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5:02
>> Today is Tuesday, August 5th, 2025.
5:02
We are live from the TBNN Ultra Drum, the Temple of Technology, the fortress of finance, the capital of capital.
5:07
Uh, >> I just lost my voice.
5:10
of actually seeing stars. >> You're seeing stars.
5:12
People said people said the intro could be louder.
5:15
Yeah, >> they were like, "That's the main feedback." >> I took it there. I took it there. >> I took it there. Good job.
5:19
Uh anyway, let's kick it off with this post from Fukco Capital Bloke.
5:22
Uh apparently Variety has reported that Roku launches Howdy, a lowcost no ads streamer, but it doesn't want to compete with Netflix.
5:34
>> Calling it a streamer is funny.
5:37
>> Streamer streaming platform.
5:37
Is it just short for sleep streaming? >> Oh, yeah.
5:40
I work at a stream a small streamer American streamer called Netflix.
5:44
>> Is that a is that is does Netflix count as a streamer? A streaming service.
5:48
>> Oh, I guess it's a streaming service because it streams the content to you. Yeah.
5:51
Um well, anyway, Buo Capital Bloke uh shares a hilarious post from the Banger Archives. Or Boxer.
5:57
>> Or Boxer says, "Have you seen the new show? It's on Tub. It's on Tubu. It's literally on Hei. It's on PY with ads. It's literally on Dippy.
6:06
You can probably find it on Wii now, dude. It's on Gumpy. It's a Fibo original. >> It's on Poob. You can watch it on Poo.
6:15
You can go to Poo and watch it.
6:15
You can log on to Poob right now. Go to Poob. Dive into it. You can Poo it. It's on Poo. Poo has it for you. Poo has it for you.
6:26
>> Where do they get these names?
6:26
Where do they get these names?
6:29
It it it's like it's like the pharmaceutical industry how they have like every drug kind of sounds like vaguely like a familiar world with goofy and ompic like they sound like real words but like the domains are available is one of the most wild things.
6:42
Anyway, uh anyway, >> yeah, we should go check out howdy and you should check out ramp ramp. com. Time is money. Save both.
6:48
Easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place.
6:53
And we have our first story.
6:56
So, we talked about this a little bit yesterday.
6:57
take him, author of the Nvidia way, uh, and, uh, huge fan of Jensen Wong and Nvidia, uh, says, "Here's what I would do if I were CEO of Apple.
7:06
Quadruple the RAM in iPhones to 32 gigs.
7:08
Have the max model at 64 gigs.
7:11
Memory is oxygen for local ondevice AI.
7:13
More equals smarter, more powerful. Take the margin hit.
7:15
Memory isn't even that expensive."
7:16
Then this is where we get controversial.
7:18
This is what we were debating yesterday.
7:20
Number two is buy mistrol or anthropic and invest a hundred billion dollars compute annually annually.
7:28
That is I didn't realize.
7:28
So buying mist or anthropic that's a hundred billion dollars out the door day one then you're spending hundred billion dollar a year to build a multi-gawatt data center.
7:41
Uh I wonder great writer and uh the more you spend time with this post the more you can imagine a world where he takes Apple >> you know out of the mag 7. >> Yeah.
7:52
Um he says build mult data centers and enter the frontier AI model race in a big way.
7:58
This would be fantastic for Nvidia.
8:00
I mean take him seems like he's he's he's really full full tilt on Nvidia to 10 trillion right now.
8:05
Um anyway Apple has the capital.
8:08
Apple knows the AI computing shift is existential.
8:11
Where's the bold action and urgency?
8:13
So, there's a lot to agree with here. We debated it.
8:14
The one thing we didn't debate is that reream is the best uh streaming platform.
8:18
One live stream 30 destinations, multiream to reach for your audience wherever they are. Go to reream to sign up.
8:22
Anyway, what are we saying?
8:24
>> What is uh >> AI seem is seemingly important, but what is the existential threat that we get?
8:31
Um >> just play this out.
8:32
>> just play this out. new computing new computing platform >> uh eyewear that's integrated with AI uh we haven't seen anybody launch a hardware device or even plan to launch a hardware device yet that's not an an additional device >> outside of your
8:49
>> we are both on MacBook Pros or MacBook Air >> using iPhones we we have iPhones they were they were additive >> and then other people went further and they added an iPad to their life or they added a watch to their life >> not even a shiftman the most bold hardware founder I'm going to replace your iPhone. >> I mean, I do think that there is some
9:08
>> I mean, I do think that there is some potent if there was ever a crack in the foundation of Apple's monopoly on high-end smartphones, it's now because like you're not going to get me to switch with slightly different design or slightly different shape or it's folding like th those phones have come to market.
9:30
No one has meaningfully shifted but a but a phone that was designed from the ground up around AI and really really optimized for chatbt and really really like AI first at the core just everything is infused. Sure.
9:43
Like maybe there's a chance there versus anything else that came out like Apple was always like like 5G was never a differentiator.
9:52
Apple was never behind on that.
9:52
They were never behind on on uh display resolution.
9:56
like they had the uh the retina screen immediately, but you could imagine a situation where if Apple was three years behind on retina screens, people would be like, "Well, yeah, like I want the one that's sharper screen or something."
10:08
And Apple's been behind on a lot of things by a year or two.
10:10
And the and that's what leads the Android fans to always say like Android's had this for two years or that's why I have Android because I like the cutting edge because you're actually you actually kind of are in many ways more on the cutting edge when you're in the Android ecosystem but you just don't have all the integration that comes >> Android owners love to tell you the specs of their new device.
10:34
>> They love to go spec for spec. >> Yes. Yes. Exactly.
10:35
But the question is, uh, should Apple actually go so hard to play catch-up?
10:44
And so, um, Apple beat earnings.
10:48
>> I think I mean, >> yeah, >> going hard could look like buying perplexity.
10:51
People have, uh, made the case.
10:55
>> My voice is still shot from that.
10:55
People have people have made that case, but it still feels insane when you look at the history, Apple's M&A history. Yeah.
11:03
And and often they're happy to to acquire talent.
11:08
Y, >> but they don't do it at the the VC's.
11:13
Historically, they're not doing it as sort of unicorn valuations, right? >> Yeah. >> Yeah.
11:18
the um like going hard could look like spending hundred billion dollars or it could look like just figuring out what their next Google deal looks like because Apple has this insane deal with Google where Google is the default search engine on Safari and they make what $10 billion profit something yeah 20 billion in profit every year off of that deal.
11:42
It's like a fantastic deal and people are worried that it might go away.
11:47
Um, so I there's something in this um but uh there's something in here but you know you could imagine a situation where Apple is getting a massive payday from a foundation model lab to route iPhone customers to that model and we haven't seen that dynamic play out.
12:06
There's this question of will Apple >> one scenario is is uh there's a world where a foundation model gets the Siri button and Google keeps the the default search. >> Sure.
12:18
>> And Apple suddenly is getting >> another like 100%. >> Yeah.
12:23
I mean Ben Thompson's written about this.
12:25
We've talked to a lot of folks about this.
12:26
Like there's this weird world where chatpt is so dominant that they might like they could swap out the foundation model for a different model and most people wouldn't know.
12:37
They'd be like, "Oh yeah, I use chatpt and they be like, "What model?
12:39
40 or or 03 or Gemini or Llama?"
12:42
And they'd be like, "I don't know. I don't care."
12:44
Like it just gives me the answers.
12:45
And so you could imagine a world where where Apple is pumping users into moni into monetized, you know, LLM queries and getting a huge check from that.
12:58
And maybe that's the most elegant solution here to like get back in the AI race or capture the value.
13:03
>> I would love to know how much OpenAI already pays Apple just through the app store.
13:08
>> Oh yeah, I don't know.
13:08
Yeah, because if you if you subscribe to OpenAI in the App Store, they probably take 30% of that.
13:15
And if they're making a billion a year and maybe a third of that is from iPhone subscriptions, inapp purchases, like you're looking at like a hundred million dollars a month.
13:25
Is that like are we in the right territory?
13:28
That seems like extremely high. I >> know.
13:30
I'm going to look in the look in the app store right now and see how they actually push inapp subscriptions. >> Yeah. Yeah. I I don't know.
13:38
I I'm pretty sure I subscribed on web long before downloading the app and then I transferred the app in.
13:43
Uh and and uh CHP might like the the team might push you out into a web view like you can do that now.
13:50
Uh it's getting easier every year because of the antitrust stuff and uh it certainly makes you know economic it's economically rational especially if you're going to get somebody to upgrade >> you can't make changes to your subscription inside this app. >> Okay.
14:03
So so the answer is zero.
14:03
So right now I I think zero dollars are changing hands between Apple and OpenAI either way, but that could change and and maybe that's the end.
14:14
Um but uh you know on the on the question of should Apple um make a huge acquisition.
14:21
Um Tim Cook actually addressed it in the earnings call.
14:27
call. uh he said something like we've acquired around seven companies this year and that's companies from all walks of life not all AI oriented we're very open to M&A that accelerates our roadmap we're not stuck on a certain size of company although the ones that we've
14:44
acquired uh thus far this year are small in nature and he said like we're acquiring one every few weeks which is not quite seven per year I mean I guess that's like one a month but a few weeks sure um so he's doing deals but he's not looking at anything massive And I think that actually makes sense. My question
14:59
My question was if you were the CEO of Apple and you had a hundred billion burning a hole in your pocket, what are the other things that you could do with that money? >> Formula 1 team.
15:14
>> You could buy every team and the division and every track and the and all the sponsorship.
15:21
>> I made a post about this jokingly. >> It's crazy. It's so much money. It's so much money.
15:24
>> I made a post about this jokingly earlier this year.
15:26
I still think it'd be cool for Apple to just be an F1 in the way that Red Bull is.
15:31
>> I think that'd be great. >> No, no, I agree.
15:32
Yeah, I think that'd be great.
15:35
>> The one thing culturally is like Apple's brand is is very premium and very high-end.
15:40
And um >> I don't know if they could handle a few seasons.
15:45
>> This was the early bare case for Apple TV.
15:48
TV. I was talking to uh someone a a very successful Hollywood producer and he was saying that um the nature of the of Hollywood is like venture capital like it is a hood driven business if you don't accept that you're going to have massive flops and egg on your face and embarrassing moments you will not make
16:10
it and just like any venture capitalist who is like I only want to make investments where they won't blow up you're not going to make it right Yeah, Mark Andre had a had a there was a clip from a episode he did recently talking about how you lose sleep over the companies you don't invest in, not the ones you invest in and don't work. >> Exly. Exactly. Exactly. And so, so you >> Exly. Exactly. Exactly.
16:30
And so, so you have to be risk on.
16:32
You have to be risk in Hollywood as you do in venture.
16:33
And so the the question was like, can Apple deal with spending 50 or hundred million dollars on some show that completely flops and everyone's like this is a disaster?
16:45
Um, and they've navigated really well.
16:48
I think that they have had some flops, but they've kind of tucked those behind the scenes.
16:51
Whereas Netflix has started to get more kind of, you know, people talk trash about what was that Red Red Notice or they they did some massive movie with The Rock that kind of flopped.
17:01
They've done a few of these big movies that haven't done that well and and it's sort of like, oh, like, you know, they're they're they're not, you know, God's gift to, you know, producing.
17:11
Um, but it doesn't matter because overall Netflix is doing very well and all it takes is like one Squid Game to like carry the whole quarter basically just like Inventure.
17:19
Um, or like one, you know, you sign the Friends deal and then or The Office and people are watching that like 20 years later.
17:27
Um, so >> and um, apparently so F1 uh has surpassed half a billion dollars in box office earnings as of last week.
17:34
I mean, it's a fantastic >> That's an example of a uh of a home run, >> but it's not like they're doing that once a quarter by any means.
17:44
>> Oh, and John Xley's in the chat. Shout out to John Xley.
17:46
Uh unfortunately, I didn't get a chance to connect with him at our party in New York, but he did attend.
17:51
You got to chat with him.
17:51
A lot of the team got to chat with him.
17:52
So, thank you for all you do, John.
17:54
We really appreciate you.
17:55
The entire team is giving you a round of applause.
17:59
General >> because general of the you've done a ton of a ton of work for us and we really appreciate it.
18:03
Um anyway, if you had a hundred billion dollars burning your burning burn burning a hole in your pocket at Apple, what would you do?
18:09
I have a bunch of crazy ideas. >> Go through your list.
18:15
>> So, uh most people would just say, "Hey, you're going to benefit from AI because you are the window into all technology and it doesn't matter if it's if it's generative video or or text like people will be consuming it on devices.
18:26
You sell devices, you'll be fine."
18:28
Uh, just like search did not destroy Apple, it actually made Apple stronger because people search on their iPhones.
18:34
Um, so most people would just say, "Hey, return it to the shareholders."
18:38
Apple's already done that.
18:40
They've returned over a trillion dollars to shareholders in the past 10 years.
18:43
Those are kind of rough numbers, but it's basically that, which is an insane amount of money to return to shareholders.
18:48
Um, but Samsung is worth 330 billion.
18:51
They could buy the entire company, lever it up with twothirds debt, and they would just own both sides of the smartphone market.
18:59
probably extremely anti-competitive.
18:59
I think Lena Khan would have a conipion fit, but uh funny concept funny concept.
19:06
Um the other uh the other the other idea is massively expand the retail footprint.
19:11
So Apple right now, I was surprised by this.
19:14
How many retail stores do you think they they have worldwide?
19:18
>> I don't know like 599 or 601.
19:22
>> Did you look Did I tell you this morning? It's 535.
19:26
Um, so it's not that many.
19:26
It's mostly in the tier one cities.
19:29
There's usually only like one in every city.
19:30
They don't really they don't take the Starbucks strategy where they put them across the street from each other. Yeah.
19:35
>> But for hundred billion, they absolutely could.
19:37
A hundred billion is enough to open 6,000 new Apple stores. So they would be 6,600.
19:44
So, they would be up around 7,000 stores, which for reference is as many Subways as there are and as many CVS's as there are and as many 7-Elevens as there are in America.
19:54
And so, everywhere you see a Subway, you could see an Apple store.
19:59
And I feel like this would be a big upgrade for America.
20:02
I feel like if you just walked around every American city where tier one, tier two, tier three city, you just see a beautiful sheet of glass and it's an Apple store on every corner in America.
20:13
They could also acquire every firearms uh store in the country and turn them into Apple stores.
20:21
>> They could do a take private of Figma.
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20:30
>> I'm still buzzing from uh Thursday.
20:32
>> It was a fantastic day. >> Absolutely fantastic.
20:34
Anybody that is tuning in, anybody that is tuning in to the show for the first time today is going to be hearing our ideas for Apple and just thinking these are some of the worst ideas I've ever heard, >> but they're definitely fun.
20:47
>> Okay, so speaking of glass from the Apple stores, they could buy Corning, which makes Gorilla Glass.
20:52
That's a $55 billion company.
20:53
Then with the money left over, they could buy Interdigital, which owns all the patents on 5G and 6G.
21:01
So they could basically patent troll everyone else in the industry.
21:02
get extremely anti-competitive.
21:06
>> They could also with the money that is left over, we're still in the first like let's vertically integrate this company mode.
21:11
They could also buy 10 rare earth or cobalt mines.
21:13
So, they own the supply chain there.
21:16
And then they could also build four battery gigafactories and lock up the sapphire crystal supply chain that's used on the uh on the the iPhone camera.
21:26
So, they could just completely own their entire supply chain for 100 billion.
21:30
Uh and and that's just one year.
21:32
one year and then then they you know the proposal was do this every year.
21:36
>> The other thing that was interesting about Tay Kim's post is if you if you listen to the earnings call Tim Cook and the team were very clear that they don't even want to finance like data center development themselves.
21:47
They're still working with these sort of like third party >> lenders to like capitalize them.
21:54
>> Um and so again Tim Cook uh is the king of >> uh efficiency. >> Yeah.
22:00
He knows his business and he's Should we get into some of >> No, I have one more. >> One more.
22:05
>> So, OpenAI, they Aqua hired Johnny IV.
22:10
They're coming out with something that's competitive.
22:11
It's going to be some some sleepless nights at Apple when that things drops, right?
22:14
It's going to be stressful because like maybe maybe it doesn't go super well, but like, you know, it's a serious threat.
22:20
Open is a serious company.
22:21
They have a lot of customers and they got Johnny OV your former goat dei designer ready to drop you knowunch former Apple employees >> tons amazing amazing team over at in in hardware at open AI.
22:34
So the question is like how do you fire back with your Apple and you have a hundred billion to spend. Here's what you do.
22:40
The cogs on an iPhone are less because they have a margin.
22:45
So you take that hundred billion dollars.
22:47
You buy 200 million iPhones and you send a brand new iPhone to 200 million Americans and you're just like, "Oh, how much are you charging Johnny IV and OpenAI?"
23:00
>> Well, ours is free this year.
23:02
>> We're doing a free iPhone for the entire year.
23:05
>> They should just do something like that where it's like your 11th iPhone in a row >> is free. >> Is free.
23:10
>> They'd probably have 200 million people with free iPhones and they're just like, "Yeah, we're actually we want to keep you in this ecosystem.
23:15
We like our services revenue.
23:17
We're excited to be a platform. >> We're excited.
23:20
We're just giving it back. We're just giving back. Can you imagine?
23:24
>> I think that would also be extremely anti-competitive.
23:25
I don't even know if there's a regulatory framework to stop that from happening.
23:28
But I mean, price competition is a real thing.
23:30
Like if you if you discover that your competitor is under capitalized and can't can't win a capital war, you could potentially cut co cut it cut prices so dramatically that it's like yeah the the other phone's like cool, but you know this one's free.
23:48
I guess I'm staying in in the blue bubble world. >> Tim earnings call.
23:54
>> All right, we're going to buy all of the minds we depend on and we're going to make the iPhone free.
23:57
stock just eats like destroys >> 80%. >> He's like, I'm petty. I'm petty.
24:03
And you know what, Johnny?
24:05
You know, I'm not going to let you win.
24:09
>> I would rather die than let you win.
24:11
>> Yeah, I would destroy myself.
24:11
Uh yeah, I've been reading a lot about cutting your nose to spite your face.
24:15
I'm pretty into the strategy. >> Do it.
24:19
Uh anyway, uh let me tell you about Vanta.
24:22
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24:30
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24:36
>> Anyway, uh so uh Ben Thompson's been noodling on uh on Apple and AI strategy.
24:44
He had a rough go because he I think he took some time off or shifted he shifted his posting schedule right when all the earnings dropped and there was all this crazy stuff going on.
24:53
So, um, he he's just writing about Apple earnings now, but he has, uh, he still has some some good takeaway saying, you know, even if they do, even if Apple does swoop in and buy Mstral, for example, uh, the overall point holds Apple isn't going to compete with OpenAI, Enthropic, Meta X, and Google on pursuing AI super intelligence.
25:13
Like five extremely well-funded, extremely serious teams.
25:16
uh they're gonna Apple's going to go their own way, center it on their devices and their direct relationship with their customers, at least as long as Cook is in charge.
25:26
And anyone that's saying that Cook uh needs to step aside, I think is uh is in for a world of hurt because he's been on a generational run and he's solving the most important problem for that company, which is not the application layer in artificial intelligence.
25:41
It's the supply chain and keeping the keeping the flows flow of iPhones coming >> and selling phones >> making put the phones in the boxes. Tim, he's doing it. He's doing it.
25:50
He's really He's really He's really underrated.
25:54
He's been CEO longer than Steve Jobs was now >> the longest tenured CEO of Apple in history.
26:01
>> He better be bringing some of these AI researcher uh comp packages in as as comps when he gets in front of the comp committee at Apple. >> Yeah.
26:09
>> Say, "Hey, >> that is true.
26:11
He should definitely be getting a bump.
26:12
Uh if he does have researchers, I mean he has he has AI researchers.
26:16
They are improving different functionality.
26:18
I feel like maybe I'm hallucinating this but it feels like the texttospech engine has gotten better on my phone.
26:25
I listened to a semi- analysis article with the default Apple Safari text to speech and it was very listenable.
26:33
So I think we're getting better there.
26:35
regardless like he's got to get his AI researchers graphite so they can embrace code review for the age of AI.
26:42
Graphite helps teams on GitHub ship higher quality software faster.
26:46
So anyway, uh Hunter SPX is uh shocked at Alex Karp's comments uh on the Palunteer earnings call.
26:53
Uh Karp said, "The growth rate of our business has accelerated radically after years of investment on our part and derision by some.
27:01
The skeptics are admittedly fewer now, having de having been defanged and bent into a kind of submission.
27:07
Yet, we see no reason to pause to relent here. So good.
27:12
Catrini says, "You can't accuse the guy of not having flare." These are so good.
27:18
>> Palanteer ticked up over 400 billion, up almost 10% in the last five days. >> Let's go.
27:24
>> So, >> congratulations to everyone over at Palanteer.
27:26
Congratulations to Elellaniano who's been on the show, friend of the show.
27:29
Uh he says he's actually in tears after uh Carp went on CNBC and said just tell the haters, read them and weep. I love it.
27:37
We covered this yesterday a little bit, but I wanted to go one step deeper.
27:42
>> My uh friend of the show, Marcus Million, uh was posting earlier a bunch of sell orders that he had for uh Palunteer earlier this year and he was uh feeling >> he was very weeping, very disappointed with himself. >> He was weeping.
27:54
So, uh, Palunteer Technologies, uh, boosted its fullear art outlook after posting higher profit and revenue for the second quarter driven by continuing demand for its artificial intelligence projects.
28:06
Uh, the Denver company, which sells AI software to manage and analyze large amounts of data.
28:12
Everyone says, "What does Palanteer do?" It sells software.
28:16
Uh, it now expects revenue to be between 4. 14 billion and 4. 15 billion.
28:19
like what a narrow band for the year.
28:23
They they know what's coming.
28:26
Uh up from the prior outlook of 3. 89 billion and 3. 9 billion.
28:32
Uh so the interesting thing here is that uh they uh where is it here? I missed it.
28:38
Um so uh revenue from US commercial customers rose 93% to 306 million.
28:44
So Karp's been talking about this for a while. Just look at us.
28:49
Like you say that we're just a government contractor.
28:51
Look at our look at our commercial side of the business.
28:55
Like we're doing very well there. Companies are buying.
28:58
>> Who are we talking to when they they casually mention that they got like a a ninef figureure contract in Japan randomly?
29:05
>> Uh uh on the on the corporate side. >> Yeah. On the corporate side. >> I don't know.
29:09
I we've talked to a lot of Palunteer people, but it's all over the place.
29:11
I mean, everyone from like Airbus, like if you want to know like what Palunteer does, just just the Airbus example is like the best because it's just like you're making planes.
29:20
There's a ton of different parts that go in that plane.
29:22
You need to see the lead time, the durability, the testing of all those.
29:28
You need not just a database of what you have in stock. Okay?
29:31
We need more seat belts to get this plane out the door. We need more engines.
29:36
We need more, you know, doors or whatever.
29:39
Like, you got to buy all these different things probably from uh Transdime or something.
29:44
Some some pebacked small manufacturer makes the subcomponents.
29:48
you got to buy all those components, put them all together, and then ship the ship the the final plane out.
29:51
Well, you don't just need a database of what everything's in.
29:55
You need to know how these things interact.
29:56
And that's why Palunteer always says like ontology.
30:00
It's it's a layer on top of the database.
30:01
And so, there's been a bunch of database companies that have grown a ton.
30:05
Snowflake and uh and Snowflake and uh and Palanteer were kind of duking it out and now they're kind of partners and friendly.
