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And big news, we have our Karazian from Ramp live in the Ultra Dome at 2:00 p. m. today.
5:09
Let's show everyone the linear lineup because we got a lot of great stuff for you.
5:14
We got Rich Greenfield coming on at 11:30.
5:20
Many people are saying he has one of the best names of all time. >> He does. He does.
5:24
>> you're if you enjoy business, if you're a business enthusiast.
5:26
Lots of people like Greenfield projects.
5:28
If you start fresh, Greenfield projects are where it's at.
5:32
Uh Yancey Strickler founder and CEO of California Forever is in the Ultra Dome at 1:00.
5:35
Then we have George uh from Testudo at 1:40 and Ara closing at 1:50 in person.
5:44
Uh it's going to be a fun show.
5:44
Linear of course is the ultimate product, the system for modern software development.
5:51
70% of enterprise workspaces on Linear are using agents today and you should be too. So, uh cling.
5:59
ai, cling AI, the video generation uh video model has been on a tear.
6:06
There's an article in the Wall Street Journal showing uh some pretty staggering numbers.
6:13
They hit 12 million monthly active users and they generated more than 20 million in revenue just last year.
6:18
I wanted to dig in and understand where this came from, the history of Kuaishou, the the Chinese company behind it.
6:25
Uh there's a new farmer filling up the trough for everyone.
6:29
Really uh interesting that they're so neck and neck with Higgs Field. Yeah.
6:35
>> Higgs Field last week comes out, announces they got to 200 million. >> This story drops. >> Yeah.
6:39
That uh Cling seems to be just slightly ahead of them, but really neck and neck and seemingly competing over the same uh opportunity.
6:48
>> Yeah, I mean on the enterprise model API level, even the prosumer level, I think 30% of their revenue is coming from API and 70% is for prosumer.
6:56
So, basically, you have someone in a marketing role or they're just a fun individual creator and they want some AI video product, some generative video.
7:07
>> silence at Davos on Cling. It's crazy. It's insane. >> It's actually crazy. It's insane.
7:13
>> They refuse to ask any hard questions.
7:16
You got Demos on stage, you got Dario on stage, and you're not asking them about Cling and the absolute tear that Kuaishou has been on.
7:25
Actually, I mean, Dario did address the Chinese question.
7:27
He said that they don't lose they're not losing enterprise deals to Chinese companies right now.
7:34
They're they're they're going up against Open AI and DeepMind.
7:35
Um there is a there is an interesting Chinese export control issue that I think we should get into at some point.
7:44
Um with with regard to this story, but first, let's tell you about Restream.
7:48
One live stream, 30-plus destinations.
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If you want to multistream, go to restream. com.
7:51
So, um uh Cling has hit 12 million MAUs, 20 million in revenue in the last month.
8:00
Now, they they seem to be on the up and to the right curve.
8:01
Uh it's pretty massive, Ramp.
8:03
The product launched 18 months ago.
8:05
Uh but Cling is not its own startup.
8:07
It it is a new project from Kuaishou Technology.
8:09
This is a Chinese company and the founders I I couldn't find a single founder >> John, I'm going to I'm going to blow your mind right now. >> Please.
8:17
Guess who worked at Kuaishou. Ooh. He's been on the show. Okay. I share a name with him. Wait, Connor Hayes? No. No. Jordan Schneider.
8:29
>> Jordan Schneider worked at Kuaishou? >> Yes. Yes. Yes.
8:31
He just just responded to the to the Daily News letter. >> want to hop on?
8:35
And said, "LOL, I worked at Kuaishou." What a comeback. Tell Tell all.
8:39
>> Jordan, come get on the show. >> You're welcome. Come hang out.
8:41
If you want to I'll send I'll send him a note.
8:44
>> I I it'd it'd be great to hear more of more of the story from him directly.
8:50
But he might be the only person we can get to to to go on the record about Kuaishou because the founders I don't think they've ever done a podcast appearance.
8:57
They haven't been you know, certainly on like the victory lap podcast American circuit.
9:02
Like many founders that get a company to this scale.
9:07
But there are some interesting links to other American companies.
9:09
So, um Kuaishou is pretty old, especially for the AI boom.
9:16
It launched in 2011 as a mobile app for creating and sharing GIFs.
9:21
This was before Vine and before Musical. ly.
9:23
They were sort of like precursor all those just by a year or two.
9:27
>> So, you could almost say that Jordan Schneider made his money in GIFs. I think so.
9:30
I think he created TikTok, basically.
9:32
We got We we should put him in charge.
9:34
We should get him in the CES seat. Put him in charge.
9:35
We're We're bringing We're bringing TikTok back to America and Jordan should be running it, for sure.
9:41
So, there's some similar threads.
9:41
So, Dom Hofmann, the founder of Vine, he worked at Yahoo before founding Vine. And Alex Zhu at Musical.
9:47
ly worked at eBay and Microsoft and I think SAP as well.
9:52
And so, both of those companies they had like big tech experience, then they went and founded these companies and the founders of Kuaishou Suhua and Shang Yixiao also did the same.
10:04
One of them worked at Google, one of them worked at Hewlett-Packard and then they jumped into the social media boom that was going on in the early odds like in the late I guess the late odds early 2010s.
10:16
Is there a word for the period between 2010 the teens? The teens. The teens? I don't know.
10:22
But that era like post Facebook there was Foursquare, Twitter, Pinterest, Snap there were just like a new one every year was popping up.
10:29
And so they jump in on this and the mobile internet was expanding really rapidly in China at that time.
10:35
There was a big boom there were a bunch of big winners that came out of that era.
10:38
Kuaishou hit 100 million DAU by 2013.
10:41
So basically 18 months after they launched they're a pretty sizable social media app.
10:49
And they actually pivoted in that 18-month timeline from gifts to videos and so once they had the new product dialed they ramped pretty quickly.
10:56
Now there was a little bit of a slowdown between 2013 and 2019 because they didn't hit 200 million DAU until 2019.
11:02
So they were sort of saturating then.
11:04
But they were on a fundraising tear the whole time.
11:08
They raised $350 million from Tencent in 2017.
11:10
They integrated with WeChat to accelerate distribution and the company was worth around $18 billion by 2018 just 7 years into the journey. So not bad not bad.
11:22
The Kuaishou IPO was a particularly crazy moment for the company. So they raised $5. 4 billion at the IPO.
11:29
They were massively oversubscribed for that.
11:31
So they say hey we want to raise 5 billion.
11:34
And 165 billion of demand shows up from the market.
11:38
So retail investors just went insane.
11:40
They're like you know what 165 billion of demand only 5 billion for sale and so the stock trades up 192% at the open and all of a sudden the company's worth $180 billion and both of the founders are deca-billionaires. Pretty sick.
11:59
Phantom Cash fund your wallet without exchanges or middlemen and spend with the Phantom card.
12:05
So that didn't last though.
12:06
There was a massive sell-off and there were a couple there were a couple like speed bumps that Kuaishou seemingly hit shortly after going public.
12:14
So China had a big crackdown on in regulation on local tech companies.
12:20
ByteDance became much more dominant as a competitor and was you know had Kuaishou in their sights and then the Kuaishou user growth just sort of slowed down and so there were a couple misses on you know DAU MAU growth.
12:31
The metrics weren't looking as good and so the investors said hey we're rotating to other things hey we're pulling out.
12:36
And so the stock traded down 80% within 6 months.
12:37
So not great but today the market cap's around $40 billion.
12:42
Like it's still a very real business and also just financially the business is very solid.
12:47
Like it's not losing money.
12:47
You can think about it this way.
12:49
So it's a $40 billion market cap 20 this is all USD. I converted everything.
12:53
So 40 billion market cap 20 billion revenue 11 billion gross profit net profit 2.
12:59
6 billion two and a half billion.
13:02
So that's like a lot of cash flow a lot of net income to work with certainly enough to do some training runs start a neo lab or a the video lab or you know take some new bets.
13:14
And so that's exactly what they did.
13:15
So in 2024 2024 they launched the first version of Kling and they did this just 3 months after OpenAI demoed Sora.
13:22
So it was kind of like the the Chinese answer to Sora.
13:27
Since then they've updated Kling 30 times and carved out a nice little place in the grid of tradeoffs around model performance and cost.
13:34
For cinematic footage people often recommend VEO-3 still but for Kling it has some really strong characteristics in motion control and and physics simulations like there's a number of places where Kling's been outperforming there.
13:47
And then there's a number of other sort of niche applications where Kling's really great and uh and at 10 cents per second pricing has been very attractive relative to some of the other options in the market.
13:59
Although there are a bunch of ways to get like free credits and then if you buy bulk like none of the pricing's like exactly apples to apples.
14:06
But they've certainly they've certainly come out as a frontier quality model at a very affordable price and that's led to a bunch of adoption as we've seen with the 12 million monthly active users.
14:18
Interestingly Kuaishou claims that Kling is gross margin positive.
14:22
And so now it's unclear that doesn't include training and we don't really I mean it's gross profit so it doesn't include the hundred or so R&D people on the team.
14:35
But my my question is like what happens if they try and scale another order of magnitude?
14:42
Will they be paying more for inference?
14:44
Will they be able to get those chips because there's still this big debate over how many Nvidia GPUs should be able to be sent over to China.
14:52
So there's a little bit of debate there.
14:54
Um and it's also just it it it honestly gets me excited about MSL dropping a video model because a lot of the same a lot of the same sort of like precursor elements in terms of like the training data in the ecosystem when you think about the just the raw data in reels that it wind it could wind up being a model that's a little bit more opinionated maybe it has some mid-journey sprinkled in there.
15:18
Like I think that the MSL the pressure on MSL has been intense and the initial vibe's launch was not loved but they certainly have the compute they have the team now they have the data.
15:31
Like they have all the key the key ingredients to a really successful video generation model launch.
15:37
The only question is when will it happen and will it be one of those like temporary leap frogs where it's better than Sora and VEO-3 for a month until the other labs update?
15:50
Will it have its own characteristics because VEO-3 when it came out it was like oh we can do audio in there then Sora was really good at vertical video and a lot of these like labs it feels like if you're in video there's more room to be opinionated and come out with something where it's like we're really
16:07
good at making content that's all one all one scene or we our model by default will do cuts and cut from different shots to another or it's really good at front facing videos or or you know it gets the faces really accurate or it does or does you know face replacement. You can upload You can upload your own.
16:24
There's always like features that you can win on I think nowadays.
16:28
Since all the all the different base video models are starting to look pretty photo realistic.
16:34
So a lot of it's about Yeah I mean I'm so I can't wait to see Meta's next real launch here right?
16:40
They have so many advantages they have the talent now.
16:43
The pressure is immense but they should be able to come out with something that's super competitive. Yeah.
16:51
Turbo puffer search every byte service backed in full text search built from first principles and object storage fast 10x cheaper and extremely scalable.
16:59
So last month they did 20 million and of course Kuaishou put out a statement about it. Their shares went 3.
17:04
6% higher to rank among the top gainers on the Hong Kong exchange.
17:11
Year to year to date Kuaishou's up 23% so they've been on a run and there's a lot of investor optimism about Kuaishou's potential to monetize AI.
17:19
The company's AI-powered video and graphics generation capabilities will likely drive earnings over the next few years S&P Global Ratings analysts wrote in a recent note.
17:29
That could lower content creation and advertising costs and boost content creation on Kuaishou short-form video platform.
17:36
The company has the second largest independent short-form video platform after ByteDance's Douyin which is basically the Chinese version of TikTok.
17:44
And so I you know is this going to be you know super important to the AI race in America? Probably not.
17:52
Like we're still living in a world where you have OpenAI Anthropic Google really be really battling it out and then stuff but they the the Chinese labs haven't been putting a ton of pressure.
18:10
But I think it's interesting because we're actually getting firm data on how these products are monetizing.
18:15
Of course Google they're not even breaking out Gemini revenue or metrics.
18:19
They'll they'll throw out sort of random numbers but it's not like YouTube where they have to report out specific things or like Amazon with AWS where they have to break out those financials.
18:29
Kuaishou's kind of doing a service to the public markets at least they're creating a comp for what what revenue looks like relative to MAUs.
18:43
And I mean right now if they're doing 20 million in revenue 12 on 12 million monthly active users they're getting what a dollar 80 per per monthly active user a dollar 80 a month basically like a $20 a year subscription.
18:59
That still feels a little low but not bad for total ARPU for such a new for such a new service that really we don't know the mix of like enterprise versus prosumer where they Well yeah they're not breaking out where their users are right?
19:14
So so Kling is available on AWS.
19:17
Like you can go and provision it in America.
19:19
And so we're not exactly sure and I think some of that inference might run in America in that case.
19:26
So not exactly sure where their where their where their biggest customers are.
19:32
But it's just interesting to see like you're not going to get this level of detail from Google because DeepMind's its own thing and then Gemini's in there and then you can't even just subscribe to just VEO-3.
19:43
You have to subscribe to Gemini Ultra and then you get VEO-3 credits and so even Google like I mean, I'm sure Google knows how much like I pay for Gemini Ultra.
19:58
And then, they know how many deep research reports I file, how many normal prompts I use, how many times I just talk to it, and they know my my usage pattern relative to how many VO3 generations I'm doing per month for my, you know, $250, whatever I pay. Yeah. Anyway, moving on.
20:14
Vanta, automate compliance and security.
20:17
Vanta is the leading AI trust management platform.
20:23
Um there is another interesting just sort of like nuanced narrative that I hadn't really noticed while I was digging into Kuaishou.
20:31
One is this China's aging tech workers issue, the curse of 35.
20:41
They're firing uncs over there. That's what's happening.
20:43
They're firing You can't even be an unc.
20:44
You can't even be an unc. You you truly can't. You truly can't.
20:48
Discrimination against older employees particularly apparent in sector where executives openly state a preference for youth.
20:57
Different different approach.
20:59
>> We've had back and forth on, you know, in VC Twitter about, oh, should your team be really young and cracked or should you get the experts in there?
21:07
What's, you know, obviously in America you cannot discriminate based on age.
21:12
But that hasn't stopped plenty of people from opining about what the correct mix is, whether or not you should follow those rules.
21:21
But there's an article in the in the Financial Times that sort of has some charts here about Uh how big tech groups in China have been downsizing in the past few years.
21:28
We can go through that, but let's read through a little bit of this China's aging tech workforce.
21:35
>> hint Lau Bai, 34, received that his position at short video app Kuaishou might be at risk is when a 35-year-old colleague was sacked.
21:42
"I was both shocked and anxious.
21:44
I realized that our situations were very similar and the same thing could soon happen to me," said Lau Bai, Lau Bai using his nickname to avoid repercussions from his former employer.
21:54
Just months from his 35th birthday, the developer was dismissed, another victim of the group's reorganization known internally as Limestone.
22:02
Wow, they're giving code names to age discrimination. That's insane.
22:07
Kuaishou is pushing out junior work junior workers in their mid-30s.
22:13
According to five people with direct knowledge of Limestone, including current and former employees.
22:17
Lau Bai was told his termination was part of the company's overall redundancy program.
22:22
The so-called curse of 35 has long plagued workers across white-collar professions with older staff widely perceived as being less willing to put up with long working hours because of responsibilities at home.
22:30
As China's tech sector reels from Beijing's crackdown, this this article is from 2024, by the way.
22:39
And economic slowdown, tens of thousands of jobs have been cut over the past several months, and older workers have are seen as particularly vulnerable.
22:47
Technology companies have made no secret of favoring young and unmarried workers.
22:51
Ageism in the tech sector is a big problem.
22:53
There's a perception that older workers don't keep up with the latest technological developments, they don't have the energy to keep up the hard work, and that they're too expensive.
23:02
Thankfully, our very own John Coogan, who is you're you're very much keeping up with the latest technological developments, otherwise we wouldn't be talking about this.
23:13
Because you didn't just read about Kling, you studied and you wrote about it. >> Yes.
23:17
Um While China's labor law prohibits employers from discriminating on the grounds of attributes such as ethnicity, gender, and religion, it does not explicitly refer to age. Whoa. Hence Project Limestone.
23:29
But Yang said some had interpreted the law more broadly as prohibiting discrimination against older people, meaning employers would not explicitly cite age as a reason for dismissal.
23:41
Chinese tech executives have long publicly voiced their preference for younger workers.
23:44
In 2019, Tencent president Martin Lau announced a plan to reshuffle 10% of the company's managers, saying their jobs will be taken up by younger people, new colleagues who may be more passionate.
23:56
Uh Baidu CEO Robin Li in an internal letter, also made public in 2019, announced the company's plan to become more youthful by promoting more workers born after 1980 and 1990.
24:07
Uh this thinking is deeply embedded across most tech companies.
24:09
Well, let me tell you about Labelbox, reinforcement learning environments, voice robotics, evals, and expert human data.
24:18
Labelbox is the data factory behind the world's leading AI teams. That's right.
24:22
Between 20 and 30, most people are full of energy, you're more willing to march forward and sacrifice yourself for the company.
24:28
But once you become a parent, your body starts aging.
24:32
How are you going to keep up with the 996 schedule, says a former sales manager at Meituan, referring to the Chinese tech sector's infamous work routine of 9:00 a. m. to 9:00 p. m. 6 days a week.
24:43
ByteDance, which owns the video app TikTok and e-commerce giant Pinduoduo, have some of the youngest recruits among Chinese tech companies, data suggests.
24:51
The average age of their workers is just 27, according to the latest figures.
24:56
The average age of staff at Kuaishou is 28 against the 33 years old at ride-hailing app Didi.
25:02
Um The average age of the worker in China is 80 is 38, according to the All-China Federation of Trade Unions.
25:09
This trend has become only more entrenched with progressive waves of layoffs.
25:13
And this is the chart that I wanted to show you.
25:15
So, big tech groups in China have been downsizing in the past few years.
25:18
So, this is 2021, 2022, and 2023 for Alibaba, Baidu, Kuaishou, and Tencent, and they're all downsizing across those three years.
25:33
Now, I was wondering if this was just an anomaly post-COVID, just one particular period during some economic gyrations.
25:40
So, I went and pulled more recent data on what's going on, and it feels like they're all continuing to shrink.
25:49
The one that's that's growing again is Tencent, but Baidu has significantly downsized.
25:56
Alibaba has continued to downsize and shrink, and I think Kuaishou has as well.
26:00
And so, there's an interesting dynamic there that I didn't I mean, we we hear about layoffs in big tech in America, but it feels like it's like a very temporary layoff and and shrinkage, and then it starts growing again pretty quickly as they do more acquisitions.
26:13
Now, to be clear, some of these some of these companies have shrunk because they've divested whole business units or sold off a piece of a company.
26:22
And so, you can't really count that because it's like the the two the jobs still exist, they're just at a separate company. Anyway, Yeah, yeah.
26:28
Lambda is the super intelligence cloud, building AI supercomputers for training and inference at scale from one GPU to hundreds of thousands.
26:35
We have our first guest >> we jump in, it's worth noting I pulled up MAG 7 employee counts, and every single company in the MAG 7 has increased head count over that same period that we just showed. Yeah. Yeah.
26:49
There have been like periods of layoffs, but even when even when Mark Zuckerberg comes out and says, "Hey, we're laying off a thousand people in the metaverse team and the reality labs team," it's like, well, he's adding tons of people to the AI teams and tons of people to the Instagram teams and Threads teams and Facebook core and marketing and sales people and finance people.
27:07
Like, the whole organization is just growing so fast that one niche like layoff is not really going to cause a multi-year trend.
27:15
At least in America, we're still growing.
27:16
So, just sort of interesting that that I I didn't realize that was going on, that there was such a concerted effort across four major Chinese tech companies to really reduce head count, but it is happening.
27:26
Yeah, it is worth noting though that that in the chat is sharing this as well, that 2022 head count and current head count look very very similar.
27:36
So, there hasn't been a ton of growth. Yeah.
27:39
Um Anyway, Anyways, without >> Graphite, code review for the age of AI.
27:43
Graphite helps teams on GitHub ship higher quality software faster.
27:45
And without further ado, we'll bring in our first guest of the show, Rich.
27:49
Welcome to the TVPN Ultra Show. How are you doing, Rich? Great to have you back. Busy week.
27:57
Busy week in media world. Earnings kicking off. Yes. >> Earnings. What's top of mind?
28:01
What's What what's keeping you the busiest?
28:06
Look, I think everyone's trying to figure out what is the future of Netflix, what happens to Warner Brothers, does Paramount come back?
28:12
I mean, we talked about this on your show a few weeks ago, right?
28:16
We were talking about sort of this battle. Yeah.
28:18
Does Paramount come back?
28:20
You know, they haven't raised their bid since we talked, you know, before the holidays.
28:26
They have not raised their bid as of yet.
28:28
But they did say it wasn't their They said it wasn't their best and final. Right? That is true.
28:36
Um but, you know, the when you look at sort of the how much Netflix clearly wants this.
28:39
You know, Netflix yesterday went to all cash on their offer.
28:45
The Warner Brothers board came out and talked about the piece that Netflix isn't buying, which Paramount said was worthless.
28:51
The Warner Brothers board said was worth, you know, $3, maybe even more, as much as four or five, maybe even more if it gets sold into pieces, which we think is possible.
28:59
And so, the bar, you know, in terms of like, what does Paramount have to do to win?
29:03
That bar is going up and up and up.
29:05
And I think that's the challenge right now is how badly do they want this?
29:10
Do they want to over-lever the company to get this?
29:15
Or is there a better use of capital?
29:17
I mean, it's not like there aren't other assets out there.
29:18
I mean, you could go into the video game world, right?
29:22
Like, there's assets like Take-Two.
29:23
Two of the biggest Actually, the two biggest entertainment franchises in the world >> Okay, but what's actually what's actually important for Paramount?
29:29
Is it to build a compelling consumer subscription, right?
29:35
Like like cuz cuz when you look at them overpaying for UFC, or maybe maybe they're not overpaying, but if they if they >> this Saturday.
29:44
Yeah, which which I'm I'm excited for, but uh uh they they pay 700 million or certain No, was it it was it was more than that. What what was it? Am I wrong?
29:56
>> the billion one on UFC. Yeah, billion.
29:58
Um About 2x what it was what ESPN was paying.
30:01
Yeah, and and and I guess like my my question is um how after they if they don't get the Warner Brothers assets.
30:12
Just and I and I and I mean that from like how compelling is their is their subscription platform?
30:19
Without without >> Warner Brothers >> those assets.
30:22
Look, you can license a lot of content.
30:24
I mean, Netflix despite trying to buy Warner Brothers, Netflix actually just went out and did a global licensing deal with Sony.
30:30
So, after Sony movies are in movie theaters, the next place they go is to Netflix all around the world.
30:36
That's a deal that Paramount could have done.
30:39
They could have outbid Netflix for that deal.
30:40
Those licensing deals are out there.
30:43
I mean, Universal uh movies are actually going to now be after they do a short stint on Peacock, they're going to show up on Netflix.
30:51
Like, if you want to license catalog content, there is lots of ways to do it.
