrolls.
2:27:00
>> It wasn't perfect at all, but I was like, "Oh, yeah, that is what he's trying to say.
2:27:04
Oh, and that matches that and that."
2:27:06
So, I do wish that in some ways I had access to AI because I think that I don't know.
2:27:10
I don't think the story would have been totally different, but I maybe some things would have come together in a different way. >> Yeah.
2:27:16
Do you think part of why the crash was so bad was just the lack of high quality real-time data that the various players had to make decisions on?
2:27:24
It feels like >> it feels like you would have just been if you're just wildly confused about what's going on and you have people banging on your office door telling you one thing and it it just feels like it's hard to actually create a plan if you don't know how bad the damage is, how widespread it is, who the different players are.
2:27:42
I'm sure people were actively trying to cover up, you know, you know, bad things that they had been doing as well, right?
2:27:48
That that kind of thing tends to happen. >> Absolutely. So, so two things.
2:27:50
The the guy Charlie Mitchell that I told you about before, his bank almost goes under >> because the bank bought too the bank was trying to buy back its own shares during all this and it bought back too many and it couldn't afford to buy them.
2:28:05
>> And so, he didn't want anyone to know.
2:28:07
So he actually goes and gets a loan, personal loan to buy the shares off the bank. >> Okay.
2:28:13
>> So I mean it was wild.
2:28:13
And then Jesse Livermore, this trader I was telling you about because he didn't because he was so worried about the issue of of having bad information, he paid for his own people to be on the floor so that then they would call him.
2:28:27
It was like Citadel placing, you know, their computers next to the exchange.
2:28:31
He would place his people on the floor.
2:28:33
>> That's you in the archive during co. You're the same.
2:28:35
Real time real time information. Exactly.
2:28:39
>> Yeah, it's the same thing.
2:28:40
>> Uh did did they have revenue backlogs back then?
2:28:45
>> That I don't know about. I don't think so.
2:28:48
>> Well, can you talk a little bit more about your process?
2:28:49
I mean, obviously you're incredibly busy.
2:28:51
How do you get in the flow state to actually write a book?
2:28:55
Do you write one chapter at a time kind of outline front to back revisions?
2:29:00
Like talk about your process as an author.
2:29:03
So, I'm one of those writers, and this is not good.
2:29:05
I don't think I really can't write one sentence.
2:29:08
I So, let me say it this way.
2:29:11
I don't really like to write the second sentence unless the first sentence I'm happy with.
2:29:17
>> I'm one of those people who there's some people who splatter on the page, meaning they sort of they sort of throw everything down and then they think they're going to fix it.
2:29:24
>> I sort of have a view that whatever gets sort of put on the page is sort of anchored in a way, and so I can really only upgrade it.
2:29:30
uh maybe one letter grade.
2:29:33
So if it goes down as a B, I can edit it and make it an A.
2:29:35
But if I just splatter it down as a C, it's never going to be better than a B unless I start over again. >> Yeah.
2:29:42
>> So that's a little bit of a a thing for me.
2:29:44
You know, this project went on for so long that I would write lots of little parts of it, little scenes, vignettes, and so I had these almost like puzzle pieces, and then it was about connecting them.
2:29:54
about connecting them. I think the hardest part for me just given the you know the things I'm doing with with the New York Times and CNBC and my dealbook stuff is for flow state I can't my wife would sometimes say oh you have half hour 45 minutes you want to go work you can go work on the book now or whatever they and unless I really had two hours yeah I couldn't really do it because the first half hour 40 minutes I like almost
2:30:19
had to rev up yep totally >> so that's a thing that's a real I think in the I don't know in the creative world or It's I think you do need to get in that flow state and and that's hard and you know I've got three kids and um
2:30:31
sometimes I actually try to write with them like I mean like hang out with them and have them around and that's that can work for me sometimes but I have to sort of like really get super super dialed in. >> What were what was the 1929 of 1929 like
2:30:43
>> What were what was the 1929 of 1929 like what were folks in 1929 looking back to and being like this is just like we've seen this before.
2:30:52
History doesn't repeat, but it rhymes. >> Yeah. Exactly. Exactly.
2:30:55
Like what were they question?
2:30:59
>> It's such a great question because the truth is they weren't for the most part.
2:31:03
They really because I think that this was such a first. >> Sure.
2:31:05
>> I I really think it was a that the 29 was such a first in terms of that break.
2:31:10
Maybe what they would say so there was a break in the market in the early 20s.
2:31:11
20 and 21 there was a break. >> Yeah.
2:31:15
Uh that was that was sub subst substantial but most people hadn't experienced it really because again it wasn't until 1919 that people were even started to think about taking on debt or or anything like that in the country to to then go trade.
