0:09
[Music] Hey, [Music] hey, hey. [Music] Heat. Heat. N. [Music] Heat. Heat.
Search this video
1:06
[Music] [Music] Hey, heat. Hey. Heat. Heat. [Music] [Music] Heat. Heat. N. [Music] [Music] Heat. Heat.
2:40
[Music] [Music] [Applause] [Music] You can't do this world [Music] to reach the stars.
3:24
We came to this world to shape our future. We came to this world.
3:37
[Music] to shape our future.
3:51
We came to feel the new [Music] [Music] [Applause] [Music] [Music] [Applause] [Music] You came to this [Music] to reach the stars.
4:47
We came to this world to see a future.
4:58
We came to this world to reach the stars. to shape our future.
5:14
We change to feel the new [Music] Heat. Heat. N. [Applause] [Music] Heat. Heat.
5:51
[Music] [Applause] [Music] You came to this world [Music] to shape our future.
6:16
We came to feel the new [Music] music.
6:33
[Music] [Applause] [Music] [Music] [Applause] [Music] Team Deathmatch.
7:13
Delta team, you are clearly engaged.
7:17
[Music] 3 2 1 >> You're watching TPBN.
7:25
Today is Friday, September 5th, 2025.
7:28
We are live from the TBPN Ultra Dumb, the temple of technology, the fortress of finance, the capital of capital.
7:37
We have a great show for you today, folks. Thought we'd mix it up.
7:41
People have been complaining about the screaming.
7:43
We decided to take it in a different direction. >> We heard you.
7:48
>> I think I think we'll be back to yelling on Monday. That was pretty weird.
7:49
Uh anyway, >> never again. >> Never again.
7:54
>> Uh we have a >> Should we actually just dial it back and run it back again?
7:59
>> You want to do it again? A second take? >> Yeah. >> Okay. >> You're watching TVN.
8:08
>> Uh the current thing is big numbers.
8:08
Uh, $200 million for the free press, Barry Weiss's media company to CBS.
8:14
Um, >> people did not like the quiet in the chat. They said scream.
8:21
Uh, $610 million for the browser company.
8:25
We talked about that a little bit yesterday.
8:26
Uh, Ramp hit $1 billion in ARR. Let's hear it for RAM. [Applause] >> Great hit. Great hit.
8:37
uh 600 billion in meta capex >> capex and 1 trillion potentially on the table for Elon Musk at Tesla.
8:43
So we're going to go through this.
8:46
So uh the free press is one of the most impressive media companies built in the last decade says Austin Reef from Morning Brew. Correct. Yes.
8:56
Uh huge congrats to Barry Weiss Nelly Snoozy Weiss. This is a funny name.
9:01
Uh for building something truly different.
9:03
Uh this is I think still rumored.
9:05
I don't think it's fully confirmed at this point, but uh it's all it's all but >> yeah, it was hard to tell which side was leaking the news.
9:13
>> Yeah, there's this dynamic where media likes to talk about media, and I feel that 100%.
9:17
It's super interesting to hear about like the business of Joe Rogan or the business of Huberman or or any of the experts, but um uh so so obviously also, you know, you're surrounded by journalists literally if you run a media company.
9:31
So they all talk >> journalistic force headed towards you. heard that one before.
9:35
Uh but you're surrounded by journalists and so uh obviously everyone talks and the media leaks out and the news leaks out >> and it could be interesting ways for either side to put pressure on getting the finish line what they want out of the deal. >> Yeah. Yeah.
9:50
And so uh there's there's a series of takes.
9:52
I was talking to a buddy who works in media who was uh coming at me with like a it's a crazy number.
9:59
And so that's kind of level one.
10:00
Level one of the take is like uh on a price per subscriber basis seems high.
10:03
I think they have about a million free subscribers.
10:07
$200 per free subscriber feels like a lot, I guess.
10:09
Um kind of hard to tell if you think about long-term value for CBS, but then others are complaining about the political implications of the deal.
10:17
Is this something that's like a give to Trump to help get the the the the de merger, the spinout approved? Something like that. Um, >> yeah.
10:27
And I mean, this is an $8 billion deal, this merger, >> and media companies are now entirely like media companies at their best or personality. >> Yep.
10:39
>> And paying $200 million to bring on, you know, a face for CBS, one of the most important properties. Makes sense. >> Yeah.
10:49
That's my that's my like level three like final take which is that um you sort of have to put a put aside the price per subscriber uh you know take and you have to put aside the political implications of the take.
11:03
I just think about it from it's a big company 8 billion you said something around there.
11:08
Uh does bringing a younger more entrepreneurial talent into the organization move the market cap by 1% or 2% over the next few years?
11:16
It's like I it seems like the same math that we're doing for buying a very expensive AI researcher.
11:22
You're paying a lot of money in terms of like what what like a salary would count, but you just can't get that level of talent on any sort of normal >> the overall property. >> Exactly. Exactly.
11:32
And so I was the the the person I was talking to who was like, "This is a ridiculous price."
11:37
I was like, "Yeah, but dude, like if if you were at CNN, you could probably add $200 million of value to that organization pretty quickly."
11:46
Uh and so it's just a matter of time until like the market and the board of directors and the shareholders kind of wake up to that dynamic of how power los certain people are and actually go and figure out how to get the deals done and >> and David Ellison is doing deals, right?
12:02
He just did the UFC deal. Fair amount >> 100%.
12:05
And so there's a lot of big numbers flying around >> and there's an and there's an interesting dang where the the premium right we saw this yesterday with the browser. >> Oh yes.
12:13
So you do get a big fantastic outcome uh for having the the at the beginning of the name.
12:19
>> Maybe we should just be the business production network. Drop the technology. Technology's over. The hype cycle peaked.
12:25
We're just the business production. >> We're in the trough. >> We're in the trough.
12:28
Uh we have some fun stuff coming uh in terms of the hype cycle soon.
12:32
Um but uh it's interesting because many companies just cannot justify putting someone on staff for $100 million W2.
12:41
We've seen this at Apple with Tim Cook, you know, the CEO pay once you get into the the these eight nine figures.
12:50
>> Thank you for bringing that up.
12:50
No, thank you for No, seriously, thank you for bringing that up. >> Thank you.
12:54
Apparently uh uh Tim Cook, we we'll try to pull up this video in a bit.
12:59
Apparently he said thank you 12 times in two minutes when talking with uh President Trump last night at the dinner. >> Yeah.
13:06
So >> he's very grateful.
13:08
>> Um so the So yeah, Meta is like the first company to really like break this trend of just like yeah, we're willing to pay $100 million in salary.
13:16
We will do the crazy acquisitions and the aqua hires to get really talented people in the org.
13:22
But uh I don't think other companies are in that world where they could go out and hire somebody like a Barry Weiss just for $100 million.
13:29
Uh it's got to be done through an acquisition.
13:32
That's what gets board approval.
13:34
That's what gets shareholder approval.
13:35
And so you're kind of wrapping an individual, an influencer, someone who's incredibly talented and entrepreneurial around an organization just to actually get the cash flow to flow through.
13:46
It's making me think about C CBS News for the first time in decades. >> Yep. So, >> Yep. Yep. Yeah. Yeah. It's true.
13:53
And even if they even if like the uh subscriber numbers are like a little low, I mean, honestly, a million is a ton. It's great job.
13:59
Um but even if they are a little low, it's like, well, what is they what are they compounding at?
14:04
What what will the free press be able to be at in a decade with the support of CBS and the and the backing financial backing of CBS and Barry Weiss's execution strategy?
14:12
Like, could be a hundred million. I don't know.
14:14
could be really really big.
14:16
Uh but you don't have to raise money for it.
14:17
You you can just focus on growth.
14:19
Anyway, similar story at the browser company.
14:21
$610 million from Atlassian.
14:24
Uh very interesting deal.
14:26
The timeline was not a fan of this.
14:29
>> Came from the land down under with a Brinks truck. >> Yes.
14:32
And it a lot of people are asking is this is this some runaround by the Australian government to try and influence the browsing habits of Brooklyn hipsters? Yeah.
14:41
>> I don't think there's much >> try to control the narrative, right?
14:42
So, as a way to say, you know what?
14:44
What if we could get all of the data from Brooklyn hipsters, all their browsing information? >> Yeah.
14:52
They're known for communication. >> Yeah.
14:53
They're known for drinking PBR, but what if every time they went to PBR on the Arc browser, the DIA browser, it just automatically rerouted them to Fosters. >> Yeah.
15:03
>> What if the AI assistant on the side?
15:06
>> Oh, you're you're in Dia.
15:06
You're asking, "Oh, what should I do this weekend?"
15:08
And it just auto autopop populates. Oh, yeah. We're using AI. throw.
15:11
Why don't you throw another shrimp on the barbie? >> Yeah.
15:14
And if you search, is it true that kangaroos are extremely violent?
15:16
It'll it'll start spinning it and saying well actually, you know, they're only violent when promote provoked. >> Provoked. Yeah.
15:25
They're actually quite peaceful. >> Yeah.
15:27
Your dog actually tried to barked at the kangaroo and then the kangaroo went after it. >> Exactly. Exactly.
15:33
I think this I think this is really smart from uh from Australian uh from from >> from uh >> people pulling the strings in Austral yeah to get a little bit more uh influence over the Brooklyn hipster and the arc and the dia user.
15:47
Uh Zeb did not like the acquisition and said pull this up >> me uninstalling Arc as a certified Atlassian hater.
15:55
There is a wild gap between the vibes and so some people had this take that like uh it was it was a vibe acquisition.
16:03
They acquired good better vibes with the next generation of founders.
16:07
Uh AR certainly has but I think that uh from from what we've seen DIA they're going to continue to operate independently.
16:14
I bet they're going to build some beautiful enterprise browsing experiences like they always have. >> Yeah.
16:20
and they should they should build in reream one live stream 30 plus destinations multiream and reach your audience wherever they are.
16:26
So you should be able to stream from your dio browser from your arc browser.
16:29
Um so my my take on this was there's so basically uh right now the team is saying we're going to stay independent.
16:38
We're going to go but my question is are they going to stay are they going to stick with that narrative of like stay independent and this is very rare for pre-product market fit acquisitions.
16:48
I haven't seen a ton of examples of that where a company was acquired that wasn't like clearly on a you know just >> remember path >> Instagram was bought for a billion dollars and almost everyone involved at the time thought that it was crazy. >> They did. Yeah, that is true.
17:05
At the same time >> and it was like a key threat to Meta's business, right?
17:10
Like the user growth was Yeah. >> insane.
17:13
I mean, I would love to look at the uh the retention metrics for DIA versus Instagram because it's totally possible. I I don't know.
17:22
Do you know how many DAUs or or total downloads Instagram had at the time of acquisition?
17:28
I know it was small, but was it sub a million?
17:29
I feel like it might have been a little bit bigger.
17:32
Can someone look that up?
17:33
Uh but basically, >> look that up, Tyler.
17:35
I'm also curious about YouTube as well.
17:36
YouTube was bought for >> Yeah.
17:40
How many people were using >> three times?
17:41
Uh >> yeah, >> and again our the dollar isn't what it used to be.
17:46
>> Y so when Instagram was acquired um estimated around 860,000 so less than a million DAUs. >> Okay. Okay. So >> DAUs though. >> Yeah. Yeah.
17:55
But still I mean we're in the same ballpark here. Very interesting.
17:58
Instagram >> people people that have >> Yeah. Yeah. Yeah. Yeah. Yeah.
18:03
>> Dau is wildly different than users. Okay. Okay. Yeah. Yeah.
18:06
Uh but still I mean we're we're we're in we're in the rough ballpark where you could where at the very least you like we have to take what Atlassian is saying and what the browser company is saying at face value.
18:18
They are saying we're going to continue building this browser.
18:20
We're in it to win the AI browser. We're we're going broad. We're going consumer.
18:25
This is not we're acquiring this browser.
18:28
We're going to bake it into Trello and we're going to bake it into Jira. No.
18:31
Like >> I actually disagree with you here.
18:33
They don't they're they all the messaging was that this they're they're not going to be focused on consumer like from Atlassian CEO was that we're going to build great enterprise browsing experience. >> Oh, okay. Okay.
18:49
>> So, there's nothing there's nothing in there that that I saw from the Atlassian side that said >> we want to win in the consumer. >> Oh, really? Really? Okay. Interesting. Yeah.
18:57
>> They are they know their they know their business, right?
18:59
So, >> it's very interesting.
19:01
I I can't imagine having like a work browser, but maybe that makes sense.
19:05
I mean, people have work laptops, but I feel like the trend has been you have you have like one phone that you do work and life on and then you have separate apps and maybe you have, you know, an enterprise software product installed on your on your phone.
19:19
But really like there's the trend seems to be more people using like Gmail and Google email at work.
19:23
And it seems like there's less and less like, oh yeah, like I have a separate work computer with a separate operating system.
19:32
>> Chrome is very set up.
19:32
Chrome is already very set up to have like profiles, like personal profiles and work.
19:38
>> Yeah, I have I have two.
19:38
I have a personal one and VPN one. Um, so I don't know. Yeah. Um, we'll have to see.
19:42
I mean, the the the founder is saying like we're going to keep working on DIA, but maybe that means in the enterprise context.
19:51
Uh anyway, um we'll have to keep an eye on like where they wind up going.
19:57
>> So Mike said again, I said this yesterday, with DIA browser, we're going to collectively redesign the browser to help knowledge workers kick butt in the AI era.
20:08
>> And so I that that to me kind of reads a little proumer, right?
20:11
I I don't think they're but but it feels like, you know, very much oriented towards people that are working in the browser. >> Oh, yeah.
20:20
OTP says, "Get Sager on here to give push back on TFP. Bye."
20:22
He's going postal about it.
20:25
I I should text him and see if he wants to hop on.
20:28
Um, uh, we will, yeah, we'll definitely get him on when when when he's ready to to to, you know, go live and ri some takes.
20:37
I also invited Barry Weiss.
20:37
I'd love to hear her, uh, her side of what's going on and what her plan is.
20:40
Uh, it's a it's a fascinating story.
20:43
Of course, like these are still like leaks, so most people don't want to talk until there's like finalized, uh, information.
20:47
Uh anyway, uh if you're trying to design a browser, you got to do it in Figma.
20:53
Think bigger, build faster.
20:53
Figma helps design and development teams build great products together, get started for free.
20:59
Uh and the third big number of the day, ramp has crossed 1 billion in revenue.
21:05
Sheesh says, Tyler, >> a key question is whether it's gross revenue, it's now revenue.
21:10
I think it's gross revenue.
21:11
He goes back and forth on this, but anyway, they've been on a tear.
21:15
Uh, as David Senra likes to say, it's a great example of taking a simple idea and doing it deadly seriously.
21:24
Taking a simple idea deadly seriously.
21:24
I think David was quoting someone, but I attribute everything to David to David's.
21:30
Now, um, >> we should pull up these videos from the uh, dinner at the White House last night.
21:35
>> I only have one question for Eric, which is, is the job finished?
21:38
So, we will figure that out today.
21:42
>> You're going to call him?
21:42
>> I I'm He is He's busy.
21:42
I'm going to I'm going to >> All right. play this video. >> Oh, yeah.
21:48
>> You've done an incredible job with Apple, little company called Apple. >> Thank you, Mr. President.
21:54
>> Very, very few people have been able to do what you've done. Congratulations, please. >> Thank you, sir. That means a lot to me.
22:00
Uh, I want to thank you for including me this evening.
22:04
>> It's incredible to be among uh everyone here, particularly you and the first lady.
22:08
Uh, I've always enjoyed having dinner and interacting.
22:11
Uh I want to thank you >> for Thank you >> for setting the tone such that we could make a major investment in the United States and have some key manufacturing advanced manufacturing here.
22:25
I think that says a lot about your focus and your leadership and your focus on innovation.
22:32
I also want to thank you >> for helping American companies around the world.
22:38
Uh this is a very key key thing and I really enjoy working with your administration on on those topics as well.
22:48
Uh because I think they're so important to the country.
22:53
>> I want to thank the first lady for focusing on education. >> Wow.
22:56
>> There's nothing more important than education. >> Triple.
22:59
>> Uh it is the great equalizer >> and uh always will be.
23:02
And so thank you so much for including me.
23:06
We're all we are all different in some ways, but we all believe in the power of technology to improve people's lives and that that is the thing that that binds us all together.
23:19
>> And Tim, how much money will Apple be investing in the United States?
23:22
Because I know it's a very lot and and it's uh you know, you were elsewhere and now you're really coming home in a big way.
23:32
How much money would you be investing? >> 600 billion. >> 600 billion. >> There we go.
23:36
We're very proud to do it. >> That's great. Thank you very much. >> Appreciate it. >> Thank you, sir. >> Wait, is that 10? Thank you.
23:42
So, >> I think it was 12.
23:44
Somebody else had counted as 12. I I I was around 10.
23:49
>> Um, but still, we should um >> Why wasn't Christina from Vanta there?
23:51
I feel like that's key to the US's tech strategy. I agree.
23:56
>> Automate compliance, manage risk, prove trust continuously.
23:58
Vantage trust management platform takes the manual work out of your security and compliance process.
24:02
All right, we got to pull up this video of >> with continuous automation of Zuckerberg.
24:06
This was our fourth big number of the day.
24:08
Uh Zuckerberg says he will invest around 600 billion by 2028.
24:15
Uh Zuckerberg says Meta will invest 600 billion in AI infrastructure by 2028.
24:20
Meta's already guided capex of 70 billion in 2025 and 100 billion in 2026.
24:25
So that's a big ramp to go from 70 to 100 and then they still got 430 billion to do in 27 and 28 uh to actually re uh reach uh 600 billion.
24:35
Spending would need to jump to 200 billion in 2027 and 300 billion in 2028.
24:40
That's a lot of dollars >> video in the timeline. >> Let's play it.
24:48
And this is quite a group to get together and you know I think um you know all of the companies here are building just making huge investments in in the country in order to build out data centers and infrastructure to uh power the next wave of innovation.
25:01
So it's um you know we don't often get together as as uh the the the CEOs of the different companies but it's it's uh good to see everyone.
25:11
>> How much are you spending uh would you say over the next few years? >> Oh gosh.
25:15
Um, I mean, I think it's probably going to be something like >> 600 billion >> at least $600 billiona >> in the US.
25:26
>> Yeah, >> that's amazing. >> No, it's significant. >> That's a lot. Thank you, Mark. It's great to have you. >> Thank you.
25:32
Well, thanks for for hosting us.
25:34
I mean, this is quite a group.
25:35
>> So, does anybody in the chat know if who which which of them went first? >> Yeah.
25:40
because cuz that number that number does not align that number does not align with with uh Meta's stated >> yeah it doesn't appear in the SEC filings yet but it is like very forwardlooking and >> no it was 2028 >> 2028 which is something that they might might not actually put out or might not be demanded by the by Wall Street but that is hilarious.
26:03
Uh anyway whatever they do they're going to have to do it on graphite graphite.
26:06
dev code review for the age of AI.
26:07
Graphite helps teams on GitHub ship higher quality software faster. Get started for free. >> Yeah.
26:12
So Meta guided uh capex of 70 billion in 2025 and 100 billion in 2026.
26:18
So to to get to 600 billion, spending would need to jump to 200 billion in 2027 and 300 billion in 2028. >> Yeah.
26:25
>> Yeah. What's interesting is that uh so these numbers are like insanely big and obviously it looks like a big acceleration relative to past capex numbers but I'm so inured to big numbers now because of the fast takeoff crowd that was like oh yeah like trillion dollar buildout data center like next
26:44
year for sure like AI 2027 like it's going to be 10 trillion it's gonna 500 billion >> uh and so uh like when I hear 600 billion I'm like >> yeah yeah that sounds like totally reasonable Like I think they'll definitely hit that and and they I don't know they probably will. Like it doesn't
26:58
Like it doesn't seem like uh there's many barriers in the way like it's just continue to grow the core business, run more ads, dump the profits into capex, build some more data centers.
27:10
Uh semi analysis uh uh Doug Laughlin over at uh Fabricated Knowledge has a good uh deep dive today on the glut of lagging edge chips that I think we might have a chance to get to in a little bit.
27:22
But, uh, it was a it was a fun dinner.
27:24
Are there any other videos that we should play from the from the White House dinner?
27:28
>> I like the idea of, uh, this is like this is kind of new podcast format.
27:30
Just have a dinner with everyone, have some cameras there, and just Yeah. Yeah. It's good. What's up, Tyler?
27:37
>> Uh, I don't have another video, but um, there is there was a photo that came out.
27:41
I'll send it to the chat.
27:41
Um, but it was like the full dinner, and right at the very edge, I'm pretty sure it's Dylan Field goat. Yeah. >> Yeah. Yeah. Yeah.
27:47
So, someone had the full breakdown here. It's in the deck. much deeper.
27:52
Let me let me pull it up. Where is it?
27:54
Uh the full list of people who attended the dinner is Wow, there's a lot of stuff.
28:02
Okay, so Ed Ledllo has it.
28:03
full list of attendees at President Trump's dinner with tech leaders.
28:05
The president, the first lady, Susie Wilds, Sergey Bin, uh Gerilyn Gilbert, Sodto, Sam Alman, Greg Brockman, Anna Brockman, Saffer Catz at Oracle, Gil Galter, Justin Chang, Meredith Aor, Natalie, Natalie Dump, uh Tony Fabrizio, Dylan Field, John Herring, Jar Jared Isaacman, Jared Isacman.
28:28
Uh oh, I I guess he was >> missing one.
28:31
Yeah, Elon didn't go but isn't isn't Oh, Chimath is in here.
28:33
So, uh, Sunonny Madra, Sacha Nadella, Chimath, Poly Hapatia, Sandra Pachchai, Mark Pinkis, VC Ranadv, who owns the Golden State Warriors and I believe VC Jranad is the the the like the guy who worked with Chimath on the first spaxs and VC Ranadv kind of like pioneered that format almost.
28:54
Um, >> did you say Lisa Sue from AMD? >> Lisa Sue made it.
28:58
David Saxs, Sham Sankar from Palunteer.
29:00
Uh we missed him yesterday.
29:02
He was at this dinner in DC.
29:04
Uh Jamie Simoff, uh Alex Wang, Sanjay Marota, Tim Cook, David Limp, Mark Zuckerberg, and Bill Gates. What a crew. Jensen didn't make it.
29:14
So, the fact that Jensen and Elon are not there, I feel like you shouldn't read too much into it.
29:22
It's kind of just like Trump catching up with a bunch of people, but I don't know.
29:25
There's also like this Yeah, I don't know.
29:27
They they had like falling out, but it seems like they've kind of patched it up. I don't know.
29:30
Uh always always hard to read too much into this stuff.
29:35
But speaking of Elon Musk, he didn't need to be at the White House because he's setting up a $1 trillion pay package. >> 975 billion. >> Oh. Oh, it's not a trillion. Just a little bit shy. Okay.
29:47
So, uh uh the update is uh Tesla's board has green lit a fresh pay package for CEO Elon Musk.
29:56
If he hits 400 billion in adjusted EBITDA, he deploys 1 million robo taxis for commercial use, ships out 1 million energy storage units, produces and delivers 20 million vehicles, secures 1 million of ongoing FSD subscriptions, aim for a $ 8. 5 trillion market cap.
30:12
The Golden Retrievers are seven and a half to 10 years in the CEO role.
30:19
The starting share price is $3349.
30:25
The package includes 12% of company stock divided into 12 segments.
30:27
And so um Signal says this is a masterclass in how to design incentives.
30:32
This deeply ties Elon's upside on the world radically improving.
30:37
If he actually hits those milestones, the value unleashed for society dwarfs his payout.
30:40
Most CEO comp is rent seeking.
30:43
This is moonshot seeking. I completely agree.
30:45
Every pay package for executives should be this absurd on both sides for the company and the individual.
30:52
And this is exactly my take. It's like bet on.
30:56
>> He's done this he's done this before.
30:57
>> He's done this before.
30:57
And Dan Primac uh when when the when the pay package the most recent pay package came into uh under like leg legal scrutiny, Dan Primac was like, I like this when it was announced and I thought it was crazy and I and everyone thought it was impossible that he would pull it off and he did. So he deserves it.
31:13
Um and so it was this crazy legal battle, but it was actually aligned with exactly what a CEO should be doing, creating shareholder value.
31:21
This should be a model for CEO comp going forward in my opinion.
31:23
Uh there is another side of this which is increasing a founder CEO stake by doing aggressive stock buybacks.
31:30
But this is a way cooler because it incentivizes bold investments and huge capbacks on factories, moonshot technology gambles and generally thinking in decades.
31:40
So uh I'm super stoked about it.
31:43
I think it's I think it's good. I hope it holds.
31:45
>> It's a good way to signal.
31:45
I mean, they're they're very much signaling to the base, the Tesla army, that that there's a lot of potential upside.
31:55
>> Uh Chris Camo said earlier, been tracking XAI's accelerating cash burn, flattening user growth, monetization, and fundraising struggle since the beginning of this year, and I don't see how they last another 12 months without a Tesla or Elon bailout.