30:13
you put all your data together into a data lake and put Palunteer on top of it.
30:17
Um, and so it's driving uh it's all good news for for uh KARP.
30:21
Uh two CEOs top 1 billion in raises.
30:28
Palunteer CEO Alex Karp's 2020 equity award has soared in value to 14.
30:31
7 billion as the company's stock grows.
30:37
That was when the company first went public and he got a bunch of stock and it's grown and grown and grown as the share price has uh appreciated.
30:42
So >> poor Snowflake stock chart looks very different.
30:48
>> Well, what's the market cap right now? >> 68 billion. >> Oh, not bad. >> Still up 30%.
30:54
>> Little side project incubation for the folks over at Sutter Hill.
30:57
Um it is the latest ultra exclusive achievement for executives of big US companies. the billiondoll year.
31:06
Two bosses made it last year, holding stockbased pay that swelled in value by at least 10 figures in a single year.
31:13
That'll buy a lot of cost crosscountry skis.
31:16
Uh, and a lot of aquinauts.
31:19
Uh, Alex Garb clocked more than$6 billion.
31:22
Effectively corner the entire >> You could buy all the aquinauts. >> Aquinauts. >> You can buy them all. >> All of them >> 100%.
31:29
I've actually done this before.
31:31
before I've asked GPT like find me the the market cap of all the supercars.
31:34
So you take the average selling price of the F40.
31:38
It doesn't work this way because once you start buying them up they get more valuable.
31:41
But um but if you take like an F40 is like a couple million bucks but there's only a few thousand of them.
31:46
You add that up that's like $5 billion market cap.
31:47
One of the biggest market caps if you use this kind of rough terminology is uh firet trucks because there are a million dollars each and there's like a million of them in the United States.
31:59
Now, they're all like slightly different brands, so it's not quite the same comp.
32:01
Uh F-150s also huge market cap.
32:05
Tons of >> Can you look into getting a fire truck for for our road shows?
32:09
>> I don't think there's enough space inside.
32:10
I think you want I think you want something else.
32:12
But you could you could load up cables in all the different sides like, you know, we pull out the hoses and just a massive HD HDMI cable. I think that's the move.
32:19
Uh so uh Hawk Tan grew uh grew his pay grew by 1.
32:26
15 billion at chipmaker Broadcom.
32:26
So Broadcom did very well.
32:29
Uh only two other S&P 500 CEOs have hit that mark in recent years according to data from a public company data provider.
32:38
Uh cryptocurrencies exchange Coinbase Global Brian Armstrong in 2021 at 2. 1 billion.
32:45
And naturally, Elon Musk, the Tesla CEO, can boast billion dollar gains in three years, including a record 43 billion in 2020.
32:55
Though all are part of a pay package that the Delaware court declared invalid on Sunday, Tesla granted Musk a new interim stock award that tentatively valued that was tenatively valued at 23.
33:06
7 billion with the promise of more this fall.
33:10
>> It's barely scraping by. >> Scraping by.
33:11
Um the other note on Palunteer, I think this was reported on Friday, they have a new US Army contract worth up to $10 billion.
33:18
So this is consolidating a handful of contracts that they have into a single deal.
33:26
>> And um yeah, so pretty pretty significant that that's over I believe the next uh decade.
33:34
>> So Palunteer Classic 20-year overnight success.
33:36
um overnight some interesting history and kind of strategy of how they got here.
33:43
>> So, we talked about this before, but you remember the famous story about Alex Karp talking to his employees early in the in the in the journey of the of the company.
33:54
He said, "When you're traveling for business, I want you to book a five-star hotel when you're in town visiting a potential client."
34:01
And Gary Tan was commenting on this.
34:04
Tan was commenting on this. other employees were saying like this we're a startup we're burning money this is kind of a crazy thing what's the rationale here and and Karp had a very contrarian take he said that when you're doing business you're going to meet a Fortune 500 company that you're going to be consulting with or rolling out or
34:21
selling them palenteer selling them software you're going to be a forward deployed engineer um they will ask you oh you're in town where are you staying >> just it's just a natural thing that comes up during introductions oh you're in town you're in you're in Dallas visiting us at our HQ We're evaluating Palanteer as a potential solution provider. Where are you staying? And if Where are you staying?
34:37
And if you say the holiday in, they will assume that you're selling holiday in level software.
34:43
Holiday in quality software.
34:46
But if you say I'm staying at the Four Seasons, they will assume that you are selling Four Seasons level software.
34:51
And so Palunteer had this culture of Karp has joked about like steak dinners being like not the correct way to sell the product and the product actually has to be very good.
35:03
But clearly from an early from from early on, Palanteer focused on >> brand positioning >> brand positioning and just taking travel and entertainment very seriously because there's going to be a lot of forward deployed engineers that are on the road a lot.
35:17
You want their life to be uh you know manageable so they can go and show up and perform and they're not um and they're not like gassed and exhausted from an economy flight and then a then a tough bed >> holiday in.
35:28
So this was wrecking their financials though like when they went out and they went >> nar the narrative was that they were a consulting company masquerading as a software company. Yep.
35:41
>> And looking at the earnings yesterday and their margin profile this is very clearly not a consulting business. >> Yeah.
35:48
So when they went public you can look up the the the market cap uh when when they kind of went out early but I believe that they were languishing in the low tens of billions.
35:56
uh might have even dipped down to five billion at some point, seven billion market cap.
36:01
Uh the stock was not >> there was a period if you bought >> a single share at the open, you could have paid $9. 20. Yep.
36:12
>> And years and years later, >> you would have been flat. >> Yeah.
36:17
>> On that entire period. >> Yeah.
36:19
>> Uh it was uh so they went out October 2nd, 2020.
36:22
And if you look uh on May 12th, they they they ticked over that initial uh price.
36:29
So, um not uh a lot of people were writing it off for a long time.
36:35
And it and it still it didn't it didn't it wasn't like a fa fast IPO by any means, right?
36:39
This was like took them what 15ish years to get out.
36:40
So, >> so 2020 2021 they were in like the 40 billion 35 billion.
36:47
I think they probably dipped lower at a very at varying points in time.
36:51
Um, but it wasn't it it the stock was not ripping and it was kind of in this it was languishing.
36:58
The consulting uh meme was was going strong and that was because they were spending a ton on travel and and entertainment.
37:06
Um, but what's interesting is what happened during COVID.
37:09
So during COVID they couldn't travel as much and companies didn't want forward deployed engineers coming into their offices.
37:16
They didn't like airlines were shut down for a long time.
37:20
everyone was working remotely.
37:22
So they switched to a remote first, you know, forward deployed engineer strategy.
37:27
And so by default during an implementation of Palunteer, you would just hop on a Zoom call or hop on a team's call or whatever.
37:36
Uh and so their travel entertainment budget like cratered and that was really really good for their bottom line.
37:42
And then they were able to just kind of like hold the line and they didn't and sure they added it back slowly, but it kind of revealed that this actually does have software margins.
37:53
This actually is more of an enterprise SAS company than a consulting business.
37:56
And it allowed them to grow very very significantly.
37:59
And so uh they've they've been on an absolute tear and congratulations to everyone over at Palunteer.
38:06
>> Well, while we're talking about earnings, >> let's talk about linear.
38:08
Linear is a purpose-built tool for planning and building products.
38:10
Meet the system for modern software development.
38:11
and streamline issues, projects, and product road maps. Start building up.
38:16
>> Ben and the production team are going to pull up a post from uh highlighting something from Reddit's Q2 earnings call.
38:23
If we can pull this up and play this video >> video, that's fun. >> Okay, let's see.
38:28
>> Let's play a video here. Let's see.
38:28
This is the hardest thing.
38:31
>> That's why Reddit is the number one most cited domain for AI across all models per data collected by profound.
38:36
That's why Reddit is the number one.
38:39
Anyway, so I wanted to highlight this because >> we just partnered with Profound.
38:43
This is a company that I invested in uh earlier this year.
38:48
James CEO has been on the show.
38:50
Profound uh allows companies to understand and improve the way they show up in LLM.
38:57
So, uh today companies are using LLMs.
39:00
Uh everyone's using LLM to research products, make business decisions.
39:04
And so if you're running a uh any type of business, whether it's consumer or enterprise focused, you got to actually figure out where you stand in these rankings, how people are perceiving your products through the models.
39:17
And profound uh lets you do all of that observability.
39:21
Uh I think the best way, the best comp for it is kind of like SEO optimization.
39:25
There's a bunch of different dynamics here.
39:27
Uh but Profound is the clear leader and uh we're super excited to partner with them. Let's hit the gong.
39:35
>> Hit the gong for Profound.
39:36
>> Profound and a new TBPN sponsor. Welcome to the lineup.
39:41
>> Welcome to the livery.
39:41
Welcome to the next drop of merch. Welcome Profound.
39:46
We're happy to have you on the team.
39:46
Um, >> welcome to the show.
39:50
>> In other AI related news, uh, Open AI has announced an opensource model.
39:53
They said they'd never do it.
39:56
Everyone's saying it's closed. It was in the name.
40:00
How could you have closed AI? Closed AI. They're not open AI. They're closed AI.
40:05
Everyone thought they were so clever.
40:06
They said they couldn't possibly open source a model. And they did. >> They did. >> They did it.
40:12
>> First open model in years, right? They used to have that.
40:16
>> Was was GPT1 open source?
40:16
Like when when was the last time that So, we're going to talk to Tyler about this.
40:22
In the studio today >> was still open source and then they decided to close source something.
40:27
Uh it's tough that I I treat you like things that I could Google and I know that you just have to search it or chat GPT it. Um but uh good luck.
40:35
Get me the information on the the history of open AI's open-source models.
40:42
In the meantime, I will read this post from Sam Alman. GPTO OSS all lowercase.
40:46
He's still in lowercase mode, although he he uppercases the other sentences, >> but he he he threw in he likes lower case.
40:57
sending you messages, John. >> I'm seeing it.
40:58
I'm seeing coded messages in here. Uh GPOSS is a big deal.
41:01
It's a state-of-the-art open weights reasoning model with strong real world performance comparable to 04 Mini that you can run locally on your own computer or phone with the smaller size.
41:16
We believe this is the best and most usable open model in the world.
41:21
We're excited to make this model the resil the result of billions of dollars of research available to the world to get AI into the hands of the most people possible.
41:29
Hit that soundboard again. I want to keep it going.
41:32
We believe far more good than bad will come from it.
41:34
For example, GPOSS 12B performs about as well as 03 on challenging health issues.
41:40
We've worked hard to mitigate the most serious safety issues, especially around biocurity.
41:47
GPTO OSS models perform comparably to our frontier models on in on internal safety benchmarks.
41:52
We believe in individual empowerment.
41:54
Let's hear it for individual empowerment.
41:56
People, >> I feel empowered the way that you're reading this, John.
42:00
>> Although we believe most people will want to use a conventional service, a convenience service like chatbt, people should be able to directly control and modify their own AI when they need to.
42:11
And the privacy benefits are obvious.
42:11
As part of this, we are quite hopeful that this release will enable new kinds of research and the creation of new kinds of products.
42:19
We expect a meaningful uptick in the rate of innovation in our field and for many more people to do important work than were able to before.
42:28
OpenAI's mission into is to ensure AGI that it benefits all of humanity.
42:31
To that end, we're excited.
42:33
I think I cut this screenshot off.
42:36
We're excited for the world to be building on an open AI stack created in the United States based on democratic values available for I didn't screenshot the rest of that but oh wait here it is available for free to all and for wide benefit.
42:53
>> So I I imagine that that was the voice authored as the author intended. Exactly. Exactly.
42:58
>> Will Depw has some more notes here uh some context.
43:01
So less than one year between 01 announced which was September of 2024 and we have an 03 level model open sourced that's runnable on consumer hardware. Wild progress.
43:10
You were highlighting earlier Sam initially had a poll.
43:14
Oh yes saying like you know should we should we what do you want?
43:17
Do you want an 03 level model or do you want something that you can run? >> He did both. >> And he did both. >> He did both. Wow. That was Yeah. So we were reading that.
43:27
So, uh, it it was what, like six months ago or something, that post that you that you shared. >> Yeah, I think so.
43:33
>> Uh, so I asked I asked Tyler to to dig this poll up.
43:35
Sam Alman shared a post that, uh, it was a poll on X saying, "What do you want?
43:41
Do you want an 01 level model, reasoning model, a frontier model, open- source, or do you want something you can run on your phone?"
43:49
And it was and it was neck andneck, and people were clicking on the phone model.
43:53
They were like, "We want the phone model."
43:54
And then Dylan Patel quoted it and said, "Oh, you idiots don't vote for the phone model.
43:58
You can just still frontier model.
44:02
>> Let's get a frontier model."
44:02
And so, so Dylan Patel was very much like like you guys don't know what you want like like the phone models are available. That that will be easy.
44:11
The hard thing we got to twist OpenAI's arm to open source the reasoning model, the 03 level model.
44:16
And Sam Alman just said you wanted this or this.
44:20
It was a false dichotomy. You get both. >> You get both. >> You get both.
44:23
Yasine says, "All caps, I'm so sorry for doubting you, Sam Alman.
44:27
I'm so sorry for saying that you were the antichrist.
44:29
I didn't realize I didn't realize your plans were measured in centuries.
44:33
I hope you forgive me for everything.
44:35
I'm so glad you kept control of open AI. I am so sorry. Please forgive me. >> That's remarkable.
44:41
Never talk down the future first ballot hall of famer, apparently the future leader of open source AI.
44:47
Will be very interesting to see how Meta responds.
44:49
Will they stay in the open source game?
44:51
Also just how important is open source?
44:53
Is this a Linux scale opportunity?
44:56
Is this an Android scale opportunity?
44:58
Like is this a you know is this GitLab to GitHub?
45:04
Like what what's actually the long-term play? Certainly cool. Great for the community.
45:09
We're going to see fun experiments.
45:11
We're going to see interesting things done with this.
45:12
I think um do do we want to talk about some of the ideas that we had for building on top of this uh open source model fine-tuning?
45:22
I can just run through some I know there's one you didn't want to you didn't want to share because you thought it was too too too good too much alpha but what was what was I talking to you about Tyler. What were our ideas?
45:31
We had one that was uh >> well initially we weren't sure there was going to be reasoning right so we were going to add fake reasoning. >> Yeah.
45:38
knew it was going to be a model that gaslights you into thinking it's reasoning when in fact it's not reasoning.
45:45
So, >> so if you pull up if if you look at at the actual like you know reasoning UI, it's just UI.
45:51
It's not there's no actual reasoning. It's like a time delay.
45:53
It's a time delay and it's delay thinking really hard. Let me think about that.
45:58
>> What would this what would a super smart person think right now?
46:02
>> We could actually still kind of do that because it's not a multimodal uh model, but we could like, you know, we just add some kind of like totally blank encoder or something for the image >> and then it's like, hm, this is an interesting image.
46:13
Let me think about what's in it. >> Yeah.
46:15
One of the best images I've ever seen.
46:17
A lot of people are saying this this is one of the greatest images.
46:20
Thank you for sharing this PNG and/or JPEG with me.
46:23
It just knows nothing about the about the image. It's great.
46:25
I I I I'm seeing that this image is uh is is large in file size.
46:31
It's purely metadata based analysis.
46:34
Doesn't know anything about what's going on.
46:36
Like, wow, this is a tough question.
46:38
I'm going to have to generate a lot of internal reasoning tokens to to answer this.
46:41
Test time inferences really is magical, isn't it?
46:45
Anyway, back to thinking.
46:45
Okay, I'm reasoning about this now. Yeah.
46:47
So, >> the other the other the other obvious opportunity, you know, people have been frustrated with uh syphency with the models and and models being >> Well, not me.
46:57
I've been frustrated with the lack of sick. >> Yeah, you want more. You want more.
47:01
>> You want the model to gas you up, but you know, fine-tuning it to go, you know, over the top.
47:05
Somebody could release the Glazinator 3000, which which just tells the user, >> uh, you don't you don't just think you're goated, you are goated. >> I know this. You know this.
47:16
>> It's like, I'm asking you to solve IMO question six.
47:18
Why are you talking about whether or not I'm goated?
47:20
It's like it it just tells you like, you got this one.
47:24
>> The timing the timing here, the timing here is interesting.
47:26
I mean, everybody's everybody's been banging the table saying, "Where is the American open-source AI or LLM leader?"
47:33
Uh it was reported yesterday by the misinformation that uh reflection reflection uh the misinformation reported that reflection uh one-year-old startup uh we've had uh the CEO on before is in talks to raise 1 billion to develop open source models to compete with DeepC uh Meta and Mstrol uh and yeah all of the you know the the Chinese open source models have been on a tear.
48:06
Uh Quen released Quen Coder recently.
48:09
>> Yeah, people are into Quen >> um or a new version of it that uh is getting good results.
48:13
So, >> it's important work.
48:15
We want >> So, one interesting thing that's kind of related to the like US China like race is like so so when Deep Seek first came out, everyone was like up in arms because they said like it's it was less than $5 million to train, right?
48:25
Y >> So, um in the in the model card for for these models, um they actually reveal like the uh GPU hours it took.
48:31
which then you can like figure out how much it probably cost costed to um you know train.
48:39
>> Give me the number and tell me if I need to ring the gong for that.
48:42
>> So so for the big model it was probably around like 4 million.
48:46
>> Oh >> so just yes but but the the small model was like 500k probably a little less >> but that's like 10x better.
48:52
The model is way better than deepse one. >> Okay. Okay.
48:55
So shall I ring the gong?
48:58
>> I mean I think it's pretty >> I wanted I wanted I wanted to hear 400 million at least.
49:02
I was expecting nine million nine dig.
49:05
They got a billion of revenue coming in every month.
49:08
But it's cool that it spent 10 days of revenue on the open source model. I know it is very cool.
49:14
So So we're ringing the gong for for the elegance of the training run. >> Yeah. Efficiency. Efficiency.
49:22
>> Everyone in open AI on efficiency and cost model saving time and money.
49:28
putting money back in the hands of shareholders and not in the hands of open source developers, I suppose.
49:32
Um, but yeah, I mean, do you think that uh is this is this like a pre-training scaling wall narrative?
49:38
Like like would you as someone who is a potential consumer of an open source um model?
49:46
Like do you want a $400 million open-source model?
49:48
Would that necessarily be better?
49:50
because it seems like they were able to distill it pretty well, get it to the frontier, not you know, burn a ton of money on on training.
49:57
Also, the question is like if they're this is probably distilled from their other models that are much bigger.
50:04
So like you there is no world where you could just spend $4 million and get this level model without also have done having done the GPT4 run, the GPT4. 5 run, etc. Right. >> Yeah.
50:17
Maybe it's also just like even if they didn't distill it, they just have the knowledge of like how they did it, which is like arguably more valuable, right? >> Yeah. Yeah.
50:26
>> I think in terms of like open source, it's either you want to go like super super cheap and super small, which they kind of did here, or you go super big, like almost like the llama like the right. >> Yeah. >> Yeah.
50:36
>> Um I think it would have been really cool to see that like literally like state-of-the-art, you know, level model.
50:42
Yeah, >> you could also try and ask Claude, hey, build me a Frontier open source model. Don't make mistakes.
50:49
>> Yeah, we're gonna have someone from Claude on soon.
50:50
Um, this is funny because wait, you said 500K for the small model? >> Yeah, probably less.
50:57
>> So, that's the same amount of money that they're putting up for this uh challenge, the red teaming challenge. Have you seen this?
51:02
So, uh, to encourage researchers, developers, and enthusiasts, that's me, from from around the world to help, uh, identify novel safety issues, this challenge has a $500 pri $500,000 prize fund that will be awarded based on review from a panel of expert judges from OpenAI and other leading labs.
51:23
At the end of this challenge, we will publish a report and open source and evaluation data set based on the validated findings so that the wider community can immediately benefit.
51:31
So, if you can hack this thing, if you can get it to teach you how to develop a nuclear bomb or take over the world, you might have 500k in your pocket. Not bad. Go get some of that.
51:41
That's a seed seed seed round in 20 two 2012.
51:46
>> Massive day for the labs.
51:46
Anthropic uh announced a state-of-the-art uh coding uh model uh Claude Opus 4. 1 uh which oneups 4.
51:56
We are having uh somebody on the show from Anthropic later today, Alex Albert. Cool.
52:05
>> Uh to break all that down, so I'll wait there.
52:07
And then Google also announced Genie 3, a new frontier model uh a new frontier for world models.
52:13
>> Yeah, Tyler, uh take us through Genie 3. What is it?
52:16
Where are we in the deployment of this particular technology?
52:21
>> Let me give a little bit more context on Genie.
52:23
So given a text prompt, G gen Genie3 can generate dynamic worlds that you can navigate in real time at 24 frames per second, retaining consistency for a few minutes at a resolution of 720p.
52:34
So >> I got to be up at 60 frames a second if I'm pulling a nocope. >> 24. >> True.
52:41
>> This isn't This is an A24 movie.
52:41
This isn't a This isn't cinema. This is video gaming.
52:46
>> Get it up at 120 frames.
52:46
I got to be on 144 hertz monitor. >> Yeah.
52:49
So, uh, Google DeepMind as soon as John can 360 no scope at 60.
52:56
>> You got a customer, but for now >> you got a customer, but you got to keep pushing it.
52:59
>> Uh, yeah, break it down.
52:59
What is this and and and where did it come from? Why is this important? >> Yeah.
53:03
So, I I thought this was really cool.
53:05
I mean, we we've seen kind of like worse versions of this.
53:08
It's not like a completely new paradigm of like basically um, you know, real-time video that you can control. >> Yep.
53:15
>> Um, >> Oliver Cameron came on the show.
53:16
Uh he was at uh Cruz self-driving.
53:18
I interviewed him years ago.
53:21
He came on the show and he demoed this and the production team was kind of freaking out because it was like this very trippy like wandering around this like kind of uh Elder Scrolls landscape basically video game.
53:32
>> We've seen the same thing with um I remember playing like a Minecraft >> Yeah, Minecraft.
53:35
People have figured out how to do Etch has a Minecraft demo too that runs very quickly >> on some of their hardware.
53:41
>> Um yeah, but it's just like I mean if you watch the videos it's like incredible.
53:45
like it looks I think it looks by far better. >> Way better. Okay.
53:48
So, we we we we're now in like where like video generation was really really crazy and then V3 came out and it was like oh it's good.
53:54
And same thing with like mid Journey.
53:57
>> It's definitely getting to the point where like you could use this for training as like a RL thing, right?
54:02
Because this is like >> kind of I mean this is how you like uh justify spending a huge amount on this stuff because then you can use that as like training data. Yeah. Right.
54:10
For agents or whatever you know robotics >> synthetic data generation.
54:14
Yeah, >> for that I mean there is like the long term of like you know people just enjoy watching AI generated videos.
54:24
People get joy out of looking through Studio Giblies for a few days.
54:30
So like there is value just in the inherent product aside from training.
54:35
So you could imagine that this becomes like >> Let's pull up some of the examples.
54:37
I have them in the timeline. >> Yeah. Yeah. Yeah.
54:40
Let's pull these up and and and try and like uh flip through those.
54:43
Um, but how far are we from like the actual game mechanics?
54:49
When we played Oliver Cameron's one, I I remember uh being able to move around with the arrow keys. That was cool.
54:55
Next thing I wanted to do was I wanted to jump everywhere because that's like the default mechanic.
54:58
I mean, anyone who's played any game like with a jump button, you're jumping the entire time. You're bunny hopping.