2:31:30
It was really a function of General Motors by the way.
2:31:31
General Motors started uh loaning money to people to buy cars that it was a moral sin in America prior to that really to to take on credit like that was a very grubby thing to do. >> Sure. before that.
2:31:44
>> Have you have you looked into tulip mania at all?
2:31:46
It's it's like referenced so often and then I've heard stories about it.
2:31:51
>> Back then they didn't back then they were not doing the tulip thing.
2:31:54
>> I've heard that it's like it was actually very short. It was very isolated.
2:31:57
It was it was not global contagion and maybe some of it was not even as big as it might have just been somebody wrote down an extra zero in their accounting that day or for whatever reason.
2:32:07
Um, but yeah, it's a it's a it's a fascinating story that now has just grown and grown in infamy, but maybe actually wasn't as big as something like 929 1929 that deserves a few.
2:32:17
>> Maybe that's the next maybe that's a slim volume. >> Maybe. Yeah. Yeah. Yeah. Maybe. Maybe.
2:32:22
>> How do you do three hours of live television a day?
2:32:25
>> I don't How do you do three hours?
2:32:25
By the way, I just want to tell you I really admire what you guys are doing.
2:32:28
I didn't get to say this.
2:32:29
We've now gotten a chance to meet each other a couple of times and it's just a joy to be on with you.
2:32:35
I think what you're doing is amazing and it's it's really really cool to see your success.
2:32:39
I was so thrilled to see that piece in the New York Times over the weekend. I appreciate that.
2:32:43
>> Well, you're you're a hero to us and my favorite we've said this line on the show before, but when when we got to hang out in New York a few months back, you said uh said something to the effect of I do TV on my way to work and hearing about your process with this book, it's clear that you're just an absolute >> workhorse. Yeah.
2:32:59
When when are you guys publishing a massive extremely wellressearched book?
2:33:02
uh because like it seems like this 3 hours of TV is really taking it out of you guys and it is.
2:33:06
But I hopefully we hopefully we will learn and develop the muscle memory and the flow state and whatnot.
2:33:11
Uh we there's a lot to learn. This is a long game. We we've learned that. So, thank you so much.
2:33:17
>> You guys are doing it. You guys are doing it.
2:33:18
>> It's an honor to have you on the show.
2:33:18
I cannot wait to get into the book.
2:33:20
We we'll have to we'll be pulling more.
2:33:24
>> I'm just sad that I'm not in person and there's no gong. I meant the NASDAQ. >> Hit the gong.
2:33:27
Hit that gong for Andrew.
2:33:30
one of the welldeserved that we've had in a while.
2:33:34
>> Thank you so much for Let's do this again soon and have fun on have have fun on the book tour.
2:33:38
I feel like you gave us the perfect the perfect amount. >> Yes.
2:33:42
>> Like a little teaser, a trailer.
2:33:42
We still need to get into it. >> Great to see you.
2:33:47
>> Thank you so much for stopping by. We'll talk to you soon. >> Cheers.
2:33:49
>> And if you're watching or listening, please go pick up the book 1929. Uh it's available now.
2:33:54
You can get it on Audible.
2:33:55
You can leave it five stars. Leave a review.
2:33:57
Leave an ad in the review.
2:33:59
I think maybe you can technically do that. >> Probably get banned.
2:34:03
Um, >> leave an ad for Squawkbox.
2:34:04
Leave an ad for Dealbook. >> Yeah, to help out.
2:34:09
>> I I wanted so badly to put the Audible on last night as I was falling asleep, but I I would have had to wait a few more hours.
2:34:16
But, uh, that's going to be my night.
2:34:18
>> Yeah, I think the Audible's probably uh 40 hours long or something. So, just do it at 10x. >> Yeah.
2:34:24
Consider consider taking off next week and just and just walking and and listening to 1929.
2:34:30
>> No, this is going to be a fantastic book to to dig into.
2:34:32
Uh Tyler wants >> It's so cool.
2:34:34
It's so cool because there would have been a way to he Andrew could have done this book. >> Yeah.
2:34:40
>> In probably a year, two years.
2:34:40
He could have sold a ton of copies. Yep.
2:34:44
>> By just using he he would have made it would have been entertaining.
2:34:46
But the fact that he went and spent seven years like actually doing it properly even though uh even like he just really cares about fundamentally creating a a great product.
2:34:59
So well we have another offer another author joining us in the TBPN Ultra Dome.
2:35:05
Brian Potter is in the reream waiting room.
2:35:08
He's the author of Origins of Efficiency.