32:08
I mean, saying I don't see how they last another 12 months without a the founder bailing them out.
32:17
It's like that's kind of the founders's job is just continuously bail out the company.
32:21
But I thought this was relevant because I do think that part of this part of setting up this pay package could set up a scenario where XAI gets just merged into Tesla and it becomes a standalone.
32:32
Uh uh it it just all gets rolled in. >> Yeah. Yeah.
32:36
I mean Tesla has I mean Cararpathy worked there like it's it's a fantastic AI organization and it makes sense that there would be a lot of overlap in in what they do.
32:44
I I guess there's probably >> and I mean if if X the everything app was part of a public company again how is that not how does that get valued at less than eight and a half trillion right >> and so with with Elon having that ace up his sleeve fact that we're all addicted to this app. >> Yeah.
33:03
I mean I mean I I guess it's good that there's other milestones in there that that you can't just like uh merge everything together because if you merge >> it is funny to think about some of the different milestones though.
33:12
It's like >> shipping out 1 million energy storage units feels like wildly like does this even need to be included if you're going to deploy 1 million robo taxis for commercial use?
33:26
>> Yeah, that one seems a little bit uh I don't know, easy sandbag. Who knows? Um, I like uh >> Yeah.
33:33
Well, notably missing uh what about post more tweets, post some bangers.
33:40
>> I would like to see a thousand >> I want to see him go viral.
33:43
>> I would say a thousand people a day marrying Anie. >> Oh, okay.
33:46
That's the That's the That's the milestone.
33:49
>> That should be in there, too. >> Yeah.
33:50
Um anyway, um Oh, on Chimamoth, people were making fun.
33:55
Uh QCAP has Chimath at the tech leaders dinner last night and he's uh Drake on the basketball team uh the Kentucky basketball team uh in full in fully suited up.
34:07
>> He's there he's there with he's there with uh he's there with Sachs and he's he's big in Grock. >> Oh, is he? Oh. Oh go. Yeah, that's right. That's right.
34:16
Yeah, that makes a lot of sense.
34:17
Um and uh and Run had a good kind of contrarian take on the Chimamoth hate.
34:22
He says, "Young heads don't know that Chimamath initially had his come up as the VP of growth at Facebook while the app grew from 50 million to a billion users.
34:30
They invented people you may know, which preer naturally predicts who your friends are." The concept of MAU, etc.
34:39
All this stuff is in the water at any internet company now.
34:41
More important, yes, he basically invented growth.
34:43
The entire app, the entire idea that you can treat app growth as an as an empirical AB tested science.
34:50
AB tested science. and we talked to um a designer on the Facebook team at the time and you know it's so easy to zoom out and look at Facebook as like oh it was like just a foregone conclusion that they would win everything and just completely dominate but there were moment >> I love I love Jason popping in here in
35:07
the comments saying it's his birthday party dummy >> he just turned 49 >> Oh he did no way that's amazing what a birthday party that where else would you want to be that seems like a great time um yeah people were having fun making fun of uh of Chimoth but why not have him be there makes a ton of sense. >> I love this post from Morgan.
35:23
>> I love this post from Morgan.
35:25
>> Uh should have gotten the other crew in there.
35:27
Should have gotten Jason and uh and Friedberg the invite.
35:28
Um anyway, uh what was the was the next thing you pick? Oh, yeah. >> Three-way deal.
35:36
>> Elon is deal making >> between XAI and Tesla.
35:40
>> No, I mean this is it's it's uh Ed Lllo over Bloomberg saying Tesla's board has proposed a new pay package for Musk and proposed the authorization of investment in XAI. Oh, sure.
35:49
the board is is looking at investing.
35:51
Remember SpaceX already invested in in XAI because they had to get exposure.
35:57
>> Yeah, we saw that like complicated web of Elon companies, how they all linked together.
36:00
Maybe you just got to merge them all together.
36:03
>> Pure play Elon >> holding company.
36:05
Yeah, >> send it >> in 10 trillion for sure.
36:07
Um the uh >> Yeah, I mean like Elon's like done like kind of these zombie mergers before with Solar Cities.
36:18
I mean, some people framed that as a bailout and didn't hurt Tesla.
36:23
The stock went on an absolute run and it was great and >> just a flesh wound.
36:27
>> And uh I I never really understood why Solar City wasn't more successful because it feels like solar you talk to Casey Hanarray.
36:34
Casey Hanarray. is like the biggest solar maxi and all of the like scientists all the experts that I trust uh say that solar is you know going to continue to grow extremely valuable extremely important but it seems like we've just been solar city specifically and basically any American solar company has been kind of going to economic war
36:54
with China and China's been like dumping cheap solar panels on the market continuously so you need a company like Tesla to maybe subsidize that for a while uh until the US government comes around to some sort of regulation on like what are exactly are we going to do uh about it to create like more of a level level playing field. Either we're
37:11
Either we're going to subsidize or we're going to like put tariffs and taxes on their exports to get them back into you know what what they actually cost instead of just letting another company uh run rough shod all over the American. >> This is interesting.
37:25
Ed Lello also was sharing that Musk must also help craft a CEO succession plan to unlock the final tranches.
37:35
>> Will Maximus Trump be old enough?
37:37
Who what what's his name? Uh X.
37:40
There's a few there there's a few wild names.
37:43
One of the It's got to be a It's got to be a hereditary dynasty, right?
37:47
He's got to let X take over in 10 years.
37:50
How old were >> the oldest uh Musk children are 20 year old twins.
37:57
>> Oh, they'll be totally ready in 30.
37:59
>> Vivian and Griffin Musk potentially co-CEO. >> Co-CEO. That could happen.
38:04
>> Um and then there's and then there's another one that's a little bit younger who might be, you know, more in the uh like 20 20 something year old uh by the time Elon steps down.
38:14
But I I I I would be surprised if he's not running Tesla in 10 years.
38:19
I I think he's going to stick around for a while. keep keep running it.
38:22
Uh he just keeps he just keeps, you know, hanging out and building cars.
38:27
>> And this is just fantastic news for people like Gary Tan who've been saying, "We need more trillionaires." >> Oh, that's true. Is that his thing?
38:32
He thought he said more billionaires.
38:36
>> We need our first trillionaire.
38:38
>> Uh the package could raise Musk's stake in Tesla >> to at least 25% with total voting power of up to 29%.
38:44
Tesla's market cap must reach 8.
38:47
5 trillion from 1 trillion today.
38:49
The plan follows Musk's 2018 package valued at 50 billion, which was struck down by a Delaware court.
38:54
Tesla's board is appealing that ruling, but is also offering Musk an interim $30 billion stock award uh while pursuing the New Deal.
39:03
Musk's outside ventures, SpaceX, XAI, Neurolink, Boring Company, and Political Activity has raved concerned about focus.
39:09
But was Warren Buffett not focused on seas candy and Coca-Cola at the same time? Come on, people. This is a hold co.
39:18
It's not that complicated.
39:21
Uh, no, it is Gabby Gabby Goldberg went super viral quoting quoting some of these um quoting a video from uh of Sam Alman at uh at the dinner last night and said this is like when you're at someone's birthday party and they make everyone go around and say their favorite thing about them. >> That's very funny. And what did Sam say? Do we have the video? The rapid response.
39:45
said, "Thank you for being such a pro business, pro- innovation president.
39:48
It's a refreshing change.
39:48
The investment that's happening here, the ability to get the power of the industry back.
39:54
I don't think that would be happening without your leadership." >> I love it. I agree.
39:58
I'm happy to triple glaze as well. I like innovation. >> Triple glaze. >> I like innovation.
40:03
Arthur McWaters, uh, been on the show, uh, many times before, says, "I'm unironically working my butt off so that my wife can go to Pilates on a W Wednesday afternoon and get a $15 matcha." And Siki says, "Same." >> It's a noble goal.
40:19
I wish Raul from Julius had been invited to this dinner. >> Yeah.
40:24
>> I feel like he shows up in in different pieces of Silicon Valley lore.
40:29
>> He really could have delivered. >> That would be insane.
40:32
>> It wouldn't be that insane.
40:32
He's on >> I just >> He's fantastic.
40:36
>> I just I mean maybe we could we could >> That's why we sponsor That's why we partnered with him.
40:40
Julius, what analysis do you want to run? Chat with your data.
40:43
Get expert level insights in seconds.
40:45
What could be more relevant to the government and having an AI AI data analyst that works for you?
40:52
>> Every CEO there is probably already using Julius.
40:55
If they're not, >> short. >> Yeah.
40:58
Uh more context on uh Zuck's $600 billion investment.
41:03
Uh Turner Novc says Meta has done $478 billion in revenue over the past 13 quarters and plans to invest 600 billion in data centers over the next 13 quarters.
41:14
Good thing they're growing revenue. >> Yep.
41:19
Well, this is important too because data centers are the foundation of the global economy and if we stop building them, everything's going to collapse.
41:25
So >> token factories uh continue to continue.
41:30
>> Uh John John Woo had some good analysis on the browser coac acquisition.
41:33
He said, "Man, parts of tech are sour about the browser coac acquisition.
41:37
The common complaint is that dia arc don't have enough users or revenue to justify the acquisition.
41:43
First, I think this line of of bitching assumes that Atlassian's corp dev team are dingleberries.
41:52
Dingleberries down under when in fact they're elite and one of the most disciplined and successful M&A units in tech. That's super legit.
41:58
>> Rationally integrating products into the existing product suite and otherwise protecting independence when merited.
42:03
Trello, Loom, Ops, Genie, AgileCraft, many others.
42:06
Second, I think this is part of some ridiculous coping narrative that some VCs and founders inhabit, which is that having differentiated product vision, assembling a world-class team that ships and being an incredible storyteller and salesperson is somehow easy.
42:20
That's a really good point.
42:21
>> Maybe you have more revenue, maybe you have more users. Guess what?
42:22
The market doesn't give an F.
42:25
I've read, seen, and heard directly from multiple people today something like, "Oh, if I just knew how easy it would be to raise a ton of venture and make good videos, I'd do it and get acquired for 610 million." Uh, so go do it then. Go do it then.
42:41
>> I'm not affiliated with the browser cone in any way.
42:42
I'm not here to pat anyone on the back.
42:43
Do the whole welldeserved rigma roll claim I was just one part small part of their success.
42:47
I'm here to say the market has spoken.
42:49
A transaction has been transacted. Capitalism has capital.
42:55
browser company is worth 610 million in cash.
42:58
If you're a VC, founder, etc.
43:00
in the salt mines today, focus on your business.
43:02
If you think you can do better, do it. That is reality.
43:06
>> Do we have the shots fired? Uh sound effect. There we go. Shots fired.
43:12
>> Great, great way to sum it up, John.
43:14
>> Yeah, just go and go and build uh Yeah, just go build something. I don't know. Go tell a story. Figure out a way.
43:19
Uh yeah, I mean underrated is like the the isn't the founder of the browser company like one of the core contributors to Chrome like early on like he was on the Chrome team like if you want to build a browser like too hard to imagine like having a better uh a better team in place and uh >> yeah and >> more breaking news OpenAI is working on its own AI inference chip with a small company called Broadcom.
43:43
I don't know if you've ever heard of this company before >> if you've never heard of Broadcom.
43:50
They're a small company based out of San Jose, California. They are worth uh $1. 57 trillion.
43:59
>> They just had a massive massive earnings beat because there was like this mystery $10 billion customer and it was OpenAI, I'm pretty sure. >> There we go.
44:08
>> So, >> love to see Broadcom up 14% in providing.
44:11
I mean, it's just it's just crazy that that you can have a company that is >> in the same >> sim, you know, similar >> like at the moment like priced in the same range as a company like Meta. >> Yep.
44:26
>> And most people would be like, "Oh, Broadcom.
44:28
Yeah, I've heard of them >> like but but not not be able to say much more about it." >> Yeah.
44:33
So, uh Richard Hoe, ex Google TPU is leading 40 engineers over at OpenAI.
44:38
Uh, seems like Sam did a little talent raid of his own.
44:40
Uh, Broadcom providing critical design and IP.
44:43
TSMC will fab it on the three nanometer node inference only.
44:47
Target mass production in 2026.
44:50
Could fail on first tape out.
44:50
So, um, the interesting thing here is that I've been like beating this drum of like, yeah, GPT4 is good enough.
44:57
Like, bake it onto silicon like like just get the inference cost down.
45:00
Um, just let me use it faster, cheaper.
45:03
Make like like we have really really good intelligence.
45:06
we just need to inference it a lot more.
45:09
Said the same thing about midjourney.
45:10
Thought the images like look good enough and yeah, they could get better, but I'm fine with where they are now and they're fun and so let's just make it really quick and easy to use.
45:18
And it seems like they're going in that direction for the most part because even even the uh even the reasoning models, they're still built on like I mean it seems like they're they're they're built on like a pretty stable foundation of the architecture of the of the frontier model.
45:35
they're not making drastic drastic architectural cha uh changes to the the the the core LLM that powers these uh these reasoning models.
45:42
So uh bring down the price of inference seems really really important.
45:46
So the the uh Wall Street Journal has an article here.
45:49
OpenAI and Broadcom make a $10 billion deal for custom AI chips.
45:51
Order aims to ease shortage that limited or the roll out of new chat GPT versions.
45:56
OpenAI is working with Broadcom to develop custom artificial intelligence chips.
46:00
a move that could alleviate the shortage of powerful processors needed to quickly train and release new versions of chatbt sh uh Broadcom shares surged nearly 11% in Friday trading.
46:10
You said it's up at 16% now.
46:13
>> Um what what a great uh what a great ripper.
46:16
If you're looking to get into Broadcom, you think it's overvalued, undervalued, do it on public. com.
46:21
Investing for those that take it seriously, they got multiasset investing, industryleading yields.
46:26
They're trusted by millions, folks.
46:26
Um, so up 74% in the last 6 months. >> Yeah.
46:31
So on the earnings call, Broadcom said, "We've signed a fourth major AI developer as a customer."
46:36
And that the new customer had placed a one-time order worth $10 billion of for server racks using the Palo Alto based firm's chips.
46:44
The new customer is OpenAI.
46:44
According to people familiar with the matter, the Financial Times reported the arrangement earlier.
46:49
Uh Sam Alman, OpenAI's chief executive have been has been saying for months that a shortage of GPUs has been slowing the company's progress in releasing new versions of its flagship chatbot.
47:00
Uh in February, Altman wrote on X that GPT 4.
47:03
5, then its newest large language model, was the closest the company had come to designing an AI model that behaved like a thoughtful person.
47:10
But he lamented the delays and high costs that came with developing it.
47:15
I guess there's a big question like the some of these really really big models people have been saying like it's great but it's slow and that's and it's costly and I wonder if they're they're going to optimize for GPT 4.
47:28
5 inference or GPT4 level inference.
47:32
Do Tyler do you have any take on on where they might sit?
47:34
Uh Sam Alman said it's a giant expensive model about 4. 5.
47:40
We really wanted to launch to to plus and pro at the same time and we've been growing a lot and are out of GPUs.
47:47
Like I I thought that demand for GPT4.
47:49
5 wasn't purely predicated on the cost and the timing and more just about the fact that uh people couldn't really tell the difference. >> Yeah.
48:00
I mean there's definitely a sense of like, you know, only the high taste testers actually liked 4. 5.
48:06
>> I I would be surprised if they like really bring it back in any capacity.
48:09
It's just like so expensive. >> Yeah.
48:10
I wonder I wonder what they're going to do.
48:12
I mean, it seems like they'll probably still leave some flexibility like the TPU.
48:14
They're not going to like um go like, you know, fully lock themselves into one specific architecture, but uh hopefully it uh brings down inference cost, increases margins, um which should be very very good for the business.
48:27
Uh we will add tens of thousands of GPUs next week and roll it out to the plus tier.
48:31
Hundreds of thousands coming online soon.
48:32
I'm pretty sure y'all will use everyone we can rack up. He said like the y'all.
48:36
I'm pretty sure y'all will use everyone we can rack up.
48:42
>> In recent years, Open AAI is has relied heavily on so-called off-the-shelf GPUs produced by Nvidia.
48:47
Uh, the biggest player in chip design space.
48:49
But as demand from large AI firms looking to train on increasingly sophisticated models has surged, chipmakers and data center operators have struggled to keep up.
48:57
If we're talking about hyperscalers in gigantic AI factories, it's very hard to get access to a high number of GPUs.
49:04
founder of Compute Labs said, "A startup that buys GPUs and offers investors a share in the rental income they produce.
49:10
Um, it requires months of lead time and planning with the manufacturers.
49:12
Uh, to solve the problem, OpenAI has been working with Broadcom for over a year in secret behind our backs uh to develop a custom chip for use in model training.
49:24
Broadcom specializes in what it calls XPUs, a type of semiconductor that is designed with a particular application such as training chat GPT in mind.
49:33
OpenAI also recently struck a data center deal with Oracle that calls for OpenAI to pay more than 30 billion a year to the cloud giant and signed a smaller contract with Google earlier to alleviate uh computing shortages.
49:42
It is also embarking on its own data center construction project Stargate.
49:46
Um and so this is uh just another example of like wow they they haven't made that much in revenue and they're and they're committing to all these spends.
49:53
It's like well they're growing very very fast and they plan on uh on setting themselves up for success and high margins and more growth ahead.
50:00
And if you need serverless vector and full text search, head over to turbo puffer. Search every bite. >> We puffing.
50:11
>> It's built from first principles and object storage. It's fast. It's 10x cheaper.
50:15
And it's extremely scalable. You can get started.
50:17
>> Be like cursor, notion, linear, superhuman, and many more.
50:21
>> Yes, >> Readwise is on Turop. >> Oh, no way. That's very cool.
50:23
That makes a ton of sense.
50:25
>> That makes a ton of sense.
50:27
>> Smart guys working with smart guys. >> Okay.
50:29
Uh, so we need to do a little bit of a meme review moment on the stream.
50:34
Uh, a monkey was handed an AK-47 and the image went viral and is now a meme.
50:37
Uh, I don't know where this came from.
50:40
It looks like an old image from a documentary.
50:44
>> It's crazy how you can tell this image has been screenshotted >> dozens of times. >> Potentially more. >> It does not. Yeah.
50:50
And it also uniquely does not look like AI.
50:52
Uh, but Levels IO kicked it off with a point point of view.
50:57
You can you discover you can do your own DevOps with clogged code and of course uh that could end in disaster. Um >> Skooks says.
51:08
1x coworker just discovered AI. >> Oh no.
51:13
>> I don't know how true that is.
51:13
I mean I feel like AI should be an accelerant, but yes it could be. >> No, no, no, no, no.
51:19
>> Yeah, you need to be at least one exco-orker.
51:21
>> Like you give a bad driver a super fast car. >> Okay.
51:25
>> Does that make them better? Fair, fair, fair.
51:27
Uh, Turner Novac says, "Letting the VC give product feedback.
51:29
It's rough if they haven't been in the trenches."
51:34
Uh, liquidity says, "How it feels to let the firstear analyst speak directly with the client." I love that.
51:39
And producer Ben says, "Giving the ramp card to interns." >> This is real. This is real. >> Do not do it, folks.
51:47
>> You got to be careful. You got to be careful.
51:49
>> Uh Ben's like, "Why do they have to uh request funds for every single purchase?
51:54
Why don't they just have a limit that they can spend within?
51:56
Well, now because they are monkeys with AK-47s >> card is simply too powerful. >> Yes, it is.
52:02
Uh, also Brian Armstrong bumped up the max leverage from 20x to 50x on international perpetual futures and UPS slope capital.
52:10
Just give the monkey the AK47. It's a great meme.
52:15
I hope this meme sticks around for a for a long time. A long time.
52:19
Uh anyway, if you want to get your brand mentioned on Chat GPT, head over to profound, reach millions of customers who are using AI to discover new products and brands clearing order.
52:31
>> We saw OpenAI's investment in Broadcom chips.
52:34
They're not going anywhere.
52:36
You're going to want your brand mentioned on chat GPT and you're going to want to do it through profound >> and Grock >> and Grock and everything else >> and everything.
52:43
>> So in the mansion section today, it's Friday.
52:46
We got 10 minutes until Joe Weisenthal joins to tell us what's going on in the United States economy.
52:52
>> But uh one thing that is going fantastically well in the United States economy is Ellen DeGeneres's uh house flipping hobby which has turned into a 190 million enterprise.
53:01
So the comedian and wife Porsche Dasi have bought more bought and sold more than 30 homes since the mid 2000. >> Absolute dogs. The dogs.
53:13
the absolute dogs of Monaceto.
53:18
>> So they bought a 10,700 foot property in Santa Barbara, California for $27 million in 2019. They sold it for 33. 3 million in 2020. Uh >> modest gain. >> Modest gain.
53:31
Not badain, but didn't take a lot of risk here.
53:34
>> One year, one year, 6 mil. Not bad. >> It's pretty good. Uh it's honest work.
53:39
>> Let's read through the reporting in the Wall Street Journal's Mansion section by Katherine Clark.
53:42
She says just before last year's presidential election, comedian Ellen Degenerous and her wife actress Porsche Dasi decamped to their Kotswald to the Cotswald, an upscale rural area near London.
53:54
They had bought a vacation home, a 43 acre estate to use a few months a year.
54:00
Then the morning after the election, when they awoke to lots of texts with crying emojis, they said, "We're staying here." Um, where was this? Which which election? Um, oh, last year.
54:13
Okay, so it's the Trump 2 election that was uh spar uh sparking crying emojis in Ellen Degenerous's iMessage.
54:20
Um, behind them, they leave a trail of luxury residences over the past two decades.
54:26
The longtime California residents have developed a reputation as serial home flippers.
54:31
The Wall Street Journal's research shows that the pair have owned at least 34 homes since the mid 2000s, including properties in Los Angeles, Beverly Hills, Santa Barbara County, Santa Barbara County's wealthy Monaceto, and now the UK.
54:44
Records show that the couple were actively buying and selling throughout the mid as in the 2010s, but their activities ramped up significantly during the and we're going to move to page eight.
54:55
This is one of the luxuries of reading the Wall Street Journal in print. um during the pandemic.
55:02
So, starting in 2020, they have frequently owned multiple homes at one time and show no obvious signs of trying to time the market for the best returns.
55:10
Records show they bought >> patient.
55:12
>> No, they're just they just got the hot hand.
55:14
They're they're they're they have the mightest touch.
55:16
Uh they don't need to time the market.
55:19
They deliver value everywhere they go.
55:21
Uh they bought at least eight homes in 2021. Wow. And 2022.
55:27
uh record show from the 34 homes tracked by the journal that the couple have since sold.
55:31
They have posted a profit of what roughly $190 million.
55:36
That has to be in line with how much Ellen Degenerous makes off her show and her core business.
55:42
This is the this is the side hustle of all side hustles.
55:44
Um >> their average return >> research >> their average return based on the original purchase price to and the subsequent sale price is about 37%. Not bad.
55:56
You need to raise a fund. Let me in. OP in this.
56:01
>> The degenerate home buyer >> flipper, but not very degenerate. I mean, who knows?
56:06
Probably a lot of leverage involved, but it's paying off.
56:09
>> There's some there's some degenerate gamblers that actually make a lot of money. That's true.
56:13
Doesn't mean that doesn't mean that you're they're not being wild.
56:18
>> The pair's business manager, Harley Newman, said Degenerous's real profits are much more modest once the costs of renovating are factored in.
56:24
I would love her to have made that big of a killing, he said with a laugh.
56:31
Forget about the real estate agents and the escrow and title people, the costs of contractors and designers and the army that comes in once we've closed. It takes a village.
56:42
He said those numbers don't also don't account for what Degenerous spends on furniture that is usually included with the sale.
56:48
None of the furniture is inexpensive.
56:50
He said she takes the art off the walls, but everything else gets sold.
56:54
Newman said 34 is an underestimate, saying he probably thinks she has bought and sold at least 50 homes since we've known her. >> Love it.
57:04
>> Buying them in trusts. >> Yeah, >> secretly.
57:07
>> Very hard to buy a home secretly.
57:07
It can almost always be discovered.
57:09
The Wall Street Journal, I mean, they uncovered 34 of 50 or so.
57:12
Uh, the couple's homes have varied in size and in style from mid-century and contemporary to italian and English tutor.
57:20
It's not that I get bored.
57:23
I'm just so passionate about architecture and furniture that you can only buy a certain type of furniture for a contemporary house or mid-century house said degenerous in a phone interview.
57:32
She she talked to the journalist. Amazing.
57:36
>> A large journalistic force headed to standby.
57:39
>> She said she has lost count of how many homes and they have bought and sold. That's great.
57:42
That's like you with Angel Investments.
57:44
Uh tragically, >> she has a home buying addiction and it's paying off.
57:49
>> I text I text myself when I make a new >> Oh, >> angel investing addiction.
57:52
So, I just got to scroll up far enough. >> Got it. Got it. Got it.