30:56
I mean, heck, Amazon Like like like the craziest thing that's happened this week, honestly, Amazon, you probably remember a few years ago, they went out and they spent $8 billion on MGM.
31:05
Everyone thought that was absolutely insane.
31:06
Then they had to go back because you actually even for that $8 billion, you didn't control the James Bond franchise.
31:11
They ended up paying the the the Broccoli family another billion dollars to get access to control the James Bond franchise.
31:18
And then what happened today, guys?
31:20
Today, the entire James Bond franchise is licensed to Netflix. >> Netflix.
31:27
Like, literally, you can go watch Dr.
31:29
No on Netflix right now instead of watching this show. Like, it's crazy, right?
31:34
So, there is lots of content to license, but you have to be aggressive.
31:39
And so, I think, you know, again, if Paramount has, you know, Larry Ellison's willing to put $12 billion into the Warner Brothers deal, the Middle East is willing to give them $24 billion to invest in this transaction, that's a heck of a lot of capital.
31:51
If you want to start really both creating a lot more content internally and licensing a lot more, Paramount has the ability to do that.
32:00
There is more NFL rights coming up for bid soon.
32:02
Like, there are many ways to attack this beyond buying Warner Brothers.
32:07
And I and I just think there comes a point where overpaying for something gets silly and you're better off finding an alternative.
32:16
And I think that's sort of the the question mark cuz remember, for for for Paramount, they need to buy all of these linear cable networks because unlike Netflix, remember, Netflix generates $11 billion of free cash flow a year.
32:29
Paramount has negative free cash flow.
32:34
So, like, the ability to bid here is very different.
32:36
These are very different companies.
32:40
So, what's Netflix's rationale for buying versus uh versus licensing?
32:47
Uh is that just thinking long-term that they're that they'll make more money over the long-term or is there some other other rationale or value that they would get from owning the whole thing as opposed to just licensing it?
32:58
John, it's a great question cuz I think if you step back and and they even said this.
33:02
I asked this question like, you know, what changed because Netflix had not been interested in making acquisitions.
33:09
They were a builder, not a buyer, you know, throughout their entire history.
33:14
And I don't if if if Paramount hadn't put this in play and like this asset hadn't become sort of in play, I don't think we'd be sitting here talking about Netflix buying Warner Brothers.
33:23
I think it once it became clear this asset was going to trade and if there was a way to buy it without getting all of those sort of dying cable networks, that there was a way to just buy the streaming business and the most importantly, the studio cuz what this is really about.
33:38
This is like when Bob Iger at Disney, remember years ago, he bought Pixar, he bought Marvel, he bought Lucasfilm.
33:45
Those three iconic acquisitions of IP have totally transformed the Walt Disney Company.
33:49
I think that's what Netflix sees here is, "Hey, these IP libraries are going to trade.
33:55
This is a once-in-a-lifetime opportunity.
33:58
Someone's going to own them. Let it be us.
34:00
Like, let's not let this get away from us because we can do so Just like Amazon for Bond needs Netflix, the ability to take all of that Warner Brothers catalog and shine a light on it the way Netflix can, I think it just too big of a you know, talk about a 5-10 year opportunity was too big to pass up.
34:19
big to pass up. How how do you think the studios and the platforms are kind of trying to process the how gen AI will impact the value of IP because if I I look at this and I'm like, if you have IP and the cost to produce new content drops dramatically, which I think is my my assumption generally is that you're
34:37
going to be able to produce like when you look at animated content and even like kind of blockbuster films, I expect the uh I expect the cost to produce these things is going to drop dramatically, which means if you actually have a monopoly on the IP, you can create a lot more different content uh around it. And I think that uh gen AI
34:53
And I think that uh gen AI will also mean that there's just a bunch of like more and more and more and more content like net new content, net new IP being created, but it's unclear if you have uh it will maybe even become harder to like generate real breakout hits if the whole zone is just being flooded with a ton of content.
35:15
Well, look, in a world where I First of all, let me just step back. I agree with you.
35:20
Gen AI is going to lead to an explosion of content.
35:22
There you know, I don't think this is just video content.
35:25
I think it's an explosion of content.
35:27
So, whether it's gaming content, you think about a UGC platform like Roblox, you think about a short-form you know, a shorter-form you know, UGC world of video like YouTube, you think about Spotify, like all of the platforms in in a world where content creation gets cheaper, the platforms win.
35:44
That is exactly part of the long-term investment thesis on why own Netflix now.
35:51
Yes, it will get easier to make content from the Warner Brothers library.
35:54
It'll get cheaper for Netflix.
35:56
I mean, certainly animated content which takes 3 to 4 years to make.
35:59
I mean, look, I you know, one of our questions for Netflix on their earnings call was like, "How big of a miss is it that K-pop Demon Hunters 2 isn't coming out until 2029?"
36:10
Like, that's embarrassing, guys, like right?
36:11
Like, it shouldn't take 4 years to get that sequel out, but that's because of the timeline for animation.
36:17
That's going to compress dramatically.
36:20
>> Is that everything because I thought that there was also uh sort of just an unpredictable It was an unpredictable success.
36:26
They hadn't negotiated the contract with Sony.
36:28
And so, they they they kind of got caught flat-footed when it became such a success.
36:32
And again, it was like it was a success that only would have happened on Netflix where a movie can go viral where if that had some limited run in theaters, it probably would have just been forgotten.
36:45
It's true, but they struck the deal at the end of '25 and you're not getting a movie till '29. Yeah.
36:50
>> That is just the timeline.
36:50
Like, Sony Pictures Animation, which is up in Canada, it there's a backlog of films that are before this and there's just no way to accelerate that at the moment.
36:58
But but I think I want to go back to Jordy's point. >> Yeah, yeah.
37:03
Making it cheaper to make content does mean the value of existing content probably comes under pressure.
37:08
Like, there is no doubt that since you're going to have so much more content created, existing content will have less value.
37:15
I think that's a negative for Netflix, it's a negative for Disney, but the platform side of the equation, which is what Netflix is known for, just like YouTube and Spotify and Roblox, I think all of those platforms become huge beneficiaries because people are going to have so much more content on those platforms than they do today.
37:33
So, I think it ultimately becomes an advantage.
37:37
Hurts one side of the business, but I think as you look at it holistically, becomes a big long-term advantage cuz the platform big platforms have the eyeballs.
37:46
Like, that's where people turn to, right?
37:48
Like, you come home from work and you turn on Netflix, you turn on YouTube.
37:52
Like, those are the fundamental winning platforms and they're battling it out.
37:58
And I think AI makes that battle even both of those companies even more powerful.
38:03
And so, the the sounds like if I if I could summarize the place that you're getting to is is maybe not believing that Paramount and the Ellisons should just lever up to this insane degree when they could potentially take some more, you know, take uh maybe still tens of billions of dollars, but just allocate it across a wider variety of deals.
38:24
Is that is that is that one path that you're seeing?
38:29
I I think this is they're stretching. Right?
38:31
Like, when they tried to buy this thing at 19 and there were no other bidders, it was a brilliant idea.
38:34
Maybe even at 23 it was a brilliant idea.
38:39
As you start getting to you start to realize that like you're not winning at 30.
38:42
That's pretty I would assume to both of you and me.
38:44
Like, they're not winning at 30. Yeah. Right?
38:46
Like, so they're going to have to bump and they're going to have to bump meaningfully.
38:49
And so, to pay 34 or 35 dollars, like you start to get to valuation levels.
38:54
I don't think you can put any more debt on this.
38:56
And so, you got to come up with 10, 12, 14 billion dollars more equity.
39:00
Like, and even that is too levered.
39:03
Like, I wouldn't want I would not want to be in this transformative AI media world sitting there with seven times leverage.
39:13
That is not a great place to be in.
39:13
So, I truly believe David Ellison has a huge opportunity over the next decade, but I don't think over-levering to buy Warner Brothers is the best path forward.
39:21
Also also we it's worth noting that state Oracle uh at the beginning of Q4 was trading at uh $313 a share.
39:31
It's now trading at $174 a share. Wow.
39:37
>> And so, that has to be a factor, too, in terms of everyone's confidence around like hey, how much how much can >> cash does he do you have available? Yeah.
39:47
Look, Larry's got plenty of capital.
39:48
If you wanted to buy this for all cash, he could. But remember, he's not.
39:52
This is a $100 billion transaction.
39:56
The Ellison family's putting in 12. Yeah.
39:58
You know, so like there is a limit on how much I think the Ellison family they put in, you know, $8 billion or sorry, they put in six of the eight billion of cash into the Paramount transaction.
40:10
RedBird put in the other two.
40:10
So 6 + 12, that's an $18 billion commitment between the two deals.
40:16
It's a big number, but on the flip side, you know, given the size of this transaction, you know, I think there is a limit to how much they probably want to invest in this sector.
40:28
And again, I just think leverage is not your friend.
40:31
Like I look at sort of how you win over the long term in this media space, especially given how much change and I think you two do a great job highlighting sort of how technology is changing what's happening.
40:43
Being levered is the last thing you want.
40:45
And I think what was really interesting is that when Skydance bought Paramount, they injected cash onto Paramount's balance sheet to delever it because they didn't want to be levered.
40:56
And so I think even they understood that they don't want to be levered.
41:00
They're being forced to lever to try to compete against Netflix.
41:03
And I think that's actually the mistake.
41:05
And I just think that there's other ways for them to win long term.
41:09
Overstretching the balance sheet does not to me seem like the right path.
41:17
Explain the cable assets that are sitting within Warner Brothers Discovery. You have CNN, I believe. There's a few others.
41:25
>> when some of the numbers are floating out, CNN doing something like projecting 600 million of of even uh on like Yeah, it seemed like a good business.
41:34
My question is you have this Netflix fight over the Warner Brothers like that that the studio, the IP library.
41:41
And to Netflix, it feels like the TV assets are less valuable.
41:47
Certainly they were carved out of the initial offer.
41:51
If are those more important to Paramount Skydance, the Ellison family?
41:53
Is there a world where Netflix takes Warner Brothers the studio and the cable assets go to Paramount?
42:03
Um they're critically important to Paramount because Paramount, as I said, doesn't generate free cash flow.
42:07
You know, doesn't have the earnings capacity of Netflix.
42:11
And so in order to finance this, to lever this up seven times, you need all of that cash flow.
42:16
If they were only buying what Netflix was buying, John, this would be levered over nine times.
42:21
And so you have to have those assets if if you're going to finance it the way they're doing it Okay.
42:26
and not do this as a cash deal.
42:29
In order to do debt, they need those assets.
42:31
This becomes really important assets.
42:33
And so for Paramount, they have to stop the split of this company, which is supposed to happen this summer.
42:37
If Warner Brothers splits, Paramount can't do this deal because they can't finance it the way they currently are financing it.
42:45
The the reality is these assets like CNN, do I think public market investors will like these assets?
42:51
No, I don't think so at all.
42:53
I don't think these are growth businesses.
42:54
I don't think investors are going to be excited at all.
42:57
But I do think that there are strategic buyers of these assets where there is the influence and power of owning a news network that will far outweigh its public market trading value.
43:12
And I think that's really the opportunity.
43:14
If you if you put this up for sale, someone's going to come in and buy CNN because it actually has important, you know, strategic value.
43:23
You think about like a Nexstar, which is trying to build their own, you know, news network, trying to build out, make, you know, they're in the process of making a major acquisition of Tegna.
43:33
Like there is certainly an opportunity where I think you'll see multiple buyers come out of the woodwork, maybe even billionaires who want or, you know, hundreds of billionaires who see this as a way to influence.
43:44
You can cuz remember, you could change the direction of CNN from the perception of liberal.
43:50
You could move it more center right if you wanted to.
43:52
And so I think there's a lot of people that would look to buy CNN if it was available.
43:58
What about uh is there any political saving grace for the Ellisons?
44:03
Is there any chance that uh it uh the Netflix deal gets blocked? Is that the angle?
44:11
Like if they're not increasing their offer, I'm sure they're back channeling trying to get it killed.
44:18
That would be my assumption.
44:19
>> are, but but you guys are the It's funny.
44:23
Doing what we're doing right now Yeah.
44:26
is the single greatest reason the deal should be approved. >> Yeah.
44:28
And I mean that sincerely.
44:28
Like look at what we're doing. Yeah.
44:30
We are sitting on the internet >> Yep.
44:34
on on X broadcasting live. >> Yep.
44:38
No cable subscription required, but you are absolutely competing against CNN Sure.
44:44
and like there is no doubt in my mind that what you're doing is a real comparable, you know, a true competitor to linear television.
44:53
So trying to tell me that you have to define, you know, streaming TV, subscription TV, let alone free streaming TV like YouTube and X, that we're going to put up artificial barriers and say this is somehow different than watching NBC or CNN or Fox News.
45:11
Like Look, you can make the argument.
45:13
Will it hold up in court? Yeah.
45:16
I would love to see how a judge is going to isolate those categories. >> Yeah. Yeah.
45:22
Uh you mentioned Take-Two Interactive.
45:24
It's a $44 billion company.
45:29
GTA 6 is coming at some point.
45:32
How does that make any sense for either Netflix or Paramount to own?
45:34
It feels like for both of them it would be a massive just different business line to enter.
45:44
Obviously like in the attention economy, they do compete.
45:46
If you're playing GTA 6, you're not watching CNN, but they just feel like fundamentally very different businesses to me.
45:53
Is there some synergy that I'm missing?
45:58
Well, I'd say for Paramount specifically, I mean Skydance Skydance Games is a a real focus.
46:02
I mean Ellison, you know, I think if there's anyone in the traditional or legacy media world that bridges Northern California and Southern California, it would be David Ellison.
46:15
You know, he grew up friends, not just obviously his dad is Larry Ellison at Oracle, but he grew up friends with Steve Jobs, right?
46:21
And like so if you sort of look at sort of his understanding of technology, you have to believe that he understands the importance and power of gaming.
46:29
It's why Skydance Games has such big ambitions.
46:34
And so, you know, I look at sort of the power of that GTA franchise and Red Dead.
46:40
And like you look at sort of like the future and you go, sure, it'd be great to make more movies and it'd be great to have a bigger studio with Warner Brothers, but there's many ways to win in entertainment.
46:49
And I think video gaming is a huge category.
46:51
And while I don't think Take-Two and Strauss is looking to sell anytime soon, look, it would be a much smaller transaction relative to Warner Brothers and you would get some incredible IP and you would shift away rather than owning more TV and more sort of legacy studio, you would shift the focus of the company in an entirely different direction, which I think could be really exciting. Yeah. Yeah.
47:15
Why did Jared Kushner pull out of the deal?
47:22
You would have to ask Jared Kushner.
47:22
I have absolutely no idea.
47:24
But I mean I'm I'm I'm suspecting that just politically it didn't look great.
47:30
I mean it might have been one thing when this was a friendly, you know, straightforward acquisition.
47:36
But when you were getting into a competitive bidding situation and it was sort of being looked at as sort of hey, this is the, you know, this is someone tied to the president that's influencing it.
47:46
It might have just been this did not look like he thought it was going to look.
47:50
But again, I I honestly don't know.
47:51
I've never I've never met him. Mhm. Yeah. That makes sense.
47:53
Uh how how are how are different video generation AI models uh are any of these factors showing up in uh earnings and financial reports and conference calls?
48:07
Like how are management teams messaging around generative AI?
48:12
Is it just a growth opportunity or is it actually becoming something that moves the needle either on the cost side or the revenue side for anyone?
48:21
I would really keep your eyes on Amazon.
48:23
I think they're the first mover here and really trying to make a dent here.
48:25
And it's not to make less content, you know, or sorry, to make content cheaper and spend less.
48:31
Amazon's literally looking at this as can we actually use AI to bring the cost down 20, 30% and then make more content for the same budget.
48:42
And so they the sort of speaks to what you guys were sort of hinting at before.
48:46
This is a way to increase the total amount of content.
48:48
And obviously more content means more engagement.
48:50
And so I really think Amazon's taking a lead here.
48:54
Netflix has their own AI playbook.
48:57
I think you're going to start to see it up from Netflix.
48:58
And of course, the other company that's talked about it, we haven't seen anything, but the other company that's most vocal about it would obviously be Paramount where Ellison certainly believes in the power of technology to change the cost structure of this business. What about Disney?
49:14
Disney did the big deal with OpenAI.
49:16
>> Yeah, I wanted to ask if you're hearing about other IP holders rushing to try to do uh like when we saw that deal happen, I was like, wow, this having like a one-year, maybe more exclusive on all the Disney IP, I feel like could be pretty significant.
49:32
Once it's live, it's going to be incredibly viral.
49:33
Parents are going to >> Jordyn, what's the last time you used Sora?
49:37
Uh I was never bullish on Sora specifically.
49:42
But that's that's the problem, right?
49:43
Like so it all of this is I don't know what >> I was going to say what I was going to say I was bullish on the on the Disney IP deal specifically because parents are going to be willing to pay to bring joy to their children by turning their life into Disney scenes.
50:04
Yeah or I mean do kids just love watching Bluey cuz they love Bluey?
50:07
Like I don't Do you want to watch yourself in a you know, I guess for the creative parent that can actually tell an interesting story.
50:17
I mean I get the gimmick.
50:18
Like I remember when Sora first came out. We all did it, right?
50:22
Like we were all trading these around, sending around.
50:23
I remember I was in a Knicks jersey before they put the copyright controls in.
50:26
I was in a Knicks jersey on the court dunking.
50:28
Like it was I was catching the game-winning pass in the you know for the Giants.
50:32
Like And and I don't I think I think you're a little I think you're a little bit jaded.
50:36
I mean Disney has a whole business of just like have lunch with a character, right?
50:40
Parents are spending I mean it goes back to you're at Disneyland.
50:43
You're the kid puts their face through the car through the cardboard cut out and they appear to be Superman.
50:49
>> and the the only anecdotally when when I first took an image of my son and I turned it I turned the two of us into dinosaurs he has never forgotten that moment and he'll bring it up all the time.
51:01
Turn us into Turn us into dinosaurs and I'm really like we're not using AI right now.
51:07
We're going to go We're going to go to the beach.
51:10
It look I think it all depends on how sort of how preconceived it is.
51:14
Like do do Is it just turning it in and you have to go figure out how to make something interesting and compelling or is it sort of already pre-engineered and preset where you stick in your faces and the scene comes to life?
51:27
Like I think it it's got to not be a lot of work cuz I think you know people don't I think I will say I am not a terribly creative from like a writing stories.
51:37
Like you know people need to be taught how to do it.
51:41
I think that initial how to prompt, how to make it good is not easy.
51:43
And so it'll be interesting to see how easy they make it for parents to make this really a great experience.
51:50
So I like the idea and I look I give Disney credit.
51:54
You would not have expected Disney to be the one to jump out in front on AI given how much they're focused on sort of protecting their IP.
52:00
So I give them a lot of credit for trying.
52:02
I I think the key is Sora needs to become something that really becomes less of a gimmick and more where you actually want to sit down and actually like watch the content cuz I still feel like it right now it feels very gimmicky. Yeah.
52:15
Yeah I I do I wonder I wonder what OpenAI is getting out of it, right?
52:20
Disney has 150 million people visit the parks annually.
52:23
If they're if in the line there's like a QR code that's like turn yourself into such and such character I think like right now OpenAI has a challenge which is that free LLMs are pretty great. Right?
52:40
And and they have this gap. Free is great.
52:43
Yeah they have this real gap between turning on commerce and turning on ads and really unlocking that from a revenue standpoint.
52:50
And I think if they can and making these sort of like magical products that are unique to OpenAI that you're not going to be able to get at at you know through Gemini or any of these other LLMs I think it I think it could buy them a little bit of time to to turn on some of the other monetization.
53:08
But uh again I think you're I think you're right on Sora.
53:10
Uh I wonder how they're doing.
53:14
See if they're still in the App Store top 25.
53:19
>> They've been in the top 100.
53:19
I think they're around 60-ish or something and I agree with you.
53:23
I haven't used the Sora app very often but I am seeing clearly content that has been generated with Sora distributed on Instagram.
53:30
And so there is a world where you know you create a prosumer tool that's subscription that people are paying for and then they're and then the really creative people are distributing that content elsewhere.
53:42
Uh they've already said that some of it will go on Disney Plus and so you could have someone who's a creative storyteller tell a story that takes place in Disney IP as the world that they're interacting with.
53:54
And then that does do well and it goes out and and maybe maybe it's not every single person using the Sora app to generate their own videos but that you're seeing content that was generated through that partnership and it's monetizing in a variety of ways. I don't know.
54:11
This all gets back to what we said before. Yeah.
54:12
There's going to be a heck of a lot more >> There's going to be more content for sure.
54:16
>> over the next 5 years. Yes.
54:16
There's going to be an exponential explosion Yes. of content. >> Yes.
54:21
And it's funny you mentioned Instagram.
54:22
Another example platforms. >> Yes. Platforms win. Totally. >> That is the key. Yep.
54:26
If you own and control a platform and the cost of creation comes down Yeah.
54:31
you're going to be a long-term winner.
54:33
And so that's why Spotify, why Netflix, why YouTube, why Roblox.
54:38
Like that's how we're positioned is picking platforms are going to be the big winners over the next 5 years.
54:44
>> maybe that means that Paramount Plus, Warner Brothers and HBO is more of a platform than separate and there is actually a creative value to putting those together and overpaying.
54:53
And so maybe there is some rhyme to the reason behind David Ellison's aggression here.
55:01
Building a platform, a daily use platform is really really hard. Yeah.
55:06
I'm not saying it's impossible but it is really hard.
55:08
>> and Looney Tunes and and Superman and Batman and you're on there as a kid you grow up and it's one of the key apps that you open next to Netflix, next to next to Disney Plus.
55:21
The funny thing is is what you're saying is it's it's all the reasons why Disney should be bidding on Warner Brothers studio as well. That That that one.
55:25
I feel like that one just aesthetically actually does trigger FTC just because Superman and Spider-Man can never cross paths.
55:36
Batman and Iron Man it's too similar. They're billionaires.
55:38
They're they're they're tech guys. It it doesn't work.
55:42
They got to be separate universes.
55:45
I'm just saying they should want a lot more content. >> They should. Oh 100%.
55:47
No I If if they could get it done.
55:50
And and and they could make the same argument that Disney Plus Plus uh Warner Brothers is no more powerful than than YouTube and Spotify and Instagram and and all the other platforms that are soaking up people's time including What are you What are you paying attention to this earning cycle?
56:10
I mean like I think the the the you know this is obviously the 2026 outlook for a lot of these companies and I think you know you're going to hear sort of like in a world where so much is changing so fast.
56:21
I mean we came out with our you know we do a quarterly earning scorecard where we sort of highlight phrases that are used and it'll be interesting to see while AI dipped in terms of mentions last quarter do we see even more companies talking about AI as we as we move through the year.
56:35
I think that's going to be really interesting to watch.
56:38
And is it in a positive or negative light and like who's being disrupted by or helped by I think it's going to be really interesting to watch.