2:35:09
Thank you so much for joining us. We love Stripe Press. We love Stripe. We had Privy on. We've had Dark Cash on.
2:35:18
We've always enjoyed Strike Press's books and we're it's a pleasure to meet you. How are you doing? >> I'm good.
2:35:23
Thank you guys for having me on.
2:35:26
>> Uh thanks so much for joining.
2:35:26
Uh would you mind uh kicking us off with an introduction on yourself and the book and we can go into a bunch of questions about it, but I'd love to just kind of uh get a little bit of background for everyone on your journey to writing this book. >> Yeah.
2:35:40
So my uh I uh am an senior infrastructure fellow.
2:35:43
I work for the Institute for Progress, which is like a progress think tank.
2:35:46
Uh I'm best known to the extent that I'm known uh for writing this newsletter called Construction Physics, which is about buildings and infrastructure and and how to get stuff built uh in the US.
2:35:59
Um and my background, I my you know, before I did this, I worked in the construction industry.
2:36:05
I worked as a structural engineer for about uh 15 years like designing buildings and parking garages and >> water treatment plants and stuff like that. >> Yeah.
2:36:15
>> Uh and the industry always seemed like extremely inefficient to me like you know everything is you know so labor intensive.
2:36:19
It takes so long you know we're doing this similar work over and over and over again.
2:36:22
Uh it should be much more efficient should all be done in factories blah blah blah.
2:36:25
in factories blah blah blah. Uh and then in 2018 I had the chance to join this like big exciting construction startup called Catera that had raised this was back when SoftBank was uh >> I remember give it up for it was kind of a precursor I think Hrien was drawing from
2:36:43
it now like it was it was uh the like machine shop almost like uh >> yeah it was like you know it was this idea is like you know construction is inefficient because it's not done in factories right so we're going to into factorybased construction construction. Uh it was run by all these former uh
2:36:57
Uh it was run by all these former uh electronics manufacturing guys.
2:37:00
So like not like software guys that think that you know that like oh I worked at Amazon so I know how to do anything right.
2:37:05
It was like people who knew about manufacturing >> um and they were going to sort of bring that knowledge to like the construction industry, right?
2:37:13
So they raised a huge amount of money money got a huge check from Soft Bank uh raised like two3 billion in venture capital >> uh and it all went sideways, right?
2:37:21
It all uh it all went wrong and they they burned through it in in about three years and declared bankruptcy and there were various yeah reasons for that.
2:37:32
>> At what point did you at what point did you leave?
2:37:34
Uh I was there about until about a year uh before they went bankrupt.
2:37:41
So I was >> So you saw the Did you see the writing on the wall? >> Yeah.
2:37:45
I when I was there I was saying it was like when my but my time there was like a year and a half of ups and then a year of downs.
2:37:52
And then after about the sixth round of layoffs I uh I uh with you know after our engineering team got cut by like about 90%.
2:38:00
I was like need to time to bounce. >> Saw yourself out. >> Yeah.
2:38:04
Yeah, but I wanted to understand, you know, why things had gone so wrong.
2:38:10
Because part of it is just, you know, startups are hard.
2:38:12
>> Uh, building startups that are, you know, moving physical things around is is very hard.
2:38:16
There's very oper various operational missteps or whatever.
2:38:19
Um, but also I kind of came to believe that sort of the thesis that they had built the company around was kind of either wrong or just like not complete enough, like missing very large chunks of it cuz people had tried to do similar things that Catera had done many many times, right?
2:38:38
If you go back over history, uh there's like a huge graveyard of companies of like, oh, you know, light bulb will just we'll build buildings and factories and it'll be so much cheaper and I'll be able to make a huge amount of money.
2:38:48
I'll be the Henry Ford of Housing and just it just has never worked, right?
2:38:51
There's like this people have tried this over and over and over again and not been able to succeed. >> Will it work?
2:38:56
Because I have an opportunity to invest.
2:38:58
I'm a lucky I have a lucky opportunity. No, no.
2:39:00
I I I I actually did meet a company that that's uh taking taking another crack at this.
2:39:06
Uh do you think it'll ever work?
2:39:06
I I do think it will work but again I I you need to I wanted to understand why specifically it had been so hard in the past and why Catera and so many other companies had failed and what specifically you know would need to be true for it to succeed in the future.
2:39:23
succeed in the future. So it was it bec basically the the where I ended up was like I need to understand what specifically makes it possible for an industry to get like more efficient over time and what specifically is happening why when that
2:39:39
is is occurring and what is what sort of can prevent those things from happening and once I understand those mechanics I will be you know I will know what specifically would need to be true for some uh for some uh you know the construction industry or any industry to sort of improve improve over time. And
2:39:53
And so that was sort of the genesis of the book is like what specifically does it take for some process to get more efficient over time.