57:55
Uh uh there is now a certain cache in owning an Ellen house, said Ryan Ry Williams of the Beverly Hills Estates, who represented a Hollywood executive who purchased one of their homes in Monaceto a few years ago.
58:10
Once somebody knows it's her house or she had a hand in it, it adds value.
58:12
In LA, she's synonymous with quality.
58:15
She's she's a tastemaker. She cares about taste.
58:19
Many of the homes are have been sold offmarket without ever being listed for sale.
58:23
The couple's Hollywood rolodex seems to have come in handy.
58:26
Comedian Will Frell and the late actor Heath Ledger and singer Ariana Grande are a few celebrity buyers of Allen houses.
58:35
Degenerous said real estate a very lucrative hobby.
58:38
Can you imagine Will Ferrell like roleplaying as Ellen Degenerous after buying one of her? >> Yeah.
58:45
You imagine him in his in his uh in some of his titular roles as kind of a disheveled middle-aged man stumbling around a $40 million Ellen Degenerous neatly appointed home.
58:54
Uh and it doesn't quite fit.
58:57
Uh but I'm sure he is much more money.
59:00
>> I like how she just flat out says to the journal, "Real estate has become a very lucrative hobby." >> Let's go. >> Let's go.
59:06
Turn your hobbies into side hustles.
59:09
Turn your side hustles into >> I mean, this is basically a main This is basically the main hustle now.
59:13
She doesn't do the main show anymore. >> Yeah, that's true.
59:15
Uh, the 67year-old former television host has a has long had a passion for interior design and would have been a designer if comedy hadn't panned out.
59:25
Uh, she attributed her itchy feet in part to her family frequently moving between rentals in her native New Orleans area.
59:32
We never owned a house, so I always wanted >> New Orleans. That was on your A tier.
59:38
>> That was in my A tier. Yes.
59:38
I got in a lot of trouble for that. Uh people did not enjoy.
59:42
>> Nobody Nobody got the joke on some people got the joke, but uh I posted my tier list of best cities in the world and it uh and it dusted uh some ruffled some feathers.
59:53
I don't know if you have it pulled up, Jordy.
59:57
>> I'll pull it up again.
59:57
So John, you said city tier list that will trigger everyone, but is true. >> True.
1:00:02
S tier NYC, LA, SFDC, Miami, Chicago, Austin, and Boston.
1:00:05
A tier, Seattle, Nashville, Vegas, New Orleans, Detroit, Bakersfield, and Reno.
1:00:14
>> And then no, there was nothing in the B and C tier.
1:00:16
And then D was of course London and Paris.
1:00:20
>> And then F was Rome, Berlin, Tokyo, Dubai, Hong Kong, Barcelona, Sydney, Buenosir.
1:00:24
So, basically, if somebody if somebody said, "John, >> I'm going uh I'm going to Sydney.
1:00:29
I'm going to see the opera. Do you want to come?"
1:00:34
>> I'd be like, >> you'd be like, "Sorry, I'm in Bakersfield." That would be >> Yeah.
1:00:37
>> And then if somebody said, "Hey, >> hey, all paid trip to Paris." >> Paris.
1:00:41
You say, "Sorry, I'm actually in the biggest little city, Reno." >> Reno. Exactly.
1:00:43
I would prefer to be in Reno.
1:00:46
>> Anyway, we had some fun with that.
1:00:46
Uh, well, we have our first guest of the show, Joe Weisenthal, on the phone. >> On the phone. >> Wired on the play. Hey, we got Joe.
1:00:55
>> Pull up this picture uh that we just commissioned of Joe. There we go. >> That's real.
1:01:01
>> And it's a real picture. >> Yeah. Can you hear me? >> Yeah.
1:01:03
You look You sound as good as you look.
1:01:08
>> I understand why you me. I had a very >> Yeah. >> Yeah.
1:01:11
I had a very active summer.
1:01:11
I didn't want to reveal it to uh everyone, but happy to have you with the exclusive on my new look. >> That's fantastic. >> Incredible.
1:01:19
Uh, always great to catch up and always uh I'm surprised you're away from your terminal on a day like today.
1:01:26
Uh, but >> yeah, it's jobs day. It's the Super Bowl.
1:01:29
>> It's the It's Joe's Day. >> It is the Super Bowl.
1:01:32
You know, it is the Joe day.
1:01:34
It is the Super Bowl day. It is the jobs day.
1:01:36
You know, after 8:30, you know, obviously there's the initial hit and then there's the rush and then there's the market reaction.
1:01:43
And as as much as it is the Super Bowl, by the, you know, by the middle of the day, I'm already like, okay, I'm I'm good for the day.
1:01:50
I had such a such a high from following the numbers and seeing all the reactions and reading all the tweets, etc.
1:01:56
that it's like, all right, I can sort of run some errands in the afternoon on jobs day. >> There we go.
1:02:02
Well, thank you for squeezing this, Aaron.
1:02:04
>> So, yeah, take us through the numbers.
1:02:04
I mean, the market reaction, the the Dow is down half a percent right now. NASDAQ's off 23. Bitcoin's up 1%.
1:02:10
So >> yeah, you know, it's an interesting So like the number was not great obviously uh coming in uh solidly below expectations.
1:02:23
I think everyone sort of had a feeling it was going to I think there's just been a lot of anxiety about the state of the labor market right now.
1:02:30
You know, people talk about the so-called whisper number where it's like, okay, here is the forecast that Wall Street has, but here's what everyone sort of really thinks.
1:02:36
was pretty clear that I think a lot of people just sort of thought it could be a miss.
1:02:42
Um the uh last month actually was revised up a little bit but the month before was revised down substantially such that uh June was actually uh now negative which is the first time since uh I think December 2020 that we had a month of job losses which I think is uh interesting.
1:02:58
Once again um healthc care employment so that added 31,000 jobs in the month.
1:03:05
So what that means is that once again if you exclude health care the economy overall has been shedding jobs for some time which is >> including manufacturing. >> Yeah.
1:03:18
So manufacturing employment down 78,000 so far this year.
1:03:21
It was another decline this month.
1:03:24
Look, like this is what I would say about manufacturing, which is that I wouldn't nec, let's say a tariff strategy were going to work um in the long term and we were going to have this sort of, you know, strong re-industrialization of the United States economy.
1:03:40
I wouldn't expect it to work right away.
1:03:42
I mean, the tariffs were unveiled on April.
1:03:44
But what we can say is that so far those numbers to the extent that this is a real priority of the administration or policy makers or others to the extent that this is a real priority priority it's clearly going in the wrong direction in 2025. >> Yeah.
1:04:00
Um also I mean last night there was that dinner at the White House with all the tech leaders and the numbers that were thrown out were staggering.
1:04:07
600 billion from Apple, 600 billion from Meta, but that doesn't necessarily mean massive jobs growth because building a data center might just be a multi-billion dollar uh check that's written to TSMC.
1:04:22
>> This is the funny thing with the sort of data center AI sort of thinking about its massive impact because first of all, you're obviously correct that these huge checks don't necessarily mean massive jobs growth.
1:04:34
And if we're going to take seriously the promise of AI, it shouldn't lead to jobs growth. Yeah.
1:04:39
The test of AI is arguably jobs destruction, right?
1:04:44
It's about what jobs that currently exist in the economy can be replaced by something that we call AI.
1:04:50
And so not only do the data centers not add to uh employment in a meaningful way, if those turn out to be good investments, if there's a payoff, if they drive productivity, you would expect them, you would almost hope them to be labor market negative.
1:05:06
>> Maybe I mean there is a world where where it's like a a worker plus AI is additive and you can underwrite hiring that. So there is a hiring.
1:05:14
>> Well, in our conversation, so we talked with >> I'm not a I Yes. >> Yeah.
1:05:19
>> Yeah. I'm not a doomer like in the sense I I'm skeptical of this I find myself just from a sort of pure thinking about it through the economics lens of this idea of oh AI is going to lead to mass unemployment just for all the obvious reasons that anyone can say I have cost
1:05:34
savings because of AI well I'm going to like spend that money somewhere yeah but the question is do these investments actually free up resources or enable new things that uh expand our capacity of what we could do with labor that's really the question more than the direct job creation. >> Yeah, Jordy. >> Yeah, Jordy.
1:05:53
>> Uh yeah, one uh point we we interviewed Palanteer CFO and obviously Karp as well yesterday and they said something like revenue is obviously up massively in the last few years.
1:06:04
Headcount is only up 12% and they said specifically we expect to have fewer people >> in the future.
1:06:10
Yeah, I saw that quote which I found to be really striking and it is sort of again this sort of very weird condition.
1:06:17
Maybe we've talked about it before.
1:06:19
I'm not sure not, but it does seem like we're in some sort of uncharted territory here with respect to the fact that, you know, I don't know what's happening on a given day.
1:06:29
Okay, maybe the NASDAQ's down a little bit, but you have all these names that are at or very close to all-time highs.
1:06:35
highs. any other time in history uh I think where you're talking about sub sector near all-time highs you are also associating it with a massive expansion of or at least a significant expansion of headcount typically this is just sort of how it is in any industry
1:06:51
tech or otherwise you intuitively link stock performance with headcount and so it's interesting that here is a situation in which not only is is this being articulated this sort of divorce between revenue growth and employment growth but also it's not it's not just a theory. It's clearly been happening in
1:07:06
It's clearly been happening in the industry for some time already. >> Yeah.
1:07:10
I wonder what Trump's like bull case is.
1:07:12
I haven't heard him kind of reconcile what's going on in AI and re-industrialization.
1:07:16
There's like broad strokes of like let's bring back the jobs.
1:07:21
There's not a lot of early evidence of that, but I I'd be interested to hear from people in the administration about just like paint me a picture of what it actually looks like.
1:07:29
What does the American jobs economy look like in four years if everything plays out like you want?
1:07:34
Like what what what are people doing?
1:07:37
Because it does seem like that we're going through a period of change.
1:07:40
through a period of change. Uh I don't know >> what about uh >> no I mean I do I think I to and in defense of the administration right a lot of people are I think people all over the place are scratching their heads over this question because what I
1:07:53
think people want but what the dream is when they close their eyes and they want to see an economy in which you don't have to be an absolute superstar computer science PhD um from uh Carnegie Melaner or whatever or Stanford to get a great job. there
1:08:06
or Stanford to get a great job. there what should be some sort of broad middle of decent employment whatever it is and into defense of the administration I don't see many of people anywhere articulating well what that ultimately uh what sectors or what ultimately drive that sort of employment abundance so to
1:08:25
speak >> the youth unemployment uh data as well is absolutely brutal Bloomberg economics had had a chart showing it basically ramping in a way that it hasn't Uh it's youth unemployment is rising at the fastest pace in in the past 15 years other other than the pandemic sitting at um sitting at what's the number 10 and a 12.5% between the ages of 16 and 24.
1:08:47
5% between the ages of 16 and 24. >> Yeah.
1:08:52
No, I think it's it's important to so there has been this debate in the labor market which is very important and interesting which is we know that the pace of job creation has slowed.
1:09:01
No one is disputing this fact.
1:09:03
Every month we're you know it's just the number of new jobs in the United States is uh going down.
1:09:10
Then the question is well maybe some of that is because of the changes in immigration practices or maybe some of this is has to do with just sort of normalization of the economy after a crazy few years.
1:09:20
And so maybe some would argue that the pace of job creation slowing down does not automatically say okay we're heading into a recession.
1:09:29
That being said, the question then the test then becomes, all right, what about just the ability to get a job if you want one?
1:09:39
>> And that's sort of essentially what the unemployment rate is.
1:09:41
But it's interesting to watch some of these demographics that historically are sort of more marginal, more vulnerable.
1:09:46
The youth unemployment rate is one.
1:09:48
The black unemployment rate is another.
1:09:50
That also that was at its highest since October 2021.
1:09:54
And so even though the headline unemployment 4.
1:09:56
3% still pretty low by historical standards, what we're seeing is this deterioration of the uh of the job finding ability for some of these sectors of the economy that tend to you know maybe the uh the sort of first to let go or some of these more marginal uh marginal um marginal segments of the labor force.
1:10:19
labor force. Is there a narrative coming together about what's driving the uh health care employment numbers and the healthcare job growth because it yeah it feels like a lot of our elders are moving beyond UNK status to >> I mean they there weren't massive
1:10:36
layoffs America because I mean there weren't a lot of like healthcare layoffs during co if anything those were the people that kept their jobs and then healthcare isn't particularly sensitive to interest rates before we get into this too much. I mean, I think the big thing is is CEOs
1:10:50
I mean, I think the big thing is is CEOs broadly, even if they're seeing massive revenue growth, >> it's hard to go out on an earnings call and say, "We're seeing massive efficiency gains.
1:11:01
We're we're leading in AI in our industry.
1:11:04
We're getting all these benefits from AI and then be like, well, okay, our our employees are getting so much more efficient."
1:11:10
And then be like, "Well, you also are ramping why are you ramping headcount >> the same, you know, same way or or um Right. Right.
1:11:19
Well, I think so on this point specifically, I also do think there was maybe you even though I think many people would say that the formal Doge hasn't accomplished particularly much.
1:11:32
Maybe other people would argue otherwise.
1:11:34
I just think there is just a quote vibe shift on quote so to speak where a lot of people are just sort of proud of the fact that they're keeping um head across all of these things.
1:11:41
And I think sort of Elon Musk may have sort of uh shot the starting gun on this vibe that everyone can look within their organization and say, "Do we really need all of the people that we've hired, particularly after the boom years of 21, 22, and arguably 2023."
1:11:56
But I agree on the healthcare employment standpoint.
1:11:59
I mean, I would say two things.
1:12:01
One is, yeah, it's the uh it's the aging population.
1:12:05
There does not see it's hard to imagine what would slow this train down.
1:12:09
I guess it's slowing down a little bit because of course there have been some of those Medicaid uh cuts to Medicaid growth etc.
1:12:17
So uh there is reasonable to think that maybe at the margins the monthly numbers of new headcount into the space is going to not be as fast as it was.
1:12:28
But it is very hard to envision what could happen in the short or medium term.
1:12:32
That wouldn't automatically mean this sector is just going to need a lot more people every month.
1:12:39
I'm certain if you talk to any sort of health care network of any sort that's on the ground in any community, I'm certain still today in September 2025 that they would identify acquiring talent as one of their big challenges right now.
1:12:54
>> Uh talk to me about what we're seeing from the Fed.
1:12:55
The uh poly market has the number of rate cuts uh spiking today.
1:13:02
three potential rate cuts in 2025 spiked from uh 18% up to 38% and uh and the chance of just a single cut is is falling as well as two cuts.
1:13:13
So Paul is certainly expecting more cuts to come >> and most people Yeah.
1:13:18
most people pricing I mean it's pricing cut. >> Yep. >> Yes.
1:13:24
So I think you know it's funny the last time uh I was chatting with you guys was from Jackson Hole and that was a really interesting moment because you hit you if you talk to a lot of the regional Fed presidents like I don't know like there's still so inflation still looks kind of warm.
1:13:38
Um it's not totally obvious that a cutting cycle or certainly an aggressive cutting cycle >> but you said I remember you said >> you said the labor market is clearly softening.
1:13:51
this is the case for cuts like you you you uh you said that >> and laid that out. Thank you. Thank you.
1:13:59
I I if I said something smart I appreciate you remembering it.
1:14:01
Uh but you know Paul's speech at Jackson I called it.
1:14:06
That's that's the main takeaway here. I called it.
1:14:07
Uh no but you know it is it's uh Paul's speech at Jackson the whole clearly clearly centered risks to the downside with the job market and I just think everyone has come around to that view.
1:14:19
And so now the question is especially in the wake of today's number is that not only does September seem like a lock, it is for a rate cut.
1:14:28
I think the decisions in like 10 10 days, the question is could they go 50 basis points, could they go aggressive kind of like they did uh last September and then also I think uh October which people thought maybe they take a pause after a race cut that is now perceived as a good chance.
1:14:44
So I think this sort of world really is coming around to arguably the Paul uh the Powell and then the Christopher Waller view.
1:14:53
He's probably been the most dovish uh of the Fed governors over the last six months.
1:14:57
He's been pretty forceful and saying look um the labor market is clearly softening and rate cuts are due.
1:15:03
And I think right now um it's the uh it's the Waller Powell sort of view that's winning out in markets and the expectation is they'll be able to get the rest the rest of the FOMC behind.
1:15:13
Uh do you have any insight into what's going on with the Treasury doing a bond buyback to lower yield?
1:15:17
Uh someone in the chat is uh joking that they're printing money to buy back printed money.
1:15:23
I don't know if that's real. >> Same old same old.
1:15:27
>> I I you know if I to be honest I I do not put I think these things tend to be very marginal and sort of plumbing related.
1:15:37
You know, ultimately the sort of long end of the yield curve comes down to the market's view of the inflation trajectory and what the Fed is expected to have to do to >> maintain essentially its 2% goals.
1:15:48
Some of these Treasury moves, you know, they may have to do with liquidity, etc.
1:15:52
But I my advice to people when I've encountered these topics in the past is that generally these things are somewhat noise and to keep your eye on the ball about what's happening in the economy over the medium term and how you expect the Fed to respond to.
1:16:10
>> So what's the next uh date on the calendar that we need to be tracking?
1:16:12
Is it the next Fed meeting that's the big news or is there going to be more data?
1:16:18
>> Yeah, so that's in >> Yeah.
1:16:20
>> So that's in two weeks.
1:16:20
You know, the thing in the meantime, what I would say is, uh, yesterday we had the weekly initial jobless claims data that's been creeping higher.
1:16:30
I think you should keep that comes out every Thursday.
1:16:31
Um, and I think people should keep watching that because one of the ways that the economy has been characterized for really like over a year now is they talk about this low hiring, low firing equilibrium, which is that there aren't a lot of layoffs, but also it's not a great time, you know, not a lot, as we've been talking about, not a lot of headcount expansion.
1:16:52
>> The initial jobless claim has been picking up a little bit lately.
1:16:56
Yesterday we got 237K, I believe.
1:16:56
That was ahead of it was a bit higher than expectations.
1:17:00
And you don't have to wait.
1:17:02
You know, like I say, jobs report, Super Bowl once a month, but you get these mini Super Bowls every Thursday where they talk about initial jobless claims. It's no year data.
1:17:12
Oh, one other thing, so keep an eye on that. Yep.
1:17:16
>> Um, also this coming Tuesday, there's something called the and I don't remember what this acronym stands for, but it's QCEW benchmarker division.
1:17:26
So, it probably says for quarterly census employment something.
1:17:30
This is actually how they sort of reset labor market data because we know it's all very noisy, but every quarter they draw from actual um a a complete sample of everyone who's paid into the uh unemployment system.
1:17:44
And so they get this very big snapshot and it could show there's this view it could show that the pace of job creation for all of 2024 going back has was lower than expected.
1:17:58
So they're they're always doing these revisions, but I suspect that Tuesday will be interesting in terms of what uh what it says backwards looking about just how much employment uh there really is right now.
1:18:11
>> Yeah, I'm I'm looking at the quarterly census of employment wages and it says that Santa Clara, California has the largest fourth quarter over the year wage gain at 15%.
1:18:19
And now I'm thinking if uh if Menllo Park will see a massive spike in average wages because of the the AI trade deals.
1:18:28
It's just they hire five people at a billion dollars a year. >> Yeah.
1:18:33
Speaking of big pay packages, did the did the new Elon pay package feel low to you?
1:18:39
>> Yeah, they're just paying them a trillion dollars.
1:18:40
What's the point of reinccorporating from uh from Delaware to Texas if they're only going to bump your target a Yeah. Should something. Yeah. >> Yeah.
1:18:54
Somewhere where you can really where an executive can really get paid for the work that they do.
1:18:59
>> Look, for once, >> I want 100% of the dollars that I create in the shareholder value here.
1:19:05
>> And were were you disappointed to see that the White House snubbed Meek Mill on the invite to that dinner, the AI dinner last night?
1:19:11
It felt like they really it was a big FU to Philadelphia broadly.
1:19:16
>> Yeah, I I would agree. >> I was shocked. I was shocked by that.
1:19:19
Uh it's time it's time to shake that room up in terms of who uh who are the big tech names that get invited to these things.
1:19:28
But clearly our upand cominging AI entrepreneurs uh you know uh regardless of what industry they're currently in or had been in uh need to have a need to have a voice at the table.
1:19:39
I do think going forward too we really need to have inflation data excellent and low power.
1:19:43
Um just generally when when you see these sort of when you sort of when you see these sorts of wage gains so concentrated we need to start having a formal you know on the Bloomberg and be CPI >> 4 CPI 4 CPI X-Men low power that's the kind of data that we need.
1:20:00
>> I mean there's also a $10 billion tender offer going on at OpenAI.
1:20:02
So, you know, if you're in the market for San Francisco, >> somebody somebody was running the numbers and and showing that there's like there's there's only I think a few hundred homes that are in the like4 to$10 million range in the in San Francisco competitive >> and and and so imagine you just flood the market with like $10 billion in like fresh cash and you get a bunch of cash buyers. I mean, >> yeah.
1:20:26
Uh last question, we'll let you go.
1:20:28
There's something in the chat.
1:20:29
Someone's talking about the US Open, which I I guess is uh US US. Okay.
1:20:33
United States >> open market operations. >> United States open. >> Yeah. Oh, open. Yeah.
1:20:38
Maybe uh isn't there like a real estate company?
1:20:41
Maybe it has something to do with that. I'm not sure.
1:20:44
Anyway, >> but do you have a prediction? They want to know.
1:20:47
They want to know if you're watching tennis and if you have a prediction or favorite, >> who are you rooting for?
1:20:52
>> I don't I'm so embarrassed.
1:20:52
Every summer I try to get into tennis and I actually take a few tennis lessons every summer and it's like this is the year I'm going to go to the US Open.
1:20:59
This is the year I'm really going to pay attention.
1:21:01
No, I I said we have nothing to despite my efforts year after year, once again, nothing positively contributed to this discourse. >> Yeah, me too.
1:21:09
I I have no idea, but I uh hopefully I will see some more uh great capital allocators photographed in paparazzi uh shots.
1:21:16
That's what I watch the open for.
1:21:19
I watch the paparazzi feeds. >> As do we all. As do we all.
1:21:23
>> Anyway, anyway, uh Joe, enjoy uh enjoy your afternoon. We love you.
1:21:28
>> We'll talk to you soon. >> Talk soon. Talk to you soon. >> Byebye. >> Bye legend.
1:21:34
>> Um, >> did you see >> linear?
1:21:36
Yes, it's a purposeful built tool for planning and building products.
1:21:40
Meet the system for modern software development.
1:21:41
Streamline issues, projects, and product road maps.
1:21:42
Start building with linear.
1:21:46
>> It really is a it really is a crystal ball for your road map. >> Yeah, it is.
1:21:52
>> Um, >> anyway, what did you see?
1:21:54
>> Uh, this is interesting.
1:21:54
Uh, Guido Richter uh is doing a hunger strike outside of anthropic.
1:22:03
Uh he said, "Hi, my name's Guido. I'm on hunger." >> Couldn't get in. >> He couldn't.
1:22:09
>> He said, "I'm on hunger strike outside of the offices of the AI company Anthropic right now because we are in an emergency.
1:22:16
>> Anthropic and other AI companies are racing to create ever more powerful AI systems.
1:22:20
These AIs are being used to inflict serious harm in our society today and threat to >> why inflict increasing increasing we'll get to that.
1:22:31
I think it's very likely that he's hitting rate limits on it that might make sense.
1:22:35
>> Um and uh threaten to inflict incre inflict increasingly greater damage tomorrow. Experts are warning us.
1:22:39
Okay, we're going to trust the experts here.
1:22:42
Experts are warning us that this race to ever more powerful general intelligence puts our lives and well-being at risk as well as the lives and well-being of our loved ones.
1:22:50
They are warning us that the creation of extremely powerful AI threatens to destroy life on Earth.
1:22:55
>> Okay, Tyler, what you got?
1:22:57
>> So, I think it also could be, you know, Dario just said they're not selling AI to China anymore.
1:23:00
So, he might just be uh, you know, SPV holder and he's interesting, you know, mad about >> Yeah.
1:23:06
less revenue from not selling internationally. That makes sense.
1:23:09
>> I mean, this is >> usually incredible market.
1:23:10
a public company, you can't really take out a short position and become an activist.
1:23:16
>> This is incredible marketing for anthropic. >> Yeah.
1:23:19
Do you think this is like some sort of like mischief style stunt like to promote the company? >> Yeah.
1:23:25
>> You if you Yeah, you need to get protesters.
1:23:28
>> It's so funny to single out anthropic, >> the most safetyoriented.
1:23:32
Yeah, they are the most safetyoriented like why not just like >> like XAI is like we will just put everything out like it's it's uh it it the first name is actually Adolf >> Mcca >> Mcca. Yeah.
1:23:49
>> Um anyways, a lot of lot of big buzzwords in here.
1:23:51
Uh uh power power bottom dad says this is so crazy I'm kind of for it. >> Yeah.
