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Today is Tuesday, January 20th, 2026.
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We are live from the TVP and Ultra Lounge, the temple of technology, the fortress of finance, the capital of capital. Ramp, time is money. Save both.
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4:55
Davos, not the best way to save money.
4:58
Apparently very expensive if you go, but a lot of people have been and for good reason because there's a lot of news happening in Davos.
5:03
Uh mainly, a lot of it's focused on Trump, a lot of it's focused on Greenland.
5:07
I'll give you a little tour of the Wall Street Journal.
5:09
Trump's amped-up rhetoric on Greenland puts issue center stage at Davos.
5:12
Why don't you pull up the cover of the Financial Times, too?
5:16
The Financial Times, yeah, you want me to do this bit? Here we go.
5:21
Uh well, uh you know, the markets are in turmoil.
5:23
The Dow slid 800 points, Treasury prices are dropping.
5:26
Uh you know that if you're investing, you got to do it on public. com.
5:31
Investing for those who take it seriously.
5:32
Stocks, options, bonds, crypto, Treasuries, and more with damn good customer service. That's right.
5:38
So, uh the front of the Financial Times, it says Trump keeps seizure of Greenland by force on table as trade tensions mount.
5:48
And so, um this is one of the most aggressive images that I can imagine running on the front of a international newspaper.
5:56
Now, the Financial Times of course is uh is a British paper, so much less uh just different dynamics with the current American administration.
6:07
Uh you know, Trump I think has a lawsuit going with the Wall Street Journal.
6:11
There's a whole bunch of things that are are going on with the American media.
6:13
Um but over in the Financial Times, they print some wild stuff and they printed this image of a of a Danish soldier pointing a gun at the camera.
6:22
So, Danish soldiers are exercising on Greenland.
6:27
>> that's been around guns knows that that pointing a gun at anyone >> barrel of a gun. Crazy.
6:32
even even a photographer to get a cool picture is typically just completely off-limits. >> Yeah, yeah.
6:38
And so, Uh But they went there.
6:41
>> what what this says to me is that uh you know, the the Danes uh said, "Hey, the head of the army has been flown out to the autonomous territory.
6:48
Uh Danish troops are on the ground in Greenland and we're doing a photo shoot.
6:53
We're getting a soldier with a sniper rifle or an assault rifle.
6:58
Uh we're going to point that at a camera person.
7:00
We're going to take that photo and then we're going to send that to the editor of the Financial Times and >> We're going to run it on the front page.
7:06
Of course, the Danes don't have the authority to just put anything on the front page, but they pitched it and clearly they sent the photo and the Financial Times editor enjoyed it, so he put it on the front page.
7:15
But it kind of gives you a little bit of a taste of of what's going on.
7:18
The Wall Street Journal's also covering it.
7:19
Uh Trump threats on Greenland mobilize allies.
7:20
Uh that is taking center stage at Davos, but this is a technology show.
7:26
This is a business show and we're focused on what Dario Amodei said at Davos. We will pull this up.
7:33
First, let me tell you about Railway.
7:34
Railway simplifies software deployment, web apps, servers, and databases.
7:38
They run in one place with scaling, monitoring, and security built in.
7:41
So, um let's pull up the clip of Dario Amodei on stage.
7:46
He's the co-founder and CEO of Anthropic.
7:48
He calls out Trump's policy around Nvidia and China. Let's play the clip.
7:55
>> into the world, right?
7:55
When we're when we're when we're um uh you know, competing against other companies for enterprise contracts, we see just honestly and candidly, we see Google and we see OpenAI.
8:04
Every once in a while, we see a couple other US players.
8:09
Um I I have almost never lost a deal, lost a contract to to a Chinese model.
8:16
But now you have the Trump administration and I think you've already protested about this giving high-speed chips, Nvidia chips to the Chinese. That's right. That's right.
8:26
The thing that is holding them back, and they've said it themselves, the CEOs of these companies say, "It's the embargo on chips that's holding us back."
8:32
They explicitly say this.
8:34
And and now, indeed, you know, there are some policies and I hope they change their mind to uh you know, to explicitly send not quite our latest generation of chips, although it was reported that even that was being considered, um but you know, the the generation of chips that's that's just one back, that's still extremely powerful.
8:53
Um and we are many years ahead of China in terms of our in terms of our ability to make chips.
9:01
So, I think it would be a big mistake to ship these chips.
9:02
Um you know, the the the analogy I thought of, if you think about the incredible national security implications of building model building models that are essentially cognition, that are essentially intelligence, [clears throat] right?
9:18
I've called where we're going with this a country of geniuses in a data center, right?
9:21
So, imagine 100,000 peop- 100 million people smarter than any Nobel Prize winner and it's going to be under the control of one one country or another.
9:30
Um I so so I I I I think this is crazy.
9:34
I think it's you know, it's a bit like, you know, I I I don't know, like selling selling, you know, nuclear weapons to to North Korea and you know, bragging, "Oh yeah, but we made the So, your your your friend your your friend David Sacks is basically arming the Chinese.
9:48
I No, I I I I wouldn't refer [laughter] to anything Trying to put words in his mouth. Yeah.
9:56
is is is you know, akin to Yeah, it's not not not not well.
9:58
Okay, I want Jordi's reaction. I want Tyler's reaction.
10:02
But first, I want to tell you about Labelbox, reinforcement learning environments, voice robotics evals, and expert human data.
10:09
Labelbox is the data labeling factory behind the world's leading labs. Uh Tyler.
10:17
Tyler, what's your reaction to that?
10:17
How do you interpret that?
10:20
How big of an issue is the China question right now?
10:25
What are you reading into Daria's rhetoric there?
10:26
Yeah, I mean I think it's uh like fairly reasonable if you basically think that AI is going to be AGI, it's going to be this massive you we're going to get 10% GDP growth.
10:34
Um cuz at at some point it's like >> [clears throat] >> uh if it's just like economy versus economy, like we got to be better.
10:41
Yeah, that that's something that's sort of lost.
10:46
Like cuz there's also the point where Just competition.
10:47
Yeah, that like if you're worried about safety also.
10:49
So there's like two ways, right?
10:50
If if you think AGI just is going to be massive uh you know, economically speaking, and then also if on the safety issue, right?
10:58
Because if you think um like maybe China is going to be less concerned about safety, they're not going to be as worried about alignment.
11:03
That's like obviously a massive danger.
11:04
You don't want it to you don't want to give the technology to people who don't uh you know, worry about safety aspects.
11:08
The funny thing about in America, we're like AI could lead to 10% GDP growth.
11:12
And China's like, "Oh, you mean what we did in 2007 when we were growing at 14% GDP growth?
11:20
Or should we go back to 1970 when we grew at 19%?
11:23
Or should we go back to 2004 when we were 10. 1?
11:25
Uh or 1992 when we were growing at 14. 3%?
11:32
Or even in 2021, they had a 8. 6 GDP growth."
11:35
They know 10% GDP growth over there. >> They felt it.
11:38
>> They'll do it with or with without AI chips.
11:40
But obviously, AI chips are big are big.
11:42
One dynamic that's interesting is China has obviously a massive advantage [clears throat] in robotics. >> Yes.
11:48
And right now we have a an advantage in the models. >> Yes.
11:51
And if that kind of continues >> But also also the chips, like the the data centers. Like we are data rich.
11:56
So I'm saying like I guess like robotics stack, AI stack.
12:02
And it'll be interesting to see how is obviously if you have an advantage in one area, that might help you gain an advantage in another area, right?
12:08
But we'll see which one ends up being more uh more impactful.
12:13
Let me tell you about Cisco.
12:15
It's critical infrastructure for the AI era. We love Cisco.
12:19
We're happy to be partnered with them.
12:21
And let me also take you through the Linear lineup today because we have some great guests on the show.
12:25
We have Martin Shkreli joining at noon, Bradley Tusk at 12:30.
12:31
>> with Martin Shkreli, he's an American businessman and investor.
12:35
>> Lucas Zenger is coming in.
12:35
We have a surprise for everyone.
12:36
We're going to be taking a look at his car.
12:39
We're very excited about that.
12:40
And then we have the Lambda lightning round.
12:41
Linear, of course, is the system for modern software development.
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12:52
Let's click it over to Palantir CEO Alex Karp who shared some commercial lessons of AI on the battlefield.
13:01
There's a clip from him from Davos.
13:03
And there's a little Easter egg in this video for the true TBPN ball knowers for the video for the TBPN fans.
13:10
>> I know what you're about to say.
13:11
>> So watch this clip and you can tell me if you identify A former guest. Former guest.
13:17
>> Enterprises in general, not all enterprises, tend to one of over time become like every other enterprise.
13:22
So if you take five, you know, A enterprise and B enterprise and C enterprise, they're in the same market.
13:28
Their tech infrastructure is trying to make them into the same enterprise.
13:33
Uh they have the same org chart. Sure.
13:36
They have presumably roughly the same they don't have the same data infrastructure.
13:39
And what you learn on the battlefield is that and in life is that's that's not particularly valuable.
13:46
What is very valuable is an enterprise can do something no enterprise in the world can do.
13:50
And so that is the goal of every single military in intelligence service.
13:55
In fact, all these intelligence services and military have their own specialization.
13:58
And so when we went to commerce, like what we're saying is how can we make your insurance company the way you underwrite?
14:06
How can we make that to your tribal knowledge about underwriting?
14:09
How can we transform this to >> pause. Okay, go back 1 second.
14:16
>> [laughter] >> Go back 1 second. Okay. Pause.
14:21
>> [laughter] >> Okay, it's very hard to see.
14:22
But behind the guy to right Behind Alex Karp.
14:28
Behind Alex Karp, there's another man and behind that man, next to the WEF logo, is a man who has been on the show.
14:36
>> Philip Johnston, the co-founder and CEO of Star C Wait, I thought you were talking about Satya Nadella. Wait, what?
14:42
I think that's Satya in the back.
14:44
No, I'm talking about the guy right there that you can see.
14:46
That's Philip from Star Cloud.
14:48
I saw him go to Davos and I was like, "This guy's on a generational run."
14:52
This whole time Maybe it's not. I think it is.
14:54
I'm really sorry, Philip, if I got this wrong.
14:57
But I that looks that looks a lot like you. >> it wrong, too.
15:00
That looks a lot like [laughter] you.
15:01
We might just be seeing things.
15:04
>> We might be seeing things.
15:04
We might be hallucinating.
15:05
But the one thing we're not hallucinating is Lambda.
15:07
Lambda is the superintelligence cloud building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands.
15:16
Anyway, enough with the Easter things.
15:19
>> whole time I thought you were I thought I I really was thinking the guy in the back was Satya. >> No, no, no, no. Kind of hard to tell.
15:23
I don't think that's Satya.
15:24
I think that's I think that's Johnston from Star Cloud.
15:28
I did see him go to Davos.
15:28
So it's not crazy, but he'll probably correct me if that's not him.
15:33
Anyway, I would love an explainer from Ragav around the recession indicator YoungBoy Never Broke Again.
15:40
I I'm familiar with NBA YoungBoy, but I'm not familiar with the recession indicator.
15:46
So I would love to get some more information from you folks on this.
15:50
Let's dive in and and dig into what Alex what Dr.
15:53
Karp actually said on the on the stage at Davos.
15:55
But first, let me tell you about Finn, the number one AI agent for customer service.
16:01
If you want AI to handle your customer support, go to finn. ai.
16:03
So um it's an interesting pitch.
16:06
It's it's particularly interesting talking about just more and more custom systems in this idea of, you know, software gets built.
16:16
It a whole bunch of companies are doing things a manual way.
16:18
One company extracts that and sort of factors out that business process, turns it into enterprise SaaS, is sold to all the different companies.
16:28
Now what Karp is really saying, it sounds like, is that every company will have some sort of custom implementation that will be way more flexible and way more tuned to their specific businesses.
16:39
This is sort of the Palantir pitch.
16:41
They'll come in and build something that's semi-custom, semi on top of of their system that they've already built.
16:46
And it's an interesting like blurring of the lines from you want something that that checks all your boxes, but in the future, will you really want if you're at if you're a large enterprise, will you really want to be vibe coding your own solutions to everything?
17:00
Maybe, but you probably won't need a system of some sort of foundational elements.
17:07
And And that's like the pitch for the ontology stack, understanding how the data links together.
17:13
Then as you build on top of that, you you have a more solid foundation.
17:17
Seems like a good a good pitch.
17:21
Would be interesting to see how this is like where the rubber meets the road. >> And at what level?
17:25
The big question with Palantir right now is you know, that that they work with the largest companies and organizations in the world, obviously the the military among them.
17:35
But will they go down the stack and have more, you know, they have AIP.
17:38
They are bringing more startups onto the platform.
17:43
Will there be a world where more sort of mid-market enterprises, sub $10 billion companies are are thriving with a Palantir back system?
17:54
Um certainly would be good for the business to just have more customers on board.
17:57
But we'll we'll be, you know, a dynamic that grows. Anyway, Eleven Labs.
18:01
Build intelligent real-time conversational agents.
18:06
Reimagine human technology interaction because uh yesterday when we spent 45 minutes talking about X articles.
18:12
I know everyone loved that.
18:15
>> [laughter] >> Uh because I did summarize it in in a in a newsletter piece that you could have read in 2 minutes.
18:19
Uh but that it was fun talking for 45 minutes.
18:22
One of the things that I brought up was that maybe Eleven Labs should do an article reader that would allow you, since there's articles all over X now, uh to just click a button and have Eleven Labs read to you.
18:32
Well, they built it and and it's already live. So very very exciting.
18:37
Uh Eleven Reader is the account here.
18:40
It says articles everywhere.
18:41
You can save them with either Chrome extension, listen on the web, or send it to your phone in under 10 seconds.
18:47
For the bookmarkers out there, for the people that are finding those articles and saying, "I'm going to book those."
18:53
Probably a pretty reasonable way to actually get through your stack of of articles that you've been meaning to read, but you were busy and you just saw it and you saw that it got a lot of likes and a lot of engagement and you want to dig in, but you don't have the time.
19:04
So you're going to head over and do that. Anyway, vibe. co.
19:06
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19:16
>> head over to Chinese Vice Premier He Lifeng over at Davos. Okay, what did he say? Quick quick 10 seconds.
19:23
>> Never seeks a trade surplus.
19:23
On top of being the world's factory, China hopes to become the world's market.
19:26
Let's watch the Chinese Vice Premier.
19:31
>> For economy and trade, we never seek trade surplus.
19:33
On top of being the world's factory, we hope to be the world's market, too. For economy and Mhm. It was an accident.
19:42
>> [laughter] >> We didn't we didn't mean to do this. It was an accident.
19:45
It was not our intention to develop a massive trade surplus Yeah. with the world.
19:51
>> I feel like I feel like you I mean you know not to go back to 11 Labs, but you have a lot of flexibility with the translator that you choose at one of these events.
19:57
How do How are you not going with an Arnold Schwarzenegger? You know? Totally.
20:01
Yeah, like you could have anyone be your translator.
20:03
So, why not get throw in a Morgan Freeman or, you know, uh Just just any type of really like incredible >> Rogan. Yeah, Joe Rogan.
20:14
>> He already is announcing UFC.
20:14
Get him on the microphone, translate it for him, and then he reads it out to the audience, and it sounds like your Joe Rogan voice is out there. I like it. >> it.
20:25
Anyway, uh I mean it's it's it's I I I think this is positive.
20:28
You know, we were just talking to Matt Grimm yesterday about uh you know, the the West versus China and and global competition.
20:35
And like I think all of that stuff is important.
20:38
I think what Dario is saying is important, but I still come back to this idea that like no one wants war, no one wants, you know, everyone wants positive some relationships.
20:47
And so, it is good to see, you know, global leaders coming together.
20:52
Better than everyone just being holed up and posting at each other on Red Book and Truth Social.
20:56
I I I I like I like an economic forum.
20:59
I'm I'm I'm I think Davos is back.
21:01
That that That's the real lesson from this year, I think.
21:04
I think the fact that Trump was going was a big pull.
21:06
There was a lot of coverage, a lot of interesting discussion around it.
21:10
And Davos really really pulled together a fantastic group this year.
21:14
And is definitely breaking through in the tech community, in the business community, in the political community uh in a way that I don't remember it being as important the in last year.
21:25
And so, little bit of a comeback. You love to see it. Console.
21:30
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21:38
Uh Leason Al Gayaib is quoting uh Dario at Davos, who also said we don't need to maximize engagement for a billion users, of course. Taking shots. Taking shots.
21:50
Okay, so folks over at OpenAI.
21:52
I threw this I threw this question to both of you earlier today.
21:56
Uh what is the problem with that?
21:58
>> that this is a shot, too, cuz it's like he is acknowledging that they've developed a Is he anti-ads?
22:02
Yeah, Anthropic is against slapping ads.
22:05
He said he's anti-ads, yeah. Wow, boo. This is hard.
22:09
I I I was falling in love with Dario.
22:12
I I love so much about his rhetoric.
22:14
Obviously, the models are fantastic, but he has to come and stab me in the back like that with a shot on my favorite favorite uh piece of the global economy, the advertising industry. Uh very very brutal.
22:24
But hopefully, we can bring it around.
22:29
>> from the conversation? Yeah, yeah.
22:29
So, there's a bunch I took So, um yeah, these ones were from he did a like a Wall Street Journal Q&A this morning. >> Okay.
22:36
Um Okay, so I'll just read some quotes. Yeah. >> Yeah.
22:39
Um He thinks we're going to have very high GDP and very high unemployment and inequality.
22:43
So, so when we we've kind of ballparked this at like >> [snorts] >> 10% GDP growth for America, that would be unprecedented, massive.
22:49
We're typically at like 2 to 3%.
22:51
10% would be a significant acceleration.
22:55
>> Yeah, and then for the unemployment it was like 10 to 20%.
22:58
>> That's [laughter] a whole lot. That's a lot.
23:00
And we can debate this more, and I'm sure we will.
23:02
We'll eventually formulate a an entire structural presentation around this at some point, but >> Yeah, and then he said um there's going to have to be some role for like a for the government to intervene on some macro level to like you know, help help with this displacement of labor. Yep.
23:16
Um He says um ideology will not survive this technology.
23:22
Ideology will not survive that.
23:25
>> vague, a bit of a vague point. >> Except his ideology.
23:26
He's like, actually mine is like kind of got a straight shot here.
23:31
Yeah, what could be more ideological than being against advertising?
23:34
He said um He's a zealot.
23:36
He's an anti-advertising zealot.
23:39
He said uh AI is uniquely well suited to autocracy. Autocracy, okay.
23:42
Yeah, yeah, yeah, this is a teal take as well.
23:45
Yeah, this was in the context of like why he's kind of anti giving chips to China. Okay, yeah.
23:50
AI is communist, crypto's libertarian, that take, yeah.
23:52
Yeah, and then he he kind of he said like Google and OpenAI are like firmly in consumer.
23:57
It's kind of this existential like battle between them.
24:02
And Anthropic is firmly in enterprise.
24:04
He's he's very happy with that decision.
24:06
He doesn't have to, you know, monetize the billion users or whatever or monetize for users.
24:09
He can just sell like He's like, I'm so I'm so happy I don't have to worry about monetizing a billion users.
24:17
>> [laughter] >> Uh Uh he said um I I on on the um question of like are they going to do generative stuff?
24:24
He said they probably won't ever do it.
24:26
I think Sholto said this, too.
24:28
But But if they need >> models out there that Claude Code can go and sign you up for the Nano Banana AI.
24:36
Yeah, like like maybe there's a use case for images and like, you know, presentations or something.
24:39
But then they can just kind of vend in some API they can contract it out.
24:43
So, my my I mean my big question is uh I think we all agree that ads in the Claude iOS app are a very low priority, something we will likely not see this year. Oh, that's right. Um [laughter] thank you.
25:00
Uh something we will likely won't see this year just because they have such a good business going on the uh on the enterprise side.
25:05
And the user base for the Claude iOS app is not necessarily big enough to support a really healthy ad business.
25:12
And they're sort of ideologically against it.
25:15
But on the slop question, you can use Claude Code to generate slop.
25:22
Like you can Article slop.
25:22
Well, article slop, but also imagery.
25:24
You can you can wire it up to the Sora API, to the Nano Banana API, and you can go create a whole bunch of generative video.
25:31
And people But but that is the Sholto promise of like it should be able to go and use other models, right?
25:35
The question for me is when will that functionality come to the Claude iOS app?
25:43
Because Claude can write some >> to like co-work.
25:45
So, I think when that comes to iOS Exactly, yeah.
25:48
But so, what will the co-work iOS product look like?
25:53
How much flexibility will it have?
25:53
Cuz it won't have all the same APIs to go into your your folders.
25:57
Like the whole cleaning up your desktop like meme on on your MacBook Pro with Claude Code, that's something that would just be sort of unaccessible to the iOS ecosystem cuz the APIs aren't there.
26:12
So, even if they tried to build it, Apple just say, "No, no, no, you're not rearranging icons on the desktop because be used maliciously, and this is a privacy issue, and this is a security issue.
26:23
And so, we're not giving you the hooks to do that."
26:25
The question is like how much can they do in the cloud and then vend back to you?
26:28
Because if you have a virtual machine that's running Python and has, you know, Claude Code running, and you're interfacing with it from the Claude iOS app, you could do a bunch of crazy stuff including generate images and go and sign up for a Nano Banana account.
26:45
>> What if we have an AI safety incident this year where somebody leaves like a Claude Code terminal kind of open and on just creates billions of social media accounts and just flooding the internet with with I thought you were going to say cuz like some kid you know how like kids will download like Fortnite and then like spend too much on V-bucks or they'll like get their parents' credit cards and like run up a bill.
27:05
It'd be funny if someone like downloaded Claude Claude on the iOS app and like accidentally kicked off something that like provisioned a ton of AWS servers, and they just get a bill for like $400,000, and they go bankrupt.
27:14
That'd be a sort of AI safety incident. That'd be funny. Anyway, Figma.
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27:28
So, what else did Leason Al Gayaib say about Davos?
27:33
Uh some companies are essentially led by people who have a scientific background. That's my background.
27:38
That's Demis's background.
27:40
Uh we had some love for Demis in the chat.
27:42
Uh shout-out to Demis over at DeepMind.
27:45
Some of them are led by a generation of entrepreneurs that did social media. Taking shots.
27:50
>> [laughter] >> Dario is like he's he's on one. incredibly entertaining.
27:57
>> because it's it's like bold statement jab. >> Yeah. Bold statement jab.
28:03
>> also, people will hit him with the hard questions, and he'll kind of be like he'll acknowledge.
28:06
He'll be he'll he'll he'll very quickly tell the interviewer, "I know where you're going with that, and I'm not going there."
28:11
But in like a fun way that's not really adversarial.
28:15
And he never flips it around like takes shots at them.
28:16
He's like, "Why are you asking me that question?
28:18
I'm not here to answer that question."
28:19
He's like, "No, no, no, I I know what you're trying to get me to do, but I'm not going to do it.
28:24
I'm not going to take the bait."
28:24
But he like knows that it's bait.
28:25
It's it's very entertaining.
28:26
Interviewer trying to bait him into saying that David Sacks was arming the Chinese. It's [laughter] crazy. That was crazy.
28:32
He says, "There's a long tradition of scientists thinking about the effects of the technology that they built, of thinking of themselves as having responsibility for the technology they built, not ducking responsibility.
28:44
They are motivated in the first place by creating something for the world.
28:46
So, they worry in the cases that something can go wrong.
28:49
I think the motivation of entrepreneurs, particularly the generation of social media entrepreneurs, are very different.
28:54
The way they interacted, you could say manipulated consumers, is very different.
28:59
I think that leads to different attitudes." He's taking some shots.
29:03
Potentially it's Sam Altman, although Sam Altman not really a social media entrepreneur, but I get that he's in that generation.
29:08
Obviously, this is more directed >> Was he saying looped with with with Mark Zuckerberg?
29:13
Is that a reference to looped?
29:14
I mean looped was technically social media, but I think of Sam Altman much much more of YC, enterprise software, startups, Stripe, like there he's never really been in-house at a major social media company that I'm aware of. I don't know.
29:29
But uh but I I I I take Dario's point.
29:32
And you know, he's just he's just trying to reinforce this idea that he does think talking about responsibility for the technology he's building is important.
29:40
That's the Anthropic vibe and brand, and it's served them very well. Uh anyway, Plaid.
29:47
Plaid powers the apps you use to spend, save, borrow, and invest securely connecting bank accounts to move money, fight fraud, and improve lending now with AI. Let's talk about Waymo. Let's do it.
29:58
So, today I wrote a quick piece.
30:01
It was a reaction to a reaction because David Zipper went in Bloomberg and he wrote a piece that we still don't know if robo-taxis are safer than human drivers.
30:10
Then Kelsey Piper went over to the argument and wrote a response to that saying, "Yes, we do know."
30:19
And her her interesting point was that what what what David Zipper's doing is he's lumping all of the different robo-taxis together.
30:27
So, Waymo and Cruise and Tesla and comma and Zoox and there's a whole bunch of other data that can go into this bucket and they're not all created equal.
30:36
Waymo's been doing it for decades this point.
30:38
They have insane capex and insane opex.
30:41
There's you know, humans in the loop a lot of times and it's just like the most advanced team.
30:49
It seems like it's you know, the most advanced technology stack.
30:51
There's a lot of advantages and that's actually showing up in the data.
30:54
And so, uh her her main dispute with Zipper is over what data, you know, she's including he he's including in in making this claim that you know, hey, we don't know if robo-taxis are actually safer than human drivers.
31:07
And she gives this great analogy that I really really enjoyed.