2:40:02
>> It feels like the entire book is kind of an abstraction on top of just this idea of like learning the learning curve.
2:40:07
We've seen this in semiconductors.
2:40:08
Everyone who follows like the AI boom is uh acutely aware of the learning curve that happened at TSMC.
2:40:12
Uh but you kind of draw a couple other historical analogies.
2:40:17
what stuck out to you as like particularly great examples of this efficiency in in in like going successfully and us actually driving down the cost and then what were the commonalities between that and and like what do they all have in common basically? >> Yeah.
2:40:34
>> Yeah. So I kind of went through and I looked at like you know dozens and dozens and dozens of different industries and and seeing you know how they had improved their operations over time and what specifically was was changing uh in them when that was happening and sort of you know and I looked at like industrial improvement systems right so like lean manufacturing
2:40:52
uh and like value engineering and all the in statistical process control and all these other things that like had you know specific ways you could try to make something more efficient and I kind of ultimately boiled all that down to like this c is, you know, a list of like a handful of things that you had to do to try to make some process more efficient. And if you could do any one of those
2:41:10
And if you could do any one of those things, you could kind of make it more efficient.
2:41:13
And if you couldn't do those things, those paths were blocked.
2:41:15
As it turns out, they are in the construction industry, you're you can't make your process more efficient, and it just gets more and more and more expensive over time.
2:41:24
And so, yeah, I looked at like a lot of different industries.
2:41:26
I go really into uh you know, Henry Ford and how he sort of dropped the cost of of the Model T.
2:41:32
Uh I look at sort of the evolution of like nail manufacturing which is uh in the in the sort of the 19th century go back even farther and how they changed the technology to make over time to make nails which started out like hand forge nails like a blacksmith like hammer and steel and they found a way you know machines that could sort of emulate that process and they replaced those machines with even better machines and uh so on.
2:41:54
So there's like dozens and dozens and dozens of examples in the book of sort of specific things uh that have gotten cheaper over time and the lessons that we can kind of learn from those things.
2:42:04
>> How naive is it to just say uh what's remain stubbornly high costwise?
2:42:12
Housing, medicine, education.
2:42:12
What do those have in common? Regulation.
2:42:14
How how naive is it to just throw regulation is the problem at those particular industries?
2:42:21
Uh that's a big part of it for sure.
2:42:24
I mean the problem is that like everything has gotten more regulated, right?
2:42:27
Like manufacturing included.
2:42:31
>> Um so it's it's like that's like part of the puzzle, but it doesn't really tell you the whole thing because even in PL, you know, the problem, you know, to take it back to construction, >> uh the problem of like construction productivity and not getting cheaper to build stuff is really something you kind of see around the world.
2:42:44
of see around the world. you like I I have a graph in there that's like >> construction costs in like a variety of different countries and they all kind of this you know scary line of going up and uh to to the right over time >> even the countries without building codes and ownorous HOA you know less
2:43:01
labor yeah or like different regulatory regimes and stuff and there's certainly places that like do better than the US in in various things like in various ways of building the US is like very far from the efficient frontier um but we have a very hard time of like pushing
2:43:15
ing that efficient frontier for so like regulation is like a big part of it but that's kind of one of the sort of things I think a takeaways from the book is that it's not just regulation like you could have all the you know remove all the regulation you wanted and you'd still run into these sort of various
2:43:30
physical constraints and market constraints that prevent these sort of efficiency improvements uh in some cases >> how are you thinking about energy in America we've we've we've gone through this AI boom now where uh we've scaled up the existing capacity of data centers. We're building new data centers
2:43:46
We're building new data centers and it feels like the last link in the chain is can we build a 100 nuclear reactors in America in 2030 to stay on track with like the most aggressive projections.
2:43:57
Um is there anything unique about uh obviously energy production is a construction problem but is there anything unique that you found in the energy industry that uh folks might be able to learn from?
2:44:10
Yeah, I'm well, you know, I write a lot about energy on on the on the newsletter.
2:44:14
Uh I don't have a background in energy, so it is a lot of me like groping my way towards like some understanding of of how this industry works.
2:44:21
Uh I'm a really big solar guy.
2:44:24
Solar has like a really lot of nice properties that like makes it easy to sort of uh make efficiently at like very very large scale.