55:05
Like, this is not something you just wander around in.
55:07
Um, and so does it have a jump button? Do you know?
55:11
>> Uh, I don't think it does. right now. >> Wow, we're so far. We're so early.
55:16
>> But but you can I mean it's cool cuz you I I actually don't remember this exact one you're talking about, but you can prompt like all sorts of stuff, right?
55:22
So in the examples that we can probably pull up. >> Yeah.
55:25
>> You can see them prompt in like Okay, a dragon flies in and they're in some like random Yeah. >> Okay. Yeah.
55:30
Let's take a look at this here. Okay.
55:31
So it's a bunch of This looks like an after effect.
55:35
>> Each one of these is an interactive environment generated by Genie 3, a new frontier for world models. >> Mhm.
55:40
With Genie3, you can use natural language to generate a variety of words.
55:45
Did >> they make this demo?
55:46
>> Explore them interactively, >> all with a single text.
55:50
>> Oh, I wanted to take the horse off the off the off the ski jump.
55:52
So, we're looking through a helicopter.
55:57
>> Let's see what it's like.
55:58
>> It's for sure photoreal.
55:58
Like, this is this is good enough.
56:01
>> G3 has real-time interactivity, meaning that the environment reacts to your movements and actions.
56:06
>> You're not walking through a pre-built simulation.
56:09
Everything you see here is being generated live as you explore it.
56:13
>> And G3 has world memory. Press space. >> Hey, 360.
56:18
We get We just got a 360.
56:20
>> World memory even carries over into your actions. >> This is That's AI. That's wild.
56:25
>> When I'm painting on this wall, my actions persist. >> Whoa.
56:29
Okay, that's pretty good. >> I can look away.
56:32
>> That's way less hallucinatory.
56:34
>> But when I look back, the actions I took are still there.
56:37
>> So, it remembers that. Oh, that's big.
56:39
So that's we haven't seen that cuz when we were when we were walking around in the other world, we would like turn around and there would just be like a cave and then you do a 360 and all of a sudden it's like Yeah, it's like a church or something. >> Horses dragon.
56:53
Yeah, that dragon looks pretty good.
56:54
>> You can use Genie to explore real world and movement.
56:58
>> I wonder how expensive this is.
57:01
>> This will probably be extremely gated.
57:03
I'll have to tag Logan to get me >> environments and even other characters. >> We're excited. Oh, there we go.
57:09
That's a really generation gaming and entertainment. >> Yeah.
57:14
>> And that's just the beginning. >> Yeah.
57:16
>> Roles could help with embodied research, training robotic agents before working in the real world. >> Okay.
57:20
Give me a top down simulation of World War II parts of iron >> and emergency treat.
57:28
>> Give me a spreadsheet.
57:28
I want to play Stellaris or >> Eve Online.
57:31
manufactur some of the use cases here.
57:34
Spreadsheets in space here's world simulation around.
57:40
>> All right, we can pause it now.
57:40
>> All right, we can pause it now. Um, you can imagine a world in the future where you give Jeie some images of you like with family growing up when you were five and you could just like be like have a third like you could just like >> very trippy >> generate like a synthetic memory like
57:57
this is where we're headed where where people are going to be having to kind of simultaneously hold their real memories and these sort of like simulated >> wow it's just like I put on my VR headset it's just like Christmas and now I'm super VR sick and I'm throwing up everywhere just like when I was a four-year-old and I ate too much candy on Christmas. It's very realistic. It's very realistic.
58:15
>> I think this would be really cool for for Llama to do or um for Meta to do like some kind of similar thing that you can run on the VR.
58:22
>> What do you think the training data set for this is?
58:24
Do you think this is YouTube gated?
58:25
Because >> it's got to be YouTube and it's also probably um just like video games.
58:28
I mean you can see so if you look at the old um this is Genie 3.
58:32
If you look at the the first papers, it's very clearly like, okay, that looks exactly like >> uh you know, GTA 5. >> Oh, really?
58:41
>> Or in the first one, um >> Yeah.
58:44
>> It's like some kind of very simple like 2D game that you can tell like, okay, that's a video game that they either built or found somewhere that they trained on. >> Yeah.
58:51
Uh yeah, I feel like the pulling from the different video games would be cool.
58:56
I wonder if you run into IP because you're basically like distilling GTA into a model. Yeah, probably not okay. Okay.
59:02
But you blend them all together, you create something new.
59:04
That's probably transformative and and uh fair use.
59:06
But I I I keep wondering I I was running the numbers and I think YouTube has like 20 xabytes of data which is 20 million gigabytes or something or 20 million terabytes or something like that.
59:22
It's like it's so much that >> you can't exfiltrate it.
59:26
You can't put it in a suitcase of hard drives.
59:29
it in a suitcase of hard drives. Like it is it is just the storage is like a data center of its own like as opposed to like the uh common crawl like the all the web text is like it's like you can put it in a server rack like it's not
59:44
that much data and same thing with like some of those image data sets and I always wonder like does Google have like a permanent advantage here or will we see the other labs catch up on this pretty quickly like OpenAI seem to have catched caught up pretty quickly in in image generation. Midjourney is doing
59:58
Midjourney is doing great there.
1:00:00
Um, but a lot of the images are out on the open web whereas a lot of videos are locked in YouTube and like if you can't get access to if scale really matters there, Google has like a serious serious >> per I mean they have Sora which is like it's kind of very slow like the architecture is definitely different than what you've seen from >> I don't even care about the speed of Sora.
1:00:20
I care about the the fidelity.
1:00:20
So, so Sora, the latest Sora feels like VO2 and VO3 feels like a full step.
1:00:27
I've said I put the same prompt in both and Sora is like way more hallucinatory. Like it's way crazier.
1:00:34
V3 still hallucinates and does like crazy things where like you'll be watching a car drive forward and then all of a sudden it flips around.
1:00:40
It looks like the car is driving backwards.
1:00:41
Like it gets confused, but just the visual fidelity is really really high.
1:00:46
>> Done that in real life. >> Yeah. Yeah. Yeah.
1:00:48
Flip flip the car around.
1:00:49
Uh anyway, get on numeral HQ, sales tax on autopilot.
1:00:53
Spend less than five minutes per month on sales tax compliance. numeralhq. com.
1:00:59
Um anyway, >> we have a post here from Close >> Cluso. >> Cluso Investments.
1:01:06
>> How do you not know how to pronounce Clusau?
1:01:08
>> Do you know Inspector Cluso? >> No. >> Oh, lore. Anyway, >> he French.
1:01:12
>> Uh it's uh actually I'm going to blanket.
1:01:14
I'm going to look really embarrassing now because I was trying to model >> fictional character. >> Fictional character. Yeah. The Pink Panther series. >> Pink Panther. That's right. Yeah. >> Movie. Is that a movie?
1:01:23
>> It has been adapted into a movie.
1:01:23
It was originally, I think, an animated show. >> Okay. Okay.
1:01:27
So, not not >> You don't know the Pink Panther theme song.
1:01:35
Real >> Cluso Investment says, "I haven't done it yet, but I really want to short Uber.
1:01:39
In New York City, there's a taxi app called Empower, which charges drivers a flat fee in exchange.
1:01:43
Takes 0% of the ride cost.
1:01:46
All of it goes to the driver.
1:01:48
If you're in NYC, I encourage you to try it.
1:01:50
I've been using it for two weeks now and every ride is 30% cheaper than Lyft and 40% cheaper than Uber.
1:01:53
LGA to Manhattan is around $25, sometimes 50 to 75 depending on Uber or Lift.
1:02:01
>> I think Uber should be in the cash generation phase, but they somehow flush the $25 to $30 they make.
1:02:04
They ride doing literally nothing down the drain. Bold statement.
1:02:09
Uh there will always be a market for Uber because some people value their time at a,000 an hour.
1:02:12
But for most people like me, waiting 2 minutes instead of one to save $30 is worth it.
1:02:19
>> I still do not understand what the engineers at Uber, PayPal, etc.
1:02:20
do because it seems like the marginal improvements they make are not worth their cost.
1:02:25
Anyways, maybe I can sell a call on Uber or something because despite Uber andyft using lobbyists and dirty tricks to try to stifle competition eventually, instead of pocketing $30 from a $65 ride and giving the cab driver 35, somebody someone like Empower will catch on and charge 40 and give it all to the drive.
1:02:41
Give it all to the drive.
1:02:44
>> All to >> the driver and Uber.
1:02:45
Anyways, typo at the end there.
1:02:50
>> I think the interesting thing here is like I can easily see something like empower working in uh New York City. Yep. >> Can't imagine Yeah.
1:02:56
high density environments where there's a lot of taxi cabs.
1:03:00
I just think in in the I've never seen a taxi cab 10 square miles around my house once.
1:03:06
And the question is like uh even if the model works, if they're not taking a cut, then they don't have money to invest in onboarding both sides of the two two-sided marketplace.
1:03:16
And so the question of like why did Uber and Lyft burn so much money?
1:03:21
Well, it's because they were running insane amounts of ads, >> convincing everyone to be an Uber and Lift driver.
1:03:28
And so they created they brought all this liquidity to the market.
1:03:31
And and New York City has had has had a few of these uh competitors.
1:03:36
There was another one for a while.
1:03:38
>> There was one that was owned by the taxi there's been a few some of the major >> and yeah I mean it's very clear that like certain markets are going to have you know different ways to slice it.
1:03:45
You go to some markets and I mean when we were in we were I think we were in New York City right and Uber had clearly lost some fight with JFK because it was like oh if you want to take an Uber just like get in a taxi cab drive 10 miles and that's the Uber pickup zone. And it's like what?
1:04:03
Like the Uber used to just come directly to the exit and act like a normal person.
1:04:07
But now >> same thing with LAX.
1:04:10
>> Yeah, LAX is LA exit black, >> which I guess makes sense because it was really congested and it was kind of crazy and it was and it was like actually probably net worse for everyone.
1:04:20
>> I think I think the bigger point here is just what what is why is the company not generating obscene amounts of cash when when their when their margins uh feel like they they they should be able to produce?
1:04:32
Uh we're going to be having David uh Richer from Lyft, CEO of Lyft on I think later this week post earnings.
1:04:39
Bunch of questions for him around autonomous vehicles.
1:04:41
And um we can maybe bring up this post as well. >> We'll see. Yeah. See the rebuttal.
1:04:47
Um well, let's tell you about Finn AI, the number one AI agent for customer service, number one in performance benchmarks, number one in competitive bakeoffs, number one ranking on G2. That's right. >> Go to fin. ai to get started.
1:04:59
Take him has a great post here from Jeff.
1:05:04
Apparently, this looks like it was in some hilarious from Jeff. >> This is hilarious.
1:05:07
Like memes are I've seen memes in VC decks like uh oh, we're doing a quarterly update on the market and somebody throws a meme in there.
1:05:15
The Jeffre is a very serious investment bank and they're throwing an AI generated image and the source, you see the source >> source co-pilot.
1:05:25
You know what that means?
1:05:26
So they made it >> the AI image generation they used is from Microsoft copilot.
1:05:30
Everyone thinks oh everyone uses chatbt not Jeff.
1:05:33
They use co-pilot because this is an Excel shop. >> That's right.
1:05:40
>> Hands off the hands off the mouse when you're prompting in co-pilot to be a Jeff associate generating this.
1:05:44
But it's a funny meme because Azure and GCP are dancing.
1:05:48
Meanwhile AWS is a sad puppy in the corner.
1:05:51
uh you know we talked about this with AWS like uh sort of lagging not having a strong you know horse in the AI race.
1:05:59
Google obviously has a fantastic uh foundation model lab.
1:06:01
Azure obviously is the open AI bet uh and is growing like crazy through the Amazon business >> has anthropic >> they do and the work they're doing with TPU there.
1:06:15
>> Somebody was saying that like tranium is is underperforming or people don't like tranium as much.
1:06:18
they prefer just give me a ton of a ton of Nvidia GPUs.
1:06:20
Um, but you know, who knows?
1:06:24
Never count out the goat, the man who invented the cloud, the cloud cowboy, Andy Jasse, >> the man himself, >> CEO.
1:06:31
I mean truly in the age of like AWS being the most important driver for Amazon as a whole.
1:06:35
Like the perfect person to run the business is Andy Jasse, right? Because he created it.
1:06:38
So, um, y >> they're in a pretty good spot.
1:06:42
>> We have a post here from Joe Weisenthal.
1:06:44
Flying first class on my flight out of New York City.
1:06:47
I was a little bit surprised here.
1:06:48
I expected him I expected Joe to be flying private, but he says, "Everyone in the front is solo, quiet, and isolated.
1:06:53
I look back >> to the rest of the plane.
1:06:56
People are joyously traveling with friends and family, sharing humor and adventure." Yeah.
1:07:01
Was just an interesting observation.
1:07:03
>> Well, I mean, I understand why I understand why people in in the front are solo, quiet, and isolated because uh first class flights have become extremely draconian.
1:07:13
>> Yeah, they really have. >> Terrible.
1:07:15
We we should share our experience.
1:07:16
So, we we we we flew a mixture of first class and and economy to New York City uh with with our lovely team and crew and uh Jordy were Jordy and I were up in first class and uh we're served.
1:07:29
We were flying uh should we name >> Yeah, we're going to name him. We're going to name him.
1:07:32
We were flying we were flying >> we were flying JetBlue Mint >> which historically I've had great experiences with mint over the years.
1:07:40
>> David Sra was singing their praises.
1:07:41
Said it was the best first class experience he's ever enjoyed and said it was fantastic.
1:07:46
But we had quite >> at times it's been fantastic but this >> quite a different experience. >> This was devastating.
1:07:51
>> Let's let's run through our problems.
1:07:51
So the seat was comfortable. Lay flat. It was great.
1:07:56
>> You didn't think it was comfortable. I thought it was great. >> The falloff is real.
1:07:58
Everything about the experience has degraded over the last couple years.
1:08:02
>> You know the worst thing about the lay flat seats?
1:08:04
This is such a me problem, but uh they're clearly designed.
1:08:05
They're like they're like 99.
1:08:08
9% of people will be able to lay down completely flat here. And the seat is 6'6.
1:08:16
So I'm I'm two inches short and so I have to like curl up >> to curl up in a little ball. >> Exactly. Like a child. Yes.
1:08:22
>> Well, it gets worse because >> Yeah.
1:08:24
That was just the beginning of our nightmare or nightmare flight. >> Order. I ordered steak. >> Yes. >> And I wasn't hungry. >> Yes.
1:08:31
>> So, of course, >> as soon as the flight attendant left, I got up and I walked the steak dinner back and I gave it to Michael and Scott. >> Yeah.
1:08:41
And then I went back to my seat and I was just relaxing and the flight attendant came up to me and a little bit later and said, "Would you like dessert?
1:08:47
We're serving uh gelato, I think it was."
1:08:50
And I said, "Sure, I would actually I would love gelato. Thank you."
1:08:53
>> And the flight attendant went back to the front.
1:08:55
I ran uh to the back and I started handing the gelato to Michael and uh a hand jumped into frame and grabbed the gelato.
1:09:07
>> Grabbed the gelato out of my hands and said, "You cannot do that." Yeah.
1:09:11
>> And um of course there's a rule that says you can't pass food between cabinets.
1:09:16
But I was just shocked because I was shocked >> once I possession possession's 9/10 the law.
1:09:21
Once I take possession of the steak, it's mine to do what I want with.
1:09:25
I think I should be able to distribute the steak evenly amongst the entire first class cabin.
1:09:28
I should be able to auction it off. It's mine.
1:09:30
I should be able to resell it on the secondary market.
1:09:33
Whatever I want to do with that.
1:09:34
>> It should be a stock expert.
1:09:35
>> Either you gave it to me. Yes. Yes.
1:09:35
This is what we're gonna do. We're gonna start.
1:09:38
We're going to vibe code an app that allows you to sell first class meals to economy customers and it runs on the JetBlue Wi-Fi. >> Okay.
1:09:46
So, credit to the flight attendant. >> Yes.
1:09:49
>> I It could be annoying if I'm distributing the the the plates and the the forks and the things like that around the plane. It's annoying.
1:09:56
Maybe maybe it's it's um it's frustrating to the other other other clientele.
1:10:00
Uh but I I was more on your side.
1:10:03
So, anyways, I brought the gelato back to back to the front and I gave it to you. You ate it. You enjoyed it. It was great.
1:10:09
>> Um, but then after that, we looked uh we we did a quick deep dive on JetBlue and I got very concerned because JetBlue >> nothing more shocking than so so the real in a metal tube at 30,000 ft and realizing you're flying a penny stock >> basically.
1:10:27
So, uh, JetBlue is now trading at >> what's the ratio between, uh, between just like >> I was just going to say market bigger than Perplexity >> because I feel like Perplexity is like pretty solid.
1:10:41
>> Smaller than than Perplexity.
1:10:42
>> They're less than onetenth Perplexity. Oh, okay. >> Yes.
1:10:44
Uh, and their entire market cap is less than Mirram Marotti seed round. >> Wow.
1:10:51
>> And so, usually if I was going to get in a tube, a metal tube Yeah.
1:10:53
and fly thousands of miles.
1:10:57
>> I would trust Mera for sure.
1:10:58
>> I would I, you know, I'm starting to think, you know, optimize for uh market cap a little bit more on the provider.
1:11:06
But >> yeah, >> anyways, uh Joanna, CEO, welcome, welcome to come on uh anytime and get down to the TBP, gentlemen, and defend your first class policies.
1:11:15
I was talking to the flight attendant and I said, uh I'd like to speak to the manager.
1:11:20
I'd like to debate the manager because I don't think I'd like to debate the manager.
1:11:27
Don't you don't want to speak to the manager.
1:11:29
You want to debate the manager because they have rules.
1:11:31
They're going to pull out some rule book.
1:11:32
I want to go a level deeper.
1:11:34
I want to go from first principles.
1:11:36
Why do those rules exist?
1:11:38
>> I was thinking I was thinking, you know, that that company Pipe Dream. Yep.
1:11:42
>> They make tubes that are underground that you can transport goods.
1:11:43
I was thinking if you could create some type of advanced straw that you could run from first class, put it run it on the side and then run it back like telescopically like back to your boys in the back and then just feed them and use like high pressure air to to feed them little bites of steak through the back.
1:12:03
And so you could do this >> you could do this without anyone potentially anyone knowing about it. >> Yeah.
1:12:07
Passing back scraps to your boys is like the it's so American.
1:12:10
I was I was deeply offended.
1:12:14
Uh, and then it got worse because the flight attendant kept bringing different trays of snacks and remember when they brought the one tray of snacks and they're like, "Do you want any of these?"
1:12:23
And this was after the after the steak debacle.
1:12:25
And uh and we start taking them and we're clearly taking more and more than we need.
1:12:28
Yeah, just give us the entire tray.
1:12:34
>> And and I I asked I asked specifically I was like, "Can I bring these back to my friends?"
1:12:38
And she said, "Technically, yes, because they were for the whole cabin.
1:12:43
>> These snacks are are And then less than 10 minutes later, she brought some nuts that were that looked very nice.
1:12:48
And those you cannot bring pass the nuts back.
1:12:53
>> And uh >> but you can pass the chips back.
1:12:55
>> Anyways, very very frustrating.
1:12:57
>> Yeah, it was it was brutal. It was brutal. Anyway, we had some fun.
1:12:59
Um >> Ben Ben definitely said at one point, you know, we're flying with like 10 people.
1:13:06
Shouldn't we just shouldn't we just charter a jet?
1:13:08
And he made a good point. He made a good point. too.
1:13:11
Um well, you will have to get on Adio customer relationship magic.
1:13:15
Adio is the AI native CRM that builds, scales, and grows your company to the next level.
1:13:20
Get started for free at Adio.
1:13:22
>> Um Kevin Quac has a screenshot from LinkedIn.
1:13:24
He braved LinkedIn to bring us this.
1:13:27
Uh he says, "This is the funniest LinkedIn title.
1:13:30
From now on, people should only use LinkedIn like this." >> Great.
1:13:33
and Peter Celis over at Discord.
1:13:37
In the title of his LinkedIn, it says, "I have full purchasing authority over Discord's extremely large and lucrative cloud contracts, and I am presently leading their renegotiation."
1:13:48
Basically putting up a billboard, >> just getting exactly what you want.
1:13:50
I want to talk to the most senior person possible at every hyperscaler. >> Take me seriously. Great.
1:14:00
His username on LinkedIn is disgruntled. >> Disgruntled. Wait, Peter Salis.
1:14:06
>> And his title, if you go to the experience section, is personality hire. >> Personality. This guy's good.
1:14:10
Since you >> prior to this, he was uh vice president president of product at Snap. So, >> very cool. >> Good stuff.
1:14:18
>> University of Chicago. Fantastic.
1:14:19
>> Come on the show, Peter.
1:14:19
We'll do a Hoffman's connected to him.
1:14:22
Orton's been on the show a couple times. >> Do a live auction. >> Yeah.
1:14:25
uh with the hyperscalers >> and you should get on public.
1:14:28
com investing for those that take it seriously.
1:14:31
Multiasset investing industry leading trusted by millions. Is Discord out yet?
1:14:35
No, they're they're they're about to go public, right?
1:14:39
>> That's >> I think that's the story.
1:14:39
I I haven't been following too close, but big fan of Jason.
1:14:44
>> I I Yeah, I know Delian was saying like it was it was the wrong move, but uh regardless, love Jason and what he's built. Fantastic.
1:14:49
One of the coolest founder stories.
1:14:51
founder stories. uh went to a a college for like video game design I believe started an app sold that and then was building a video game built a uh League of Legends for your phone like a MOA and took that to Techrunch Disrupt and was demoing it was just like super into the
1:15:08
gaming world eventually got lucky with Discord and found the correct product market that scaled >> the the building games to >> put the KPIs in the orbit >> the building games to building dominant messaging platforms pipeline undefeated Slack Discord Uh, Paraclet in the chat says, "What kind of country is this? We can't even
1:15:25
We can't even pass back little stakes to our boys." >> I know. I agree.
1:15:30
>> He also says, "I love audio." >> Thank you, welcome. >> We feel the same way.
1:15:35
>> Good to have you here. Good to have you.
1:15:37
Uh, let's talk about Scott Woo.
1:15:37
There was a report about cognition.
1:15:39
He is replying or kind of subweeting the the coverage.
1:15:44
Uh basically 30 out of the 200 people that were acquired from Windsurf got laid off and then the rest got uh a buyout offer if you're not interested in staying on the boat.
1:15:54
You were on a ghost ship.
1:15:56
Now you're on the Titanic. No, not the Titanic.
1:15:58
You're on the you're on the uh >> Carnival Carnival Cruise Carnival Cruises.
1:16:04
It's uh it's a destroyer. >> Yeah.
1:16:06
You're on a battleship and uh everyone's got to be pulling in the same direction.
1:16:10
Everyone's got to be hoisting the sales on this gallion.
1:16:12
Uh, and so Scott Woo says, "People have asked about our culture and recent employee communications.
1:16:18
Cognition has an extremely performance culture."
1:16:20
And we're upfront about this.
1:16:23
This is Scott Woo's This is my Scott Woo impression.
1:16:27
We We are routinely at the office through the weekend and do some of our best work late into the night.
1:16:30
Many of us literally live where we work. That's true.
1:16:34
They have a house in uh in uh Silicon Valley somewhere and they a bunch of them live there.
1:16:38
Uh we know that people who joined Windsurf didn't expect to join Cognition and we're proud of how we work.