31:09
So, she says, "Imagine someone writes a piece and they say, 'We don't know if airplanes are safe.
31:14
Some people say that crashes are extremely rare and others say that crashes happen crashes happen every week.'
31:22
And when you investigate this claim further, you learn what's that what's going on is that commercial aviation crashes are extremely rare. This is true.
31:34
While general aviation crashes, small personal planes including ones that you can build in your own garage, are quite common.
31:40
And so, yes, if you lump that together, you're going to get this muddy muddy picture of aviation.
31:45
But you shouldn't use that to sort of fear-monger about getting on a 747 because 747s just so rarely crash.
31:52
But yeah, if you build your own Cessna and you're modding it and you're taking it through the canyons like you got to watch out.
32:00
>> any recreational pilot if they've ever gotten into any hairy incidents.
32:03
They'll tell you like, "Oh yeah, well this time I was flying Yeah.
32:07
and and the wind came on super strong and I landed and I was basically, you know, 90° [clears throat] And in what times that counts as a crash?
32:15
Like I mean like Harrison Ford has has like crash-landed on a golf course and no, I believe no one was injured.
32:22
I think it I think it's happened multiple times actually. By Harrison Ford? >> Harrison Ford.
32:26
Yeah, he flies his own planes but he flies like old planes and stuff.
32:29
Like he's like a true enthusiast.
32:31
Like he's he's he's he's like a plane guy. >> simpleflying.
32:34
com, how many plane crashes has Harrison Ford had?
32:38
In the last 25 years, the actor has been involved in several incidents involving emergency landings, rescues, and runway incursions. Exactly. Like it happens. It sounds crazy. It is crazy.
32:48
I would never want to be in any sort of plane crash.
32:52
But there's just way more there's just way more planes flying around when you include those Cessnas and it's not really fair to put that on United Airlines or American Airlines.
33:05
13th of February 2017, Santa Ana, California.
33:07
Single-engine Aviat Husky flown by Harrison Ford was cleared to land on runway 20L.
33:12
Ford's aircraft reportedly landed on a parallel taxiway overflying American Airlines 737 was holding short of runway 20L.
33:22
Uh 5th of March 2015, Santa Monica.
33:24
Ford was a pilot and sole occupant of Ryan ST3KR recruited two-seat open-cockpit aircraft that had that was used >> Open cockpit. Think about that.
33:34
You're flying and the wind's in your hair.
33:37
Like that's not a normal experience.
33:39
That's not coach on American Airlines.
33:43
>> extensively as a training aircraft by the US military in World War II.
33:47
According to a preliminary report, Ford reportedly reported a loss of engine power shortly after taking off and was attempting to return to runway three.
33:56
So, he ended up crashing into like a a field. Looks like Exactly. It happens.
34:01
Uh Ford chose to land on a nearby golf course clipping the top of a tree before landing.
34:08
>> [laughter] >> Like if you just took Harrison Ford, he's probably more dangerous than like American Airlines. >> 2000.
34:13
While landing in Lincoln, Nebraska, Ford's plane departed the runway due to a gust of wind.
34:17
The aircraft sustained minor damage. Oh no.
34:21
23rd of October 1999 >> a fourth one?
34:23
I I thought I was on a plane. That's crazy. That's crazy.
34:32
>> [laughter] >> Although the helicopter rolled over on its left side, neither Ford or the instructor were injured. >> Yeah.
34:39
That's all that I can find.
34:41
>> Okay, I I have another plane story.
34:41
I don't >> [laughter] >> I don't want to >> four major incidents like make it into the record.
34:46
He's got to have at least like 10 more that are just like sketchy situations >> one wrote a piece about it. No one saw that happen.
34:53
>> Let's Let's agree that you know, >> call his PR person.
34:55
Hey, let's clean this up.
34:56
How about you take a picture of me outside Erewhon?
34:59
>> [laughter] >> We can get call the paps.
35:02
I'm willing to get coffee with somebody. >> smoothie.
35:04
We need We need a new story. >> a different story.
35:06
I want to be on the front of the New York Post.
35:07
I'll I'll I'll I'll take the bad picture at the beach of me falling off or something.
35:12
Anyway, Cognition, they're the makers of Devin, the AI software engineer.
35:14
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35:17
So, I actually have a friend who's been on the show.
35:19
I'm not going to dox him but we we have two friends. Both of them fly.
35:23
One of them's extremely serious, has you know, IFR rating.
35:27
So, there's VFR which is visual flight rules.
35:29
That's like you take the plane up, it has to be clear cuz if you get into clouds, you're not trained for that. You can't fly at night. Exactly.
35:37
IFR is you're flying on the instruments instrument flight rules.
35:41
And so, we have one we have one friend who's like super by the book, super safe.
35:45
And then we have another buddy who's a little bit wilder, VFR and he will rent like the cheaper planes and one time like the dial lights went out and he was landing at night.
35:55
Shouldn't be flying at night at all.
35:57
Just like botched the schedule and didn't check sunset and he has to use his phone flashlight while he's landing to look at the dials as he's coming in on this rickety like old plane he's flying.
36:10
People get crazy out there. They get confident. It is very dangerous.
36:14
But the just like if you're if you're getting into personal aviation flying your own planes, the the jump in safety from VFR to IFR is significant.
36:24
Like the the IFR guys like crash way way less.
36:27
So, highly recommend that if you are getting into flying your own planes. Anyway, Restream.
36:33
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36:36
So, so Waymo is funny to write about because there's still a class of people that are writing these stories about like, "Hey, Waymo's actually safe."
36:46
And I'm like, I I I completely buy it. I'm I'm in.
36:47
Roll the Waymos out everywhere. I've been in them. I feel safe in them. I've seen the data. I think they're safe.
36:53
Like I'm just like my eyes glaze over when someone's like, "I'm going to blow your brain out.
36:59
I'm going to blow your mind." Yeah. Waymos are safe. >> Robot car safer. >> I'm I'm in. I'm totally in."
37:06
But there's still this debate and most most people in tech are debating about just Waymo's unit economics and like can they beat Tesla? What happens there?
37:13
And so, typically I don't really wade into the safety thing cuz I think it's very safe.
37:18
But this Piper piece this pipe this piece by Kelsey Piper did make me wonder about if what happens if you further segment the human driver population.
37:25
So, we we need to segment robo-taxis into Waymo and everyone else because Waymo's so good.
37:33
But how do you how does Waymo compare against the best human drivers?
37:37
And I wasn't thinking like the Lewis Hamiltons of the world.
37:40
I'm sure Lewis Hamilton could could be superhuman at driving if he needed to.
37:44
I wanted to be think about it more as like if I'm an insurance agent and I'm underwriting a class a group of people, what would I be going for and are they better than Waymo?
37:51
And you can't look at fatal crashes per 100 million miles because there have been so few fatal crashes in Waymos and there's just not enough data yet to look at that.
38:01
So, what you can look at is any injury crashes per million miles.
38:05
And the Kelsey Piper piece is really good.
38:07
It goes into a bunch of different methodologies for data collection looking at incidents where Waymo's airbags release cuz that's a very binary moment where there's a question about like, "Well, what's an injury?"
38:18
Like if somebody like got motion sick and then they had to go to the hospital like does that count as an injury or like what if they were getting out of the car and then they fall like does that count?
38:25
So, there's all these things where it's like does it count?
38:28
So, the best data that we have on Waymo is all any injury any injury crashes per million miles.
38:35
For the average human, it's about four any injury crashes.
38:37
So, any injury that counts, four per million miles.
38:43
Waymo is way better way better. 0. 75.
38:46
So, about five times safer than humans broadly.
38:51
But there's one very specific case where humans I believe are safer.
38:55
Now, there's debate about the data.
38:56
I just had Claude like crunch it all together and try and pull a bunch of stuff together. But I think this holds.
39:02
So, a married 60-year-old woman who's college educated and is driving a large luxury SUV in Massachusetts on a Tuesday morning is closer to 0.
39:12
5 injury crashes per million miles.
39:16
>> Is the Tuesday morning part real? >> Yes.
39:18
So, the the most dangerous time to drive and I'll flip it around.
39:20
The most dangerous time to drive is midnight on Saturday because that's when people are at the bars. They leave. They're drinking.
39:27
And so, there's a it's dark. It's the weekend.
39:30
There's a lot more people on the road.
39:32
They're driving much faster. They're getting places.
39:34
They might be inebriated or under the influence of something.
39:37
And so, Uh, morning is the safest time to drive.
39:40
Uh, and so basically I looked at all the I it's a the the the the the government IHTSA data.
39:48
It's the transportation authority.
39:51
I I'm getting the acronym wrong.
39:52
But uh, you look at all the different segments and then you add all those together and you get kind of like the synthetic safest driver cohort.
39:56
It's a little loose, but uh, it does seem like if you looked at that cohort, they're still beating Waymo. Humans still got it.
40:05
Uh, at least like kind of. It It's pretty close.
40:08
It's honestly neck and neck.
40:08
Uh, but um, so none of this should take away uh, anything none of this should take away from >> Feels like a Nathan Nathan Fielder episode in the making of like studying the the women in Massachusetts.
40:20
>> Yeah, like what did they do?
40:20
[laughter] drivers on the planet and he's just interviewing all of them to like >> married 60-year-old college-educated women.
40:27
>> like the exact wrong conclusion. >> yeah, yeah, yeah.
40:28
We need to We need to get everyone married and college-educated.
40:33
>> Every No, the conclusion is everyone needs to move to Massachusetts. >> Yes.
40:36
And >> Well, it's the married 60-year-old women that need to be the taxi drivers everywhere in the world. Yeah.
40:40
They need to be It's like instead of Waymo Yeah, he starts like he starts like a competitor to Waymo Right.
40:44
Hey, like that's just them.
40:47
>> Yeah, that's just them.
40:47
>> [laughter] >> Yeah, but it only works in Massachusetts.
40:48
Um, so uh, clearly Waymo's are very safe.
40:52
Uh, rolling them out nationally would be a huge safety upgrade uh, for our society broadly, but it's worth noting that the Massachusetts married women still got it.
41:01
Uh, but if you want to know if you want to flip this around and find the hypothetically riskiest driver profile, it's very funny.
41:09
It's an 18-year-old single male with a DUI driving a Dodge Challenger at midnight on a Saturday in rural Mississippi.
41:18
That's as risky as you can get.
41:18
Uh, and that and that's like you know, an order of magnitude or or 40 times as dangerous as the as the Massachusetts Yeah, but the interesting takeaway is that uh, that that you said earlier off the show was like Waymo's actually not super superhuman level driver. Yes, yes.
41:34
It's not >> because in order to be that you actually have to be better than the best human, right? Exactly. Exactly.
41:41
So it we we we need a word for for not above average and in the top cohort of humans, but not better than any human ever.
41:52
Because a lot of AI tools are getting there.
41:57
>> guess Okay, so I actually looked up uh, the definition.
41:59
So superhuman means having powers, abilities, or qualities beyond normal human capacity.
42:03
So it's potentially these women in Massachusetts >> superhuman Yeah. And >> That's right. Uh, as well as Waymo.
42:10
So maybe maybe we do need to give Waymo a little more credit.
42:14
>> Well, if you're looking for superhuman pay payroll, head over to Gusto.
42:15
The unified the unified platform for payroll, benefits, and HR.
42:19
Built to evolve with modern small and medium-sized businesses.
42:23
The backbone of this show. >> It is.
42:26
Uh, Max Hodak had a post about Waymo.
42:29
He said, "Interesting benefit of Waymo.
42:30
It always matches instantly since it since it knows exactly what cars are available and that they will always accept and it can also provide accurate wait times before requesting."
42:40
And so um, lots of love for Waymo.
42:42
Interesting to see where they'll roll out.
42:44
The really interesting thing is that we we've had a number of people on the show advocate that rolling out Waymo is a societal good.
42:52
It will reduce the number of traffic fatalities. That's all true.
42:53
But if you really want to accelerate the impact that Waymo will have on safety, you got to deploy it in Mississippi before you bring it to Massachusetts.
43:03
Which and I I I just feel like Waymo's coming to Boston before it comes to Vicksburg, but uh, I don't know. Uh, it it it is fun.
43:10
There's there's other love for Waymo on the timeline.
43:12
First, let me tell you about Okta.
43:13
Okta helps you assign every AI agent a trusted identity so you get the power of AI without the risk.
43:20
Secure every agent, secure any agent. Um, Mike Volpi.
43:24
He said, "I have to say I love that Waymo operates from San Francisco to the South Bay. So great.
43:31
Some folks say the free freeway driving is so-so. I hadn't heard that.
43:33
Uh, the antidote to that is I get uh, into an Uber and and do the same drive.
43:40
It's literally life-threatening."
43:44
I was driving I was driving uh, with Paul the other day and I heard uh, he was telling me about the different modes that Tesla has.
43:50
I've never owned a Tesla so I wasn't familiar.
43:54
But did you know that Tesla actually has something called Mad Max mode with the autopilot where it'll drive it It'll drive it like roughly around 85 on the freeways and it will uh, it'll if if you're in the fast lane and you come up to somebody, it will merge over into the into the lane to the right, make a pass, and go back to 85. That's insane.
44:13
[laughter] Somehow somehow feels uh, slightly illegal, but uh, I like it. Okay. Uh, MongoDB.
44:22
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44:27
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44:29
Uh, we have an update in the ti- in the Warner Brothers Netflix deal.
44:34
Netflix, they're going all cash. All cash deal.
44:40
Uh, Netflix had said to Paramount, "Hey, what we want is an all cash deal."
44:43
David Ellison and the Paramount crew, they brought Netflix uh, they brought Warner an all cash deal and Netflix or or Warner was still saying, "Hey, we're going with Netflix." Now Netflix is upgraded.
44:54
So we can read through a little bit of this from the Wall Street Journal.
44:57
The Warner Brothers uh, Discovery and Netflix said Tuesday they struck a new all cash deal for Netflix to buy Warner Brothers Studios and HBO Max.
45:06
Warner also released financial details on the cable network's business it plans to spin off.
45:10
The all cash deal of $27.
45:10
75 per share replaces Netflix's previous cash and stock deal.
45:16
The sweetened offer comes as rival bidder Paramount continues pushing its all cash offer for all of Warner Discovery.
45:22
The value of Netflix's offer remains 72 billion.
45:26
Warner and Netflix said they expect the new structure to enable Warner shareholders to vote on the deal by April.
45:31
The change could also help sway some shareholders who might be weighing its bid against Paramount's.
45:35
Netflix co-CEO Greg Peters said in a statement that revised agreement "demonstrates our commitment to the transaction and accelerates the process for Warner's shareholders.
45:44
The new Netflix agreement reduce reduces by 260 million the amount of Warner debt being placed on Discovery Global, the company that will house cable channels including CNN, TNT, and Food Network.
45:56
Um, there's also another uh, uh, the next kind of thing that I was going to get to is interesting.
46:03
Uh, uh, CNN is doing uh, 600 million in profit on revenue of 1. 8 billion.
46:06
So uh, they they are truly newsmaxing quick size for CNN. Not bad at all. Not bad at all.
46:19
Of course of course a ton of debt strapped to uh, the the broader group.
46:24
And Peter Kafka is saying that private equity should pick it up.
46:29
It's a shrinking business that throws off cash.
46:31
It's perfect for private equity.
46:33
Let's give it up for private equity. I know you're a big fan. I'm a big fan.
46:40
Uh, somebody somebody uh, you know, I was saying yesterday that maybe maybe AI could save Hollywood.
46:44
Somebody somebody would uh, I knew I knew that was going to piss a lot of people off for a lot of reasons.
46:50
>> I wasn't really clocking what you were saying either and so we should talk about it more, but continue.
46:55
>> Well, well, one of the critiques was like, you know, uh, interesting to say that LA is [laughter] dying as you're building a media business from LA.
47:00
And my response is that we are in a huge complex.
47:05
We're recording the show from a huge complex and every other building in the complex is empty pretty much every single day.
47:12
Like there's no nothing going There's the when I when I said LA is like dying, I was specifically talking about the context of the entertainment.
47:21
Yeah, I mean there's that there's that Wall Street Journal report that just shows sound stages were you know, typically leased 90% of the time and it's just way off off peak down to like 60%.
47:32
And so there is like a like a broad trend.
47:35
Uh, and then just in general like I don't think we're necessarily yeah, at a phase in our life where we're like, "Okay, tabula rasa.
47:45
Where's the best place to build this business? Let's go find that." It's like we live here.
47:51
>> Yeah, we didn't We're not like, "Okay, we should go to Atlanta or something." Go to New York.
47:56
Yeah, we certainly didn't say like let's start a media company because we live in LA.
48:00
>> It's like the the the the current struggles that LA is having are not going to hold us back.
48:05
If anything, it's going to be easier cuz we can get space and hire people.
48:08
In in 10 years ago this space would have been like two three times the price to rent.
48:14
The bigger the bigger question is uh, you know, there there are these blips in industry towns that have happened many times.
48:21
New York famously in the what 70s and 80s went through a really rough patch.
48:25
San Francisco during COVID, everyone was moving out and there was a real there was a real vibe of like, "Oh, is San Francisco going to be less relevant in tech?"
48:35
And then it came roaring back with the AI labs.
48:37
Uh, and I I think most people don't you know, debate that that you know, cities go through rough patches uh, and then can come back.
48:44
And so we certainly we certainly hope that LA comes back. It'd be fantastic.
48:48
Um, but there are there are a lot of changes that need to be made.
48:51
And this has been said by a number of a number of famous people in Hollywood and Hollywood actors who have talked about uh, different tax regimes, different incentives, different changes structurally to the way content is made and distributed.
49:04
There's a lot of different elements that are contributing to LA having a rough go.
49:07
At the same time, it's a fantastic city.
49:09
It's where I was born and raised. I love it. I'm not going anywhere.
49:12
You're going to have to pull me out of here. He's not leaving. He's not leaving. Gemini 3 Pro.
49:17
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49:19
State-of-the-art reasoning. Next level vibe player.
49:23
And deep multimodal understanding.
49:23
Uh, in its Tuesday filing, Warner projected 17 billion of revenue in 2026.
49:28
Adjusted I won't explain EBITDA, but uh, 5. 5. 4 billion of EBITDA.
49:34
Those figures are expected to decline to 15. 6 and 3.
49:41
8 billion respectively in 2030.
49:44
The only individual network projections were CNN, which I just shared.
49:46
They're increasing they plan They're They're expecting to increase revenue to 2. 2 billion in 2030. Mhm.
49:53
Um and and expecting to Yeah, continue to grow Yeah. EBIT as well.
50:02
Well, Netflix seems to be doing everything right.
50:03
Um as much as I enjoyed the David Ellison profile and learning more about how seriously he takes his business, it does feel like Netflix is just willing to pull out all the stops to get this across the finish line.
50:15
And if they're able to match Paramount on the cash deal nature and all the different consideration, deal with the regulatory hurdles, it might take a long time, but it does it does still feel like they will land on it. Yeah.
50:30
>> And again, I mean, it just feels like Yeah.
50:32
I I'm so curious to see how this works out because it felt like the Ellisons were were putting on this absolute master class and then and then this one and then kind of ran into ran into a brick wall with this, right?
50:46
You could argue they overpaid >> [clears throat] >> Yeah.
50:50
>> by a ton for the UFC, which made sense if you had this again, like if you have all these assets under one roof, it is going to be a really compelling consumer product, consumer subscription, but currently kind of unclear who who who the Yeah.
51:07
who this who this kind of platform is really going to be for. Yeah.
51:09
It was also surprising to me because Netflix for 20 years has been pure play tech company, right?
51:17
And many of the previous tech companies when they come out like they haven't done a lot of acquisitions of legacy assets that I'm aware of, maybe.
51:27
But I'm just thinking like social media sort of like disrupted the news business.
51:31
They didn't Meta didn't go out and acquire the New York Times.
51:34
They could have done some sort of hostile takeover, they have the money, but that never really figured into the into the business and they wound up just working together synergistically.
51:42
And now the New York Times has been growing across social media very effectively and they have they've adapted their business model.
51:48
Both businesses are doing well.
51:50
They're sort of disruptive to each other, but ultimately they never decided to to to to buy the legacy player.
51:56
So, it was always something that was never on my bingo card of oh, Netflix is going to buy, you know, a a TV channel. Yeah.
52:05
Or you know, a movie studio or traditional Hollywood player.
52:10
That just didn't seem like something that was going to be, you know, logically happening anytime soon. And yet here we are.
52:17
And it makes a lot of sense when you think about the assets and the IP specifically and the longevity that that will bring when it comes when you get Batman and Superman on Netflix.
52:26
That's going to be exciting.
52:28
So, Century Century shows developers what's broken and helps them fix it fast.
52:33
That's why 150,000 organizations use it to keep their apps working. [music] What's that? We got a deal. We got a pact.
52:39
It's not just a deal, it's a pact.
52:42
Open AI and ServiceNow, they struck a deal to put AI agents into business software.
52:47
ServiceNow, one of the greatest software companies in history, one of the few to reach revenues at their scale.
52:54
The line from the Wall Street Journal is the AI model maker and business software provider, they signed a three-year pact. I like the word pact.
53:01
That underscores The partnership is economy is over.
53:06
>> Yes, you got to be a release economy is over.
53:07
This is the pact economy.
53:07
You get no more deal guys, no more deal titans, deal makers, pact makers, pact guys. That's what's next.
53:16
This is going to underscore how AI agents are increasingly being embedded in corporate software.
53:21
You heard Dario talk about where he's potentially going up against other labs on corporate B2B deals.
53:26
He said open AI, he said DeepMind.
53:30
He didn't really say he said no China labs have ever competed.
53:34
Well, ServiceNow went with open AI on this one.
53:36
So, they signed a three-year deal that will integrate the the AI models, ChatGPT's models into ServiceNow's business software.
53:43
The deal deal depends on customers using open AI's models within ServiceNow and also includes a revenue commitment from ServiceNow to open AI.
53:53
Enterprises want open AI's intelligence applied directly into ServiceNow workflow, said Brad Brad Lightcap, Open AI's chief operating officer.
54:00
Look ahead, customers are especially interested in a gentic and multimodal experiences so they can work with AI like a true team teammate inside of ServiceNow.
54:10
We've seen a lot of other companies add We've talked to Marc Benioff about Slackbot.
54:15
We've talked to Satya Nadella about Copilot.
54:17
Satya Nadella about Copilot. Like if you have one of these massive software suites, enterprise software suites with just so much surface area, you're going to want to vend LLMs and agents into every little nook and cranny and you
54:31
probably don't want to build your own lab because it's going to be incredibly expensive when Open AI will go and marshal the capital and build the data centers and train the models and then you can just focus on the implementation and delivering value for your customer. So,
54:44
So, Salesforce has already folded AI agents into its flagship sales and marketing tools.
54:49
SAP and Workday have have been similarly pitching businesses on the idea that they're embedded AI agents are essentially getting are essentially getting the value out of AI.
54:57
The deal comes as Open AI looks to build its enterprise business both by selling direct access to its models and AI agents through business software collaborations like with ServiceNow.
55:07
It bases competition not just from rival AI model maker Anthropic and but also Google and Microsoft's suite of enterprise AI tools.
55:16
For ServiceNow >> I want to find I want to find a company that is using the agents at ServiceNow or Salesforce or or a company like that saying I can't live without these agents. I love these agents.
55:30
We got to find We got to find one person. Yeah.
55:32
Um Uh I I wouldn't I wouldn't be surprised if it's uh if it's just like really sort of like maybe a year or two behind on the actual implementation, but it's just like oh, I get like daily summaries of what's going on in the system and it's a little bit nicer and neater.
55:53
And I I Yeah, I could probably extract all the data and write an agent to that does that, but you know, it was just one click of a button to add it to my installation and I did it and it's adding a little bit of value.
56:06
I don't think you're going to see anyone who's like it's transformational.
56:10
I It just works on its own. I don't do anything.
56:12
It's more it's much more incremental than that.
56:14
It's It's It's still in like an auto complete phase, little helper tools there. It's Clippy.
56:20
Clippy's going into every piece of enterprise software.
56:22
Um And so, people are having fun.
56:25
ServiceNow increased revenue 22% in the third quarter as AI demand from both existing customers and new customers grew particularly in its customer relationship management business.
56:33
The software company will report its fourth quarter earnings and full 2025 financial results on January 28th.
56:42
We got to do a deep dive for that day.
56:44
Anyway, AppLovin profitable advertising made easy with axon. ai.
56:48
Get access to over 1 billion daily active users and grow your business today.
56:53
Uh what's uh what SaaS founder should know about entering the Japanese market?
56:59
Yeah, I found this on Hacker News and I just thought it was interesting because we've talked to a few folks about expanding into Japan.
57:05
It's not been on the top of the road map for many founders that we talked to, but I thought this was interesting and I thought we could go through just a just a little bit of it and then you can read the article if you want.
57:16
So, this is from embedworkflow. com.
57:20
In one sentence, what's the difference between selling SaaS in Japan versus other countries?
57:25
And the answer is the process is different.
57:27
You can't You just can't treat sales as a whole in Japan the same way you would in North America or Europe.
57:32
The SaaS sales process in Japan is structurally different from the United States and other Western markets primarily in terms of pace, decision-making style, and buyer behavior.
57:45
It's not that Japanese companies are unwilling to try new software, but rather that they prefer to do significant research before engaging directly with a vendor.
57:54
So, many successful SaaS companies in Japan structure their websites with two primary calls to action.
58:00
So, one is just for downloading product documentation.
58:06
And then the second is for booking a demo and starting or starting a free trial.
58:09
And most Japanese leads enter through the documentation path first.
58:12
In America, we just want to get on the phone.
58:16
I'm not reading the instructions.