2:44:31
very large scale. There's this really interesting paper um but basically it's this like big graph of like the sorts of energy technologies that have become cheap and the sort of energy technologies that have not become cheap and the ones that have become cheap are these sort of things that like you can
2:44:45
make repetitively in very large volumes and you don't need like a lot of customization of and so like solar panels which are like you can make in like really really really really enormous numbers and you can kind of plop down wherever it doesn't need a lot of like sightsp specific customization uh are kind of in this like very cheap quadrant. And then something like a
2:45:03
And then something like a nuclear reactor which you make in like much much smaller numbers and like needs a lot of like specific design for the specific reactor that you're building is sort of in the much more expensive uh quadrant.
2:45:14
Um and so solar and like the batteries which like really complement them really nicely is like a really good way to sort of make this stuff really cheap.
2:45:24
these cost curves have like gone like down like a lot and there's like >> no sign that those are stopping anytime soon.
2:45:31
And so um you know that just you know those this aligns with like so much of what we know about what what it takes to sort of make something inexpensive that I kind of see that like biting off a very large chunk of the of the energy uh that we produce uh in the US assuming you know take it back to regulation assuming that sort of regulation interferences don't kind of get in the way.
2:45:54
>> How how often did you find uh capital being a constraint lead to more efficiency?
2:45:59
I think every startup founder has a has like an example of a time when like maybe if they they threw uh you know a hundred people at a problem they would have gotten a different solution but they only had a handful and so they were able to create some novel uh uh a more efficient way of doing something uh or we saw this with like deepsek and and having having potentially fewer chips and creating a more uh efficient architecture.
2:46:24
Was that a common theme at all in in uh in the >> Yeah, it's it's interesting.
2:46:30
I think there's kind of like two sides of it.
2:46:35
One is that in some cases like what a repeated theme of the book is that like scale is really really very important and if you can the more you can make of something the more opportunities you have to make that less expensively and often scale is like very very expensive
2:46:49
right so like one of the sto the story of like container shipping over time is a story of like needing really really enormous investments to like build these big giant ships which are like cheaper per container that they're transporting but very expensive overall. all and also
2:47:04
all and also like really really big expensive terminals to sort of handle those ships.
2:47:10
And so only like a certain number of like countries could like invest in these like giant terminals that were needed to sort of service these huge ships.
2:47:17
And so you know cost of transporting these goods fell a lot but like there was winners and losers in who sort of gained gain from this technology development.
2:47:26
It was really the people that could afford uh to put the money into it to do it.
2:47:29
Um, but then on the other hand, you also see cases where kind of like you talked about with Deep Seek, people working under these constraints were able to come up with like really improved ways of of doing something that were much cheaper and much better than what was uh what came what came before.
2:47:48
So a kind of example of that would be like Toyota's manufacturing methods which were like Toyota production system which evolved into lean manufacturing.
2:47:56
uh those kind of were created in this environment where like they couldn't develop these like mass production methods that Ford had used because their car market was so much smaller and it was so much more varied.
2:48:06
They couldn't just make a million of a given model or whatever that they had to find ways of like producing this stuff efficiently that didn't require this like massive capital investment basically.
2:48:17
And so that was sort of the genesis of that those those ideas.
2:48:22
And so yeah, I think there's definitely cases where yeah, you need like a lot of investment to sort of find ways to make this cheaper, but then there's also cases where it's like also working under constraints of not very much investment has has uh been important as well.
2:48:35
Are you at all optimistic that uh this data center boom will teach a generation of people uh uh uh that you can build big things quickly and efficiently if you just basically put your mind to it because there's like a lot of from from an energy standpoint just like you know if you look at what what Elon has done with um Colossus 2 he's basically doing the impossible.
2:49:00
a lot of people would have like looked at that project and said it's not possible and so that sort of it feels like that sort of mindset of like we're just going to make it happen.
2:49:10
Uh these is being applied to data center development but then presumably those people can say I'm going to build a bridge and uh they can imply that same kind of approach elsewhere.
2:49:24
>> I I certainly hope so.
2:49:24
We're certainly building like an enormous amount of this infrastructure like it's really really unprecedented.
2:49:29
there's all these crazy stats like you know data center spending is now uh exceeded like office building spending or or something like that which is which is totally wild.
2:49:39
I guess one thing that worries me is that historically people have been like you know not really cared about data centers.
2:49:49
They've been happy to just like let them get built and the jurisdictions sort of collect the tax revenue for it and and not really worry about it beyond that.
2:49:56
uh as like the buildout of them is like going forward and there's like more and more of these data centers and they're bigger and larger uh you're really starting to see like a grassroots movement of people like you know the nimbies sort of now being opposed to data centers in a way that they weren't before.
2:50:12
So like Virginia which historically has like been you know a major place where data centers get built and has basically been fine with them getting built there.
2:50:20
Now you're starting to see like residents oppose them more and more and you're starting to see, you know, grassroots movements around in different states uh springing up to oppose these things.