1:16:45
We understand it's not for everyone.
1:16:47
We gave our team the opportunity to decide.
1:16:49
We offered for all employees who joined via acquisition to opt into our culture with full clarity on what that entails.
1:16:56
We know that we will lose some strong talent in doing this, but we truly believe the level of intensity this moment demands from us is unprecedented.
1:17:07
While not everyone is looking for a culture like ours, everyone deserves respect and appreciation for their work.
1:17:13
Regardless of their decision, we accelerated and cashed out all four years of equity for everyone in Windsurf.
1:17:18
Even for the 85% of employees who didn't hit their one-year cliff and for those who opt out, we're providing an additional nine months of pay on top of this.
1:17:27
Uh this is just good guy Scott.
1:17:29
He's just doing everything right.
1:17:29
He's he's setting the bar high.
1:17:31
He's letting people know, hey, we take this really seriously.
1:17:35
We just don't want there to be a culture clash.
1:17:36
Look, >> if you got one of these out, if you got if you if you just went from >> almost acquisition from OpenAI Yeah.
1:17:45
>> ended up on the ghost ship through the Google deal, >> ended up at Cognition, got all your got got the full upside from the deal. >> Yeah.
1:17:54
>> Even if you had invested and then now you're at Cognition and realize I don't want to work as hard as everyone else here and you get the opportunity, you get nine months of pay to just walk away. >> Yeah.
1:18:04
>> Yeah. that person is there's there's going to be some people in that group that are >> totally I mean it's not it's not like the norm but there are definitely people who are like I was actually excited to rest and vest I was I was actually excited to hit the ping pong table you know I wanted to just be on the beanag
1:18:20
chair for a while and I wanted to kind of cruise and and have like a normal nineto-5 like there are people who who like that's what they maybe they maybe they maybe this was their third startup they're already got some liquidity they're doing great and they have a family and they're you you know, they they want to be a little bit more flexible, take more time off. And like
1:18:35
And like that's the beauty of, you know, the American labor market is you can kind of choose and pick your own adventure.
1:18:41
But that, you know, Scott wants to create a cohesive team, a cohesive culture.
1:18:45
He doesn't want this idea.
1:18:47
It's very tough when when half the team is staying up really late grinding and they love it.
1:18:54
And then the other half is like, I'm dipping out early.
1:18:55
It's I'm just awkward for everyone.
1:18:59
So, he's just saying, "Hey, like you're welcome to stay on the team, but you got to buy in or you got to bounce and go, you know, take your take your liquidity from the accelerated investing you got, take the nine months of extra pay and go find something that actually brings you joy. Go do your life's work."
1:19:16
So, I think this is well managed.
1:19:18
Uh, it seems like the comm's leaked prior to this. I don't know. I don't know.
1:19:23
Would it have been better if he posted this beforehand uh and just kind of own the narrative?
1:19:26
Maybe that would be the move because you kind of know that people will frame this poorly and so you get out and say, "Hey, I'm going founder mode.
1:19:34
I'm I'm I'm offering this buyout offer."
1:19:36
Because there are plenty of companies that have done these buyout offers before.
1:19:38
I believe that there's one major company, I forget which one, that has a standing offer at 247 every single day.
1:19:44
Like doesn't matter if you just joined.
1:19:47
I mean, of course, you can't just like join and leave immediately and get the buyout offer, but basically like you if you hit a cliff and they're like, "We'll reup you.
1:19:55
We'll keep you incentivized.
1:19:55
we're going to keep paying you, but like the buyout offer is always there for you to take some cash, go figure out what's next, find a better fit because we just don't want people who are just like hanging on to this job because they are like just hesitant about going somewhere else when they should just figure figure out the next thing. >> Yeah.
1:20:14
>> Anyway, you don't want to be losing sleep. Get a pod five Ultra. Go to eightsleep. com.
1:20:17
5year warranty, 30 night free trial, free returns, free shipping.
1:20:22
I got a great night's sleep.
1:20:22
I slept for eight hours last night and I think it's showing.
1:20:26
>> Didn't you say eight and a half? >> Something like that.
1:20:28
>> You put up some crazy numbers. I got a 95 last month.
1:20:30
I've been down >> in the dumps. I had a 45 Sunday night.
1:20:34
>> No, you're you're you're back in the game.
1:20:36
The energy's coming through.
1:20:36
You can feel it in the intro.
1:20:40
>> You're sleep is great.
1:20:40
Sleep inversely correlated with your voice.
1:20:45
>> The the more sleep you get, the more horse you will get from screaming into the microphone.
1:20:49
>> You can tell my sleep score by the by the intro. >> Yes. Exactly.
1:20:52
Skooks says after they put GLP1s in the water, being obese will be back in vogue, a sign of indomitable vitality and enormous wealth. >> This is not obese. This man is not obese. He is prosperous.
1:21:03
Prosperous and prosperity should be celebrated. >> Yep.
1:21:08
>> Uh love the cane, too.
1:21:09
>> It's a it's it's a wild our next move. Bringing back canes. >> Canes. Smart canes. It's going to happen.
1:21:15
A lot of battery life in a cane.
1:21:17
Plenty of room for a ton of batteries.
1:21:19
>> Uh lot that you can do with a cane. on device inference. GPT OSS. Run it on the cane. >> Run it on the cane.
1:21:28
>> The ultimate status symbol.
1:21:30
>> Does Nvidia make a narrow 4090 like a GPU that could be could be put in?
1:21:33
Maybe we just need to string together a bunch bunch of iPhone chips.
1:21:37
I really I really think building a smart cane might be a challenge.
1:21:41
I I don't know if you can uh I mean I guess the chip in the iPhone is probably small enough to fit in the cane, but you'd have to figure it might be it might have a thick part to the cane.
1:21:51
>> Well, yeah, you could make a very wide cane, right?
1:21:53
Almost like an elephant's, you know, leg.
1:21:56
>> That seems like not the vision I'm going for with the cane.
1:21:59
I want I want an aesthetic cane.
1:22:00
I want a cane that that doesn't jump out at anyone. >> You doubt.
1:22:04
Well, >> doesn't doesn't jump out at anyone.
1:22:06
>> We'll put Tyler on it.
1:22:06
Just just trying to build a smart cane using open source LLMs, please. Thank you.
1:22:11
Uh, and then when you launch the cane, buy a buy a billboard for it on adquick. com.
1:22:16
Out of home advertising made easy and measurable.
1:22:18
Say goodbye to the headaches of out ofome advertising.
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1:22:27
Let's >> one of our billboards been taken one of our billboards was taken down this morning uh after after a good run.
1:22:32
by by a state actor, do we think?
1:22:37
>> Probably >> probably some type of Yeah.
1:22:38
nation state >> hacker group, but >> or was it a false flag? You'll never know.
1:22:45
>> Zack uh Zack Prop noticed that uh that it had been taken down. I was very disappointed.
1:22:49
So, working on getting more up, Zack, we are on it.
1:22:54
>> Maybe maybe SF next time.
1:22:54
Maybe I don't know where else we should go. Probably Sanrope.
1:22:59
That'd make sense for a billboard. >> Abene. >> Abene would be good.
1:23:02
Abalene would actually be great.
1:23:04
Abalene would be the way. Audience of one.
1:23:07
I just want I just want Chase and Sam to see it.
1:23:11
Basically >> audience in two.
1:23:14
There's also a lot of people in Abalene that are just getting >> the billboard in Abene should just say it shouldn't even say listen to TBN.
1:23:20
It should say come on TBNN. Call in to TVPN Sam. Call in to TBPN.
1:23:26
We'd love to chat with you.
1:23:29
>> If we put that up, I think we I think we get him.
1:23:31
He'll he'll of course come on the Welcome to Data Center USA. >> Yes. Yes. Congratulations.
1:23:37
>> Ser and Jetty says, "I can't help but love every iteration of the Moon Swatch." >> Yes. What do you think?
1:23:43
>> Collaboration between Omega and Swatch.
1:23:46
>> Is that the same company?
1:23:46
Does Swatch Group own Omega? Omega.
1:23:48
I always listen to the James Bond pronunciation. The Daniel Craig. He says Omega. Omega.
1:23:56
>> Does Swatch Group own? >> Anyway, looks nice.
1:23:59
History of the Moon Swatch.
1:24:01
The moon watch was uh wor it was an Omega.
1:24:03
It was worn by the astronauts.
1:24:06
>> Same company watch group. >> Same company. Yep.
1:24:08
Uh very big, very big company.
1:24:10
Um so if you're not familiar with the moon watch, uh there was a there was a knockout dragout fight.
1:24:15
It was like the AI talent wars all over again in the 1960s to decide which company would send the watch to the moon on the wrist of the astronauts.
1:24:23
Uh everyone expected it to be Rolex. Omega won the contract.
1:24:28
The Omega Moon Watch went to uh went to space, went to the moon and came back and now is a celebrated time piece.
1:24:36
The the the ones that went to the moon are obviously in museums and the the the models from that year trade at a very high premium, but they but they issue new moon watches regularly and the Moon Swatch is something that's a little bit more I think affordable, certainly more rugged and uh has nice has a nice fabric strap.
1:24:53
So, >> will release Saturday, August 9th, and is priced at $400. Oh, okay.
1:24:57
And if you're looking for your own watch, go to getb bezel. com.
1:25:01
Your bezel concierge is available now to source you any watch on the planet. Seriously, any watch. You can get an Omega.
1:25:06
You can get uh something uh worn by Mark Andre. He's an Omega guy.
1:25:12
Uh little little bit of a >> Yeah, we clocked that.
1:25:16
>> We clocked that early.
1:25:18
>> Came out with an interview.
1:25:19
>> We were expecting on the wrist.
1:25:20
>> Yeah, we were expecting a graph diamond hallucination.
1:25:22
Maybe four of them ideally, but uh you know, he went with the budget option.
1:25:26
Yeah, >> but uh we'll get him.
1:25:28
He's coming on the show, I believe, tomorrow, and we will pitch him on picking up a couple graph diamond hallucinations >> with the pennies in his couch cushion.
1:25:36
>> He's got a lot of real estate.
1:25:37
Everybody's got a lot of real estate.
1:25:37
A lot of people I don't know what what's up with people just wearing one watch, especially allocators. >> Exactly. >> His caliber, right? Why stop at one?
1:25:46
>> I You've seen a couple people that wear a watch and then the Whoop band or a watch and then an Apple Watch or something, but why not why not four Daytonas? Anyway, something there.
1:25:55
Congratulations to Joe Weisenthal again on the absolute run.
1:25:59
Oddlots is the number one business podcast in the world and the number six podcast in the world uh after cold bloodooded from ABC News and Crime Junkie and the J the Joe Rogan Experience is sitting at number three.
1:26:15
Mick Unplugged Leadership Because Growth, which I'm not familiar with, is number four.
1:26:20
And the Daily from the New York Times is at five.
1:26:22
And and to be clear, this is not because uh we our our episodes of OddLots released yesterday.
1:26:30
It is because they got a profile, a a glowing profile in the New York Times on Sunday.
1:26:36
>> Yes, >> they're on a generational run. We love to see it.
1:26:40
>> The and Joe said the business category of the Apple charts is very funny.
1:26:42
It is funny because >> a lot of >> money rehab, uh, Andy Frisella, real AF, like a lot of like I think Jaco Willink is in the business category and >> it's very different than the OddLots stuff.
1:26:55
Like OddLots is like let's talk to an expert on the grain market and like let's see what's going on the yield curve.
1:27:02
Uh and it's very much listened to by uh by hedge fund folks and capital allocators and a lot of these other uh podcasts are listened to more by lifestyle entrepreneurs and and small business folks and they and obviously that's a much larger audience much larger addressable audience but it's good to see odd lots on an absolute tear.
1:27:22
Uh and Joe says okay going to stop with self congratulations but fun to be number one for what will be a brief moment. surreal week.
1:27:28
Also, one last thing, if anyone knows how I can parlay my 15 minutes into throwing out the first pitch at a cyclone game.
1:27:37
>> Um, I have no idea what the Cyclones is.
1:27:39
Is that some sort of Is that sports of some sort?
1:27:43
>> It's some I've never heard of this. >> Hi Affiliate. The Brooklyn Cyclones. >> Okay.
1:27:49
>> Hi Affiliate of the New York Mets.
1:27:51
>> This is So this is baseball. >> Yeah.
1:27:53
>> And that's the one with where you throw the ball and then you hit it with the >> Is this like a feeder team?
1:27:56
This is the one where you throw the ball and you hit it with the bat.
1:27:59
And there's like gloves, too, right?
1:28:00
Well, good luck to Joe throwing out the first pitch.
1:28:03
That would be great to see. Good content.
1:28:08
>> Uh Nikita says, "Things that will cause a user to churn. One, friends leave.
1:28:12
Two, product stops growing and becomes culturally irrelevant.
1:28:14
998 feed has a bug where it flashes.
1:28:18
999 bookmarks are not searchable."
1:28:21
You have to imagine uh Nikita's DMs are are potentially gnarier than than Elon's at the moment of thousands of his uh mutuals and friends messaging him every possible bug in the app.
1:28:35
I know we would do the same to Jacobe before he left.
1:28:36
I mean, I I was just talking about this, like we don't use the bookmarks feature, we use the shared groups feature to kind of track posts that we want to share on the show.
1:28:46
And I was like, I wish I could search across all of these, but I was like, I'm literally the only person that wants that.
1:28:52
Like, I'm the only I'm the only person whose entire job and career depends on this one niche feature.
1:28:56
And so, it's not even worth requesting.
1:28:59
I'll just figure out a workaround, hopefully scrape it out of there, and then make that searchable or something.
1:29:03
um because um I can I I can work on a workaround.
1:29:09
Um but yeah, fortunately friends have not left and X continues to be culturally relevant.
1:29:14
It's where news breaks and we saw that on full display with the Soho Pereique saga.
1:29:18
The entire thing played out on X.
1:29:20
Started with a post, wound up with everyone else chiming in on various posts.
1:29:25
Kind of ended with like us interviewing him live on a stream on X. It was very cool.
1:29:29
all within the X ecosystem.
1:29:32
You know, stuff stuff still happens elsewhere, but in terms of like where the tech conversation is happening, it's entirely it's entirely action.
1:29:41
And there's there's no there's no even close second.
1:29:45
Now I I do think it's interesting to see I want to get better at understanding like what what is the current thing on Instagram today and where what is the real community that is formed on various other platforms that are adjacent because I know some people that have grown accounts and uh and when I was big
1:30:06
on YouTube and really focused on YouTube uh I would notice things like we were talking to Samir uh yesterday about like different metas that devel develop and different themes and you you sometimes these break containment but a lot of times it's just just a story that that happens within the YouTube ecosystem. Somebody posts a video and then there's
1:30:24
Somebody posts a video and then there's a reaction to that video.
1:30:26
There's a whole cycle of news that happens within the YouTube system.
1:30:30
>> X still feels, you know, if you're generally interested in tech, >> it feels like a shared experience. >> Totally.
1:30:37
>> Whereas if you're interested in tech and you're on Instagram, Yep.
1:30:39
It doesn't feel like you're you have a feed that feels at all similar to even another friend that's like loosely interested in tech. >> Yeah.
1:30:48
I'm trying to think on YouTube the big the big discourse is always it's always about YouTube like uh Colin Samir really are at the center of the of the discourse on YouTube >> creator industrial complex. >> Yeah.
1:31:03
And I think a lot of that has to do with the fact that on YouTube, you have to have a YouTube account and you have to publish a YouTube video to have a voice whatsoever. >> Yeah.
1:31:12
>> Like anyone can show up on X and type out 280 characters, go viral, and be the main character, be the current thing, start a conversation, engage with that conversation, but the bar on YouTube for having a voice, like the comment section just doesn't rise to the same level as like a reaction video.
1:31:28
And so when when like when Mr.
1:31:32
Beast is embroiled in controversy, there will be other YouTubers like there was this the Mr.
1:31:37
Beastification of YouTube. This idea that Mr.
1:31:39
Beast had created this meta and then other YouTubers were copying it and it was all this like yelling at the camera and fast-paced editing and lots of like in-your-face highs saturation graphics popping up.
1:31:50
all this different stuff going on and and that entire that entire news cycle played out on YouTube and it was because there were commentary channels and cultural an anal analysis channels that that replied essentially but instead of it being like a quote tweet dunk like the the equivalent is like responding viral video >> another viral video responding to the analysis.
1:32:15
So someone put out so Mr.
1:32:18
Beast was on a tear and then other people were copying it and then somebody put out the Mr.
1:32:20
be obification of YouTube which went viral and then other people would respond to the Mr.
1:32:24
Beastification is overstated or it's not that big of a deal or it's it's even worse than you thought.
1:32:28
And so people will take the conversation in different ways but it moves much slower because if you're like, "Yeah, I want to do a reaction video." Okay, see you in a week. Right. >> Yeah.
1:32:36
>> Anyway, >> find your happy place. Find your happy place.
1:32:41
>> Book a wander with inspiring views, hotel grade amenities, dreamy beds, top tier cleaning, and 24/7 concier service.
1:32:46
It's a vacation home but better. Is that gong new?
1:32:48
This gong is relatively new, a couple months since our new studio.
1:32:51
Uh we do have another new gong over there that we haven't uh that we haven't actually uh showed anyone yet.
1:32:56
We and we got a completely new gong for the Figma IPO and we had Dylan Field hit it on the day of his IPO. It's a game hit. It's a game IPO gong. It will be retired.
1:33:07
It will hang in the rafters of the TBPN Ultradome.
1:33:11
And eventually this eventually this dome will be filled with gongs from historic technology moments.
1:33:20
>> And uh we're going to give the Computer History Museum a run for their money.
1:33:23
They might have Commodore 64 or whatever.
1:33:26
They have the They have the original like touring machine.
1:33:27
It's like this it's this computer that you crank.
1:33:32
It's like the craziest thing.
1:33:32
And it can do calculations and has like it's it's literally no electronics and it's a computer.
1:33:37
It's like it's all just like basically like marbles flowing around. Not really rig. Yeah, dream rig. Imagine posting on that.
1:33:44
Um >> but uh we're gonna give them a run for our money with our gong collection.
1:33:50
>> Anyway, uh what's up with Labs has a new launch today.
1:33:53
Can we pull this video up sometime?
1:33:56
>> Yeah, I want I want to listen to the 11 Labs music.
1:33:58
>> They're saying 11 music is here.
1:33:58
Created with leading labels, publishers, and artists.
1:34:01
It lets you craft studio quality tracks with control over genre, style, and language using just text.
1:34:07
built on licensed cataloges.
1:34:07
Every song you create is cleared for commercial use. That is pretty insane.
1:34:11
I had an eye openening moment probably two years ago at this point.
1:34:19
>> Uh one of uh I enjoy the music of the rapper Gunna. >> Sure.
1:34:24
>> And somebody made an entire a Gunonna album that was entirely AI generated. >> Was it good? >> And it was solid.
1:34:31
>> It wasn't necessarily I I I listened through it a couple times.
1:34:34
You could if you paid it if you were not paying attention to it, it sounded just like a regular Gunonna song album.
1:34:43
>> Did any of those Was it on Spotify?
1:34:45
>> Uh I I think they published on Spotify, but I >> did any of those Did any of the songs migrate over into a playlist >> for me?
1:34:53
You're saying uh consider like crossing the chin would be like it's in your liked feed or it's in your it's in your playlist.
1:35:00
Spotify's in an interesting place here because you're one way to piss off artists is allow people to generate AI versions of the same artists and the artists are losing revenue.
1:35:11
And I knew a team a friend that was working on on basically Spotify for just AI generated content.
1:35:18
>> They uh ultimately pivoted because they didn't feel like they wanted to withstand decades of lawsuits.
1:35:22
Um but it sounds like 11 Labs has found a solution here. Let's play this video.
1:35:29
>> Yeah, let's play the video.
1:35:30
Let's see what they have to they have to say.
1:35:32
Hopefully we don't get copyright strike.
1:35:34
I think we should not because this is the first time this music has existed.
1:35:38
Okay, so we got some orchestral music. It's pretty epic.
1:35:47
I told the founder to make us a WWE theme song.
1:35:51
A really aggressive over the over the top uh track for us.
1:35:54
This is This is not quite our vibe, but it's nice. It's nice.
1:36:03
>> Okay, this is definitely past the uncanny valley.
1:36:06
Like, this could just be a real song, and I would This is hidden. >> I'm digging it. I'm digging it. >> Okay, let's see. Did they do any Ghana? >> Okay. Okay.
1:36:21
You got some fast pace, a >> little elevator coded, but I'm getting What else we got?
1:36:30
[Music] >> Their customers must just love like falling asleep. >> Reggae.
1:36:39
Yeah, this is pretty cool.
1:36:44
>> Give me some heavy metal.
1:36:50
>> Feel the pulse every >> It's pretty sick. I like this one. This is epic. I want this song. I I'm sold now. Oh, this is good. It's hit. >> That's great. Get me that track.
1:37:08
>> I want I I I want >> Get me that track.
1:37:10
This is a good time to talk about So, last week the Panama playlist came out.
1:37:13
John and I were featured in >> uh we were uh targeted by the Panama Playlist. If you go to panopplay.
1:37:20
com, uh they basically scraped a bunch of people's without them knowing and then published their >> playlists.
1:37:28
Uh I was wondering, I was looking at this playlist and I I didn't immediately have a memory of it.
1:37:32
It the playlist was called No Cap and I was like, why would I name a a uh a playlist that and it took me a second to come back to me.
1:37:42
It's because >> uh I was collecting songs, rap songs with obscure references to venture capital and investing >> as one does. >> As one does.
1:37:52
And so uh if you look at the first song, God Did >> Clearly for a Party Round drop that never happened.
1:37:59
>> Never h never happened.
1:37:59
But first song God Did uh DJ Khaled or one of the other rappers on the track says I'm at the cap table.
1:38:06
What the splits is, not that cap table. Boy, we live this.
1:38:09
And uh then you have okay Kanye West price went up angel investor um >> and uh anyways bunch of other random random references but uh it's all making sense now.
1:38:26
>> What else we got John?
1:38:27
>> We got GPT5 news uh on Poly Market.
1:38:27
GPT5 released by August 10th is now sitting at 92%.
1:38:37
It was sitting at 75% yesterday, earlier this week, 80%.
1:38:41
Uh, and so that's the end by the end of the week.
1:38:43
Uh, there is a 92% chance that GPT5 is released.
1:38:46
Um, and it it has moon recently.
1:38:51
Just back on August 3rd, it was sitting at 31% chance.
1:38:58
So, it has just in two days gone from 31% to over 92%.
1:39:00
So, people are definitely expecting GPT5 to be released uh in the next 5 days, which should be exciting.
1:39:10
I'm sure there'll be lots of coverage, lots to talk about, and we will want to hop on with as many as many legends, as many uh as many met list AI researchers as possible to get the to get the deep dive. >> Um, >> absolutely.
1:39:25
>> In other news, uh, flying private is the new wealth yard stick.
1:39:28
I know our audience is going to want to know about this. We talked about Joe. >> Is this news? >> This is news. >> Is this new news?
1:39:35
Is this >> people hearing about this for the first time?
1:39:39
>> But I love this because do you know Max Tuning?
1:39:42
>> He started a gummy candy business, sour candy business.
1:39:44
He sold it to Hershey for $75 million.
1:39:46
I just love the name, Max Tuning with two X's. It's like a great name. Uh so he was a YouTuber.