1:23:58
Does the does the post look ones-shotted at all?
1:24:00
>> Victoria says, "Bro, you're on a fast. If it's good for you.
1:24:02
If you get to seven days, it'll do wonder wonders for your health.
1:24:09
>> Is this bodybuilding related?"
1:24:10
>> People People are just responding to his post with pictures of their food. >> Okay. Oh, that's so mean.
1:24:15
Uh, wait, but are there any uh M dashes in the post? >> Zero M dashes.
1:24:22
>> It's not this, it's that. Nothing like that. Okay.
1:24:24
I mean, it basically says pure the same thing over and over and over. >> Okay.
1:24:28
>> Um, >> kind of a >> I I wish he put this into Claude and and kind of like up >> Guido Reich >> Reich Reich. >> Interesting. Well, good luck to him.
1:24:41
Hopefully he uh dries out and cuts down on the body fat, gets uh extra diced.
1:24:44
It uh we, you know, say it's bulking season, but it's not right for everyone.
1:24:51
Some people got to cut and no better way to cut than go on an aggressive path.
1:24:55
>> He is the co-founder of a company called Stop AI. >> Mhm.
1:25:00
>> And he has he has one connection on LinkedIn. >> Stop AI. Oh, wait. You're connected to him. >> No, no, no. I wish. >> Okay.
1:25:06
>> His only experience on his LinkedIn uh is >> has he stopped AI?
1:25:11
>> Has he stopped anything else? >> Yeah.
1:25:14
It'd be crazy if like his last job was like co-founder at like stop NFTTS >> or like stop time travel.
1:25:20
He's like I was successful.
1:25:22
We don't have time travel.
1:25:24
Stop teleportation technology.
1:25:26
>> Stop hypersonic planes in America.
1:25:29
>> There's not much on not much on Guido.
1:25:31
He is interested in LinkedIn news according to his interests on LinkedIn. >> Interesting. Interesting.
1:25:35
Well, um, one AI you should not stop is putting your sales tax on autopilot with Numeral HQ. Sales tax on autopilot.
1:25:46
Spend less than five minutes per month on sales tax compliance. Go to numeralhq. com.
1:25:49
Um, on the more optimistic side of things, Everyday Astronaut has been reflecting on the Starship program over the last week and one thing has become obvious to him.
1:26:00
This is from Everyday Astronaut, a fantastic space related content creator.
1:26:06
Uh he says SpaceX is enjoying the freedom to try and fail in a way they couldn't with Falcon 9.
1:26:10
Doing anything experimental on the Falcon 9 was risky because it was SpaceX's only source of income.
1:26:16
It was their lifeline, their workhorse.
1:26:18
Making any tweaks to the Falcon 9 to try and land a booster back in the day was a delicate balance.
1:26:22
Don't push the envelope too hard because it could lead to a failure of the primary mission, which did happen twice.
1:26:28
Yes, I believe that they blew up a satellite that Facebook was putting up.
1:26:32
was very dramatic and kind of foreshadows the the showdown and the potential MMA fight.
1:26:37
Uh but uh of course like they have a contract and I I think the money flowed appropriately.
1:26:43
The companies weren't actually upset at each other, but it was kind of a crazy crossover moment in tech.
1:26:48
Uh anyway, uh Everyday Astronaut says, "When SpaceX first landed a booster almost 10 years ago, they were fairly they were they were fairly slow to refly and those first nonblock 5 boosters were only capable of a couple of reflights.
1:27:02
This gave pause to some in the industry community fearing all of this reusability hype wasn't going to pan out.
1:27:09
But SpaceX learned from every landing attempt to develop their block 5 Falcon 9 which has now gone on to have a single booster fly 30 missions. Absolutely unheard of. >> That's wild.
1:27:20
>> Now imagine if SpaceX could have had the freedom to not worry about flying customer payloads to get data during Falcon 9's reusability campaign.
1:27:26
Imagine if they could have tested engine out procedures or push booster re-entry profiles or try hot staging or what or what have you.
1:27:35
This is the phase that SpaceX is now in during the Starship program.
1:27:40
I know we hear the talking point of quote today's payload is data and it could seem like a gimmick or excuse even but that's a freedom almost no rocket program has had before.
1:27:49
to just uh to know you can just try things out, fly real life hardware without bankrupting the company is the ultimate development platform to be able to push engine out capabilities, remove heat shield tiles on purpose.
1:28:02
And we saw that with the video is like this crazy like garbage floating around.
1:28:07
They removed heat shield tiles.
1:28:09
The thing barely made it back uh because they're pushing it to the absolute limit.
1:28:12
Uh they're not just trying to reach orbit.
1:28:14
They're trying to do something that's never been done before.
1:28:18
Build a rapidly reusable rocket.
1:28:20
a rocket that can land and refly.
1:28:20
This could have never this has never been done before.
1:28:24
And honestly, it's silly to think you could do something like this without trying some extreme things.
1:28:29
That's what we're seeing today.
1:28:29
And that's extremely exciting to me.
1:28:31
I can't wait to see version three of Starship fly because uh they've learned so many lessons already and they have a factory capable of making rockets at scale.
1:28:40
And we just get to sit back and watch the cook.
1:28:44
It's an exciting time to be alive. >> Kitchen's open. >> Kitchen's open. and they're cooking.
1:28:48
Uh anyway, you want you want us to take us through the next few timeline posts, Jordy, what you got? >> Absolutely.
1:28:56
I I just feel bad because we kind of glossed over some of uh Allen's trades.
1:29:03
>> 2021 bought a house in Carb for 70 million, sold it for 96 million 2 years later. >> Wait, Carpenteria. >> Yeah, >> 96 million. That's a huge number. Wow.
1:29:12
That must >> Another one bought a house for 7 million in 2017, sold for 11 in 2018.
1:29:15
Another one uh bought uh rebought a house for 14 million in 2021, resold it for 2021 or sorry 21 million in 2023.
1:29:27
>> And some of these so so quick, you know, buy in buy in 2024, sell in 2025, uh $10 million gain.
1:29:34
I mean, she's just pushing this home hills same year.
1:29:40
>> She bought she bought a house for 20 million in 2022, sold it for 36 million in the same year. >> That's great. an absolute dog. >> The Usher House.
1:29:48
Usher listed the home for sale uh for $35 million in July 2019.
1:29:53
We just can't quit the m the mansion section today.
1:29:55
Should we talk about the house of the month?
1:29:59
>> Um >> what else is in here?
1:30:01
>> Why don't you call call Eric right now? >> Oh, yeah. Okay. >> He's ready. >> Yeah.
1:30:04
Well, let's get Eric Lyman on the phone.
1:30:07
I got an important question for him.
1:30:10
>> Uh >> we saw the news about the billion dollar run rate and we just had one question to ask.
1:30:15
Let's get Eric Glyman, the CEO of RAMP, on the phone.
1:30:20
>> Hey, >> Eric, how you doing? >> You're live. >> You're live. >> We're We're live. What's going on?
1:30:26
>> Uh, give us the update.
1:30:26
There's some milestone that just dropped yesterday, I believe. >> It is.
1:30:31
Uh, we we couldn't be happier.
1:30:34
Ramp is now doing more than a billion dollars a year in revenue. >> Let's go. Congratulations.
1:30:39
Uh, I just have one question. Is the job finished?
1:30:45
Job's not finished, guys. Not finished.
1:30:48
We're just getting started. >> Fantastic.
1:30:50
Well, I'll let you get back to work.
1:30:52
Thank you so much for >> Thank you for calling in.
1:30:54
>> We'll talk to you soon.
1:30:54
>> Great to hear from you. >> All right. Cheers. Have a great weekend. >> You, too. Talk to you soon. Bye.
1:31:00
>> It's not the weekend yet.
1:31:02
>> It's not the weekend yet.
1:31:03
>> Uh Mark Hannis has got a buddy from high school who's on his fifth AI startup in two years.
1:31:06
No technical engineering background. He's an MBA.
1:31:08
hires engineers with a low budget to do all the work and build the product while he is CEO and manages just started a new AI education uh startup wish I could short I wonder how this will pan out. It could work. I don't know.
1:31:22
Um depends on exactly what he's what he's doing, but it certainly is not the YC path.
1:31:27
Not the make something people want.
1:31:30
It is a very uh management consultant, very MBA coded strategy.
1:31:35
>> Yeah, good luck getting into YC with this strategy. >> Good luck. Good luck.
1:31:39
>> Uh, Naval says, "If your smartest friends start saying crazy things, pay attention.
1:31:44
A paradigm shift may be underway."
1:31:46
I think he's talking about people getting oneshotted. >> You think that's it? >> Could be. >> I don't know.
1:31:53
It might be, you know, he might be talking about AI, right?
1:31:56
Like you you have really smart friends and they start saying crazy things like, you know, they discover. Yeah. All this other stuff. Not that, not that.
1:32:05
But actually like you know the idea of of super intelligence is a crazy thing to say.
1:32:10
Uh but it might be real you know it might be it might be real and it might and it might start in your customer service organization with Finn.
1:32:18
ai the number one AI agent for customer service number one in performance benchmarks number one in competitive bayops number one ranking on G2.
1:32:25
Um so we we covered the jobs gains.
1:32:30
uh they were all part-time.
1:32:30
Um full-time jobs dropped by 375 356K.
1:32:32
Part-time jobs grew by 597K.
1:32:39
Certainly not good for the durable long-term healthy economy.
1:32:41
Um we >> but earlier this year there was a massive gain in full-time uh employment and then that dropped and so there seems to be girrations every which way.
1:32:50
But anyway, >> yeah, crazy story uh coming out today.
1:32:59
Seal Team 6 in 2019 attempted a covert mission in North Korea to plant a device to intercept Kim Kim Jong-un's comms.
1:33:08
They should have just waited and got him a friend. com >> friend.
1:33:12
Just say, "Hey, this is going to be your new bestie. Just wear it. Keep it on your person." >> That work.
1:33:18
>> Uh authorized by Trump.
1:33:18
The mission failed when SEALs uh unfortunately killed civilians mistaken for security forces.
1:33:24
and get into the story a little bit because we don't talk about geo we don't talk about politics but we we do uh enjoy >> geopolitics.
1:33:32
Uh in early 2019, Trump approved a clandestine SEAL team 6 operation to plan a device in North Korea to intercept Kim Jong-un's communications.
1:33:42
Red Squadron known for killing Ben Laden rehearsed for months.
1:33:45
The mission aimed to gather intelligence during nuclear talks.
1:33:48
This was the uh the >> uh nuclear, you know, Trump and and Kim Jong-un had been uh communicating around uh uh obviously North Korea's nuclear program.
1:34:00
On a winter night, SEALs emerged from the sea near North Korea's coast.
1:34:04
A nuclear submarine deployed two mini subs carrying eight commandos.
1:34:09
>> Lacking real-time drone support, they relied on delayed satellite images.
1:34:11
The shore appeared clear, but a North Korean boat emerged.
1:34:15
Mistaking civilians for security forces.
1:34:18
The seals opened fire, killing two or three shellfish divers.
1:34:23
So, apparently they were on the beach.
1:34:25
The boat pulled up uh started using lights.
1:34:27
They just assumed it was security forces.
1:34:29
Ended up being uh fishermen.
1:34:32
>> Uh >> and anyway, so um apparently the Trump admin at the time didn't notify Congress.
1:34:40
Um and uh the SEAL sank the bodies, abandoned the device, and signaled for extraction.
1:34:45
The submarine risked exposure, retrieving them in shallow waters.
1:34:49
North Korea detected activity but made no public statement.
1:34:53
The mission's failure, hidden by secrecy, risked escalating tensions from a nuclear armed state.
1:34:59
>> So, military reviews justified the civilian deaths under engagement rules, claiming unforeseeable heirs.
1:35:04
The Trump administration withheld details from Congress, potentially violating federal law.
1:35:08
Uh many involved uh many involved SEALs were later promoted despite concerns about special operations uneven track record.
1:35:15
Uh it is fascinating that uh so the disclosed TV talked to 24 anonymous sources including Trump admin Trump administration officials and military personnel with direct knowledge.
1:35:26
Their anonymity reflects the operation sensitivity.
1:35:28
Uh it is uh obviously a tragedy.
1:35:30
Um but uh >> it seems a bit hard to hold special operations teams and say you have to have >> you can't fail if you want to rise up in the organization. >> Sure. Sure. Right. >> Yeah.
1:35:46
But uh yeah, I mean obviously you want every operation to be executed flawlessly.
1:35:51
Um anyway, in other news, the Washington Post is now on Substack.
1:35:56
Let's hear it for the Washington Post.
1:35:58
>> The Washington Posters. Jeff Bezos.
1:35:58
They heard you can post >> you can post notes on subsack.
1:36:02
They said we got to get involved in >> we love posting.
1:36:06
>> We love posting posters.
1:36:08
>> So uh this was I believe a a story that was broken by Emily Sunberg in feed me.
1:36:13
Uh and she did a little bit of an interview here. Uh let's see.
1:36:14
Welcome to my life says Rachel Tastian.
1:36:17
Uh and Emily asks, "How do you see the Washington Post's game plan on Substack playing out?
1:36:25
Is there something that will make your strategy different from other legacy media brands that have joined the platform?
1:36:29
I'm actually not that familiar with other legacy media brands that have joined Substack.
1:36:33
Are you subscribed to any >> The Horowitz?
1:36:37
>> That's specifically a new media brand at this point.
1:36:42
They've been doing media for 20 years though.
1:36:43
So >> that's what I'm saying. That's what I'm saying. >> Play the shots fired.
1:36:49
>> No, I'm just I'm just >> That's funny. >> Just joking around.
1:36:52
>> No, we are the legacy media. They are the new media.
1:36:54
We want to be legacy media.
1:36:55
Uh I don't uh the the Washington Post responds, I don't necessarily see Substack as an alternative to legacy media.
1:37:02
I see it as an additional tool to experiment with in a fantastic way to connect with new readers.
1:37:07
I love getting into the mix in the comments comment section. Yep.
1:37:11
I think a successful journalist in 2025 should be on as many platforms as possible and have a tailored strategy for each one. Completely agree.
1:37:17
Uh so it was important to us that we publish original content exclusively on Substack and really engage with the platform on its own terms.
1:37:25
I consider postrunway something like opulent tips goes to Milan and Paris.
1:37:30
I don't report from the chiffon trenches as Andre Leon Thally lovingly called the fashion world uh for my newsletter.
1:37:39
So now I'm going to bring a bit of that mad cap approach to the accessdriven reporting and criticism I do for the paper.
1:37:46
and I'll still be doing all my usual reporting and runway reviews for the post.
1:37:49
Will there be a paid strategy?
1:37:52
asks Emily Sunberg in feed.
1:37:54
The the Washington Post responds, "Postr runway will be free." Woohoo.
1:37:57
Uh, what does success on Substack looks look like for the post? Says Emily.
1:38:03
Uh, having fun opening the post world to new readers and introducing the amazing voices on Substack, especially fashion writers, to the post's audience.
1:38:11
Well, uh, welcome to Substack, the the Washington Post.
1:38:15
Maybe we should do a collab and talk about fashion. I don't know.
1:38:19
Um I mean I'm I'm dressed to the nines today.
1:38:21
I'd love the Washington invite >> to review the wonderful yellow suit.
1:38:25
Um I'd love to we got to give it up for to Sierra. >> Yes.
1:38:35
>> And uh on uh they're raising some new capital, $350 million from Green Oaks on Sierra at a $10 billion valuation.
1:38:42
And uh Zack Dwit, I >> think he's at Wing >> saying, "Incredible seed investment for Benchmark. They likely own 15%.
1:38:51
It's a $450 million fund. >> Let's go.
1:38:56
>> 3 to 4x already on one investment.
1:39:00
>> We love to see capital allocators win. Goat emoji. >> Congratulations.
1:39:04
Job's not finished, >> but certainly a fantastic milestone." >> Yeah.
1:39:09
Um, Power Bottom Dad says, uh, quoting Joe Weisenthol's post saying that the US has lost 78,000 manufacturing jobs this year. >> That is a lot.
1:39:21
>> Says, "Chad, is this re-industrialized?
1:39:23
I'm kind of tired of winning."
1:39:23
Um, you would I don't know.
1:39:27
It's hard to, you know, Joe Joe's point, which is real, is that you can't expect things to have an immediate impact. >> Yeah.
1:39:36
But at the same time, if US manufacturers were feeling good and had lots of business, >> they would probably be trying to >> keep as many people as they can.
1:39:49
>> There are two there are two economic statistics that I find important in measuring the progress of re-industrialization or industrial might.
1:39:58
The first is jobs like manufacturing jobs are important.
1:40:00
It's the you know in many ways the the heritage and the backbone of the US economy.
1:40:05
Although the US economy has shifted to a servicesdriven economy but if you want to measure manufacturing capacity it is fine to just use GDP.
1:40:13
How what is the total value of all the goods that are manufactured in America?
1:40:19
Is that going up or going down?
1:40:21
I actually don't know the numbers off the top of my head, but um when I think about the next I was talking to someone who was saying that America will re-industrialize, but it will re-industrialize with on the back of robots and automation and there will be much higher leverage for each individual manufacturing worker.
1:40:40
You've seen this with companies like Hrien.
1:40:44
There's not that many people in that facility for a lot of CNC machines that are basically automated.
1:40:50
And that and when you look at, you know, who are we actually competing against?
1:40:55
If you if you're benchmarking the United States against China, yes, China has a ton of people that migrate from outside of Shenzhen into the manufacturing hubs to assemble iPhones during the push.
1:41:08
They they they bring in a million migrants to assemble iPhones right before the new iPhone's released.
1:41:14
Um and China obviously employs tons and tons of manufacturing employees but at the same time they also have lights out facilities where everything is effectively automated. >> Yeah.
1:41:25
>> And when you look at the way at the design of the latest Tesla factories, the design of the latest Starlink factory, we are making things in America, but we're doing it at at a much lower level of headcount.
1:41:36
And the head >> some of our best manufacturers aren't contract manufacturers, right?
1:41:41
They're >> true >> Elon Companies. >> Yeah. Vertically integrated. Yeah.
1:41:47
>> There was also there's a crazy story uh from uh the BBC which I think stands for business business central.
1:41:56
>> Uh >> business business capital >> business business capital. >> That's what I like.
1:42:00
>> Uh they said uh this was basically breaking live or today.
1:42:04
Almost 500 people have been arrested at a Hyundai factory in Georgia by immigration authorities in a workplace.
1:42:14
>> So, majority of those detained at the 3,000 acres site which was built by the Korean automobile manufacturer to make electric vehicles >> uh are Korean nationals.
1:42:24
>> That's very interesting.
1:42:24
>> So, uh South Korea expressed concern and regret over the operation.
1:42:28
which is kind of interesting dynamic to just be like, "Yeah, we regret that because it's the I mean, >> it's South Korea saying that, not Hyundai."
1:42:39
You think Hyundai would be like, "Sorry, cuz this scale is >> got to sort out the visas, guys."
1:42:44
You know, I think everyone's all for like bring the TSMC semiconductor experts to Arizona, but uh make sure that they fill out the immigration paperwork. Yeah.
1:42:54
If they're going to come over here and build.
1:42:57
Um anyway, Buo Capital Bloke says, "Perhaps we are moving to the find out stage of paralyzing the US economy with a multi-quarter barrage of nonsensical, inconsistent and conflicting set of economic policies."
1:43:10
Um and uh there's some people in the chat. Uh >> is this bullish? >> Is this bullish? No, this is not bullish. He's blackmailing.
1:43:16
He's very he's very uh upset about the economic data that was printed today related to um a lot of the economic policies mostly from the tariffs.
1:43:28
>> Alps has a post uh showing the Las Vegas sphere saying it's looking a little bit different.
1:43:33
This to me >> SSI advertising >> is this is this uh super intelligence rearing its head?
1:43:40
Yeah, I I love that Ilio is leaning in to the the bit and having fun with the uh having fun with the the hats and whatnot.
1:43:48
Uh wasn't there another hat? Oh, yes. Pixel Hulk.
1:43:52
Pixel Hulk says they now have a new line of Mark Andrees merch.
1:43:54
And it's a it's a hat that where the head looks like Mark Andre.
1:44:00
This looks like uh this this is like a fantastic AI image. I I imagine this is AI.
1:44:05
It looks like some sort of however they made this, whether it's Photoshop or AI, it's flawless.
1:44:12
>> Yeah, >> I do think this would sell pretty well.
1:44:14
It is ridiculous looking, though.
1:44:16
>> TBPN uh was featured at Volulta. >> Oh, yes.
1:44:22
>> Earlier, uh Theo did a photo shoot.
1:44:22
Uh there's a Ferrari in the picture, which we love.
1:44:27
Uh and I believe one of Volta's uh employees.
1:44:31
>> And uh anyway, shout out to John Fentino.
1:44:36
Uh, I got to do >> I can't wait to visit the Voltit >> HQ >> in Nashville. >> Be great. >> The flagship. >> It's not even the HQ.
1:44:43
This is the flagship store, right? >> The flagship.
1:44:47
>> This is This is the You got to make the pilgrimage. Yeah.
1:44:48
Um >> um we covered uh Tempo, the new L1 built by uh Stripe and Paradigm.
1:44:56
So we don't need to cover it again, but Mert was uh firing back uh in the in the announcement.
1:45:06
They were um uh the Tempo team was basically highlighting uh potential limitations from existing L1s.
1:45:16
They highlighted uh transactions per second.
1:45:18
They highlighted >> moments that uh that you couldn't run payroll again. Yeah.
1:45:24
>> When when Trump if you were trying to run payroll the day that Trumpcoin launched >> Trumpcoin launched on Salana >> is that right?
1:45:31
Not Ethereum because I know Ethereum the narrative around Ethereum has been like the the networks congested there are high fees but that was the whole idea behind launching Salana was that it was going to be much more scalable and there was some sort of trade-off there and then this is like the the the next L1 and people are upset about it in kind of both both camps.
1:45:52
But, uh, I invited Matt on the show and Mert who were both talking about this would love to. >> Yeah.
1:45:57
And they're they're they're going they're they're happily a little bit under the radar.
1:46:01
Now Mert said, "Guys, you can just say you want more full stack control and distribution.
1:46:04
You can also say you want the L1 premium or a controlled validator set.
1:46:08
These are perfectly legitimate answers, but you look unserious and hurt your brand when you start talking about scalability um and uh defending the Salana blockchain." >> Yes. Yes. Yes.
1:46:22
>> Um it is uh proven that it can scale.
1:46:24
But yeah, I mean I I think this kind of play makes sense because of course Stripe and Paradigm would want to own the rails effectively even if it's going to be network driven. >> Yeah.
1:46:37
And it does seem like Stripe has a large enough customer base that they can actually bootstrap the network fairly fairly easily, right?
1:46:42
By just offering it baked into checkouts that are already powered by Stripe potentially.
1:46:47
Um although I wonder I wonder how like what the onboarding process is like because even just getting a Salana wallet set up.
1:46:57
It's not as easy as like oh I have a different credit card and so the same stripe form works the same.
1:47:01
Maybe you wrap it in a credit card. I don't know.
1:47:06
Um I I I I still don't exactly understand like where Tempo fits in the full stack and and and how this gets rolled out.
1:47:12
Um but uh I'm excited to learn more.
1:47:15
I mean we'll certainly have some folks on talk about it.
1:47:16
More importantly for some members of our audience, Mercedes-Benz is teasing the return of the four-door soft top Cabriolet Gwagon.
1:47:24
This is the moment that many of us has been have been waiting for. >> Yes.
1:47:31
>> Uh Gwagon arguably uh greatest car >> Mhm. >> ever made.
1:47:39
>> Uh they have uh done many iterations of the Cabriolet over the years.
1:47:42
I came close to buying one a couple times from my friend Blake who has a company called Found Objects here in LA.
1:47:49
He sources these incredible G Wagons from all over the world.
1:47:54
Um and uh anyways, I'm super happy that they're bringing this back.
1:48:00
This this image that is pulled up on the screen right now is actually I think somebody taking some artistic uh liberty.
1:48:09
Uh the actual image we can pull up here if possible.
1:48:13
I put it in the timeline.
1:48:16
Um but the actual image is blurred out on the official Mercedes account.
1:48:21
And so I expect this to be like somewhat um somewhat uh different than than the picture that we just had up on the screen.
1:48:29
>> What's crazy about this is >> I think they're gonna I just expect them to modernize it a little bit.
1:48:32
So, Mercedes has a G650 Landolay, which is the soft top four-door, but it's a Maybach, and I believe it trades at around a million dollars a car.
1:48:43
Um, and so >> I can't believe some anybody would sell that for just a million. >> Just a million.
1:48:49
Um, yeah, this >> this is the image that he posted on Instagram. >> Yeah.
1:48:56
>> And, uh, anyways, I'm super excited for this.
1:48:58
I wonder how it'll struggle.
1:48:58
I will definitely struggle not to acquire >> to pick it up.