56:43
And then of course just going back to where we started you know whether it's Netflix or Paramount someone's going to win Warner Brothers.
56:52
Well then the question is what does everyone else do because everybody else looks really small and so sort of seeing you know the reverberations of what happens because of all of this is going to be really important to listen as you move through earnings.
57:05
What do you think about some of the private movie studios?
57:09
Do you think those will get picked up? A24 uh did around at 3.
57:11
5 billion uh Thrive Capital mid 2024.
57:15
Uh certainly building a lot of IP.
57:20
They found an interesting mix of content.
57:22
I really like a lot of their films.
57:25
Uh do you think anyone will try and acquire some smaller studios?
57:31
Uh look the biggest problem is smaller studios don't move the needle which is why I think you know something like Lionsgate hasn't been bought but why Warner Brothers you're seeing this massive interest.
57:42
Um I don't know about the smaller studios.
57:43
I certainly think like as you look at something you know you look at Sony Pictures or Sony you know Sony you know pictures and TV.
57:49
Um there are assets out there that you know look like they are ripe for you know M&A whether it's sale or some form of combinations.
58:00
It does feel like you're going to see more combinations in the year ahead.
58:01
But again you can you can also just license their content which is what Netflix and many of the other streamers have done.
58:08
Well thank you so much for taking the time to come chat with us.
58:09
Always a good time to hang out. >> Great to hang.
58:11
Have a great rest of your week.
58:13
We'll talk to you soon Rich. Goodbye. Plaid.
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Back Back to the timeline.
58:30
The messy drama that dealt a blow to one of AI's hottest startups.
58:33
This is an exclusive in the Wall Street Journal.
58:37
After a relationship with a colleague a Thinking Machines co-founder had his role changed.
58:42
Months later he was fired after after a contentious uh meeting.
58:48
Megan Berbro ski has the story in the Wall Street Journal alongside uh Keach Hagey.
58:53
Um Mira Murati's meeting with her co-founder is going off the rails.
58:58
Murati the chief executive of AI startup Thinking Machines Lab had shown up for work on last week expecting to have a one-on-one with Barrett Zoph her chief technology officer according to people familiar with the matter.
59:12
Last summer she had learned that Zoph was in a relationship with a colleague.
59:16
In the months since she had expressed repeated concerns about his lack of productivity according to the people.
59:22
Uh she was invited instead to an impromptu meeting with Zoph, another co-founder and a third employee.
59:28
The three told her they agree they disagreed with the direction of the company and that they were considering leaving.
59:33
They asked Zof to be given charge of all technical decision-making, according to people.
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Murati responded that Zof was already CTO and asked why he hadn't been doing his job for months.
59:44
So, they're clearly beefing.
59:45
It's a very funny It's a funny request.
59:48
Like, what was he doing as CTO if he didn't have full control?
59:51
But, I mean, I mean, obviously CEO can override all sorts of stuff and there's other people around the table and, you know, titles only mean so much.
1:00:01
There's soft power all over the place.
1:00:03
So, two two days later, Zof was fired.
1:00:05
Within hours, all three had signed offers to rejoin OpenAI, the AI lab that they ditched a year ago to join Murati's fledgling startup.
1:00:13
The departures are a sign of how the heated AI race that is consuming hundreds of billions of dollars and transforming the economy is as much a battle for talent as technology.
1:00:23
For all the high-tech advancements AI startups are spring to develop, they are ultimately at the mercy of the humans' power.
1:00:30
>> So, do you think this was a 3-hour talent acquisition process?
1:00:35
Do you think OpenAI just just looked at checked the timeline and said, "Hey, we got three people that are on the market.
1:00:43
Maybe we should hire them."
1:00:44
It seemed like they were talking before.
1:00:46
They entered the portal and then they immediately got the job.
1:00:49
>> The trade portal, for sure.
1:00:49
That's exactly what happened.
1:00:51
>> No, I think I think very obvious that the conversations had been ongoing.
1:00:54
It's very likely I would assume they had already agreed to to terms.
1:01:00
>> Yeah, it seemed like it.
1:01:01
>> Prior yeah, to the news going out.
1:01:01
Well, let's continue, but first, vibe.
1:01:03
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1:01:11
So, Zof's firing and decision to rejoin OpenAI with colleagues also marks a pendulum swing for a company that Murati, the startup that for startup that Murati, that startup's former chief technol former technology chief had founded with 20 former OpenAI employees.
1:01:30
So, 20 people from OpenAI left during the Thinking Machines foundation.
1:01:37
Addressing Zof's departure to Thinking Machines employees, Murati said there had been multiple issues with his performance, trust, and conduct, according to an internal message viewed by the Wall Street Journal.
1:01:47
Zof said she fired him after he exposed an intent to take a job elsewhere.
1:01:52
Thinking Machines terminated my employment only after it learned I would be leaving the company. Full stop.
1:01:58
At no time did Thinking Machines lab cite me on any performance reasons or unethical >> And you're like, "No." >> You're fired.
1:02:08
I'm breaking up with you.
1:02:08
It does feel like a little bit of that going on.
1:02:09
But, there yeah, there's a war for narrative here between between Mira and Barrett, clearly.
1:02:16
They didn't So, he says Thinking Machines didn't cite any performance reasons or unethical conduct as part of the reason for the termination, and any suggestion otherwise is false and defamatory, Zof said in a statement to the Journal.
1:02:29
The exits, coupled with fellow co-founder Andrew Tulloch's decampment to Meta last fall, leave Thinking Machines with just three of its original six founders.
1:02:38
Murati spent six years at OpenAI, where she earned a reputation for emotional intelligence and lack of ego and was named interim CEO during the brief period when CEO Sam Altman was deposed.
1:02:48
She helped launch the its first product and ran almost every aspect of the company before starting Thinking Machines last February.
1:02:56
Many of the early researchers, including Zof, that she hired came from OpenAI's post-training team, the division that built ChatGPT and was tasked with teaching AI models how to communicate with humans.
1:03:08
Murati's issues with Zof started over the summer when she began to suspect he was having a relationship with a colleague who with whom he had lobbied to bring over from OpenAI, according to people familiar with the situation.
1:03:17
In responses to questions from the Journal, Zof said that many people at Thinking Machines wanted to hire the woman, including Murati.
1:03:24
At the time, Murati was in the process of raising one of the largest seed rounds in Silicon Valley history.
1:03:30
The company ultimately raised $2 billion at a $12 billion valuation when she confronted Zof about the possibility of an undisclosed relationship with a female employee.
1:03:39
Um who was junior to him at the company, but did not report to him.
1:03:42
He initially denied it, according to people familiar with the situation.
1:03:46
By June, however, both Zof and the woman had told Murati about the relationship, which had begun when they were colleagues at OpenAI, people with knowledge of those discussions said.
1:03:55
The woman then left the company and returned to OpenAI.
1:03:59
There's sort of a wrinkle in this.
1:03:59
Uh Zof told his boss that he had been manipulated by the woman into a relationship, according to people familiar with the matter.
1:04:07
Shortly after that conversation, he took a break from work.
1:04:10
Okay, I got to I I gen generally uh think that the >> Mira, she told me it was cuffing season.
1:04:19
I didn't know what it meant, so I just said, "Okay." I got cuffed. Is that what happened?
1:04:23
Yeah, I mean, I I think just saying like I I was manipulated into becoming the significant other, you know, you got to take a little responsibility.
1:04:33
>> everyone is assuming that this is a romantic relationship.
1:04:35
They never reported that this is a romantic relationship.
1:04:39
They just said that he had a relationship with someone else and it was undisclosed.
1:04:42
And I think that more companies need to be clear about the rules around disclosures of relationships.
1:04:47
Like, if you and Tyler start an esports team, for example.
1:04:53
Like, you would have a relationship.
1:04:53
You would be teammates on playing Call of Duty.
1:04:56
And if you didn't disclose that to me, I would be I would feel left out.
1:05:00
I'd be like, "Why don't I Why am I not on the team?"
1:05:03
If if I find out that that Tyler and Scott are going off and and drinking a bunch of athletic beers athletic brews every night, you know, without me, that's a relationship. They're bros. And it wasn't disclosed.
1:05:17
>> wasn't disclosed, yeah.
1:05:18
>> be very angry that they didn't disclose >> So, I I I think the relationship disclosures need to go beyond romantic relationship disclosures.
1:05:27
If you're if you're just broing out and broing down with people, That actually is That actually is kind of a real thing.
1:05:32
Sometimes catching up Monday after the weekend, somebody's like, "Oh, yeah, I was hanging with so-and-so on Saturday."
1:05:37
Like, "Wait, >> my invite?"
1:05:38
You guys hang out on Saturday? What?
1:05:42
You didn't disclose that relationship. >> barbecue? Yeah.
1:05:44
Oh, so you have a relationship where you go to Korean barbecue together. Okay.
1:05:49
>> And you just didn't think to tell the rest of the company that. >> KBBQ. >> Yeah.
1:05:54
What what what what's your thoughts?
1:05:55
>> I I was going to say I think there's, you know, I I like to imagine there's some kind of like Shakespearean tragedy here, right?
1:06:00
Where it's like the the Montagues and the Capulets, that's OpenAI and Thinking Machines. >> Oh, yes.
1:06:04
>> And it's these forbidden lovers who can't be together. >> But, now they are.
1:06:08
They're you know, they're united because everyone is at OpenAI.
1:06:11
Even though, I mean, if you go to the Journal and you say, "I've been manipulated by that woman who's now my colleague," because they both work at OpenAI now, right? So, that's odd.
1:06:19
Wait, do we know that that the the woman went back >> the woman left the company, Thinking Machines, and returned to OpenAI.
1:06:26
So, so Barrett >> and the woman in this relationship, which might be romantic.
1:06:32
They might just be playing board games together or playing COD professionally together, who knows.
1:06:38
But, they had a but they were both at OpenAI.
1:06:40
They both went to Thinking Machines, and they both went back to OpenAI.
1:06:45
And so, they're the they're all in the Montague camp now or the Capulet camp. I don't know who's who.
1:06:49
I I I haven't studied enough to to assign roles.
1:06:51
Do you do you Have you read Shakespeare recently?
1:06:55
Well, at you know, at the end like they both die.
1:07:00
Is that what Is that They they both die and they get steamrolled by a neo lab?
1:07:04
Is that what happens in in Romeo and Juliet? I don't know.
1:07:07
>> Okay, one thing is like rewinding to November 13th, Yes.
1:07:11
Bloomberg reported Thinking Machines in funding talks at $50 billion valuation. >> Yeah.
1:07:19
So, That's a big step up from 12.
1:07:21
Yeah, the big question now is is did any any of the this financing talks actually convert into real investment?
1:07:29
And if not, I think that is very little chance that a round gets done in that territory anymore. >> Yeah.
1:07:36
Yeah, it is it is like certainly not the best thing to have hit the Journal if you're out on the fundraising track.
1:07:45
At the same time, these mega rounds, it just feels like they take a long time.
1:07:49
We've been hearing about the Anthropic round for a really long time.
1:07:50
We've also been hearing that the Anthropic round, even though it's been going on for, I don't know, 6 months or something, like it's going really well and everyone's excited.
1:07:58
And there was a whole bunch of FUD around the XAI round. Is it going to happen?
1:08:03
Have they hit benchmarks?
1:08:03
Is there Is there, you know, too much fear around all the different hallucinations and whatnot?
1:08:12
Are they seeing real traction? The round got done.
1:08:14
And so, I I this is not like it's not over because these rounds can just take a long time.
1:08:20
So, it's not like, "Oh, you need to have the round closed in 3 months."
1:08:23
Yeah, If you're raising it this long.
1:08:25
But, yeah, so so Mira's out there fundraising.
1:08:28
>> Yeah, but this is obviously Yeah, we're figuring a lot of stuff out.
1:08:30
You know, we have a lot of momentum.
1:08:32
We're really excited about what we're doing.
1:08:34
And then you have articles in the Journal that are saying your own co-founders disagree with the direction of the company. >> Yeah.
1:08:45
I think most investors are going to be like, "Hey, we should probably chat before we give you another $5 billion."
1:08:50
>> Mira's going to say they they only disagree because I fired them for having relationships. >> Yeah. Like, like, >> she said. We're solid.
1:08:56
Yeah, it is it is a he said, she said.
1:08:58
And it has Silicon Valley talking.
1:09:01
Over the next several months, thinking executives at Thinking Machines witnessed a drop-off in Zof's performance after he was cycled back to a new technical contributor role with reduced executive and managerial responsibilities.
1:09:15
They were tracking his performance.
1:09:17
They said his usage of Slack, the main arena where the company did its work, declined precipitously in the following months. He was locked in. I don't know.
1:09:26
I I don't see a problem with with if you go from a manager to an individual contributor, you don't need to be slacking as much.
1:09:32
You need to be locked in.
1:09:34
You need to be grinding, right? And right in prompts.
1:09:37
Um, In his responses, Zof said he worked as an individual contributor for 2 months and also worked on projects that included recruiting and retention of talent, road map planning, and the release of the company's model training product Tinker.
1:09:49
He said he was also out of the office for parts of November and December due to illness and a death in the family. Very tragic. That's very sad.
1:09:57
Um, in addition to the holidays.
1:09:59
So, he's like, "I'm not on Slack.
1:09:59
I'm I'm I I I was with my family on Christmas."
1:10:03
Um, in October, shortly after Tullock left for Meta, where he had previously worked, Zof reached out to Altman to talk about coming back to OpenAI.
1:10:12
By the time of their meeting Morat with their with Morati last week, Zof, co-founder Luke Metz, and third employee Sam Schonholz uh, had been unhappy with the direction of the company for months and had been holding talks with both OpenAI and Meta in recent weeks about joining either company as a trio, according to people familiar with the matter.
1:10:31
Interesting that Meta, amid the crazy buying spree that they've been on in the talent wars, did not jump in with something, you know, so much higher.
1:10:40
They already have Andrew Tullock.
1:10:41
They've already got one Thinking Machines co-founder.
1:10:42
They're basically acquiring the whole team piece by piece.
1:10:45
They're going to wind up paying more than the than the 12 billion price.
1:10:48
Yeah, and I I don't know.
1:10:48
I mean, it wasn't that long ago that people were speculating, "Okay, what it what is Thinking Machines worth in an in an acquihire scenario?"
1:10:55
And and based just on that type of analysis, it's worth a lot less today than it was >> Yeah, less talent. >> months ago.
1:11:03
I wonder I wonder what they mean when they say unhappy with the direction of the company.
1:11:07
Like, what do they what do they want?
1:11:09
Like, do are are they are they excited about the ads product at ChatGPT?
1:11:13
Are they excited about Sora?
1:11:15
Are they excited about OpenAI for health or for science research?
1:11:20
A particular technical direction? Just the GPU scaling? The the buildout?
1:11:25
Just the how rich OpenAI will be with the backing of Oracle and all that? Yeah, it's 1. 4 trillion.
1:11:30
Little bit nerve-racking if you're an investor, but if you're an AI scientist, you're like, "I'm going to have unlimited resources."
1:11:38
Uh, and so it could be that. I don't know.
1:11:39
I think I think the the big question is obviously what is what's Albania's move? Mhm.
1:11:43
Stand by Mira, ride with Mira. >> Yeah.
1:11:47
Potentially lead this round at 50, right?
1:11:50
Uh, >> Albania, the the government of Albania invested around 11 million dollars >> into Thinking Machines.
1:11:58
>> The uh, they could decide to take a bigger swing, though.
1:12:00
The GDP of Albania is somewhere around 30 30 billion USD. >> 30 billion.
1:12:06
Um, and uh, anyways, they might you know, take a Trump Intel kind of dynamic and say, "You know, we need a national AI champion and potentially nationalize Thinking Machines." They could.
1:12:15
Have like a joint joint venture between >> a company that's based in America if you're not an American company.
1:12:22
>> Joint venture between A16Z and and Albania. Yeah.
1:12:26
Yeah, I saw I saw a viral of Jamie Dimon talking about like how important it is that uh, his bank is big and he says JP Morgan has to be big because we bank, you know, all of the Fortune 500. We bank governments.
1:12:36
We bank the US government. That's what he said. It's such a good line. Banking governments.
1:12:40
I I really want to know what's involved in that. Anyway, um, Yeah.
1:12:43
So, I I think like I think that my takeaway from this is like the pressure the pressure for Thinking Machines to deliver >> Mhm.
1:12:55
went from like like pretty extreme to like maybe slightly more extreme, but it's actually not that much of a difference.
1:13:02
I feel like they were already under a lot of pressure similar to Meta where like dense talent concentration, haven't shipped anything like, you know, truly remarkable yet.
1:13:13
Obviously, everyone's looking to see if they're going to be a real Yeah. uh, horse in the race. Yeah. Yeah. Yeah. Um, Yeah.
1:13:21
And the the other thing is like this team was created during an insane period of drama. >> Yeah.
1:13:27
The most >> all that it's surprising that Born in the drama.
1:13:30
>> They were born in the drama. And continue to be. >> living in the drama.
1:13:34
And but they can consolidate. They can refocus.
1:13:37
They can realign the team.
1:13:37
They still have a bunch of super talented people. >> Yeah.
1:13:41
And uh, I'm I'm sure they can still, you know, figure out kind of a niche and and deliver. Yeah. Anyway, Okta.
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1:14:00
Uh, After the meeting, so uh, the three co-founders, the three Thinking Machines employees that have this meeting, Uh, Mira asks them, "Have you already committed to jobs elsewhere?"
1:14:12
Metz and Schonholz said they hadn't.
1:14:14
Zof didn't answer, according to some people that were in this meeting.
1:14:18
Uh, the day after the meeting, Zof had dinner at a pizzeria with Meta executives Alex Wang and Nat Friedman.
1:14:25
He confirmed on Wednesday he was fired.
1:14:28
Uh, Morati posted on X that Thinking Machines had quote parted ways with Zof.
1:14:32
Less than an hour later, OpenAI's CEO for applications uh, is it CEO for applications, Fegee Simo?
1:14:39
I thought it was CEO of applications, Fegee Simo.
1:14:40
Uh, anyway, she's she's running the application.
1:14:45
Uh, she posted that Zof, Metz, and Schonholz were returning to the company and that negotiations had been underway quote for several weeks.
1:14:53
That's an interesting thing to put in your put in your hiring post uh, because there's clearly going to be a narrative about how sudden was this?
1:14:58
What when was this decided? Blah blah blah.
1:15:00
Uh, but she is saying proudly that we've been talking to these folks for weeks.
1:15:04
Uh, she said Zof would report would report to her while the other two would report to him. So, Uh, Yeah.
1:15:11
The the the craziness with Thinking Machines >> End of the end of the day, you got Mira, you got John Schulman, >> Yeah.
1:15:18
like still And it feels like there's Yeah, it feels like there's some sort of niche that could they could carve out.
1:15:23
Uh, the I mean, when we first heard about the like fine-tuning for LLMs for business for B2B companies, like that seemed like not it was not the AGI super intelligence pitch.
1:15:37
It was also not the okay, we're going to niche down and give consumers one specific thing.
1:15:42
We're going to go after audio.
1:15:43
We're going to go after video.
1:15:45
We're going to go after uh, we're going to make a an AI version of Excel or AI version of PowerPoint.
1:15:49
Like, there's so many like niche AI companies that have done very well.
1:15:53
We're going to do AI for legal. AI for health, right?
1:15:57
Like, there's all these ways that you can niche down.
1:15:59
They kept it sort of broad, but but it felt like going into the enterprise with her connections and her background and the team seemed like something that could ramp revenue very very quickly.
1:16:09
>> Yeah, and the raw talent of the team. Totally. Yeah.
1:16:10
A lot of which still exists. >> Yeah.
1:16:12
>> Yeah. So, uh, but I I mean, really like the the strongest way to counter like the vibe war that's happening right now is um, just show some good numbers because if the business is working, even if you have a little bit of tumult on the technical side and there's, you know, a CTO leaving, like if the
1:16:30
business is working, >> with OpenAI, it's like, you know, some of the craziest drama ever surrounding a company and then you look at, you know, the revenue ramp and it's like, you know, >> And the DAUs are just through the roof and you're like, "Okay, well, clearly the user was completely unaffected." I
1:16:41
I bet if you look at the ChatGPT daily active user growth chart, you cannot see Sam Altman getting fired and then rehired.
1:16:51
It's not like people were like, "Well, I'm not using this app today and I'm firing it back up once he's in."
1:16:58
Like, no, there was no there was no blip in the graph, I'm sure, around that because that was like Silicon Valley drama.
1:17:03
And for the average user, it's like, "Did it did it deliver or not?" Yeah.
1:17:07
Um, and that's just the something that happens all the time when there's these drama elements that burst onto the scene and take over the timeline for a few days.
1:17:14
Yeah, the the another another possible route and then things would have to get really bad over there.
1:17:20
They'd really have to be directionless, which uh, again, you know, the team clearly was was debating uh, on on if the direction was correct, but sounds like they do have a direction.
1:17:31
But I I still think this is a company that would have a pretty meaningful valuation in an acquihire context, right?
1:17:39
Like if Amazon were to come and buy them, how much would Amazon pay to get John Schulman and Mira Morati like at Amazon.
1:17:49
>> able to clear the Prop Stock, for sure.
1:17:50
Yeah, by by like a long shot, you would imagine. So, um, anyway.
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1:18:02
Um, I wanted to look at this photo of Davos.
1:18:06
It's AI generated, but it captures a good vibe.
1:18:09
A whole bunch of private planes uh, parked there.
1:18:11
That's not real, but I like that Kevin Kwock contextualized it anyway saying, uh, "This looks like Hoth Echo Base."
1:18:19
Um, and and he shared one further down that's that's uh, Davos transformed into a into a a Star Wars scene.
1:18:28
Um, anyway, uh, over in Davos >> Trey Trey says, "We need to know what those machines are thinking."
1:18:34
They need to call it Thinking Machines Intelligence.
1:18:36
Thinking Machine Intelligence. TMI Labs. >> Yeah.
1:18:40
I mean, we we don't know too.
1:18:40
It's possible that when they think when they're they're they were debating the product direction, they were talking about should we make branded 45s, right?
1:18:50
We know they're making We know they have branded plates. >> yes. Yes. Yes. Yes.
1:18:55
We know they >> technical direction.
1:18:56
Like, do you lift heavy or do you do lower weight, higher reps? Yeah.
1:19:00
And there was a massive debate over that.
1:19:02
Uh, Anyways, I mean, gym buddy is another relationship that you need to disclose.
1:19:07
If you're spotting each other, I want to know about it.
1:19:08
I want to know who's spotting who cuz that's an important relationship that's happening outside of the workplace.
1:19:14
I got to know about it if you're if you're going to be lifting together.
1:19:16
Uh, Anyways, I'm I'm I'm rooting for Thinking Machines uh, and uh, excited to see what they do.
1:19:23
The uh, Demis and Dario are apparently just bro-ing out in Davos. I love it.