1:39:51
He started a sour candy business, Sour Strips, and just grew it and grew it and grew it and wound up selling it for 75 million and did very well.
1:39:59
Uh but the first thing he did before buying a Rolex or a dream home was a private jet for his wife and six friends to veil on a Desult Falcon 900.
1:40:07
They skipped security lines, zipped straight to the runway, and seated themselves in leather recliners with gold accents in the wood paneled cabin.
1:40:16
The price tag for this adventure, $100,000, worth every penny.
1:40:21
Tuning's golden doodle, dude.
1:40:21
This guy is phenomenal with the names. Love it.
1:40:27
>> Uh sprawled at their feet.
1:40:27
The joke is I had to get a private plane so I could bring my dog, the 35-year-old said.
1:40:32
I didn't really care what the price was.
1:40:36
The ultra wealthy have always enjoyed flying private.
1:40:38
That exclusive club is growing as soaring stocks and crypto prices mint more millionaires and billionaires who now have a range of choices to book a seat on a jet.
1:40:45
And you know the best part, he can give the stake to his dog if he wants because he's flying private, baby.
1:40:51
Doesn't have to deal with the draconian rules of JetBlue Mint.
1:40:56
Um, flying private has become the ultimate luxury splurge for many wealthy individuals, surpassing Ferraris, Hermes, Birkin bags, topping $14,000, or even waterfront Hampton homes, all the above, >> which we recently learned are very interestingly priced where property in the Hamptons is somewhat reasonable.
1:41:13
you know,510 million dollars might get you in the game, but renting a house in the Hamptons for a single month during the high season, $250,000, right? Something like that.
1:41:26
That's what we're saying. >> Very expensive.
1:41:27
And and and the the rental rates are are so extreme because you really only want to be there.
1:41:33
>> You only want to be there during summer, the hot season, >> when Emily Sunberg will be out there.
1:41:36
Uh for many of those aspiring to join the ranks of the truly rich, having private jet money is the new goal.
1:41:44
dividing the 1% from the 0. 1%.
1:41:46
The pandemic unleashed a burst of demand and providers say popular culture has turbocharged enthusiasm and envy for the fly private lifestyle.
1:41:57
Social media has given let me swift >> in the chat says uh his friend flies their dog private solo.
1:42:05
Well, we talked about on the show earlier a dog that flies private alone because the owner uh signed a contract to do the interior design for the private jet and as part of the deal their dog gets to fly priv.
1:42:24
We were laughing about >> one of the worst deals >> about like what if you want to get to, you know, New York to Miami and the dog wants to get to LA and you have to do a layover at at Van N to get to Miami because the dog has to fly private.
1:42:37
Um, but uh the younger people are getting a glimpse into the lives of jet setters.
1:42:43
Whether it is a model flying with friends to a bachelorette party in Los Cabos, Mexico, or a hedge fund manager hopping a plane for a birthday in St. Barts.
1:42:54
Realistic expectations are in or in order.
1:42:58
It's my dream to fly private, said a user on a Reddit forum for so-called Henry's, which refers to high earners not rich yet.
1:43:05
I think that's everyone on our team.
1:43:08
Uh adding that he earns about $300,000, is married, and has a kid in daycare.
1:43:13
Definitely closer to broke than flying private. Another user responded. >> Moged.
1:43:20
>> Yet the number >> Henry the Henry term emerged during the DTOC boom.
1:43:24
>> Never heard of that before.
1:43:24
that whole era where >> a lot of DTOC brands were kind of looking at their customers as people that weren't necessarily going uh head to toe Laura Piana but they would >> you know maybe buy flex up and and get you know an item or two or or buy some away luggage that that whole thing >> buying a Clydesdale not a thoroughbred that type of money.
1:43:49
>> Yeah something like that.
1:43:49
Uh, I mean the rain that I I I did a deep dive on like the horse market recently and the uh as one does and the uh the the spread between the cheapest horse and the most expensive horse is staggering.
1:44:01
You can spend millions or you can spend just a couple thousand dollars.
1:44:05
So no excuse not to have a horse one horsepower.
1:44:08
What's my how much power do you need >> at least?
1:44:11
>> The US added more than a thousand millionaires every day last year on average according to UBS.
1:44:15
The billionaire club grew more than 50% between 2015 and 2024.
1:44:20
Private jet hours flown touched a high in 2022 and then have stayed elevated since.
1:44:26
According to data, uh travelers can now use apps to snag individual seats on private jets or pay for flights by the hour.
1:44:33
Others charter flights, paying for just the occasional trip from New York to Miami.
1:44:39
While there are rare business moguls whom who might spring for the entire jet, some jet providers accept payment in crypto, shrimp, cocktails, and facials.
1:44:47
Ken Reachi, a pilot and chairman of Flexjet, a private company, said the frugal, wealthy, high earners who don't typically splurge, started spending big on travel during the pandemic because of health concerns.
1:44:58
Many of them have found it tough to go back to flying commercially.
1:45:00
Yeah, because of the JetBlue rules. We know this.
1:45:03
uh and years of economic growth have helped ease the stigma around conspicuous consumption that's set in after the financial crisis.
1:45:10
It's invogue to be wealthy, he said.
1:45:13
Sometimes we love the rich, sometimes we hate the rich.
1:45:16
It isn't just avoiding the security line or the hoy paloy.
1:45:18
The flying private means trading bisoff cookies, which were also given to us on the JetBlue flight for freshly baked ones and packing lunch with such items as shrimp cocktail and filet man from menus spanning a dozen pages.
1:45:31
Chef Nou Matsu Matsuhisha Heisa crafted a menu for Vista Jet that includes miso salmon.
1:45:40
Some cabin hosts are trained to give travelers facials 40,000 ft above the ground with do Dr.
1:45:45
Barbara Sturm's line of luxury skinare. >> Very nice. >> Anyway, fly private. Stop making excuses. >> More excuses.
1:45:56
>> Uh we had a >> breaking news actually.
1:45:57
I I made us a song on 11 Labs. >> Yeah. Yeah.
1:46:03
Can we play it on the stream? >> I think so. I think it set up.
1:46:06
>> Let's hear the song from WWE style >> and code where pitches rain and valuations grow.
1:46:10
Brace for the venture showdown. >> Let's go. >> Wired for disruption.
1:46:17
Seed rounds come am works.
1:46:24
>> I don't really know what you're >> I'm not into this. No. Go do some research. Go do some research. >> Shut down. >> Shut down.
1:46:32
>> Shut down by >> No, no, no.
1:46:33
The whole point of the WWE intro is that is that it it it has no words.
1:46:38
>> It's it's purely instrumental.
1:46:40
>> So, so, so look up look up some WWE intros because it's meant for the announcers to speak over it.
1:46:45
And so, I'm sure you can just prompt it and say no words, but also like the words are going to be the hardest thing to get right because it's it's like telling jokes.
1:46:54
It's it's it's creative writing.
1:46:54
It's very very difficult for the models to get that right.
1:46:57
Um, obviously amazing work by 11 Labs, very convincing, but we got to do some work on prompting this one's >> Yeah, go back to it.
1:47:05
I don't I don't want I don't want any of that cringe like rap. >> Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. And and and Yeah.
1:47:10
And and and the and the abstract like chat compression of uh of the concepts that we talk about. >> Good.
1:47:16
Good effort though, Tyler.
1:47:19
>> And impressive that it was able to be turned around so quickly.
1:47:20
This isn't something that cooks over >> before we before we go into the next story.
1:47:23
Uh funny story from earlier this year.
1:47:26
We were flying back uh from uh a trip and our and uh we're joining a buddy, friends of the show on their jet. >> Yep.
1:47:36
>> And the morning of it was a super uh early flight.
1:47:40
We didn't text him to remind him that we were coming.
1:47:43
And so we got to the we got to the the terminal, got on uh the golf cart.
1:47:47
We're driving out to to the plane and just watched it take off.
1:47:53
No, we didn't watch it take off. It was taxiing.
1:47:57
>> It was t We watched it taxing.
1:47:57
I thought I thought >> No, no, no, no, no.
1:48:00
It didn't It didn't leave the ground.
1:48:03
>> Oh, we got out of view from it, so I thought it left the ground.
1:48:05
>> No, no, it didn't leave the ground.
1:48:05
It was But it was running down the runway.
1:48:09
>> It It was on the runway taxiing stuff.
1:48:11
It was not It was not active.
1:48:13
>> I thought it had turned around. >> I don't know.
1:48:14
But either way, they turned the plane around for us.
1:48:16
It was the nicest thing anyone's ever done for me. >> We felt really bad.
1:48:19
>> If I If I ever go on the best, what's the nicest thing everyone's done for you?
1:48:22
Turn around the PJ for sure. That's up there.
1:48:26
>> Uh it was it was mortifying.
1:48:26
It was uh it was a low point, but then the rest was fantastic. It was fantastic. We had a great time. Learned a lot. >> It was fantastic.
1:48:34
>> We are forever >> indebted. Yes.
1:48:35
Anyway, in other news, the New York Post is launching the California Post.
1:48:41
>> Uh the New York Post goes to Hollywood plans to launch plans launch of the California Post daily newspaper.
1:48:44
uh New York Post, you probably know them from their hilarious and wild uh front page uh uh what do you call them? Just like headlines.
1:48:55
They write really great great headlines with like these hilarious puns.
1:48:58
And so they are going to come to California and launch a uh daily newspaper which of course will probably be instantiated on the web very seriously.
1:49:08
But um they call it the new venture.
1:49:11
Uh they're bringing the signature highbrow low mix uh high high lowbrow mix of content that the New York Post is famous for alongside fearless common sense journalism, celebrity entertainment news, worldclass sports reporting and legendary covers.
1:49:25
Uh >> we got to get we got to start getting the California Postend covered.
1:49:31
>> Yeah, I'm very excited for this.
1:49:31
You know who founded >> Post? I don't. Who?
1:49:35
He uh happens to be a founding father really of this country. Alexander Hamilton. >> Wait, what? >> Yes. >> You're kidding me. >> Yes.
1:49:45
>> I thought you were >> New York Post was founded in 1801 by Alexander Hamilton, a founding fathering >> George Washington appointed as the nation's first Secretary of the Treasury. >> Wow, what a story.
1:49:54
Uh we we we have our next guest, but uh in other media news, uh Barry Weiss is apparently looking to sell the free press for $250 million.
1:50:04
I'm going to hold off on ringing the gong until it's confirmed.
1:50:06
We're all rumors, the rumors actually come from the New York Post.
1:50:09
Um, but this would be a fantastic outcome for a new media company that's only something like four years old.
1:50:16
Barry Weiss left the New York Times opinion page.
1:50:18
Uh, there was a huge dust up that's that happened in uh 2022 and she's reportedly met with Skyance Media CEO David Ellison and at the high-powered Allen and Company summer camp for billionaires.
1:50:31
and Ell and David Ellison is the son of Oracle founder Larry Ellison and he's apparently reportedly interested in buying the free press as Sky Dance continues.
1:50:41
>> We I think originally covered this briefly when they were meeting at uh Allen and Company's uh event earlier this month or I guess earlier in July. Yes.
1:50:53
>> This screams like talent acquisition as much as it does >> Yeah.
1:50:57
Barry Barry is traditional >> hair and she Yeah.
1:50:59
is a she she does the she leads the podcast interviews and brings great guests on and she writes but then they also hi they also have gotten a bunch of great people on the team.
1:51:09
Uh Tyler Callen has a column at the free press like like that was the that was the thing that got me to subscribe >> because I love Tyler and I was like I want to see what he has to say and I don't want to like it's paywalled so I have to pay.
1:51:22
Um, and so she's been very good at at at like hoovering up talent, building this thing, and and they publish a ton when you go to the the the free press.
1:51:30
Uh, you just see tons of articles, all sorts of stuff.
1:51:31
Uh, just today I was looking at the free press's homepage.
1:51:34
They have a basically an op-ed written by Palmer Lucky.
1:51:36
Like they got Palmer to write about his thoughts in the Free Press.
1:51:41
And I thought it was just like that's the example of like great great uh written written work.
1:51:46
Congratulations would be able to help make CBS relevant again even if she was continuing to run the free press.
1:51:52
>> Anyway, anyways, without further ado, we have Alex Albert.
1:51:55
>> Alex, welcome to the stream.
1:51:55
Thank you so much for joining on short notice. Great to meet you. Great to have you. How are you doing?
1:52:01
>> Great to meet you guys.
1:52:01
Very excited to be on here.
1:52:02
And I'm hoping you hold on to that uh that mallet so we can get a gong ring in. >> Give us some news. What you got?
1:52:09
>> We went from >> Yeah, it's Oh, go ahead. >> No, you go for it. >> Yeah. Yeah.
1:52:13
I was going to say it's an exciting day.
1:52:15
Uh we dropped Claude Opus 4.
1:52:17
1 just about three hours ago.
1:52:20
>> You got to give us a number. How many parameters?
1:52:21
How much money do you spend on the thing?
1:52:24
>> I can give you a sweet bench score. >> Okay. Yeah. Give me a bench score. >> How is it. 5? >> Congratulations. >> Thank you. Thank you.
1:52:33
It's been a very very exciting week.
1:52:36
Uh we're shipping like crazy.
1:52:37
A lot of stuff happening.
1:52:37
Um don't know how you guys are even keeping up over here. Oh, it's it's amazing.
1:52:44
It's Yeah, I mean, we've been talking about streaming for seven hours a day.
1:52:47
We'll we'll get there eventually.
1:52:49
Fortunately, 3 hours is like just enough to barely cover scratch the surface of what's going on in tech.
1:52:53
Uh talk to me about where this fits into the rest of the landscape.
1:52:57
There's a ton of stuff going on in open in uh in anthropics world uh from cloud code, different consumer models, open there's so many different projects. How does this fit in? >> Yeah.
1:53:08
So this is our best model yet for just general capabilities and intelligence really really is pushing the frontier on all sorts of agentic reasoning coding tasks.
1:53:16
Um back in May we kind of hinted at the launch of Cloud 4 that we want to get on a more continual release schedule with our upcoming models and this is kind of our first step towards that vision of now being able to ship models faster and faster to our customers and end users. >> Yeah.
1:53:33
One of the narratives that's kind of stuck around with Claude for a long time is this idea of like the vibes just being really good and yeah it does great on the benchmarks but it's just like fun to talk to.
1:53:43
People like the way it talks but uh at the same time Anthropic's been fantastically successful in the business context.
1:53:50
Is there an important overlap there?
1:53:52
Like are you hearing from business customers that the vibes being good is driving bottom line results? Well, yeah.
1:53:59
More so, how much do developers care about vibes versus just raw?
1:54:04
>> It seems like developers are the only ones that can tell that the vibes are good, but but I'm always interested like how does that actually translate to like my bottom line if I'm an enterprise SAS company and I need to use a anthropic API for something.
1:54:15
Am I am I happy with the vibes or is that just kind of like a nice to have on top?
1:54:20
>> Yeah, I mean it the the vibes are kind of there's you can measure vibes in a lot of different areas, right?
1:54:24
So if you're a developer, you're measuring vibes in in the coding domain and how long of a task can these models complete?
1:54:30
Can you just let it go off aentically and work on your files?
1:54:32
Um if you're creating an application, you're enterprise that has end users and you're having those end users actually interact with the model.
1:54:40
You want those personality vibes to be uh pretty stellar.
1:54:44
Otherwise, you're just going to give a bad experience to your customer.
1:54:48
Um I think Claude has like a really wide range of things there.
1:54:51
And of course, we're known for kind of that natural feeling personality and we've done a lot of character work there.
1:54:56
We have some really great researchers on the team that focus on that.
1:54:59
But then on the other side of the spectrum for the developers, for those folks that are building agents, um that's where we really get into that that other type of vibe, which is, you know, how how long of a task horizon can these models operate on?
1:55:13
>> Is there a good benchmark for for task horizon yet?
1:55:15
We've heard baby AGI, 15 minute AGI, 20-minute AGI.
1:55:18
We've seen a lot of people like string these things together in but like in terms of like most consumer interactions I think the where where most people hit the interface of an LLM they feel like like 20 minutes is the kind of the upper bound of what the average AI user is experiencing.
1:55:39
Do can you tell talk to me about that?
1:55:42
Yeah, I mean I I do think uh LLMs right now have somewhat of like a jagged intelligence frontier where in some tasks of course they spike more than others.
1:55:51
Um for me personally when I'm trying to assess that capability in a model there's a couple places I look.
1:55:58
One is especially coding benchmarks.
1:56:01
>> Um these are really really important because often it's the model trying to complete a PR end to end.
1:56:05
So it needs to take a lot of actions.
1:56:07
It needs to call a lot of tools and modify a lot of files.
1:56:11
Um so things like sweet bench are actually like good proxies in some degree to measuring that.
1:56:18
>> Um there's also thirdparty institutions that are doing this research right now.
1:56:22
So one is is called meter their model evaluation threat research >> and they have that really nice that really nice line goes up graph of like plotting out the models and how long of a task they can do compared to a human developer. >> Sure.
1:56:35
Um, and Claude has always been uh pushing the frontier on that and I'm assuming uh once they get 4.
1:56:39
1 up there, it'll be be up and to the right as well.
1:56:43
>> Yeah, I mean we've seen like the in terms of the spiky intelligence like ArcGI is like the main thing that people point to as like a weird valley of capability because it seems like it should be obvious and and easy to do and yet it reveals something about the models.
1:56:58
Uh are there any are there any places in the coding world that are more specific where we're underperforming either just because we haven't focused on it?
1:57:08
I'm thinking about like like >> I imagine that most models are better at Python than for but but is that I is that an outdated take?
1:57:16
I is forran now just kind of like solved because somebody had just got all the training data together and RL done for and now we're good.
1:57:24
Yeah, I I definitely think there's still probably if you were to like take Sweetbench for example and you translate it into every coding language, I'm sure Python and and JavaScript, TypeScript would be totally uh ahead of the other languages.
1:57:38
But we are seeing especially with the cloud for models that they're able to handle a lot more of those like >> older languages or the languages that don't really appear as much in in the training data to a much better degree.
1:57:50
And that's through a combination of of things from RL to just general uh architecture improvements.
1:57:54
Um so we're we're kind of covering the bases with the models, but yeah, it definitely started in one way and now is expanding out.
1:58:03
>> Uh what what have uh reactions been to 41?
1:58:06
I'm assuming a variety of people got access to it, you know, pre-release.
1:58:10
What what are the areas that people are kind of most excited about? >> Yeah.
1:58:13
Um again, it's it's kind of those coding and agentic tasks have been really the star of the show here.
1:58:18
Uh what I think is interesting about that is that coding is kind of the proxy for allowing everything else.
1:58:25
So if you think about how a model actually interacts with things on a computer, uh everything can be done through coding operations.
1:58:32
So when we say coding, it's almost like a little disingenuous to just like narrow it to that domain.
1:58:36
Um, but some of our early customers that were playing around with 4.
1:58:40
1, Windsurf being a great example, in one of their benchmarks, they showed that from Opus 4 to 4.
1:58:47
1 showed roughly the same performance jump from sonnet 3. 7 to sonnet 4.
1:58:52
And this was like a real world junior developer task eval.
1:58:54
Um, so something that I definitely would pay attention to.
1:59:00
>> How are things going on the rate limit side?
1:59:03
side? have heard that like capacity is generally constrained for everyone everywhere all the time because we don't have enough data center obviously people are working on that but uh like I I guess like broad update on like how
1:59:17
things are going but then more specifically um like when you're talking to companies that are building on top of anthropic APIs are there specific strategies that you recommend to just embrace the realities of the modern AI era and capacity constraints. >> Yeah, I mean the rate situation is
1:59:36
>> Yeah, I mean the rate situation is something we're just continuing to iterate on and of course we have like very very smart people much smarter than I think about this problem in terms of building out compute and also working on making our inference just overall more efficient.
1:59:48
Um generally we want to provide the best experience we can to our customers.
1:59:54
So whether this is on the cloud code or through the API, um there's various things that we do whether it's like through our applied AI team helping our our enterprise customers with like their specific deployments or on cloud code making sure that our rate limiting system is fair and actually allows for people to utilize it as much as they can without rewarding people that might be like abusing the system and kind of detrimenting the other users.
2:00:16
Uh so it's really about like kind of monitoring and keeping it consistent so we ensure like great experiences for everyone that's trying to use cloud. Uh, what about pricing?
2:00:26
Is there a step up in in like cost associated with 41 versus 40?
2:00:30
What what does that look like?
2:00:34
>> Pricing is the exact same.
2:00:34
Uh, we really do intend for this model to just be like a drop in replacement for Opus 4.
2:00:41
>> So, if you're using Opus 4, you should just be able to to cleanly kind of switch over the model string and you're good to go. >> That's awesome. >> Yeah.
2:00:48
What are some of the weird use cases that you've seen for cloud code?
2:00:53
I've talked to some people that are like, >> "Yeah, >> like they because coding is kind of like an abstraction over like everything that a computer can you can do, they're coming to claude code with tasks that don't that feel more like just general like personal assistant agent stuff, but then it just writes a bunch of code." Um, are is is that real?
2:01:12
Is that is that something that it's more just like when you know you know when people do those like beautiful artworks in Excel where they like color every single cell as like pixels and it's like that you're not you're kind of abusing the tool here but it's still impressive or or is that actually like you know a glimpse into the future?
2:01:33
>> I think that is a glimpse into the future.
2:01:35
Um there there was a a tweet I posted a few days ago kind of asking the community for, hey, what's all the best non-coding use cases you're using Cloud Code for?
2:01:44
And it got hundreds of replies and really the answers kind of were super wide ranging.
2:01:50
Everything from like managing your own personal knowledge base, second brain on your computer, >> you know, maybe you have a ton of notes and text files to some folks are actually using it now for like video production.
2:02:01
So we have we have a guy on our team that uh >> uses cloud code and uses like an open source library to create animations and things for like all our product launches.
2:02:12
>> Which is just absolutely amazing.
2:02:12
I didn't even know that was possible.
2:02:15
>> Uh but it is kind of hinting at this thing that it's like well if you can control code you can really control anything that happens on a computer. >> Yeah.
2:02:21
>> So now we're moving into this like operating system abstraction almost.
2:02:22
Um and I think that's really the direction you're going to start to see cloud code heading in. >> That's awesome. Anything else, Jordy?
2:02:30
any any uh I'm I'm curious to get uh an update on it seems like a lot of the companies that we talked to.
2:02:36
You know, we were talking with uh Dylan Field the day of the IPO and he was talking about updates they're making with with M MCP.
2:02:46
What's going on uh in that realm?
2:02:46
Any updates while you're here on that front or or interesting use cases?
2:02:53
>> Yeah, I mean MCP's been absolutely just ripping lately.
2:02:55
Um the community is awesome and it's like really got to this point now where it's almost its own like self- sustaining thing uh where there's like meetups and gatherings that are being hosted completely outside of of like our facilitating and um thankfully we get to participate in them and that's just like been super cool to see.
2:03:14
>> Uh I think MCP is going to be a large part of like making sure this kind of agentic future goes well.
2:03:18
So if you can spin up easy integrations and connections to any service or any product or any internal application, all of a sudden you kind of um unhobble Cloud to some degree and you give it access to that knowledge that it needs to actually go out and do those correct operations.
2:03:35
Um so very excited about the team there and yeah, hopefully a lot more good stuff coming on the way there soon as well. >> Awesome. >> Very cool.
2:03:44
>> Well, congratulations to the whole team on the launch.
2:03:46
It's a massive day, massive week, and uh love to have you back on soon.