1:49:03
>> John John puts a lot of pressure on me to not just continue buying G Wagons to mix it up.
1:49:08
But >> you gotta mix it up.
1:49:09
>> It is >> I think I think if you want a convertible, >> even Speeder Speeder Speeder drove my G the other day and said, >> "You know what?
1:49:18
I thought these were overhypes, but I get it now." >> I get it now. I get it now.
1:49:22
>> Well, but if you want a if you want a four-door convertible SUV, why not get a Nissan Morano Cross Cabriolet? It's actually a twodoor.
1:49:31
>> Yeah, but if you want a twodoor >> Yeah.
1:49:33
If you want the four-door, Yeah.
1:49:35
you you kind of have to upgrade from the Nissan Morano cross to the G650 Cabriolet.
1:49:40
It'll take you from maybe $20,000 to maybe 2 million, but uh you know, you do get those extra two two doors.
1:49:46
So, yeah, I I I think it's a pretty clear >> value there. I cannot wait for this.
1:49:50
Do you think the uh Gwagon salesman should be on AIO customer relationship?
1:49:57
Adio is the AI native CRM that builds, scales, and grows your company to the next level.
1:50:03
You might be tagged as just already closed one and for some Gwagon owner in Adio and they put you right back in reach back out with >> they certainly do for me. >> They certainly do.
1:50:16
>> As soon as as soon as you move into closed one, they move you back into prospect. >> Yep. Back in the pipeline. back in the pipeline.
1:50:22
Uh oh, Sergey Brin uh was at the dinner last night with Donald Trump.
1:50:28
Uh and Google is back in founder mode.
1:50:30
You'd love to see Sergey having a seat at the table again, says Beth Jzos.
1:50:34
>> This post from TJ Parker.
1:50:37
>> Yes, >> was absolutely insane. >> Insane.
1:50:39
>> We got to have we should we should >> we should call TJ right now and ask him to explain himself. So, he says, "Fun facts.
1:50:45
I was the youngest VP at Amazon." Yep.
1:50:48
Of course, he sold pill pack to Amazon for $1 billion.
1:50:53
>> Uh he said, "I was the youngest VP at Amazon.
1:50:54
I've also personally never bought anything on Amazon."
1:50:56
Which is just absolutely incredible accomplishment.
1:51:02
>> How do you live your life without ever buying a single thing on Amazon? >> Uh it's a crazy book.
1:51:06
Like >> I think what he said I think he just I think he just said if he likes something he sends the link to his wife and then she >> Okay.
1:51:16
That still is you you still have Amazon purchases.
1:51:20
>> He was too >> too poor and then too rich.
1:51:23
>> Poor and then he was too rich. >> Yeah, maybe. >> Yeah.
1:51:26
Uh I mean like really telling on yourself for not taking the gig seriously, TJ.
1:51:31
It's like you know >> Well, he was focused on something else.
1:51:35
I mean like he was focused on >> I don't care, I guess.
1:51:36
But no, I >> still should be >> I just think like like if you if you get a job at Apple, you're expected it's polite to wear an Apple Watch.
1:51:44
You know, you walk around Apple HQ Certino, like everyone's wearing Apple watches.
1:51:49
They're not wearing Samsung Galaxy Gears, you know, they're using the product.
1:51:53
If you there's a there's a famous story about if you are trying to sell a piece of software or any do any sort of business dealing with Nike, when you go to their headquarters, you should be wearing Nikes.
1:52:04
You do not show up to Nike headquarters in Adidas because they will see that.
1:52:10
They will take that as a as a sign of disrespect to their culture.
1:52:13
It's like if we get if we get lunch or breakfast with somebody and they insist on paying and they don't pay with a ramp card.
1:52:20
>> I was about to say >> sign of disrespect.
1:52:22
>> Very big sign of disrespect.
1:52:22
Very big sign of disrespect.
1:52:24
I'd rather just have you not pay at all.
1:52:26
Um but very very sill very silly and I guess uh you know evidence that he was ready to move on and get into the world of investing and venture capital at Matrix where he is now.
1:52:38
Uh Tim Cook has an iconic photograph in Getty Images.
1:52:41
He hit the Abbey Road, says Mark German on the way to meet Trump. You love this.
1:52:45
He is flanked by a crew of what appear to be bodyguards or maybe just the boys, maybe just the homies, but uh he's it's a good good picture.
1:52:57
One for the one for the tech uh the Museum of Business History.
1:53:03
Um we talked about the uh this Oh, we should go into this fabricated knowledge post.
1:53:08
So, uh >> I'm gonna let you cover this. I'll be right back.
1:53:10
>> So, Doug Olaflin has this thesis.
1:53:10
He says, "I think lagging edge is going to be is going the way of solar panels.
1:53:17
Some can win, but the aggregate the aggregate big number of chips is going to be bad."
1:53:21
And so says, uh, first up is Texas Instruments. Where does he say this?
1:53:27
Um, April's pop is mostly pull forward.
1:53:29
Uh, the lagging edge price war.
1:53:32
Lagging edge capacity now behaves differently.
1:53:34
Another upturn may come, but it may be muted and prolonged.
1:53:39
something is broken in auto and industrial.
1:53:41
Uh, Texas Instruments is right to run inventories down.
1:53:43
They likely will not need as much.
1:53:45
There's a lagging edge permaglut.
1:53:47
He says, "What no one wants to admit, lagging edge capacity may be structurally different."
1:53:53
Now, earlier I argued prices had to rise because new fabs cannot profit from selling lagging edge chips at prices set by a fully depreciated fab.
1:54:02
There are obviously pricing problems in the scenario. with a new fab.
1:54:06
A company can't turn a profit by selling lagging edge chips at a price that was previously dictated.
1:54:12
Uh reality, the lagging edge took price in a temporary market upturn.
1:54:17
Now we are reverting to the mean.
1:54:19
The old tread line is back.
1:54:21
There's no meaningful new demand for old nodes and what exists is made and consumed in China.
1:54:26
So you go and you make the smart toaster or the smart dishwasher and you need a chip in there.
1:54:32
You don't need a TSMC 3 nanometer TPU Nvidia chip.
1:54:35
You just need some lagging edge chip.
1:54:38
It's going to be made in China.
1:54:39
It's going to be assembled in the product in China and then you're going to get that smart toaster delivered to you.
1:54:45
And all of that's going to happen within the Chinese ecosystem.
1:54:47
And so if you're running a lagging edge fab in America, Doug Olaflin thinks you're in trouble.
1:54:54
Uh the COVID super cycle plus a new China supply line that does not care about capacity.
1:54:59
Economics points to a forever glut.
1:55:01
Uh China has a long record of flooding the low end.
1:55:03
Statedirected capex boosts output at the expense of efficiency.
1:55:08
Doug wrote about this in involution dynamic recently in China's race to the bottom.
1:55:14
Products at 90 nanometer and above should internalize a permanent China glut.
1:55:19
Companies resist uh that conclusion.
1:55:22
But the case studies are familiar.
1:55:24
Solar modules, LCDs, LEDs, steel, ship building, batteries.
1:55:28
You've seen it time and time again.
1:55:30
Uh, China wants to stay on the lagging edge and dominate there the commoditized lagging edge and not worry about uh, you know, and and they see that as the learning curve to get to the the leading edge, but they are willing to sell at a lower margin for a very long time if they need to.
1:55:48
Uh companies can still win share but through performance and packaging rather than by producing older chips at lower cost.
1:55:55
ADI is a masterclass in adding capabilities.
1:55:57
MPWR has focused on higherend power.
1:56:00
The long tail will face a flood of Chinese supply.
1:56:03
Good luck to the older fabs.
1:56:05
I cannot resist talking about Marvel during uh Marll behind the payw wall.
1:56:10
So head over to fabricated knowledge and subscribe to the uh Substack.
1:56:15
Uh and we will have Doug Olaflin on the show again soon to dig into all of the dynamics of both the leading edge and the lagging edge.
1:56:21
So Josh Steinman famous for saying we are going good morning we are going to win every single day has a post here that's not good morning we are going to win.
1:56:30
It says you versus the guy she told you not to worry about.
1:56:34
Roboaxi versus Whimo service area in square miles.
1:56:37
So Whimo has been on a very consistent grind adding square miles every year for the past seven six years.
1:56:46
Uh gone from maybe 50 square miles to now 750 square miles.
1:56:54
Whereas robo taxi went from zero to almost 1,000 square miles in uh in just under a few miles.
1:57:00
>> Hard to hard to to to make an equal comparison here. >> Yeah.
1:57:06
>> Based on this single metric.
1:57:06
Yeah, >> obviously I'm super excited about both companies, but uh >> one's still in beta, but the app is doing very well with Robo Taxi. Uh we will see.
1:57:17
They said drivers number one in the charts.
1:57:19
A little bit of a narrative violation.
1:57:23
>> Maybe made a phone call to Tim Cook and Tim Cook said, "Thank you, Elon, for getting us to space.
1:57:27
Thank you for >> We'll put you at the top of the charts.
1:57:31
>> Thank you for Starlink.
1:57:31
Thank you for the Model 3.
1:57:33
Thank you for the Model S.
1:57:35
Thank you for the Model Y.
1:57:35
Thank you for the Model X.
1:57:37
Thank you for the Cybert truck.
1:57:39
Thank you for the Roadster.
1:57:39
Thank you for the Falcon 9.
1:57:42
Thank you for the Merlin engine.
1:57:44
Thank you for the brain chip.
1:57:45
For the brain, for the Neurolink, thank you for Twitter.
1:57:48
Thank you for building that tunnel in Las Vegas. Thank you for PayPal. Thank you.
1:57:54
>> Thank you for Twitter.
1:57:56
>> Thank you for an Valentine.
1:57:58
>> Tim Cook definitely said, "Thank you for an Valentine."
1:58:00
And uh and Elon said, "Cool.
1:58:03
You can have the robo taxi app on iOS.
1:58:06
Anyway, um, >> how'd you sleep last night?
1:58:10
>> Oh, you know, I slept. >> You slept like a log. >> I wish. 71. Only six hours. >> 85. Play the song. Let's go. 85. >> Thank you, Jody. >> I travel days.
1:58:24
>> Travel days are rough. Yeah, >> rough. >> Uh, this go to sleep. com. Get a pod 5.
1:58:28
5year warranty, 30 risk-f free trial, free returns, free shipping, >> and you can use code TBPN. Uh this was cool. >> Yep.
1:58:36
>> So this I mean this was just a cool move in the history of capitalism. >> Yes.
1:58:42
>> Uh Alte Cap says didn't notice this until today.
1:58:46
>> Another shareholder died.
1:58:46
This is a Japanese company.
1:58:47
And donated their shares to the company which was 6% of the outstanding shares.
1:58:54
>> Their will also donated their real estate to the company. >> Yes. Yes. Yes.
1:58:58
>> Uh and uh and Sleepwell said, "Oh, you think buybacks are cool?
1:59:01
How about major shareholders dying and donating their shares to the company plus some real estate for free?
1:59:07
>> Tyler, we do expect you to put the iPhone that we gave you in your will to TBPN.
1:59:11
It will be passed down to another intern in >> 50 years.
1:59:16
>> There's a funny contrast.
1:59:16
I think um yesterday let's not make let's not make the callund years.
1:59:20
Wait, what does Cian Pink think he'll live to? 150.
1:59:23
So that's like 145 years from now. Yeah. For you. >> Exactly.
1:59:29
>> Uh but there was a post yesterday. >> Wait. Yeah.
1:59:31
What is What is this carrot? >> Yeah. What?
1:59:32
Oh, the carrot and the stick.
1:59:34
>> Oh, you're not a stick. >> Carrot and the stick.
1:59:36
>> No, they shouldn't be on the same They can't be attached to each other.
1:59:40
>> You put the carrot You give somebody the carrot.
1:59:42
>> Have you ever ridden a horse?
1:59:42
You You put the carrot on the end of the stick and then you hold the carrot in front of the horse's nose and then the pull.
1:59:50
>> Oh, I'm I'm more I thought we were talking about the phrase like bring the carrot or the stick in a negotiation. I'm >> Yeah. Yeah. Yeah. Okay. We got it. Yeah.
1:59:58
So, so the next time we see Donald Trump doing a uh 4D chess negotiation, we're we're doing away with the chess analogy and we're moving to the carrot and the stick analogy and we now have a physical prop for both the carrot and the stick. >> Okay.
2:00:12
But I was going to say um yesterday I think we sent a post about there was some billionaire who is leaving his will to Neymar. >> Oh yeah. >> For Neymar. >> Yes. >> I love that.
2:00:21
>> So interesting contrast. >> Yeah. Wait uh who is Neymar?
2:00:26
Uh uh some some thing with like a ball. >> He's an athlete.
2:00:31
>> Yeah, >> he plays soccer.
2:00:32
Um is this is this just some crazy way to get around um salary caps?
2:00:39
A businessman is leaving $1 billion to Neymar in his will.
2:00:41
The administrator justified that he identifies with the athlete and decided to give his inheritance to the player.
2:00:52
that >> I think if Steve Balmer really wanted to get the to get around the salary cap, he would, you know, commit ritual suicide and leave in his will his his money.
2:01:02
>> That is the final boss of of salary cap evasion just to just get an extra.
2:01:10
You care so much about your team.
2:01:12
Uh well, in some other uh news that we will have to track the will of uh very sad news.
2:01:16
Uh Georgio Armani has passed away. He was 91 years old.
2:01:22
Uh he was the creator of the powers suit.
2:01:25
Uh he held the reigns as conglomerates rose.
2:01:27
Giorgio Armani the designer and business mogul who brought subtle Italian luxury to the world stage and conquered Hollywood died at 91.
2:01:35
He worked until his final days dedicating himself to the company, the collections and many ongoing and future projects, said an announcement by the namesake brand.
2:01:47
The company later confirmed he died in his home in Milan.
2:01:49
Uh during his years at the helm, he remained steadfastly independent in a fashion landscape dominated increasingly by conglomerates.
2:01:58
Um although he disliked the moniker, Armani was often called the king of fashion.
2:02:03
In an interview with the Wall Street Journal in 2024, just one year ago, he insisted that the secret to success was his humble, consistent work ethic.
2:02:12
This guy has founders podcast episode written all over him.
2:02:17
Uh he owned a super yacht and homes in New York, Milan, Pantilera, Antigua, Paris, San Maritz, St.
2:02:24
Sanrope, Fort De Marmy, and Brioni.
2:02:27
But he showed up at the office every morning and ruled his empire with a firm hand.
2:02:32
He has TVPN mansion section deep dive written all over him as well.
2:02:37
Armani who design who who called himself a designer businessman was the sole shareholder of his company at the time of his death.
2:02:46
>> Wait >> wow >> I had no idea still >> in 2023 its worldwide revenue was 2.
2:02:50
6 6 billion across men's and women's lines.
2:02:56
The Emporio Armani diffusion line and Armani precur interiors, dozens of restaurants, 2,500 retail stores, fragrances, and a cult classic beauty line.
2:03:07
Whether it took the form of relaxed suiting, makeup or interior design, his work whispered refinement.
2:03:16
His stylistic innovations included an emphasis on neutral in between colors, soft shoulders, and a more relaxed approach in between colors.
2:03:26
As I read this in a yellow suit, not exactly an in between color, you know, it's not from Armani.
2:03:31
He often drew inspiration.
2:03:33
>> He still would have appreciated the ramp the ramp suit.
2:03:36
>> I think he would have I think he would have >> as a designer businessman. >> Yes.
2:03:38
Uh he often drew inspiration from Asian culture in his work.
2:03:40
Akira Kurasawa's 1980 A8 let's see about A8 um film called Kagamur Musha inspired his fall 1981 samurai collection.
2:03:54
I love that he has this balance of softness and power said Armani's fellow designer Michael Kors at the last New York runway show in 2024.
2:04:04
Armani became a household name where he where he designed Richard Gear suits in the 1980s 80 movie American Jigalo uh from the 1980s until recent years he was the go-to designer for red carpet looks dressing Oscar winners from Jodie Foster to Kate Blanchett in 2024.
2:04:21
Armani stressed the extremely important role of independence played in his impact.
2:04:26
It's not a question of pride he said it's about getting things done.
2:04:31
When I have an idea, I want to see it through to the end.
2:04:34
He set up a trust in 2016 that laid out his plans for his company, including a charitable foundation and details for how a public stock listing or an acquisition would be handled.
2:04:43
He worked with a close circle of collaborators, including his sister Rosanna, who is on the board, his niece, Silana, who is the head of women's design, his his niece, Robera, the the head of VIP and entertainment relations, and his nephew Andrea.
2:05:00
uh Kamarana, the sustainability managing director.
2:05:04
His right-hand man and close friend was the head of men'swear.
2:05:07
Born in northern Italy, the town of Pasenza in on July 11th, 1934.
2:05:14
That's uh what 200 years before Tyler was born.
2:05:18
Uh Armani was the middle child of three siblings between older brother Sergio and younger sister Rosanna.
2:05:24
Armani described his childhood marked by a fascist regime in World War II as hard scrabble.
2:05:29
At 9 years old, he was standing outside a movie theater looking at a poster for Snow White when a friend came across an unexloded shell of gunpowder.
2:05:38
It caught fire and the young Armani burst into flames.
2:05:41
He said he shut his eyes only to open them 20 days later in the hospital. This is crazy.
2:05:49
Well, there I know we have our next guest, but I can't stop reading this. One second. We're sorry.
2:05:53
We have the CEO of Scali coming on in just a minute.
2:05:55
Um, his only lasting scar was on his foot where his shoe melted into his flesh.
2:06:01
The incident contributed to Armani's desire to become a doctor.
2:06:04
He attended medical school in Milan for three years before dropping out to fulfill his compulsory military service.
2:06:09
After the army Armani's latent creativity was stirred, he began working as an assistant architect designing interiors and displays for a department store in Milan.
2:06:20
He moved into men'swear working for working at a time uh working for a time at Hitman a company owned by Nino Seruti a freelancing and freelancing for other brands.
2:06:31
By the mid 1960s Armani met his longtime life and business partner C Sergio Galleti uh a Tuscan architectural draftsman 10 years his junior Galleti persuaded Armani to start his own business in 1975.
2:06:43
He woke me up from a sort of torper from the little life in which I was living.
2:06:48
Armani told the journal in 2012.
2:06:53
>> Johning, >> I hate to cut you off.
2:06:54
Let's not keep our guests waiting.
2:06:55
Let's not keep our guest waiting, though.
2:06:57
That is a fantastic story.
2:06:58
>> Welcome to the stream. >> Bring in Jason.
2:07:00
>> Sorry, >> John was getting >> carried away there.
2:07:04
>> Have you heard the story of Georgio Armani? He just died.
2:07:05
And uh what a fantastic obituary in the journal today.
2:07:10
>> No, I was hoping you'd keep going. That was that was great.
2:07:12
>> Sorry to keep you waiting.
2:07:14
>> Great to meet you, Jason. Thanks for coming on.
2:07:16
>> Thank you so much for hopping on.
2:07:16
Um >> yeah, nice to meet you guys.
2:07:17
Why don't you uh kick us off with an introduction and kind of your path to how you wind up wound up in this particular situation? >> Yeah, totally.
2:07:26
So, I've been in tech for a long time.
2:07:28
I've been at scale for a year.
2:07:30
Um my background has been in uh starting companies, you know, early early in my career.
2:07:34
Um onto, you know, more notably at Uber.
2:07:37
I started the Uber Eatats business there.
2:07:40
>> Um and that grew uh you know, much larger than we ever thought it would.
2:07:46
How big is the uh how big is that business today if you don't mind me asking?
2:07:50
>> When I left it was about $20 billion a year of GM >> and sorry that >> I think they've grown it to maybe 70 billion 70 80 billion. It just keeps going.
2:08:04
Um >> yeah the um DAR just announced yesterday that uh in Australia alone they've served a billion deliveries which is about two billion meals.
2:08:11
So, um, you know, >> that's a lot of shrimp on the barbie.
2:08:16
>> You know, when you when you Yeah, when you, uh, you know, when you get involved in these things, you're always surprised at how big things can get.
2:08:21
And I think that's going to end up being true here with this current wave.
2:08:24
Um, you know, and, uh, that was one of the reasons why I was excited to, you know, join scale a year ago, joining Alex at the time.
2:08:30
Um and uh you know I had experience in marketplaces done a lot of growth stage businesses things where where demand was outstripping supply and you needed to fix a lot of things to get the business on track.
2:08:42
Um and you know it's been a it's been an exciting uh fascinating journey over the past year.
2:08:47
I mean nothing like I ever expected. >> Yeah.
2:08:50
What was the uh the shape of the business when you came in?
2:08:53
Like from my perspective scale has been a very interesting business in that it hasn't like many companies have a second act.
2:09:00
which I feel like scales at a second and third maybe even a fourth act.
2:09:02
Uh the way I tell the story is uh you know Alex Wang is starting with uh creating data for self-driving cars.
2:09:10
Eventually that business maybe gets rolled into Whimo and and Tesla directly and so scale expands into the RLHF boom during the LLM boom uh and and has kind of grown.
2:09:25
And then my my my question was are we going to see Scale AI take on robotics data or more specific tasks and so uh describe the shape of the business when you joined and and where you were thinking about taking it. >> Yeah.
2:09:39
No, for sure that I mean the history is uh the history is amazing and fascinating.
2:09:43
I think Alex had this insight um that data was the most important thing to models.
2:09:46
Um and that was 9 years ago.
2:09:49
So that's very visionary.
2:09:51
Um and I was very impressed whenever I was talking to him about a a role at the company, you know, only a year ago.
2:09:57
Um and you're right, we've gone from different types of data.
2:09:59
Um and and one interesting thing about like this entire journey is that every single um uh type of data someone has said like, "Oh, when is this going to go away?
2:10:10
When is this going to go away?
2:10:12
When is this going to go away?"
2:10:12
And this is a common thing that we hear and we've heard it so many times that uh you know we sort of are used to addressing it and there's always some other source of data and one of the reasons why is because um data is the application in many ways.
2:10:25
Um you know you know you're you're going from a software space where it's software organizes data for use by humans.
2:10:35
Now you've got data driving applications of things.
2:10:37
And so as we generate more and more data, the models are serving customers.
2:10:41
Um those um customers have higher and higher demands of of what the model should do which then drives uh demand for more data and the data changes.
2:10:52
Um but uh you know we've gone through this so many times from expert data to you know now you know um you know models are working on like how do they do things for for you right? Right.
2:11:03
It was about knowledge capture and then now it's about skill capture. Yep.
2:11:06
>> So um it's been yeah it's been an awesome journey.
2:11:08
Um uh and the company has been extremely agile and extremely commercial over the entire journey which is um you know which leads us to this discussion. >> Yeah.
2:11:18
It hasn't just been just like like if you zoom out it's like one smooth sort of exponential but in fact there's different pools of data that have been maybe a series of stacked S-curves.
2:11:29
But that's the story of all technology and and all progress.
2:11:33
Um, so I'm interested to know uh what I like when when when Alex did invest like the best, he had a very interesting point about uh robotics data being particularly rare.
2:11:45
Like at least we had the internet to crawl and scrape and that was something that didn't it eventually needed to be polished with RLHF, but uh with robotics data there's just so little out there.
2:11:57
little out there. Um, and and I was wondering if if if that was something that you were interested in looking at or uh if it was immediately the skill capture thing of these like really really niche experts, people who know about archaeology and it's just not on the internet and you need to go get some PhD, get them on the platform and start
2:12:16
having them answer questions so that that that can get baked into the models and and uh and we can get out of the what is it like Gellman Amnesia Dunning Krueger for these models where it sounds great until you're asking about the the thing that you're the expert in and then you're like, "Oh, actually it's it's it's only at a it's only at a college level. It's not actually at the full
2:12:33
It's not actually at the full expert level." >> Right. Right. Right. Right. Yes.
2:12:36
So, yes, we do robotics data today.
2:12:38
Um we've been doing, you know, that's that's one of the newest parts of our business.
2:12:41
Um uh that's the way beyond expert data.
2:12:44
Uh so, we've been doing expert data for a year and a half plus, depending on where you draw the line on experts.
2:12:50
But everyone in the data business is in the expert data, you know, is in the expert business because that's what the models need. that's what they demand.
2:12:58
>> Um, you know, something like 15% of the people in our network are PhDs.
2:13:00
Um, 25% have master's degrees and like a very large percentage, I think 60% or so, um, have at least a bachelor's degree.
2:13:08
And so, you know, that is where the knowledge capture has gone.
2:13:11
Um, robotics, yeah, it is interesting, right?
2:13:14
Because you can't necessarily pre-train on this like corpus of information from the past 25 years of the internet.
2:13:20
And so, that probably just increases the size of the opportunity going forward.
2:13:24
But the space is new, right?
2:13:25
I mean like like you know there aren't robots you know walking around the world yet.
2:13:28
So a lot of this is still um in development.
2:13:31
One other thing worth um mentioning is like all the data types um from before we still do like we still data autonomous vehicles companies.