1:19:30
Lisa Al Gaib says, "Demis Hassabis is CEO of Google DeepMind at the Davos quote, 'When when told that Dario Amodei was here earlier today, his face lit up.
1:19:41
2 minutes later he was talking about a CERN-like collaboration for AI once the labs are close to AGI.'
1:19:46
They're just stoked on each other.
1:19:49
'I'm pretty I'm on pretty good terms with pretty much all of the other leaders at the leading labs.
1:19:54
I love Ilya and we're good friends.' You love it.
1:19:56
Just some positivity hanging out at Davos.
1:20:00
Demis said that he thinks entry-level jobs and internships might fall away due to AI.
1:20:04
Sees consistency as the biggest problem with current agents.
1:20:07
Advice for college graduates, get incredibly proficient with these new tools, AI agents.
1:20:14
And so, yeah, it we were debating this earlier.
1:20:17
Like like the the role of a junior engineer is is is going away, but is it possible that it just changes?
1:20:24
Like like what what what makes a senior engineer that much better with an AI tool that they don't need anyone else who can potentially use AI tools as well?
1:20:38
How how much of this is uh is something where I mean to go back to like the the Chinese young hiring boom, there's an element where I'm sure there's companies where you have older software engineers who are more resistant to adopt AI technology and you'd actually be better off with a young junior >> Here's a tough question for you, Tyler.
1:21:00
What what are you fantastic at that AI is bad at?
1:21:06
Um uh walking around, being physical physically embodied. >> Embodied.
1:21:12
That's the last >> that's like for China it's like maybe the you know, Silicon Valley has kind of found like pederasty from First Principles. Mhm.
1:21:19
Maybe you know, it's just a similar thing over there, right?
1:21:23
There's actually a lot of value.
1:21:23
I think so generally like I'm kind of I've always gone between like is our jobs actually going to go away from or are they just going to get like more fake?
1:21:33
Like Jordy and I were talking about this earlier where it's like are there just going to be no junior jobs in like 5 years or are they just going to be like you're just kind of it's like you know, you're in the office because like it's like people like having other people in the office and stuff like this.
1:21:50
So I I I don't really know where I sit, but I think I'm probably more in the camp of like you just don't need to hire new people. Yeah.
1:21:58
Well, Ken Griffin What did Ken Griffin say?
1:22:01
He took the other side of this one. >> a tear.
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Let's play So so the post here one up for the team.
1:22:20
Uh Citadel CEO says AI has re-empowered technology departments in every business, but claims that 50% of entry-level white-collar jobs will disappear due to AI in 5 years is hype.
1:22:31
He's throwing some cold water on Dario's uh talk track, but let's play the video. Let's play the video. Are we getting audio?
1:22:44
Where where's Ken Griffin on this one? Is this the right one?
1:22:48
The from Disclose TV, Citadel CEO says AI has re-empowered technology. Is that the one, Jordy? Yeah. Let's play it.
1:22:59
And we were we are I guess in the market for an AI agent that can play videos on our Let me tell you about Figma.
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1:23:17
First of all, it's a it's a pleasure to be on the gloom and doom panel. Yeah.
1:23:21
We're not We're not You know, the 1920s were an extraordinary period.
1:23:24
As I said at the beginning, it's not preordained that it has this love the end note of the 1920s, which was of course the Great Depression.
1:23:31
So let's let's take a step back and and talk about where we are right here right now.
1:23:39
The the area of recklessness is the is the spending of governments around the world who are all with with little exception are all spending well beyond their means.
1:23:51
That's the recklessness of this moment in history.
1:23:54
This is not a parallel to the 1920s in terms of the recklessness of the of the private capital markets.
1:24:01
It's a story of the recklessness of government spending.
1:24:06
Within the private sector there's a huge question as to where AI will take us.
1:24:09
And I I was carefully taking notes and listening to what Larry has to say or to what Madame Lagarde has to say because this is one of the big issues of our moment.
1:24:21
Will AI create the productivity acceleration that is honestly that's hoped for in Washington and in the halls of government around the world as a ways to overcome the profligate spending that we're currently engaged in.
1:24:40
Like the world the world needs a savior.
1:24:43
And the hope is that AI is the savior that we need for productivity.
1:24:49
And the challenge with this is it is it may or may not be. We just don't know yet.
1:24:53
Now, there's a tremendous amount of hype around AI.
1:24:58
And in some sense, the large AI companies need to create that hype to raise the tens of or actually hundreds of billions of dollars of investments >> that are going to the field.
1:25:13
Like you wouldn't be able to raise hundreds of billions dollars.
1:25:15
We'll spend and and Larry can probably correct me on this, but roughly 600 billion dollars this year in CapEx for data centers in the United States.
1:25:23
I think it's going to be larger.
1:25:25
But does that mean that it's getting hyped up too much or it's just the hype is required as a as a sales mechanism? Go ahead.
1:25:33
Larry's backing you up, Tyler.
1:25:35
All right, let's play the next video, which was the one I was originally talking about, which is talking about job job loss.
1:25:46
What AI has done is it has re-empowered the head of technology in every business in the United States.
1:25:54
And it has pushed budgetary resources into the hands of of the chief technology officer.
1:26:00
So what you're seeing across American business is actually the impact of American businesses spending more on digitization writ large, of which AI is just one component.
1:26:17
It's one component, but it's the it in some sense it's the cover story that creates the space for American companies to really embrace technology in a much more profound way.
1:26:29
I was in I was in China about a year and a half ago with a group of prominent global executives.
1:26:33
And they were all talking about how AI was changing their business. It was so fun.
1:26:38
And I said, "Let's go around the table and let's each share a story as to how we're using AI to make our business better."
1:26:48
I heard five or six great stories.
1:26:52
Not one involved generative AI.
1:26:55
But does that mean He just mugged you to death, Tyler.
1:27:00
Bro, you're telling me a big company's inefficient in implementing technology?
1:27:03
Like You know, as Dario Amodei says, you know, half of all entry-level white-collar jobs will, you know, be gone in the next 5 years.
1:27:10
Is it that kind of change >> Look, you know, put yourself in his shoes.
1:27:15
How much how much money does the AI community need to raise over the next 5 years?
1:27:19
>> wrong about this, right?
1:27:19
Demis doesn't need to raise money.
1:27:20
We'll spend in the this year over half a trillion Google's doing this with cash flow.
1:27:23
over 500 billion dollars.
1:27:26
Like that's true for every other lab lead except for Demis.
1:27:31
Like you would expect Demis to be like, you know, like Yeah, but the question is about Dario. Oh, Dario. Okay. So is it hype? Yes, of course.
1:27:40
AI will >> Like how How else are you going to get people to write 500 billion dollars of checks just this year alone? Right?
1:27:49
There needs to be a level of like AI is your savior almost.
1:27:54
And the question is where will AI land in productivity gains at the end of the day?
1:27:59
In certain areas we know it's going to be profound, whether it's call centers, whether it's helping to improve the productivity of software engineers.
1:28:07
But in a number of white-collar jobs, you know, there was a there was a recent Harvard paper on this.
1:28:10
They called it AI work slop.
1:28:15
That it looks good, but if you sort of peel back the onion the substance isn't there.
1:28:19
I was with one of my colleagues who runs our commodities business and they he handed a report on that we were generating with a an AI engine.
1:28:28
Doesn't matter what the topic was.
1:28:28
The first few sentences like, "Wow, that's that's really insightful."
1:28:32
And then you go down below that and it's all garbage.
1:28:36
So that's going to and we all get we are running out of time, but that suggests that AI is not going to come to the rescue to make up for the various negatives that we discussed about in the first part of this conversation.
1:28:44
So in 10 seconds So but remember the spending on technology writ large is having a clear positive impact on the economy.
1:28:54
So which economy in the world benefits most from this conflagration of geopolitics, economic policy, and technology change?
1:29:04
I mean Who benefits the most?
1:29:08
That's a really interesting way to put it. In 10 seconds. In 10 seconds.
1:29:16
You know, when it's all and done, it it's somewhat ironic, but it's it's the United States and China are the two big beneficiaries of this moment.
1:29:28
Uh yeah, so so one thing Yeah, but like my the way that I like process this is as somebody who who's not indexed to AI scaling and AI progress.
1:29:40
But a lot of the most talented people he's ever worked with have ended up working in AI, right?
1:29:48
They've gone from the East Coast >> Yeah.
1:29:50
and gone and and over to the West Coast and started working in the labs.
1:29:53
And so while he's not, you know, working in a lab, I do feel like, you know, his his and you can argue like he's not AGI pill.
1:30:02
He he clearly is not processing models developing like more advanced like reasoning and agency and all these things >> Like we could be here next year and he could be like, "Oh, like I got a I got a report from a commodities trader. It was AI generated. It was amazing."
1:30:16
Like that's happening in so many other fields where people have said, "Oh, like I'll always be able to clock generative imagery."
1:30:24
And then they look at the latest Nano Banana Pro output and they're like, "Yeah, okay, actually I can't. I I I have updated."
1:30:29
Uh that that certainly happens.
1:30:31
Um the the interesting thing about his So I I I like his I like the point about the incentives of lab leads to make grand proclamations about progress in order to underwrite larger financing rounds. That's clearly true.
1:30:46
That's that's clearly something that does happen.
1:30:50
But explain Demis sounding exactly like Dario in terms of timelines and and impact.
1:30:57
Like a lot of their rhetoric is very very similar.
1:30:59
And and Demis is in a position to just say, "Oh, yeah, like we're going a lot slower because we're doing this off of cash flow and like we don't need to raise and it's going to be longer."
1:31:11
Like that actually might be to his benefit to sort of like pour cold water on all the competition that's out there trying to raise all this money.
1:31:19
If he comes out and says, "Yeah, like you don't you don't need to lever up and and build a trillion dollars worth of data centers because progress isn't going to be that fast."
1:31:29
Um that would be probably beneficial to Google, maybe. I don't know.
1:31:34
But it it certainly doesn't seem like he has to message that.
1:31:35
I mean, maybe to the Google shareholders somewhat, but not really.
1:31:38
It's not really showing up in Google's financials yet.
1:31:43
It's not really changing >> might wait until Anthropic and OpenAI get their S-1s out and then decide, "All right, it's time." It's actually over.
1:31:52
What what what do you think about that?
1:31:53
Is as a counterpoint to Ken Griffin's uh you know, CEO of Citadel, he's saying that uh all of the AI hype is about fundraising for these labs.
1:32:06
Demis doesn't count there, right?
1:32:06
Yeah, I mean, doesn't he still have to like convince, you know, Sundar to >> Yeah, and then the internal markets >> Yeah.
1:32:16
Yeah, and and the shareholders >> that's probably true.
1:32:17
But I still it's like, you know, he he had the example of like, "Oh, I talked to business leaders and how how are you improving your company with AI?"
1:32:23
And none of the examples were AI.
1:32:24
Like those are you just know those are like it's from some consulting firm that gave them they the model that was like 3 years ago. Yeah.
1:32:31
Like I >> some they need some younger people at these companies that would be using Yeah, I I just don't know >> generative AI in transformative ways as opposed to uh Yeah, I mean, it it it feels like those two things cannot be true.
1:32:45
You cannot have a sclerotic uh you know, large business that is failing to take advantage of AI and simultaneously not be hiring young people who are more AI native.
1:32:55
It feels like you you have to you have to, you know, embrace one or the other.
1:33:01
Like either Yeah, and he's discounting like any concept of progress, right?
1:33:05
Like he's like, "Oh, you when you read something it's like total slop now."
1:33:10
That's exactly how how how code was like 2 years ago.
1:33:12
Now there's software agents that can Yeah.
1:33:14
you know, pretty autonomously build entire system.
1:33:18
That's that's certainly like not unlikely to happen in in just general writing. Yeah. Yeah.
1:33:23
Ken Griffin needs to vibe code a mobile game or something.
1:33:27
>> Yeah, I think I think calling calling out that saying like labor replacement theories and pitches are like catnip for venture capitalists.
1:33:36
They're doing white-collar work.
1:33:41
And if they get the pitch that, you know, some technology is going to Like if you go to if you went to a VC and you gave a really compelling pitch of how your product is going to replace all VCs in the world, and it actually made some sense and you could kind of imagine how it play out.
1:33:56
I'm sure you get a lot of investor interest in something like that, right?
1:33:59
Cuz you're just trying to hedge, right?
1:34:00
So it is it is like the most compelling narrative. narrative. Yeah. fin.
1:34:06
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1:34:08
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1:34:12
Uh let's click over to Jamie Dimon at the World Economic Forum in Davos.
1:34:17
He's talking about raising taxes and special interest groups and the audience that makes society work better for everybody.
1:34:25
And Would you raise taxes to pay for that?
1:34:29
I don't think you have to.
1:34:29
I think it would drive a lot of growth.
1:34:30
I think it would I I I did the numbers at one point be $60 billion of uh of uh spending.
1:34:33
I think it would probably create more than that of growth and taxes.
1:34:37
Uh you know, and if you have to raise taxes a little bit, that's fine.
1:34:41
But again, I don't want to buy an argument.
1:34:42
I don't I don't know anyone, okay, and you guys in the room might be Democrats, Republicans, who thinks the spending that that sending another trillion dollars to Washington, D. C.
1:34:52
will actually improve anything.
1:34:55
So when you say raise taxes, I if you said raise taxes and directly give it to the people who need it, I'd do it. Of course. No.
1:35:03
But that's not what happens.
1:35:03
It goes to all these interest groups.
1:35:05
>> It goes to all these interest groups, you know, and they give it to their friends and all that.
1:35:07
And which is why which is why the people consider it a swamp. It it's kind of a swamp.
1:35:11
You know, the 17,000 lobbying groups.
1:35:13
And but bank companies are guilty, too.
1:35:17
They're just fighting for their one self-interest as opposed to what's good for my country.
1:35:20
But you know, that's what happens in Congress, you know, uh and you see these how these bills get spent.
1:35:25
Like the Chips Act was a good idea until, you know, it was it was had to be union, it plays base, child care, diapers, you know, what the hell are we doing?
1:35:36
And and and we do it over and then we then it's >> my president. That's my president.
1:35:42
Yeah, Jamie Dimon's great.
1:35:42
Uh Let me tell you about Sentry.
1:35:45
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1:35:49
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1:35:54
Uh Demis, we we've been talking about him and his uh blockbuster performance at Davos.
1:36:00
He had a number of interviews.
1:36:00
Uh this one with Emily Chang uh talking about uh a pause on AI and whether or not he supports it.
1:36:09
A very revealing quote, very, you know, uh uh says a lot about his timelines and his his his P-doom in some ways.
1:36:17
Uh let's watch this uh clip from Emily Chang interviewing Demis.
1:36:23
>> to give regulation time to catch up, to give society time to sort of adjust to some of these changes.
1:36:28
In a perfect world, if you knew that every other company would would pause, if every country would pause, would you advocate for that? I think so.
1:36:37
I mean, I've been on record saying what I'd like to see happen.
1:36:40
I It was always my dream of the the kind of the road map at least I had when I started out DeepMind 15 years ago and started working on AI, you know, 25 years ago now, was that as we got close to this moment, this threshold moment of AGI arriving, um uh we would maybe collaborate, uh you know, in a scientific way.
1:37:00
scientific way. I sometimes talk about setting up an international CERN equivalent for AI, where all the best minds in the world would collaborate together uh uh and and and do the final steps in a very rigorous scientific way,
1:37:15
involving all of society, maybe philosophers and social scientists and economists as well as technologists, um to kind of figure out what we want from this uh technology and how to utilize it in a in a in a way that benefits all of humanity. And I think that's what's at
1:37:29
And I think that's what's at stake.
1:37:31
Um unfortunately, it kind of needs international collaboration though, because even if one company or even one nation or what even the West decided to do that, um it's the has no use unless the whole world agrees at least on some kind of minimum standards.
1:37:46
And, you know, international cooperation's a little bit tricky at the moment.
1:37:49
So um that's going to have to change if we want to to to to have that kind of um rigorous scientific approach to the final steps to AGI.
1:37:59
Pod friendly guy in the YouTube chat says Demis is the Steve Jobs of AI.
1:38:04
>> You're you're wearing the TVP internal neck today.
1:38:06
Maybe we need to make a turtle neck and award it to the the who we crown the Steve Jobs of AI.
1:38:11
No, he's a fantastic communicator.
1:38:13
Demis is is inspiring, balanced, measured, knowledgeable, just uh not he's not completely accelerationist at all costs, but also not completely doomerist. I don't know.
1:38:26
I It's a really it's really great take. I don't know.
1:38:28
What do you think, Charlie?
1:38:30
>> Yeah, I I think there's maybe an interesting way to look at this like the question of pausing.
1:38:33
Um where if so if you take Dario says that um he's not competing with with DeepMind or OpenAI, right?
1:38:40
Cuz he's an enterprise, they're a consumer. Yeah. Wait, wait. Who Sorry, sorry.
1:38:44
Wait, clarify who who's who there?
1:38:46
So Dario >> Dario at Anthropic >> Anthropic is enterprise.
1:38:49
>> Is saying we're not competing with DeepMind because that's a consumer company.
1:38:52
Is that what he's saying? Yeah, and OpenAI.
1:38:53
That's what he said yesterday.
1:38:55
Like probably he was like we don't have to monetize billion users, whatever.
1:38:58
>> He's like, "Just just ignore those companies and their enterprise businesses." They don't matter. Okay.
1:39:02
Yeah, but so so if you take that and then um so that means, you know, there's some way in which uh you know, DeepMind's real only competitor is OpenAI.
1:39:09
Uh if you know, we were just talking about how uh DeepMind doesn't have to raise money, right?
1:39:13
They're funded by cash flow.
1:39:14
So, basically, there's a way to look at it where you can either pause for for safety reasons so we can catch up with regulation or whatever, um, or it's just because if we basically pause all AI, uh, it's actually fine for Anthropic, right?
1:39:27
Because uh, they're they don't have a like super direct competitor, right?
1:39:30
OpenAI is trying to get more into enterprise.
1:39:32
Maybe DeepMind is as well, too, but like they have a like fairly strong position, perhaps. >> Yeah.
1:39:37
And then, it's going to hurt OpenAI a lot, they need to raise a lot of money to compete with DeepMind. Yeah.
1:39:42
So, if you can basically make this like almost cartel-looking, you know, like thing, group with Anthropic and DeepMind, you can basically try to take out OpenAI. No, it's interesting.
1:39:52
I mean, that's very cynical way to look at it.
1:39:56
Yeah, yeah, yeah, yeah, yeah, I hear you.
1:39:58
The other The other interesting thing is that he says he says, um, he would he would like maybe potentially support a pause, but then what he describes is not all the researchers focus on productization of the current models.
1:40:13
Like, stop training, stop doing reinforcement learning, stop optimizing models, and instead, like, let's build more great SaaS.
1:40:19
Like, that's not what he's saying.
1:40:20
He's saying, like, let's all still do research.
1:40:24
>> progress to focus on ads and AI progress.
1:40:26
And that would fire me up, but, uh, that's not what he's saying.
1:40:30
What he's saying is like, get all the researchers together in and in CERN.
1:40:31
And CERN is not pausing scientific research.
1:40:36
Like, if anything, CERN is a way to accelerate AI research, but in a collaborative way.
1:40:40
So, he's really just calling for more collaboration and a pause on competition or a pause and I mean, I feel like everyone in the scientific community in the in the research community definitely laments the the the days of yore where there were more open research papers, more sharing of knowledge.
1:40:57
It wasn't all, uh, constantly just backdooring through hiring and poaching.
1:41:03
Some of it was just open, you could just download the Transformer paper.
1:41:07
>> Yeah, so but but even in that case, like, uh, DeepMind is still like, you know, on the defensive, right?
1:41:11
Because OpenAI is trying to take like Google is like, oh, search is dying, right?
1:41:14
OpenAI is trying to take it away.
1:41:16
If you can basically get everyone to be like, oh, we're going to, you know, collaborate, everyone's going to share the research, that's I that's probably better for DeepMind.
1:41:24
>> yeah, so game theoretically, yeah.
1:41:26
So, you would never expect the leader to say, "Hey, let's pause the race."
1:41:29
You would You wouldn't expect OpenAI to pause the race because they're the ones who have so much more to gain from like attacking the other Just continue pushing further, yeah. Yeah. Okay.
1:41:39
I mean, depends on what you mean by pause because I I feel like if there was like a a model freeze and you only have Opus 4. 5, GPT 5.
1:41:46
2, Gemini 3 Pro, uh, you have those models, like, OpenAI could still compound on the on the DAU front, right?
1:41:59
>> Yeah, I mean, yeah, there's a bunch of ways it could like actually go down.
1:42:02
But, there's like different ways to look at it, I think, rather than just like pure safety. Yeah.
1:42:07
Uh, there's some extra context here from Andrew Curran.
1:42:08
He says, "Darius said the same thing during the day after AGI discussion this morning.
1:42:12
They were both asked for their timelines.
1:42:14
Demis said 5 years, Darius said 2.
1:42:16
Later in the discussion, Darius said that if he had the option to slow things down, he would because it would give us more time to absorb all the changes.
1:42:25
He said that if Anthropic and DeepMind were the only two groups in the race, he would meet with Demis right now and agree to slow down, but there is no cooperation or coordination between all the different groups involved, so no one can agree on anything."
1:42:40
And it's very funny thinking about this CERN-like bring all the researchers together in the context of like the craziness at OpenAI, the craziness at Thinking Machines, all the interpersonal aspects, the human element of of AI progress, that that, you know, you get everyone in and it's like, "Okay, we need to pick a leader.
1:42:56
Like, okay, who's in charge? Who decides what?
1:42:58
Like, how do do these all do all these people get along?"
1:43:01
Because some of them have some real pretty crazy bad blood.
1:43:03
He's like, "Hey, you kicked me out of this lab and then you quit when I thought you were going to be my co-founder and then you were having this relationship with this person."
1:43:10
Like, creating harmony in the in the in the barnyard might not be the easiest thing.
1:43:17
>> Interesting point from Deepak in the chat.
1:43:19
No OpenAI at Davos, question mark. Which is There is.
1:43:22
So, I believe Sara Friar did an interview there.
1:43:27
The The interviews are on like a delay.
1:43:29
A lot of them happen at 10:00 p. m. Davos time.
1:43:31
Also, the first day of the conference was yesterday, so we will be getting more Davos content today.
1:43:37
I I I did feel that, though.
1:43:39
But, a lot of it's just about when different segments happened.
1:43:42
So, I mean, amazing move by Dario and Demis to come out with, you know, absolute heater on day one very early, establish some some ground game, some ball control because Satya Nadella is there.
1:43:57
He's going on the All-In podcast and he's already given quotes and there's some clips from him, but we haven't seen him.
1:44:03
He hasn't He hasn't been aura farming.
1:44:05
Microsoft hasn't been aura farming Davos as effectively as Google and Anthropic.
1:44:11
So, you know, little bit of tail of the tape there.
1:44:12
Well, let's skip ahead >> to 11 Labs.
1:44:15
Build intelligent, real-time conversational agents.