2:03:49
I'm sure they'll I'm sure 4.
2:03:52
2 will be right around the corner.
2:03:54
>> Oh yeah, lot more coming soon. Yeah, stay tuned. Have a good one. >> Cheers. Bye. >> Bye.
2:04:00
>> Up next, we have Scott Kapor from Andre Horowitz.
2:04:04
He was in the OPM business, the other people's money business.
2:04:09
Now he's the director of OPM for the US government, the office of personnel management.
2:04:13
Uh, welcome to the stream, Scott.
2:04:16
We are excited to talk to you. How you doing? >> I'm doing great. How are you guys doing?
2:04:21
>> We're doing fantastic.
2:04:21
Um, >> it's great to have you on the show.
2:04:25
>> I We're in a very funny era where more folks from Silicon Valley have moved over to the government and every time they do, I have to have them explain to me like I'm in the VC world what they do.
2:04:37
I think I learned about the OPM uh that like the entire office uh was a new term to me just a few years ago.
2:04:42
Explain the Office of Personnel Management to me.
2:04:47
>> You mean to tell me that you guys don't know what OPM is?
2:04:48
That is really disappointing.
2:04:50
I'm I'm shocked to hear that.
2:04:51
>> I probably learned about it about a year ago.
2:04:53
>> Explain it like I'm a venture capitalist that's about to write a thread.
2:04:56
Explaining it like I've always known about it and I'm an expert in it.
2:05:01
>> Yeah, my my wife asked me the same thing when I got appointed to the job.
2:05:02
So, I'm not surprised to hear that.
2:05:04
Hey, so really quickly, what it is is we are the talent management organization for the government.
2:05:09
So in in simple in our corporate VC terms, we would be the HR department basically for the company. >> Sure.
2:05:16
>> So our job is like make sure we have the best talent, make sure we have actual things like performance management standards, which by the way we don't have which we're working on.
2:05:23
Uh make sure we have the ability to you know kind of understand the employee base through technology which we don't have currently.
2:05:30
So but basically think of us in very simple terms as >> we would be the HR department inside you know any other you know traditional VC back company.
2:05:37
And and does this cut across all the other departments or are you like wh where where are the boundaries of your >> Yeah.
2:05:45
So um it's it's a hybrid is actually what it is.
2:05:47
So basically so like there's some stuff that we have exclusive province on.
2:05:49
So like I'll just give you a simple example like the president puts out a hiring an executive order saying >> we want merit hiring to be the standard in government which you and I can we can talk about that forever if you want but basically so he says look I direct OPM to figure out like what are the standards that we need to do cross government to make merit hiring a reality.
2:06:08
reality. So we will go put out a bunch of you know regulations and research it and say great okay now this is the law of the land for all the other agencies this is what we expect you to do and you know OPM will not formally approve and issue offer letters and stuff like that unless you guys do that >> so that's what we do and then but there are HR departments obviously in the different agencies and you know so think
2:06:28
of it as like you know in a company you might have like centralized HR but then you have like business partner HR that might sit in the sales organization or other stuff like that and they may be kind of you do things that are domain specific, >> but all the big things about like how do we recruit people, how do we train them, how do we actually manage them, you know, performance-wise, we will provide guidance for. >> Yeah. And sorry, Jordy. >> Yeah. And sorry, Jordy.
2:06:50
>> Yeah, I was just going to say like getting into it, what what what are your priorities first 90 days, 180, the year?
2:06:57
>> Uh I'm sure there's you you've uh like uh even any any >> you know, I'm assuming you're trying to bring in best practices that you >> simp mistakes. Yeah, exactly.
2:07:05
Just ask the model to do >> we're gonna make we're going to make some mistakes which is okay.
2:07:10
That's part of the problem by the way which is like we've been living in this environment where like you literally cannot make a mistake and so nobody actually tries anything.
2:07:16
So yeah, really simply there's three big things we're trying to do.
2:07:18
One is create a high performance culture in the talent.
2:07:22
Uh so in other words like we my simple goal is look we want like the best and brightest people to take government jobs but as you guys know look A players want to be around A players.
2:07:32
They want to be in a in an environment where they're held accountable where when people do well they actually get rewarded.
2:07:36
We have a very like tenure-based uh and conservative riskmanagement based system here in the government which is like you get power and you get promotion by having more people in your organization and a bigger budget and the longer you spend time in government.
2:07:49
So we've got to just flip that on its head and say look we're going to reward things like innovation.
2:07:53
We're going to reward I've been using the term measured risk takingaking because look we can't go just like literally throw stuff against the wall and see what works like we do in Silicon Valley. Yeah.
2:08:02
>> Um, but anyways, that's thing number one.
2:08:03
So, like goal is how do like all the smartest people in the country feel like coming to work for the government actually is great for them.
2:08:08
They learn stuff and they'll they'll go get they'll get paid for that in the private sector.
2:08:13
>> Number two is we've got to make operational efficiency like a core tenant of government.
2:08:17
So, again, I know this sounds crazy coming from, you know, the world that I know you and I came from, but today basically um there's no incentive for efficiency.
2:08:24
So, uh, again, you need to like bake it into people's performance plans and say like your job every day is are you doing a great service on the behalf of the American people and are you constantly like turning the crank to figure out how do we use technology?
2:08:36
How do we, you know, use AI to do stuff?
2:08:38
How do we like reorg to do things?
2:08:40
Again, because >> spend less money, >> spend less money, right?
2:08:43
Today, again, right, I mean, it's the exact opposite incentive, which is more money means more people means more power, right?
2:08:48
And so, like everything we have to do is yes, spend less money to deliver a better service.
2:08:53
And so we've got a ton of like technology initiatives that we can talk about there.
2:08:57
And then the final thing we want to focus on is we've got to make like we've got to anticipate what living in an AI first world looks like for government and we got to not be flatfooted and realize that we have none of the talent we need and we don't even know what the jobs are.
2:09:10
So this is I think a huge opportunity quite frankly where I think we should work with the private sector and say great you guys understand what AI is going to do.
2:09:16
Let's figure out ways where we can have information sharing even like quite frankly swap employees back and forth but find ways so that we don't wake up five years from now and realize there's all these new jobs that are being changed andor augmented by AI and the government is not like you know figuring out how to actually get that talent into the government.
2:09:36
>> Yeah, you mentioned spending less money.
2:09:38
>> I want to know about the potential of spending more money.
2:09:41
spending more money. uh is there is is there a world where we remove salary caps on government employees like you you've seen this in Silicon Valley there's not like you know obviously founders are very driven but they have uncapped economic upside like the venture capitalists have uncapped
2:09:58
economic upside in so many ways the AI researchers that are getting poached like it is just moneyball at the end of the day for a lot of sectors of the economy is there a reason why the government is fundamentally structurally different or do you think that we uh just need to make a better pitch for civil service? >> Yeah, I I think it's a little bit of
2:10:17
>> Yeah, I I think it's a little bit of both. So, okay.
2:10:19
So, look, we're never going to solve we're never going to solve like the ultimate like uncapped upside pay gap between the public and private sector.
2:10:26
And look, that's just, you know, politically that would never work.
2:10:28
You know, we're not going to, you know, like you know, we're not going to have a Zuckerberg equivalent of like paying engineers a billion dollars a year, right? Yeah.
2:10:35
>> But we can do two things.
2:10:35
One is we can change the compensation structure so that yes, like a players actually get rewarded.
2:10:40
So I'll give you a very simple example here.
2:10:43
>> Everybody gets ranked one through five at the end of the year in their performance evaluations in government.
2:10:47
Five's the highest, one's the lowest.
2:10:49
>> 70% of the people get ranked a four or five.
2:10:51
Okay, which means like they're awesome.
2:10:53
They're doing outstanding work. 0.
2:10:55
2% of the people get ranked a one or a two.
2:10:57
Now again, mind you, this is across a population of 2.
2:10:59
4 million people where at a minimum you might expect a normal distribution, but like there's just no way that 70% of the people are above average, right?
2:11:06
Unless you're in, you know, Lake Wagon basically.
2:11:08
So we got to solve that problem and then if you solve that then the incentive structure can follow it right because again a typical government employee gets 0.
2:11:16
government employee gets 0.5% of cash bonus at the end of the year that's because again there are too many people highly ranked and the delta between low and high is like you know 50% or something right so what I'd like to do is say
2:11:30
>> you ought to have many fewer people ranked to four or five and let's give those people like most of the bonus pool for example so we can't solve all the problems but like we can solve that and then your your other point is a really good one which is we got to change the pitch. So again I'll give you a story
2:11:41
So again I'll give you a story here.
2:11:43
When I first came in one of my one of the employees here said the pitch that we use for government is job stability basically. Like that's the pitch.
2:11:51
>> And I was like I'm sorry to say but like unfortunately I think somebody's been lying to you because like there's no job in the world where we can guarantee job stability for people even in the government.
2:11:58
government. To me the pitch has got to be you can see things at a scale and solve really hard complex problems and yes like you can you know do a public service as well but we've got to get people excited about like you know you know putting people on the moon or all the things that you know guys like Elon do you know it's the whole like founder story of like what's the mission of the
2:12:16
organization the mission of the organization cannot be we provide job stability so um we've got to like tell that story and we got to go tell it on college campuses and we got to go like show it and look people don't have to commit their life to being in government but if you could come here for two years and work on really hard, really cool problems and you could actually advance
2:12:32
in the organization because you're not tenure limited but you actually are skills you know uh you know you're awesome at skills we should be able to promote you faster like there's no reason why we can't compete for really smart people in that environment and then again go take that skill set and go work for you know Elon or go work for Zuckerberg and get paid a billion
2:12:49
dollars a year after that like you can do both things so we got to sell the story >> yeah I was talking to a friend who had some experience in China and he said that the the main difference that he noticed was that the really really top performers over there just kind of got sucked into government work and uh he was kind of framing it as like it wasn't exactly optional for them. Uh and I know
2:13:09
Uh and I know that uh that's not on the table here.
2:13:11
We love uh freedom and choice and >> we kind of decided long to that we actually like democracy is actually a good thing, right? Yeah. >> Yeah. Of course.
2:13:18
Uh but I I guess my question is like is like should I I know that like when the when the administration changes over I mean this happens every four years now eight years most uh there's there's a push to bring in new folks and there is some recruiting that goes on and and there's uh like whisper networks of uh who's really talented and let's make the pitch to them that maybe now's the time to go and and and serve your country.
2:13:40
And a lot of people do swing at that pitch and they and they take it and some of them do very well with that.
2:13:46
Um but should it be more aggressive?
2:13:48
Should have should recruiting be be 10 times bigger in terms of just every talented founder, engineer, venture capitalist, anyone who's high agency, high intelligence, high EQ is at least hearing the pitch for where they would fit in in the US government because I think a lot of people I know a lot of people that got calls.
2:14:10
I know a lot of people who are talented and didn't get calls and I'm wondering if we should have reached them with something. >> Yeah.
2:14:15
And it felt like at the beginning of this year and and maybe the end of last year was just recruit Doge was just dominating recruiting.
2:14:23
>> It's a fantastic recruiting engine. >> Yeah. Yeah.
2:14:25
But I didn't I didn't see that.
2:14:26
I didn't hear like oh I have a a fintech founder who you know they they were great but they got kind of clobbered and now like the IRS is calling them.
2:14:34
Like I didn't hear that story that often for example. >> Yeah. So yeah.
2:14:37
So let me try to just unpack that a little bit because so first of all you're absolutely right. We should 100% do that.
2:14:41
So there's there's a problem we have today which we which we are working on fixing which is today believe it or not um you can actually there are weird hiring procedures in the federal government which makes it very hard in some cases literally to hire people based on their skill skill assessment.
2:14:56
So let me give you a great example.
2:14:58
So people have gotten really good at we put a job description up on this thing called USA jobs which is basically the the website and people essentially tailor their resume to exactly the words that are in that job description and the filtering process puts them at the top of the list but it's all selfassessed stuff.
2:15:14
We we literally like you could hire an IT network administrator in the government today and not have a technical person interview that person to see do they know like what like you know HTTPS means basically.
2:15:26
Um, and the good news is we just actually part of it is because like people are worried about, okay, is it are those tests discriminatory?
2:15:33
We actually just had a good legal ruling the other day that clears the path for this.
2:15:37
But believe it or not, literally like we do not have skills-based assessment for many jobs in the government.
2:15:42
So the the way to so like it's just really hard it's really hard for those people to come in.
2:15:47
Um, we but you're absolutely right, which is look, the real solutions problem is we got to do both.
2:15:52
We got to fix that piece and then we have to literally go tell the story.
2:15:54
Like I don't think this is the solution.
2:15:56
We're not going to do TV commercials like, you know, the Army and Navy and, you know, we need a few good men basically, >> but we need something like that.
2:16:01
We got to go tell the story.
2:16:02
And you're absolutely right, which is I I would bet there are I don't know.
2:16:06
I bet there's thousands of data scientist jobs open across the government today.
2:16:10
You as an employee, if you're interested in that, you should just be able to apply once and we should then send your resume to all thousand of those jobs.
2:16:16
Like we don't even do that today basically.
2:16:18
So like you literally have to go find out where those thousand jobs are.
2:16:21
So there's all this stuff that again it's not they're not bad people.
2:16:24
It's just that the system has not been set up for that goal.
2:16:27
The system has been really set up to say, let's really be conservative.
2:16:31
Let's really be kind of, you know, careful on these things.
2:16:32
And we just we have to change that paradigm. >> Yeah.
2:16:35
It feels like we're fishing with a really large net.
2:16:38
You know, you put up a big ad, we need a few good men and whoever gets caught in the net comes into the organization.
2:16:43
And we need to get some harpoons out and go find the really like laser focused people for the perfect job that will thrive.
2:16:51
>> The military, you know, it's been interesting.
2:16:52
I I think things have changed, but there was a period where military recruiting, to my knowledge, was was really really tough.
2:16:57
And that's still with a lot of a lot of people that do end up joining having been marketed to and and and and kind of exposed to Army, Navy, Marine Corps, Air Force since they were kids, right?
2:17:09
But nobody's getting nobody most most Americans wouldn't know.
2:17:13
They think OPM if anything is other people's money like you were saying and they wouldn't know it.
2:17:19
And so how do you how do you get somebody like even open to the idea?
2:17:21
You know, a lot of kids today in high school, college, they know they want to work in tech.
2:17:26
Nobody's going through those periods of life knowing they want to work in a specific organization or or very little uh on on the >> you're absolutely right.
2:17:35
So yeah, and we got look we got to just like have a presence on college campuses and be there just like Goldman Sachs is and just like Facebook is and we got to go tell our story.
2:17:42
tell our story. Like you know you guys know this but uh I used to work for a head of sales one of my companies and his famous thing was you know uh show it sell it hide it keep it basically right and right now we are hiding it basically and people find us because they are looking for stability as opposed to us
2:17:56
finding people who are looking for like an actual real interesting challenge >> it's an interesting time you know apparently uh CSgrads are struggling to find roles you can you can see the variety of reasons for that you know we just had someone on from claude claude code performs really well. Now maybe
2:18:12
Now maybe it's performing at the level of a junior engineer, but uh the the opportunities in government where you don't need to be you're not out there competing, you know, with other foundation model Luke Fair like he is a programmer.
2:18:25
It from that massive Bloomberg article, it didn't seem like 90% of what he was doing was programming.
2:18:32
It seemed like yeah, he was able to scrape some data together and do some analysis to know how to make a decision, but a lot of it was just sending emails, having phone calls, having meetings.
2:18:40
But Luke's also an example of somebody who's truly elite in in his category.
2:18:45
And I'm talking about like the next like 10,000.
2:18:48
>> But I feel like if you're a new grad and you can program that gives you a superpower that then you can also just be effective to be rigorous and first principal thinker in a meeting where you're just trying to decide how much money should we spend on this thing. >> Yeah.
2:19:00
>> Did you see by the way did you see the quote from the uh unnamed government source in that article about why they didn't like why they didn't want Luke?
2:19:06
They're like he's not qualified because he didn't go to college and he didn't have 5 years experience. Right.
2:19:08
And that is exactly the problem, right?
2:19:10
All of our criteria for evaluating people are based upon credentiing and based upon tenure.
2:19:16
And this is where merit based hiling matters so much.
2:19:18
Like to me, >> if you're Luke, I don't care if you're 18 years old and you can actually function at the level of somebody who like, you know, knows programming at at a high level.
2:19:26
Let's pay you that level.
2:19:29
Let's hire you at that level.
2:19:29
And and okay, like if you need some help around the edges to like, you know, make sure you can sit in meetings, you know, with your shoes on, that's great.
2:19:35
We can teach you that basically. >> Yeah.
2:19:37
But we can't we can't exclude people from the process because they don't have like you know a sheep skin that says you know they went to Stanford for four years. I mean that's crazy. >> Yeah. Exactly.
2:19:46
>> How is your AI strategy forming?
2:19:46
When people hear AI in government as citizens they get scared. That sounds scary.
2:19:52
If they hear if you're working in the government and you hear AI, you're probably thinking I don't want to lose my my job.
2:19:59
Uh but but clearly it should be able to be you know beneficial.
2:20:04
The big thing just feels like get every government employee access to an LLM >> because before any of the job displacement, any of the cyber punk terminators, like let them search the knowledge quickly, like please.
2:20:17
Anyway, what was your take? >> Yeah.
2:20:20
No, you're exactly right.
2:20:20
So today on my government computer, if I want to do something on an LM, I have to like go to my personal computer to do it, right?
2:20:26
It's not >> how many government jobs are email jobs, too. >> Right.
2:20:31
Look, the privacy issues are real and we got to be kind to them.
2:20:32
But like there's but there's but so much of what the government does is already in the public domain.
2:20:36
So let me give you a very simple example.
2:20:38
So >> one of the things my team does as I mentioned is we develop like rules and regulations for you know let's say how how you should do merit hiring in the government. Okay.
2:20:48
>> And the way the process works which I won't bore you with but basically like we put out a rule and then we have to invite public comment on it and literally people submit comments.
2:20:54
So we're doing a rule right now where we got 40,000 public comments on this rule. Okay.
2:20:59
some a group of people in my team literally read all 40,000 of those comments and they write a written response to them and do it, you know, the oldfashioned way.
2:21:07
Now, I'm not going to say like let's just have let's just get rid of all the people and have AI do that.
2:21:12
But there's no question in my mind that we can get a 10 to 15% easy efficiency advantage if we actually had a very simple LLM that we could train on totally public data.
2:21:20
I'm not talking about private data.
2:21:21
All that regulation stuff is public. >> Yep.
2:21:24
>> You know, help people manage that process.
2:21:25
But like we have so we have to start with that.
2:21:28
start with that. So like what I what I'm doing here in in OPM is uh I'm actually going to have somebody come in from the outside and like do the full landscape of like what's happening in customer support and what's happening in you know HR organizations and like what are all the use cases out there and then what
2:21:43
I'm doing is just telling my team look now your job is to go back and find like what are the small wins we can make on little use cases and again I'm not asking you to like you know get rid of 100% of your people but like you need 10 more heads and and you need to find some place to get 10% more productivity. We ought to be able to do that within
2:21:58
We ought to be able to do that within our current budget without actually having to, you know, add headcount.
2:22:01
So, we just got to start with little baby stuff that doesn't scare people, get them educated. You're exactly right.
2:22:08
Everybody should have, you know, an LLM on their desktop and then we can tackle the hard problems, which is, okay, are we going to put confidential government data in them and do we need them airgapped and all that crazy stuff, but like we don't even need to do that right now.
2:22:19
We just need to like educate people and then come up with use cases that are based on like literally public data >> with human augmentation.
2:22:24
is the does the federal workforce have a like an an aging problem?
2:22:30
You know, we'll talk with uh CEOs on this show or investors that say, you know, the majority of factory owner operators in the country are going to retire within the next 5 to 10 years, right?
2:22:41
That becomes concerning because there's a lot of just like general knowhow and process that could just kind of get lost or evaporated.
2:22:46
Is that a challenge that you're facing in terms of you know people that have been in the government for 30 plus years and are and are uh getting to the point where where they're ready to retire?
2:23:00
>> Yeah, if you look at the demographics of the government, I don't know the exact number, but there's no question like the government is is very skewed towards people who are kind of later in their career.
2:23:08
And again, I think this is a problem that we've had, which is we haven't figured out a way to actually get people in at earlier stages in their career because we've got all these impediments that I talked about that make it hard for you if you're a recent Stanford grad or whatever to be able to get a job here.
2:23:20
So, yes, we have to solve that problem.
2:23:22
Look, I mean, sure, there's going to be knowledge that walks out the door.
2:23:25
Look, I'm more worried about the long-term thing, which is can do we have a steady pipeline of really smart people who will come here and then then we can solve that aging problem by just, you know, over time kind of changing the demographics.
2:23:36
But yeah, like I don't think I'm not worried like there's a cliff here where, you know, 10 years from now all the experienced people walk out the door, but I do think we have to have like a demographic and a and a set of hiring practices that allows us to actually kind of, you know, build a funnel from the very bottom of of folks. >> Yeah, it'd be cool.
2:23:51
I remember maybe in 2012 like Teach for America was really popular and obviously that was like non-governmental but like aligned with this idea of like a a tour of rough service and there was code for America and you know it's like cut out the middleman and just go straight for America like work for the government. >> I love that. Yeah.
2:24:11
>> It'd be great culturally if it was like yeah somebody So because now like I feel like if you did four years just in civil service and then you jump into Silicon Valley it's kind of like a weird track but like it shouldn't be.
2:24:20
It should be completely normalized. >> Yeah.
2:24:22
A long time ago, right there, and this is not the perfect analogy, but there used to be something called like the civilian conservation corps, which was exactly that, right?
2:24:28
It was like people came right out of school, they did some heavy labor for a while, and then they went to the private sector.
2:24:34
So, yeah, like we ought to do this.
2:24:34
So, like what I would love to do is I would love a program where we say, you know what, >> take all the smartest people, have them come here for two years.
2:24:40
By the way, if we can do this, let's forgive your let's forgive some student debt as part of that, right?
2:24:46
that, right? So, like let's actually have a real trade-off, which is you do public service and we'll give you some financial compensation and oh, by the way, I want to work with the private sector and say, you know what, we're
2:24:54
going to get a private sector employer to guarantee you a job when you finish your two years here and they might even give you credit full credit for those two years so you come in as a third year and that and like just work on that stuff, right? So, uh you know, that's
2:25:04
So, uh you know, that's what we need to do and and look, I've been using this term that's terrible that my kids joke at uh which is make government cool again, which is magaka if you pronounce it out loud. >> Magaka.
2:25:14
>> Magaka. my uh my my uh my uh marketing team who's sitting here next to me off camera will tell me doesn't run off the tongue >> doesn't really yeah it's not it's not the greatest but like that's what we have to do like we have to make civil service like super exciting and the good news is like we've got no shortage of
2:25:31
like moonshots now right so like >> AI right like how do we transform the government with AI that's a great moonshot let's go do that but we need like a you know Apollo mission-like moonshot which I think the president has given people with AI and we got to go tell that story and you If we can do that, then I think like we're in a totally different situation. >> Are you going to be visiting college
2:25:49
>> Are you going to be visiting college campuses for career fairs at all?
2:25:50
Are you going to be pounding the pavement? >> I would love to.
2:25:55
Look, you all know this having been in the valley.
2:25:56
Look, >> if you're in the valley, 99% of your job is recruiting basically.
2:26:00
Like that is like probably the most important thing that any manager does.