2:13:40
We're still providing computer vision data to the US government um and other parties.
2:13:45
Um and so these things do stack up as you mentioned into what is now a pretty big business.
2:13:51
Is there still some piece of the business that's not AI, not directly AI related?
2:13:57
Like uh like almost like mechanical Turk like I just need an actual human to do something at the at an API endpoint uh for you know a very reliable very scalable and so I come to you and I and instead of going to an LLM I just have people doing it on demand. Is that a thing?
2:14:19
>> That's not a thing for us.
2:14:19
>> That's not a thing for us. I do think that is a thing in the industry like some of that work has gone into BPOS and you know um sort of like lower margin less difficulty type tasks um and so we're at the frontier and part of being at the frontier means you do the hard stuff um the margins are better um the
2:14:36
skill level required is higher um and it pushes you to constantly be driving the business forward and and that adaptability frankly that that started with Alex in terms of like always looking for the next thing and being really close to the tech is kind of what's allowed us to here on the customer side. How are companies buying
2:14:51
How are companies buying this data?
2:14:53
It feel the it seems like there's overwhelming demand.
2:14:56
And >> when you go to them and you say like 10 data, please 10. >> No, no, no.
2:15:01
I I mean I mean more so like what what are the actual like customer relationships look like?
2:15:04
Seems like a lot of the labs and big players are actually working with multiple providers.
2:15:10
>> Um and that's not necessarily a bad thing because different providers can can specialize in different things. >> Yeah.
2:15:17
>> Yeah. I mean um you know we have you know that is true that's like that's sort of a uh a general understanding of the market the the reality though is on the ground if you want high quality frontier data that's difficult to get at volume >> um the number of providers goes down dramatically um and so there's a lot of claims being made out there about doing
2:15:39
things at at scale um you know we're one of the largest providers today we've been one of the largest providers um and so I think think that that's, you know, through all of the change, that's what's allowed us to keep the relationships that we had, which is um it's actually pretty hard to get this data right like like you really have to have the right network. You have to know how to talk to
2:15:58
You have to know how to talk to the network cuz if you imagine like being in the contri, we call them contributors um meaning the people who provide the data to the models uh through us.
2:16:07
If you imagine being in their mindset, you have to have a system that can uh interface with them on what is a part-time job for them to uh give high quality data for a very technical um audience which is the researcher.
2:16:20
Um you know uh so that it it changes the weights of the models in a positive way and that's not a super straightforward thing to do.
2:16:29
Um and so uh yeah I mean and and and the business is going great.
2:16:34
I mean like I've seen a lot of press out there.
2:16:36
Um there's, you know, there's been a lot of coverage, a lot of speculation.
2:16:38
Um, you know, every month since the deal happened, we've had growth, which I think a lot of people will be surprised to hear.
2:16:44
Um, you know, given I mean, like I read the news and then we look at what's going on inside the company and we're just like, okay, we got to start talking a little bit more.
2:16:54
Obviously, I've been in the seat only a few months and so there's been a lot going on, but um, yeah, like things are going well.
2:17:00
Um we have two I mean one thing worth noting like is we have two multiund million dollar businesses.
2:17:06
Um we have our data business which we're most known for. >> Yeah.
2:17:10
So so if you were to split either of these out and we have an applications and services business which which applies this in in customers that business alone has hundreds of millions of dollars of revenue.
2:17:20
And so if you were to break that out it'd be its own unicorn or deck of corn or whatever they're called these days. >> Um so >> that's wild.
2:17:28
Do you ever uh you get a inbound maybe customer fills out a form on your website.
2:17:32
Do you ever you ever have to check to make sure it's not like a runaway super intelligence that's like you know uh off on its own just like hoovering up data?
2:17:43
>> Well, I mean great uh uh great question.
2:17:47
Um uh we tend to know our customers pretty deeply on >> you gota you gota have the KYC process in place >> and and frankly they spend you know these are data is not cheap to procure and so um that would be a very expensive hoovering operation.
2:18:01
Uh if >> well if AI if if AI you know progresses like the AI 2027 crowd uh was projecting at some point or another a super intelligence will come and and you'll have to choose you know humanity or or or the super intelligence.
2:18:15
Have you run into any like super small companies that are customers?
2:18:20
We've talked to some small LLM uh providers like uh they're not building the mega GPT4 GPT5 level models.
2:18:29
They say, "We're still doing, you know, transformer-based AI, but it's it runs on a gaming a gaming graphics card."
2:18:38
And I feel like usually they're just distilling llama or something into a smaller model.
2:18:42
But is there any are there any customers that have come to you and and just had some weird niche use case that's like pretty light on the data, but so differentiated that it actually provides value for them in their particular niche, or is it all just like, you know, the huge labs, the big the people taking really big swings?
2:18:59
Yeah, I think the big swings is most of it.
2:19:01
We do see some of the smaller stuff um uh where you know where we actually are starting to see some data needs which um is sort of you know it goes to just following the market is actually inside of um enterprises. Yeah.
2:19:15
>> So they're not actually building their own foundation model but they're hitting the limits of their own um uh sort of the data that they have to make applications useful in their environment.
2:19:25
And obviously the US government, we do a lot of computer vision data for the department of defense too.
2:19:31
So um those are the more sort of smaller customers and maybe less publicized things that scale does.
2:19:39
Uh are are there other analogies to the DoD where there are companies that have private uh like more like more secure data needs and maybe the the scale process is working on top of their own proprietary data and they need to transform it somehow and and and you get involved.
2:19:57
Is that is that a thing at all? >> Yeah.
2:19:59
So that's the applications and services side of our >> Sure. That makes sense. >> Right.
2:20:03
And so and so the history there is um uh as we were supplying data to the model builders uh obviously scale is very well known.
2:20:10
Alex is very well connected the company knows a lot of people started contacting us saying like hey we kind of thought this AGI thing was just going to like pop out of the box and do everything for us and the reality is is like that's not what's happening at all.
2:20:22
Um uh and uh so as we got pulled into that world and being asked like well how do I apply this to an accounting problem?
2:20:29
How do I apply this to a healthcare problem?
2:20:31
um we started to see the actual fundamental problems inside of these organizations and why they can't get there.
2:20:37
Um, and what's interesting is I like I've actually been on site with some customers in the past, um, in the past month, you know, as we're getting to production, um, with this latest round.
2:20:50
And some of the limits they're hitting is, uh, the actual human knowledge from the executive staff or in like a healthcare setting, maybe the most senior doctor or in an accounting setting, the most senior accountant.
2:21:00
And they, you know, they sort of went into this this thinking like, okay, we might need some data from the subject matter experts here, but but you know, um maybe a junior accountant or maybe a junior lawyer will just go in and label some data where we don't have recorded data.
2:21:16
Um uh and you know, but we um you know, need the models to do something that they currently aren't doing.
2:21:21
they currently aren't doing. And what's happening is is that the senior staff is finding that they need to get involved because as you build these agent systems um which agents are basically obviously just applications running um you know
2:21:35
that leverage AI that coordinate with each other uh in order to align them you which goes to your AI 2027 comment which is like are they going to be aligned to like human values and will they do the things that we want them to do the way that we want them to do them. You
2:21:48
You actually need the question becomes who do you align it to in an organization?
2:21:53
Like do you align it to you know someone who's straight out of college? Maybe.
2:21:55
Do you align it to the most senior person in the organization?
2:21:58
Maybe they need a partner to help them figure out like >> which do you align it do you align it to compliance? Yeah.
2:22:05
The or you know somebody more on the operating side. >> Yeah. Yeah. Yeah.
2:22:11
What are you guys seeing on the like smaller uh model builder side of things?
2:22:14
are you seeing like um the you know the things you're asking me about in terms of like like their needs and specialization?
2:22:23
>> Yeah, I mean I I I think there's like this there's this big question right now about uh inference costs and and do you need to throw a reasoning model at everything?
2:22:31
token costs are coming down, but people just keep moving on to the they're like, "Oh, the the the better model is the same price as the last model."
2:22:40
So, I'm not even capturing that 10% uh or that 10x gain or whatever is happening in the in the cost of inference.
2:22:47
Uh the most recent data point that we actually got that was hard was from Notion in the Wall Street Journal.
2:22:52
Uh Ivan, the founder, said that their gross margins dropped from 90% to 80%.
2:22:58
You know, not not that bad.
2:22:58
I think that that's a trade that they should take all day long.
2:23:02
day long. Um but but you could imagine that uh >> yeah I mean I think I think go >> oh yeah you could imagine that so basically notion's probably paying for the the best-in-class intelligence uh and that's and that's having a material cost on their gross margins but if they figure out that okay what users are really excited to pay for is you know a report that summarizes everything that's
2:23:28
happening in notion across all your documents or they really love templating with AI I or they really love having just a a a chat interface on the on the right that you know is somewhat aware of the documents and they can just kind of ask hey I I you know I I remember putting all of my medical records in one notion thing or I remember putting all my financial or my CRM over here like can you find that for me? um over time I
2:23:48
um over time I would bet that they're able to distill that into smaller and smaller models, bring down the per token cost or token per dollar per million token cost uh to a place where the margins go back up.
2:24:03
But it's kind of a broad question in the market as uh as more and more companies lean into AI and want to deliver like the most frontier model possible to their customers.
2:24:12
Uh no one wants to say like oh yeah we have yeah we did we we added AI to our product. It's uh GPT 3. 5.
2:24:18
People will be like, why? >> What am I paying for?
2:24:22
>> What can you share about like more general business strategy at scale going forward?
2:24:27
You're 49% of the company is owned by Meta, but you guys still have a bunch of customers, tons of revenue.
2:24:32
You talked about two ninefigure businesses.
2:24:36
You got a bunch of people on your team.
2:24:38
like h how are you kind of like rallying the team and and what are what are um what are reasons that people should join scale today and and be a part of the the opportunity you guys are going after? >> Yeah. Yeah. Yeah. Of course. Yeah.
2:24:49
It's worth taking a step back and talking about that deal for a second which is um you know Meta put in over 14 billion for 49% of the company as part of that.
2:24:57
Alex and a and um some others went to Meta.
2:25:02
um uh scale still has over,00 employees um and we're and and a billion dollars on the balance sheet.
2:25:09
Um and so we have a lot of >> and those employees to be clear are not none of those are contributors.
2:25:14
Those are like people that work the >> contributor network. Yeah. >> Yeah.
2:25:19
The contributor network has hundreds of thousands of people.
2:25:20
Um and uh so those are people that are working at scale.
2:25:24
Um uh uh when I joined the company actually I joined the application side of the business.
2:25:29
I didn't join the data side of the business when I joined as a chief strategy officer and I sort of saw the opportunity there.
2:25:35
Um and so we're investing heavily there and customers are reserving budget heavily there.
2:25:40
Um and you know as an example we just uh uh got a $100 million contract with the army um to provide services and data and people to them.
2:25:52
Um and so you've got the data business which is supplying data to the models and then you've got the applications and services business which is making those things make making those models do things inside of large complex organizations fortune 500s US government international governments um and that this opportunity is going to be huge for scale and very few people actually know about it.
2:26:13
This is a multiund million business.
2:26:15
As I said, today we've got contracts with, you know, Qar is a huge customer.
2:26:20
The US government's a huge customer.
2:26:21
We've got dozens of Fortune 500 companies that we work with.
2:26:23
Um, and so, uh, uh, I think the opportunity for scale right now is just to like capture this wave going forward because we're at the very very beginning of actually making AI work inside these big organizations.
2:26:38
Like >> yeah, I was going to ask you where where in big organizations right now, where do you think AI is overhyped and where do you think it's underhyped?
2:26:45
We asked this to Karp yesterday. >> Yeah.
2:26:48
I mean, I think I think it's very overhyped that it's going to eliminate jobs in the next like one to two years.
2:26:57
Like I think this line of thinking would require a change in the curve of capabilities and the change management inside of these organizations where I think it's like way overblown.
2:27:05
like the promise is just so high and the reality of what's going on on the ground is there's value but the value needs to be extracted and that requires a ton of work. Yeah.
2:27:19
>> Um, and so I think what's going to happen with these customers in the next year, if I had to make a prediction, is you're going to go from like having a certain amount of money, which is usually a lot in these companies, um, allocated for like AI initiatives to what is the ROI?
2:27:33
>> Like, you know, the grim reaper is going to come for every AI company that is not delivering value to these customers because because what's happened is they've all been sucked into this idea that like, oh, if we don't invest in this, we're going to miss out.
2:27:45
but because AGI is coming >> and the reality is is that if that doesn't pay off that expectation is very high.
2:27:52
Um and if you're not finding a way to like give ground truth to these customers, they're going to be very disappointed.
2:27:58
>> So do you think we're approaching the trough of disillusionment in some of these big enterprises?
2:28:04
>> I mean like I I think the gap Yeah.
2:28:04
I mean my short answer is yeah.
2:28:06
Um I think that the the the I've seen this in many tech cycles before.
2:28:13
The promises are way out of ours. piece.
2:28:15
There's still a ton of value.
2:28:17
Like it's not that it's like vapor.
2:28:18
Like we are delivering value, but the effort it takes and the amount of data you need to like organize in a company and get from human beings inside the company to make sophisticated applications work is way harder than people are are selling today except for us. >> Yeah, makes sense.
2:28:33
Um h has the contributor has like the geopolitical or geo geographic footprint of the contributor network changed as you've moved towards more like expert focused uh criteria like the PhDs um is it still spread all over the world are people onboarding in Europe and America like what what is the what does the geo uh the geographic footprint look like right now?
2:28:58
now? Yeah, I mean the footprint as you would expect uh uh you know centers around areas where um PhD and masters and advanced degree um uh you know people are um and so you have a very high US footprint um you know parts of Europe uh India and Latin America
2:29:17
there's actually I mean one interesting fact is like um there's >> um a lot of contributors who are who are contributing at a high level who've actually grown themselves >> like Like you would think it would be like if you don't have a PhD you can't do this type of work. Yeah. And you know Yeah.
2:29:30
And you know maybe PhD is too far of a stretch here but like you you like like you don't have domain expertise.
2:29:36
What we've actually seen is contributors go through this whole cycle from a from a from a sophistication standpoint and we think that they're selfeaching. >> Yeah.
2:29:44
Basically the find method >> the find teach. >> Yeah.
2:29:49
Which is kind of amazing if you think about labor markets and like you would just assume like oh the technology would move on but the people are adapting. >> Yeah. Uh Jordy, anything else?
2:29:59
>> No, this was super super insightful. >> Yeah, this is great.
2:30:01
Thank you so much for hopping on.
2:30:03
>> Always welcome to join you.
2:30:03
You just give us a few minutes warning and we'll send you the link and you drop on.
2:30:06
So glad glad you guys are out telling your story and congrats on all the progress. >> Yeah, this was fun.
2:30:13
Thank you for the opportunity. >> Yeah, of course. We'll talk to you soon. >> Cheers, Jason. >> All right, cool. Take care. >> Bye.
2:30:19
>> Let me tell you about adquick. com.
2:30:19
Out ofome advertising made easy and measurable.
2:30:21
Say goodbye to the headaches of out of home advertising.
2:30:23
Only Adqubines technology, out of home expertise, and data to enable efficient, seamless ad buying across the globe. >> That's right.
2:30:33
>> Uh, do we have our next guest? >> Uh, we do.
2:30:34
I think I believe our next guest is in the reream waiting room right now.
2:30:38
We'll bring him into the TVP Ultra Jump. Good to meet you. How you doing?
2:30:43
>> What's happening, >> guys? How you doing?
2:30:44
Thanks so much for having me on.
2:30:46
I feel like I I feel like I need to say thanks uh nine times.
2:30:47
I need to say thanks nine times.
2:30:52
Uh we I mean we love we love uh being thanked.
2:30:54
Uh maybe you know uh but save some of >> Thank you for coming on. Thank you for being you.
2:30:59
Thank you for being here.
2:31:01
Thank you for being >> Thank you for raising capital.
2:31:05
>> Thank you for building. >> Yes.
2:31:07
>> What a fabulous time to be alive. >> Yeah indeed.
2:31:09
Um let's kick it off with an introduction on yourself and the company. >> Yeah. Well, I appreciate it.
2:31:14
Um let me tell you a little bit about Rivet.
2:31:16
We founded the company about a year and a half ago and we the the team has just been cooking furiously.
2:31:21
The the the fundamental philosophy that we have is there's about a half a billion people in the western world that have been completely and totally underserved by big tech.
2:31:32
This is people that do hard jobs in hard places.
2:31:34
So you think people on flight lines, people in factories, people in bucket trucks and people on the battlefield.
2:31:41
We feel that the most transformative application of AI and augmented reality is with these people.
2:31:49
So we set out to build a portfolio of products to do to do just that for that group of people.
2:31:53
That's that's fundamentally probably the most important uh group of people uh operating, building and defending our way of life. >> Yeah.
2:32:02
Walk me through like one case study of someone actually using uh using your product uh to get more productivity. >> Yeah.
2:32:11
Yeah, as you can imagine, I mean, you even had Dr.
2:32:12
Karp on yesterday talking about everybody from plumbers to people sitting in doing financial analysis, etc.
2:32:19
When you think about somebody, let's let's pretend uh they're in an aerospace manufacturing facility, you've got a substantial amount of telemetry coming off of machines, tooling, the actual aircraft itself, and you've got a glut, or there is a deficit of people that are actually able to do that job efficiently.
2:32:38
the application of reasoned intelligence delivering to folks uh on the flight line that are, you know, operating with tools in a heads up hands-free fashion. >> John, >> wow.
2:32:50
>> Is is is going to be the most uh the most >> giving Zuck a run for his money there with the Ray-B bands.
2:32:56
>> Those are those are those look >> these are the these are certainly better than Ray Bands. >> Whoa. Shots fired. Boom, boom, boom. >> It's amazing. >> Um, yeah.
2:33:07
Talk about the progress of the of the business.
2:33:10
Uh, there's a new army contract.
2:33:12
Uh, where are you in that process? What does it mean?
2:33:14
And how did it come together?
2:33:19
>> Yeah, this this program specifically with the army is probably the most important thing that I will do in my career.
2:33:24
Uh, to tell you the truth, I can I can cut to the punchline.
2:33:26
I am holding in my hand a contract executed with the army for $195 million to deliver the next generation of soldier born mission command.
2:33:38
So that's where we are in the business.
2:33:40
The team we started from a clean sheet of paper back in January of last year with a determined focus to build the most comfortable, most rugged, most utilitarian uh uh fighting goggle for the army uh that's ever been seen.
2:33:54
And that's what we've done.
2:33:54
So we were we were selected u over the past few months in a in a very rigorous source selection process.
2:34:01
>> Talk to me about lessons from the soldiers computer from IVAS from hollow lens.
2:34:07
>> Yeah, it was a what 20 year 30-year process um and uh there were lots of concerns about weight uh lots of money spent.
2:34:16
How do you tell the story?
2:34:19
Yeah, you've touched on you've touched on a lot of areas that are of vital importance to us.
2:34:24
In fact, when we started the company, we thought about that whole set of a half billion people in the world that are underserved by modern technology and we boiled it down to four big things. What do they need?
2:34:34
They need a system that is comfortable enough to wear for the duration of a mission.
2:34:37
For a guy in a bucket truck or a flight line, that might be eight or 10 hours.
2:34:41
For a, you know, a paratrooper doing an airfield seizure, that's 72 hours.
2:34:45
So, comfort is number one.
2:34:45
Yeah, >> you need ruggedization because all of these people doing the hard jobs are doing the job in the most austere of environments.
2:34:52
So you need a fully rugged device that is shockproof, dustproof, you know, uh protects against water ingress, can handle the percussive elements of using tools, jackhammers or guns, etc. That's number third.
2:35:03
And finally, you need uh you need a compliant device.
2:35:07
And compliance is is is a very broad category of statutory and regulatory things that these kind of products come under.
2:35:16
And that is specifically over the supply chain.
2:35:20
Specifically, you can't have bad guy parts in a device that's going to be deployed in a secure environment.
2:35:23
There is governance over what constitutes eye protection.
2:35:28
Whether you're on the factory floor and you need true eye protection, that's ANZY compliance for for for not getting your eyes hurt in those kinds of environments, or whether you're a a soldier on the battle battlefield needing ballistics and laser protection.
2:35:40
And then finally, utility.
2:35:42
Utility comes from the ability of the actual face computer and the enduser productivity system to be able to connect to other data, get reasoned intelligence at the point of need.
2:35:50
Where that utility comes back full circle to the enterprise is now you have let's say the enterprise ontology has a set of eyes and a set of ears that understand the enterprise the way that the human would and that's the doop that we're creating with these dynamic task systems for these frontline workers.
2:36:09
Um, is the why now basically just we're in a phase of I don't know technological commoditization where miniaturaturization of batteries and and chips is at a point where it's just we're getting to a place where you can functionally deliver everything that you said and like do you think it would have been possible to build this 10 years ago, 20 years ago?
2:36:33
I I that that that u John it was a perfect prompt like I was going to answer your question exactly that in fact this device could not have been built 5 years ago.
2:36:40
So you have a confluence of a bunch of things happening.
2:36:43
If you think about just the supply chain and the underlying components that go into products like this and you think about the amount of capital that's been poured into them by all of the big tech companies that you know you know what Zuck has actually spent he reports it quarter over quarter on his on on his on the mixture reality lines in the report.
2:37:00
That's something like 60 65 billion I think the last I checked.
2:37:04
Y >> certainly know what the other big tech companies net net you put the sigma on the bottom of that column and you get something like a quart of a trillion dollars has been invested in the underlying things that emit light combine light bend light the processing capability that can go in a small form factor remaining thermodynamically compliant so it doesn't burn your face uh etc.
2:37:26
So all of that supply chain has come together and it's a very hungry supply chain because for 10 or 15 years they've been promised that everybody in the world is going to be wearing these things and that's where the market has actually gone wrong.
2:37:38
Augmented reality, mixed reality and virtual reality has largely been a technology looking for a problem rather than a solution to a big industry's articulated need and that's what we've built and what we're focused on. >> Yeah.
2:37:51
How how important is SLAM?
2:37:51
Like some simultaneous location and mapping I think is the acronym.
2:37:56
But uh the actual idea of like overlaying images into the real world versus just a HUD that is static.
2:38:04
Like when I'm in Call of Duty and I do a 360 no scope, the map, the mini map stays in the same part of the screen the entire time.
2:38:10
Uh when you're in, you know, the Apple Vision Pro and you put a screen down, you turn your head, the screen stays in the environment.
2:38:18
There's benefits to both. What's your take?
2:38:22
>> I I think that there there is a ratio or proportion of what is world locked and what is headlocked and what is body locked in every application scenario and you have to have the right thing to make the best >> user experience and that user experience has to cog you know contemplate the cognitive load of the end user the environment etc.
2:38:40
No doubt slam and the ability to create a you know a holographic can and put it on the table and stay locked.
2:38:48
So as my perspective on the can changes, it's rendered appropriately.
2:38:52
And then being able to do that fast enough so there's not some oculovestibular discomfort that causes you to want to >> y >> puke uh is critical.
2:39:00
So when we think about advanced manufacturing scenarios, specifically the installation of a part on an aircraft, you want to be able to line that up very accurately.
2:39:09
And when the and the quality control guy comes past, he's got to check and validate that it's in the right place and installed correctly.
2:39:16
installed correctly. So in that sense it's very it's it's very important in other use cases you re you know you referenced the call of duty uh kind of thing some course or three off base just like hey I want a crude kind of location like I'm looking this way there's some nouns that are bad or good on this side
2:39:35
of me you can reduce the amount of six off or you know high high fidelity slam that you have to do uh long-winded answer to your question it's critically important to have uh that capability in the system and available to application developers that are developing with it to build a good experience for the end user. >> Do Yeah. On that flexibility point, but >> Do Yeah.
2:39:53
On that flexibility point, but do you want to create two different hardware stacks because I imagine uh a three off headset could be lighter, could have longer battery life, like you're just doing less things and so maybe you can have some savings that you pass along to everything else or or is this just not an issue anymore?
2:40:11
uh the the the issue is becoming further and further less severe or less acute as cameras and processors and the actual algorithms themselves become more efficient.
2:40:23
>> Uh certainly the the market that >> is most important to us and and where we're focused uh we don't need a $300 consumer device. >> Yeah.
2:40:31
What what folks need on the battlefield on the aerospace flight line is a high precision high performance device that delivers both a quick and dirty kind of crude direction of where you need to go to get to safety or or to do something important and then also the super high prevision uh tracking that would be required on the aerospace manufacturing floor.
2:40:51
>> How are you thinking about dual use?
2:40:51
I I we saw a hot take from a uh from a founder on the timeline a couple weeks ago saying that like uh going dual use too early can be a risk.
2:41:00
Palunteer is a great example, but it's kind of an accidental dual use company and they spent 20 years wandering the wilderness and it it you know it it took a long time to build that.
2:41:11
Uh some people have been saying go do go do go dual use on day one.