1:44:18
Re-imagine human technology interaction with 11 Labs.
1:44:20
And I believe the CEO of 11 Labs is there at Davos, but what do you want to move on to, Cory?
1:44:27
>> this is I mean, this was the probably the the story that got reported on the least out of Davos over the last 24 hours, but is arguably the most important.
1:44:35
The most expensive car in the world.
1:44:39
Everyone wants to know, of course, it is the car that Jensen bought his parents.
1:44:44
So, let's pull up this clip. I love it. This is great.
1:44:49
We have many more years of that journey ahead of us. Thank you. I appreciate that.
1:44:53
My only regret was at the IPO after the IPO, I wanted to buy my parents something nice.
1:45:00
And so, I sold Nvidia stock at a valuation of $300 million.
1:45:08
Uh, the company was at a valuation of $300 million and I bought them a Mercedes S-Class.
1:45:14
It It is the most expensive car in the world. Yeah. >> it? Do they still have it? Oh, sure.
1:45:23
Yeah, they still have it, yeah.
1:45:25
Jensen, congratulations on that journey. Yeah, what is, uh, five?
1:45:29
>> So, it's currently at four and a half trillion dollar. Four and a half?
1:45:33
And an S-Class when uh, they went public in 1999. So, at >> S-Class.
1:45:42
So, what what was S-Class costing like 60k something back then? I don't know.
1:45:46
How much what did I mean, you're talking about a maybe a billion dollar car?
1:45:52
I don't know if I have the math right there, but it seems like it >> Yeah, around 65k.
1:45:59
>> It seems like the stock might be up 15,000x or something. I don't know.
1:46:03
I mean, it's definitely up 1,000x, right?
1:46:06
Cuz it's, uh, yeah, 300 million 300 billion and then you get another zero, so 10,000x. Wow, that is brutal. Brutal. Brutal.
1:46:16
Worse than the TV I bought with a Bitcoin. Hey, worth it. Worth it.
1:46:18
>> I I bought a TV with a Bitcoin. Terrible. Not even 4K.
1:46:22
Thing's in the trash now.
1:46:25
It was like a It was like a thousand dollars back then. It's ridiculous.
1:46:28
Anyway, Cisco, the Davos of Cisco.
1:46:30
Cisco AI Summit, it's February 3rd.
1:46:33
It brings together leaders from Nvidia, OpenAI, AWS, and more to discuss the future of the AI economy.
1:46:39
The whole thing will be live streamed and we'll be there for a gig stream.
1:46:43
Mark your calendars, February 3rd, Cisco AI Summit.
1:46:46
Hope to see uh, many of you there. We're very excited.
1:46:50
>> President Trump had some comments in Davos.
1:46:53
Alex Heath broke the story, took it to the timeline.
1:46:58
Alex Heath says, "A quote from Trump, Mark Zuckerberg showed me a plant where he put it over map the size of Manhattan, miles long, miles wide.
1:47:07
It literally covered most of the island of Manhattan.
1:47:10
It's called a big plant."
1:47:14
I think he's talking about a data center, but I like that he's calling a plant.
1:47:19
That is a big plant, a power plant, essentially. Plant of things.
1:47:21
Um, and, uh, President Trump also said that the stock market dip is peanuts, that the stock market is going to be doubled.
1:47:32
And, uh, and Boring Business Quotes then says, "The The president is literally telling you that the stock market will double from here and you are bearish?"
1:47:41
It's, uh, it's a crazy crazy line.
1:47:41
What else did Trump say here?
1:47:43
He said, "Our stock market dip is peanuts.
1:47:44
The The Dow is going to hit 50,000 and double to 100,000 in a relatively short period of time."
1:47:52
Anyway, let me tell you about AppLovin.
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1:48:02
Uh, Someone should try to follow up and figure out ask the president, are you giving financial advice? Yeah. And what's driving it?
1:48:08
Are Are are multiples going to double or is is our earnings going to double or are we going to see a little bit of earnings growth and then a little bit of multiple expansion?
1:48:18
What's driving the valuation increase? I'd love to know that.
1:48:21
Let's get to the bottom of it.
1:48:22
Uh, Semafor made a print newspaper Yeah. for Davos.
1:48:28
>> Well, I mean, first we need to confirm that Philip Johns- Johnston, the founder of StarCloud, former guest on the show, he is there at Davos. He's dropping takeaways. He's asking questions.
1:48:39
He was the only person that got to ask Demis a question, right? That's crazy.
1:48:47
I mean, makes you ask some questions. >> It does. It does. It's Yeah, yeah.
1:48:48
I mean, what what a run from, uh, from Philip Johnston, but, uh, it's been fun seeing like the on-the-ground.
1:48:56
Obviously, there's a lot of polished clips that are going out from the media organizations, but he's doing citizen journalism over there.
1:49:01
And, uh, we thank him for his service bringing clips to the timeline uh, saying that Jensen Wong announced that we need more energy and also he broke the story at least to me that Jensen's parents own the most expensive Mercedes in the world.
1:49:16
I wonder if they still have it.
1:49:18
Anyway, let's go to semaphore.
1:49:20
First, let me tell you about Gemini 3 Pro Google's most intelligent model yet state of the art reasoning next level vibe coding and deep multi-modal understanding. I like that sound cute. It's a good one. It's the best.
1:49:31
Anyway, Reed over at semaphore says it's fun to work for a print newspaper again, although I missed the print deadline for some changes which brought back some fond Wall Street Journal memories and traumas.
1:49:41
We we really missed our window to do the TVPN print newspaper.
1:49:46
Somebody uh uh somebody sent us a fully built out TVPN print newspaper.
1:49:51
It looked absolutely fantastic last year.
1:49:53
We wanted to roll out uh at least a weekly maybe daily print news newsletter, but uh couldn't get around to it.
1:50:02
Uh This is a very interesting uh lead too.
1:50:04
I can't find this actual article.
1:50:06
I'll have to find a digital version of this, but he says techies ignore the geopolitics on their Davos home turf.
1:50:13
Quote, this reminds me of Burning Man, but not how you think.
1:50:15
I'm like just zooming in to try and read this.
1:50:17
AI has finally been eclipsed by geopolitics at at Davos.
1:50:21
There are essentially two conferences happening.
1:50:22
One involves Greenland, Venezuela, and the rewriting of the world order, and the other is really just a tech conference centered around selling and deal-making.
1:50:29
That's the one I want to go to.
1:50:30
the one I want to go to. Yeah, I we were we were texting with the journalist who is writing a story about tech's involvement in Davos and and uh my my point was like it does feel like Davos is coming back and and the and the tech companies are there, although from the outside I think a lot of people think of Davos purely as a meeting of world leaders and geopolitical and they're following the
1:50:50
Greenland story and they're very much looking at the the front page of the Wall Street Journal, but if you go to the front page of Axios in the timeline, it's all Demis and Dario clips uh and Ken Griffin and a few others, but mostly like the stuff that I've been seeing has been focused very much so on tech, but there is a whole different uh uh different story going on all over all around Greenland and whatnot. Um
1:51:12
Um but we got to talk about AI timeline.
1:51:16
It's more interesting to me. I'm just so excited.
1:51:18
Uh Should we talk about why Elon is racing to take SpaceX public? Absolutely.
1:51:25
Absolutely, but first, speaking of public, public.
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1:51:35
So, why is Elon racing to take SpaceX public?
1:51:39
>> Putting data centers in space pushed the the billionaire toward an IPO, sources say, according to the Wall Street Journal.
1:51:45
SpaceX resisted going public for years, then came the rise of artificial intelligence.
1:51:53
Elon's rocket maker became one of the country's most valuable private companies due in part to its ability to develop risky space businesses outside the scrutiny of public investors.
1:52:00
Its executives like to say the company wouldn't IPO until its rockets were regularly flying to Mars.
1:52:05
That was before the rush to build data centers for AI computing prompted Musk, Jeff Bezos, and others to propose putting them in space.
1:52:13
The idea has prompted skepticism from many engineers given the technical challenges poised by building solar-powered AI data centers that zip around the earth, but it has continued to gain traction and Musk has become obsessed with the idea of SpaceX being the first to do it.
1:52:27
Such a feat would be hard to attempt without billions of dollars in capital an IPO could deliver in one fell swoop.
1:52:32
The billionaire uh it's so funny to just refer to Elon as like just a billionaire.
1:52:38
The bill the billionaire also sees the SpaceX IPO It's like he's you correction like two months ago he tried to buy Twitter. He's a trillionaire.
1:52:45
teen-air teen-air teen-air's a new I'm I'm excited to be throwing that around. Oh.
1:52:52
Uh the sees a SpaceX IPO as a way to help his AI company xAI catch up uh to rivals.
1:52:59
Uh Musk has a long-running rivalry with OpenAI uh CEO Sam Altman who last year explored buying a rocket company to deploy satellites with AI computing capabilities in the space.
1:53:07
Two of xAI's competitors, OpenAI and Anthropic, are eyeing their own IPOs this year, and Musk seems eager for SpaceX to hit the public market first.
1:53:15
SpaceX is expected to select banks to lead the stock offering soon.
1:53:19
Musk has told people he wants to complete the IPO by July.
1:53:21
He wants to get it done so he can have a nice summer.
1:53:27
>> Philip Johnson needs to SPAC Star Cloud like today.
1:53:30
If he SPACs it, it's going to 20 billion like overnight.
1:53:34
Like it's going to be the biggest meme stock.
1:53:36
Anytime that there's a that there's a like a public SPAC'd comp to an Elon company that's like private, it's just like everyone wants it cuz they want the they're they're they're like, well, if the Elon thing works like this one, we'll take 2% of the market. So, that's out.
1:53:51
Um You could certainly be able to raise a lot of money.
1:53:56
Musk's apparent change of tune on SpaceX IPO plans in the middle of last year surprised many.
1:53:59
The billionaire, soon to be teen-air, has loudly complained about running his existing public company Tesla and has repeatedly tangled with regulators in the courts over issues like his compensation.
1:54:09
Everyone thought like Elon ran the biggest AB test on what it's like to run a large cap company in the public markets and the private markets.
1:54:19
He had a terrible experience in the public markets with Tesla getting sued and dealing with all that, uh dealing with complicated comp packages, um and so it felt like he would definitely prefer to be private all the time.
1:54:28
He wanted to take Tesla private, remember? At uh funding secured.
1:54:33
Um He he's never been a fan of the public markets, but he has changed his tune.
1:54:40
So, Uh anyways, uh building and launching thousands of satellites would be technically demanding and costly, and SpaceX officials quickly decided the easiest way to raise the tens of billions of dollars it required was to dip into the newly thawed US market for IPOs.
1:54:53
Meanwhile, uh xAI, which is trailing rivals including OpenAI and Google's Gemini by key metrics such as revenue and user base, a SpaceX IPO was seen by some of its investors as a potential cash cow that could supercharge xAI's growth growth and help and in turn help SpaceX.
1:55:09
If SpaceX succeeds with putting data centers in space, its investors expect xAI to become a customer. >> Yeah, makes sense.
1:55:14
Some investors believe SpaceX could purchase a percentage of xAI or Musk, who owns more than 40% of SpaceX, could tap that stake to invest in his other companies including xAI.
1:55:23
Plus, a publicly traded stock creates a capital safety net of sorts and would be reassuring to investors.
1:55:31
Um So, anyways, um The two companies have existing ties.
1:55:34
SpaceX has invested 2 billion in xAI as part of a 5 billion financing, and then uh xAI raised a bunch more money. So, uh very exciting.
1:55:44
Anyway, CrowdStrike, your business is AI, their business is securing it.
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1:55:52
And we have our first guest in the TVPN old friend Jens Remec, the founder and CEO of California Forever.
1:56:00
Good to have you on the show again. Welcome back. How are you doing?
1:56:04
Sorry, let me get my diet coke out of the way. How are you?
1:56:08
How's the How's the new year going? How was your break? How were the holidays?
1:56:12
Uh we have three young kids on the floor and we dragged them 9 hours.
1:56:15
We dragged them 9 hours to see my mom and dad in the Czech Republic. Okay.
1:56:19
9 ti- 9 hours time difference there and then 9 hours back. Yeah.
1:56:22
So, you can imagine how my Christmas was.
1:56:26
More more more like like a day of travel with young children is is more stressful in many ways than than 99% of of work days.
1:56:37
I went to Europe over the break.
1:56:37
I went to Austria, but didn't bring the kids.
1:56:41
So, it was very relaxing. >> difference.
1:56:43
My new my new pet peeve is uh single people or couples on airplanes who complaining about the long flight. I'm like, really?
1:56:49
You had to sit there for 12 hours and drink wine and watch Netflix. That was terrible.
1:56:52
Well, I I used to think when a when a kid was crying, it meant the parent was doing something bad.
1:56:58
So, as you know, I'd be on a flight and the kid's crying and I'm like, wow, this parent is just like being abusive or whatever.
1:57:04
Why is the Why is the kid so upset?
1:57:06
Turns out kids will just cry cuz they're kids. A million reasons. >> Yeah. Anyways.
1:57:11
Uh anyway, give give us the update. Uh how are things going?
1:57:13
Uh just sort of reset for us on the project.
1:57:17
How long have you been working on California Forever?
1:57:19
Where are you in the process?
1:57:22
Uh I've been working on this for almost a decade. >> Almost a decade. Almost a decade.
1:57:24
So, 2016, started in 2017. Okay.
1:57:27
Um It was about 7 years of land assembly and then we introduced it publicly in about 2 years ago. Mhm.
1:57:34
Um I think Were you full-time back in 2017?
1:57:39
>> Yeah, I was full-time.
1:57:39
I was the um I was the only employee for 7 and 1/2 years. >> Okay.
1:57:44
And obviously confidentiality was very important for us.
1:57:46
And so, what that meant is when I say I was the only employee, I mean I did everything We raised a billion dollars in that period and I did everything from bookkeeping to being everything else in the company.
1:57:54
I literally did And the confidentiality, was that in part because if people knew what you were doing, they would come in and start trying to bid against you on land stuff and realize that He needs this plot, so he's willing to pay more and that is the game theory.
1:58:08
Yeah, and you have it's always happens.
1:58:09
I mean, even if you have university if you have public universities buying land in a city to build a building, they don't come in and like, we are MIT and we would like to buy this plot of land.
1:58:18
You some kind of companies. That was why.
1:58:21
So, what was the what was the structure of that fundraising because you probably had to draw a salary.
1:58:25
Is it like a search fund where a venture capitalist might raise some money, pull some management fees to fund their salary and operational overhead, and then like when there's a deal to be done, there's a capital uh there's a capital commitment that happens, a transfer. Is that what it's like?
1:58:42
We structured it as a partnership that raised money over time at at different valuations as we as we made progress.
1:58:47
And then I just took salary like any other founder.
1:58:49
So, it was it was pretty similar to a normal normal tech company.
1:58:53
There's some nuance because it's real estate and because of the just the sheer amount of capital that we needed and how long how long to do it.
1:59:00
But other than that, pretty pretty standard. Yeah.
1:59:01
And what was the what was the first pitch?
1:59:04
What was the first plot of land that you bought?
1:59:05
What was that negotiation like?
1:59:09
Well, the first few were the first few were listed.
1:59:11
So, when we came to the market, there there were four or five properties that had just been listed and sitting on the market for 2 years or something like >> anyone else thinking about doing anything in this particular region?
1:59:24
I don't know of anyone else.
1:59:24
I mean, not right now, but the the great irony of the situation is um lots of people thought this was a really good idea in 1958. Oh, yeah. Seriously. >> Yeah, yeah, yeah.
1:59:36
You've told me this There there there were there there is this there is in 1958 the Federal Commerce Department and the Army Corps of Engineers got together.
1:59:44
This is before almost before computers.
1:59:47
And they they they wrote this thick binder.
1:59:50
They called it the future development of the San Francisco Bay Area 1958 through 2020.
1:59:54
And decade by decade they planned where growth should go in the Bay Area. >> Yeah.
2:00:00
And you open these maps and they did a decade by decade and you look at the first one and Santa Clara is still orchards and so on.
2:00:07
But then they correctly predicted this explosion in places like Pleasanton and Dublin in the East Bay in the '80s and in the '90s.
2:00:16
But the part of Solano where we're building remained open.
2:00:18
And then you flip open the 2010 map Mhm.
2:00:22
and where I thought there should be a city they had a city. Mhm. There you go.
2:00:26
And I was sitting there in 2015 and I'm like, okay, maybe this isn't just Jan's insane idea.
2:00:30
Maybe some smart people thought about it.
2:00:32
And then you look at other regional planning documents in the Bay Area, something called the Association of Bay Area Governments, which is the regional planning body.
2:00:41
Had a plan called 1970 to 1970 to 1990.
2:00:43
And in the plan they literally said, by the end of the '90s we are going to be running out of space in the Bay and we're going to need to build some new cities, otherwise the region is going to become unaffordable.
2:00:55
And there are some areas where you could build cities that are really good for it.
2:00:58
And the part of the Bay that's the best place to do it that is five times bigger than anywhere else is the area of which we've acquired about 90% of the last 10 years.
2:01:06
So, this is a very old idea that we've dusted off and and obviously we're building something different than they would have built there in the '50s, but lots of roots in regional planning.
2:01:18
So, in terms of development, it it feels like, you know, AI has been the the mega trend over the last few years.
2:01:24
Most of the building that's happening around AI is happening in Abilene, Texas and just wherever the natural gas plant lines are and sort of all over America in pretty low population areas.
2:01:36
No one's really thinking that, oh, you know, Meta needs a data center right next to their Menlo Park campus.
2:01:43
But the AI mega trend also might drive up housing prices in San Francisco a ton.
2:01:49
A lot of people are predicting this based on the IPO schedule.
2:01:52
If OpenAI and Anthropic get out, there's a trillion plus in liquidity going loosely into the San Francisco housing market.
2:01:59
You could see some really crazy dislocations in that market.
2:02:06
Is that is that something you're tracking as an an accelerant of your plans? Yeah, 100%. >> Okay.
2:02:12
And I think it's and I think it's it's honestly it's more from the policy perspective cuz the the last time I mean, this has happened in the Bay Area periodically for the last 20 years.
2:02:21
The problem is we haven't done anything about it in 50 years.
2:02:24
And every time it gets worse and then there's a bit of a pullback and like, oh, it's going to be better and then it just comes back stronger than before, right?
2:02:31
And dot-com boom, then social, crypto, now AI.
2:02:37
And so, from a policy perspective, the argument that we've made is we need to get ahead of this because if we don't, this is going to be way worse than what we saw in 2017, 2018.
2:02:45
And when when it last happened in 2017, 2018 the problem is tech is going to get blamed for this. Oh, yeah. Of course.
2:02:56
It's it's it's it's wrong and it makes no sense because you just create all of these really well-paid jobs, but you're going to get blamed for it or we're going to get blamed for it.
2:03:02
And so, we as an industry need to get ahead of it and you saw attempts at this in 2017 and 2018. >> Yeah.
2:03:09
And Google and Apple and Facebook and I think Amazon up in Seattle all made these 500, 1 billion, 2 billion dollar commitments to go and build affordable housing. Yeah.
2:03:19
But what happened when you look at the numbers is they would maybe build a few hundred units or a few thousand units because building in existing cities is just so time-consuming, so expensive.
2:03:29
It costs a million dollars to build a small two-bed affordable apartment in San Jose. Yeah. A million dollars. That's a lot.
2:03:36
And it takes 11 years of planning.
2:03:38
Whereas our argument affordable housing for millionaires. Yeah, exactly.
2:03:42
Heavily subsidized by the taxpayer.
2:03:44
Whereas our argument is um if you create a place where you can build, you can get the private capital markets to build it and we are proposing to build 174,000 homes.
2:03:58
For context, 174,000 homes is more homes than San Francisco has built since 1950. Since 1950.
2:04:05
And sure, we should build a lot more housing in San Francisco.
2:04:07
The idea that you can solve the Bay Area housing problem The trends are the trends.
2:04:13
>> in San Francisco or in Menlo Park is insane.
2:04:15
No city in the world has ever solved a housing affordability issue without spreading out a little bit.
2:04:20
And then the question is do you spread out just by spreading out with sprawl or do you spread out and actually thoughtfully plan it and be able to build something really magical?
2:04:30
>> What what is what is the number of homes that uh that Calif- the California government has projected are needed to sort of solve the housing crisis? >> 3 million. 3 million? Yep. It just in California? Just in California. >> Yeah.
2:04:43
And the and the way and the way that they plan to make that And so, like in some ways you you could say like, okay, 174,000, like it's starting to make a dent. Yeah. It's less than 10%.
2:04:53
>> But it shows that you need projects at this scale to ever solve it because you're not going to solve this problem by like, oh, yeah, there's an empty lot, you know, behind this this, you know, in this neighborhood.
2:05:02
Let's put up eight units here, right?
2:05:04
It just doesn't That really doesn't make a dent, right?
2:05:07
>> Yeah, I mean, I think that's going to be a part of the solution, but you'll need I think California will need multiple California forevers and our hope is that by blazing the path and showing how you can how you can finance it, how you can
2:05:19
buy it, how you can work with the community to get the buy-in and to convince people that you actually care about it and you want to do it right and you want to do it well, we make it easier for others to do it. I
2:05:27
I will say we do have what I think is by far it's a very unique site.
2:05:32
The idea that you can put together I mean, we own 70,000 acres at this point. It's 110 square miles.
2:05:39
It's two and a half times bigger than San Francisco.
2:05:41
It's five times bigger than Manhattan.
2:05:43
It's bigger than Washington, D. C. by one and a half times. >> Wow. Wow.
2:05:48
And so, the idea that you can find that By the way, I drove from my meeting in downtown San Francisco to the site in 55 minutes the other day.
2:05:55
Now, that's not the case depending on how you time it with traffic, but it's pretty close.
2:06:00
So, it's going to be hard to do it at this scale, but we certainly should be finding 500 acres at the edge of or 1,000 acres at the edge of Sacramento and all different parts of LA and so on and building it at medium density and walkable and some industry and jobs.
2:06:17
But I think in California it's 3 million units.
2:06:20
It's about 2 million in Southern California.
2:06:21
It's about a million in Northern California.
2:06:23
And so, we come close to solving 20% of it.
2:06:27
And that's just one of our projects.
2:06:29
That's the expansion of a city called Suisun.
2:06:32
We're also looking at doing a second project on lands that we own on the west side so so on the east side of our property around a city called Rio Vista that could add tens of thousands of additional units.
2:06:42
So, we get close to solving 20% of Northern California's deficit, which is a big deal.
2:06:48
Talk to me about the transportation issue.
2:06:49
55 minutes when there's not that much traffic could be more.
2:06:53
Uh As an LA resident, I'm thinking Yeah, it's easy. Exactly. daily.
2:06:57
That's my daily uh commute.
2:07:00
So, But uh yeah, what has the Bay Area done recently?
2:07:03
I know the the bridge the Oakland bridge was improved.
2:07:08
Um but uh what's on the table in terms of like toll roads, congestion pricing, building new bridges, adding ferries?