58:19
>> I'm not reading the instructions. No way.
58:21
I don't have time to understand how this thing works.
58:23
I need to go straight to a steak dinner.
58:24
Steak dinner first, then I'll figure out what your company does.
58:28
But let's talk about golf first.
58:31
Let's talk about a track day first and then you can give me the pitch for your company.
58:36
>> That would That would honestly the steak dinner button on a SaaS website.
58:38
It's like you can try the product now or there's a button that's just like steak emoji and if you click that, you can get steak today on demand with somebody on the team. >> Yes.
58:50
No matter where you are, no matter agentically books a steak restaurant.
58:55
>> I'm tired I'm tired of all these people that are like oh, oh, you know, it just take just take a demo and we'll give you some AirPods.
59:00
Spend the money on steak.
59:02
Take the AirPods budget and put a steak button on your website. >> Steak button. And have the steak flow.
59:08
The steak [laughter] Stakeholders. Stakeholders need steak.
59:13
So, in the US, the typical flow is that a prospect visits a website, books a demo on their own, or drops off and is followed up aggressively by sales.
59:20
A conversion happens quickly.
59:22
A proof of concept or trial begins and the deal either closes or the buyer moves to a competitor.
59:28
The cycle is fast and transactional.
59:30
Buyers are comfortable testing tools or replacing them and switching vendors if something doesn't work.
59:36
In Japan, the process is slower and more deliberate.
59:38
A company will usually download product materials first.
59:40
The vendor then reaches out and begins a longer engagement process focused on education and relationship building rather than pushing for an immediate demo or trial.
59:49
The goal is to support the buyer's internal evaluation process.
59:55
The lead will take the information back to their organization and begin internal discussion about whether or and how to proceed.
1:00:01
So, I just thought that was pretty interesting.
1:00:03
How do you gain trust from the Japanese market?
1:00:05
Part of it is showing your commitment to the Japanese market where things where simple things matter.
1:00:09
Is your product localized?
1:00:11
Is your documentation localized?
1:00:13
Do you have a support person that I can speak Japanese with?
1:00:15
That's one layer and the other layer, which is harder to potentially navigate at first, is the social proof aspect.
1:00:20
So, you need to get some social proof. Anyway.
1:00:25
>> Yeah, I'd be so I'd be so curious to know how like a company like Notion has done in Japan, right? It's product-led.
1:00:32
They do have enterprise as well, but again, it's a product that just, you know, kind of scales naturally.
1:00:38
But but yeah, for for so many different kind of like vertical SaaS players, it would feel like unless unless the Japanese startup ecosystem is asleep at the wheel and not paying attention to what's working outside, like can you imagine as a vertical SaaS player going and trying to compete in Japan against a local like a talented local team?
1:00:56
It feels like it'd be very feels like you just get smoked.
1:01:00
Anyway, Vanta automate compliance and security.
1:01:03
Vanta is the leading AI trust management platform.
1:01:09
Max Hodak is on the line as well.
1:01:11
Fun fact, rather than asking Claude to double-check its own work, you can lie to it and say coded codex went romping through the code and left bugs and it should find them.
1:01:21
>> [gasps] >> I like the idea that that somewhere in the weights the all the drama of the AI lab battles are being encoded and creating bitter deep rivalries.
1:01:33
It's yeah, it's it's very funny.
1:01:34
I saw I saw something else about Claude just rejecting a prompt whole Claude. Did you see this?
1:01:41
Somebody was like, rewrite this entire app in jQuery and Claude was just like, no.
1:01:46
>> [laughter] >> That's a bad decision, bad use of resources. I'm not doing it.
1:01:49
I don't know if that's real, but I thought it was very very funny.
1:01:54
Anyway, we have our first guest of the show, Martin Shkreli in the Restream waiting room.
1:01:58
We will bring him in the TBP show. Martin, how you doing? Great to see you. What's up, guys? Good to see you. Happy New Year.
1:02:04
How is your year going so far? Great.
1:02:08
I'm a new dad, so that's uh Congratulations. It's pretty wild, yeah. Congratulations.
1:02:12
That's Uh is it has it has it been wild or is it uh Where does it rank up there with the >> a bit on the normal?
1:02:20
Like to to me to me parenting is it does feel natural.
1:02:27
And so there some people some people have this idea of like oh, it's so it's so insane and you know, it's so complicated and and I have to read 20 books and other people is like kind of follow just follow kind of your own nature and just like take take care of your child.
1:02:42
It it is straightforward to some extent.
1:02:46
>> I mean, I'm following my nature.
1:02:46
The kid's got to produce at some point.
1:02:47
He's starting to come into work like once a month.
1:02:50
You know, comes in, sky guys, you know, entertains the troops here. Perfect.
1:02:55
>> But at some point, you know, some trades, something. Do something. Yeah.
1:02:59
You know, Put some trades on.
1:03:00
Yeah, you got to find some alpha.
1:03:03
>> Have some have some conviction. Yeah. Yeah.
1:03:07
Uh how how big's how what what's the environment like in your office?
1:03:10
You guys have remote component? You anti-remote? >> Remote is is evil.
1:03:16
You know, I think that if you're going to war together, you can't go to war remotely.
1:03:19
You know, it's uh >> [laughter] >> you know, my my people fought the Ottoman Empire and you know, one one man, you know, famous general, you know, he stopped the Ottoman Empire largely by himself and at least that's the legend.
1:03:33
You know, and and if we're going to take on Bloomberg or whoever we're fighting, um you know, I just don't think you could do it with some guy sitting in, you know, at home with his feet up.
1:03:44
What's the current what's the current battle that you guys are fighting and how is the war going overall? War's going great.
1:03:50
We just closed a seed round. We raised five. Whoa. All right. Congratulations.
1:04:00
Did you raise five million?
1:04:03
Raised two like a year ago to get the ball rolling or a year and a half ago.
1:04:06
Raised five as a seed round and then we'll probably do like a 10, 20, 30, something like that this year as an A.
1:04:14
We have a lot of revenue. We're almost profitable. That's great.
1:04:16
Uh it's you know, the interesting thing about financial software is traders want to try everything.
1:04:21
Like they just, you know, it's the greatest business in the world.
1:04:24
And you know, you do have to have domain expertise, which nobody has.
1:04:27
So, I think that's a lot of fun.
1:04:30
Do you mean Do you mean nobody in nobody in tech has? Yeah. Yeah, that.
1:04:36
>> [laughter] >> The people with the Yeah.
1:04:39
Our customers are brilliant.
1:04:41
The people who are in finance have financial expertise or at least many of them, you know, believe they do.
1:04:47
Obviously, to some extent it's like a casino and and you're you're sort of arming them with tools.
1:04:51
A lot of tools haven't changed.
1:04:53
I do have this thing I want to show you guys when I'm when I'm ready.
1:04:56
I think we're going to call it like sit or sit sit rep or sitch.
1:05:00
It's going to be like the situation monitoring suite. Yeah, that's perfect.
1:05:04
Bloomberg has these like fake um systems that are they're pretty awful, but they're something where you can like see the map and you can kind of see different things happening like earthquakes or whatever.
1:05:13
But like take that and actually make it really good.
1:05:16
I think people would would truly want to monitor situations.
1:05:20
I think that's a new like there's no situation monitoring out there.
1:05:25
>> I mean, I think it's a new sector. Yeah.
1:05:27
You know, it's a new it's a new category.
1:05:29
It's a and it's a prosumer category cuz cuz cuz cuz people I think actually enjoy it so much that it's like camping where there I think people will be willing to spend money. Like >> Oh, totally.
1:05:41
So, think think about the revenue of Bloomberg with 8 billion, 10 billion, whatever.
1:05:44
A satellite constellation, maybe it's 100 mil.
1:05:48
And imagine if you're sitting at Citadel or Millennium or some hedge funder Fidelity or something and you and you're literally tasking a satellite.
1:05:52
Like, no, actually I want the satellite point here.
1:05:55
You know, and what margin difference would it make?
1:05:58
You could probably pass through you could probably be accretive to EBITDA to have your own constellations like satellite constellation and then things like drones or maybe, you know, there's you know, Bloomberg right now I think they have like ships and shipping routes and flights and like kind of fairly boring stuff.
1:06:12
But you you could make it 100 times better.
1:06:15
So, that'll be fun when it's ready.
1:06:16
And again, this is all inspired this whole sector started with the Bezos kind of Yeah. [laughter] That's right.
1:06:24
>> It really really really did.
1:06:24
What's your take on prediction markets? Do you enjoy them?
1:06:29
Do you think that they're valuable uses of information?
1:06:31
Do you think it all just winds up being sports betting?
1:06:33
Like where where where does all this go?
1:06:35
And we will be we will be trading on what you said here.
1:06:38
So, Do you guys get Do you guys get paid uh >> [laughter] >> No, no, no. No, no, no.
1:06:44
I yeah, I'm super uh I'm a thousand X long on you saying biotech at some point during this show. No. >> put $3 on it. >> Yeah, exactly. Exactly.
1:06:53
No, no, but but yeah, what what do you think on on on prediction markets? Valuable, useful? Do you use them? Do you trade?
1:07:01
>> Yeah, it's great I it's a great question.
1:07:02
I mean, I think I think the it's probably like social media.
1:07:04
Like the first social media companies, if you like go back into like that Steve Levy book about Facebook, which I think is just fantastic like almost documenting, you know, every part of it.
1:07:16
There were a couple of very random even before Friendster, you know, a couple of these really proto social media companies and the sector exploded.
1:07:25
I think that's where we're at.
1:07:26
I don't think I mean, I I wish the companies the best of luck except for Kalshi. But the two companies.
1:07:33
But the I do think that you know, markets have been around for, you know, hundreds of years if not longer.
1:07:41
And ICE and Cboe and these other companies are publicly traded.
1:07:45
They don't sit there and twiddle their thumbs and say, "Gee, I you know, I hope I hope some creative new market comes along."
1:07:51
They make financial products all the time that fail.
1:07:52
You know, they they they innovate, they add new things and then they they actually take them down because they don't catch fire on Wall Street.
1:07:59
So, if you want to be like that micro kind of uh you know, micro markets sort of pioneer, it's interesting, but it's sort of still like you get into scale problems with like who actually arbitrates some of these bets.
1:08:13
Obviously, sports is easy and some of these other things, but you know, how much are you just financializing for financializing's sake?
1:08:19
And is that sustainable when you actually need people with tons of money to fight the arbitrage gradient?
1:08:24
You know, if you're betting So, in full disclosure, I've been running this bot on Polymarket that that makes a market in the Bitcoin 15-minute markets, which are somewhat inefficient.
1:08:36
And nobody needs to trade this, right?
1:08:40
There's no actual, you know, benefit to trading this other than you you can you can take two to the end bets, so you get around, I guess, 96 bets a day.
1:08:49
And if you somehow, you know, the money velocity of getting one of those right, you can compound insanely well. Of course, it's random.
1:08:59
But you know, people hope springs eternal that you could somehow get the rhythm of the market every 15 minutes and you can you can I think somebody posted on Polymarket that they took a very small amount of money into a very large amount of money.
1:09:08
So, you know, it is it is kind of a I think it's a bit of a waste of ingenuity and engineering.
1:09:13
And we're we're working on trying to sort of make a prediction market that might be more relevant to say private companies.
1:09:21
You know, right now the binary outcomes of prediction markets have forced you into this box Yeah.
1:09:24
of like will OpenAI go public this year?
1:09:27
Will SpaceX hit a trillion valuation?
1:09:29
Why can't it just be dollar for dollar?
1:09:31
Why not like This this is just a market that pays you N dollars per you know, like a swap.
1:09:37
So, and I'm sure that might be being worked on by other companies, but I think that's like an economically rational thing. So, the spirit is there.
1:09:44
Like we should have our own markets.
1:09:44
We should be able to deploy whatever we want, but actually make it make sense.
1:09:48
What is >> still a lot of What is the state of tracking large late-stage private companies' valuations?
1:09:56
We have a ticker at the bottom with uh you know, MAG 7, big tech companies with market caps.
1:10:01
I would love to add Anduril, OpenAI.
1:10:04
Uh but yeah, I saw some debate over, you know, how you actually get the data, how reliable it is. Yeah, explain.
1:10:12
I got into a I got into with Lonsdale. I unfollowed him.
1:10:16
I unfollowed him for 5 minutes because of it. I was just so mad. Brutal.
1:10:19
Because Worst 5 minutes of his life. Worst 5 minutes.
1:10:21
I might have I might have made a few days.
1:10:24
Um but eventually I I uh relented, but >> capitulated.
1:10:30
Yeah, I think that what Lonsdale's saying is right in that if he gets invited to a deal, for say Ramp or whoever, you know, he was complaining that my Ramp number was too low. And okay, fine. That's that's fine.
1:10:41
But it's the same thing as insider info in the stock market.
1:10:45
So, you have insider info, great.
1:10:47
You know Ramp's going to trade up 50% higher than my number.
1:10:49
He's like, "Your number's wrong."
1:10:51
What's no different for me saying, "Well, you know, the um you know, the the Nvidia number's wrong, but I know they have a lot of quarter." Oh, yeah.
1:10:59
>> [laughter] >> Well, you know, how am I supposed to know that?
1:11:01
You know, my market only reflects the people trading on it, not you know, um the news you know before everyone else knows it, which is in private, as you know, guys know very well in private world, that's in that's that's to be expected.
1:11:15
Otherwise, you won't part with your money, but in the in the public world, you're not supposed to have that information edge.
1:11:20
So, he's so used to having the information edge cuz he I'm sure he gets invited to many many great deals.
1:11:25
That you know, he knows how the price is about to change.
1:11:27
And so, SpaceX is a really funny example.
1:11:29
On our platform, SpaceX price has tripled because you know, Elon sort of dropped this bomb that like, "Oh, we're going to do a uh you know, do a a buyback at this crazy price." Yeah.
1:11:40
Obviously not crazy to him, but to the marketplace they're like, "What? WTF?"
1:11:43
It's like more than double for the last few months. >> Wow.
1:11:49
You know, just just because >> and and a lot of the stuff late-stage, if if somebody, you know, there's so much demand and there's so little supply that if somebody comes to you and they're like, "Hey, I've got SpaceX at 1 and 1/2 trillion."
1:12:01
And somebody's like, "Do I I'm really if I believe Elon can get this thing out at 1 and 1/2 trillion, sure.
1:12:07
I'm going to be flat over until they get out or whatever, but at least I'm in, right? So, I don't know.
1:12:16
It it it it it uh people will start to be able to justify almost any any price up until that point. >> Sure.
1:12:23
And I know Matt MacGruber is on this, you know, warpath against these um Yeah, SVB house first. >> Yeah, yeah, yeah.
1:12:29
So, I mean, I feel like the only solution is we have to have a private we have to be able to trade like just like Polymarket private private companies.
1:12:37
And there's there's a big battle brewing behind the scenes over this.
1:12:40
We'll see where we'll see what comes of it, but >> Okay, speaking of Elon, speaking of XAI, SpaceX, uh walk me through all of the internal secrets that you learned from the infamous podcast.
1:12:52
if if your most junior employee went on a on a on a cinematic podcast for for 90 minutes and [laughter] just told all about Goedel and everything, would you uh >> Yo, how would you react? >> How would you react?
1:13:07
I I think, you know, the first my first like week in hedge funds, I thought this was a good idea.
1:13:12
And then I I the my sense for asking the boss just like kicked in at the last second. Yeah.
1:13:19
>> [laughter] >> Like Wait, so you were going to call up Bloomberg and say like, "I got to tell you, we're working on some exciting stuff.
1:13:25
I got to tell you about some of our new trading strategies."
1:13:26
This specific market is wildly mispriced and we're going to make a killing. We're printing.
1:13:32
I was long the stock and the company told me, "Oh, we're doing this in newspaper piece.
1:13:36
Do you mind giving a quote for it since you're an our investor?"
1:13:39
And I I told our CFO, I said, "I'm going to be doing this, just so you know." And he's like, "No."
1:13:44
No, you will not be doing that.
1:13:46
Okay, so what did you actually learn from from the XAI deep dive?
1:13:52
I think it's less about learning than more about like who's the gumption of like the way he answers questions.
1:13:55
I can understand like, "Look, you're an engineer.
1:13:59
You should be able to go on a podcast.
1:14:00
Questions come up about XAI.
1:14:03
You probably say, 'Look, I can't really talk about it.'"
1:14:04
You might drop a few things, but you know, he was really like people asked the the interviewer asked him how is Optimus going to roll out?
1:14:11
And he was like, "Let me tell you."
1:14:14
>> [laughter] >> That's Elon's job, you know, it's not yours.
1:14:17
And so, the real reason I kind of came after this guy in a not-so like kind of an oblique way is he had I looked I looked up this guy.
1:14:24
I have a lot of friends at XAI.
1:14:26
I was like, "Who is this guy?" And he had blocked me. Mhm. I said, "Oh, no, no, no.
1:14:30
[laughter] This is a big thing."
1:14:32
So, I'm going to amplify you know, that you did this.
1:14:35
And again, I mean, I think the guy was fired, you know, >> Okay.
1:14:40
at least the second he went on the show.
1:14:42
I doubt that I had any part to do with it, but I I definitely didn't mind amplifying the the insane kind of decision he made.
1:14:47
And you know, if you block me, that's that's I mean, Ro Khanna. Ro Khanna.
1:14:55
No, he came at me for absolutely no reason.
1:14:57
I said, you know, I I replied to his tweet like 80 million other people. Like this is a bad move.
1:15:01
And I wasn't a I I was like, "Look, I think that the problem is that it's not the billionaires that it's the billionaires and their teams. Right?
1:15:12
So, if Peter leaves uh California, if if Palmer leaves California, if Elon leaves California, it's not just them who leave. Yeah.
1:15:21
works for And that's and it's every florist that works for those guys.
1:15:24
I'm trying to find florists.
1:15:26
Well, yeah, yeah, cuz you you have you have the the highly productive, high-agency team members that are like, "I want to be in the same building as my boss every single day because I don't want to go to work remotely, like you said.
1:15:39
And if I'm going to be a serious player at this company, I need to be have proximity to the person I mean, yeah, the the average billionaire family office has got to be 50 employees.
1:15:48
Their families like it gets pretty big when you think about the footprint.
1:15:55
the companies they're running, right?
1:15:55
I mean, just the companies they're running.
1:15:57
If if it's There has to be a ton of new employment in Texas because of this.
1:16:00
And then it will only continue.
1:16:02
I mean, I heard I heard Jordan was just saying that that uh he's like Ro Ro Khanna is just rage-baiting you guys and you just completely, you know, played into it.
1:16:11
And and I I think that's I'm I'm sure Ro will use this to set up, you know, his next uh his next play.
1:16:17
But it's still it doesn't take away from the fact that you're going to leave.
1:16:21
I don't care if you like if you're just using this as a as a stepping stone to like, you know, go to the national stage being like, "I stood up against the California billionaires that weren't playing their fair share."
1:16:33
Well, like I live in California and I had we still have to live with the consequences of like your political ambitions, right?
1:16:38
And pushing something that that's so obviously, you know, I I said like, "What do you want California to become?
1:16:44
Like an agrarian society, you know, where it's just like agriculture and and vineyards and tourism?"
1:16:51
Like there's a lot of like every other state will be happy to take take these jobs and and uh you know, host these companies.
1:17:00
Um and uh I don't think we should just, you know, hand them all over.
1:17:04
What's really crazy is you you my my partner's at one of the big AI labs.
1:17:05
And you know, if she leaves California and then sells her stock, California will, you know, kind of come after you.
1:17:12
And someone just posted this um really almost like fascist letter that the California tax department sent them.
1:17:20
I don't know if you guys saw this. >> Yeah, I saw it. I saw it.
1:17:20
Yeah, yeah, it was insane.
1:17:22
It's basically the the the letter was like, "We want to understand the narrative of why you left California."
1:17:28
It's like, "Tell us spin us a yarn.
1:17:31
>> [laughter] >> Give us tell us a story on how you decided to on how you had the audacity to leave this state." Yeah. Uh I I'm shocked by it. Yeah.
1:17:39
On on on XAI, did the uh did the podcast make you more bullish on the strategy at Open at at XAI specifically?
1:17:49
Were there things that you thought were particularly exciting about what was what was laid out or things that you uh thought were maybe misunderstood or mispriced?
1:18:01
It's hard to tell from the junior engineer, you know, it's I think like, you know, you get a window, which is great, but it's also it's Elon's show.
1:18:08
And like the risk of of over-indexing to something like that is like, "Okay, this guy saw it. He worked there. That's cool."
1:18:14
But what is Elon really thinking?
1:18:16
And I think that there's this new thing coming from the AI companies that nobody's expecting.
1:18:23
And you know, I wanted to see if he was going to drop sort of that.
1:18:28
And I think all of the labs are gearing up to think about this.
1:18:33
Uh and it's sort of this new um derivative of of kind of the outcomes of AGI.
1:18:38
And I think almost nobody in the market's talking about it.
1:18:42
Um so, it's going to be very interesting to see how the next I'll I'll just, you know, leave the teaser there.
1:18:47
See how the next uh No teasers. Unpack it for us. Break it down. 5 to 10 years. I can't. >> You can't. Okay.
1:18:52
next 5 to 10 years comes.
1:18:55
But I I I think that the question is really what what can AI really do? Yeah.
1:18:59
And I think that we've we're we've very much over-indexed to chatbots Mhm. and LLMs.
1:19:04
And like a good a good new direction, you know, people have talked about endlessly is robotics.
1:19:11
But imagine there's 50 new directions, you know, and I think that you know, I hate to say something like this changes everything, but like there there's a couple of clever ones I I coming that are just haven't been seen yet, and I think the smaller like the non-Google, non-Meta, I'm sorry, non-Google, non-Microsoft type of players, you know, including X is kind of what I'm thinking about are are are actually thinking about this very very heavily.
1:19:35
And MacroHard, I guess MacroHard is kind of, you know, an example of like what is that really?
1:19:38
And what's really going to be MacroHard as we see you know, MacroHard be revealed more and more.
1:19:46
I think there's a lot more to that than you know, in some ways I think MacroHard's going to be bigger than XAI.
1:19:52
It's all the one entity if I'm not mistaken, but [clears throat] it MacroHard is probably worth more than XAI, and I think that we just don't know what's coming out of that.
1:20:00
We also know about Elon's gaming AI gaming ambition, which I think Yeah.
1:20:04
And and I don't know if you guys have seen Martin Casado's Yeah.
1:20:07
uh coding is very cool stuff. Yeah.
1:20:10
And uh you know, it's amazing that guy can invest and uh do that stuff.
1:20:14
And I think one leads to the other.
1:20:16
I sort of do the same thing for for my end.
1:20:17
I wanted to talk to you about really fast uh this idea of photonic computing, Okay.
1:20:21
which I think is time is coming. Okay. Explain.
1:20:27
>> So what Yeah, so photonic computing is is what it sounds like.
1:20:30
It's using light instead of electrons to compute. Mhm.
1:20:32
It's it's been around for 50 years.
1:20:35
It's sort of like quantum's ugly stepsister, >> Mhm.
1:20:38
but it I think it's actually the belle of the ball because and there are very few companies working on this.
1:20:43
You probably know all about it from Interconnects, Yeah.
1:20:47
Silicon Photonics as well.
1:20:47
But recently in Nature and a few other like preeminent sort of journals, especially Chinese companies have shown they can do matmuls with light. Huh.
1:20:56
And it's actually pretty remarkable.
1:20:59
Light goes to 100 terahertz, but it's more important than that, it it actually is is you can do 3D matmuls in they're all of one complexity.
1:21:09
>> [clears throat] >> So it's a pretty insane speed up versus GPU.
1:21:11
GPUs are great, but they're almost too general, which is why TPUs have sort of been there.
1:21:16
But if you throw out the need for, you know, lots of different instructions, you just need to do a matmul, which as you guys know is 95, 90, 95% of what a GPU chip's doing all the time.
1:21:25
A matmul is done with light very naturally through constructive and destructive interference.
1:21:29
It's it just nature does it.
1:21:32
So I think this could be an interesting new space, and I'm I'm spending a lot of time on it, and you know, very curious about, you know, uh could there be a chip?
1:21:39
There's a couple of private companies, Mhm.
1:21:40
um and I'm starting to dig around and, you know, see what's what's here.
1:21:44
I think most people stop short of actually making the full photonic computer because they need revenue, they need earnings, they need something.
1:21:51
And Celestial AI, they got bought out by Marvell, you know, they there's some or Marvell, there's some attempt to sort of do push more and more of like we used to use copper wires to transmit information.
1:22:05
Now we use photonics and fiber.
1:22:06
And more and more of the chip and more and more of the entire global kind of computer infrastructure is going photonic.
1:22:12
And maybe the whole thing goes photonic someday and that electricity is actually the odd man out.
1:22:18
It photons don't have some properties that are perfect for, you know, computing, but others like in the case of matmuls, which is now like most of the compute we need in the world, they're actually kind of perfect.
1:22:27
So, you know, it's it'll be interesting to see if there's one of one private Chinese company called Lightelligence, and it sort of has a foot in the rest of the world.
1:22:36
They're in Singapore, but they're also a foot in China.
1:22:39
They started at at MIT, Mhm.
1:22:39
so they're privately held.
1:22:42
There's Light Matter, which it's not really clear that they're still pursuing kind of all optical photonics.
1:22:47
And then Microsoft's done done a little bit in space, too.
1:22:49
So I'm I'm really interested in this this is the potential next like as we think as Grok, that position of Grok has sort of and the quantum insanity, this is kind of why I care about this in the first place.
1:23:01
I'm a biotech guy, you know, this is very weird for me to think about this, but um the Grok acquisition for 20 billion, the quantum crap that's trading for 10 or 20 billion, people really want to think about what's next in compute.