2:50:32
So that worries me a little bit and I hope the sort of forces of getting these things built and enthusiasm about building infrastructure are are stronger than that or um but uh you know it always seems like uh the NIMBI forces are are quite strong.
2:50:48
So hopefully they uh they uh they don't build momentum. >> They're OP.
2:50:54
>> I have one last question.
2:50:54
Um there's this post by Rune who's talking about Dan Wang's new book.
2:50:59
Uh and he says the general elite consensus now is that industrial process is a technology that lives in the heads of people.
2:51:06
And he goes on to say that it was a mistake to let so much lowv valueue industry be offshored due to the loss of tacid process capital.
2:51:14
And I was just wondering what your thoughts were on this idea of industrial process knowledge that there might be a few key people that actually know how to build something at scale and uh just what the ratio how how steep is the power law of human capital when it comes to largecale industrial manufacturing efforts.
2:51:36
>> Yeah, I think it's dead on.
2:51:36
And I think that's absolutely very important and I talk about that at various parts uh in the book how it's often really hard to transfer like manufacturing or production technology from one place to another place in part because it's hard to like pick up and lift these uh process knowledge which is just in the heads or like embedded in this web of relationships and so it doesn't necessarily even exist in explicit form, right?
2:52:01
It's just like this is this system that turns out to work very well and you can't just like recreate it because we don't essentially know how it how it came to be in the first place.
2:52:10
And then you know we talked you talked about a little bit about the learning curve earlier and that's kind of this really similar idea where a lot of your improvements to some technology over time come from just like the factory floor and learning how to sort of do this um better and better over time, but it's very coupled with actually physically doing the the work.
2:52:28
And so that's one thing that I yeah I I think is is really important is that often times just technological progress is coupled to sort of this like process factory knowledge of actually having the experience uh doing things.
2:52:41
experience uh doing things. One one really fun sort of example of this is um during the the early days of of the space race where the US was having like a really hard time uh building their rockets and there's a part where like you know because of various political things uh uh the uh Navy was going to send up their rocket uh first they were
2:53:04
going to be like the first ones to sort of launch a US satellite into space and Wernern von Braonn who was the German rocket scientist who then had been brought over to the US and was working for the army He goes to some like, you know, military leader and he says, "Look, you can tell these Navy guys they can do whatever they want. They can take
2:53:20
They can take my rocket and they can paint Navy on the side of it and do whatever they want, but they need to use my rocket and not theirs because my rocket will work and their rocket won't."
2:53:30
And then what ended up happening was they didn't listen to him and the Navy launched their rocket anyway and it didn't work.
2:53:36
It blew up on pad and then so finally they listened to Wernner von Braonn and just launched his rocket and that's when we finally got uh a satellite into space using Ver Wernner von Braonn's uh rocket and then of course Wernon Braun was like a major force in the Apollo program >> as well.
2:53:50
So it was like you know the German the German rocket knowledge that had accumulated during World War II was like very very important and both the U both the Soviet and the US uh their early rocket development efforts were basically built on this German knowledge that had been accumulated.
2:54:05
So this process knowledge and like this you know expertise that gets embedded in the heads of these of these people working at the sort of forefront of technology uh is not easy to sort of recreate.
2:54:15
Um, I think it's very very important.
2:54:20
>> Well, thank you so much for stopping by the show.
2:54:22
The book is Origins of Efficiency from Stripe Press.
2:54:24
It's available now for purchase.
2:54:26
Highly recommend picking it up. >> One click on Amazon. >> Thank you.
2:54:30
Stripe checkout hopefully. >> Hopefully.
2:54:33
>> Uh, we will talk to you soon.
2:54:33
Have a great rest of your day. >> Thanks. >> Thank you so much.
2:54:38
>> Um, really quickly, let me tell you about adquick. com.
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2:54:50
Speaking of founder mode, we have a founder in the reream waiting room.
2:54:54
Let's bring him in to the TVP ultradome. >> There he is. >> How are you doing? Good to meet you. >> Hey, I'm doing great. How are you guys doing?
2:55:02
>> We're doing fantastic. >> Fantastic.
2:55:03
>> Uh kick us off with an introduction on yourself, the company, the news. We're excited. >> Yeah. Uh I'm Terry Singh.
2:55:08
I'm the founder and CEO of Flow Engineering.
2:55:10
Uh, Flow is a collaborative development platform specifically built for next generation hardware companies.
2:55:16
Our customers design things like rockets, airplanes, cars, nuclear reactors, and they use Flow to design, build, test, and iterate massively faster than they can do today.