2:07:14
Like are there lessons to be learned from Manhattan and how they they've solved things?
2:07:21
I've seen people be very pro congestion pricing, very anti-congestion pricing all over the place.
2:07:26
Um what's your what's your vision for uh what you would advocate for in terms of uh modernizing transportation in the Bay Area? It's a great question.
2:07:36
I I And there's so many layers to it.
2:07:38
I'll I'll try to keep it brief.
2:07:40
I'll give a slightly nerdy answer.
2:07:43
Um The first step in any kind of transportation planning is land use planning. Mhm.
2:07:49
Where do you put things and how do you lay them out to kind of eliminate the needs to go that much in the first place. Okay, sure.
2:07:54
So, you So, yeah, you don't want to have to go to San Francisco just to get a burger.
2:07:57
You should get a burger joint locally and same thing for, you know, all the different amenities.
2:08:03
>> And jobs in particular because in Northern California, we have this really really dumb distribution of jobs where the Northern California mega region increasingly works as one place from Sacramento all the way to San Jose.
2:08:14
I mean, you have people who live in Sacramento, they work in the Bay 2 days a week.
2:08:18
They do the commute, right?
2:08:19
There's a ton of people that live north of the Golden Gate Bridge and commute to San Francisco.
2:08:22
And then there's a ton of people that are really far south and commute up to the tech companies what not. Exactly.
2:08:27
And right now the challenge is basically all of the jobs are between San Francisco and San Jose and then up in Sacramento.
2:08:33
And then you have 4 million people in places like East Contra Costa County and Solano and Stockton and San Joaquin and there's basically no jobs.
2:08:40
So, what happens in the in the morning is all of those people get in a car and they have a 2-hour commute to Menlo Park.
2:08:46
The number of people who live in Solano County who work in Menlo Park and have a 2-hour commute each way every day would would blow your socks off.
2:08:54
It's half more than half of the county commute. I'll just leave it.
2:08:58
>> outside of the county.
2:08:58
So, it's it's completely it's completely insane.
2:09:00
So, the first solution, and this is actually our big contribution to the region, is to take a bunch of jobs and put them in the middle of the region, which makes life better for everyone who lives in Palo Alto, San Francisco, cuz you don't have all of those people sitting on the 101 or 280 coming down.
2:09:17
>> big office buildings for tech companies or big companies, big employers big manufacturing >> big manufacturers.
2:09:22
Um have you talked to companies?
2:09:25
Are they receptive to that?
2:09:27
Because there's sort of like a the first mover is going to have a rougher time, I imagine, than if they're already hey, we're already in Menlo Park and most of our employees are right here, at least the executives are.
2:09:36
Yeah, there's a lot of people that commute, but you know, uh maybe 50% of the employees only commute less than 30 minutes.
2:09:42
Like that's probably a pretty common stat for a tech company in the Bay.
2:09:45
Uh how are you thinking about pitching this to companies to go and take that leap and be the first one?
2:09:51
I mean we we start with there has to be a reason for them to be in Solano.
2:09:55
And And generally the ones that >> Not just price.
2:09:58
Not just not just pricing.
2:10:00
Um and And the biggest one that we found two big ones.
2:10:02
Um the first one is manufacturing.
2:10:03
You have this whole wave of companies doing manufacturing.
2:10:07
A bunch of them are headquartered in the Bay Area.
2:10:10
Um and then I think the sweet spot is you are a company, you figure out a new way to do X, you've raised 20 million, you have 20 people.
2:10:18
You've perfected it, now you've raised 100 million, and you need to build a factory.
2:10:22
And the factory is going to have 100 or 200 employees, and you want to build it somewhere.
2:10:26
Right now, what happens for virtually every single company, and we've spoken to 400 of them, is they say, we really want to build it in California, because we're still figuring out how the factory works.
2:10:35
>> Yeah, the factory is the product. >> is the product.
2:10:37
And if every time that um our software engineers or AI engineers need to go to the factory, they need to go on a plane and fly to another state, that's a 3-day trip. >> Yeah.
2:10:47
It's like, oh, it's 3 hours to go to Austin. No, it's not 3 hours. Yeah, yeah, yeah.
2:10:51
It's an hour and a half to the airport, then it's TSA, then it's flight, then you fly, then it's to get there, then So, it's a 3-day trip, right?
2:10:58
Um and our value prop is put the factory in Solano, because if you get in a car in Menlo Park in the morning, you can be in the factory in 80 minutes, and you can be back home >> Mhm.
2:11:08
and have dinner with your kids. And that really works.
2:11:10
Now, what means what that means is if you put the first factory there, then you go and you raise 500 million dollars. Mhm.
2:11:14
And you need to build factory number two.
2:11:17
Our value prop is we have so much land that if you want to build factory one, which is 100,000 square feet, Mhm.
2:11:23
we can reserve enough land around it for 5 or 10 years that you can put factory two, three, four, five next to it, and you can have them all in the same place, instead of having to solve this problem over and over and over again in a different place. Mhm.
2:11:36
Um Now, that means that we get the factory that employs 500 or 1,000 people.
2:11:41
Now, if you want to build a giga factory that employs 10,000 people, where you are really, really cost sensitive, maybe that still goes to Ohio, but that's okay.
2:11:49
But a lot of the cutting edge stuff would be in Solano.
2:11:52
And I to your point about AI, that's becoming even more important because >> down in LA, by the way.
2:11:56
There's a lot of startups that start in El Segundo, and they have, you know, 5,000 square feet, they're doing some R&D, and then once they start building larger factories, they move just outside of El Segundo, just a drive.
2:12:09
They might still have, you know, SpaceX was started in El Segundo, but eventually moved to Hawthorne and grew out of that, and then eventually Starbase in Texas.
2:12:17
And so, for that interim step in the San Francisco hard tech, deep tech community, that can make a ton of They don't have that exactly.
2:12:22
El Segundo doesn't have a lot of And then And And And even in LA, when you at least when we talked to a bunch of those companies, LA is becoming a kind of El Segundo and Hawthorne are becoming and Torrance are becoming victims of their own success, cuz they are fully built out.
2:12:35
There's no available land.
2:12:37
So, a bunch of these companies will tell you, we can't really build another factory here, and we still have R&D in the Bay.
2:12:44
So, it might be an even outlet for companies that started out here, they have a factory here, they have a bunch of talent in the Bay.
2:12:50
And to your point about AI, everyone talks about building the factories of the future.
2:12:58
How are you going to build the factories of the future?
2:12:59
You're going to build them with AI talent.
2:13:00
Where is 85% of the market cap in AI? In the Bay Area.
2:13:03
Do you think you're going to convince those engineers easily to spend every week flying to some other state?
2:13:10
It's a real It's a real competitive Yeah, it's like, hey, I know you can go work at Meta for 100 million dollars a year, but how about if you work for less than that in Utah?
2:13:19
Yeah, and then you fly on >> tough It's a tough pitch.
2:13:21
What is What does success look like for this year?
2:13:23
Uh one thing that I just appreciate so much about this project and this company is that most people uh come up with an idea like to make a new make a new city or make, you know, uh and they start running the calculations and they realize, okay, not only is this going to be hard, but it's going to take, you know, 10 plus years, so I'm not even going to start, right?
2:13:45
Cuz I want to be doing something where maybe I can see more tangible progress on a on a faster timeline or I need a billion users like 2 years from now.
2:13:52
Not not uh >> million ARR today. Today. Today. The bar is 3 months now.
2:13:59
Uh but but so you you've just chunked it out and you're just like, you know, um uh 10 years in, which is uh probably at the the moment where it really is hopefully more exciting than ever. Mhm.
2:14:12
Uh what is What does this year look like in terms of just pushing pushing the ball forward? >> Mhm.
2:14:18
Well, hopefully we'll break ground this year. Mhm.
2:14:19
Uh and so, I that would have seemed ambitious a year ago, I think.
2:14:24
But um I think there's a few things that kind of aligned, and um um So, if I just there's this really interesting thing that's happened where a lot of things have come together at the same time for us, where we've announced it What is it? 2 years ago.
2:14:41
And of course, it was very controversial, right?
2:14:43
You come to a community, and it's a guy with a funny accent, and he says, we want to build a major new city, which we haven't done in America in 100 years, so nobody even thinks that you can build new cities.
2:14:52
And it's like, oh, it's not just going to be a city, it's going to be a massive manufacturing park.
2:14:55
And by the way, we'll build the biggest shipyard in in in in America on the south end of the property.
2:15:01
And everyone is like, you guys are crazy, and we don't trust you.
2:15:02
Um But of what's happened over the last 2 years is we've actually done the work, we've put together this incredible team.
2:15:10
Um and so, we've built a lot of trust, and now there's a tremendous amount of support for it in the community.
2:15:13
And then what's happened at the same time at the state level and at the national level, I mean, think back to where we were as a country 2 years ago.
2:15:23
Abundance wasn't really a thing.
2:15:23
Build wasn't really a thing.
2:15:25
We didn't just have an election on affordability. Mhm.
2:15:28
Um reindustrialization was kind of beginning.
2:15:32
And so, at a macro level, there's been this massive shift towards um we need to do this, and that exists in California. Yeah.
2:15:39
And so, right now, where we are is um we had a big announcement this morning that we can talk about, but basically the the goal for this year is um the the stretch goal for this year, I'll say that is is is is to break ground.
2:15:53
And there's a lot of reasons for why that makes sense for Solano County, makes sense for California, it makes sense for the country. Sorry.
2:16:00
Going back, uh closing the loop on congestion pricing. >> Yes, sorry. Are you pro, con? What do you think?
2:16:07
I think it is I think the the direction that I'm most excited about is we should use congestion pricing to build a lot more capacity. Mhm.
2:16:19
I think it's really politically complicated to come and say, we are going to take this existing road that right now is free and make it paid. Yeah.
2:16:28
But I think people want a lot more capacity. >> Sure.
2:16:32
And paying for it with congestion pricing is great.
2:16:33
Um New York has proven that it I mean, I lived in London when they introduced congestion pricing, it clearly worked.
2:16:40
We've known that this works for a long time.
2:16:41
To build was a big fight to do it in in in New York. Yeah.
2:16:43
Um I think that self-driving cars are going to force us to do it, because there's a there's an induced demand with self-driving cars.
2:16:51
When the cost of driving a car is just the the financial cost, but you can be watching Netflix or drinking milk or whatever, people are going to drive more, we're going to send packages back and forth, deliveries are going to >> if you believe the self-driving car narrative, you have to be long suburbs.
2:17:09
You You have to be long suburbs, and then you have to believe that it's going to force us to price at least some of the roads and some of the capacity, because without it, it's induced demand, and there's just going to be more and more driving, right?
2:17:21
Because if the cost of your DoorDash delivery drops by 70% because you don't need to have the driver in the car.
2:17:27
You're going to get more DoorDash orders.
2:17:28
Um and yes, there's some we're intelligent routing that you can do have multiple people in the same car.
2:17:32
But that's what congestion pricing incentivizes.
2:17:35
But I think I think the political I think the political opening is to say, we're going to charge we're going to we're going to we're going to uh price these roads, we're going to use the part of that revenue or all of the revenue to fund the construction of them.
2:17:46
And that that also, I think, is a way to get it through politically, cuz in California, you have a environmental um uh interest group that doesn't really want to build highways, but if you price those highways, they are much more open to it.
2:18:01
And so, I think that's the grand bargain that you can you can drive.
2:18:03
The other thing that I would say is um what we hope the city will do at a at the scale of the mega region is if you look at the California mega region from San Jose to Sacramento, Mhm.
2:18:15
it's kind of like a donut.
2:18:17
In the middle of the donut is all of the property that we own. Mhm.
2:18:20
And part of the issue we have is that this used to be two regions.
2:18:22
It used to be the Bay Area and Sacramento, and they've become one, and they've grown, and they've become what would be I mean, if if if the Bay Area was a state, if Northern California was a state, there's 12 million people who live there.
2:18:35
It would be a seventh largest state in America.
2:18:36
And right now, we haven't really tied it together in terms of transportation infrastructure the way that we need to. Yeah.
2:18:44
That's why when you try to go from Palo Alto to Tahoe on a Friday night, it's such a disaster.
2:18:49
And so, we need to build more capacity there, and putting a major new city in the heart of the region is how you help pay for some of that.
2:18:55
What are you seeing on the Are you tracking the rebuild of the Palisades and Altadena in LA?
2:19:02
Obviously, we experienced the fires down here.
2:19:04
There's a huge amount of construction.
2:19:07
The hope is that it's really quick construction.
2:19:09
We've already talked to a friend who's I think finishing rebuilding this summer, which is pretty crazy, pretty fast.
2:19:20
Are there any lessons, learnings, just supply shocks to demand for building labor or are assets actually getting reallocated from Northern California to Southern California to to enable the rebuild or is that something that's not really changing your plans at all?
2:19:34
Are there Are there any lessons that you've learned from Yeah, I mean I I'm not deeply involved in the in in the rebuild.
2:19:41
We're far away from it, but my from from my vantage point, we are still at a point where permitting and coordination is the bottleneck.
2:19:47
It's not It's not the labor.
2:19:49
It's not the construction. It might become that.
2:19:50
Um I I think what it illustrates is just the complexity of building infill in general, just building in existing cities because you have thousands of people who own the land and they need to all agree on construction schedules and redoing it and so on.
2:20:06
I will say that there are some pretty um impressive success stories. I'll give a shout out.
2:20:11
I mean, Alexis Rivas at Cover has been doing great work in terms of both documenting the permitting challenges and then I think that they delivered several units already.
2:20:18
Uh and so I'm a huge fan of what they're doing.
2:20:21
I think the product is beautiful. Yeah.
2:20:23
Um and then >> ADU company. Exactly.
2:20:25
I think they started out as an ADU and now increasingly single family and then I think they have ambitions beyond that.
2:20:32
So I think that's an interesting area, but um I do think what the Palisades did, if there is one silver lining to it, um is that And it was it And it's partially because of when it came out with um Abundance and and other books of the topic, is it exposed a lot of people to just how insane the system is that we've built for permitting something in California.
2:20:56
And my my favorite example that I give is um I think a lot of the rules that we've put in place in California were genuinely well-intentioned. And I mean it.
2:21:02
I mean, some of them were just bad people using a pretense to put in place a rule that they knew exactly what it would do, but most of it was well-intentioned.
2:21:12
Um but um I think having two glasses of wine is a pretty good idea.
2:21:16
I think having 50 glasses of wine is a pretty bad idea. Uh and and >> here?
2:21:22
And and and regulations in California The regulations in California are like that.
2:21:26
Yeah, it's like every single one of those regulations, you look at it and you It's like it's a good idea.
2:21:31
Like it's a good idea to have more standards on heating in the building.
2:21:34
It's a good idea that the community should be able to have another review on the design. This is a good idea.
2:21:39
This is a good idea, but this is 50 years of legislators who each felt like they wanted to fix an issue, but they've created this layer cake of regulations that is very hard to get through, which actually is one of the things that we can deal with better than individual homeowners because in some sense we are permitting the entirety of the city at once.
2:22:02
And what that means is we're doing it wholesale, which it means we have to spend an insane amount of money on lawyers and consultants to do all of that work, but we can drive down the costs of the housing because we are spreading it out over so many units.
2:22:18
And personally, a big And a big factor is to permitting is speed, right?
2:22:19
Like even even if you're still dealing with the same number of regulations, if you can just turn turn approvals over faster throughout the build process, you can still have a tremendous impact by doing that.
2:22:33
>> I I want like a synthetic permitting office in like embedded in CAD or something.
2:22:40
So as you're designing your structure, you put a window there and it runs a simulation to say, "Hey, if you were to submit this, the permitting office would say no to that."
2:22:48
Or Or and then you slide the window over 2 in and it says, "Okay, now you're good."
2:22:52
And you just have like sort of red, green lights on everything you're designing.
2:22:57
So you're getting feedback instead of having to submit, wait for them to come back with the revision.
2:23:00
You like what you submit should be almost always approved and accepted, but there's still all of this uncertainty when you submit permits.
2:23:09
I think that's much closer than it might seem.
2:23:12
And I think there's a And even before we get to it, I'm really optimistic about AI tools that you basically embed in cities. Sure.
2:23:19
And then as they get these applications come in, um instead of people manually review them, you just do a pre-scan.
2:23:26
And I actually had discussions with legislators in the in in in in Sacramento who want to run those bills that you could basically I I actually it's very much what you said.
2:23:35
It's you can submit your application um and it just runs it through and it says, "We think that this is acceptable or here are some issues to fix."
2:23:41
So that's kind of the the front end to the client, to the architect or to the builder.
2:23:46
But then even to the employees who are working those jobs and approving it, you could see a system where it comes to them and it's like "Recommendation is that you approve it and the five areas where me, the AI, have the least confidence is these five. Go check them."
2:24:01
Cuz I think I think it's I think it's easy to verify some of the permitting authorities and some of the people who work there, but they're just trying to do their best. And some of it is real.
2:24:13
I mean, I I I don't know the details of it, but the the tragedy in the nightclub in in Switzerland, I was talking to a friend who um is on the ground and who knows it.
2:24:22
And And part of the issue allegedly there is you basically had a situation where um it was a small town.
2:24:28
There were some relationships um and the fire chief My My understanding is the fire chief or whoever was in charge of doing the inspections was friends with the club owner and they didn't want to deal with the costs of revising the material they had on the floor and then they had a fire exit and uh they locked it because they didn't want the teens to be sneaking into the nightclub.
2:24:53
And so you're like It's very easy to be really, really upset about the old fire department and be like, "This is stupid.
2:24:58
We should get rid of it."
2:24:59
But if you want to be able to walk in a restaurant or you have kids walk in a restaurant or walk into an office and feel like feel secure and feel secure in the environment, I think you need a balance and I'm hopeful that AI can actually give us the best of both worlds. Yeah, me too. Jordi, last question?
2:25:16
On the on the customer side for California Forever, customers being businesses that would come in and build facilities, are you within the range now where you can move You You've said you've talked to hundreds of companies that it would be potentially uh leasing or buying uh or, you know, building in California Forever.
2:25:37
Given that you're hoping to break ground this year, are you at a point where you can actually get more serious with these companies and say like, "Hey, like let's actually like put this into not go from like concept to actual like planning around building uh factories, shipyards, etc."
2:25:53
Yeah, I mean we've we've So the So we have we we have two timelines.
2:25:58
We have a default timeline, which is we're going through the usual process when we would break ground in 2028.
2:26:02
And that's what we've told the companies.
2:26:04
We said, "This is This is what we feel pretty strongly that we can deliver."
2:26:06
Um and actually part of where the 2029 breaking ground Sorry, 2026 breaking ground is coming from is a bunch of those companies have come back and said, "You know, we'll have Solano as a location.
2:26:17
We'll have putting the facility in the middle of what you're building, but we need to place it and break ground in 2026."
2:26:23
And so if Solano can deliver and if you can break ground in '26, we want to put it there.
2:26:28
If you can't, unfortunately, it's going to have to go to name another state, generally speaking.
2:26:34
Um and so we've brought that to the local elected officials and we've brought that to kind of economic development agencies at at the regional level and said, "Can we work on this?
2:26:43
Can we figure out a way to do the permitting in parallel?"
2:26:47
Because you don't want to lose these jobs, right?
2:26:49
>> and jobs that just go to other places and we have an opportunity to keep it here in California.
2:26:52
Has the How How How is the support been from local officials and even Sacramento?
2:26:57
It's I mean, night and day from 2 years ago.
2:27:02
And as I mentioned kind of in the beginning, obviously very controversial and and people didn't know what to make of it.
2:27:06
You look at it today, there's a there's a there's an open letter that that that I was put up this morning on our website in connection with a later announcement we've made that is basically this I mean, honestly, it's it's it's a love letter to California that is signed by the construction unions, by us, by a bunch of other people saying, "Hey, this is the state that used to be able to build the Golden Gate Bridge in 4 years.
2:27:28
We built We built Hollywood and we built the California Water Project.
2:27:31
Surely we can break ground on this quickly." And there's a moment.
2:27:36
And if you look at the signatures, it's it's the former speaker of uh the California Assembly, Bob Hertzberg, who wrote the legislation around how cities would expand.
2:27:45
It's Alan Bruton, who I think is one of the most respected urban planners in the world.
2:27:49
It's uh former Senator Bill Dodd, who who was senator for our district until 2 years ago.
2:27:57
It's countless local mayors, former supervisors.
2:28:00
And so there's there's there is a really incredible coalition that's come together um to say, "Hey, we can do this.
2:28:06
We can We don't have to kind of skip steps.
2:28:08
We can just do them in parallel and and break ground."
2:28:13
Um and part of that is companies saying that.
2:28:15
Part of that is construction workers saying, "I'm sick and tired of commuting for 2 hours.
2:28:19
I want to have a job 20 minutes from home."
2:28:20
Part of that is Solano had some old industries close down in the last couple of months.
2:28:24
They had a um there was a uh Budweiser brewery in Fairfield that was 50 years old that's closing.
2:28:31
There's a refinery that's closing.
2:28:33
And so there's a need to replace these jobs.
2:28:36
And so you see the outlines of this compelling argument to say, "Hey, this can be a solution to the very practical local issues of tax revenue and jobs.
2:28:46
Um but at a much bigger level this can be this can be a real moment for California where the state can show, "Hey, we can do big projects.
2:28:54
This isn't just high-speed rail."
2:28:55
And I think there's something deeply poetic about, um, doing that in 2026. Yeah.
2:29:04
I mean, it's 250th anniversary, right? I love it.
2:29:06
Growing up as a, growing up as a, as a kid, I can't tell you how many times I like saw a piece of land and thought out loud with whoever I was with, "What if we put this there? What if we put that?"
2:29:17
And every single time the messaging was, "Oh, like, yeah, technically you could, but it'll take so long.
2:29:23
Like, it's not, it's not worth doing."
2:29:25
And so, I'm so optimistic that, uh, uh, getting California Forever off the ground, active, a real place that people live and work and build will just inspire, uh, could be like really a real turning point for the whole state. So.
2:29:38
How many acres do you have now? Your empire's growing.
2:29:42
What's the total amount of acreage?
2:29:44
For California Forever, what was the number? >> Uh, 69,000 acres. Boom. [Music] Congratulations.
2:29:53
Thank you so much for coming. Hey.
2:29:56
Always a pleasure to have you in the studio. Yeah, yeah.
2:29:57
I'll come back when we break ground. We can't wait.
2:29:58
I, we can't wait for our first episode.
2:30:02
>> From there, we'll do it.
2:30:02
You can come over, we'll do it from there. Thank you so much. >> gentlemen. See you. We'll talk to you soon. Goodbye.
2:30:07
The New York Stock Exchange.
2:30:09
Want to, want to change the world?
2:30:09
Raise capital at the New York Stock Exchange. Ching ching.
2:30:16
Um, we have some news here from OpenAI.