1:23:13
And of course the the unconventional and their raise at 5 billion just for a new co, um that's it's it's all sort of clear that anything that can beat an Nvidia matmul in my opinion could be Lightelligence. Mhm.
1:23:28
Uh what's the state of the quantum computing market?
1:23:29
It seems like the companies have not sold off, but you went viral on a podcast sort of breaking down your overall thesis.
1:23:37
Is the market sort of waking up to your way of seeing the timelines around quantum computing or the impact of quantum computing, or uh is there still more work to be done on your end?
1:23:50
Yeah, so I I think there's no more thinking that needs to be done.
1:23:52
I think this is a war of attrition where both sides are right.
1:23:56
And this is why I've kind of started to look for for other kinds of compute. >> Mhm.
1:24:00
Um and as as you know, our great friend uh Jeff Bezos has has his own kind of compute.
1:24:04
So like the point is you got a 5 trillion market cap, and if you if you bought a stock at 5 billion, which is not a small cap, that's a big company. Yeah.
1:24:14
Most of us would be very happy to exit at 5 billion. >> Yeah.
1:24:17
You can still get a thousand X. That's right. Right? If it's the next Nvidia. So if you even have a 0.
1:24:22
1% chance that one of these quantum stupid companies is the next Nvidia, I mean, take a flyer, you get a thousand X.
1:24:29
So I feel like there there kind of is a rational thinking there, even if it's impossible, you know, who's to say what's the difference between 0. 1 and 0. 0?
1:24:37
It's it's the kind of difference I think about, but most other people don't care.
1:24:41
And so any chance to get It's like the menu problem.
1:24:44
What's on the menu for the average Joe versus what's on the menu for you and me.
1:24:47
We might get in a Grok round.
1:24:49
We might get in an unconventional round.
1:24:52
The average person can't, but they can buy $2,000 Rigetti or or D-Wave on their Robinhood, and maybe they'll get the same kind of, you know, self-manifesting in some ways, you know, beta. Yeah.
1:25:02
But I'm also curious if you guys want to talk at some point, expand this and talk about biotech more. Yeah. Yeah.
1:25:09
Yeah, we'd love I mean, I I'm like give it give us a lay of the land currently, how you're thinking about the year broadly, what's exciting, uh what what's maybe uh being oversold about AI's potential impact in biotech versus being underappreciated.
1:25:27
Yeah, I think that this the Nvidia Lilly have made announced this big partnership. Yep. Um billion.
1:25:34
>> And I've been thinking about drugs and AI more and more and more, and I feel like there is something to do here, but it's not the stuff that everyone thinks about like drug discovery itself or for small molecules or even proteins, I'm not sure AI is is very useful.
1:25:47
We have great forcing functions for that, whether they're physical chemists or software.
1:25:52
You don't need a 10X or 100X improvement in that.
1:25:54
The actual part of drug discovery, and I can say this as a, you know, very uh worn out drug company CEO, the biggest problem of drug companies is the people.
1:26:06
And there's fantastic people that work at drug companies.
1:26:07
It's just that you have 10, 15, 20 different departments that have to talk to each other, whether it's toxicology, you know, pre-clinical, PK, you know, there's all these little subsections.
1:26:20
They all have to talk to each other, and everything gets lost in the translation.
1:26:22
Project management is supposed to sit on top of all that.
1:26:25
It just often makes it worse.
1:26:25
And so you have this like impossible You know, you talk to anybody that works in big pharma, they'll tell you how how ugly it is.
1:26:33
Um and so if you had machine doing it, it'd probably probably work better.
1:26:37
And I think that more and more companies are going to whe- whether it's a drug company or law firm or anything else, there's going to be these sort of self-organizing, you know, um more decision-making gets pushed down.
1:26:50
You know, sometimes I ask ChatGPT about, you know, what would be a better marketing strategy?
1:26:53
Or how do I how do I get more users? What should I do?
1:26:57
It's like, "Oh, have you thought about, you know, this?"
1:26:58
And you know, sometimes you'll you'll get something surprising.
1:27:02
So I think that's sort of the angle I play for drug companies. There's so much inertia.
1:27:07
Often times the CEO will like kill a drug for no reason.
1:27:12
He'll promote another drug for no reason. Data says no.
1:27:13
The chief scientist, you know, has a personal vendetta with another company.
1:27:18
He really wants to push that drug.
1:27:20
Like there's all these irrational decisions that get made over which is basically hundreds of millions of dollars to spend.
1:27:25
And it it's remarkably inefficient.
1:27:28
So when Viveik came in to try to really upset the apple cart here, Yeah.
1:27:31
um as as as I did, too, we sort of did the same thing.
1:27:36
It was a little tricky because it's just not an industry that moves fast and breaks things.
1:27:40
And for all the occasional luck you get on a drug, there's a lot of that luck is distributed as well.
1:27:46
So Viveik got a lot of bad luck sometimes with Rory Vance.
1:27:51
He got a couple of things of good luck. It's done fine.
1:27:52
But like it's very hard to get the compounding effects that you get.
1:27:57
So Lilly has somehow been able to do it because that drug is not going to go generic.
1:28:00
But again, the problem is you make a great drug, you have a great hit, you have 10 years to make money, and that's it. Mhm.
1:28:05
And so, you know, none of these AI companies would be worth anything if in 10 years they they all um had to give up their assets because there was a generic AI company.
1:28:15
So I feel like drug drugs still are in this perilous situation.
1:28:17
The whole industry is sort of cooked um because there is fewer and fewer drug targets to go after. Yeah.
1:28:24
So we keep fighting over the smallest number of patients in these random diseases, sometimes like the slight skinniest slice of cancer where there's like 600 people have it, and there's like 12 drug companies that are developing a drug for it.
1:28:38
And so there's overcapacity in the industry.
1:28:40
I mean, the same thing happened in steel and some other places, and we arguably have too much going on.
1:28:44
And the real fear right now is China.
1:28:44
Um the China drug development capability has gotten so good >> Mhm.
1:28:49
that there's really no Who who was it that was saying like yeah, I would hate I would hate we all want to cure cancer, but I would hate if China cured it before us.
1:28:58
[laughter] Which is a wild quote. It's a wild quote.
1:29:02
On on on the AI impact in in pharma, drug discovery, what is the lever that we should be watching between, you know, more frontier models basically raising the IQ, making them smarter, more knowledgeable, versus just speeding them up, getting the state-of-the-art models running on Grok or Cerebrus, so that it's faster, so you can do more.
1:29:23
Or is it more of like a adoption diffusion training?
1:29:29
You need to just get the CEO to actually have like turn AI loose in the organization.
1:29:35
It's like a change management problem.
1:29:36
Well, I think I mean I think you mentioned HR and one thing I think XAI should do is take a little bit of macro hard and build an HR function that when employees just say, "Hey, can I go on a podcast?" it just says >> no.
1:29:52
I think it'd just be an if statement.
1:29:53
>> And it's like, "Yeah, you if [laughter] Elon, yes."
1:29:55
>> If if podcast mentioned, say no.
1:29:59
Anyway, uh it's the keys to success in AI and bio.
1:30:03
I think that I think pharma is a misunderstood business.
1:30:04
So, there was a this this sort of drug goat, this guy named Paul Janssen.
1:30:08
So, he created um Janssen and Janssen was acquired by J&J, but Janssen himself just personally invented, you know, I think half a dozen to a dozen critical medicines, not like me-toos or anything like that, but like he personally discovered, you know, I think the first antipsychotic, fentanyl, antipsychotics, several like massive massive From the creator of fentanyl, we have anti- >> It wasn't that back then, [laughter] right? No, it was good.
1:30:38
It was It's very useful, yeah, in many cases.
1:30:40
Uh what are you How are you um how are you processing the peptide boom? Yeah.
1:30:48
Well, that whole thing is another story, but I I want to get back to Paul.
1:30:49
So, there's there's statues of this guy in Antwerp.
1:30:54
We need more Paul Janssens, whether they're digital synthetic bio synthetic sort of intelligence or not.
1:30:58
The drug industry is an idea industry. Okay.
1:31:02
>> not an industrial process.
1:31:02
It's some guy sitting down saying, "You know what I think would stop cancer?
1:31:06
If we made an HDAC inhibitor."
1:31:08
Well, actually people tried that, it doesn't work.
1:31:09
So, and then somebody saying, "I read a paper about this and you know, actually maybe this would do it."
1:31:14
Is the same thing as like getting a digital Ilya who can just go and try a bunch of AI research ideas?
1:31:20
You get the AI researcher in a box, turn that loose, and then that unfurls into progress. Certainly a challenge.
1:31:27
Is that constrained by hardware, compute scale?
1:31:32
Are you still scaling pill, or is there an idea that will will lead to that?
1:31:39
It's a great question cuz in the in the old days, if you wanted to run computer experiments, you didn't need much cost.
1:31:44
In fact, that was a fraction as I used to sit there and and write code.
1:31:46
And now it's like, "No, no, I need a cluster."
1:31:48
And for drugs, you know, it's it's sort of has always been an expensive capital, you know, thing, but in the scheme of things, you know, it's cheaper than AI.
1:32:01
>> [laughter] >> You know, you you could you could probably get some proof of concept in in animals and and people for, you know, less than you might imagine.
1:32:10
And then from there, you know, you could develop a portfolio of drugs.
1:32:15
So, I I think that, you know, getting the idea part of the drug discovery industry more sort of capable is is one thing AI can help a lot with.
1:32:25
And that downstream means less expenses in clinical trial development, and also the decision-making.
1:32:29
Somebody looking at the data and saying, "Look, this drug is a dog.
1:32:32
Let's not do a phase two.
1:32:33
Let's not do a phase three."
1:32:33
And oftentimes the scientists and the the companies have like, I don't know, Wall Street wants us to see it see us in phase three.
1:32:40
We can't really fall behind our rival.
1:32:42
And and they'll often push I mean, I'd say up to a half of all drugs in clinical trials shouldn't be in clinical trials.
1:32:50
And you know, that's uh That's a lot of money wasted.
1:32:52
That's a lot of patient time wasted.
1:32:53
And and a lot of it is pushed by other incentives and other things like that.
1:32:56
So, I think AI has a lot of, you know, potential for for drug discovery, but every time I talk to somebody that wants to talk about AI and drug discovery, they've never been in a drug company.
1:33:06
They've never actually done it.
1:33:07
And when you do it, you realize it's much more about who's Paul Janssen discovering the next, you know, bunch of hits and who's lucky and got a one-hit wonder, and then who just sucks in general, like Pfizer or something.
1:33:19
And so, you you sort of have to like generate those ideas.
1:33:21
Uh it's almost like an investor in hedge fund space.
1:33:25
>> cuz cuz I feel like I can't remember who exactly, but there was somebody on the show that was saying we we don't need It's not that we don't need more ideas, we need a cost reduction across the rest everything from that point. Yeah.
1:33:36
But But most of the cost is clinical trials.
1:33:40
So, you Well, yeah, and so what you were saying is like if you have these 15 departments and if you can somehow make it so that, you know, you you can have Is it a Is it a head count like how much is like a head count reduction actually going to impact overall cost?
1:33:52
I think it's all clinical trials.
1:33:55
Like so, once you've invented a drug, say that costs 10 to 50 million, the next four or 500 million is going to find a bunch of people to try it and compare it to placebo because you have to monitor those people so carefully and so closely that it ends up being this massive cost across, you know, tons of clinical trials. That's the hard part.
1:34:13
Um if you could just take shots on goal for 50 million, 20 million left and right, um you know, you'd have a really productive drug industry.
1:34:21
But unfortunately, getting 10,000 people to take a new diabetes drug is it's pulling teeth.
1:34:25
And you you have to like really, you know, incentivize doctors and patients, meaning you have to pay them.
1:34:31
And once they do that, you have to pay the company that collects the data.
1:34:34
You have to pay the company that, you know, sort of puts it together, sends it to the FDA.
1:34:38
All that stuff is like just massive paperwork.
1:34:41
Uh and it's it's it's a lot of it's done still on >> How is China's process for running clinical trials different than ours?
1:34:50
Very similar, but like I think the wages that they pay the people to collect all the stuff is less.
1:34:54
And I think that they they sort of have it a little more streamlined.
1:34:59
I mean, it's it's amazing what they can do.
1:35:00
Like so, one of the things that confused me about China the first time I looked at it in biotech was like the average mid-sized American biotech is like 100 people, 200 people, maybe 300.
1:35:09
But in China, it's like 6,000 people work at the same market cap.
1:35:15
Wow, what are they doing? You know?
1:35:17
It's like, "No, we have like 800 chemists sitting here."
1:35:19
>> [laughter] >> Wow, what are they doing?
1:35:21
>> just because of the structure in America, we have more like labs and consultants, and we still employ 6,000 people, but it's all at secondary and third-tier supply chain companies? Maybe.
1:35:32
I I think it might be more capital markets, where it's like they raise the same amount we raise in in the Hong Kong market.
1:35:38
So, they raised 300 million.
1:35:40
I said, "Well, what is 300 million buying you in China?" A lot more people.
1:35:43
I said, "You have 800 chemists, you know?" 800 chemists.
1:35:45
Whereas you have about 40 chemists in San Diego. Yeah, yeah, yeah. That's crazy.
1:35:48
What is What is your take on on the peptides boom? Yeah.
1:35:54
Yeah, and peptides are, you know, every time somebody asks me about it, I have to laugh because peptide is a defined as a a small protein. Mhm.
1:35:59
And so, what you're really asking is what is my take on the on approved self-medication boom. Mhm.
1:36:08
And you know, when you phrase it that way, Yeah. No, no, no, no.
1:36:09
And that's that's like to me to me, I I uh I I tried a peptide cycle probably five years ago.
1:36:19
And I was like, "Okay, this is like cool."
1:36:21
And I noticed like a moderate effect, but I also acknowledge that like this is I'm like administering administering like effectively an experiment like experimental drug is not the right framing, but it's it's not like the same as like walking into Erewhon and getting some vitamin D and, you know, having a having a daily supplement.
1:36:41
It's like you're like inject your your you're doing an injection, the source matters a ton, and it is I you know, far closer to, you know, taking a round of anabolic steroids than it is, you know, adding adding some creatine to your smoothie.
1:36:59
I I just think it's nuts.
1:36:59
I I just think it's nuts. I mean, if you think it's a good idea to do your own research on medicine, self-medicate, and on uncontrolled substances that are manufactured God knows where that have not been clinical trials, and I mean, I'm I'm as libertarian as it gets, but I I I just don't understand why what the impetus is
1:37:19
to like take foreign substances without like some emergency need, and it just it's it boggles my mind because, you know, people I there's some psychological phenomenon where people need to feel in control, or they need something in their life that they feel like they're taking a risk on, or, you know, it's nuts. I mean, why why would
1:37:34
I mean, why why would you do it?
1:37:36
>> Well, and and and explain why there probably will never be clinical trials for these drugs. Right.
1:37:41
There's this edge case where, you know, you have a cosmeceutical in in essence, or kind of like something that doesn't quite fit what's a disease to the FDA.
1:37:49
So, a good example is premature ejaculation.
1:37:53
Um so, the FDA does not consider that an illness.
1:37:55
Um European drug regulators do.
1:37:59
And so, you can get approved for impotence in America because it's actually sort of a medical problem, where it's like, "Oh, if I can't, you know, copulate or reproduce, it's it's a big medical kind of emergency in a sense."
1:38:10
Premature ejaculation is sort of like, "Well, you have it."
1:38:16
And you know, so the FDA has never been willing to approve a company.
1:38:17
A long time ago, they tried to get an old J&J drug called dapoxetine approved for premature ejaculation, and the FDA basically said there's no set of circumstances where we will approve this.
1:38:26
And you know, what's weird about that is, okay, well, what if you actually do supplements?
1:38:32
And it's a severe psychological detriment.
1:38:34
As much as we joke about it, people joked about erectile dysfunction a long time ago, and it's it's a serious, you know, illness to many.
1:38:39
So, you you sort of live in this twilight of like, well, I I know what drug works.
1:38:45
This drug dapoxetine actually does work.
1:38:47
But I also know that it'll never be FDA approved. So, what do I do?
1:38:50
And in some ways, you know, you're you're sort of like, "I'm taking an unapproved, technically illegal substance, and I'm buying it off some shady, you know, third-party market."
1:38:59
So, eventually I think we need to find a way, just like almost like what we just talked about prediction markets.
1:39:03
You have these third markets, where it's like, "Yeah, you can bet on, you know, what Trump's going to say in a speech."
1:39:08
And it's It's a registered stock exchange, but it's also more than just you and me making a side bet.
1:39:14
And it's the same thing with with this where it's like depakine is not a peptide, but you know, I depakine is medically useful for that disease, if you call it a disease, FDA won't say no.
1:39:24
So, it's not like I'm taking some random goop, you know, it's a real medicine, but it's it's in this middle of like, what do you do with this thing?
1:39:29
And so much of, you know, so much of what we do as investors or whatever is in that middle.
1:39:35
Uber, you could sort of define Uber as in that weird middle as well.
1:39:38
So, I think eventually, you know, we need to address like, it's not as insane as maybe I'm I'm making it out to be.
1:39:43
I think some of it is, but eventually you need to address this like, how do we Yeah.
1:39:50
Do peptides >> Well, even even like, yeah, BPC 157, like there's no incentive to spend the tens of millions of dollars on trials because like, you would need some type of like, you know, trade group or something in order to fund that because if one company did it, then every company would get the benefit of it.
1:40:05
So, why would one company spend the tens of millions of dollars >> for that.
1:40:10
In drug development, we have an app for that.
1:40:12
We we can take that drug, twist it, change it, figure out make it better, you know, and and then you get a new patent.
1:40:19
And then you have an incentive.
1:40:20
So, there there is sort of a way to do that, and that's not that's not uncommon.
1:40:24
I mean, you know, trolling around PubMed looking for, oh, this drug actually does something, I'll make, you know, take it to my boss at Merck.
1:40:32
Boss says no patent, come back the next day and say, here's the same drug with a nitrogen atom coming out of here.
1:40:38
It's going to work the same way.
1:40:40
And he says, all right, well, you know, maybe we should run with that. >> Run it. Yeah. Run it.
1:40:43
Well, thank you so much Always fun. Always fun. Come back soon.
1:40:49
Yeah, come back on again soon.
1:40:49
I have a bunch more questions I want to ask about Go Dell and everything, but good to see you. Yeah.
1:40:55
Congrats on the progress.
1:40:55
And congrats on the new on becoming a father. >> Yeah, fatherhood. Massive. Massive news. Great stuff. We'll talk to you soon. Have a good one. Goodbye.
1:41:04
Phantom Cash, fund your wallet without exchanges or middlemen, and spend with the Phantom card.
1:41:09
Uh our next guest is Bradley Tusk, the founder and CEO of Tusk Ventures.
1:41:15
You might know him from his work with Uber.
1:41:17
Thank you so much for waiting. Welcome to the show. How are you doing? Good.
1:41:22
Thanks for having me, guys. Fantastic.
1:41:25
>> I'm upset that it took us over a thousand guests to get you on. >> Yeah, it's I know.
1:41:29
I have I have to say >> I know.
1:41:31
Uh so, you just hired a friend of mine named Jackson Fordis.
1:41:34
Do you guys >> We love Jackson.
1:41:36
So, I mean, he I literally had to like call him a few weeks ago where he's like, what do I do with my life?
1:41:41
And I said, take the job.
1:41:44
Those have never had me on.
1:41:45
>> [laughter] >> And so, those two things came together.
1:41:48
But Well, glad we could do it.
1:41:48
Yeah, but I mean, you're getting an incredible person in that hire.
1:41:51
So, good really nice job there. That's great news.
1:41:55
Uh tell us about the bookstore.
1:41:55
I heard that you have a bookstore. I do.
1:41:57
So, first of all, anyone is looking to lose money, I highly recommend owning a bookstore.
1:42:06
So, you know, I've written a couple of books.
1:42:08
I had started this thing called the Gotham Book Prize in 2020.
1:42:11
In fact, we announced the nominees for this year today.
1:42:14
And I'd always thought like, one day it'd be fun to own a bookstore, but it's kind of thing you would just do later in life.
1:42:22
And then during COVID, New York City just got whacked by everything.
1:42:24
And we lost, you know, half a million jobs.
1:42:27
And my thought was, look, if you're going to do something nice for the city from a retail perspective, because I knew I wasn't ever going to make money on it, like now's the time, right?
1:42:37
Don't wait till you're 70 or whatever it is.
1:42:38
And so, we started looking for space.
1:42:42
And we found one on Orchard Street on the Lower East Side.
1:42:46
If anyone knows where that is. And it's a great spot.
1:42:48
So, it's about 3,500 square feet. It's an indie bookstore.
1:42:53
It's a podcast studio that is free for anyone to use.
1:42:55
You just go on our website, and you can sign up and use it.
1:42:58
If you guys are ever in New York, you're welcome to use the studio.
1:43:02
We've got an event space.
1:43:02
We built an amphitheater that seats about 80.
1:43:04
So, we have authors or different types of events like open mic, teenage poetry, or whatever, pretty much something every night. And a cafe.
1:43:12
And the store has a funny name.
1:43:15
And the reason why is So, when I when I leased the space, I texted my dad and said, didn't the store that my grandfather started when they came to this country in 1950, wasn't it right around here?
1:43:29
Because that store was closed before I was born, but I knew it was right around there.
1:43:32
He's like, yeah, it's was one block over on Allen Street.
1:43:35
And I said, remind me the name.
1:43:37
He said, P and T Knitwear because, you know, if you were an uneducated Jew that survived World War II, the one job you could get in the US, especially New York, was in the garment business.
1:43:49
So, my grandfather started a sweater company.
1:43:51
And then my dad wrote P and T Knitwear, but you cannot name a bookstore P and T Knitwear.
1:43:58
So, of course, our store is called P and T Knitwear.
1:43:59
So, >> [laughter] >> so that's our store, and yeah, other than the fact that, you know, nobody buys books, it is a really fun business to own and run, and a fun place to hang out.
1:44:11
So, anyone who is watching, if you happen to be in New York, you like bookstores, check us out. That's very cool.
1:44:17
What's it going to take to get it profitable? Mhm.
1:44:21
I don't think it's possible.
1:44:21
You know, there's not there's actually not one.
1:44:24
So, because I've looked at like, okay, let's say I ran it aggressively.
1:44:26
We charged for the studio, we charged for the event space, we didn't give the employees health care, all this, you know, other stuff.
1:44:33
We would still lose money.
1:44:36
>> [laughter] >> So, I don't quite understand how somebody actually makes a living running a bookstore.
1:44:40
I'm sure Manhattan's sort of the worst place to do it.
1:44:42
But still, but even like in LA, like my friend Zibby has a great bookstore in Santa Monica, but the same thing.
1:44:47
She's, you know, lucky to you know, have other money, and she part of the way she uses it is to have this indie bookstore.
1:44:53
So, it does seem like sadly, you know, bookstore ownership these days is somewhat equated with philanthropy. Yeah. Yeah. Oh, well. >> Yeah.
1:45:02
Uh well, yeah, let's get back to let's get back to business.
1:45:06
Um I want to talk about specifically these businesses that you've been involved with where you've been so helpful to founders on the local and state regulation level, how companies position themselves.
1:45:22
Uh it feels like every company right now is focused on what's happening in DC, the federal level.
1:45:28
Um how do you how are you how do you think about what's different when you're working with a company at the local level?
1:45:35
What are the what's the playbook?
1:45:37
What works if you have a problem and you need to change local laws?
1:45:43
What are you recommending to new founders? Yeah.
1:45:45
So, the first thing is, look, human beings naturally, or Americans at least, when you say the words government or politics, your mind kind of instinctively goes to DC.
1:45:53
So, you think about the capital, the White House, Trump, whatever it is.
1:45:57
But the reality is, most regulation, including most tech regulation, does not happen at the federal level.
1:46:04
There's some crypto, biotech, but by and large, most things that touch a consumer in some way, directly or indirectly, are regulated either by state government or local government.
1:46:15
And that's actually a good thing.
1:46:17
So, what everyone thinks is, oh, I'd rather solve my problem at the federal level, it's a one-stop shopping, I one-shot, whatever, I got my thing done, I'm set.
1:46:25
But, you know, the phrase an act of Congress is literally synonymous with a miracle, right?
1:46:29
You can't base investment strategies on miracles.
1:46:32
Whereas in states, and you guys had my friends, you know, Adam and Matt from DrOnc on a few weeks ago, where we worked with them to make Utah the first state to allow prescription via AI.
1:46:44
Um in states, you can get things done.
1:46:47
And we don't necessarily win in every state every time, but by 50 by 50, we take the apple.
1:46:52
We can figure out this makes sense for a red state strategy, blue state, whatever it might be.
1:46:57
It might not matter in that way.
1:46:59
And because states have sort of six-month legislative sessions in which typically a couple of hundred bills on average pass, you have a reasonable chance of getting your same thing done if you run a good campaign.
1:47:10
And then once you establish precedent for it in one state, you have a stronger argument to then invest in, we highly prioritize companies that can get their stuff done at the state and local level because I don't invest in stuff where I don't think that we can move the needle for the company itself, and I think our odds of doing that are so much better outside of Washington.
1:47:36
How confident were you that you guys could get this a deal like the one you got done in Utah with DrOnc?
1:47:44
Like when you when you invested Yeah, yeah, cuz I was I was Yeah, we kept having to like be like, really? That's what happened? Really? I know. I know.
1:47:52
We even we, we're we literally the people who do this for a living, right?
1:47:56
The company only fund that does this.