2:55:26
Basically, the way to think about it is we're taking the last 30 years of software development practices, everything from agile to continuous integration, continuous testing, and we're bringing that to the design of massively complex hardware products.
2:55:38
Uh, our news today is that we raised our series A with Sequoia Capital.
2:55:43
Uh, uh, and >> how much how much did you raise? >> 23 million. >> There we go. >> Congratulations. >> Uh, amazing.
2:55:54
I love that you uh you started uh building hardware yourself and and then figured out along the way, I got to build software.
2:56:01
I got to build SAS for this.
2:56:04
>> And what uh what are you replacing most of the time?
2:56:07
Is it is it Sounds like am I getting it right?
2:56:10
You basically built you built an internal tool for yourself initially while you guys were building rocket engines and then realized like hey seems to be pretty valuable. >> Yeah, exactly.
2:56:19
So like a little story of the company.
2:56:22
Uh I'm a mechanical engineer.
2:56:23
I became an engineer cuz I wanted to build machines that mattered.
2:56:26
Uh went into the industry went to companies like BA systems and BP and just realized the fundamental approach to designing hardware was completely out of date. Mhm.
2:56:35
>> So the company started out as a hardware company, not a software company.
2:56:37
We were called the rocket company.
2:56:38
We built the world's fastest design consultancy for hybrid rocket engines.
2:56:43
The best people in the world could go from requirements to to detail design in 12 weeks.
2:56:46
We could do it in 2 hours.
2:56:47
And the reason we could do it in 2 hours is we built this internal platform for ourselves called Flow.
2:56:52
Uh that massively integrated and accelerated the design process.
2:56:56
And that's what became has become flow today.
2:56:58
So are you you're just simulating physics like what is the actual like you're you're I imagine you're basically you're building a workflow and then you're able to are you able to get a good read on if the the the process or the the product will work without actually testing it in the real world or what does that look like? >> Yeah.
2:57:19
So let me give you the 101 on like hardware development versus software development.
2:57:23
In software development, we have canban boards and tickets and you build a spread, you burn it down and you go for it.
2:57:28
When you're designing something like a rocket or an airplane or a car or nuclear reactor, it's much more complex.
2:57:32
The way that we fundamentally design and collaborate are using these things called requirements.
2:57:38
Let's say you're building a rocket, you'll say, hey, I need to get this much payload to this delta to this uh orbit.
2:57:44
And then to do that I need to design this first stage and this second stage.
2:57:47
And to do that and you go all the way from these top level requirements to very very low level temperatures, pressures, masses, and design criteria that engineers will use day-to-day.
2:57:55
The big problem is that when you're designing a like a humanoid robot or you're designing a reusable rocket or you're designing a self-driving car, you don't know whether those requirements can be met or not.
2:58:06
Like 10 years ago, you would have these fixed requirements and you'd be able to execute against them.
2:58:11
you'd build a big gant chart and you'd burn it down.
2:58:13
In a modern massively complex system, our products are so complex that we have no idea whether we can design it.
2:58:19
The requirements are changing on a nearly daily basis and the design is changing on a nearly daily basis too.
2:58:24
So what flow does is it's a single source of truth for all of the company's requirements and systems information and we glue all the requirements together, all the design together and we have continuous integration between the requirement side and the design side which enables teams to design and propagate changes much faster than the cat is today.
2:58:43
Are you aiming to go straight to the Fortune 500, the Fortune 100, the biggest companies in the world that are manufacturing at scale?
2:58:50
And uh maybe it's a lot of steak dinners and a really hard pitch that you get a couple of those clients and you're in business or do you want to focus more on startups, smaller companies, scaleups, like what's the sweet spot for you right now?
2:59:03
>> Yeah, we um we we think about this very deeply.
2:59:05
We regularly turn away Boeing and Airbus and these massive conglomerates.
2:59:09
So here's a way to think about it.
2:59:11
the hardware engineer >> mogged.
2:59:16
uh >> you can't >> you're like sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry sorry we're we're busy helping the next generation create the next Boeing >> yeah exactly um so the way to think about it is the hardware engineering
2:59:26
industry is going through a generational change right now and it's this generational change from old school waterfall think NASA Loy Martin to new school agile think Nandural the way that SpaceX Nandural and Joby and Archer work are much more like software companies and traditional legacy primes. They
2:59:43
They don't design top down.
2:59:45
They design bottoms up and things are changing on a nearly daily basis.
2:59:49
>> We're very very very specifically built for that new way of working in the same way this happened in the software engineering industry.
2:59:56
So in the 2000s we went from old school uh waterfall to new school agile and companies like GitHub came about to serve that market.