2:30:20
Uh, this is, uh, sort of leaked through Foxconn, but, uh, from Dan uh, Nystedt says OpenAI will reveal, will unveil its first AI earbuds dubbed Sweet Pea in September this year and shipments are expected to reach 40 to 50 million units in 2027.
2:30:39
So, uh, you know, this is citing, uh, OpenAI's Chief Global Affairs Officer Chris Laine, Taiwan's Foxconn will do the assembly for these buds.
2:30:46
Uh, makes a ton of sense.
2:30:49
You know, you're chatting with OpenAI, you're chatting with ChatGPT.
2:30:53
Uh, you got Johnny Ive on the team, former Apple, um, and you put something together that's your always-on AI assistant that you're chatting with.
2:31:02
But, 40 to 50 million units, that's a lot.
2:31:05
So, I wanted to put some context around, uh, how how massive that would be.
2:31:11
So, um, the Amazon Echo in year two sold 11 million units.
2:31:17
Uh, the Xbox Series is the sequel to the Xbox, there's already an Xbox install base, 16 million units in year two.
2:31:28
Uh, the iPhone, the iPhone in year two, 17 million units.
2:31:31
The Apple Watch did 20 million units in year two.
2:31:34
Uh, the PS5, massive success, hugely anticipated product, the PS4 was almost a decade old, lots of people upgrading.
2:31:45
The PS5 shipped 30 million units in year two.
2:31:48
The Nintendo Switch did between 35 and 37 million units in year two.
2:31:54
AirPods now, AirPods did do 50 million.
2:31:57
So, if the, if the ChatGPT OpenAI earbuds dubbed Sweet Pea perform as well as AirPods, you could see 50 million units.
2:32:07
And the iPad, the iPad sold 55 million units in year two.
2:32:12
Uh, but it's a tall order. From the go.
2:32:14
It's a very, very tall order. Consumer hardware.
2:32:16
Uh, there is more news from Wayne Ma and Keiona Erlu.
2:32:18
Apple is developing an AI-powered wearable pin the size of an AirTag that is equipped with multiple cameras, a speaker, microphones and wireless charging. >> Shots fired.
2:32:27
The device could be released as early as 2027.
2:32:28
Yeah, wait, wait, why are you reacting?
2:32:31
I'm just like, like the, I feel like a lot of reason why people like do the pin or something is because they can't get all the features from the iPhone, but like they already have the iPhone, so why don't they just make that good?
2:32:39
I guess they probably will, but like what, do you think this is a good idea, Jordy?
2:32:44
I feel like I'd rather just have it in my phone.
2:32:45
Yeah, it is, it is crazy if you're in the Apple ecosystem and you have a MacBook, an iPad, a watch, an ear, earbuds, AirPods and the phone Look. and the Vision Pro.
2:32:56
It's like they got 90% of your body covered with tech.
2:33:00
Like, you're pretty good.
2:33:02
>> to a wired headphone guy.
2:33:02
I've been rocking Apple wired headphones.
2:33:07
>> So, if this was wired in, you'd be good to go?
2:33:08
Probably five, five years now.
2:33:12
Uh, no, no, I, I, I, I'm not in the, I'm not in the, in the market for this?
2:33:14
I'm not in the market for this, uh, but I got to wait and see.
2:33:19
I'll, I'll continue here.
2:33:21
So, Apple's trying to release their device as early as 2027 as well.
2:33:25
Such a product would position Apple to compete more effectively with OpenAI, which is planning its own AI-powered devices and Meta, which is already selling smart glasses that offer access to its AI assistant. >> Mhm.
2:33:35
Google also plans to release smart glasses in conjunction with Samsung.
2:33:40
Apple's development is still in the early stages and it could still be canceled. >> Mhm.
2:33:43
Still, Apple is endeavoring to move faster than usual to try to stay competitive because of OpenAI.
2:33:47
It's planning to man, manufacture roughly 20 million units at launch, the person added.
2:33:53
Apple's pin joins a growing portfolio of AI-powered products that tech giant has under development including AirPods equipped with enhanced sensors.
2:34:01
Like, yeah, I, I, it's kind of, uh, it's like, are people really going to have like their pin on and their AirPods in and have their phone?
2:34:14
Just how many AI-enabled devices do we need? What?
2:34:18
Shoulder pads, the smart cane, you want the, the, the breastplate.
2:34:23
>> the, there's the Apple, there's the Apple home device that's going to be like, you Okay, I actually do, I I mean, we have to, we have to get to our our next guest, but I do have a hot take that, uh, there might be a future wearable that looks like the Pip-Boy from Fallout.
2:34:38
Are you familiar with the Fallout series?
2:34:41
I'm not, I'm not, I'm actually not kidding about this and I'll unpack it.
2:34:44
So, basically, in in Fallout, you wear a device on your arm and you, and you turn it and it's basically a phone that's like glued to your arm and then on you can access your menus through here, right? Um, Yep.
2:34:58
and it's, and it was always like something fun that like the, the, you know, the cosplay community would build out.
2:35:04
Yeah, there's the Pip-Boy.
2:35:04
Uh, and and people have made real versions of this.
2:35:08
It has this cool retro aesthetic.
2:35:10
Uh, it's never taken off.
2:35:10
But, I've noticed that if you look at the live streamers like IShowSpeed, Kai Cenat, when they're out in the world, they often have phones strapped to their arms to read chat while they're going around.
2:35:25
Like, when I think it was Speed that went to China and he went on this world tour, he toured America, he keeps a phone strapped to his arm so he can use both hands.
2:35:33
And it feels like weird and cyberpunk, but it feels like a, like a glimpse of the future.
2:35:39
Like, we're all going to be living like Speed in the future maybe and maybe we're going to have phones or something like it glued to our arms.
2:35:45
That could just be an accessory that actually helps you glue the phone to the arm.
2:35:49
It could be some sort of modified device that's curved to wrap around your arm.
2:35:52
But, I feel like the, the end state is like more technology on your body constantly.
2:35:56
Uh, and that's like an easy one that people could adopt.
2:36:00
You've already seen, you've seen Apple sells the, the sock that you can keep your phone and a lot of people are wearing, uh, like almost necklaces with their phones.
2:36:09
So, their phone never goes in their back, never goes in their pockets.
2:36:12
It's always just here and then they just pull it out and take a picture or do whatever cuz they're so glued to their phone.
2:36:17
I think like a, an interim wearable is just something that makes your phone like permanently dangle here because the phone is powerful, it has a lot going on in that, but you just never want to put it in your pocket. You're obsessed. What do you think?
2:36:28
Yeah, I mean, the next step is just like a pair of glasses that you you mount the phone. >> Jordy.
2:36:34
It uses the camera to show you the world. >> Google made that. Google Cardboard.
2:36:36
You can take a cardboard box, fold it up and put it, put the phone on your face. Uh, anyway.
2:36:42
Yeah, I'm so, I'm so curious Yeah.
2:36:46
to see if, if OpenAI and Apple just happen to simultaneously kind of land on the very similar form factor >> and it actually becomes good enough that that they're in a, a race >> currently, you know, using LLMs like multiple times a day for search and research or whatever.
2:37:07
I'm not having these moments where I'm like, "Oh, if I could only just not get my phone right now." >> Yeah.
2:37:14
Especially because of the, the, I mean, the, these prompts, they take 5, 10 minutes.
2:37:18
I feel, I still feel like going into a, an agentic coding experience or or even just a deep research report, uh, it's going to, I'm going to spend a couple minutes there.
2:37:28
And so, the, the two seconds it takes me to follow my phone is not the rate limit.
2:37:32
Maybe if the models get faster, uh, but, uh, expectations are sky-high and it'll be interesting to see the, the reveal, how it's marketed, how it's pitched and then ultimately how it sells.
2:37:42
Let me tell you about Cognition.
2:37:44
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2:37:57
We have our next guest, George from Testudo in the restroom waiting room.
2:38:02
Let's bring him into the TVP and LTN.
2:38:03
George, how are you doing? Wow.
2:38:05
Good afternoon, gentlemen. >> Good afternoon. Good afternoon. Great to see you. >> Good afternoon.
2:38:10
We got, we, we, we got to, we got to ask first, where does the name come from?
2:38:15
Well, it's Latin, it's Roman military history, it's all things that we love. Okay.
2:38:20
>> It basically is Latin for Roman military formation where the shields are on all sides, the front, the back.
2:38:24
It's been in Lord of the Rings, it's been in many Gladiator films and, uh, that is exactly what our insurance is for the enterprise we work with.
2:38:35
We are that protective coverage from litigation that they they experience.
2:38:40
Yeah, talk to us about the the early customers, who you're going after with this insurance product, and then we can get into how AI plays a piece into your business.
2:38:51
Yeah, so this is a brand new category of insurance product.
2:38:53
This is generative AI insurance, so excited to announce and and launch that category today.
2:39:00
Category creator, let's Oh, yeah, of course.
2:39:06
And former Goldman Sachs VP, so gong Yeah, there we go.
2:39:14
Lot of gong-worthy moments. Love it. Yeah, exactly. So, brand new category.
2:39:19
You'll have heard of cyber insurance. This is AI insurance.
2:39:22
>> Yeah, so so walk me through Is this I build a tool with generative AI, and then at some point a lawsuit comes along because of a hallucination?
2:39:31
What are some of the downside risks that folks are insuring against?
2:39:38
Yeah, so enterprises are deploying AI for, as you know, a huge range of different things.
2:39:44
The enterprise is our target customer.
2:39:46
Any company in any industry deploying AI for anything.
2:39:49
Quite a a large market for us there, so our focus is to cover these enterprises with an insurance product.
2:39:56
So, if they are sued, for example, for copyright risk, for kind of bodily injury, personal injury, all sorts of different types of risk, we cover the legal costs, damages, and settlements associated with any liability risk that they might be exposed to.
2:40:12
How do you possibly underwrite this? There's so little data.
2:40:16
There's the Anthropic like billion-dollar settlement, Open AI might have some massive settlement.
2:40:22
At the same time, there's like two data points.
2:40:23
How are you actually planning >> Yeah, yeah.
2:40:24
I I mean, the the I'm sure a lot of enterprises are like So, it's one of those interesting challenges where like, you know, if you're if if you get you kind of need to balance that like if demand is too extreme, and if you're underpricing it, but I'm sure you have a lot of comps from again cyber insurance and maybe other insurance categories.
2:40:46
That we're seeing in the past.
2:40:48
>> Yeah, so that's the secret sauce, and that's what's taken us over a year to figure out how to price this insurance without needing to connect or invasively audit the enterprise that we're working with.
2:40:59
So, we can turn a quote around in the same day.
2:41:01
You know, companies like Goldman are not going to allow third parties to invasively integrate or audit their proprietary AI systems.
2:41:07
We can price and give a quote indicative terms within the same day.
2:41:12
So, that really is key to getting this product out via brokers, distributed to these enterprises, and the the pricing, obviously, is what we spent a huge amount of time doing.
2:41:21
We're using some very special new data that we have sourced ourselves.
2:41:26
We're using lawsuits and basically have ingested the federal and state US lawsuit databases.
2:41:30
We've taken all of the generative AI lawsuits, and then we break down those lawsuits in specific causes of action, so we know exactly what's driving the losses where in the US.
2:41:42
Off that data, we then took it to Lloyd's of London, the largest specialty insurance market in the world, where we source all our capacity, and essentially presented our view of the frequency and severity of the generative AI liability risk in the market.
2:41:55
And, you know, we're super excited that we're launching the product today with nearly a billion dollars of of risk capital backed by Apollo Specialty in in Lloyd's. Let's go. Another gong hit. Two gongs. Love it.
2:42:13
What what what I mean, obviously, I'm I'm sure every policy is different, and you guys are acting as the You guys are the broker, right?
2:42:21
So, you're not actually deploying your own capital, or how does that work? >> Yeah.
2:42:28
So, we're called a Lloyd's cover holder.
2:42:30
In the US, a similar structure is called an MGA.
2:42:32
It means we have full delegated underwriting authority.
2:42:34
We have the pen, essentially.
2:42:36
So, the insurer has the balance sheet and the risk capital.
2:42:40
We essentially have the pen.
2:42:42
We do all the technology, the infrastructure, the pricing, the data, the monitoring, the portfolio controls, and we take submissions from insurance brokers, and it's our decision yes no as to whether we cover that company or not, again up to 10 million dollars or 8 and 1/2 million dollars of of risk for those different areas.
2:42:59
And very excited to, you know, be working with enterprises deploying And so, how does a claims process work?
2:43:08
If I'm if I'm, you know, if I'm an enterprise is running some gen AI product, and and uh some they they end up getting sued because of that, like what like what typically qualifies versus just a company just being like generally negligent, right?
2:43:26
So, like if somebody's driving a car and they're drunk and they crash into someone, the insurance company is maybe going to like freak out.
2:43:34
>> says like, "Please go download all of Netflix to train a video model."
2:43:36
Like that's pretty blatant infringement.
2:43:41
I imagine that wouldn't be covered.
2:43:44
Yeah, so I'm hoping we're not going to be doing too much of paying out claims, but obviously we will be paying some to prove that the product is useful, but the claims are being managed by our capacity provider, by the insurer in Lloyd's.
2:43:58
And essentially, you're right, we'll be getting kind of logs, we'll be getting all the information associated with exactly why there's been a lawsuit.
2:44:06
What's really interesting from all our legal data is only 4.
2:44:08
9% of all of the generative AI lawsuits in the US market have been caused by model hallucinations or performance-related issues.
2:44:17
So, you would think that the model performing, you know, incorrectly is driving a lot of the litigation, but that's not actually the case in the data.
2:44:26
Obviously, a lot of copyright risk, a lot of patent infringement, a lot of D&O claims, things like that.
2:44:30
So, if you over-index too much on the performance of the model rather than where that enterprise is deploying the AI or which industry or or what type of revenue that company has, you will miss the driver of the liability.
2:44:43
So, we're very excited to, you know, talk through our approach.
2:44:48
Uh how scenario in the future where people have a bunch of agents deployed working on behalf of a company, and let's say an agent goes a little haywire, starts bribing bribing a bunch of officials.
2:45:00
Like how how much are you like thinking about like kind of like the sci-fi future where companies have more basically robots working for the company than uh Yeah, if AI kills everyone, I definitely want a payout.
2:45:16
That's important to me, cuz I'll be on a spaceship going lightspeed away from the from the gray goo, boom, and I expect you to send the wire immediately. Exactly.
2:45:29
Product two for us is AI agents, as you said.
2:45:31
Product three is AI and robotics.
2:45:35
And so, we're getting inbounds for both of these things now.
2:45:36
We are going to be multi-line across, you know, the whole AI economy, and I really believe that AI insurance is the biggest horizontal play, picks and shovels for the AI economy.
2:45:47
Everything in in every industry is insured up to a certain level, so you know, we think this is going to be a massive category.
2:45:53
We're excited to be defining and leading it.
2:45:57
And, you know, that agent product is number two for us, but we don't see a huge amount of enterprise deployment of agents yet.
2:46:03
We think obviously these types of insurance products can unlock that adoption.
2:46:08
And you know, you heard last week with JD from with coverage, companies like Coalition have done a really good job on the cyber insurance side.
2:46:16
They're a great comparable for us, and you know, huge fans of their work.
2:46:19
You know, this is not cyber insurance, this is AI insurance, and so we're very excited about the future roadmap and the category that we're creating.
2:46:28
Talk about policy concentration, diversity of revenue, and and policy size for you.
2:46:33
I imagine that some of the big labs would probably love a billion-dollar policy.
2:46:37
They'd take 100% of what you have to sort of allocate.
2:46:43
Are you looking for 100 to spread that across 100 companies at a 10 million-dollar policy cap, a thousand at 1 million dollars?
2:46:50
Like what's the right shape of diversification for your business?
2:46:55
Yeah, that's a you That's a genius question and exactly what we're focused on.
2:46:58
Obviously, coming from a capital markets perspective, you know, diversification across jurisdiction, industry types, revenue bands, AI models deployments, that is exactly right.
2:47:09
We are weaving a basket of of diversified clients, which means we can manage risk on the on the portfolio, on the on the whole portfolio.
2:47:19
>> and and then walk me through uh a YC company, for example.
2:47:22
They they raise 5 million, 50 million-dollar valuation or something.
2:47:27
They have a couple, you know, customers.
2:47:29
They you know, they're making some money. They're still early.
2:47:33
They're deploying a bunch of generative AI products.
2:47:34
Should they get AI insurance at that point?
2:47:37
There's sort of a normal function when you do a series A of getting, you know, D&O insurance, a couple other pieces of insurance when you leave the garage.
2:47:47
How quick on the on the life cycle of a startup should someone consider this?
2:47:54
Yeah, so unfortunately, this is not a a product for startups.
2:47:56
This is for kind of mid-market enterprises who are deploying AI.
2:48:00
So, we are not uh currently working with AI vendors or the base model providers.
2:48:04
We think there's too much concentration risk.
2:48:07
We've seen the number of lawsuits that have hit, especially the the base model providers.
2:48:12
So, as you say, like if we were insuring some of the big guys up to a billion dollars, I'm sure we'd be paying a hell of a lot of that out in claims already.
2:48:19
So, um we are focused on enterprises, you know, things that we're getting from architectural companies to law firms to, you know, banks to, you know, any anything under the sun, really.
2:48:29
So, those are the target customers, and we start, you know, in the mid-market.
2:48:33
What about non-legal negative outcomes from AI?
2:48:37
I'm thinking of uh I run a I run a company.
2:48:41
I let a chatbot talk to some customers.
2:48:44
The customers uh prompt inject the the bot and they get refunds or discounts that I didn't want to give them and it happens sort of quickly and I'm like, "Ah, they they they took like some scammers came in, hacked the bots and they took 20 Gs off me.
2:49:00
Like, can you do anything for me?"
2:49:03
Yeah, I think um we absolutely could do something for you.
2:49:05
It depends whether this is a like a first-party loss so you say like a financial loss that you've suffered yourself >> Yeah.
2:49:11
or you've been sued, right?
2:49:11
This is a a liability product.
2:49:12
So, this is protection from litigation.
2:49:17
So, um first party is definitely in the hopper for us, but this first product is third-party litigation and uh the liability exposures that enterprises are are are exposed to kind of out of the box um when they're deploying these AI systems. Fantastic.
2:49:30
Well, >> Did you uh have you announced any funding yet or what's the story there?
2:49:36
We don't announce funding.
2:49:36
We don't believe that's the purpose of this company.
2:49:39
I mean, you guys have Cenra and David Cenra on all the time and he says the focus is building a durable business.
2:49:45
Honestly, that's what I'm focused on with our moat within within the data, within the licenses, within the capacity, the balance sheet, and obviously our incredible team.
2:49:52
And and honestly, I'm not >> Hit the gong for for not announcing that he's not announcing anything, but but building a durable business.
2:50:03
>> I'm reading that as we're building a durable business that has raised a little bit of money. Maybe a lot of money.
2:50:09
Maybe a lot, but No, I love it. I love it.
2:50:12
When you're ready with other announcements, uh please come back on. This is a lot of fun.
2:50:16
>> Yeah, yeah, very very cool and uh >> Congratulations.
2:50:18
I mean, honestly, like having having the backing of Lloyd's is is like probably harder to get, bigger, more important to the core business than grabbing a couple of checks from some Silicon Valley investors.
2:50:29
So, that's why we're ringing the gong.
2:50:31
Yeah, yeah, good luck to any YC startup going into Lloyd's of London.
2:50:35
It is a a den of uh you know, of underwriters.
2:50:39
Good luck going to Lloyd's of London without an accent like this. I'm serious.
2:50:44
And if you wear the wrong colored shoes or the wrong type of suit, Okay.
2:50:49
um you will be laughed out of that building. So, That's your moat. That's your moat.
2:50:53
I mean, honestly, they're like, "Oh, what's what's your moat?"
2:50:55
Uh the moat is I know exactly what kind of suit to wear. >> Yeah.
2:50:59
And the and >> AI can't disrupt that.
2:51:01
AI cannot disrupt those relationships.
2:51:03
So, uh You You both are invited to Lloyd's of London and a tour of the inner sanctum of underwriting by by our head of insurance and my co-founder, Mark.
2:51:12
So, we'd love to have you there.
2:51:14
You know, if you can drink Guinnesses at high velocity, we'd also love to welcome you to Leadenhall Market, the home of insurance boozing, but you won't find us there.
2:51:25
We are we are hard at work 24/7 around the clock and excited to launch the category. That's amazing. Congratulations. >> Where are you based?
2:51:34
We're in between SF and and uh London um but looking to expand into kind of New York and and other other cities as well. >> Amazing. >> Amazing.
2:51:42
It's so great to meet you, George.
2:51:43
Congrats to the whole team.
2:51:45
Not congrats on the funding, congrats on uh the incredible partnership and all the progress. Yeah.
2:51:50
We'll have you back on soon. >> Great. Thanks, gents.
2:51:53
>> Have a great rest of your day. We'll talk to you soon. Goodbye.
2:51:56
Gusto, it's the unified platform for payroll, benefits, and HR built to evolve with modern small and medium-sized businesses. Get on Gusto.
2:52:05
phone and then also head over to Shopify.
2:52:07
Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with the AI agents. In seconds. And so fast. Yes.
2:52:16
I will routinely just buy the products of our guests if if they're on Shopify.
2:52:25
I'll just buy it during the interview.
2:52:27
It's one of my favorite pastimes. I really love it.
2:52:29
>> Well, we have our second in-person guest in the TVPN ultradome, Ara Khazarian from Ramp. He is the economist. We'll bring him on down.
2:52:36
He's here in the TVPN ultradome.
2:52:39
So, welcome to the stream, Ara. Good to see you. How you doing? Good to see you.
2:52:46
Welcome to the ultradome. Thank you so much.
2:52:47
For those who uh have been living under a data center, please introduce yourself for everyone.
2:52:55
>> My name is Ara Khazarian.
2:52:55
I'm the economist at Ramp.
2:52:56
Time and money saved both. >> Let's go.
2:53:00
I uh I research data on where businesses spend, where they're investing, where they're pulling back, and what's growing.
2:53:06
Our flagship research is called Ramp AI Index.
2:53:07
Tracks the size of the AI economy. >> Okay.
2:53:10
Well, uh we're going to we're going to have you I I think Tyler had might have some beef with you.
2:53:14
We'll see, maybe you agree.
2:53:15
Because there's this article in the Wall Street Journal that I want to go through.
2:53:18
It says, "CEOs say AI is making work more efficient, but employees tell a different story."
2:53:25
Tyler took to the timeline to say, "Auto manufacturers say cars are making more travel inefficient.
2:53:32
Horses tell a different story."
2:53:35
And so, he's having fun with it, but there is an interesting stat in this Wall Street Journal article.
2:53:39
I don't know if you've had a chance to read this, but uh basically, they asked workers and C-suite executives, "How much time do you think you're saving each week by using AI?"
2:53:51
And the C-suite said only 2% of C-suite executives that were surveyed by the Wall Street Journal said no time at all.
2:53:58
"I'm getting no benefit from AI."