1:47:58
And even we were like, wow, that one was pretty cool.
1:48:02
But, you know, there are states that are very thoughtful around AI regulation.
1:48:08
And there are a couple of states, Utah, Texas, Arizona, Kentucky, that have created regulatory sandboxes.
1:48:15
Do you guys know what that is? Little bit.
1:48:17
So, it's effectively like a notion saying, okay, you know what?
1:48:19
There's this thing that we know is really important.
1:48:22
We know it's going to take experimentation, and rather than subjecting it to the political process, let's put together a team of experts who can, at least on a provisional basis, say, we're going to try out these ideas in our state, and as long as it's working the way we thought, it'll keep going.
1:48:37
And those are four states that have chosen to do that.
1:48:39
So, those were the obvious places for us to start.
1:48:44
Utah is just a really well-run state.
1:48:47
Governor Cox is is an excellent governor.
1:48:50
And so, we and they're not a typical state for a lot of reasons.
1:48:52
And also, they are becoming a very very tech-forward and friendly state because you've seen migration, especially from California, let alone before the billionaires referendum tax thing happens.
1:49:06
Utah is becoming, you know, Silicon Slopes are calling it.
1:49:08
So, um, yeah, we're going to Texas next, uh, which is a giant market, obviously, the second biggest in the country.
1:49:14
Um, and, you know, once we start showing that it works, you know, it even if you think like the very first tech company that I worked with was Uber.
1:49:21
Um, started doing that early 2011.
1:49:26
And the thing that that Travis Kalanick, who was the founder and CEO of Uber at the time, understood, and he was right about it, just get the genie out of the bottle.
1:49:33
I mean, Travis didn't pretend to understand politics, but what he did know was that he had a product that was meaningfully better than the status quo.
1:49:42
And if you guys think back to the first couple times you used Uber, it was magic, right?
1:49:46
You couldn't kind of couldn't believe it.
1:49:47
You just pressed a button and this nice car showed up and here they were and you have to like hail it down or deal with some crazy cab company or anything else.
1:49:54
Um, and we knew that once people saw that it worked, they would fight for it, and the arguments against it would get weaker and weaker, and we were able to effectively mobilize our customer base.
1:50:06
Well, you have you have the two it's it's both participants fighting for it, too.
1:50:10
In the in the you have the drivers and the and the users, which is the most powerful dynamic. Right. Right.
1:50:16
And that's So, when you can do that, um, but you know, it's funny.
1:50:20
There is a whole question as to when do you have a product or a service that people will fight for?
1:50:25
And sometimes it's you might have a really good company that's going to be a good investment, but it doesn't sort of excite people in that way.
1:50:33
But what we found is um, FanDuel worked really well.
1:50:38
Um, Bird scooters worked really well.
1:50:40
Eaze, which is cannabis delivery, worked really well.
1:50:43
Crypto, that works really well for us.
1:50:44
So, you know, you have to think about if you're a founder, do I you're obviously passionate about it because otherwise you wouldn't have founded the company in the first place and made all the sacrifices that you've made, but you have to be somewhat objective in saying, okay, do regular people find this thing that I am doing truly critical and fascinating?
1:51:02
>> You said you said FanDuel. You said FanDuel.
1:51:04
So, like are there people out there that will stand up and protest their state government if they try to for banning sports betting?
1:51:12
>> Well, so we we we did that.
1:51:12
So, in 2016, um, the New York Times published an article effectively accusing employees at FanDuel and DraftKings of conducting a form of insider trading where, according to the Times, they were giving each other information to then put bets on the other's platform.
1:51:28
It turned out to actually not be true, but putting that aside, it unleashed this total shitstorm where a couple of dozen states, in the course of a few days, issued cease and desist orders to us saying, you can no longer operate.
1:51:40
And we had to all of a sudden go all over America and either pass bills to legalize daily fantasy sports betting, or at least get them to understand that that we were complying with the existing laws.
1:51:53
And the way that we did that is we went to our customers and said, listen, um, if you like this product, we need you to fight for it.
1:52:00
And every time they were on the app, we knew where they were located and we'd say, "Hey, click here to tell your local state senator, state rep, whoever it might be, that you want FanDuel uh, to stick around."
1:52:11
And enough people did it that, you know, it shifted the political inputs.
1:52:16
If you guys just take a half a step back, in politics, if there's one thing to take away from this interview, it's that every policy output is the result of a political input.
1:52:28
Every politician makes every decision solely based on the next election and nothing else.
1:52:32
And there are some exceptions.
1:52:33
I was Mike Bloomberg's campaign manager when I ran for mayor of New York.
1:52:36
Not for the good of the world? >> [laughter] >> No. Not in the slightest. Right, Mike Bloomberg.
1:52:41
That's who that's pretty much.
1:52:42
So, um, as a result, that's incredibly depressing, admitted, but it's also kind of a useful place to work from because then you have to understand what can I do to make said politician feel like doing what I want will either help them win the next election, or if they don't do what I >> So, the tech industry should tell Ro Khanna, we won't we won't trash you in the next election cycle if you don't put our industry in the dirt. Yeah.
1:53:10
Or quite frankly, it's funny, just by, you know, Larry Page and others acting in their own self-interest and already saying, "I'm moving to Florida," the billionaires referendum is already on the ropes because of that.
1:53:22
So, sure, uh, if you you know, if you think about why, let's say the place like California, there are unions that just SEIU, the teachers have so much power in Sacramento, it's because they have so much money that they can threaten any given politician and say, "If you don't do what we want, we're going to spend a million dollars, five million dollars, whatever number they want, against you in the next election."
1:53:45
And everybody backs down because winning the next election is more important to them than any given policy or any given issue.
1:53:50
So, not every tech startup obviously has the kind of money that a union might have to throw around.
1:53:56
So, you have to be more creative about it, and that's where your customers can be really useful advocates. Interesting.
1:54:02
What's your current outlook on the venture landscape broadly?
1:54:06
We've been talking a lot about the the K-shaped dynamic.
1:54:11
There's a whole bunch of headlines around lower total venture funding, more SPV activity.
1:54:16
What do you what do you see? >> Yeah. A few things.
1:54:18
So, I kind of have I have it from both a deal by deal standpoint and then kind of a macro fund model standpoint.
1:54:23
So, on a deal by deal standpoint, I think we're in this very bifurcated world.
1:54:27
So, um, I started investing outside capital in my first fund in 2016.
1:54:32
In fact, FanDuel was the first deal I ever did.
1:54:34
And at that moment, there was a period of irrational exuberance, right?
1:54:38
Everything was incredible and everybody threw tons of money at everything and every startup was going to be, you know, a unicorn or decacorn or whatever.
1:54:44
Then 2021 came, everything fell off the cliff, and all of a sudden things like unit economics and margins and, you know, burn and all of that stuff started to matter.
1:54:55
Um, and then AI came along, and then so for AI companies, we're back to the 2016 days where people are just having valuations to me that sometimes make no sense whatsoever.
1:55:06
Uh, you know, I've seen seed companies, you know, with valuations in the hundreds of millions of dollars with no product or certainly no revenue. That's crazy.
1:55:14
And yet, some of the discipline that you saw post-2021 crash is still being applied to non-AI companies.
1:55:23
And while I do think that overall, if you had an ETF of private AI startups, it would do well over time, um, that doesn't mean that any individual valuation is right simply because the letters AI are attached to it in some way.
1:55:36
From a fund model standpoint, um, I really believe that there's effectively only two types of funds that could work if you were to start now.
1:55:45
One would be a fund with billions of dollars of AUM simply because at that point, the management fees are sufficient that the GPs can make a living from that alone.
1:55:53
Um, as long as they can raise the next fund, you know, it doesn't really matter.
1:55:57
Or a sub-$100 million fund, or even sub-50 you can get away with it, where the hurdle is relatively low, you can get into carry pretty quickly.
1:56:07
You're not making much on the management fee, so that certainly you've either got to have other resources or really be super scrappy.
1:56:14
If you if you were if you wanted to start a fund with the the lowest chances of success, what would it be?
1:56:20
For me, it would be a $200 million Series A only fund. Sure.
1:56:24
Yeah, generalist generalist with nothing differentiating. Yeah.
1:56:30
Even that sub-100 million still only works if you have something truly differentiating, right?
1:56:37
So, for me, uh, because we're the fund that does the regulatory stuff, for better or worse, we're the people you call if that's the if if that's your issue.
1:56:45
And if you don't have a regulatory >> But then how do how do you What's your framework?
1:56:48
Because cuz, uh, there's times where I've invested in a company where I'm like, okay, this this founding team is fantastic.
1:56:57
And they don't understand, but they don't they're they're good at all this stuff, but they don't understand marketing.
1:57:01
I'm very good at marketing.
1:57:01
I can invest and I can help.
1:57:03
The problem is I'm I'm going to be in the room with them like less than 1% of the time, right?
1:57:10
Like I'll do a handful of calls, I'll make intros, I'll help however I can, but I'm not actually on the team.
1:57:16
And so I've ended up getting I've yeah, I've ended up getting burned because I'm just like I I can't, you know, 1% of my time is not enough to take them from bad at marketing to even good, right? Right.
1:57:28
So, for us, there's first thing is we ask two simple questions.
1:57:30
Is there a gating regulatory issue or opportunity that if it were solved, could really drive growth and valuation?
1:57:37
And then if so, can we solve it?
1:57:39
And that's what led us to that in companies like FanDuel, Lemonade, Bird, Ro, Coinbase, Circle, Latch, so on.
1:57:47
Um, and then the other part though is if you take Dr.
1:57:50
Chron as an example, we are their GRPR department.
1:57:54
Um, we effectively become the in-house group for a company until they get up to a point where it's like, "Okay, we are now big enough that we probably need an in-house team."
1:58:04
In which case, like Ro is a really good example where when we started working with Ro back at the seed, um, you know, it's funny with Dr.
1:58:12
Chron because it's prescription via AI.
1:58:13
When it was Ro, which was really not that long ago, the question was, is tech is prescription via tech legal? Um, nobody knew, right?
1:58:22
Cuz they had no until Z, no one had ever tried to do it before.
1:58:26
Um, and he saw something that was incredible, and our job was to legalize this everywhere, and we we worked on that and did it.
1:58:32
And then eventually they grew to a point where we helped them, you know, put together their kind of in-house people.
1:58:37
And then we still talk to them all the time.
1:58:39
We jump in on stuff, whether it's GLP-1 compounding rules, or whether they want to be a COVID test provider, or whatever it was.
1:58:48
Um, but for those early rounds, we really are part of the team, and that's why we take equity for our work, um, because, you know, we're lucky to be in a position where I don't need to take cash usually cuz I have the the resources to sort of fund it myself, but uh you know, we are there day-to-day.
1:59:06
Talk to me about mobile voting.
1:59:09
Uh we've heard about it for a long time.
1:59:11
Do you think it's ever going to happen?
1:59:12
What are you doing in this space? Why is it important? Okay, explain.
1:59:16
>> So, all right, let let's start.
1:59:16
It's important because in a world of gerrymandering, and I'll make the assumption that the the viewers know what that is.
1:59:22
Um the only election that matters is the primary.
1:59:25
So, the New York Times did a study of the 2024 general election, only 8% of congressional races were decided by five points or less, and only 7% of state legislative races were decided by five points or less, which means well over 90% of elections are really determined in the primary.
1:59:40
And the problem is primary turnout is incredibly low. It's usually about 10%. Wow.
1:59:44
And so, who are those 10%?
1:59:47
They're the extremes, the far left or the far right, or they're different special interests, whether it's the NEA or the NRA, either side, um that effectively dictate what happens.
1:59:59
And if you're a politician, and all you want to do is stay in office, then you cater to those groups at the exclusion of everyone else, but because those groups are purists, they don't want compromise.
2:00:08
They don't want consensus.
2:00:10
They just want to sort of hold true to their principles, no matter what the cost is, and so nothing gets done.
2:00:15
Um and the simplest way to solve that is to meaningfully increase primary turnout, but the only way to do that is to meet the voters where they are.
2:00:24
Every single one of us has a supercomputer in our pocket, um and if you can allow people to vote um in at least state and local elections on their phones, you can get primary turnout from 10 to say 40, and now all of a sudden, if in order to get reelected, you have to represent 40% of your constituents instead of 10, that 40% is much more moderate, and they want things to get done.
2:00:48
So, if that means working with the other side to find a reasonable compromise on immigration, or guns, or healthcare, or climate, or whatever it is, you can do so.
2:00:55
It's not that government doesn't know what the answers are, it's that embracing them imperils reelection, and they won't do that.
2:01:04
And so, um I started something called the Mobile Voting Project in 2017, and the first thing we did was test the hypothesis that I just laid out, and so we funded elections out of my foundation.
2:01:13
It's totally philanthropic.
2:01:15
In seven different states, where either people with disabilities or deployed military were able to vote in real elections on their phones, and the answer was, of course, as you guys know, when you make something a lot easier and you put it on people's phones, they do it. So, that was true.
2:01:30
Then the next question became, okay, but is the tech really good enough to do this at scale?
2:01:34
It was totally fine for 2,000 soldiers from West Virginia, 3,000 blind people in Oregon, but if we're trying to get every district from 10 to 40, and the tech that was on the market at the time wasn't good enough for that.
2:01:45
So, we spent five years building our own mobile voting technology that is end-to-end encrypted, end-to-end verified, has biometric screening, multi-factor authentication, air-gapped, and all of the code is open source, which means it's on GitHub right now.
2:02:00
So, it's totally transparent, totally auditable.
2:02:04
Um and the next part is then, okay, getting government to say, yes, you can actually do it.
2:02:08
So, that's about to happen for the first time in April.
2:02:12
Anchorage, Alaska is making mobile voting accessible to all of their uh voters. It's a gong.
2:02:17
Hit the gong for mobile voting. Overnight success. Thank you.
2:02:23
And um we are running legislation now in five states, uh Minnesota, Colorado, Vermont, New Jersey, Maryland, that would allow cities in those states to start offering mobile voting uh as an option for local elections.
2:02:39
Citizens, I can imagine, are super excited about this. Who's not excited?
2:02:45
Yeah, cuz you're just like, oh oh no, I love going to the poll I I I love I love taking, you know, an hour out of my day to to go to this thing that uh So, there's the people There are a few smaller opponents, and then there's in reality the big one.
2:03:00
So, the smaller ones are There are some cryptographers who have said, it's impossible, can never be done, something can go wrong.
2:03:09
And they're not wrong, something could go wrong, but things go wrong at in-person ballot places all the time.
2:03:14
Things go wrong with mail-in voting all the time, and the risk of inaction is where we are today, and this is not sustainable for 24 years.
2:03:23
Um And there are groups like this one called Verified Voting that are kind of the anti-vaxxers of voting.
2:03:27
So, they're just like, in paper on paper, in person, nothing else, you know?
2:03:32
And they're the crazies, just like the anti-vax people, in my view, are a little crazy.
2:03:36
Um but the real opponents, at the end of the day, are the status quo, because if you are an ideologue or special interest, and primary turnout is 10%, you have a lot of power, because you can Your threats go a long way.
2:03:50
Well, yeah, and you look at who's showing who's actually turning out for the primaries, and you can concentrate budget on influencing that subgroup, which is much better than having to appeal to an entire region, or or, you know, a huge age range.
2:04:04
So, uh So, that's what we're really going to have to fight through.
2:04:09
But, you know, if you think about every major right in this country that's ever been won, women's right to vote, Civil Rights Act, Voting Rights Act, same-sex marriage, Americans with Disabilities Act, whatever it is, status quo didn't want to do any of those things, right?
2:04:21
Enough people stood up loud enough and long enough and demanded their rights, and eventually they won, and it's not easy, and it takes a while, and it's expensive, but that's what we have to do here, too, and we're trying. Amazing.
2:04:35
Really quick, I I know we're mostly out of time.
2:04:37
Uh how do you think uh what do you think the dialogue will be around AI in the in the midterm elections? Uh Uh negative.
2:04:46
I think it's going to be pretty bad. Yeah. Yeah.
2:04:47
Um And it And is this the kind of thing that certain politicians are going to make their entire brand anti-AI?
2:04:57
Well, so I think what you're going to see, which is we can get Cal Shapiro, or someone to take take a set of light on this, is the word that will be cited the most in the midterms.
2:05:09
By the way, it's not just Congress, there's 36 governors, the state most states legislatures, um is affordability, right?
2:05:14
So, that's the word, right?
2:05:15
You heard Trump say it, you heard Mondami here in New York say it, everyone's going to say it.
2:05:19
So, then the question is, where does AI fit into the affordability puzzle?
2:05:22
And it fits in in a couple ways. One is job loss.
2:05:24
I do believe that some of the jobs that are that we saw in 2025 reflected layoffs, typically kind of bigger tech companies that are the earliest adopters of of AI new technology using it, realizing this works pretty well.
2:05:38
I don't necessarily need as many people to perform any given function.
2:05:41
So, you're going to have layoffs.
2:05:43
The second is energy prices.
2:05:45
So, right now, in the way that data centers that were conceived by the hyperscalers was, you know, we build these things, and we would consume a lot of energy, and that would be from the grid.
2:05:56
And the problem is, everyone else who's on that same grid then has to pay the price for that, and so there are a lot of states where AI data centers have already come online, where people are paying 30, 40, 50% more in their energy bills every month.
2:06:09
The problem is, no consumer on either side of the aisle is interested in having to spend more money out of their pocket to help make Sam Altman or Jensen Huang a trillionaire, right?
2:06:18
So, [clears throat] politicians are starting to push back.
2:06:21
But, people were like, I want Uber in my area, around where I live.
2:06:24
Nobody's like, if I don't get a data center in my backyard, I can't use ChatGPT.
2:06:28
ChatGPT is going to work no matter where the data center It's going to work.
2:06:31
And by the way, the data centers don't even create that many jobs, right?
2:06:34
So, there's not even like you can mobilize that for it, and you see now a bunch of different states on both sides of the aisle start proposing legislation that would find ways to curtail um the ability of the data centers to impose those costs and externalities on consumers, whether it's around the having to use different types of energy, or alternate forms of compute, or water, or whatever it might be.
2:06:57
And so, AI is going to get blamed, not wrongly in some ways, for both job loss and higher energy prices, um along with things like mental health, chatbots having weird problems with teenagers, and things like that.
2:07:09
And so, I think it's going to be a huge attack uh vessel for um challengers against incumbents, you know, in pretty much every election this year, and I think that, you know, when we in the tech world just think everyone loves AI because we love AI, that's not true, and if that is the mindset you take, you're going to lose. Yeah.
2:07:31
No, that makes total sense. Agreed.
2:07:33
Yeah, it's going to be a really important story to follow this year.
2:07:37
We'd love to have you back on the show to talk about it more.
2:07:39
>> anytime, love talking about this stuff, so anytime that works for you guys, just let me know.
2:07:42
Thank you so much for taking the time.
2:07:44
>> expect emails in the morning when stories are out. >> it. We got it. Come on. We got it.
2:07:47
All right, great having a real expert.
2:07:49
And thanks for pushing Jackson over the line.
2:07:52
No, yeah, it's it's great.
2:07:52
He's He's He's going to love it. It's going to be great. Yeah.
2:07:55
Have a great rest of your day. >> guys, thank you.
2:07:57
And Barnes & Noble's opening 60 stores, they're going to appeal Somebody sent us So, I like just don't don't limit yourself, right?
2:08:06
If, you know, make it up with scale, right? Open 50 more stores.
2:08:11
Make You'll make it up with volume. >> Yeah, for sure. Yeah, there we go. There we go.
2:08:14
I just have to, you know, just make it I I need another Uber to be able to afford that.
2:08:18
So, >> [laughter] >> I'll work on it. So, Thank you so much.
2:08:21
Thank you so much for having me. I appreciate it. Cheers. Take care. Bye. Shopify.
2:08:24
Shopify is the commerce platform that grows with your business and lets you sell inside things online, in store, on mobile, on social, on marketplaces, and now with AI agents.
2:08:35
And we have a very special segment on TBPN today.
2:08:37
We have Lucas Zinger from Divergent uh in the UltraDome.
2:08:39
He's actually outside the UltraDome.
2:08:42
So, we're going to take a walk, and we're going to We're going to We're going to do a walk and talk for I think this is the first time we've ever done this.
2:08:51
So, I should be able to click over to the live.
2:08:53
Mike, do you have the live mic material?
2:08:58
Let's go see what's waiting for us outside of the ultra dub station.
2:09:01
I think we have audio from outside already.
2:09:04
I think we have audio outside. Let's go and see. Okay, we are ready.
2:09:08
Wow, >> [laughter] >> look at this.
2:09:12
Thank you so much for coming. Look at this.
2:09:15
Walk us through what we're looking at.
2:09:16
And reintroduce yourself for those who might not remember. >> I'm Kevin Zinger.
2:09:20
I'm the CEO of Divergent and Zinger Vehicles and you're looking at our first car, the 21C.
2:09:26
>> Wow, you had to bring it you had to bring it in green, too. Yes, it's amazing.
2:09:30
It matches the outfit here for you. >> remarkable.
2:09:33
I've watched the full video.
2:09:35
I watched Doug DeMuro's review. Okay.
2:09:37
>> And seeing it in person, the scale is remarkable. It is a wonder.
2:09:40
It's a spacecraft for the road. It's a land jet.
2:09:42
It's a hell of a car to take in traffic from Torrance to here.
2:09:46
Wait, did you drive this on the street here? >> Yes.
2:09:49
I was assuming you were going to trailer >> No, no, we drove it.
2:09:51
We drove it an hour in traffic on the way over, so.
2:09:56
>> believe you drove it here. >> Okay, full carbon. Full carbon body.
2:09:57
Uh before we go into the details, tell us the story of your journey with cars.
2:10:01
Why did you want to build this car?
2:10:05
[clears throat] When did this project start?
2:10:06
This doesn't look like it was built in one day, but No, this is This is This is a 10-year building company from a vision moment.
2:10:15
So, we started as a family business.
2:10:17
My father had the vision for Divergent.
2:10:19
I joined them soon thereafter.
2:10:21
And we have a business that has changed the way that we engineer and manufacture fundamentally.
2:10:27
So, when we talked last time, we talked about the defense application, the manufacturing application.
2:10:33
That company is scaling right now.
2:10:35
But Zinger was the first product within Divergent.
2:10:37
So, when we said, "We've got new design software, new added manufacturing technology, new robotics, how are we going to prove this, validate this?"
2:10:48
We turned to making our own car.
2:10:48
Then that evolved into making our own car company.
2:10:54
So, Zinger Vehicle is about 5 years old within 10 years of what is the Divergent journey.
2:10:59
And now it's the world's fastest hypercar. It's American-made.
2:11:03
It's got five plus international track records. And it's road legal.
2:11:09
And most excitingly, there's over 16 of these in the wild now.
2:11:11
So, they've been delivered Los Angeles, Miami, London, all the usual suspects. This is remarkable.
2:11:20
Um and this car it represents fully that 10-year journey.
2:11:25
Yeah, I mean Jordan was just making the joke with me today that you could build the ultimate American-made hypercar garage for remarkably cheap.
2:11:36
Wait, compared to an Italian hypercar collection or even a British, you know, hypercar.
2:11:42
You've just raised the stakes significantly with this, I think.
2:11:46
This is This is remarkable.
2:11:46
So, so what has the testing been like? You said five records.
2:11:51
Who's driving these cars? What tracks?
2:11:53
What are the records that you're going for?
2:11:55
What what has stood out in the journey?
2:11:57
So, Joel Miller has been our test pilot.
2:12:00
And he's an exceptional driver, factory driver for Ferrari, great coach.
2:12:03
And we nailed five track records in five days, which has never been done before.
2:12:08
We made a documentary of it.
2:12:10
And it was all about the street usability of the car and the performance envelope it has.
2:12:15
So, instead of showing up to You took five in five days.
2:12:19
What does that actually look like?
2:12:20
You're getting a record, immediately packing it in a trailer, driving to the next track?
2:12:24
Driving Driving it to the next track.
2:12:26
So, that was the epic journey.
2:12:27
And we made a documentary, called it California Gold Rush.
2:12:29
And we drove from NorCal through SoCal.
2:12:31
And we had we track on the way.
2:12:34
And every day we'd set the track record.
2:12:36
Every night we'd get in the car and we drive a couple hundred miles to the next track, get in late, get some sleep, get up early next morning and do another record.
2:12:45
So, it was as much of a human feat as a vehicle feat.
2:12:47
But what it was meant to show was these hypercars can be driven on the road. This one can.
2:12:50
It was built as a road car, not only a track car.
2:12:55
And it's got so much performance that quite literally you can show up at the track on used tires and set a track record and not need a pro team next to you supporting you. It's amazing.
2:13:06
Talk about the decisions in usability.
2:13:06
I see three pedals in there.
2:13:12
Between, you know, the Carrera GT or Supercar, no supports, extremely dangerous to some of the more point shoot.
2:13:19
Where did you want to land? Where did this car land?
2:13:23
>> So, ultimately this was about creating a road car that was otherworldly in the way that it drove on the street, but could beat the best on the track.
2:13:30
And that's a hell of a design brief cuz usually those two worlds don't marry well together.
2:13:36
We also wanted to create a vehicle that was engaging.
2:13:38
That's part of that otherworldly experience, right?
2:13:42
You wanted something that wasn't numb at low speed, that was very, very lively on the road, but ultimately could shave 10 seconds off the Thermal track record when you go 10 out of 10, right? Thermal, yeah.
2:13:55
10 seconds off the track record at Thermal.
2:13:57
Do you know who who had the previous record? I won't say.
2:14:01
That's too [laughter] big of a margin to to say.
2:14:03
But we we've had an epic back and forth.