2:26:02
And yeah, like I don't think any of us is beneath that. We got to go sell.
2:26:06
So yeah, I'd love to go to campuses.
2:26:07
I'd also look I I want to we've been talking about campuses.
2:26:10
I also want to make clear though, one of the priorities the president has, which I totally agree with, is we shouldn't use credentiing as a shortcut for this stuff.
2:26:17
So look, yeah, I don't care if you went to college or not, if you have the skills to do this job, like we got to go find you too.
2:26:21
U look, college college campuses are nice aggregation points and make it more efficient, but like we need to go find anybody who has a, you know, technical degree or not a technical degree or a trade degree or anybody who's just really smart and capable and go find those people.
2:26:33
And we should hire them not because they, you know, have a, you know, a diploma, but because they actually can contribute to the workforce >> or even like experience at a startup, like they've been there for a couple years, they vested, they run to the next thing, go do a tour in the government. >> Sounds good. >> Yeah. >> Last question.
2:26:48
Have you had any pleasant surprises since starting your job?
2:26:52
Anything that you're like, "Oh, that's actually run pretty well." >> Yeah.
2:26:56
You know, look, I'll be so to be totally honest.
2:26:57
Look, um, there are my pleasant surprise, which is I don't think is a surprise, is look, there are very good people here who are who are really care about what they're doing.
2:27:05
So, look, >> you know, everybody in the government here, there is a serious element of public service and they all take it very seriously and believe it and believe it and and it's incredibly like noteworthy.
2:27:15
The what I what I really think is look I think the system has failed them which is look as as leaders and managers we have created a system where you know we've told them do not ever make a mistake do not ever risk innovating because we don't you know look you guys know the valley right in the valley we always talk about look we're looking for uncapped upside on stuff
2:27:31
>> yeah you get fired for not taking the risk >> that's exactly right there is no value today in in maximizing for uncapped upside if that means you also take an extra 5% of downside risk and again look I want to be totally clear we can't be cavalier you know we're dealing with people's you know, social security or we're dealing with national security. So, we can't just, you know, literally
2:27:46
So, we can't just, you know, literally throw caution in the wind, but we can accept that there are some things where we may not get in the 100% right and then we'll fix them when we do.
2:27:54
And we have to have a culture to do that.
2:27:55
So, that to me has been again the very positive upside surprise, which is and and which I hope will prove true, which is if we can change the incentive system, I think you have really good people who will do what the incentive system incents them to do basically.
2:28:07
But right now we just we have an incentive system that in my mind at least kind of encourages behavior that just is not you know efficiency maximizing is not innovation maximizing uh and you know is just outdated I think in a world where you know we know technology and the needs of the government are going to change very rapidly.
2:28:25
>> We need to be innovation maxing. Let's do it. I love it.
2:28:27
Thank you so much for joining.
2:28:29
>> Thank you for serving our country and and rallying so many smart uh people to join you >> and thanks for breaking it down for us. This is very helpful. Thank you so much. >> Appreciate the time. You take care. Bye. >> Cheers. Hi.
2:28:39
>> We need a Luke Ferator for the CIA.
2:28:39
We need to send Luke Ferator to North Korea. Infiltrate Pyongyang.
2:28:42
Get behind enemy lines and turn it into a capitalist utopia.
2:28:48
Make South Korea look like a complete blackout by comparison.
2:28:54
You've seen that map of the North Korea is dark and South Korea is super bright.
2:28:59
More lights in Pyongyang than all of South Korea combined.
2:29:01
Luke Fair on the front lines. Get it done. >> This is breaking.
2:29:05
This is breaking in real time.
2:29:06
So, John actually hit up Peter Salis over at Discord.
2:29:11
>> Uh, HR apparently just threw a note on uh Peter Salis just posted guys at TVPN WTF.
2:29:19
John Xi, I think I'm in trouble.
2:29:19
HR just threw this on my calendar.
2:29:23
>> It's Peter and HR discuss TVPN issue.
2:29:26
>> Wait, is this real now?
2:29:28
>> No, I think I think he's joking.
2:29:28
But, uh, very good stuff. >> I love it. That's amazing.
2:29:31
Thank you for sharing that.
2:29:33
>> Peter, come on the show.
2:29:33
We're going to do a uh we're going to figure out your cloud uh your cloud.
2:29:36
We're gonna have people live bidding. >> Yeah. Yeah. Yeah. We should have three. We should be Shark Tank. He's the shark.
2:29:44
We have three hyperscaler uh cloud SDRs. Come on and pitch. Okay.
2:29:48
This is what we can bring to you.
2:29:50
This is what we're asking.
2:29:52
We're asking for we we got 100,000 H100s.
2:29:55
>> It's an auction for who can deliver the lowest price. >> Exactly. Exactly.
2:29:57
Anyway, we have our next guest in the Temple of Technology.
2:30:02
We have Kyle from Contrary. How you doing, Kyle? Good to see you.
2:30:05
>> Welcome to the stream. >> How's it going, guys?
2:30:07
>> What's new in your world? Break it down for us.
2:30:11
>> Well, we're just uh we're just launching our latest deep dive from Contrary Research. >> Very cool.
2:30:16
>> So, for folks who don't know, Contrary Research is our private markets research database we launched a couple years ago.
2:30:22
Contrary is a venture fund, but our focus is on talent and on research.
2:30:24
So, finding the best ideas, best people, bringing them together.
2:30:28
Um, and so Contra research has published research on 500 different companies.
2:30:32
I think we've got most of your sponsors on the list.
2:30:36
So we're working our way down.
2:30:38
>> Um, but we just published our latest deep dive on building an American TSMC.
2:30:42
So TLDDR the piece is the idea that >> we're completely dependent on Taiwan for 90 plus% of of advanced semiconductors and it's probably the dumbest bottleneck that we could possibly be in.
2:30:52
And it feels like we're basically just hoping that it doesn't become a problem when it could become the most significant geopolitical flash point and effectively lead to World War II.
2:31:01
And so it feels like there is something we should do about it.
2:31:04
And and so we kind of go through the options of do we build it from scratch?
2:31:06
Do we borrow it from TSMC?
2:31:08
Uh do we try and and buy it from from some willing sellers?
2:31:12
>> It seems uh consensus that Intel is not the American TSMC, is TSMC the American TSMC?
2:31:17
Is Samsung the American TSMC?
2:31:20
We've seen a lot of progress from both of those companies.
2:31:22
Elon doing a big deal with Samsung.
2:31:24
TSMC obviously seeing great results out in Arizona.
2:31:27
What's your take on just porting or expanding the current uh set of fab companies that are doing quite well?
2:31:36
>> Our biggest takeaway from doing the research is that um a little bit that the ASMC is more of a mindset than a specific company.
2:31:44
It's an ecosystem that we have to build a lot of different aspects of this.
2:31:47
Yeah, >> there's a ton of startups that are building a lot of advanced stuff in chip design and using AI and that TSMC is pouring 165 billion into the US more so there's a ton of things that we can take advantage of.
2:32:00
The biggest limitation is that when you try and build a lot of this stuff from scratch, you just don't get there quickly enough for it to make a difference, right?
2:32:07
There's a bunch of stuff like the folks at >> and they have this idea sort of internally of of >> China 27 where it's this idea of you know if if China is going to invade Taiwan it's probably going to happen over the next you know call it four or five years.
2:32:21
Xi has talked about 2027 specifically.
2:32:23
So it this is an urgency thing.
2:32:25
This is not a long-term bet.
2:32:25
And so the question is how do we get to scale where if if China was to take Taiwan tomorrow is there something that we could do to have some capacity here?
2:32:35
The unfortunate reality is that the startup ecosystem, as great as it is, and as much as it can benefit us in the long run, it's not going to get there quick enough.
2:32:41
As much benefit as we get from TSMC partnering, a lot of the the results they're having in in uh in Arizona, um there's a huge cultural blowback in Taiwan because they have this Silicon Shield where they think of our dependence on them as their protection from China.
2:32:55
And so yes, TSMC wants to pour a bunch of resources here, but whether we get those sort of leading edge nodes that allow us to compete for things like AGI and to really compete with China, that is a much longer battle.
2:33:07
And so despite the fact that Intel is is struggling is it's basically sending up emergency flares.
2:33:12
You guys talked about it on the show basically in their last quarterly earnings.
2:33:15
They talked about, you know, we're going to do our best and if we don't get material customers, it may not be economical for us to continue to compete in leading edge nodes, which is going to be a huge hit for the US to stay competitive.
2:33:24
And so our thesis in the piece is that we we basically have to take Intel as our only hope of getting to scale quickly enough.
2:33:34
Intel's not going to do it on their own.
2:33:36
There's a bunch of stuff that we have to do to make that possible. >> Yeah.
2:33:38
So, what's the biggest request from TSMC or Taiwan?
2:33:40
Like should we be pulling the hey we'll invest alongside you, we'll subsidize, we'll give you tax cuts to build the second, the third, the fourth fab in America, or should we be more focused on let's commit more defense resources, more government spending to Taiwan to create uh, you know, an American shield that's independent of the Silicon Shield. Uh, or maybe both.
2:34:08
Yeah, I mean there's definitely when you talk to all of the major defense companies, uh Palmer has a great line where he talks about turning Taiwan into a prickly porcupine that people don't want to step on.
2:34:17
That is absolutely priority number one to make them to give them all the capabilities that they need and and the folks at Anderol are on the ground in Taiwan all the time.
2:34:23
So that's a huge component of of sharpening the partnership.
2:34:28
I also think that you need to emphasize um that American companies need to be the government needs to incentivize American companies to be purchasing Americanmade uh semiconductors as much as possible.
2:34:40
So as you reshore more of this stuff to whether it's TSMC efforts, whether we literally, you know, nationalize Intel and take it and take the foundry business private, right?
2:34:49
Like Dylan Patel, who you guys have had on the show and is an absolute rockstar, he has made it abundantly clear that the survival of Intel foundry is critical to America's economic and technological dominance.
2:35:02
And so we have to take that seriously as well.
2:35:04
And there's a bunch of incentives that we can build in terms of making, you know, getting people access to uh semiconductors that are made by Intel in the US, by TSMC in the US.
2:35:12
We have to incentivize people to be using our own ecosystem so that we get the reps we need to get as as far away from dependence on Taiwan as possible.
2:35:22
>> Do you think that Lip Bhutan is the right leader for this transition for Intel?
2:35:27
It seems like they need to with broader support reinvent themselves and yet hearing Lip Bhutan on earnings calls and and just talking through it just feels like cut after cut.
2:35:41
>> He's good at firing people, but is he really good at firing?
2:35:44
>> I haven't been I haven't been inspired by uh he's definitely not Karp on the mic.
2:35:48
Uh he's not not exactly inspiring people. Um so I'm curious.
2:35:51
also has like 1,000 employees and I'm pretty sure Li Bhutan has like a 100,000 employees or something.
2:35:58
>> Yeah, they so Intel has more employees than TSMC and Nvidia combined. >> Yeah.
2:36:04
>> So, he's got he's got plenty of people that he can fire.
2:36:06
>> Uh the the biggest thing that is compelling about Intel is that they are already in this process of cultural change. Right.
2:36:13
You look at that I mean it's back to 2005 was the first time they had a CEO who wasn't an engineer by trade and basically they went through 15 years of financialization like it was literally the Jack Welch playbook of just dumping money into stock buybacks and and robbing R&D for for decades.
2:36:27
Um he you know those CEOs were the ones that put um them on the on the path sort of stumbling uh losing their lead.
2:36:33
So like even even with Gellzinger like that transition is already in its way like putting engineer they talk about bringing the nerds back and that transition is already in it way which is important.
2:36:44
I think the cultural leadership that you should be paying more attention to is the leadership level at intel foundry specifically when you think about Intel's two core businesses.
2:36:54
You have Intel products Intel Foundry.
2:36:55
Intel Foundry has had four different leaders over the last three years, like some of them lasting no more than two months, right?
2:37:01
And what was compelling, this idea that like you you can you can have this sort of within a division leader who can be really inspirational.
2:37:10
I think the folks at Whimo, they have a co-CEO setup, but it's their former head of policy and then their former CTO.
2:37:14
You have the technology, you have the the policy.
2:37:19
Like that's a great duo for sort of the Whimo setup.
2:37:22
something at Intel Foundry that could be similar could be really compelling.
2:37:25
The thing that's the biggest concern for me is that the first person they had once they started breaking out Intel Foundry into a separate P&L, the first CEO that they the first leader of the of Intel Foundry that they had, they called him the president of Intel Foundry, he d he reported directly to Galsinger.
2:37:40
Four leaders later, it's now this person is the general manager of Intel Foundry.
2:37:45
They're also the chief global supply chain officer and the chief technology officer of Intel's core business.
2:37:51
Meanwhile, like Intel products has its own dedicated CEO with the title of CEO.
2:37:56
I think the biggest problem is not necessarily even liutan, but it's more about are we actually acknowledging that that Intel foundry needs to be a growth engine that you can invest in to be able to build back dominance and that's absolutely not how they treat it.
2:38:10
>> Was I feel like earlier this year there was a rumor that Elon was kicking the tires on Intel.
2:38:14
Is was how how real was that? Did he kick the tire?
2:38:17
And >> it was it was the PJ tracking.
2:38:19
That was how they all but the PJ but the PJ tracking felt like a bit silly cuz everybody was in Maron. >> Yeah. Everyone was there. >> That's right.
2:38:28
You can you could spin probably a lot of compelling narratives based on all of the people who were there at the same time. Right. >> Yeah.
2:38:34
>> Um in terms of like what is actually sort of official, the two things that you know for sure are there was talks that that TSMC was going to acquire Intel's Foundry business.
2:38:44
their board flatly denied that that that wasn't true at all.
2:38:48
Then there was talks that they might invest heavily and run a joint venture where they take over operations of Intel's foundry business even if they're not buying it outright.
2:38:57
>> And what's funny is that they did not deny that outright. They refused to comment.
2:39:00
And so the general census of folks is that that was a conversation that was active.
2:39:06
>> Yeah, that makes sense.
2:39:06
How much of the uh the race for American semiconductors is driven by the question of like founder mode?
2:39:13
Just that abstract question of uh you know do we need Elon in the seat leading?
2:39:18
He said he was going to be walking the floor at Samsung.
2:39:21
Um obviously like the founder mode pattern has seemed to work in so many stuck kind of stagnating worlds like rocketry, electric cars or Elon's gotten in and kind of jarred things loose.
2:39:35
Um but uh but is that is that something that we that we should be looking out for or optimizing for? >> 100%.
2:39:43
I mean when you contrast Lipu versus Jensen, it's like night and day difference, right?
2:39:48
You you do not have visionary leaders in chip manufacturing in the US because we don't do it anymore.
2:39:54
Like it's not a fundamental part of who we do of what we do.
2:39:55
There's not a core DNA there.
2:39:57
And so do you need somebody who is that visionary leader? Absolutely.
2:40:02
And does Intel have any of that DNA? No.
2:40:03
And so when you think about what needs to change, I think our thesis and takeway after doing six months of research and drilling into all this stuff is that you cannot ignore the entire ecosystem.
2:40:13
And that leader that that visionary leader role is absolutely critical and that's that is an unanswered question like we don't have that like we don't have an you know somebody retweeted our our um our post today and said we just need an Elon Musk like you know herculean act of god to be able to make this possible.
2:40:32
And like the the takeaway is accurate.
2:40:34
The how to do that is much more difficult. >> Yeah. Yeah.
2:40:39
It can't be manufactured.
2:40:39
Um but I mean green shoots all over the place.
2:40:43
Lots of cause for optimism.
2:40:43
But >> so hope hopefully the piece uh starts a conversation can be a catalyst for change.
2:40:50
What are you hoping to see out of like the immediately next quarter for Intel to get on the right track?
2:40:57
>> The biggest opportunity is for Intel to stop treating Intel Foundry like it is an ugly stepchild.
2:41:01
like it is this like embarrassing accident that they happen to have and they're trying to distract people over to this other thing or dress it up like it's this fancy thing.
2:41:08
And the biggest problem is and this goes back to this is a great conversation I've heard a couple of folks have.
2:41:13
They talk about the I think it was um Buck Buco Capital talking about like the the greatest thing that Elon Musk has built independent even even think Tesla, SpaceX, everything.
2:41:24
>> It is the investor base at Tesla is the is got to be the most incredible investor base any public company has ever had to let him do what he's doing and to have the vision and everything.
2:41:35
Intel is is just smattered with what Palmer would call Wall Street weenies is everybody's just thinking about it is how can we optimize this thing as effectively as possible and it's like that is not how you build the future nor is it how you build American dominance and so really you need that investor-based turnover and it feels
2:41:50
like that comes from narrative where if you're telling the story of Intel foundry we can get a visionary leader we can have this opportunity they're already at scale they have a lot of the technology they've they have sort of caught back up in in many ways they're still failing operations pretty miserably. And so the opportunity
2:42:05
And so the opportunity is like tell that story and get an investor base that is stoked to be investing in the ASMC.
2:42:14
>> Well, thank you so much for joining.
2:42:15
It's a pleasure catching up. We'll talk to you soon.
2:42:17
Have a good rest of your day.
2:42:19
>> Thanks for coming on, Kyle. Great work.
2:42:20
>> And speaking of Ander, our next guest works for Ander and uh she's the uh general manager of Ander RMS and we're excited to talk to her about uh the new rocket motor facility.
2:42:30
But we'll let her break it down for us. Welcome to the stream. How are you doing?
2:42:35
We have one minute while we get >> to keep clapping.
2:42:39
John, >> just keep clapping.
2:42:41
Just keep >> welcome to the stream. How are you doing? >> What's happening?
2:42:47
>> Oh, it's a really good day.
2:42:47
Just uh just commenced or finished a ribbon cutting uh with our new facility in coastal Mississippi with uh Chairman Wicker about 10 minutes ago.
2:42:57
So, uh it's good day so far. >> Fantastic.
2:43:00
Uh tell us more about this facility. What are you making? How big is the facility? Um R&D.
2:43:04
How big were the scissors?
2:43:08
>> You know, the scissors were not as big as I was expecting.
2:43:10
Uh >> I mean, they they were big, but they weren't like the uh the comically big.
2:43:15
No, we uh just finished the uh a full rate production facility for kind of what the 2020s can do for automated robotic full rate production of solid rocket motors.
2:43:26
We have a 450 acre facility in coastal Mississippi about nine buildings.
2:43:32
>> And uh when we moved in here, it was a mult facility in 2020 and we we saw that the good bones it had and the ability of of what it could do.
2:43:39
So we we took one of the buildings on the far south end of the campus uh nearly quadrupled the footprint.
2:43:46
um got worldclass um engineers specifically from the automotive industry to really look at what solid rock and motor production could look like in the 2020s with robotics automation and really putting um you know robotics everywhere where there's a safety critical or a quality critical component.
2:44:07
>> Speaking of robotics, what's behind you?
2:44:09
>> That is one of two robots that are involved in the casting assembly.
2:44:12
Uh so we we go through a mixing of solid rocket propellant.
2:44:18
Um and then you have to cast it where you uh you're essentially filling a mold like you were uh solid rocket motors is a lot like making a cake.
2:44:25
You you mix together dry ingredients, wet ingredients and then you pour them in a mold and you cure in an oven.
2:44:31
And so this is uh the robots that's used for the casting process.
2:44:36
>> Can you give us a a view into the shape of the company?
2:44:38
I know uh Adronos was the rocket motor company that was acquired, but it sounds like you've hired a lot of people.
2:44:44
How big is the organization now?
2:44:48
>> So uh you you are right. We started as Adronos.
2:44:50
I was one of the two co-founders of Adronos back in 2015 uh with my co-founder Chris Stoker.
2:44:57
>> Um and uh we grew that into about a 40 person company at the time of acquisition by Andre who was previous to that had been one of our customers.
2:45:05
So, a little bit of a vertical acquis uh vertical integration play. Yeah.
2:45:10
>> Um we have since grown that organization to just about 200 people today. Wow.
2:45:12
For Andor Rocket Motor Systems.
2:45:15
Uh I sit as the uh vice president and general manager of that business line. >> Very cool.
2:45:23
>> What did you see back in 2015 when you started the original company uh that that kind of caused you to uh take on the mission?
2:45:31
And it felt like broadly Silicon Valley started kind of being aware of rocket motor like supply chain challenges.
2:45:39
I want to say like in 2022, but you clearly saw it way way ahead.
2:45:46
>> Yes, this is all very much before all of the uh I guess need uh that has risen for solid rocket motor um production enhancements.
2:45:55
Um really back in 2015 I had developed a brand new formulation uh called Alletch that can bring more performance to the uh the industry.
2:46:03
I saw a need to commercialize it and naively thought that I would be able to to progress it to a spot where the two kind of incumbent providers of solid rocket motors would fight over themselves to get access to the IP.
2:46:14
Um but what I quickly realized is the um the desirement for them to innovate and get these new propellants was was not there.
2:46:26
And the only way I would ever be able to see um full adoption and utilization of that product was was if I was my own customer, if I was the solid rocket motor provider.
2:46:35
And uh a a big piece of my PhD at Purdue was looking at innovative ways to uh process energetic materials, new ways of mixing, new ways uh of doing things.
2:46:45
So I was able to leverage those learns uh those lessons along with taking what is state-of-the-art for kind of automation and and different manufacturing processes.
2:46:55
Uh put them all together to uh create what my vision was for what solid rocket motor production could look like in the 2020s. >> Very cool.
2:47:03
and uh we we really were kind of ahead of you know all of the other suppliers that have that have joined into that market. >> Amazing.
2:47:11
Well, thank you so much for calling in on such a busy day.
2:47:15
Congratulations on the massive launch and good luck with the next phase.
2:47:17
I'm sure you're going to be making a lot of product very soon. >> Yeah.
2:47:22
and hopefully copy I don't I don't know a last question I had is this is the idea for this uh new facility to be a model that you would copy and paste to to scale production or is this going to be able to kind of take take you guys all the way? >> No.
2:47:37
Uh that that's exactly the the purpose of what we are wanting this facility to do.
2:47:41
It's it's really looking at a manufacturing line that is agnostic to what goes through it.
2:47:45
So, we can do anything from a small uh 2-in diameter motor to something that that's really big up to 32 in in diameter.
2:47:52
Um, and we are agnostic in the manufacturing process, but really focusing on kind of the one piece flow out of uh manufacturing practices.
2:48:01
We can take this um this facility and copy paste it elsewhere.
2:48:07
On our 450 acres, I can fit another two full rate production facilities.
2:48:11
each one of if you look at a midscale tactical motor like say 9 in diameter we can do about 6,000 of those a year out of one facility.
2:48:17
So if I place another two of those here you know that's just a a linear increase in production without having to have a brand new giant explosives campus.
2:48:26
Then alternatively I can take this small footprint agile manufacturing process and place it strategically uh for integration purposes with our different customers both domestically and abroad.
2:48:40
And uh we are on the record looking at you know multiple places for that including Australia through the uh the new guided weapons enhanced ordinance program. >> Amazing.
2:48:48
Uh well thank you so much for joining >> the update. >> Have a great day. We'll talk to you soon. >> All right. Thank you. >> Bye.
2:48:54
Up next we have Sean Henry from Stored.
2:48:57
We ran into him in New York City.
2:48:59
Uh got a chance to sit down.
2:49:01
>> Staying at the same hotel. >> Yeah. Yeah.
2:49:02
Staying at the same hotel.
2:49:03
We just had Well, we had breakfast.