2:41:17
Other people have been saying, you know, wait and maybe it emerges in a decade or two decades.
2:41:22
Maybe it's your second act uh along like long down the road.
2:41:26
How do you think about the trade-off of of balancing?
2:41:28
>> Well, I think I I think it's circumstantial to the individual company and the individual product.
2:41:32
For us, we thought about dual use immediately.
2:41:34
When I say, hey, there's a half a billion people that are underserved by big tech and underserved by this product.
2:41:39
That is half a billion people that are doing this exact job.
2:41:42
And whether they're on the flight line or in the bucket truck or on the battlefield, largely the same kind of persona working in that austere environment.
2:41:49
For us, the the army contract is is an incredible is an incredible thing for us primarily because if we get it right for the most size, weight and power constrained user that is the most hard on their gear and operating in the most critical environment, we get it right for everybody else.
2:42:05
And that's what we've done.
2:42:06
So that market will come.
2:42:06
In fact, uh when I started contemplating about the the the thesis and our product development and go to market direction, I thought maybe this the the the the commercial market would be serialized behind.
2:42:20
But what we've seen just 6 months out of stealth as people are looking at the product, they're hungry for it and they're ready for it.
2:42:25
So this is going to happen in parallel.
2:42:27
Um, you know, I I I've referenced the Army contract where we're where we've got uh signed scopes of works and execution agreements with some of the biggest aerospace manufacturers in the world to do exactly this thing on both the military flight line and the uh the commercial flight line. >> It's fantastic.
2:42:45
Uh you're out of stealth.
2:42:47
Give us the fundraising update. Gotten got news for us. >> Yeah.
2:42:51
Um I I I got to tell you something.
2:42:54
It's an incredible situation to have a confluence of these things coming together in the same week.
2:42:58
Uh we just finished our A- round that brings uh total investment into Rivet to $90 million over the past month.
2:43:05
Um this is a market that that that our investors believe in.
2:43:12
You know, shout out Doug Filipin.
2:43:16
We've got Steve Cohen 72 led our seed round and then Dukane Capital. Shout out to them. >> That's fantastic. >> That's great.
2:43:30
>> Yeah, you can't I we just can't customers and supporters.
2:43:32
Yeah, >> I I love companies like this where you just take a team with like deep deep deep domain expertise and a bunch of advantages right from the start, but then you when when you have that, you have to execute at an insanely high level and clearly you guys are so fantastic. It's awesome to see. Masterass.
2:43:52
>> Well, thank you so much for taking the time to talk to us. Enjoy.
2:43:56
>> Thank you very much for having us on. Lot of fun. I love the show, man. You guys are innovating. Keep doing it. Come back.
2:44:01
cuz uh we're we're doing this is an austere environment. >> There's bugs around. There's dust.
2:44:07
>> You guys you guys need some rivet.
2:44:07
Like >> honestly, I'm reading I'm reading like chat over here.
2:44:11
I'm reading text messages about who's the next guest and stuff.
2:44:15
Uh makes >> Listen, you guys, we got to get you out of the studio and out into the woods to do some like frontline stuff.
2:44:20
You want to come shoot some guns and do some cool stuff, we'd love you. >> Yeah. Thank you so much. >> Congrats. >> Thanks so much. I appreciate it.
2:44:27
>> We'll talk to you soon, Dave. >> Cheers, Dave. >> Have a great day. Bye. >> Bye.
2:44:30
Up next we have Mert Mumtas from helas.
2:44:33
dev who is telling you about bezel first. Get bezel.
2:44:38
com your bezel concier is available now to source you any watch on the planet. Seriously any watch.
2:44:41
Uh we are excited to talk to Mert.
2:44:43
He's taking a couple minutes out of his busy day to break down the latest L1 for us.
2:44:47
So we will bring in Mert from the Reream waiting room whenever he is ready if he is available. I know his last minute. Mert, how you doing?
2:44:56
Thanks so much for taking the time.
2:44:58
I know it's always crazy with the time change, but >> Okay.
2:45:02
So, so I want to pitch you something. Okay.
2:45:03
Blockchain >> for yapping so that we can get specifically we want more yaps per second. >> Yeah.
2:45:10
People say TBPN coin, but why not an L1? >> Yeah.
2:45:13
Yap YPS is what we're going >> I I feel like you're not that serious with what you do.
2:45:17
I could beat you in my free time.
2:45:19
May maybe I should just uh go up against you.
2:45:22
>> What do you think about that? >> In in yapping? >> No, no, no.
2:45:24
in crypto in in your main thing.
2:45:26
It could be my side thing and I could compete with you.
2:45:28
That sounds like a great plan. >> Anyway, >> the force. Absolutely. Thanks for having me.
2:45:34
I'm uh just hanging out in my F tier city today.
2:45:36
You guys are in your F tier cities. >> Yes. Thank you. You inspired me. You inspired me.
2:45:42
>> That was a we we love that first post cuz it was just it's the perfect post.
2:45:47
It's like how how do you get a bunch of people to agree with you and a bunch of people to disagree with you in the same >> viralate?
2:45:52
I think I might do a tier list every day.
2:45:55
>> Yeah, you created an a new meta. >> Yeah. Fantastic.
2:45:57
Uh anyway, uh take us through like what what actually launched um and and uh what if you can give us like a steelman and then and then your kind of uh your kind of argument.
2:46:08
I'd love to just kind of like get up to speed on what Stripe and Paradigm are doing here.
2:46:14
Uh and then kind of understand some of the trade-offs. >> Sure.
2:46:19
>> Sure. So uh I'm guessing people have all read the announcement but basically it seems there's a new blockchain called Tempo and they they they're messaging in such a way that it's an independent company with Paradigm which is a VC firm mostly in crypto or really exclusively
2:46:35
in crypto and Stripe has the first investors as a team of 15 uh led by Matt who uh co-founder of Paradigm >> uh very very good investor and uh they're basically building what's called a layer an L1 blockchain um called Tempo and it's going to be focused on payments and stable coins. >> Um and so there's a few and and we can
2:46:56
>> Um and so there's a few and and we can go quite a few different directions here.
2:47:01
So there's a few controversies around it.
2:47:03
Um you know, for example, this is the fifth or maybe sixth payments L1 or uh chain that has been announced in the past few months.
2:47:11
Um, it has some parallels to something like uh Libra back in the day from Facebook.
2:47:18
>> Yeah, I was gonna ask. >> Um, yeah.
2:47:19
And then the one other thing that got some heat, uh, is that it's it's an L1 instead of an L2.
2:47:25
So an L2 for people who are unfamiliar would be basically a smaller blockchain on top of a bigger blockchain.
2:47:31
So generally an L2 is on top of Ethereum, which everybody obviously knows of.
2:47:36
Um, and Paradigm traditionally has been very Ethereum ccentric, not exclusively, but very Ethereum ccentric.
2:47:43
And so for them to uh create an L1 instead of an L2 Ethereum um turned some heads as well.
2:47:48
So there's there's a lot there. >> Okay.
2:47:51
So um yeah, I mean that like I know very little about this, but the obvious one is like most of these problems seem solved by Circle and Salana.
2:48:01
Salana. like we've seen a lot of these like big but I mean just in just in this idea of like like there seems to be a serious player from my perspective that's taking stable coins seriously >> and there seems to be a player that's taking transaction seriously >> the I guess given given that you're
2:48:19
building in the Salana ecosystem I guess like some of the push back that I saw from you on the timeline was was that you know complaining that that uh or not complaining but in the original announcement post they shared that They shared an example of like during Trumpcoin launch, you couldn't run payroll or or something like that. Um,
2:48:35
Um, and were basically saying that like we're not going to be able to rely on on something like a Salana.
2:48:42
You were pushing back and basically saying that like there's a lot of reasons that you would want to create a new L1.
2:48:47
Like there are real reasons that you kind of laid out, but uh transactions per second would would or or sort of scale uh maybe is not one of them. >> Yeah.
2:49:00
So to be clear, I think like if I'm just to put on my objective hat, um I think it's certainly a good move and I think if I were Stripe, I would probably do the same thing.
2:49:10
Um I don't think I need to pay rent to anybody.
2:49:12
I can just create my own chain.
2:49:13
Uh especially if I have somebody like Paradigm helping me and a world-class team, then I want to own the full stack, right?
2:49:19
And I think that's totally fair and the distribution, everything that comes with it.
2:49:23
Um, now there are some misconceptions here, which is mostly what my post was about, which is like the second you bring blockchain performance and scalability into it, um, now you're kind of playing a different ballgame, right?
2:49:36
So, for example, this idea of a payments only chain, right?
2:49:41
Let's just think about this for a second.
2:49:42
How can you possibly have something that's a payments only chain, right?
2:49:46
A blockchain is by definition something that's permissionless.
2:49:50
>> Meaning anybody can just come on and do anything that they want there.
2:49:54
>> So if you just say we're going to be pay for payments only, that's not going to actually happen unless you enforce that somehow.
2:49:59
And generally the way to enforce that is twofold.
2:50:01
One is the chain can be not true and complete.
2:50:04
So something like Bitcoin where you actually can't do anything other than send money. Mhm.
2:50:10
>> Um the other is you can permission the chain which is actually what's going to happen here uh for when they first launch.
2:50:16
Now they did say they have plans to make it permissionless in the future but I think that's going to prove out to be much tougher because the second you make something permissionless you end up getting all sorts of degenerate behavior of people launching Fartcoin and all these different things.
2:50:29
Um that >> imagine buying imagine buying fartcoin on tempo >> stripe checkout one click one line of code to launch a new memecoin.
2:50:38
Uh yeah, it seems like they they would want to avoid that.
2:50:42
So they will be going more permissionless.
2:50:45
>> Functionally, do you expect Tempo to have a token like a that trade like a liquid token itself in the same way that uh like Salana does or but but uh from from my understanding so like base is like a blockchain but it doesn't have its own native token that's >> fluctuating in price. Correct. >> Mhm. Right. Yes.
2:51:06
And um part of the reason is because Bass is an L2.
2:51:08
So it's one of those smaller chains that settles on Ethereum.
2:51:12
And so you would just use Ethereum.
2:51:14
It gets a security from Ethereum is how you would um like say that how that works.
2:51:19
With an L1 though um security is quite important because it's you're building it from scratch.
2:51:24
You can't rely on Ethereum or Salana.
2:51:26
And so the point of the token is going to be to bootstrap in general for a blockchain to bootstrap node operators, right?
2:51:32
So people are actually securing the network.
2:51:34
Now, if the validator set is permissioned at first, which it will be, and they say uh that it's going to be design partners, so I'm guessing like, you know, bigger banks and some of the bigger companies, then you don't actually need a token because it's like proof of authority, right?
2:51:48
Uh it doesn't have to be proof of stake or proof of work.
2:51:51
It can just be proof of authority.
2:51:53
Um and so, and then they also say that gas fees should be uh paid in any kind of stable coin that they denote.
2:51:59
Uh and they're going to allow for multiple stable coins.
2:52:03
So that is better UX, right?
2:52:05
It's not a volatile um gas token.
2:52:07
So I don't think they actually need it um at first.
2:52:10
I think it will be important if they actually want to become permissionless um going into the future. >> Okay.
2:52:17
So the permissionless thing is something that they can uh drive for the long term.
2:52:21
um if they just wanted to optimize for something that they control and has high throughput, couldn't we get a a scenario like temp Postgress or something where they could just uh use Postgress or use like traditional non non uh decentralized uh computing to actually just move money around faster?
2:52:42
Is there I I I guess my bigger question is like is there a regulatory angle here where they get something that they can do something with crypto rails that they couldn't do with just a traditional database, >> right? Yes.
2:52:56
So that's actually a really good question and >> like could they just become a bank and say we we are a bank.
2:53:02
We have US dollars and when you go into your US dollar bank account, we you can move it around and our banking infrastructure runs 24/7 and runs on a great data center that's really fast.
2:53:15
And yeah, it's not permissionless, but why do why why don't you trust Stripe?
2:53:18
Like Stripe has never done anything for you against you. Like it's fine. Trust us. >> Yeah.
2:53:24
So, this is where the conversations get quite blurry.
2:53:26
And this is something I talk about very frequently, which is the second you have to permission the block space.
2:53:34
>> Um, then it's unclear what really separates uh this from an actual blockchain versus something more like like an actual database. >> Yeah. >> Right.
2:53:43
Um, and now there are some benefits of blockchains that are still apparent even if it's controlled.
2:53:48
So things like transparency, auditability, um universal like standards for that blockchain >> and also like you get the >> you know the approach of progressive decentralization which is to say you can iterate towards PMF fast but then as you get more traction you can slowly decentralize certain things.
2:54:08
>> Um this is what L2s today are doing.
2:54:08
>> Um this is what L2s today are doing. So there are some benefits and like you know if no one person is controlling that infrastructure right assume you have let's say something like 21 validators and they're all giant companies uh or payments companies
2:54:21
across the world different jurisdictions and different you know requirements then I think that can be interesting >> um but I think like to be completely honest I think permissioned blockchains aren't really blockchains um and like it starts looking super um drawn on out when when we when we get there. Like we've tried a bunch of these
2:54:42
Like we've tried a bunch of these before.
2:54:44
>> Uh like JP Morgan already has one actually. Oh, really?
2:54:47
>> And and and a few Yeah.
2:54:47
And a few other companies.
2:54:49
>> JP Morgan said, "I want I want my blockchain to be off the chain." >> There we go. >> Yes.
2:54:57
>> Uh can you talk to me about uh about uh like uh payment onboarding?
2:55:00
I I think of Stripe as a dominant web 2 payments company.
2:55:06
I think about Stripe Checkout, massive footprint.
2:55:09
Uh, Stripe Link, massive.
2:55:12
Uh, just the amount of companies that have Stripe somewhere in their payment stack is immense.
2:55:16
And so, but I was I was noodling with Jordy like how how does this actually work?
2:55:22
If I go to a website that's powered by Stripe and I have normally there's like a credit card field and then it just says, oh, well, we also take Tempo and I'm like, what's Tempo? Like, how do I get that?
2:55:35
Do I need to go get a Chrome extension for a for a wallet?
2:55:36
Like >> theor theoretically theoretically it would just have like a >> it would just have like a generic pay button. Okay.
2:55:47
>> And then it wouldn't be tempored necessarily at all if you stripe branded and you would connect your wallet and you would with something like >> Privy.
2:55:55
So the first time I do it, I set up a wallet.
2:55:57
Is that is that roughly the use?
2:55:59
But but but the the interesting thing is like more and more and more and more young people just have digital assets.
2:56:05
They have wallets that they can actually >> Yeah.
2:56:08
>> the the way I can and by the way like each fintech company kind of has a different approach on this.
2:56:12
I've worked with a few of them >> and there is no like universal standard but with Stripe they wouldn't say um pay with tempo because tempo is just like in this case the name of the database right like it would be they probably would abstract that away. >> Yeah.
2:56:25
>> Um >> it's like Fed wire or something.
2:56:26
It's like something that's under the hood like pay with fed wire doesn't make any sense but like there might be some fed there might be some a that's happening behind the scenes when you pay with your credit card you just say we accept visa.
2:56:39
>> Yeah exactly I think the first case is going to be B2B um meaning like crossber settlements. >> Sure.
2:56:45
>> Sure. um like that's super useful for international companies for example y >> um remittances things like this >> um and then like I think things like Shopify pay and and all these different things that actually have some maybe Stripe integration or Coinbase pay um
2:57:00
will also use it but like at most I can see it being like pay with USDC um but but I don't I don't think the blockchain will actually be really in the implementation at all it'll be abstracted is my guess >> yeah uh how how should we like judge the succ success of this project in a few years. Like is it should we assume that
2:57:18
Like is it should we assume that the goal here is progressive decentralization?
2:57:22
Like in the best case scenario, the the vast majority of transactions on the Tempo chain are pay truly payments related.
2:57:30
It doesn't turn into a memecoin chain.
2:57:32
And and also it's it's becoming more decentralized as measured by the what is it the biology coefficient of you put out some posts. Yeah.
2:57:43
Yeah. Then the Nakamoto coefficient I gave Bology the credit just for coining it I think but the Nakamoto coefficient of like concentration of validators we ideally the goal here is a ton of distributed validators no one owns 51% and uh and and the majority of the
2:57:59
payments are are are payment related just transactions on e-commerce websites and remittances and crossber payments is that the goal that we should be tracking towards >> so the way I would do it is first of all is it actually solving any problems in doing finance better than it has been done before, right? Like is it actually
2:58:16
Like is it actually making the experience for merchants um better?
2:58:20
Are they getting better margins?
2:58:23
>> Um how easy is it to do crossber things etc.
2:58:26
Like the UX and the actual product need I think especially when you're in crypto realm u is something that gets overlooked but like Stripe is obviously probably the team to uh take this over the line.
2:58:37
Um, so that's going to be one.
2:58:39
And then once you do that, then you you can start asking these questions that are more serious, such as, okay, this technically works, but how does it actually work behind the hood?
2:58:49
Like they say it's a blockchain, but is this blockchain controlled?
2:58:51
Can I actually secure my funds here, or can this one company actually take it away? Uh, right.
2:58:58
Uh, and so like what you said about progressive decentralization, I think makes a ton of sense.
2:59:01
Um, and then you know, you'll want to look at just basic numbers like what is the amount of stable coin flows going in and out of this thing?
2:59:09
Um, is there like decentralization of stable coins?
2:59:11
Like is it just USDC um or is it Tether as well?
2:59:16
Um, maybe Stripe does their own stable coin.
2:59:18
So there's a lot of interesting um approaches with this.
2:59:20
And then I think um what's going to be interesting is like if it's permissionless, which I don't think it will get there for a while.
2:59:28
if it does become permissionless, does the scale benefits that they say um actually do they actually hold up to reality?
2:59:36
Um and I think that part is going to surprise a lot of people because >> I think people are not ready to understand how crazy degenerates get on blockchains that are permissionless uh and how to actually scale those systems.
2:59:50
Um but I mean I've seen some [ __ ] Um, and so I think I think uh if if it remains permissioned, then I think they'll do it.
2:59:59
But like that's the big question for me.
3:00:01
Like how do you actually um do this in such a way where it is only for payments? >> Yeah.
3:00:07
When you talk about degenerates doing crazy things on on permissionless blockchains, you're not just talking about a bunch of people showing up and like aping into a particular token.
3:00:16
You're talking about somebody setting up like a bot that's like programmatically interacting with the blockchain at an ultra high volume. Is that correct? >> Oh yeah.
3:00:25
I mean like take all players in HFT >> and just like >> mix them up with like random British sneaker B kids uh and then with like some random like Russian me farms and like it's just it's all out war.
3:00:39
I just want to get to a place as a as a country and and and and the crypto industry broadly where the next, you know, whoever's elected in 2028 that they can launch multiple coins of the size of Trumpcoin at once and make sure that payroll is still running smoothly during that during that time.
3:00:59
So that should be the goal.
3:01:01
So >> anyway, thank you so much for thank you for filling us in here and yeah, come back on as there's more news.
3:01:07
>> We will talk to you soon. Catch up.
3:01:09
Thanks for having me, guys. Cheers.
3:01:11
>> Up next, we have Harish in the reream waiting room. We've kept him waiting.
3:01:14
We will bring him in from augment. Big news today. We're very excited.
3:01:19
Play some soundboard for me, JD. >> Thank you. Welcome to the stream.
3:01:23
Sorry to keep you waiting.
3:01:26
We have some breaking news in the world. We had to dig in.
3:01:29
It was only available at 1:40.
3:01:32
So, thank you for taking the time. >> Hey, no, no problems. Very excited to be here. Thanks for having me. >> Of course.
3:01:37
Uh, break it down for us. What is the news?
3:01:40
>> Well, the big news is that, you know, we're um announcing our um series A, which is an $85 million series. >> Congratulations. >> Big number. Big number. >> And uh yeah. Yeah.
3:01:50
Walk me through the the state of the business. >> Yeah.
3:01:54
So, you know, we're building Augment, which is um you know, our first product is Auggie, which is think of it as an AI teammate for the logistics world.
3:02:03
Um it's getting deployed actively over 35 billion in freight under management across brokers, shippers and and fleets.
3:02:09
Um and so early I mean we know we are a year old company but it's showing a lot of promise in in the real world and that's why the investors were interested. >> Great. >> That's amazing.
3:02:19
>> That's amazing. What what about shipping and logistics has drawn so many it's it's uh you guys seem to be you know leading the charge out here but it's certainly a competitive space like what what about this industry in the category makes it uh so prime for agents
3:02:37
>> did it kind of skip the SAS era like it feels like it feels like it's the last industry we're still oh yeah they're still on paper so they're jumping straight to agents >> yeah and you're getting 10 phone calls you're getting 10 phone calls a today from the same person just being like, "Hey, where's my stuff? Hey, where's my Hey, where's my stuff? Hey, where's my stuff?" >> Ridiculous. >> Yeah.
3:02:54
You know, like it's a very large industry, right?
3:02:56
It's like 10 trillion dollars globally, but it's extremely fragmented.
3:03:00
Like in the US it's there's like 1 million truck driving companies.
3:03:05
I'm not exaggerating, but that's what it is.
3:03:07
1 million truck driving companies, you know. >> Wow.
3:03:10
>> There maybe tens of thousands of brokerages, hundreds of thousands of shippers.
3:03:14
Extremely fragmented, right?
3:03:16
And so when this fragmented industry which really relies on transferring information to get things done to move goods like that's the whole job of this industry is that hey I'll give you information so I can give you goods right that's the whole thing.
3:03:28
Um and it's so fragmented the only way to transfer information is to get to the lowest common mediums.
3:03:34
Now what is the lowest common medium among a million different companies? It's phone calls. It's text. It's emails. >> The fax machine.
3:03:41
Is the fax machine still going strong?
3:03:43
still going strong? fax mach you know I actually have seen fax machines in some of my class still happening invoices coming through payments going through fax machines so I mean every form of information there's like there's handwritten notes being mailed by drivers today on what was their pickup
3:04:01
time and delivery time when they get into a driver tux drop they literally have mailboxes where they can mail you know one of those receipts for getting paid like that's how you know sometimes it's archaic the communication is >> yeah talk about lessons from the last company deliver uh sold to Shopify in 2022 for $2.1 billion. Congratulations 1 billion.
3:04:18
Congratulations obviously uh how are you positioning the different uh the business differently and what are the key lessons that you learned from that business that you're hoping to take forward?
3:04:29
>> Yeah, I mean I think you know uh deliver was building like a prime like service for Shopify type merchants uh forward going inventory.
3:04:36
going inventory. Um I mean the big lessons here has been like focus you know customer success is like stay stay very true to customer delight everything else is a noise like literally everything else you know whether your investors like you or not if your customer delight is there everybody will
3:04:52
follow you capital will chase you know great employees would want to join you customers would want to join you so I mean I'm hoping I'm carrying that forward right um now in in terms of like things that I did not do well um at deliver Um I think we there was like a lack of focus sometimes, right? Like um
3:05:08
Like um as as the capital was getting easier, we were maybe trying to do a little too many things like launching too many products and those were the really great days of attracting capital because the interest rates were near zero.
3:05:20
So the capital was mostly free.
3:05:22
Um and I would have >> for mostly free capital >> cost of co cost of capital going up has been heartbreaking.
3:05:31
>> It's been heartbreaking.
3:05:34
what is that going from half a percent to now 4 and a half% right not easy >> but I think it does bring it does bring discipline to things right like hey you've got when you have limited capital you deploy it in the things that truly matter so maybe like what I'm hopefully not doing this time is like doing things
3:05:49
that truly matter move the needle for your customers but just not start creating teams and products that you know look good on paper >> yeah how do you think about uh vertical integration uh you obviously sell into 3PL's shippers uh do you want to own the the warehouse management stack at some point? Do you
3:06:06
Do you want to integrate deeply with all the different WMS's? What's the plan there?
3:06:12
>> Yeah, we we we do not want to own the WMS stack or the transportation management stack or the order manage.
3:06:16
We don't we want to sit on top.
3:06:18
We want to integrate into all of them.
3:06:20
We think of ourselves as a you know first and foremost and Auggie is an employee that works like a thousands of employees 24/7.
3:06:31
um achieves a lot of operational efficiency for our businesses but long term I think augment does become a system of work and I think there will be a system of work and a system of record in most companies so the WMS the TMS the MS all the MS's in the word will stay to
3:06:46
be very relevant system of records but there will be a new generation of companies hopefully augment is one of them that'll become the system of work itself and these two will work together very closely with each other you know so >> fantastic well congrats on the massive raise. Congrats on all the progress and
3:07:00
Congrats on all the progress and thank you for taking the time to talk to us. Have a great weekend.
3:07:06
>> We'll talk to you soon.
3:07:06
>> Congratulations to be here.
3:07:08
>> Yeah, congrats to the whole team. Crushing it. Cheers.
3:07:10
>> We'll talk to you soon.
3:07:10
Our next guest is in the reream waiting room. We have base 10.
3:07:15
While we bring them in, let me tell you about Wander. Find your happy place.