3:00:03
Now GitHub didn't go to IBM and say we're going to build you a slightly better gant.
3:00:08
They went to companies like Google and Facebook when they were five people and they said this represents the new industry and 10 20 years from now these small companies like Google and Facebook will be the mass market and then when IBM and Oracle wake up they will change how they work and they'll come to GitHub because they are changing to an agile way.
3:00:27
So that's what we're doing.
3:00:27
We're exclusively focused on next generation aerosp space nuclear defense companies.
3:00:34
We're growing very very quickly with those guys and we're making that workflow as good as it can be.
3:00:39
>> How is it going in the Gundo? What's the update? >> Uh yeah.
3:00:43
So this is like a global movement but as you mentioned the epicenter of the global movement is Elsa Gundo which is in LA.
3:00:49
So everything from like rockets, airplanes, robots, cars, uh autonomous submarines are being designed like the the five or 10 square miles which is Elsagundo.
3:00:59
Um Elsundo is is amazing.
3:01:02
I think it represents something like 70% of our customers.
3:01:04
And the companies in Elsagundo design and iterate at a speed that Boeing and Loy just can't comprehend.
3:01:11
They're designing massively complex systems.
3:01:13
They're designing and iterating them faster than anybody thought they could do.
3:01:17
And that is the reason they will become so much more competitive than the traditional primes that the traditional primes just can't keep up.
3:01:25
And I imagine what an advantage that is for you being able to walk a few blocks and like see your product in action and actually get that real-time feedback and then just be on that same you know iteration cycle with your customers.
3:01:37
Uh >> yeah we we have a kind of crazy story which is um most of our like most of the other tools in the market came from Elsa Gundo.
3:01:45
We actually came from London and we were engineers and we wanted to build um and the European market just didn't want speed or at least the market that 5 years ago didn't want speed.
3:01:56
years ago didn't want speed. So we sold into traditional legacy companies and they they fell in love with the dream and the mission but they didn't really they didn't really use the software and then the Elsagundo market found flow and
3:02:07
they pulled us into it and what started out as just one or two companies working in this crazy new way designing and iterating like a software company have ended up becoming the new market and that represents a really important part of our customer base. >> Well congratulations in the funding news
3:02:20
>> Well congratulations in the funding news congratulations on the progress and good luck to you.
3:02:25
Thank you for >> when you announce the bee. Come on over. 20 minutes.
3:02:28
We're 20 20 30 minutes from the Gundo Hollywood. We'd love to have you. >> A sweet. I'd appreciate it.
3:02:33
>> Bring the gong in person. We'll talk to you soon.
3:02:35
Have a great day for >> the whole team. Catch you guys.
3:02:38
>> And when you announce that series B, you know what you got to do. >> I know. >> Go over to getbasel. com.
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Your bezel concierge is available now to source you any watch on the planet.
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Seriously, any watch cape.
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Take a couple mil off the table in secondary. Put in an FPJ.
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Put it in a Rolex Daytona. deploy it. >> Put it in a tack.
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>> Get a couple aqua >> before you before you get the starter home. >> Yeah. >> Get a starter hitter. >> Starter hitter.
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And then uh book yourself a vacation on wander. com. Find your happy place.
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Book a wander with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, and 24/7 concier service.
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It's a vacation home but better that never gets old.
3:03:15
Jordy, >> uh >> I just saw a post that I'm not going to read on the timeline. That is funny.
3:03:20
Um but uh anyways, uh story. >> Cool. Cool story. No.
3:03:25
Uh what I was going to say, I was going to check the timeline before we get off.
3:03:27
We uh have to enter our fourth and then fifth hour of podcasting.
3:03:33
>> So glad we get to Jackson Doll is, I believe, already here >> uh at the in the Ultra Down. >> Breaking news.
3:03:41
We're doing >> we're going to be doing his podcast right now.
3:03:44
Uh so >> so head over there, subscribe, turn notifications on to Dialectic, and then you'll hear us talk more if you're not sick. >> Yeah.
3:03:52
I don't know when this episode will come out, but if you message Jackson now or you comment on one of his posts, I'm sure you can ask uh some questions uh there.
3:03:59
And uh we hope you have a fantastic evening.
3:04:02
We will be back tomorrow for another beautiful day of technology.
3:04:09
>> Hopefully, it's another cozy, warm day and we can put the fire on.
3:04:10
I really enjoyed the fire.
3:04:13
>> We should have the fire on for for Jackson's podcast.
3:04:15
>> We'll we'll Yeah, we'll consult with him.
3:04:16
Uh thank you so much for We'll see you tomorrow.
3:04:19
>> See you guys tomorrow. Cheers. Thank you.