2:54:00
Workers, 40% of workers said AI's not doing anything for me.
2:54:03
Con- uh conversely, um 19% of executives, the C-suite, said they were saving more than 12 hours a week and only 2% of workers said they were saving more than 12 hours a week.
2:54:16
So, you have this huge disparity, at least in the reporting from the Wall Street Journal.
2:54:18
How are you interpreting this piece?
2:54:21
>> There's two things going on here, right?
2:54:22
You've got either the fact that the surveys may be the improper way of measuring this cuz surveys don't always correspond to people's revealed preferences.
2:54:29
So, if you look at actual spend on AI models, it doesn't tend to reflect uh you know, this kind of hesitancy to use them or any lack of lack of adoption. Yeah.
2:54:38
Especially because when we track spend, we're not just seeing that people are blowing a ton of money on models.
2:54:42
We see that the spend that they're doing is becoming uh larger and you know, they're renewing their contracts more, they're doubling down on them, they're typically extending those contracts out.
2:54:50
That's not the type of spend that you do or investment that you make unless you're actually seeing some benefit from it.
2:54:56
>> And specifically, I think a year ago, sort of like mid-AI boom, post-ChatGPT, there were a lot of startups that came out and had uh you know, we're doing vertical AI for this, vertical AI for that, AI SaaS.
2:55:08
And a lot of people saw the charts that went from zero to a hundred million dollars in 12 months, eight months, two months, two days.
2:55:14
And people were wondering, is it going to be sticky?
2:55:18
Are the venture capitalists going to get burned?
2:55:20
Are these going to be flash in the pans?
2:55:21
Are they going to get steamrolled?
2:55:22
But from the data that you've pulled, it seems like a lot of these companies, probably not all of them, but a lot of them have become sticky. Yeah.
2:55:27
The spend has been recurring and it's growing, but tell me more about what you're saying.
2:55:31
>> And well, that's the second part of why the surveys might not be the best way to measure this is that the this kind of adoption takes a long time to actually take place.
2:55:38
We're still in our own tech bubble. >> Yeah.
2:55:41
Where So, I just posted this uh data about Cursor and Anthropic. >> Okay.
2:55:45
And every time I post about Cursor and Anthropic, it gets way less engagement. >> Why?
2:55:49
>> Because a lot of people don't know what Cursor and Anthropic are. Oh, interesting.
2:55:52
And not to no shade about Cursor and Anthropic.
2:55:54
Like, great technologies, but when I go >> I literally thought you were going to say the opposite that like the Cursor fanboys and the Anthropic fanboys are like down-ranking you or something.
2:56:03
>> addressable social media market for content about Anthropic is just significantly lower, which is a lot of my followers, particularly those in the accounting space, even people Sure.
2:56:13
don't are still new to understanding well, what are the dynamics in this market even for Anthropic, which is you know, the second largest player.
2:56:20
>> So, Jordy had a Jordy had this this thesis.
2:56:22
We didn't really fully run the analysis, but I'd love to sync it up with what you're seeing because he was saying that there's a vibe war on X about the hottest lab.
2:56:31
Everyone over the break was obsessed with Claude code. >> Yeah.
2:56:35
And then Jordy was saying like, "Let's try and marry that with what we're seeing in the app store."
2:56:38
And look at where things are ranking.
2:56:40
There's the discussion that's happening, but then you go back to the app store and you see a very different picture.
2:56:45
Uh what what stuck out to you about the the the the the vibes versus public perception in the consumer market?
2:56:51
And then maybe we can marry that to what we're seeing in the Ramp data.
2:56:56
Yeah, I mean, that that was really consumer.
2:56:57
Just just just cuz you have consumers on X just saying, "This company's cooked. That's Yes. cooked."
2:57:04
And then you just look at like the actual reality in the charts, which shows acceleration and it just shows that social media reactions in real time are not even actually driving like Yeah.
2:57:14
macro acceleration in the even downloads of Sure. Sure. Sure.
2:57:18
That has less to do with enterprise. >> Yeah.
2:57:21
And then And then what are you seeing in the spend data?
2:57:22
A lot of those consumer trends start to reflect in business trends as well.
2:57:26
So, in our data set, we see that OpenAI has the highest adoption rate amongst US businesses.
2:57:32
It's actually about 35% and to be clear, only about 46% of businesses on our platform are paying for any AI model service at all.
2:57:38
The vast majority of them are probably using OpenAI in some way.
2:57:42
>> 50% just being like horses. Yeah.
2:57:42
Horses are actually fantastic. Yo, yo, yeah. Unpack that.
2:57:47
Is it Is it that they're just not paying, but they're using free tiers?
2:57:51
Is it that maybe they're paying, but on a personal basis and the CEO is paying for a ChatGPT Pro subscription or Claude code or something?
2:58:01
And then the when they go to work, they're not expensing it, so it's not showing up on a Ramp card.
2:58:07
There's a couple of dynamics, again. Yeah.
2:58:09
Like, we already get criticism for having a data set that is probably a little bit more tech forward. >> than other data sets.
2:58:17
Uh and we're transparent out about that and we think that's an important part of doing this kind of research.
2:58:22
At the same time, I think that we're likely underestimating AI adoption in some ways because we don't capture free usage.
2:58:26
We don't cap cuz we only see anything that's associated with Ramp card spend.
2:58:31
We don't capture uh employees using their personal accounts.
2:58:36
And then even when you do capture all that, well, where do you draw the line on what AI usage actually is?
2:58:38
I mean, this is a big debate happening in these sort of AI economics research, particularly as far as how we're going to measure the labor market impact.
2:58:46
Cuz the real question you want to answer is are companies using AI?
2:58:50
And then secondarily, how intensely are they using AI? >> Yeah.
2:58:53
And it's very difficult to measure.
2:58:55
You can't just use dollars to measure AI intensity. Yeah. >> Right?
2:58:58
Because the models are getting cheaper over time. >> Sure.
2:58:59
So, comparing those dollars spent over time is not going to be helpful to you as a researcher.
2:59:05
Uh and then second, where do you draw the line on what AI usage is?
2:59:07
And then what kind of job can actually be automated?
2:59:11
So far, the research has tried to define job families with characteristics that are exposed to AI and likely to be automated.
2:59:18
That research has it has, you know, gotten plenty of criticism itself. >> Yeah.
2:59:23
Uh especially as the AI models develop and it's they start to be capable of doing more and more. >> Yeah.
2:59:29
So, now the research community is coming around to well, we need to figure out which companies are using AI. Get a data set.
2:59:33
Ideally, that's something that private sector is working on.
2:59:36
This is why we put out our ramp AI index research. >> Mhm.
2:59:39
Tracks which businesses are using AI and spending out in some meaningful way and how they're using it.
2:59:43
And then ideally, be able to marry that with payroll statistics.
2:59:47
And see, well, are there shifts happening in this part of the labor force or others?
2:59:50
Yeah, the the the the thing that is going to be like, I don't care if a CEO does a layoff and says like, we're getting we're doing this because we're getting efficiency from AI.
3:00:00
Cuz the incentive is just to like blame it on AI efficiency instead of we over hired or business isn't growing as fast as we thought it was or all that stuff.
3:00:09
Like, you actually want like to to for the labor replacement kind of theories uh to be proven, you have to see somebody like actively switching spend from payroll to to uh tokens. Yeah.
3:00:22
And you're going to have to see it over a long period of time.
3:00:26
I agree that when you see these layoff announcements, the CEO might may or may not say that it's about AI, but that's not going to matter when you know, hundreds of thousands of people get laid off all the time.
3:00:35
It's sort of a drop in the massive size of the labor market.
3:00:39
You really want to track these changes over time as they happen, particularly as they affect other sectors. >> Sure.
3:00:44
And whether or not those sectors that are how seem to concentrated employment effects are that have an AI story.
3:00:50
Have you been surprised at all at the types of individual companies that are uh adopting AI?
3:00:54
You know, are you seeing a difference?
3:00:57
Have you broken out like professional services firms?
3:00:58
So, like accounting, tax prep, legal versus SMBs like retail and or uh you know, like let's say like car dealerships Yeah. or things like that.
3:01:12
>> A lot of the early adoption is where you'd expect.
3:01:13
I mean, the vast majority of tech tech companies, for example, we do track their adoption and it's been high for a long time.
3:01:19
The vast majority are already using some AI models.
3:01:22
Finance directly follows that.
3:01:22
And I think that makes sense, especially for tech, right?
3:01:25
These are the tools that were developed by engineers for engineers and therefore the best productivity enhancing tools were things like cloud code or the code AI code editors.
3:01:36
Things that would directly help the people who were building the uh technology in the first place.
3:01:39
What we're going to start to see soon though is how it's going to affect other parts of the labor force, especially now, you know, cloud co-worker is out.
3:01:47
Increasingly, there AI agent tools that can automate and have access to broader context of a worker outside of like a coding tool.
3:01:54
So, you could start to imagine a more typical office worker benefit from these tools now. Mhm.
3:01:57
And that's where we're going to see the greatest productivity gains as those tools proliferate. Yeah.
3:02:03
And we're starting to see that, you know, change in business strategy now from the model companies themselves.
3:02:07
Anthropic is doubling down on subscriptions, increasingly growing their subscription revenue.
3:02:12
They used to be sort of seen as like, oh, it's just about APIs.
3:02:14
That's their business model.
3:02:15
No, they're like really leaning into the consumer side and the employee subscription side. Mhm.
3:02:21
Um you know, I think we're going to see that from Open AI and a lot of competitors, too. >> Yeah.
3:02:25
Can you help me understand a little bit more about how you would theorize about the substitutability between uh payroll dollars and AI spend?
3:02:35
Because what if I see a public company CEO lay off a thousand people, like that might be half a billion dollars of payroll spend over a year.
3:02:43
And if I'm not seeing well, a quarter billion dollars of AI spend, I would not attribute it to AI just instinctually because I feel like if there was a substitute effect, it would be well, you know, AI an AI worker is half the price.
3:03:03
Not an AI worker is 1,000th the price.
3:03:06
So, sure, yeah, get, you know, spend spend $100,000 on AI and lay off a thousand people that was costing you a hundred million dollars.
3:03:13
That just doesn't clock for me, but am I off there economically or do you think there's something to that?
3:03:19
Our early research right now shows that the the job profiles that are going to be affected most by this transformation are those most marginally connected to the workforce.
3:03:28
So, you can imagine something like a labor marketplace like an Upwork or Fiverr.
3:03:32
Like, this is where people go to it's anything from designers to software engineers to uh >> Yeah, we got to check in we got to check in on on some of those businesses cuz I used to think like, oh, you want a song made for like a video?
3:03:45
Like, go to go to go to Fiverr. Go to Upwork.
3:03:48
Oh, you want to like a simple website written for SEO.
3:03:52
Like, a lot of SEO blog post writing was done through >> one-off tasks as well.
3:03:58
And instructing a human being to do that task is not dissimilar from instructing an AI. >> of know Yeah. Yeah.
3:04:04
>> We're not entirely sure.
3:04:05
Uh but for the tasks that it's figured out pretty well, I think most companies are very receptive to evangelizing it fairly quickly.
3:04:10
>> Are you uh as part of your research, are you actively trying to replace your own work?
3:04:15
Like, you know, an algorithm like you were an economist >> at Ramp.
3:04:18
Your job is to look at all of our data and turn it into easy-to-understand reports.
3:04:25
>> what do you Yeah, what's your tool chain?
3:04:26
In the ex- I mean, I for a couple of reasons, I just have to be on top of it all of it all just so I can talk about it effectively.
3:04:33
>> But for the experimental early stage research process, they're so good.
3:04:37
I mean, even a a rudimentary aspect of most economic analysis is just doing like a seasonal adjustment on your data. >> Sure.
3:04:46
And it's really just integrating a Python package.
3:04:49
But there's a lot of different times where you might use this or that package.
3:04:51
And if before you might have to write that code yourself to say, hey, do this seasonal adjustment, >> Yeah.
3:04:56
you can now just instruct it to like swap in and out packages and really check your results across different methodologies.
3:05:03
So, it really does make my work a lot better cuz it allows you to you know, particularly for my job, you know, you everything I do is public facing.
3:05:10
So, all my research is just out there.
3:05:12
But you really only see 10% of what I ultimately worked on. Mhm.
3:05:14
A lot of the research threads that I go down never see the light of day. >> Sure.
3:05:19
And so, AI allows me to experiment a lot more, check a lot of different results faster, and ultimately get through the bad ideas more quickly so I can focus on the good ones.
3:05:27
Do you think without AI, you would need like a bigger team in order to put out the the amount of research that you put out? >> For sure. Yeah.
3:05:35
I mean, for me, it's certainly been a productivity enhancing tool. Sure.
3:05:38
Um but I haven't figured out yet how to do the uh the more multimedia stuff.
3:05:43
Like, I encourage [Music] >> haven't figured out yet how to do the the more multimedia stuff.
3:08:27
Like I increasingly am making my own videos.
3:08:31
Like I'm still doing a lot of my own editing.
3:08:33
Like I make my own like promo images. I make my own charts.
3:08:36
I don't have I haven't found the AIs to be helpful for me in that.
3:08:40
I think they need to build the the the RL environment for round like premier some video editing.
3:08:46
No, my yeah, girlfriend's always telling me that to work on that aspect.
3:08:48
I'm just I'm just I'm just thinking about you all the time. I don't want that.
3:08:54
Uh there were some there were some fud around OpenAI towards the back half of last year. Is OpenAI cooked? What does the data say?
3:09:04
There's no definitive leader in terms of the AI race.
3:09:06
Uh market's changing really quickly.
3:09:09
OpenAI has a distinct advantage as far as distribution.
3:09:12
It's at the most businesses.
3:09:13
Now, Google also has a distinct advantage.
3:09:15
Cuz it integrates Gemini for free across all of Workspace.
3:09:19
So, in our data set, I think we likely undercount uh Gemini adoption.
3:09:21
But OpenAI just by nature of being kind of this consumer default, uh if you're a company that is going to make some early business investment in in AI model for your employees, it's kind of a no-brainer often times just go with hey, what do you know about as a consumer and what do your employees know?
3:09:40
And so, for that reason OpenAI I think is in a very safe place.
3:09:44
Uh but it's a pretty tense race and we have seen particularly in the sort of product layer, you know, large incumbents being uh losing a lot of market share very quickly to like a new entrant.
3:09:57
GitHub Copilot a couple years ago, that was the major that was pretty much the only AI code editor available for enterprise.
3:10:01
6 months later, Cursor comes out and it's at 50% market share.
3:10:07
So, I don't think any company should feel particularly comfortable even if they have the enterprise backing and distribution.
3:10:12
Yeah, only the paranoid survive. So, OpenAI's growing.
3:10:15
Anthropic's also growing 1.
3:10:18
6 percentage points to 16.
3:10:18
7% of businesses using uh Anthropic.
3:10:22
Big biggest spenders in the tech sector leaning heavily on API spend.
3:10:27
And then Google adoption growing as well.
3:10:29
So, basically it's it's all good news.
3:10:33
There's still a little bit of a horse race, but everyone's making across the finish line for the most part.
3:10:35
People were worried over the last couple months well, Claude Code is getting so much better.
3:10:40
Is this going to automate away things like Cursor or obviate it away?
3:10:44
And what we just found in our latest research is that uh Claude Code is definitely accelerating in its uh adoption, but Cursor if you look at dollars spent, like the pie is still getting bigger, too.
3:10:54
So, there are enough people entering the market such that And also, by the way, enough people that are enough companies that are willing to buy multiple tools and are still experimenting where at least finding that you know, they can afford to to have multiple tools at their disposal.
3:11:09
So, neither of them are losing you know, revenues and they still continue to grow.
3:11:16
I imagine that as businesses scale, at a certain point they want to go with an enterprise plan, they want a contract, they want billing.
3:11:23
Um do you think you'll maybe have to supplement your data with survey data because you might see a drop as a bunch of businesses say, hey, we don't want you training on our stuff.
3:11:34
Let's just sign some big master service contract and we'll wire you the money or something.
3:11:38
Or or how are you thinking about adjusting to that?
3:11:39
I think that the value of Ramp data and is that we see actual money movements.
3:11:44
And you can go to another researcher if you want survey data.
3:11:49
I think what we do well is that we're focused on what we uniquely have access to.
3:11:54
There's no data set that tracks where and how American businesses spend, at least not one that's available to the general public.
3:12:01
So, our research tries to focus on that and track those. That's great.
3:12:04
And you're pushing the Ramp sales team to get even more businesses on on the Ramp platform. Feed me.
3:12:12
Feed Every time you sign up for Ramp, you build my data set.
3:12:14
All anonymized, all aggregated.
3:12:16
We don't do anything like that.
3:12:18
But for that reason, I this is the at the start of this podcast probably the first time I ever pitched Ramp.
3:12:22
I'm like pretty separate from the sales team for that reason.
3:12:27
Uh yeah, the real nightmare is when Ramp rolls out enough AI tools that you have to classify being a Ramp customer as an AI adopter and then 100% of the data is AI adopters.
3:12:37
Yeah, this research at some point is going to become useless when it hits 100.
3:12:40
I mean, imagine if there was like a Ramp internet index in the '90s.
3:12:44
And how many people have websites?
3:12:45
And we were still talking about that 20, 30 years later praying that people are still interested in it.
3:12:51
It would be would be useless research.
3:12:53
>> But at the same time, there's a ton of interesting research to be done deeper in the internet stack.
3:12:57
Well, what clouds are you on?
3:12:59
What databases are you using?
3:13:00
What front-end frameworks are you using?
3:13:02
We're hiring on economics lab if you're great ideas if you're I know you got your talent signing today.
3:13:08
Ron Ron helped with the the census at one point.
3:13:11
>> I did work for the census at one point, yeah. In college. They do great work. They do. They do.
3:13:17
Yeah, I mean, I from from working there and and and doing everything on pencil and paper, I was like the first person I think to ever use like Google Were you a Jordan door census taker?
3:13:25
I was No, he quickly worked his way up.
3:13:28
So, I was a manager of a unit that would re-interview people to make sure that the door-to-door census takers weren't like lying.
3:13:37
Because if you're a door-to-door census taker, you get paid 20 bucks an hour.
3:13:40
You just go up and you're saying I I have to walk to all these doors and say, I saw three people. I saw four people.
3:13:45
Or but you could just write that and then just turn that in and not do the work.
3:13:49
And so, we'd go reality check all the day.
3:13:54
who's listening to this was 20 at 20 at the time managing a team of hundreds.
3:13:58
It was a big team and they were all older than me. It was very crazy.
3:13:59
I want every tech person listening to recognize the value of government data and the checks that it off always goes through and and the great work that you did in your early career.
3:14:08
Yeah, it was a lot of fun.
3:14:10
Anyway, thank you so much for coming on the show.
3:14:13
>> Great to Great to have you here. Thank you. Always great.
3:14:14
We'll wind down the show. Thank you. Thank you so much.
3:14:17
And uh with that, we will conclude today's uh show.
3:14:23
We will be back tomorrow at 11:00 a. m.
3:14:26
Pacific sharp on the dot, hopefully earlier.
3:14:29
Is there anything in the timeline that we need to go through before we get out of here, Jordan? Let's see.
3:14:34
We didn't even talk about CIA.
3:14:34
We are officially signed with CIA. We went Hollywood mode. Uh that's very exciting.
3:14:42
Yeah, very very exciting.
3:14:42
We were pleased to be partnered with them.
3:14:44
We put up a trading card. We're very CIA team. Yes.
3:14:50
They're going to be helping us navigate Yeah.
3:14:54
the entertainment landscape. Yeah. Very exciting.
3:14:57
Yeah, yeah, we went down.
3:14:58
We took some headshots at CAA HQ.
3:14:58
Also, you know, I like to think of the creative artists agency.
3:15:05
Sort of the Anthropic of agencies. Do you know the lore?
3:15:09
Did you actually get up to speed on this?
3:15:11
So, Creative Artists Creative Artists Agency was formed by five agents. They were at WME.
3:15:15
They were at William Morris Agency in 1975. Who you got? There's a dinner.
3:15:21
You got Michael Ovitz, Michael Rosenfeld, Ronald Meyer, and Roland Perkins, and William Haber.
3:15:28
And they're at this dinner and they decide to create their own agency. What happens?
3:15:33
They They're like, okay, we need some financing.
3:15:35
We're going to start a rival agency. We're leaving WME. We're starting CIA. What happens?
3:15:39
Before they can get financing, they all get fired. They all get fired. Seriously, this is real.
3:15:46
This is all the way you get thinking machines dynamic in Yeah, no, it really is like AI lab talent wars all over again.
3:15:54
I don't know if they're the Anthropic or the Thinking Machines, but maybe they're the OpenAI in this.
3:15:57
But uh the the metaphor is extremely messy, but it's fun lore.
3:16:01
Uh of course, CIA was incorporated in Delaware and had a $35,000 line of credit and a $21,000 bank loan.
3:16:08
They rented a small office in Century City.
3:16:10
And within a week, they sold a game show called Rhyme and Reason, The Little Rascals show, and the Jackson 5.
3:16:16
An early plan was to form a medium-size full-service agency, share proceeds equally, and do without nameplates on doors or formal titles, or individual client lists with guidelines like be a team player and return phone calls promptly. I like those rules. Great rules.
3:16:32
We're very happy to be partnered with them.
3:16:34
So, I got to reread Who Is Michael Ovitz? For sure. For sure. Absolutely legend.
3:16:38
And we when we were at CAA last week, Yeah.
3:16:40
uh we were were yeah, last week.
3:16:44
Uh we did confirm that the mail room still exists. It does.
3:16:50
And there was a lot of mail. A lot of people in it.
3:16:52
They were moving the mail around.
3:16:54
Apparently, they said we were the only only talent to ever That was crazy.
3:16:56
I think they tell everyone.
3:16:58
They probably tell everyone.
3:17:01
But there was a lot of aura in there.
3:17:03
There was a lot of positive energy.
3:17:03
You could see that the next generation is already cooking.
3:17:07
And uh yeah, getting ready to build.
3:17:10
Anyway, thank you so much for tuning in. Is that the bomb?
3:17:12
The bomb has been planted.
3:17:15
Uh Mark Gurman says the Siri chatbot is known internally as Campos.
3:17:18
It'll likely be powered by Gemini running on Google's own TPUs and cloud infra, meaning it's far more powerful than the one coming to I'm very excited for Gurman.
3:17:25
He's coming back on the show.
3:17:27
We're going to get him in person.
3:17:28
Leave us five stars on Apple Podcasts, Spotify.
3:17:30
Sign up for our newsletter at tbpm. com.
3:17:34
>> Meta superintelligence lab delivered its first base models internally.
3:17:36
Boz worth calls them very good.
3:17:38
A tremendous amount of work to do for post-training.
3:17:42
[Music] Anyway, thank you so much for tuning in.
3:17:45
We will see you tomorrow at 11:00 a. m. sharp. Goodbye. Nice work, brothers. I'll see you on the