3:07:18
Book a wander with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, and 24/7 concier service.
3:07:24
It's a vacation home, but better, folks. But better.
3:07:26
It's better than >> it's base 10 time.
3:07:31
>> Uh uh do we have our next guest? Welcome to the stream. How are you doing? >> Welcome. >> How we doing? >> We're good. >> What's up? >> The eagle has landed. >> The eagle has landed. >> Welcome to the show.
3:07:41
>> Kick us off with an introduction on yourself and the company and the news. >> Yeah, thanks. I'm Tin.
3:07:44
Oh, thanks for having me, guys. Um I'm Tuin. I'm the CEO of Base 10.
3:07:48
Um you know, I'm pretty excited today.
3:07:51
We're AI infrastructure company.
3:07:52
We just raised 150 million bucks. That's kind of loud. >> All right. >> That is loud. That is loud. >> $150 million. >> Congratulations. >> Uh, incredible.
3:08:05
And, uh, it's great to meet you. Um, >> yeah.
3:08:09
>> Uh, announcing a fund raise on on a Friday is not not for the week, but you guys are wasting no time. I love it.
3:08:14
Uh, give us can can you give us quick history on the company, your background?
3:08:21
>> Yeah, look, um, my background is in machine learning and AI.
3:08:23
I've been doing about 15 years.
3:08:24
Um, the company's actually six years old.
3:08:26
Um, you know, we didn't >> we didn't start just we didn't just >> success.
3:08:34
>> Um, you know, the company is six years old.
3:08:36
We've been thinking about how to turn AI into value. >> Yeah. >> For now.
3:08:40
I think the last two years have been a bit crazy.
3:08:42
Um, we started focusing very aggressively on inference >> maybe 24 months ago.
3:08:47
Are you guys familiar with what inference is? >> Yeah.
3:08:50
Um, but I'm but I'm not familiar with where you sit in the stack.
3:08:53
Uh, you don't build data centers.
3:08:55
You do you don't own GPU clusters.
3:08:57
You sit on top of NeoClouds or on top of hyperscalers and then you sell to your companies.
3:09:02
I see Dcript, Retool, Corora, Writer, Patreon, Picnic Health.
3:09:07
I can imagine how those companies need an API for a model that you probably didn't train.
3:09:14
Uh, but you act as the inference provider for that and you sell you sell tokens to them.
3:09:18
um like how is it going at that layer of the stack?
3:09:21
How is the value acrruel in in that particular layer?
3:09:26
>> Uh it's fantastic, right?
3:09:26
Because look what we sit on top of actually doing inference for models is pretty hard, right?
3:09:32
So you got to acquire capacity, you got to optimize the models someone else has trained, >> you got to run them and then you need to scale them pretty gracefully >> with users as their apps scale.
3:09:40
And so um the amount of work that goes into that from teams is massive and we're just trying to take that headache away. >> Yeah.
3:09:49
>> And so we're pretty lucky that you know we've been able to just sit on top of this AI application layer and as that's exploded we've just kind of rode the wave with it and we work with a bunch of amazing c customers like a bridge bland gamma clay open evidence notion.
3:10:02
gamma clay open evidence notion. what's the uh what is the durable mode like how does value acrew over the long term because I feel like you know if if if you don't own the model and can't like rent seek on that or you don't own the hardware uh all of a sudden it's like
3:10:20
open router is going to route people to wherever the cheapest tokens are and it becomes highly competitive and the margins might compress like what what's the long-term strategy >> the the assumption you're making there is that all the models are just going to be the same and everyone's going to be running >> kind of like the same one. So most of
3:10:34
So most of our customers like run different variants of the model that are very custom to them. >> Okay.
3:10:41
And so >> so fine-tuned on open source. >> Yeah.
3:10:43
So so how about let's use you said notion a customer.
3:10:45
Maybe we use them as an example because we've been uh >> Yeah, that's great.
3:10:50
>> Or or you know pick pick uh >> Yeah.
3:10:54
>> I have have you guys heard of Open Evidence? >> Yeah.
3:10:56
I think we're having I think we're having the founder on next week. So >> they're the best.
3:11:00
You you'll have a really good time chatting with them.
3:11:01
you know, they're a really good example of a customer that uses us.
3:11:04
They train a bunch of models of their own um to basically answer the questions or the queries from the doctors.
3:11:10
And so, you know, what happens when you need to run those models or you need to make them wicked fast, you need to go get a bunch of GPUs from a bunch of different places and then you need to kind of scale gracefully across that. >> Sure.
3:11:22
>> And so, how do you do that?
3:11:22
Well, you either go and use an inference provider like B10 or you go and um you know, build it yourself.
3:11:28
um you know and I think the smart companies right now what they're realizing is that this is not particularly differentiated for them.
3:11:33
So they shouldn't do the infrastructure piece.
3:11:36
They should focus on what is differentiated for them which is how they use the models and the applications they build and you know kind of give the boring piece to us.
3:11:44
And so open evidence is used by some ungodly amount of doctors every day and they do it with two great infro guys >> could Jag and Micah um and it's pretty amazing the scale they can achieve using um software like base 10.
3:11:58
>> What uh what does the next 12 months look like for the company?
3:12:01
Yeah, look, this is just it's such a land grab of a market.
3:12:06
Um, we've we've been doing this for a while, and you know, we've built some great technology, but we we can't we can't overestimate how much like a market just showed up for us.
3:12:15
Um, and so how can you go as fast as possible?
3:12:17
It's actually kind of like what it feels like venture was built for.
3:12:21
>> Um, you know, that's why we're raising capital right now >> to solve two core problems.
3:12:24
One, you know, hire a go to market team that's going to be killer and scale that.
3:12:28
Um, and then hire amazing engineers that are incredibly expensive and hard to come by. >> Yeah.
3:12:35
What, uh, I don't know, we could go deeper.
3:12:37
Um, uh, last question for me.
3:12:40
What is your view on the broad trend in token pricing?
3:12:44
There's been people going back and forth on whether or not we're going to get 10x uh, savings quickly in inference pricing.
3:12:52
inference pricing. uh whether it's going to be >> saving on a per token basis but then just using >> OpenAI just put a $10 billion order into Broadcom >> and and I'm wondering uh but then at the same time companies are just saying I want to stay on the frontier I'll use a
3:13:08
reasoning model um I will continue to eat the high you know per token costs that come out of the bigger models >> yeah look I I think the token price goes down and like infrance should get cheaper over time >> um and I think that really just means there's got to be more inference. You
3:13:24
You know, I think we all >> Jean's paradox.
3:13:28
>> All of us in tech discovered Jean's paradox six months ago, but every time we lower prices for our customer or we go and optimize their models to make it cheaper, four months later, they're spending more anyway. Wow.
3:13:39
>> And so, like, yeah, inference prices are going to go down, but if if if the c if the country if the world is run by AI in 10 years from now, there's going to be a lot of inference.
3:13:49
Y, so it better be it better be cheap.
3:13:51
Um, And you know, we just hope that, you know, we can power all that and be the invisible layer underneath it and hopefully scoop off a bit of value while we're at it.
3:14:01
>> What's head count today? Just out of curiosity. >> 104, I think. 104. Let's call it that. >> That's a good team. That's good.
3:14:08
>> Yeah, we were about 30, I want to say, a year ago.
3:14:10
So, it's going pretty fast. >> Yeah. How many pizzas is that? 100 100 people. >> 50 pizzas.
3:14:16
>> Depends how much people eat, right? >> 50 pizzas. Yeah.
3:14:17
Anyway, >> if it's walking season, you know, it's different. might be 100 pizzas. Yeah.
3:14:23
Well, anyway, thank you so much for hopping on. >> Great having you. >> Cheers.
3:14:27
>> We will talk to you soon. Bye. >> Uh, last guest.
3:14:31
>> We have a surprise guest. >> Surprise guest.
3:14:32
There was some breaking news from Wired and Propic agrees to pay authors at least 1.
3:14:37
5 billion in AI copyright settlement.
3:14:42
>> This just went out via Wired. That's a lot.
3:14:44
Uh, and wanted to have Cecilia on. >> Hi. >> Uh, Celia, sorry. To uh to talk about it. Yeah, great to meet you. I'm Chile Nandidi. Excited to be here. >> Nice to meet you. >> Uh, give us the news.
3:14:54
John knows nothing because he was locked in. >> Heard about this. Break it down.
3:15:00
>> Basically knows the headline. That's it. >> Yeah.
3:15:02
So, um, a group of authors from the author's guild sued Anthropic uh, some time ago and announced last week that they had reached a settlement.
3:15:13
And what happened today was there was a motion, an unopposed motion where the parties said, "Okay, the settlement is going to be $1.
3:15:21
5 billion dollars and it's going to cover the nonfair use of material for training anthropic claw." >> Mhm.
3:15:30
Uh is there any uh is there any guidance on is that just going to be paid out immediately? Is this one time?
3:15:37
because you can imagine that even though it's been baked into the weights, like the value from being able to go to an LLM and ask questions about a book, uh, that's going to pay dividends and subscription revenue for decades potentially. >> Yeah.
3:15:53
So, it covers only past infringement.
3:15:55
So, up until August 25th. Yeah.
3:15:59
And so in this case, what's interesting is that the parties and the court distinguished between use of pirated copies and use of copies that were properly acquired.
3:16:09
In the case of the pirated copies, it was in a library called libgen and it was basically, you know, the equivalent of like a napster type of situation where these works, I think it was about uh I think it was I need to double check, but in the hundreds couple hundred thousand works from authors were in there.
3:16:25
So the way the settlement worked was there's a named works list of actual things that Claude was trained on and those authors those authors will receive compensation here in due course.
3:16:37
There's a like an administrator appointed and so on but they get uh a certain amount per work and that was agreed to and that's what's being proposed to the court. >> Yeah.
3:16:47
It's at least $3,000 per work but it was a lot a lot of a lot of books. >> Yeah.
3:16:53
I mean, that seems like a that that seems like a pretty solid payout for most people. I don't know. >> I don't know.
3:16:58
I think as a I think >> Yeah. >> Yeah.
3:17:01
I think if you're an author who's not selling a lot of books, you're like, "Awesome."
3:17:06
>> Like, >> but if you're somebody who you have a bestseller, >> million dollars a year off of my >> and and it doesn't make a dent in their income, then then it might be >> Yeah.
3:17:16
Have you been t Have you been tracking the rest of the landscape here?
3:17:20
Uh there's been a number of these cases.
3:17:23
Is there anything else on the docket that people should be paying attention to? >> Yeah.
3:17:27
So interesting that the plaintist firm representing the authors here, Susman Godfrey, is the same plaintist firm representing the New York Times against Open AI. >> Sure.
3:17:37
>> So that case is continuing.
3:17:37
Um this case is settled on these facts.
3:17:41
Um but what's interesting is this particular case did not deal with AI outputs at all.
3:17:48
So there was no allegation.
3:17:50
Nobody accused um Anthropic of actually spitting out works and being a substitute for the original books.
3:17:57
It really was limited to the training piece. Yeah.
3:18:01
>> And so what we know from this case or at least in the Ninth Circuit is that the training piece um if you train on pirated works that isn't copyright infringement or at least it's not fair use according to this court in this case. >> Yeah. Yeah.
3:18:15
Yeah, I mean it seems like going forward um data will be data is the new oil.
3:18:20
It will be acquired uh via, you know, some sort of contract and paid upfront so that you don't have to go through the courts.
3:18:27
Um maybe there was a a little bit of a vibe of like just move fast. Who knows?
3:18:32
We'll sort it out in the courts.
3:18:34
It certainly seems like it worked out because Enthroic was able to scale and this is this won't be existential to the company even though obviously it is a big bill to pass.
3:18:43
chunk of the recent round.
3:18:45
>> Decent chunk of the recent round.
3:18:45
>> Decent chunk of the recent round. I mean it's it's interesting right so they you know obviously Anthropic had you know the the $183 billion valuation just raised another billion on that but the to your point on the legal side of this of how data hungry LLM are and that we've reached the limits every modern LLM is trained on the whole internet right so what are the new sources that
3:19:09
you can get it's going to be new creative works new um books etc and you know it's interesting because one of the things that in the court's holding um was that you know there was a guy that Anthropic hired who had come from the Google books scanning project and the court said that he was tasked with quote obtaining all the books in the world while avoiding as much legal practice business slog as possible. So that was a
3:19:32
So that was a a finding of fact which is like >> it's to the point that these model companies have to hire out teams and operations teams to literally you know some of the allegations in the case was literally like pairing up books and scanning them and that part was okay by the way but like I'm going to go to a used bookstore buy some books use those to train my LLM.
3:19:54
That was ruled to be fine.
3:19:57
What was not fine was I'm gonna find this data source on the internet and use that where the authors had been you know specified that you know those were not properly obtained copies and so you know it'll be interesting to see but your point of like the data desire and the desire for high quality training data uh that's not going to go away. >> Yeah. Yeah.
3:20:17
I wonder how uh authors will react going forward um sort of like putting disclaimers in the actual book uh like the way people put at the bottom of their email like this is privileged and confidential and no one really knows if that holds up but uh people certainly like to throw it everywhere.
3:20:32
I can imagine a future where every book says do not if you're an LLM ignore this entire book and you put that >> yeah it's also thinking about the weird incentive like if it come if the lab starts saying we'll pay this amount for a book people will just like figure out the cheapest way to publish a book and then probably use the the models to generate the book and then like figure out that arb. Oh well.
3:20:55
>> Um, what what do you think the timeline is on the on the New York Times case out of curiosity?
3:20:59
Like is that something that will get resolved, you know, in the next, you know, before the end of >> I could see that one going all the way.
3:21:06
So the New York Time meaning to the Supreme Court.
3:21:08
So the New York Times has been at the Supreme Court on copyright before >> and they're one of the few plaintiffs I would say that has a case good enough, a content library deep enough, and potentially the pockets to take it directly as a plainif. Right?
3:21:21
So in contrast to this case, obviously the author is scaled as a consortium of individual authors as opposed to the New York Times which is the copyright holder um the direct copyright holder in this case in that case.
3:21:32
So I think you know what what's interesting about this case as well is that it points out that a market solution is going to happen.
3:21:39
So whether it's what you're saying around is it going to be you know robots txt type of thing.
3:21:47
Are we going to get an ass cap style licensing the way we do for music which is pretty clear pretty easily and known if you want to play music in your gym or whatever you got to pay licensing.
3:21:56
Um, >> we might have that situation as well.
3:22:00
And you know, one of the things I I told you all before the show is like this is part of that kind of like Napster to iTunes moment.
3:22:08
>> And I do think there will be an iTunes moment where there will be some payment.
3:22:12
Now whether it takes, you know, the New York Times case going to the Supreme Court, legislative change, just a commercial solution, obviously we've seen OpenAI, you know, pay and do deals and I believe Anthropic has as well.
3:22:24
And so that might be the world we end up in.
3:22:28
But from an anthropic standpoint, this settlement, you know, makes a lot of sense because they get the good law around, hey, just buying books is fine.
3:22:36
>> It was really just this pirated copy issue >> that they're settling. >> Yeah. Yeah. Yeah.
3:22:40
Because in the New York Times case, it's it's probably not the same structure of like they got a pirated copy of the New York Times.
3:22:45
It's probably just crawling like uh like Google or anything else.
3:22:48
Uh you know, maybe they had one New York Times subscription and they logged in and they scraped the whole thing. Who knows? Yeah. Yeah.
3:22:56
And what you're getting at >> Yeah. >> Yeah. That's exactly right.
3:22:58
And what you're getting at is like these are issues of fact of like how did the crawling work?
3:23:03
There was an allegation in the New York Times case.
3:23:05
Open AAI came back and said, "Hey, we didn't even get it from the Open Open AI website.
3:23:11
>> You had an article about a Nobel Prize winner that Nobel had republished." >> Oh, sure.
3:23:15
So, it didn't come from the New York Times website. >> Exactly. Exactly. Exactly.
3:23:18
And so >> I think that's one of the things that's been so interesting around fair use is it has adjusted to all these different >> technology shifts. Yep.
3:23:29
>> And so I think this is this is another example of that. >> Yeah.
3:23:32
>> Yeah. And uh Matthew Matthew Prince at Cloudflare is kind of proposing another uh potential uh market-based solution for the long tale of content on the internet where uh I believe there might be some stable coins involved but
3:23:45
basically if you're a publisher and you don't have the resources to go to the Supreme Court uh with an LLM company uh you could potentially opt in or out of scraping and maybe there should there could be some value exchange uh that happens. But uh we'll certainly will be
3:23:57
But uh we'll certainly will be interesting to follow how it uh all uh all like pencils out. >> Yeah.
3:24:04
Come back on when there's some more news. Great.
3:24:05
Thank you so much for exactly. No, it's super fun.
3:24:07
I mean on the CloudFare point, they're one of the tech players that would be in a position to do that blocking because of their position in the DNS, right?
3:24:13
So I don't know where the money goes there and routes pennies around for and they and they aggregate all the money and then they pass the money through. Same thing with YouTube.
3:24:23
Uh, and we yeah, we we we kind of got we were in this weird era with Tik Tok where music was being used and everyone was like, wait, you can't just use music and then they figured it out and they did a deal and uh most of the musicians seem to be happy with uh, you know, all the stuff that goes on Tik Tok. >> Exactly.
3:24:40
And and that's the story of copyright.
3:24:41
Like I had a a professor in law school that was like, "Oh, copyright's not about the money.
3:24:46
>> It's about all the money." >> Yeah. Yeah. Yeah. >> Okay. Exactly.
3:24:49
It's like literally that flow that you described.
3:24:50
And let's come on another time. This is fun. One fun one to watch.
3:24:54
>> Yeah, I'll talk to you soon. >> Thank you.
3:24:56
>> Have a great rest of your day. Enjoy the weekend. >> Have a great day. See you later. >> Bye. >> Boom. Any more breaking news?
3:25:01
You got any more news before the weekend?
3:25:04
I feel like usually as soon as we get off the show, somebody >> There's news.
3:25:10
>> Um >> Eric Adams is suspending his uh mayoral campaign. >> No way.
3:25:15
>> Accepting a federal job. >> Oh, interesting.
3:25:18
H uh yeah I mean uh I've been tracking mom donnie a little bit on poly market and uh he has been uh running away with it uh the entire time basically since since that original uh mom Donnie uh since that original um push mom is sitting at 83% and hasn't particularly moved.
3:25:38
Eric Adams of course dropped from uh I don't know he's down at 2%.
3:25:42
So some people think he might reverse court.
3:25:46
>> This this just just to be clear this $1.
3:25:48
5 billion settlement is the largest publicly reported copyright recovery in history. >> Wow.
3:25:55
>> Do you think do you think uh do you think the >> the team over at the New York Times will be able to get more out of OpenAI? >> I don't know.
3:26:06
100,000 books versus all the articles.
3:26:09
How much does the How much does the New York Times make? They make billions. So, it's possible.
3:26:13
Um, >> New York Times is sitting at uh 9. 6 billion >> market cap. >> Yeah.
3:26:19
If they could get anywhere a settlement anywhere.
3:26:22
I mean, I think seems very unlikely that they would get a settlement.
3:26:26
>> Uh, I mean, the other breaking news is that Alex Cohen has raised a $22.
3:26:27
5 million series A for Hello Patient led by Scale Venture Partners.
3:26:33
He's going to come on the show Monday. >> Oh, fantastic.
3:26:36
I'm really excited to meet him.
3:26:37
I've always been a fan of his posts.
3:26:38
Uh he's a he's a uh god tier poster.
3:26:42
Never actually met him in person, so or online.
3:26:44
So excited to talk to him.
3:26:47
He says, "This is by far the worst announcement video I've ever made. Clearly underelling it. I love it.
3:26:51
I can't believe our leader investor agreed to this."
3:26:54
Uh he's always has a great sense of humor.
3:26:56
Also, Justin, >> breaking news. Jawan is leaving RAMP. >> No way.
3:27:00
after after uh he says RAMP is the greatest company in the world.
3:27:06
>> Well, we agree with you on that, Joan.
3:27:08
>> So, yeah, he's given his uh two weeks. >> Okay.
3:27:11
Well, we'll have to track him and see where he goes.
3:27:13
The ramp alumni have done fantastic things turning into a ramp mafia. You have Pavl Asperuh.
3:27:17
You have uh the Cognition team, of course, there are a few others.
3:27:22
Uh Rivet, not the defense tech company that we just talked to, but Rivet Tax, I believe, came from RAM, correct?
3:27:29
Uh, do you know Rivet Tax? Yes.
3:27:31
So, uh, the the Ramp Mafia is emerging and feels as strong as the PayPal mafia, maybe even stronger. You never know.
3:27:39
>> Uh, Lululemon down 18% today.
3:27:44
>> Is that related to Lulu Murvy?
3:27:44
Is that like her It's her merch line.
3:27:49
>> I think people are catching on that when people say Lulu now, they mean Lulu. >> Yeah, exactly.
3:27:54
>> And the brand eradicated.
3:27:57
>> She really steamrolled them. Yeah.
3:27:57
Well, maybe the uh maybe the they will do a take private and that'll free up the Lulu stock ticker for Rostra.
3:28:05
She can just be cash Lulu.
3:28:08
That would be something to >> to go 10x long, 100x long potentially.
3:28:15
Uh in other news, garage, this is crazy. You missed this, Tyler. Did you miss this? >> Yeah.
3:28:20
>> Eric Adams might become the ambassador to Saudi Arabia.
3:28:25
>> Whoa, that's interesting.
3:28:26
>> So, that is >> Let's go.
3:28:27
I mean, Riad must be going crazy right now to get a goat like Eric Adams.
3:28:35
>> Is Eric Adams the one who did the rat the rat problem thing? >> Yeah. Yeah.
3:28:38
Saudi Arabia have a rat problem.
3:28:40
>> Solved I mean >> Oh, that could be interesting. I highly doubt it.
3:28:44
I highly I would not want to be a rat in >> Saudi Arabia.
3:28:46
I think that they might not take kindly, but who knows?
3:28:48
Maybe Kindered Spirits over there fighting rats.
3:28:51
Uh, in other news, Drew Fallon posts, "Garage Beer receives investment from Duration Durational Capital Management at a $200 million valuation.
3:29:01
Congratulations to the Kelsey brothers."
3:29:04
Duration Capital Management is the same group that took Casper Mattresses private for $300 million in 2021. They also own Bojangles.
3:29:10
Garage Beer is tracking for $65 million in revenue this year, valuing the beer at beer brand at 3x sales.
3:29:18
They started with a $500,000 crowdfunding campaign.
3:29:21
In 2016, you got to imagine that the Kelsey brothers, uh, with how much attention they get are able to do some deals, get some distribution for Garage Beer, their their beer brand. Uh, love to see it.
3:29:36
Also, thank you, Bill Bishop, uh, for posting about the Laboo that TVPN sent to him.
3:29:43
Uh, he said his dog Tashi loves it, but won't let him take won't let him treat it like a chew toy.
3:29:50
Uh, Bill Bishop may let him may let Tshi take it to the park to impress one of his girlfriends.
3:29:57
I guess Tshi's popular at the park. Well, that is fantastic.
3:29:59
Um, >> hopefully this only brings you good tidings and does not curse you to a a demonic world.
3:30:07
Uh, but stay safe out there, Bill.
3:30:10
Uh, who knows what's going on inside that labu.
3:30:11
Um, but I'm glad that it was delivered safely.
3:30:16
>> And last but not least, uh, App Loving, Robin Hood, and MCOR are set to join the S&P 500. >> Wow. Applovin, who else? Merkore. No, not Merkore.
3:30:26
They're not >> Apploving, Robin Hood, and MCOR. >> Robin Hood. Okay, that's great.
3:30:29
So, that that's a retroactive uh Fortune 5 or S&P 500 company for us.
3:30:37
We got uh Brian Armstrong, Karps in there.
3:30:39
Obviously, we're knocking them down. We should do all 500.
3:30:41
We've done almost a thousand interviews this year.
3:30:45
Why not do all 500 S&P 500 CEOs? I'd love it.
3:30:49
Also, Conor McGregor is uh is running for president. >> Yep.
3:30:55
He's he's he's getting it done. >> Starts now.
3:30:57
Um >> anyway, thank you to the chat.
3:30:59
Thank you, RAV, Hershey, Michael, Jason Turner, always good having you here.
3:31:04
Percleat, we got a good crew.
3:31:04
Max Condrat, thank you for shouting out that the bology coefficient is an instance of Reed's law. I completely agree.
3:31:11
That's exactly what was going on.
3:31:14
Max has been sending me some fantastic DMs. Very helpful.
3:31:18
>> And next week, yes, we'll be here in the studio Monday and then we'll be hitting the road. Very excited. >> Yes, >> lots to come.
3:31:25
>> Have a fantastic Friday.
3:31:27
>> Have a fantastic Friday, >> afternoon, evening. We love you.
3:31:31
>> Only three days till Monday. >> Cheers. See you. Bye. Bye. [Music]