2:14:06
You know, because I've I've been in a Valkyrie at Thermal with our friend >> with our friend, yeah.
2:14:11
who I won't I won't name them cuz he's a private person, but but this car but I was in in the Valkyrie at Thermal almost every single corner I thought that I was going to die.
2:14:23
So, 10 seconds faster than that.
2:14:23
10 seconds faster than that is insane.
2:14:26
Yeah, you're pulling major Gs, the cornering, the acceleration.
2:14:28
But back to your question, this car marries those two worlds, track driving with road driving. It's a one design brief.
2:14:34
You got the center seating.
2:14:36
That's of course intentional.
2:14:38
That's based on the aero package that allows for less frontal surface area.
2:14:42
It also gets you centered in the car, which is the best track driving position you can have, right?
2:14:48
Your left feel the same as your right.
2:14:49
>> I've always wondered why more manufacturers don't go with a center seating.
2:14:52
I mean, it's iconic from the McLaren F1.
2:14:53
Uh and then maybe it's just a practicality thing.
2:14:57
Yeah, the back seat, right?
2:14:59
It looks a little tight in there.
2:15:01
Your feet go outside of the front seat.
2:15:03
So, you actually have much more room than you think.
2:15:04
You don't need to get your knees up behind that front seat.
2:15:07
And when you're in there, your package pilot, co-pilot.
2:15:09
That's a really cool car.
2:15:11
It's a really dynamic driving experience.
2:15:13
I mean, our customers that drive with their partners, they actually love the layout.
2:15:16
And in terms of hybrid strong hybrid Okay.
2:15:21
ground-up developed in the US as well.
2:15:23
So, we've got a V8 that we took all the way through California CARB to road homologate.
2:15:27
It's about 750 horsepower twin turbo 2. 88 L.
2:15:33
We have another spec that takes it up to 850.
2:15:35
And then you get another 500 horsepower out of the front wheels.
2:15:37
So, you're doing 1250 to 1350 total horsepower, all-wheel drive, 7-speed AMT automatic manual transmission.
2:15:45
But you have that EV feel on the front axle.
2:15:50
You've got the middle EV motor, the MGU.
2:15:52
So, you have a really, really seamless gear shifting experience.
2:15:54
Feels much more like a DCT than a single clutch, but you get the weight of a single clutch package.
2:16:00
How early did the door design come together?
2:16:03
It's It's pretty striking.
2:16:05
I mean, people have done scissor doors, butterfly doors, all these things, but there's something about how long these doors are that really stands out.
2:16:13
>> Yeah, it had the record for the world's longest door for some time.
2:16:16
And that's because of course you're opening the front and the rear at the same time.
2:16:20
And you've got this 45° angle that looks like wings coming up.
2:16:25
It's part of the design brief, part of the functionality brief.
2:16:28
We didn't want to split the passenger side into a separate door from a styling perspective.
2:16:33
And then Can I Can I get in the cockpit for a second?
2:16:36
>> Yeah, yeah, let me show you how to do that real quick.
2:16:38
And maybe spin around this side. Let's do it. It's a two-stepper.
2:16:44
So, you're going to take a seat right here. This is the battery box.
2:16:45
And then swing your legs in.
2:16:48
>> don't want me to put my my feet right on that exposed carbon. Okay. Yeah, swing your feet. You got it. Nice. Here we go.
2:17:01
Yeah, when you're in there, cuz you got the center seat, you actually have a lot of room.
2:17:04
I mean, compared to the Valkyrie where you're pretty squished and you're also at an angle, this actually has a lot of headroom.
2:17:11
>> you have a helmet on in the Valkyrie, you you hardly have any Yeah.
2:17:13
You're probably touching a tiny bit.
2:17:15
And that seat's almost all the way forward.
2:17:17
You got seat controls on your left.
2:17:20
What is the name of the 21C?
2:17:22
So, stands for 21st century. Okay.
2:17:25
So, Divergent's mission statement is build the 21st century industrial base.
2:17:29
So, this car represents the 21st century in the vehicle space.
2:17:34
Can I pull this down for personal see?
2:17:37
>> [laughter] >> How important are the materials?
2:17:38
I mean, I imagine >> Put your foot on the brake.
2:17:41
I see >> have a key in here? Oh, there we go. Oh, baby.
2:17:47
I'll see you guys I'll see you guys later.
2:17:49
See you [laughter] later. Wow.
2:17:54
Okay, so you get a feel for it.
2:17:56
You've got your different modes.
2:17:56
You've got an EV only mode. You've got a track mode. You've got a sport mode.
2:18:02
And you're pulling gears on the steering wheel there.
2:18:04
You've got all your controls on the wheel, centralized. Cool features.
2:18:08
You got some 3D printed AC vents even.
2:18:10
You've got your 3D printed uh speaker grills.
2:18:15
You've got the wheel, the center node.
2:18:18
And it's a full carbon body, but the full chassis that is printed underneath. Lock him in? Yeah, lock him in there. Here you go. Wow.
2:18:29
Wow, it's such a different It's such a different experience actually feeling like you're in a cockpit here. Insane. In the green. Yeah.
2:18:40
Man, the the urge to just throw it in reverse.
2:18:42
Yeah, we should go for a drive.
2:18:45
This is America's hypercar. Insane. Yeah.
2:18:50
How important are the materials?
2:18:50
I imagine this door, if you made it out of steel, it'd be incredibly heavy. You couldn't lift it.
2:18:57
What What are you using as building materials and how important is that?
2:19:01
>> So, the entire chassis architecture is what really differentiates the car, as well.
2:19:05
So, when you look at it from an optimized system, we didn't just optimize rear frame and front frame.
2:19:09
We actually built a full vehicle model with our topology software. >> Okay.
2:19:14
And what we're building on the chassis is additively manufactured aluminums, which are actually their own chemistry.
2:19:20
So, they have the right strength and durability, but also for auto elongation to absorb energy.
2:19:24
So, if you get in a rear impact, you need to have a material that doesn't shear or break.
2:19:32
>> Okay, that makes sense.
2:19:32
And that's really, really hard to get in an additive material.
2:19:34
We had actually make that aluminum in house. Yeah.
2:19:37
The body then is fully carbon fiber.
2:19:39
So, you're marrying essentially 3D printed aluminums and inconels with a carbon fiber exterior for aero.
2:19:45
You're taking all of your load cases, your main large forces through that additively manufactured chassis, and then all your aero load through the carbon body.
2:19:53
And then what is what pieces of the car?
2:19:57
I mean, Michelin tires, you don't make the tires.
2:19:59
What are What else is in the supply chain where you're buying instead of building?
2:20:04
Yeah, we have great partners in the supply chain, right?
2:20:06
We can't build every piece of this.
2:20:07
So, you named it, tires, infotainment system, right?
2:20:10
We've got Apple CarPlay on there. That's the standard.
2:20:15
Uh we have a partnership on our transmission where we actually did part of the design.
2:20:20
We additively manufacture the housing, but then someone else cuts the gears for us and integrates it.
2:20:24
Um on the engine side, we designed that V8 ground up and we actually build that V8, as well. Yeah, yeah.
2:20:32
Let's go look at it right now.
2:20:33
On the battery side, we've got a partnership there.
2:20:34
So, almost every system on this car is bespoke, either fully engineered and manufactured by Zinger and Divergent, or done in a JV where we have a partner where we've taken a design brief to them, said this has never been done before, will you sign up to do it with us?
2:20:49
And then this sort of structure, this sort of structure, it looks very organic.
2:20:53
Where did that come from? Whose idea was that? Is that someone in CAD? Is there AI involved? What What's going on? >> the computer's idea. >> Okay, interesting.
2:21:02
>> That's not the designer's idea.
2:21:02
So, when we talk about Divergent process, design, print, assemble, the design portion is a fully integrated set of microservices that takes requirements and turns it into optimal CAD.
2:21:14
>> Okay, so you're you're setting parameters.
2:21:15
You want the lightest weight for the most strength with this performance and this volume, cuz it can't be bigger, [clears throat] Yes.
2:21:22
and then it will go and try all sorts of things, and then you can finally do use additive manufacturing to manufacture the part. >> You got it.
2:21:29
So, 10 years ago, we started in machine learning, the basis of modern AI, right?
2:21:33
And AI-based algorithms and prediction to do a weighted optimization function for designing these parts.
2:21:40
Importantly, we simulate the full manufacturing side, as well.
2:21:42
So, once we've designed, say this rear cross brace, and that wing is going to interface directly on that part.
2:21:48
So, that entire rear cross brace is going to take the aero load of 5,000 plus pounds onto it. So, you're Yes.
2:21:57
So, you're going to give it that force vector, that downforce.
2:22:02
loads and then that diffuses across the whole >> Exactly.
2:22:04
So, then you also give the software the crash impulse case, the durability case, the load cases coming off the the road, the vehicle, the tires, all into that functional system.
2:22:15
The software actually then says add and subtract material against those requirements until we hit a Pareto optimal point. Makes sense.
2:22:21
That means it's the lightest weight while meeting those requirements.
2:22:24
And then the beauty is it's already simulated for manufacturing.
2:22:28
So, there's no design for manufacturing loop.
2:22:29
We go through our MES, homegrown, and actually make that part and then assemble it with our robotic cell.
2:22:36
So, this is chassis 28 of 80.
2:22:39
You said there's 16 that are out in the wild already.
2:22:41
So, you have 12 or something that are maybe ready to go. Is that right?
2:22:45
>> Yes, so there's cars in between.
2:22:45
This one's also a special number for us.
2:22:49
Sometimes people request the the exact number on a vehicle, but we're typically around 20 cars a year.
2:22:54
These are the records that this car has set specifically?
2:22:58
Yes, so this is Laguna Seca and Circuit of the Americas, which are two of the main American iconic tracks, right?
2:23:04
This is probably our best track in California.
2:23:05
The beauty about this one is it's outdated.
2:23:08
So, we just had an epic back and forth with Koenigsegg, the Swedish hypercar maker, and we set a 1:22. 3.
2:23:18
So, we beat our previous record by over 2 seconds, beat their record by almost 2 seconds, and put a whole new benchmark for Laguna.
2:23:24
Then Circuit of the Americas rivalry with Christian von Koenigsegg, but just settle it on the track. It's just beautiful. I don't know.
2:23:31
It's industrialist for hundreds of years in America have been building the fastest train, the fastest plane, now the fastest car.
2:23:36
Is there any Is there any ambition to one day make cars for everyday consumers, or is it racing and hypercars?
2:23:45
Zinger will stay at the tip of the spear.
2:23:48
It's all about big R&D budgets, making a car that is a next step forward in terms of consumer experience, and therefore it's got to be expensive. It just has to be.
2:23:57
It's like it's the most modern high performance niche that does develop systems that then do make their way into more mainstream vehicles, but Divergent is the company that's going to do, you know, the Ford F-150 one day on the chassis technology side. With partners. Exactly. Exactly.
2:24:15
So, that tier one supply, the volume game of doing millions of vehicles, that'll come through Divergent.
2:24:20
The tip of the spear, highest performing vehicles in the world, that'll come through Zinger. That's amazing. Very cool.
2:24:30
Anything else we should know about the car?
2:24:31
Should we go sit down inside, talk about business and how things are going?
2:24:35
>> let's talk about business a bit.
2:24:35
This is >> that's the step for you all is to This view right here, Michael, you got to get this view, this shot from this angle is just absolutely insane. What a beast. Stunning.
2:24:54
Yeah, that's real functional aero. Yeah.
2:24:56
The scale of the car is just is is twice It's everything. It's wide, long, tall.
2:25:02
That front splitter Yeah, you can put a lot of weight on that. Yeah, yeah. Quick shot here. There we go. >> Woah.
2:25:16
It's actually functional. It's got to. Insane. Okay, let's go sit down.
2:25:21
We'll chat and dig in more.
2:25:26
We are back in the ultra dome.
2:25:31
We'll have you sit right here. And uh We're back. It's fascinating.
2:25:36
We're back. It's fascinating. I mean, I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I
2:25:43
I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I [laughter] I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I It's fully road legal. Yeah, what it How
2:25:49
Yeah, what it How How difficult is that process? Oh, it's difficult.
2:25:55
Cuz we went through This is not an EV car.
2:25:57
It's a strong hybrid, so it has an EV system, but a combustion engine, as well.
2:26:01
And we went through full California CARB emissions compliance on that V8.
2:26:04
Just heard it start up, right?
2:26:06
And that is a difficult process.
2:26:09
Cuz they're looking at while the car is running, when the car first starts, what the evaporation is of fuel or oil in a what they call shed test, as well.
2:26:18
So, there's a huge amount of requirements to actually certify that car.
2:26:22
I think the amount of fuel you actually burn in the certification process might not actually make it logical for cars that are this low volume.
2:26:29
But you go through that and you show that this car is actually designed to be environmentally friendly with that V8.
2:26:36
What would you do if you're making a track-only version?
2:26:38
We would strip out a lot of weight and a lot of the safety monitoring software and systems.
2:26:45
So, first off, you're talking about all your airbags go, all your passive safety environment goes, a lot of electronics that are there for redundancy.
2:26:55
>> any that have like a full roll cage in them, or or was the intention just like, "Hey, we want to set records with Yeah, so road car, right?
2:27:03
Maybe in the future we'd make a track-only car.
2:27:05
It would be different almost entirely.
2:27:08
That roof design, the carbon A-pillars that run all the way across, that is rated for a rollover.
2:27:16
So, you can roll that vehicle and have similar performance to a rollover cage, but integrated there.
2:27:20
You don't want a roll cage in a road vehicle because it's a very hard surface in the car, and if you're not harnessed in, you're going to move more, and you're going to hit your head against it if you get in a crash.
2:27:32
The roll cage on the track, where you have the harness on and the helmet, makes sense, but the roll cage without the harness and no helmet, it actually is is a major hazard on the road.
2:27:39
Yeah, talk more about the the safety approval, getting the car road legal.
2:27:44
Is Is there a hurry up and wait element while you're in the queue, there are other cars, and there's a rate-limiting factor there, or is it more of a quick back and forth, but you're making dozens of changes constantly?
2:27:59
What's the actual process like?
2:28:01
So, it is an iterative process.
2:28:01
It is known to be a real headache for certain OEMs in terms of the timing and attention that they get and how quickly they can iterate.
2:28:09
And I'm sure if you're like Ford and you're like, "There's a new Corolla coming or that's Toyota, but >> [laughter] >> there's a new, you know, there's a new F-150 coming every year with a refresh and we're changing this."
2:28:19
They They have a whole system set up.
2:28:20
It's It's not It's not as bespoke.
2:28:22
So, they must have a whole team for it.
2:28:25
You sort of have to build that.
2:28:28
>> CARB's credit, I think they saw that this was one of the first new OEMs in America, period.
2:28:33
And there was a narrative that they wanted to support there, as well.
2:28:37
And we managed to get their attention, and our team was able to work with them effectively.
2:28:41
So, I don't know how much you're using this as a part of the sales process when you're pitching uh let's say other OEMs to to make parts with you guys.
2:28:51
Are you saying like, "Hey, if you don't believe me, get in the let's like go for Early on it was like the proof is in the pudding moment, right?
2:28:58
You come to our factory, you see our car, you can drive it.
2:29:00
If you're Bugatti or McLaren or Aston Martin, you see that and that's a huge benefit, right?
2:29:06
So, we used that a lot early on in the company as a sales tool.
2:29:08
Now, in defense, you know, we're hosting anyone from Secretary Hegseth um to a CEO of a prime.
2:29:16
When they see a company that can integrate a road legal vehicle and they see that manufacturing process, it just builds a lot of confidence, right?
2:29:24
There's a cool narrative.
2:29:24
Hegseth loved revving that in CAR but there's also a capability narrative and that systems engineering is proven out through that car. Yeah. Yeah.
2:29:32
How how I mean, I was looking at the your your careers website, you're hiring tons of people.
2:29:39
Uh how scaled is the is the manufacturing plant? How large is the team?
2:29:43
How large is the business?
2:29:43
How are you growing these years?
2:29:45
So, we've gone in the last 3 years from not being a defense focused business and Divergent to being a defense focused business.
2:29:53
We're dual use, dual tech.
2:29:53
So, we do have our commercial arm.
2:29:55
The auto business is growing.
2:29:57
Our supply to really the European luxury brands is growing but the focus is on defense right now.
2:30:02
3 years ago, we had zero contracts.
2:30:05
Today, we're on over 40 active contracts.
2:30:07
And that's what's really unique about Divergent is we're not competing head-to-head with Anduril and Lockheed and Raytheon.
2:30:13
Rather, we're servicing all of the primes.
2:30:15
So, you can build this horizontal manufacturing layer as a service to all of them.
2:30:19
You can bet not on one to five programs of record but rather service 100 programs of record over time and be that manufacturing supplier for them.
2:30:29
We've gone through that journey of first refactoring the company to work on defense, winning our first contracts, delivering our first prototypes, flying those, proving the performance of a new technology, and then actually in the last 6 months winning our first scale production programs.
2:30:47
Now, if you come to the facility, you'll see exit rates at around 100 a month of main bodies for large cruise missile systems.
2:30:55
So, 80 a month or 100 a month, it's not high volume for auto but for our defense landscape, making 1,000 missiles per year, that's on the high volume side of things.
2:31:05
That's what Divergent's factory in Torrance is already churning out.
2:31:09
>> Now, we've almost gotten to full capacity on our Torrance facility with those contracts.
2:31:13
We're we're starting to look at factory two, three, four, five.
2:31:18
We got multiple states that were, you know, kind of shopping and partnering with right now and then also looking at California cuz it makes sense for especially the startup community here, which are great partners for us to have another manufacturing platform here. Yeah.
2:31:32
What about uh other applications outside of defense and automotive? Maritime comes to mind.
2:31:38
I can imagine a lot of that additive manufacturing technology being useful on high-speed boats, yachts, I don't know.
2:31:45
Uh aviation planes we were talking about Harrison Ford crashing Cessnas all day long.
2:31:52
Maybe he needs some more reliable uh manufacturing.
2:31:54
Uh but what what other areas have you uh at least thought about expansion into?
2:32:01
Yeah, the TAM for this system is so large and that's a blessing but you need to be disciplined in what you address first and second and third.
2:32:11
Right now, it's a primary focus on defense.
2:32:13
Within that, looking largely munition systems and then looking at torpedoes and similar structures but on the the navy application side.
2:32:21
Outside of defense, we look to space.
2:32:24
So, we're doing quite a bit of work in space.
2:32:28
Optimization, mass saving there really matters.
2:32:31
So, you think about things like satellite buses.
2:32:32
As we get more and more launch vehicles and they're carrying different payloads into space, what is the structure that essentially attaches those to to the launch vehicle?
2:32:40
We've got several programs ongoing there.
2:32:42
And then you look at at Divergent over 10 years.
2:32:46
Really any metal structure that takes a complex load path, so has some sort of force that's interacting with, should be designed by the platform and manufactured by it.
2:32:55
So, you think commercial air, you think oil and gas, you think mining vehicles.
2:33:02
Um you even think over time as the prices come down enough, construction and where can it get into almost the city planning side of of the equation as well. Yeah.
2:33:10
Yeah, that makes a lot of sense. Wow.
2:33:11
Um what what is what are you saying on the hypersonic side?
2:33:14
I know a lot of it's under wraps but uh we've talked to Castilian and some other folks that are thinking about this and just broadly, the defense industry has been talking about the hypersonic gap uh over the the cruise missile.
2:33:29
Um are are you excited about that?
2:33:29
Are you following that story at all? >> Oh, absolutely.
2:33:32
You know, we're working on multiple hypersonic programs right now, designing primary structure for these vehicles.
2:33:38
You know, in terms of narrative or or when I zoom out a notch, you need both.
2:33:43
You need the affordable cruise missile that's $200,000 instead of 3 million.
2:33:47
You also need the hypersonics capability across different classes of hypersonics.
2:33:50
And for us, what do we need to be good at at Divergent?
2:33:56
We need to be great with our material science.
2:33:57
So, we need the right nickel-based alloys that can get very hot and still perform.
2:34:00
So, that's different than the aluminums that you saw mostly on the car.
2:34:04
We've designed several of those materials.
2:34:06
We have commercially available ones.
2:34:08
We've got ones that the government has actually contracted us to do a special materials development for a higher performing version of what's commercially available today.
2:34:17
And then we need to be able to print these at scale.
2:34:19
Company like Castilian is really not only about hypersonics but hypersonics at scale, right?
2:34:25
They want to make a lot of these.
2:34:27
They're down the road from us.
2:34:27
We want to help them make a lot of them.
2:34:30
>> [clears throat] >> Uh talk about what's unique about additive manufacturing in aluminum, nickel.
2:34:36
I think, you know, most people will be familiar with like 3D printed plastics but uh is it is it similar to just soldering lines of solder and just building up slowly?
2:34:47
Like what It's It's the most advanced way to make a metal part and it's the most [clears throat] controllable way as well.
2:34:52
It's not really related to um in terms of technology, 3D printing of plastics, right?
2:34:58
Maybe the narratives are tied a bit together but in terms of technology, molten push through a nozzle like a We do something called um powder bed fusion.
2:35:06
So, we have a powdered aluminum or Inconel in a build chamber.
2:35:09
That build chamber has no oxygen in it.
2:35:11
It's got nitrogen instead, so it's non-reactive in there.
2:35:14
And then you've got high-power lasers overhead.
2:35:16
And those high-power lasers essentially melt, laser weld one layer of that part at a time. Sure.
2:35:23
You put a new layer of powder on top and you laser melt that layer to the layer below.
2:35:27
So, if you think about a part, think about it standing vertical, think about it as a layer cake, maybe 5,000 layers, and you're laser welding with those lasers every single layer, layer by layer, and you're getting full data at every single layer.
2:35:42
So, maybe that one section of a defense product is 7,000 layers.
2:35:44
I get 7,000 layers of information on that build, right?
2:35:51
So, this is the most controllable process in terms of in-process monitoring.
2:35:56
It's the most advanced way to make a metal part and you also end up being able to make exactly the net shape you want.
2:36:02
Cuz when you have a cross-section, you can do the exterior and the interior and you have full control of that geometry.
2:36:07
You vacuum away your unused powder, you end up with your net shape.
2:36:12
So, in terms of waste and efficiency of the process, you can get something that runs at a higher OEE when we talk about manufacturing efficiency.
2:36:19
And you can get something that actually performs better.
2:36:21
So, when we talk, you know, application focus, if you're a missile system, we typically are seeing about 30% lighter structures while hitting the requirements.
2:36:31
And more importantly, we're able to functionally integrate that structure with the fuel tank, with the avionics mounting, with that whole complex system, we're usually increasing fuel volume by about 30 to 40%.
2:36:42
So, if you're a missile and you get 30, 40% more fuel volume, that's a real game-changer and that's what the customer looks at Divergent to do is one, get the best engineered product and that's going to change in a positive way the performance of your vehicle.
2:36:57
And then two, scale the manufacturing.
2:37:00
And that second part is where in the modern age of defense, where we are looking for volume, is where there's a big gap right now.
2:37:09
And that is part of the reason why Divergent has gotten one, so much business but two, so much attention as well is it's starting to be viewed as a manufacturing layer, right?
2:37:16
Our mission statement 10 years ago, "Build the 21st century industrial base."
2:37:22
is actually starting to happen now. >> That's amazing. Uh last question for me.
2:37:26
The the pieces that seemed uh clearly made in your factory with additive manufacturing, uh they looked white.
2:37:35
They didn't look like metal. Have they been coated?
2:37:36
What's the post-processing once you make a product? >> Yeah.
2:37:39
So, our as-printed aluminum comes out almost like a silvery white color.
2:37:44
So, what you're seeing is probably some of that but we do do coatings.
2:37:48
Especially on the defense side, we have a fully automated anodize line. Okay.
2:37:52
>> So, it's essentially a process where you clean the part, dip the part, and then one of those um stations, one of those tanks is actually electronically charged.
2:37:59
So, when you're anodizing, you're essentially plating that part with a certain coating.
2:38:05
That makes it more corrosive or more resistant to corrosion.
2:38:10
Um for navy applications.
2:38:10
But also, depending on the system, once it's fully integrated, if it's a stealth system, there might be a special paint that goes over top.
2:38:19
There might be a gap and flush process over it.
2:38:21
And Divergent will either do that or partner with the prime to do it.
2:38:25
>> At least prep the material so that it can go get the special paint that might be classified or something. Exactly.
2:38:29
Uh you're handing out Last question from my side.
2:38:32
Want to understand the how uh local kind of politicians and how like what what's your relationship like?
2:38:39
How does Torrance think about uh kind of neo primes and and overall building up the manufacturing base in Torrance?
2:38:45
Yeah, we've had a strong relationship with the city, which is part of the reason we've been able to get fast permits for our factory.
2:38:53
You can think about something like automated anodize.
2:38:55
That's usually something that can take some years to stand up.
2:38:59
We've been able to build relationships that allowed that to accelerate.
2:39:02
Um are there states that are lower cost and probably even faster for permitting a manufacturing? Absolutely.
2:39:10
Um in terms of engineering headquarters, Los Angeles or the greater, you know, Southern California area is very special because we have the environment to create hardware and test hardware.
2:39:21
And we've got some of the brightest people in the world all centralized.
2:39:24
And now we have a VC community and general, I'd say, growth um funding community that is focused in this area as well.
2:39:32
So, Divergent will stay headquartered here.
2:39:36
We will go through some serious scale production here as well.
2:39:39
But over time, you're going to see factories across all the states in the US.
2:39:43
And some of those factories will be at a lower cost basis uh than the ones here. Yeah. Very cool. It's so awesome. I love it.
2:39:49
I just everything about this company is so fun.
2:39:53
Uh congratulations on all the progress.
2:39:55
And seriously, thank you for bringing the car. What a treat. What a special moment.
2:39:58
We've been wanting to do a TBPN track day.
2:40:00
You'll be one of the first to know when the date is set. We got to bring it out.
2:40:05
Yeah, you can come out and smoke us all.
2:40:07
>> [laughter] >> Absolutely, dude. laps laps around us.
2:40:10
Uh but thank you so much for taking the time Yeah. to come on the show.
2:40:12
This was an absolute pleasure.
2:40:16
Uh yeah, I'm I'm I'm sure we'll be talking much more over this year as you roll out everything. Good to see you both. So great.
2:40:20
We will talk to you soon. Yeah, good to see you.
2:40:22
Have a good rest of your day. Enjoy the drive.
2:40:25
>> And I will tell you about Graphite, code review for the age of AI.
2:40:28
Graphite helps teams on GitHub ship higher quality software faster.
2:40:35
And uh we have our Lambda lightning round starting in just a few minutes.
2:40:37
We have Andy McCune from Cosmos coming on first, then FabFitFun.
2:40:42
The co- the co-founder and CEO of that company has launched a venture fund. He's coming on.
2:40:48
And Aaron Katz, the co-founder and CEO of ClickHouse is coming on.
2:40:49
Um and it sounds like we have Andy in the Restream waiting room.
2:40:55
So, let's kick off our Lambda lightning round and let him in to the TBPN ultra lounge. What's going on? How are you doing? What's up, guys? How are you? Good to see you. Welcome to the show.
2:41:06
Uh first time on the show, so please >> too. Yes, we love the green.
2:41:08
The green is what matches the car.
2:41:10
I have a Cosmo racing jacket and on our way here, guys. It's amazing.
2:41:14
We just had a green hypercar. Yeah.
2:41:15
We're doing a quick tour of Uh anyway, first time on the show, please kick us off with an introduction of yourself and the company. Yeah, for sure. Um I'm I'm Andy McCune.
2:41:25
Uh we're based here in New York.
2:41:25
Uh 20-person team um building building a new home for inspiration on the internet. Um visual search engine.
2:41:34
Uh just announced our series A today, super exciting. Uh $15 round. Did it. Amazing. Okay.
2:41:48
Yeah, there's so so much to talk about right now.
2:41:50
And it's such an interesting time to be building this company because there's so there's just like an explosion of content.
2:41:56
You don't need to get a pretty picture now.
2:41:58
You don't need a you don't need a camera.
2:41:59
Anybody can generate one from their own home.
2:42:04
Uh why don't maybe we start and you can give us kind of the history of the company, what the initial Maybe even go back further pre- about the previous company you worked on. Yeah, for sure.
2:42:14
Um yeah, in 2017, I I founded a company called Unfold.
2:42:17
Um so, we were like a mobile content creation tool, kind of Canva-adjacent.
2:42:23
Um ended up selling that company to Squarespace, did a few years there uh leading creator product strategy, and I've been working on Cosmos for the last 4 years or so now.
2:42:30
Um and yeah, I'm I'm a really creative person, always work working on a lot of different creative projects, and I very much grew up on Tumblr back in the day, and ever since then I've been an obsessive collector and curator of things on the internet.
2:42:45
Um I was just saving things to a million folders on my desktop and folders on my phone, things just in all of my different bookmarking folders on different platforms.
2:42:53
And um so, Cosmos just started out as me wanting to build a place where I could bring all of these references into one home um where everything would be tagged by AI so I could quickly search and re-surface anything that I'd saved.
2:43:04
I wanted to be able to work with collaborators in these different projects. Um so, yeah.
2:43:08
I mean, just started out as as building a side project for myself as everything I ever built has kind of started out as.
2:43:17
Um started getting into the hands of my most creative friends, and people are like, this is awesome.
2:43:20
Um And so, were those friends the ones that were uploading the original content?
2:43:24
Were you scraping the internet to bring on the first and like seed the community?
2:43:28
Like where was the actual content coming from?
2:43:32
Yeah, we we weren't scraping anything.
2:43:35
Um it's always come from the users.
2:43:35
Um we have great importing tools, and people can upload links from a lot of different platforms and around the play around the internet. Um so, yeah.
2:43:43
All of the content is is seeded by the community um which has grown in a really really beautiful way.
2:43:48
We've tons of millions of images on platform now, um an amazing global search, you know, all of the recommendation layer that you would expect from a product like this.
2:43:54
And what were the early adopters looking for?
2:43:58
Is it more like cuz I I you know, when I think about image search, I think about people that are doing home renovations, but also designers that are looking for inspiration for clothing or web design.
2:44:08
There's some people that just uh sit there and scroll just to enjoy their favorite images like you enjoy your favorite books.
2:44:15
Um what were the early drivers of growth?
2:44:20
Yeah, I think, you know, we we amassed a waitlist of a few hundred thousand folks before we launched the product.
2:44:24
And I think if you look at the cohorts of users that were coming in really early, it was, you know, designers across every discipline.
2:44:30
We're talking interior designers, architects, graphic designers, brand designers, uh photographers, folks like this.
2:44:37
Um which really helped seed such an amazing, you know, original corpus of content.
2:44:40
But really where we're seeing a lot of the growth come from now is sort of this, you know, Gen Z wave.
2:44:46
Um you know, I call them kind of the next generation of Tumblr kid.
2:44:47
Um you know, they they they love to mood board for fun, you know, maybe they're not saving typographical references on a day-to-day basis because, you know, they need it for their client work, but maybe they're just dreaming up um a version of themselves that they aspire to be.
2:45:01
Um and they want to surround themselves with beautiful things. Yeah.
2:45:04
And then how is how have you been grappling with the AI generation image generation boom?
2:45:12
Four you started the company 4 years ago.
2:45:14
It's pretty much pre-AI content, essentially.
2:45:17
Uh now it's indistinguishable.
2:45:21
Uh what is what what's the journey been like for >> there's so much pressure on each platform to take a stance right now.
2:45:27
When you look at most of the platforms, the stance is like, AI content is welcome here.
2:45:31
We may try to identify Yeah, we may try to tag it. >> Yeah.
2:45:35
Uh but it's being harder and harder to tell.
2:45:37
>> platforms, you just have to search, okay, I only want to see images before 2022.
2:45:43
>> [laughter] >> And and it's like almost [clears throat] like an art like an archive that can be really good.
2:45:46
Uh but yeah, you just how have you been processing it? Yeah, for sure.
2:45:51
I think that, you know, we're definitely seeing a lot of backlash within the ecosystem against a lot of other platforms where AI-generated content is kind of proliferating all of the feeds.
2:46:00
And um you know, people are engaging with stuff that they don't even know is AI-generated content.
2:46:05
Um and maybe they search the thing and then they click into it and they see that it's labeled by AI and they they find that really frustrating.
2:46:13
And you know, we're definitely we're definitely growing a a lot of users now that we kind of consider like refugees from this.
2:46:18
Um you know, we really want to be a platform that champions um human creativity and human-created content.
2:46:24
Now, that's not to say that we're drawing a hard stance against AI-generated content, but I think that it's really important that people are able to decide what they want to see.
2:46:32
Um and so, we've done, you know, what some of these other platforms have have done as well is every image that gets uploaded on platform, um we're running it through, you know, multiple different algorithms to detect if that is AI-generated.
2:46:42
And so, every user has settings within their profile where they can um choose to show or hide AI-generated content. Okay. Yeah. Interesting.
2:46:50
And then How how confident are you that you're catching all of it?
2:46:56
Yeah, I mean, it's a it's an uphill battle, right?
2:46:58
I mean, it keeps getting better.
2:46:59
You have to keep retraining the models. Yeah.
2:47:00
Um it's only going to get more difficult. Yeah.
2:47:03
Um so, you know, I I think that it's only a matter of time before it's, you know, pretty difficult to There's also some AI image models I've noticed where I will upload an image, ask it to do something, and it kind of just spits out the exact same image, or maybe it just like adds a piece of text.
2:47:19
And it feels like it didn't actually run a new diffusion model.
2:47:24
It just sort of used some tool to like layer over text.
2:47:26
And it's like, well, it's kind of just acting as a genetic Photoshop at that point.
2:47:30
It's not really creating an AI image.
2:47:32
Like all of the details and fingers of her same because it's literally the same pixels that it's just using.
2:47:38
And so, to my account, yeah, it's going to be all hairy.
2:47:41
Um I'm interested to know how you think about for you pages, algorithmic feeds versus search, and being a like a more of a search engine. Is that line blurring?
2:47:52
What are the important tradeoffs?
2:47:54
What do you like and dislike about algorithm design? Yeah, for sure.
2:47:58
So, we have a for you page on on Cosmos that, you know, learns your taste and learns your interests as you save things.
2:48:03
I think it's important that you have something like that so people have a new vector that they can discover content through.
2:48:08
Um you know, what's really interesting is the search problem is actually very similar to the for you problem, especially when you get into the world of serving people personalized search, right?
2:48:16
So, you train your for you, you know, we have an idea of what your tastes and and your aesthetic leanings are.
2:48:22
And then when you search something, you're actually just adding that keyword over sort of this vectorized database of um you know, visual aesthetic that you've already identified with.
2:48:32
So, the problems are actually very related um and intertwined.
2:48:35
I think one thing that we've done that's really interesting is we've started um, developing in-house aesthetic prediction models.
2:48:43
Um, so we've actually been using all of our own data, user data, the you know, user user uploaded content, and we've been training models that understand kind of like what good versus bad looks like.
2:48:52
Um, and we're using we're using these aesthetic predictions to loosely re-rank our search results and our for you pages to try to keep, you know, the slop off of the platform.
2:49:00
Um, you know, we believe that >> Slop wars.
2:49:04
Yeah, you deep in the slop wars.
2:49:06
Frontline soldier here in the foxhole.
2:49:08
[laughter] I salute your your your service.
2:49:12
Uh, it's a good >> like we believe that your outputs are a reflection of your inputs, and so it's like very philosophically important that we're we're feeding people high-quality inputs because, you know, so many creative projects start with the mood boarding phase.
2:49:22
Um, and so if the inputs are going to become the output, it's really important that, you know, we're we're giving people a place where they can find the highest quality things.
2:49:30
What's been the growth loop for you?
2:49:33
What's been the key to growth?
2:49:33
I know that you've been uh, you know, featured by Apple as one of the top 25 apps for 2025.
2:49:40
You're 500,000 followers on Instagram.
2:49:43
But, uh, is there a traditional like referral flow?
2:49:45
What what are you using from like the web 2.
2:49:49
0 boom era versus viral social playbook?
2:49:53
What's been the big growth engine?
2:49:55
Have you had to just run ads? Like what what's worked?
2:50:00
Yeah, we haven't been running ads.
2:50:00
I mean, it's really been organic up until this point. Yeah.
2:50:04
Um, >> you know, we had an early like invite friend flow which was pretty successful for us.
2:50:08
I think that that's not as successful as it was a few years ago when we ran it.
2:50:11
Um, but I think, you know, the nature of Cosmos is really collaborative.
2:50:14
Um, you know, you you start what we call a cluster as like a collection.
2:50:18
You start a you start a cluster, you start inviting, you know, your collaborators to those.
2:50:23
Um, the experience gets so much more valuable.
2:50:26
Um, and we're seeing really high density as well within some of the best creative teams in the world.
2:50:31
I mean, we have, you know, hundreds of users on platform on Nike. com emails.
2:50:33
We have, you know, teams that Chanel is using Cosmos, teams that Apple is using Cosmos. Yeah, yeah.
2:50:38
So, that density within creative teams has been really really powerful for us.
2:50:41
Where are you >> I feel like you're going to be anti-ad just because as soon as you have an ad, it's hard to influence like, "Okay, can't say like, well, you can only serve pretty ads."
2:50:54
>> you can post the sloppiest AI slop with six fingers.
2:50:59
But, you're it's we're going to charge you a pretty penny.
2:51:00
No, no, I I want to know the real uh, monetization strategy. Yeah, for sure.
2:51:05
Um, so we're not monetizing yet.
2:51:07
I mean, we have a premium subscription right now, but it's pretty demoted within the product.
2:51:09
Um, I think, you know, there there will be a lot that that we have yet to reveal.
2:51:14
Um, but I think that where we're going is, you know, going deeper on sort of focusing on those those creative teams that are using Cosmos and how can we better serve those folks?
2:51:23
Um, and then we're also starting to to build into commerce as well.
2:51:27
So, we launched a a commerce pilot um, last year.
2:51:30
And, you know, you can imagine, you know, we're running hundreds of thousands of searches a day right now on the platform.
2:51:34
And if someone searches for brown leather couch, they're probably looking to buy a brown leather couch.
2:51:39
Um, and so how can we Yeah.
2:51:39
Yeah, how how can we create a compelling commerce experience that doesn't feel like we're trying to force products down your throat?
2:51:46
Um, but it's really commerce through through inspiration. Yeah, yeah.
2:51:50
It's like aesthetic first, taste first as opposed to like feature set, price, like all the filters that you see when you're on Google shopping.
2:51:57
It's a like those are probably going to be way lower in the funnel than the aesthetic that you're looking >> Shoppable mood board.
2:52:03
You can think of people doing inspiration for, you know, interior design, their wardrobe, all this stuff.
2:52:10
It's like that's that's a a high-intent moment when somebody's trying to um, Yeah, can you can you explain a little bit more about the aesthetic trends that are popular?
2:52:18
I I've seen these different like like phrases used to describe how certain people describe their whole aesthetic.
2:52:27
Like what what is uh, what what how would you describe the communities that have formed around these like modern sub-niche aesthetics?
2:52:38
Yeah, it's a it's a really interesting question.
2:52:39
I mean, we we launched a new feature today.
2:52:40
Um, so we gave the the profile a really big refresh.
2:52:44
Historically, everything that you saved had to go within a cluster.
2:52:46
Um, the the release that we put out today gives you a a core feed of images that sit at the forefront of the profile, which is really akin to like your Tumblr blog back in the day.
2:52:56
It's really like, you know, a snapshot of your taste and and what you're into.
2:53:00
Um, we're starting to go really deep on, you know, the data's in the trends um, that we're seeing on the platform between, you know, what people are searching, what clusters are they creating, all of those sorts of things.
2:53:11
And we're going to start putting out trend reports, which we're really excited for.
2:53:13
And we've started sort of seeding these into our newsletter, which has been really really fun. >> That's great. That's cool.
2:53:18
But yeah, it's been really cool to see these different sort of niche aesthetics blossom.
2:53:22
Um, I think historically, a lot of the usage has been just around again the core use cases that we were talking about on like graphic design, interior design, whatever.
2:53:29
Um, but if you think about something like Tumblr, right?
2:53:32
There was like fandoms that were popping off and, you know, like emo aesthetics and culture, right?
2:53:37
So, we're starting to see some of these pop up, but it's a little early to tell.
2:53:41
Um, but we're really excited to start publishing these more publicly.
2:53:43
Okay, last question for your personal aesthetic.
2:53:46
The Pantone color of the year for 2026 is cloud dancer.
2:53:48
It's a soft, lofty white that symbolizes calm, peace, and fresh starts. Underrated or overrated?
2:53:59
You know, I'm I'm a neutral palette guy, but I know it was really uh, in a contention within uh, within the creative community.
2:54:06
I think we could have gone a little bit more creative with it, but uh, I'm never going to hate on a neutral palette. >> Okay.
2:54:11
This is pretty out of This is pretty out of pocket for me.
2:54:13
I think >> So, it sounds like cloud dancer might be working its way into your >> It's a good name. into your cosmos.
2:54:20
>> in the X chat says, "How do you avoid creating an automatic house aesthetic if you're algorithmically filtering slop?" Uh, any thoughts there?
2:54:28
Like is it >> great question.
2:54:30
Is part of this like >> Yeah, it is so user-generated somebody might have.
2:54:35
Like you're not trying to like have an overarching aesthetic other than like somebody could come on and create a bunch of clusters for an aesthetic that that is not aligned with your personal taste or taste of Cosmos.
2:54:49
>> ArtStation look became the Midjourney look, and then now that just looks like the AI art look.
2:54:53
But, you know, what if you're actually just into like, you know, matte painting?
2:54:57
Like what if you're going to get filtered, maybe? I don't know.
2:55:01
Yeah, I think like the point of the aesthetic prediction model is is less to um, pedal what we think is good and is more to set a bottom bound on what we think is bad.
2:55:11
And so, that bar is set pretty low.
2:55:15
Um, but it's it's a great question.
2:55:15
You know, we're continuing to retrain the aesthetic the aesthetic models that we have.
2:55:19
Um, and we're kind of going through this right now of how we're trying to widen the aperture of that um, to service more folks and and and and to reach a broader audience.
2:55:26
Um, so I don't think there's a clean answer to it other than just like, you know, continuing to iterate on your models and and pass them into production and and measure and and learn from there. Very cool.
2:55:37
Well, thank you so much for taking the time to come hop on the show. Great to meet you. And good luck. Congratulations. Great to see you. We'll talk to you soon. >> Cheers. Goodbye.
2:55:46
The New York Stock Exchange.
2:55:46
Want to change the world?
2:55:47
Raise capital at the New York Stock Exchange.
2:55:53
And with that, we will Oh, you can hear I hope you can hear it.
2:55:55
I don't know if it's coming through the speakers. >> is fired up. That V8 is roaring.
2:55:59
Uh, and we have Michael from FabFitFun.
2:56:02
And Steve 33 in the [music] restream waiting room.
2:56:06
We'll bring him in the TBN ultra dome. How are you doing? >> the show. Welcome to the show.
2:56:10
>> Hey guys, doing great. Good to be here.
2:56:12
>> Thanks so much for hopping on. Uh, give us the news. >> at this jacket.
2:56:15
First First of all, this jacket is fantastic. >> news for us. What's the news? >> dressed impressive.
2:56:20
I didn't want to let you down, so. Incredible. >> Thank you.
2:56:24
Uh, you raised some money. How much did you raise?
2:56:27
Uh, we've got a $150 million fund.
2:56:27
We've closed $150 million fund.
2:56:35
Um, what what what what what submarkets are you most interested in? What strategy? What stages?
2:56:43
How are you thinking about focusing your investing work over the fund life cycle?
2:56:48
Yeah, so we are a deep tech fund focused on the US-Israel corridor.
2:56:52
So, we'll be investing across US and Israel.
2:56:55
And so, you know, what's what's unique especially about the the kind of the Israel ecosystem focus is there isn't a a deep tech fund let's say in the mold of let's uh, you know, an Eclipse, a DCVC, a Lux Capital focused on that ecosystem.
2:57:10
And we just think there's enormous opportunities.
2:57:16
Uh, what are the what what are the great uh, uh, recruiting hubs for entrepreneurs in defense in Israel?
2:57:24
We've heard about Talpiot and a few other groups.
2:57:26
Where are you finding talent?
2:57:28
Uh, are they uh, you know, ex uh, founders themselves or repeat founders?
2:57:35
Where are you sourcing deals from?
2:57:38
Uh, so interestingly actually the the former commander of Talpiot is actually one of my partners in the fund. There you go.
2:57:45
For those of you who uh, aren't familiar with Talpiot, you know, there's a there's a lot of different uh, elite units in in in the IDF, but Talpiot is the unit of the physicists.
2:57:54
Um, it was a bet the the IDF made to to really train physicists uh, uh, and and combine that with the defense industry.
2:58:01
Um, so we do we we work closely with uh, with, you know, the the different uh, groups.
2:58:08
Another of my partners is from 8200, which many of you might be familiar with as kind of the cyber unit within the IDF.
2:58:13
Uh, we have uh, tentacles into into those alumni groups and networks as well as a lot of the institutions of higher learning.
2:58:20
So, Weizmann Institute, Technion, etc. Sure.
2:58:24
Um, you know, we're we're kind of uh, I'm actually the the only uh, non-Israeli on the team of five partners. Yeah.
2:58:30
Uh, so we're we're deep in that ecosystem.
2:58:33
>> Five partners, that's cool.
2:58:33
Out the gates, it's sort of the the the counter position pretty squarely against the solo Solo GP, yeah.
2:58:40
There are a lot of people that were doing that.
2:58:41
Yeah, how do you how do you all meet and what was the what was the concept between the maybe the larger partnership at this phase? I don't know.
2:58:48
Yeah, so so we have a what we call an expert first model.
2:58:54
The I you know, my main my main code GP is Leo Prosor who has been a venture capitalist for 15 years.
2:59:02
Decided to start a new platform because of the opportunities we thought were emanating specifically in deep tech and out of the Israeli ecosystem.
2:59:08
But to do deep tech right, you actually have to have you know, significant capabilities to go deep on the technical side to have people who are you know, domain experts.
2:59:20
And so three of our other partners are actually domain experts in the categories that we're most bullish on.
2:59:26
One being quantum computing, the second being AI infrastructure, a third being energy.
2:59:32
And then we also have a venture partner and advisor in the robotic side.
2:59:36
How are you thinking about point solutions versus defense platform companies?
2:59:42
Are you looking for a multi-product defense firm that can build sensor towers and drones and submarines or do you want to invest in a bunch of different teams that are doing small like smaller product bets, see what works and then maybe scale out of that?
3:00:05
Like what's the current meta on the ground in Israel?
3:00:10
Yes, so interestingly, although you know, defense is an important part of the ecosystem and shoots off a lot of the innovation that we are investing into, we don't think of ourselves as a defense fund.
3:00:20
In in in fact, we're we're not focused on kind of kinetic battlefield companies although a byproduct of the types of companies and technologies that we're investing in often times do have defense ramifications and capabilities on the battlefield.
3:00:38
We we just think that the commercial opportunities of those technologies when they extend beyond defense kind of specific companies are are much bigger.
3:00:48
They can have much bigger outcomes.
3:00:49
So, there's a lot of dual use in in the in the types of things that we're looking at and you know, what we're looking for is just you know, in insanely capable founding teams, really groundbreaking kind of technology and IP and enormous end markets.
3:01:02
And you know, when when you look at the kind of the confluence of things of that that Israel has in terms of the defense industry, the institutions of higher learning, the concentration of elite scientists, RF industry, silicon industry, optics industry, etc.
3:01:20
There's really you know, the only other geography in the world that has that sort of concentration of those types of mixes of assets is really California.
3:01:28
And you see what California produces.
3:01:31
So, we think Israel is kind of this looming deep tech giant.
3:01:34
In a lot of ways, the ecosystem there in deep tech is kind of where cybersecurity was maybe a decade ago in Israel.
3:01:39
And now it's this powerhouse that's producing these you know, just insane outcomes.
3:01:45
We think of the next decade that the deep tech outcomes from Israel are going to be right up there.
3:01:51
Where did the name come from? Yeah.
3:01:54
So, I think deep speaks for itself.
3:01:54
You know, one, we go deep and we're focused on deep tech.
3:01:58
And 33 is actually it has a mystical connotation in Judaism.
3:02:04
It's the it's the day of Lag Ba'omer which is a Jewish holiday where the kind of the depth of the the hidden secrets of the universe were were revealed for the first time.
3:02:14
And you know, that's what we really think our founders are doing.
3:02:16
Our founders are companies and kind of the mission of the firm is to go into the tech technological and scientific frontiers.
3:02:24
And we think of that as a way of revealing hidden truths.
3:02:26
The the type of work that that that these companies are doing, what we're trying to build is really frontier tech and and new innovation that you know, moves moves the world forward and moves our understanding of the world forward. >> That's cool.
3:02:41
Last question for me, energy.
3:02:41
Do you put that in the deep tech realm?
3:02:44
Are there particular areas within energy that you're interested in?
3:02:48
Solar, nuclear, wind, anything?
3:02:51
Yeah, it's a great question. Absolutely.
3:02:53
We actually have two energy companies already under our belt.
3:03:00
We you know, in in particular kind of our thesis on energy is is where the point of production and the point of consumption are brought together.
3:03:08
So, where can you create unique types of energy outputs on location, on site?
3:03:19
So, for for for instance, if one company we haven't announced is is is able to produce carbon fuels, carbon based fuels out of a laboratory.
3:03:31
And you know, so and and there's a scale up model around that that we think is extremely compelling.
3:03:37
You know, the the name of the game for a lot of you know, US security interests, Israel security interests and the shared interest between the two of them is this kind of supply chain resilience.
3:03:48
I think you we saw the president speaking at Davos and and even you know, describing maybe you know, the the kind of the the counter swing of globalization is here and that means these capabilities on site being less reliant on any specific partner and trade for their national security.
3:04:08
And so that that ability to to bring things on site becomes incredibly important. It's amazing.
3:04:11
Well, thank you so much for taking the time to come chat with us. Congratulations.
3:04:16
>> Next time you join, you can join from Tel Aviv.
3:04:18
I'm assuming you're are you calling in from LA right right now?
3:04:20
I'm actually calling in from New York. I'm here.
3:04:25
Deep 33, you know, we're we're across LA, Tel Aviv and New York.
3:04:27
So, the team all came together you know, announce the fund and and do some critical work together. So, Amazing. Amazing.
3:04:34
Well, I'm sure you'll be back soon. Yeah. Congrats. We'll talk to you soon. Fun to get Cheers. Goodbye.
3:04:41
CrowdStrike, your business is AI, their business is securing it.
3:04:44
CrowdStrike secures AI and stops breaches. That's right.
3:04:48
Up next, we have Aaron Katz.
3:04:48
He's the co-founder and CEO of ClickHouse.
3:04:53
He'll be joining in just a minute.
3:04:56
In the meantime, let's head over to the timeline.
3:04:57
Elon Musk has confirmed that he's unhappy with the Twitter algorithm.
3:05:02
Data Hazard said Twitter algo has gone to hell.
3:05:04
I want to again see obscure technical posts from outside my follows, not this cornucopia of low IQ rage slop.
3:05:15
That's interesting coinage.
3:05:15
Elon chimed in said, I agree, sigh. So, that's the thing.
3:05:20
Anytime that there's a bad day on the timeline, bad week on the timeline, I feel like they're pretty aggressive about just mixing it up.
3:05:26
I don't know, you might not like the new thing, but it's going to be different.
3:05:29
You're going to see some new stuff.
3:05:30
And there's been some fantastic deep fakes of Elon Musk as the farmer from Babe: Pig in the City looking at the slop and being sad.
3:05:38
So, fun day on the timeline.
3:05:41
Good that there will be some changes coming.
3:05:43
Anyway, without further ado, we have Aaron Katz with ClickHouse. Welcome to the stream.
3:05:48
Thank you so much for hopping on the show. Good to meet you.
3:05:50
How's your year going so far?
3:05:54
Well, the calendar year is behind us, but our fiscal year is about to finish the end of this month and it's going really well.
3:06:00
We got you know, whatever eight or nine days left and you know, we're off to off to a good start to finish the year in the fiscal quarter and get the new year up and running beginning of February.
3:06:11
What's the theme of 2026 for the company? Is it just more AI?
3:06:14
It feels like AI is so obvious, but also what else are you going to focus on?
3:06:20
Well, you know, ClickHouse has been a back end database to a lot of agentic workflows over the past couple years even before the chat GPT moment.
3:06:26
You know, we're being used by Lovable Cursor, Anthropic, Open AI.
3:06:31
Pretty much every leading AI company right now is using ClickHouse in some sort of capacity.
3:06:38
So, but it's just not AI companies.
3:06:40
I mean, we're the back end to technologies like Ramp for example.
3:06:45
They're your sponsor if you talk to Eric.
3:06:46
We power most of the analytical experiences if you're a Ramp customer.
3:06:51
And so it's just kind of doubling down on what's gotten us here.
3:06:53
It's a very large surface area that we're going after and just kind of broadening the competitive landscape.
3:07:00
Have there been any challenges on on actually scaling the business from an infrastructure size?
3:07:06
You're at a scale where many AI companies are struggling with data centers, GPU poor.
3:07:13
How is the actual build versus buy decision changed over the last few years?
3:07:18
How is the how is the infrastructure side of the business changed?
3:07:22
Yeah, well scalability is one of ClickHouse's strengths and always has been.
3:07:25
I mean, we've got you just talked about Elon's many of Elon's companies are using ClickHouse.
3:07:29
Tesla's a great example of that where they're ingesting a billion events per second into ClickHouse.
3:07:35
And there just isn't another database in the world I think you need to stop.
3:07:39
Just tell us who's not using ClickHouse.
3:07:44
Yeah, just tell us who's not a customer and then it'll be quicker that Yeah, fair enough.
3:07:48
I mean, you just kind of get your head around the volume of data that these LLMs are generating and the ability to ingest that in efficient way to be able to store and analyze that, you know, ClickHouse really shines.
3:07:59
So, scalability is something that we we really promote and our customers talk about as one of the unique characteristics of ClickHouse. Yeah.
3:08:07
How are you thinking about just walking through the ladder of different analytics suites and analytic functions and and just case studies that can actually that are best practice today?
3:08:19
I mean, people are familiar with you know, like big data, map reduce, you know, count a a of things across a bunch of databases.
3:08:27
We're in a much more modern era.
3:08:27
What are you seeing companies do that's unique, surprising, interesting, or uniquely enabled by ClickHouse?
3:08:36
Yeah, you mentioned MapReduce or any sort of kind of batch-oriented processing.
3:08:39
It's all moving towards real-time.
3:08:40
And Ramp is a great example of that.
3:08:43
If you're a user or customer of Ramp and you want to run analytics on spend patterns inside of your company, you're not going to wait, you know, 2 to 5 seconds for that dashboard to render that graph to update or the report to produce results.
3:08:56
You expect to see those in milliseconds.
3:08:58
And so, there's just this broad shift from an analytical perspective to real-time experiences.
3:09:06
You batch processing, you know, even waiting, you know, 3 to 5 seconds for any sort of dashboard to refresh is just an eternity.
3:09:13
And so, that's a big pull to why people are moving towards ClickHouse.
3:09:18
You're Oh, sorry, Jordan.
3:09:18
Yeah, I wanted I wanted to ask about the engineering culture.
3:09:21
Uh last week we were at a dinner and somebody was telling me about I don't I I'm I I'll I'll kind of mix up some of the details, but they were telling me about like the an investor was going through the due diligence process with ClickHouse.
3:09:33
And click you guys had shared like that uh that they couldn't believe how like how few engineers had created some of the early technology and they just uh honestly didn't believe it.
3:09:45
So, I wanted to ask about kind of the early engineering culture and and how that's evolved and and and uh what you guys are doing on the talent side that uh allowed you to, you know, work with so many in uh of these, you know, massive important companies.
3:10:01
I mean, I I I love that question.
3:10:01
And I don't get it often enough.
3:10:03
The engineering team at ClickHouse, to the broader community behind ClickHouse, but the creators and the committers that are part of our company are the best engineers that I've ever worked with and I've been in the industry for quite some time.
3:10:16
I know you've had Marc Benioff on your show several times.
3:10:18
I spent 12 years at Salesforce that had an incredible engineering culture.
3:10:22
Um the team that we've assembled here specifically in infrastructure software is the best in the world.
3:10:28
And you're right, it was a very small team of primarily Russian engineers inside of a company called Yandex, Yeah.
3:10:37
which was commonly referred to as the Google of Russia that actually created ClickHouse originally.
3:10:40
My co-founder, Alexey Milovidov, who lives in Amsterdam, is the one that actually named it.
3:10:46
It's short for clickstream data warehouse.
3:10:48
And so, he was thinking about the data warehouse use case when he created the database itself and then made the brave decision to open source it in 2016.
3:10:57
And that's essentially you just expose your source code to the world and then anybody can adopt and deploy the technology with no attribution to the creators of the software without any sort of commercial relationship. And it was a small team.
3:11:12
It was a dozen engineers uh who were the primary committers that created this incredibly powerful, feature-rich uh database.
3:11:19
And it's a total joy to work with this group.
3:11:21
They're all in Holland, in the Netherlands, uh now all part of our company uh continue to advance the project.
3:11:28
And then we've built a managed service that runs in the cloud called ClickHouse Cloud uh that they're also contributing to.
3:11:33
Um and that's the primary business model.
3:11:35
And this is a managed service that runs on Amazon, Google, and Microsoft infrastructure.
3:11:41
And then in Asia, and primarily in China, we have a partnership with Alibaba. Mhm.
3:11:47
How are you thinking about the way that developers and teams are selecting database backends, data storage products in the age of agentic coding?
3:11:58
I feel like we talked to a lot of folks who uh they go to an agentic coding solution.
3:12:07
They say, "I want to build this type of application.
3:12:09
I want to build, you know, some custom piece of software."
3:12:11
And the database choice is sort of made for them by the by the coding agent.
3:12:17
And and this feels like it's hyperrelevant at the vibe coding the the DIY hack project level, but is this something on your radar where you think that in a few years, maybe it's already happening, um how you show up in LLM search results and how how the different uh AI agent coding models feel about ClickHouse will be important to your business?
3:12:46
Well, you know, Anthropic uh spoke at our event uh last year in San Francisco. So did OpenAI and Tesla.
3:12:50
And Anthropic discovered ClickHouse by asking Claude what they should be using for observability.
3:12:58
And Claude said you should be using ClickHouse.
3:13:00
And I had a I had a call with the CEO of a very large fintech company in Europe last week.
3:13:05
And he said every LLM we ask what we should be using for this new real-time analytics product we're building suggests ClickHouse.
3:13:10
And so, you know, fortunately a lot of people are turning to these LLMs for guidance on what technologies they should be uh they should be adopting.
3:13:18
And I think as everybody knows, like, you know, IT decision-making has been completely turned on its head from kind of a tops-down C-level mandate, you're going to use Oracle, you're going to use IBM, now to a developer-led uh evaluation.
3:13:32
And open source creates such a fast path for a developer who's building an agentic application to deploy, experience, experiment with a technology without any sort of vendor relationship.
3:13:45
They can actually push it into production for some of these agentic applications without any sort of vendor relationship.
3:13:50
Open source is completely disrupting, you know, how these uh LLM providers and enterprises are deploying these applications.
3:13:56
And we made an acquisition last uh week that we announced on Friday alongside our financing that we're super excited about.
3:14:03
It's a company out of Berlin called LangFuse.
3:14:05
And they have built, you know, an industry-leading LLM observability application so that now enterprises can observe, you know, the types of experiences their users are developing on these LLM applications. Mhm. Very cool.
3:14:21
How are you How are you processing uh all the chaos in SaaS right now, the sell-off broadly, the industry's transition, you know, uh uh you know, went through uh you know, couple decades where a big question about the shift from seats to consumption or or performance results >> Yeah, there's so many there's so many I feel like open questions.
3:14:42
How much of a threat are our new uh you know, you you probably laugh when people say like, "Oh, I made this database with a prompt."
3:14:50
And you're like, "Okay, well, you're missing like, you know, the the 90 other features that, you know, an enterprise is really going to care about.
3:14:57
But after spending, you know, uh more than a decade at Salesforce and then running ClickHouse, I'm curious what your point of view is.
3:15:05
Yeah, I mean, you know, John mentioned this move from a seat-based model to consumption or usage-based, which infrastructure isn't that unique.
3:15:11
I mean, it's been around for quite some time.
3:15:14
Like, our customers simply pay for what they use, which is a combination typically of storage and compute.
3:15:18
And these are very kind of AI-intensive applications.
3:15:24
And what's unique about our service is that it automatically scales up and down.
3:15:28
So, you don't need to provision all of the compute that you otherwise would cuz a lot of these analytical workloads are quite kind of spiky in nature.
3:15:35
And you want the application to be able to idle during periods of inactivity, for example.
3:15:39
And so, I do think that, you know, these traditional seat-based Although, I think we should separate like traditional business applications like Salesforce and Workday from kind of infrastructure software, which is much more of kind of the plumbing of, you know, the internet.
3:15:54
And the stuff that you don't see necessarily when you look at a mobile app or you look at a business app or consumer app, it's a lot of the processing that occurs, you know, behind the scenes is primarily where we exist.
3:16:07
I'll give you an example is, you know, we where I would historically use some sort of BI reporting to build a graph or a chart to show me how the business is performing, you know, build me a bar chart that shows revenue growth or build me a stack bar chart that shows regional revenue distribution, things like that.
3:16:25
And I'd go to some data analyst and they'd go and find the source data and they'd spend a week pulling this together and we'd have like multiple reviews.
3:16:31
I now simply ask Anthropic.
3:16:31
So, we've integrated Anthropic's, you know, Claude, I think it's 4. 5, Yeah.
3:16:36
their latest model with our own MCP server and then a ClickHouse Cloud service that has all of our customers product not not our customers' data, but like our customers' use of our service.
3:16:46
And I can ask that uh I can ask that prompt like build me a bar chart that shows these dimensions.
3:16:53
And it builds it in like 5 seconds.
3:16:53
And it's just and it cost me 20 cents uh that single prompt.
3:16:59
And that simple semantic search is generating like dozens of SQL queries.
3:17:03
All of those SQL queries are all being stored in ClickHouse.
3:17:07
And if you think about the characteristics of these uh agentic experiences, like, the number one requirement is latency.
3:17:13
They have to be low latency in terms of the interactivity between the text prompt where you whether it's ChatGPT or anything else where you put in that query and then the database itself that's actually storing the data that's providing the response. Yeah.
3:17:27
Uh it's it's it's fascinating how much of a global company ClickHouse is, the Alibaba partnership, the Russia history with Yandex.
3:17:35
Uh we were reading a post about selling software in Japan and how the Japan software buyer often will want to read a lot of documentation and details before jumping on a call with a sales associate.
3:17:48
Uh does that match with the reality in Japan?
3:17:49
What What can you tell us about the difference of buyer across different uh different countries that you've experienced throughout your career?
3:17:59
Like, what's the key to global growth uh broadly?
3:18:04
Yeah, it's a great question.
3:18:04
I mean, so, you know, half of our employees are outside of the United States.
3:18:07
We employ people in 22 different countries.
3:18:09
Half of our customers are outside of North America.
3:18:14
Half of our revenue comes from outside of the US.
3:18:17
So, the company is extremely diverse uh internationally.
3:18:20
I had the good fortune in 2005, so 21 years ago, Mark Benioff asked me to move to Singapore and I spent 4 years helping Salesforce expand across the Asia Pacific region.
3:18:32
And at the time, Japan, I believe, was the second largest country behind the US, ahead of the UK, Germany, France in terms of revenue contribution.
3:18:42
Now, I don't think I can be quoted on that cuz I'm not necessarily true it's number two or three, but it was like top five and I would argue it's probably top two if my memory serves me correctly.
3:18:50
And you could add South Korea to that same description of just how unique these markets operate and how localized the selling effort is.
3:19:00
We recently did and I've seen both models and one being you do a joint venture and where you partner with a local company and you share the risk and you share the economics and you share the upside and they leverage local relationships in the market and local market knowledge, etc.
3:19:16
Or you try to do it yourselves, establish your own KK in Japan and I've gone down both paths and learned a lot of lessons along the way.
3:19:26
And so here at ClickHouse, we did a joint venture in Japan.
3:19:28
We recently announced that with a firm called Japan Cloud and they were previously SunBridge, which is the firm that did salesforce.
3:19:36
com's joint venture and so worked with these folks for you know, two decades now.
3:19:39
And so yeah, it's a highly localized market.
3:19:42
The buying behavior is very different in Japan and in South Korea than other parts of Southeast Asia, putting aside greater China or Australia, New Zealand or the Indian subcontinent.
3:19:55
So it's a huge market, but not many companies get it right.
3:20:00
Honestly, you know, they try to do it themselves versus leveraging local expertise.
3:20:04
We also brought on some investors, firm called Geodesic Capital and that's run by an individual named John Roos and John, I believe he's still on the board of Salesforce, but he was the previous ambassador for the United States to Japan and just having those types of relationships are very important for a company like ours that we frankly don't have the same level of awareness in Japan that we do here in Silicon Valley or you know, in New York. Mhm.
3:20:27
Yeah, makes a ton >> Makes a lot of sense. Fascinating. Jordan, anything else? Yeah, very cool. Thank you. >> get back to your day.
3:20:34
Thank you so much for hopping on the show.
3:20:36
>> Yeah, this rate I'm I'm sure there'll be many reasons to have you back on. >> ring the gong.
3:20:39
There there there's a recent fundraise.
3:20:41
Can you tell us the details? Yeah, happy to.
3:20:44
You know, we we weren't running a process or racing capital.
3:20:48
There's a lot of investor interest and so we ended up pulling a round together kind of over the holidays that was led by Dragoneer here in San Francisco and we ended up raising 400 million.
3:20:58
We had participation from a number of our existing investors and new investors.
3:21:07
So Pulled together over the holiday.
3:21:08
We've talked to a lot of VCs who said it that it was easier to do deals over the holidays.
3:21:13
There were less distractions at the office and so plenty of time to hop on the phone with like a tight partnership to get something through. So congratulations. Love it.
3:21:21
All right, well I appreciate it. Thanks for having me on.
3:21:23
Yeah, we'll talk to you soon. Have a good one. Goodbye.
3:21:28
Turbo popper, serverless vector and full text search built from first principles on object storage.
3:21:31
It's fast, 10x cheaper and extremely scalable. We are puffing. We are puffing. Back to the timeline.
3:21:39
Did we miss anything else Um yes, we missed the fact that Keith Rabois has hit 5,000 Barry's classes. Woah.
3:21:49
Some people would say that's too many.
3:21:51
It's an incredible [laughter] amount only possible, I think, mathematically because he does multiple per day. Yeah.
3:21:59
But what an absolute generational run, sometimes a literal run on the Barry's treadmill from Keith Rabois.
3:22:07
Demis Hassabis from Google told Alex Heath at Sources that that he has no plan no plans to put ads in Gemini.
3:22:16
It's interesting they've gone for that so early.
3:22:18
He said of Open AI putting ads in ChatGPT, maybe they feel they need to make more revenue.
3:22:25
>> [laughter] >> What's interesting is I I feel like yes, it's like it's like at what level do the ads bake in because you can you can access some level of Gemini model through the AI search overviews, the the enhanced results that come from come from Google searches and they've already monetized those and it doesn't ruffle any feathers.
3:22:46
So of course on this show, we're very pro ads and my answer my my response to Demis should be let's do it, buddy.
3:22:55
>> [laughter] >> That's right.
3:22:56
I'm ready for ads in Gemini 3 Pro.
3:23:00
But of course they're in a very different position.
3:23:02
The business is much larger, much more much more established and so they have much more flexibility with timing these things.
3:23:08
I do wonder, you know, the the whole ads in ChatGPT news cycle.
3:23:14
It was released on a Friday.
3:23:17
It was very much crowded out by the Elon Open AI lawsuit.
3:23:21
It had been rumored and discussed multiple times.
3:23:27
Sam Altman had mentioned it in many different podcast appearances.
3:23:30
He talked to Ben Thompson about what he liked about Instagram's ads. He had been messaging.
3:23:36
Feji Simo came on to find a couple things to talk to us on our show about it.
3:23:41
And so people it it was a very slow process of building up this idea that ads will be coming to ChatGPT.
3:23:46
And the benefit of that is that, you know, it should it's not just all of a sudden, "Hey, the thing that I like now stuff full with ads."
3:23:53
It's a been a very slow roll out.
3:23:55
I think it's been deliberate. I think it's smart. I think it works well.
3:23:58
We've been discussing whether or not the first chat app to in to in to add digital advertising might get like a branded with a scarlet letter of like that's the one that has ads and you always remember that one as the one that has ads even if they all add them eventually. Yeah.
3:24:14
I don't know that that will happen, but I have yet to see any real backlash across the internet around, "Oh, ads are coming to ChatGPT. It's bad."
3:24:25
So in general, I feel like the rollout has been has been handled well.
3:24:28
I'm sure we'll see more interesting things when the ads actually go live.
3:24:33
People will be taking screenshots of them, sharing them.
3:24:35
As long as they partner with good companies like the Ridge Wallet, I think they're going to be I think people will be thrilled to see Ridge Wallet ads in in ChatGPT.
3:24:42
Imagine getting one of those like really sketchy like supplement ads, you know, that that they they run these on like display. Yeah, yeah, yeah. I know.
3:24:51
Getting [laughter] one of those.
3:24:51
Yeah, it's like some some x-ray and it's like this one thing is destroying your metabolism.
3:24:56
>> Doctors hate >> Doctors hate this, yeah.
3:24:57
Um the the Bank of America CEO says he hired 2,000 recent graduates from 200,000 applications.
3:25:04
I wonder how much of that is driven by AI applications.
3:25:08
People Yeah, some people are wondering like how many of those applications were duplicates.
3:25:14
You apply to multiple jobs.
3:25:16
You can only be hired once.
3:25:18
But Bank of America clearly growing.
3:25:21
Humans and the new Neo lab founded by Anthropic, XAI and Google staff.
3:25:25
They're trying to build interactive AI.
3:25:29
They raised a >> a Neo Neo lab.
3:25:32
It's a Neo it's a post Neo lab.
3:25:34
This is a they raised a 480 million dollar seed round from Nvidia, Jeff Bezos and others at a 4.
3:25:40
48 billion dollar valuation and it's in the New York Times. You can go check it out. Cade Metz has the story. Um So that's exciting.
3:25:50
We we we have to do a proper deep dive on the Neo lab landscape.
3:25:55
What do you have for us, Tyler?
3:25:57
I mean, you said it was post Neo lab.
3:25:58
I think it's actually closer to like trad Neo lab. >> Okay.
3:26:03
It's I mean it's it's kind of like like we're going to release models.
3:26:07
They're going to be for consumers. >> Okay.
3:26:09
Um we're going to do it with this human-centric view, but it's not like they're going, you know, that we're combining this with bio wet lab or something.
3:26:15
This is like >> Sure, sure. Yeah.
3:26:18
Like Fei-Fei Li's World Labs in is many ways more of a post Neo lab than this So if I'm if I'm getting this right, Tyler, this is less about okay, I'm going to send off this agent to go work for a week and and I'll check in with it when it's done and more of this kind of like co-working approach. I believe.
3:26:38
I mean, they haven't released much, but it seems like it's point is very interactive.
3:26:42
I mean, like I'm the expert on what they've they've put out, which is very little.
3:26:47
>> [laughter] >> So so the name of the company is Humans, plural, and then an ampersand.
3:26:51
Humans and and Dylan Patel says, "We are all calling this startup Human Sand." Sorry, I make the rules. It's a fire name.
3:27:02
>> Near says, "Um what are you guys actually doing or what are you guys actually making?
3:27:05
I literally cannot tell at all."
3:27:08
>> [laughter] >> Well, they haven't been on TVPN yet.
3:27:10
They haven't broken it down for us like we're a bunch of venture capitalists.
3:27:12
In other news, our very own Dylan Abruscato got a major scoop scooping like a Ben & Jerry's play.
3:27:21
He figured out Instagram replaced the following tab or the following sort of word keyword word with friends, which are followers you follow back.
3:27:31
>> Yes, and this has implications. Explain.
3:27:32
>> Yes, the implications here are that some people aren't following accounts because they want to keep they have some idea of what their follower to following ratio should be.
3:27:42
>> Yeah, if I if I follow 800 people and have 100,000 followers, it looks really elite, but if I'm but if I have 100,000 followers and 100,000 following followers following, it just looks like I reply I'm like doing some scheme.
3:27:56
I have some bot going or something.
3:27:58
I mean, hilariously Barack Obama had a follow back bot on Twitter, I think, throughout his entire presidency.
3:28:08
So this comes up all the time because someone will find some crazy account and they'll be like, "Barack Obama follows this. What's going on?"
3:28:13
And it's like because he follows like 3 million people or something. >> Yeah.
3:28:16
Um but is a continuation of the kind of product decision where they they allow people to not show the number of likes a post has, right?
3:28:23
They want people to post more. Oh.
3:28:24
So, if they're not showing the number of people that >> That's why sometimes I just see a heart that's blank because they don't want to show me who how many people like it?
3:28:32
>> Yeah, it's the user gets to decide.
3:28:32
I don't I don't want to be I don't want to be measured by how many people tapped, right? Okay.
3:28:38
So, the idea was to encourage people to post more if they're not feeling this pressure to put up put up crazy numbers. Oh, I always get 100.
3:28:46
If I get 80, I won't feel good that day, so I will just turn that feature off and tell people. >> Yes, that's correct.
3:28:50
So, I think they want people to follow more people and yeah, we'll see.
3:28:54
I don't I don't think this is rolled out to everyone yet. Yes.
3:28:57
And and and the net effect that you believe will happen is that there will be more following activity on Instagram.
3:29:04
So, uh lots of accounts will be followed. Yes.
3:29:06
>> Yeah, so I I I will say when I go on Instagram, I instead of seeing on this Well, this is this is this is this is a very limited uh test.
3:29:11
And >> Yes, but so I see friends, but I don't see the post number.
3:29:16
I I see the friends, the followers, and following. Okay.
3:29:20
>> Where in this screenshot, I think it was I I don't see it anymore, but it was posts.
3:29:23
Oh, so maybe you're in another test. I'm in a different test. Yeah.
3:29:27
Adam Mosseri is treating us all like guinea pigs over here, lab rats in his maze. Uh it's great.
3:29:32
Uh anyway, is there anything else you want to talk about? We got to end on this.
3:29:35
This is extremely important.
3:29:36
This kid was sent to the principal's office for lying that his uncle was Superman.
3:29:40
The next day, his uncle, Henry Cavill, dropped him off at school.
3:29:47
>> [laughter] >> And Andrew Feldman said, "Dip s h i t school."
3:29:51
Andrew >> Andrew Feldman is the CEO of Cerebras, a $22 billion company, does not like that the school sent the kid to the principal's office. But justice was done.
3:30:01
Henry Cavill showed up and stole the day.
3:30:03
Uh and it's the wholesome side of X.
3:30:06
If your algorithm's all sloppy, maybe you need to adopt Andrew Feldman's algorithm because he's got some great posts and he's not afraid to reply to them.
3:30:14
And last but certainly not least, John Palmer says the TV PN guys are just two Fortnite archetypes.
3:30:20
John has maxed out stats, 6 ft 8, 230 lb, zero V-bucks, still on default skin after a year, no emotes, pure fundamentals.
3:30:28
Jordy's mid-cracked, only 6 ft 1, and absolutely loaded with V-bucks, rotates legendary skins, spams rare emotes on the soundboard every 5 minutes. That I do.
3:30:41
This is extremely accurate.
3:30:43
>> I certainly I feel seen. I feel seen. John knows us well. >> knows us well.
3:30:48
I'm going to hit the hit the repost on that one. That's a good one.
3:30:51
Anyways, folks, thank you for tuning in today. Fun day. It's only Tuesday.
3:30:54
We got three more shows for you.
3:30:57
>> Yeah, lots more in-person in-person guests this weekend or this week.
3:31:01
Uh leave us five stars on Apple Podcasts and Spotify.
3:31:03
Subscribe to the TV PN newsletter at tvpn. com.
3:31:07
Uh we will be live tomorrow at 11:00 Pacific.
3:31:11
>> afternoon, evening, wherever you are. We love you. Goodbye. This is weird.