2:49:03
He just sat there and listened to us. Yeah. >> He was walking by. He was busy.
2:49:07
We said, "Hey, >> sit down. Sit down.
2:49:10
We got to talk about supply chain >> tariffs and the dimminimous uh uh the diminish deminimous exemption."
2:49:19
We will welcome him to the stream. How you doing? >> Great to be here.
2:49:23
Thanks for having me guys. >> Good to see you.
2:49:25
Uh >> great to see you last week.
2:49:27
>> Where where where did you land? Where where are you now? >> Back home in Atlanta.
2:49:30
No longer having fun in uh New York having some uh breakfast with you guys. >> Yeah. Ve very nice.
2:49:35
And uh business is good overall.
2:49:38
>> Crashing breakfast, I should add. I guess >> crash.
2:49:40
We were It was a great uh breakfast company.
2:49:43
>> We were crushing breakfast.
2:49:43
It didn't feel like you were crashing because we you you were you were probably it was a busy day for us.
2:49:48
You were probably even busier and and we uh we we requested that you hang with us.
2:49:53
It was fun >> and uh shared some insights on on all the different things happening in your world.
2:49:58
So yeah, G uh give me the update on uh on tariffs, the dimminimous exemption, where things how we kind of got here and then where we are now and then we'll get into where we're going next. >> Yeah, absolutely.
2:50:10
So I guess background, there's two types of core tariffs.
2:50:12
One is the general commercial, something's coming into a US port and you're charging a tariff based on the commercial value of the goods at that time.
2:50:22
And that's largely what was rolled out at liberation day a few months back was all of these tariffs particular around large imports.
2:50:28
But there's a separate category that had a big action last week which is dimminimous uh exemption which is really started in the early 1900s mostly for international travelers think hey I want to send a package back to my family.
2:50:41
Well there's these rules created that as long as that package is under $800 and in these categories you don't pay any tariffs.
2:50:49
Well, what's happened the last few decades is if I want to store my inventory locally in the US, meaning bring it through a port, hold it in the US, now ship it locally.
2:50:57
If I'm say, let's paying uh $2 for warehousing, $7 for delivery, and $5 for uh the tariff to get it in, I'm paying $14 to ship that locally.
2:51:10
But if I never bring it into the US, if I just keep it in China, keep it in Europe, put it in Mexico, Canada, and instead I'm maybe paying $1 for local warehousing and labor, a more expensive package like $9, $10 internationally, but I never pay the tariff.
2:51:26
I'm now comparing $14 to ship my unit through the US versus maybe $10 to ship it from international.
2:51:32
That's a big difference on your average product.
2:51:34
And so Trump and the administration had formerly said that they well they've been waging war on this since even before election day, but they formerly said it was going to go away in 2027.
2:51:43
So since the start of the year, brands thought they had maybe two years to get ready for this.
2:51:48
And all of a sudden last week you saw announced on Wednesday that it's going away on August 29th.
2:51:52
And so now brands are rapidly trying to move inventory into the US. >> Yeah.
2:51:58
And uh is it apocryphal to say that this all like Teimu and Shien like kind of started this trend or did they just merely capitalize on it?
2:52:06
Were there other other companies that kind of found this?
2:52:11
It's not necessarily a loophole.
2:52:13
It's more just like an opportunity that if you exploit it to the max, you can scale a multi-billion dollar business. >> People were using it.
2:52:19
Nobody exploited it to the same degree. >> Yeah.
2:52:22
I wouldn't call Shien and Timu just like you know the tourist example.
2:52:27
It's like they're they're shipping billions of dollars through this platform.
2:52:29
But uh what are are they the are they the the the the real progynators of the idea?
2:52:38
>> They've definitely exploited it at a greater scale than anyone else. >> Sure.
2:52:42
>> But what's crazy is that if you look at the top 100, let's say Shopify businesses, over 50 of those roughly was the estimate are shipping out of Mexico into the US.
2:52:50
So this is very prevalent across brands of all sizes, particularly very large in the apparel category.
2:52:56
And just some quick numbers, last year alone, there was an estimated $64 billion of commerce that entered the US through the dimminimous exemption, which is roughly 10 billion of missed tariffs and roughly four to five billion of missed US logistics infrastructure revenue.
2:53:14
And so broadly speaking, uh, logistics USoriented companies like ourselves are very excited by this because it's very hard to compete with Chinese and Mexican and other labor, real estate, and no tariff versus local fast shipping.
2:53:30
>> So yeah, what I mean this sounds like a huge tailwind for your business, but um, what are your customers actually coming to you with questionwise?
2:53:36
It sounds like, uh, there's a very quick shift on the horizon around the day minimus exemption.
2:53:42
So, they're coming to you and saying, "Hey, I need to move all my inventory from Mexico or China or Taiwan or Vietnam into Atlanta or somewhere else as soon as possible."
2:53:52
Is that is that basically what's happening? >> Exactly.
2:53:57
Because well, one I think it's important to note that when you look at tariffs, a lot of people apply it linearly.
2:54:02
Okay, a 10 20 30% tariff product cost is going to go up 10 20 30%.
2:54:07
30%. that's on the commercial value of the individual unit and so much of the cost is both margin for the brand advertising local US logistics and so these tariffs don't translate one to one for how it's going to impact the consumer but at the same time we're not necessarily talking to the brands as much about changing manufacturing origin to get away from those tariffs because the impact can often be absorbed for
2:54:32
these mid-market brands who have real profits real growth we're talking to them about is back to that math I gave of if you were spending uh $10 to ship it internationally avoiding a tariff but you're doing a one to two week shipment so a slow delivery but cheaper and it was you could do two three day delivery in the US but maybe $14 all in with the tariffs well all of a sudden if you're
2:54:55
now spending uh or I I said 11 at first with the tariffs or in the US well all of a sudden now if you're going to jump all the way to 14 it doesn't make sense to pay more and deliver in two to three weeks cheaper but now all of a sudden there's massive influx of volume where all these brands are saying how fast can you get me live in the US I'm in Mexico I'm in Canada I'm in Europe and the problem is with outdated technology most
2:55:17
logistics businesses are going to tell them four to six months andor with the influx of volume a lot of capacity is becoming challenged again like we saw all the way back in 2020 and 2021 with such shortages of warehouse capacity it's not that there's not leases on the market it's that ready to go warehousing capacity with all the infrastructure technology and labor that capacity is rapidly getting gobbled up. And so we
2:55:39
And so we actually had a case study on our website uh from exactly what's going on where True Classic TE's is great example, massive many hundred million dollar uh t-shirt retailer wearing one right now earlier this year.
2:55:52
they were stuck in Mexico and the Mexican president first signed away their exemption which was, hey, if you first bring it into Mexico and it's here for less than 180 days because we know you're going to ship it into the US, you also never pay our tariffs, but please pay our labor, our real estate, etc.
2:56:09
Well, they first signed that away.
2:56:10
There's since been a pause put on it, but we already migrated customers.
2:56:14
Take someone like True Classic.
2:56:16
They were often told, we can get you live in the US in six months.
2:56:19
That's insane cost that they're going to face for those six months relatively.
2:56:21
We had them live in 18 days from meeting us to go live.
2:56:25
And that's all because we're really the cloud in comparison. >> Makes sense.
2:56:30
Uh last question from me. Um uh how solid are we?
2:56:32
I mean when we went into uh when we went into liberation day, a lot of it was just uncertainty from the business community.
2:56:42
How how confident whether or not it's good or bad for your business?
2:56:45
How confident are we that we will be at least on the same course for whether it's good or bad for the next few years, for the next 12 months?
2:56:53
Like how much confidence do people have that these set this set of rules that are in place right now will stick?
2:57:02
>> Personally, I think the confidence is going up.
2:57:03
I think this is one of the last uh exemptions people are curious about.
2:57:07
While there are still a few negotiations going on with specific countries, the kind of broad general tariff, the reciprocal tariff, and even key countries have already been set.
2:57:15
And frankly, I tend to believe the administration is liking the results.
2:57:19
So far, we've taken in over 150 billion of incremental revenue since Liberation Day just via tariffs alone.
2:57:26
There was a GDP posit or sorry, um kind of balance budget positive month as a result of these tariffs and more.
2:57:33
And so I don't think we're going to change course and go backwards.
2:57:36
go backwards. And I think some of the logic is while it may drive a slight increase in cost on the the front end, you have to wonder what it's going to do on the back end when there is more production in the US, more middle and
2:57:49
lowerass jobs that have been competing with Mexico, China, these other countries, labor on logistics, and ultimately if they're able to use tariffs to impact other taxation on citizens leaves me thinking the administration is going to stay course on this. >> Makes sense. Awesome. Well, >> Makes sense. Awesome.
2:58:04
Well, congratulations on all the growth and it seems like a lot of these uh decisions are going your way.
2:58:08
So, uh happy to have you on the on team America building infrastructure and everything that we need to uh bring products to market in the United States.
2:58:19
So, thank you so much for joining.
2:58:20
>> Great to see you, Sean.
2:58:22
>> We'll talk to you soon. >> Absolutely. Thank you.
2:58:23
>> Have a good rest of your day. We'll talk to you soon. Bye.
2:58:26
>> Up next, we have Andy from Two Cents.
2:58:28
We've highlighted his posts many, many times on the show.
2:58:30
so excited to meet him and chat about the the business and his his day job outside of posting um because he's built a very very fun social network where username is your net worth.
2:58:43
Andy, welcome to the stream. How you doing? >> Great to be here. Thanks for having me.
2:58:48
>> Are you in a secure location?
2:58:48
You've probably upset a lot of people with what you've built, but >> it's opt in.
2:58:53
It's >> I guess it's opt in, but it just feels like something people would push back on, right?
2:58:56
You've gotten push back for that, right? to a degree.
2:58:58
Uh people have been a lot more positive about it than I thought they would be actually. >> Okay.
2:59:05
>> I think what happened is I tapped into a latent anxiety that everyone actually had and it seems sort of like people are like, "Thank god someone's doing this so I don't have to worry about it anymore."
2:59:16
>> So is it is it anonymous? It's just your network. >> Yeah.
2:59:19
Quickly explain explain the product for people that haven't seen it.
2:59:23
I think a lot of people have probably seen it without realizing it.
2:59:27
seen screenshots of like polls or comments or things like that which I think are fascinating but but yeah explain it uh for the audience.
2:59:35
>> Yeah, so we're building an anonymous social network where your username is your net worth.
2:59:38
The main idea is to provide a verified place to have financial conversations that are difficult to have in person or with other people around you because of the inherent uh private nature of finance.
2:59:51
And so we're collecting net worth information from bank accounts, brokerages, crypto wallets, and then later we're also going to do real estate and all kinds of other financial assets.
3:00:00
And we're trying to calculate this one big number that we can assign to everyone and allow you to speak from your position basically.
3:00:08
>> What what are some of the key learnings insights?
3:00:11
I mean I think I think the polling function where people can users can ask a question and then see like you know let's say it's a yes or no answer.
3:00:20
you can see how much net worth is like backing up the results.
3:00:22
And so I feel like it it exposes like okay what what what does like what side is wealth on on this specific issue but I'm sure you've had a bunch of other interesting learnings. it.
3:00:35
I think probably the most interesting thing is when I set out to build this, I thought it would be inherently a place for financial discussion where people would talk about tax strategies and ARBs and alpha and stuff like that.
3:00:45
And it's really become more of a general place to hang out and what I figured out is actually every conversation is a financial conversation.
3:00:53
Your net worth and the experiences that have led you to that number uh sort of dictate the way that you are going to look at other things as well.
3:01:00
And even if you're talking about something that's kind of boring or weird, that number is still relevant in that conversation, even if you don't bring it up every time you talk to someone. >> Totally.
3:01:13
>> I feel like there's a lot of anonymous social networks that have gotten like problems with like bullying and stuff and just like toxic communities because of the anonymity.
3:01:20
Have you run into any problems?
3:01:22
Are you fighting it in any particular ways or do you think it like >> Yeah.
3:01:26
Do people ever come on there and try to eat the rich?
3:01:28
just net worth negative $2,000.
3:01:33
>> We are actually in an incredible position as a social network because our moderation strategy is to just ban your bank account.
3:01:41
>> And so if you break the rules on the platform, we can just block out the accounts that you've connected with.
3:01:47
>> That's so interesting because normally on like Reddit, you could have somebody that's angry and then they can just create they could be getting banned and just recreate accounts.
3:01:53
Yeah, it's like how would you create new account with a huge you have to set up a new bank account, transfer all your money over there.
3:01:59
Like that takes a long time.
3:02:01
>> And if you do that enough times, eventually you will uh make other people angry who will ask you why you're making so many bank accounts and we don't even have to worry about it. >> That's very funny. >> That's wild. >> How's growth been? What's the news?
3:02:13
How's uh are you monetizing yet?
3:02:13
I can imagine lots of different ways to monetize.
3:02:16
can see, you know, you you have interesting data that other social media companies need to kind of piece together through behavior and things like that.
3:02:26
Like I I imagine the big social networks try to build a profile to understand like what is this person's purchasing power? You guys get it.
3:02:32
You the users, you know, providing it.
3:02:37
>> Um but how are how are you thinking about monetization?
3:02:41
>> I think there's a couple of big strategies that we can try to go after.
3:02:45
Uh referrals is something that I've looked at for a while.
3:02:48
Uh if you look at a public company like Nerd Wallet, a lot of their revenue is coming from referrals to loans and mortgages and credit cards.
3:02:55
And from our position, if we have a bird's eye view into your finances, we're actually pretty well equipped to show you products that would benefit you financially.
3:03:03
Um so we're not just selling you something, but we're also trying to sell you something that makes sense with the type of portfolio that you currently hold. >> Yeah.
3:03:11
It's like, hey, we noticed you're not using leverage.
3:03:13
Did you know did you know that you could love her up?
3:03:16
>> I'd love to refer you to Harry Winston rare jewels of the world.
3:03:18
Discover the sunflower collection or maybe what are you reading?
3:03:24
>> I'm reading how to spend it.
3:03:24
It's the it's the wealthy section of the Financial Times that comes on the weekend.
3:03:28
Uh refer you to Vasheron Constaton the quest.
3:03:30
Vasheron Constanton celebrates seeking excellence for 270 years.
3:03:38
>> 270 years of doing better if possible. >> What were you doing?
3:03:40
What were you doing if possible?
3:03:42
These are going to be great referrals.
3:03:43
You got to call you got to contact the the ad salesperson at uh at at HTSI.
3:03:48
They got the graph diamonds ad in there.
3:03:51
This is going to sell like hotcakes when you go when you start monetizing.
3:03:55
>> That's the broad plan. That is the broad plan.
3:03:58
>> Uh before this, I was doing basically a bunch of different side project apps.
3:04:01
Two cents started as a side project. >> Sure.
3:04:03
And I was just trying to figure out something that could ship out the door three or four times a month or or a year and see if anything would get traction.
3:04:12
And so the early growth on Two Cents has been really amazing.
3:04:14
It's probably the most popular thing I've ever built.
3:04:17
Uh and almost entirely organic.
3:04:19
So it has come from Twitter on the timeline from other posters wanting to sign up and be on it.
3:04:23
Um I've actually gotten a lot of comparisons to this earlier app, Poster, >> which was popular a couple years ago.
3:04:32
Oh, >> I I invested in poster. >> Really? >> Yeah.
3:04:34
It was a wild It was a wild place.
3:04:37
>> Last but but it's so you know pe people are >> It's interesting.
3:04:41
A lot of people will use two cent that have never had an alt or an anonymous like account and I think it becomes extremely freeing for them to feel like they can have conversations online without being tied back to their LinkedIn, you know, or being tied back to their family.
3:04:58
And I and I do think yeah I just think you've tapped into something super interesting because money is so is just at the core of everyone's life whether they want it to be or not and giving people a place where they can talk about it freely.
3:05:12
Of course there's still going to be judgment.
3:05:15
Like of course there's going to be people on the app that are going to think a certain way about someone's financial situation or or you know what they're saying or or how they're spending their money. But it does.
3:05:24
Um I feel like the next uh I I feel like it'd be funny to build out uh I'm curious.
3:05:32
Would you ever build out like a feed of like the users kind of like if they obviously opted into it, but just like purchasing?
3:05:38
Uh I feel like I feel like a lot of people would would be very fascinated in that.
3:05:42
Um in in a different way than like Venmo used to do it, which I was like why is Venmo a social network?
3:05:48
you know, it's like I don't want >> like I don't want people to know what what I you know, whatever.
3:05:53
But >> yeah, this is on the road map.
3:05:56
We would love to have a feature where you can opt in your transactions, your recent transactions, and then almost quote tweet them and say like, I I bought this $18 shawarma at this bodega. It sucked. Here's a picture of it.
3:06:08
And it kind of proves that you did that, right?
3:06:10
Like you're not just saying it.
3:06:12
Uh and same thing for brokerage movements.
3:06:14
If you sell a bunch of Apple stock or whatever, you can write your due diligence and then also prove that you actually made that sale.
3:06:21
So, you're not just saying you did it.
3:06:22
We're proving it through financial history that it happened.
3:06:24
Uh, and obviously that's going to be entirely opt-in.
3:06:28
You can choose to show things or not show things, but it it'll be the only social network where you can have these types of conversations where you can prove that you're actually moving your money or making these transactions that you're claiming that you are. >> Very cool. >> Well, very cool.
3:06:41
Uh, speaking of money, have you raised any money? >> We have.
3:06:44
We have raised $3 million from Dragonfly and starting line. >> Congratulations.
3:06:51
>> And was that just announced today?
3:06:51
I didn't see it anywhere. >> It was uh yesterday.
3:06:56
>> The official two cents account on two cents increased by 3 million. Right. >> And so you saw it.
3:07:02
>> We are our spot on the leaderboard has jumped up uh a couple places which I'm very happy about. >> There we go. >> Congratulations.
3:07:08
>> What's What's the What's the number one spot on the leaderboard right now? >> Oh yeah.
3:07:11
Who's the richest >> right now?
3:07:12
We have well so I don't know because it's anonymous but they are at 26 million >> 26 million >> verified liquid. >> Wow which is crazy. >> Verified and liquid. >> That's pretty crazy.
3:07:21
>> My DNA researcher >> maybe maybe you got to get MS on there 8 million 333 every month.
3:07:29
You're like okay I know who this is.
3:07:31
Got $100 million contract.
3:07:32
Anyway, thank you so much for stopping by.
3:07:34
Uh great to meet you and have a great rest of your day.
3:07:37
>> Congrats on the round.
3:07:37
Thank you for having >> Bye. >> Cheers, Andy.
3:07:40
Up next, we have Gabe from Harvey AI.
3:07:42
Very excited to talk to him about legal AI and the impact of open source.
3:07:47
I want to know if anything changed this week for his business.
3:07:49
We will bring in Gabe from Harvey AI, the legal Hello. Welcome. How are you doing? >> What's going on? >> Good. How are you guys? >> We're great. Great background. >> Great background.
3:08:03
>> About to say >> is that mahogany? That's nice.
3:08:05
>> The official wood of business and law. >> That's mahogany. Some books.
3:08:08
It's got to look professional. >> Fantastic.
3:08:11
Um, what what's the latest uh g give us the update.
3:08:14
I have a bunch of questions that'll go all over the place, but give us the update in your world.
3:08:19
>> Yeah, so last week hit three-year anniversary.
3:08:21
Um, have kind of scaled up to 350 people, 500 customers, just hit 100 mil in revenue. >> There we go.
3:08:32
>> Love hitting love hitting the gong for revenue.
3:08:34
You know, we hit the gong a lot for hundred million dollar rounds, but it feels better when it's real customer.
3:08:40
>> We we have this silly soundboard where we play the over overnight success sound, but uh >> overnight success. >> Yeah, that one.
3:08:47
Um and usually it's because some founders been grinding for like 10 20 years and then they finally hit breakout success.
3:08:52
But like Harvey is kind of an overnight success.
3:08:55
What actually set you up for this?
3:08:57
Obviously, uh you were in a unique position to actually go after this opportunity.
3:09:01
this wasn't just something that you just lucked into obviously.
3:09:06
So give me a little bit of the prehistory.
3:09:09
>> Yeah, I I actually I started doing AI research in like 2012 and >> tried to do some other startups and so I think there was a lot of this experience of trying to build these companies >> without this technology.
3:09:21
Um, and I think I was at Meta on the large language model team right before Harvey.
3:09:26
And my roommate, who is now my co-founder, Winston, was an associate at a law firm.
3:09:32
>> And I was showing him kind of the GP3 models and he was showing me his kind of the legal work he was doing.
3:09:38
>> And I think it was pretty obvious these models were going to get much better.
3:09:42
Uh, and that seemed like a great application.
3:09:43
And then I do think there was like some factor of luck of you know raising from open AAI how good GPD4 was and then kind of really focusing on big law. >> Yeah.
3:09:52
So you add all that in then we can do the overnight success because it's like easy if you want to just grow really quickly just spend a decade researching a fundamental technology that will change the world.
3:10:01
Uh >> anyway um what uh yeah uh so so much to go into here. >> Yeah.
3:10:08
I mean I one one thing I want to you know you at this point I'm sure are talking to or have closed all you know pretty much all the top law firms in the United States.
3:10:17
Uh I'm sure the reaction internally at all the different firms.
3:10:23
I'm sure there's some excitement.
3:10:23
I'm sure there's uh there there's clearly excitement otherwise they wouldn't be uh you know signing up uh and becoming customers.
3:10:32
But I posted something uh last week.
3:10:34
I was in New York and I spoke with uh I was speaking with a lawyer randomly and he was telling me about their AI adoption uh internally and he said and uh this was his point of view.
3:10:47
He said adopting too much AI will hurt our bottom line.
3:10:49
Uh and I po I posted that note uh yesterday and it sparked a big conversation.
3:10:54
Um, you know, the obvious response is that you don't pay great law firms and lawyers for the execution.
3:11:03
You pay them for the overall product and the sort of like guidance and advice and strategy and and all these other things.
3:11:10
Uh, it's not just like the raw like generation of documents or reviewing contracts and things like that.
3:11:16
So, how how do you know how are um give us kind of the overview of how different firms are reacting and sort of leveraging AI and then I want to hear how you think law firms uh might need to like reinvent themselves and like kind of even adopt new business models and approaches and things like that over time. >> Yeah.
3:11:36
So, it's definitely like a wide range both law firms but also kind of individual partners within law firms.
3:11:44
And so we have, you know, firms that are still in the let's test this out.
3:11:46
Let's see what to do with this.
3:11:49
And then firms that are we have already co-built software products or models with them and they are we are revenue sharing and selling that to their customers.
3:11:57
So there is kind of the full range and yeah, I think it'll be interesting to see how it plays out.
3:12:03
I think my guess is long-term where this is going is I think your point is exactly right.
3:12:10
Like I actually think if you look at partners billables, they're actually undervalued where it's like if you want to do a massive public merger, that partner is worth much more than 3,000 an hour, but it kind of gets subsidized by all these associate hours.
3:12:23
And so I think there will be some changing of, you know, how you charge for these.
3:12:27
Um, but so far I think we're still kind of early days in that conversation and it's much more how do you, you know, get adoption?
3:12:34
How do you start upskilling lawyers to use this technology?
3:12:36
Um but do have a lot of fun. >> Yeah.
3:12:39
>> Yeah. The interesting thing I think you know we obviously have a bunch of founders uh that uh watch uh the show and I think it's interesting to look at the invoices you get from your law firm and and just like look line by line
3:12:53
where was I getting like real value and legal advice and strategy and all these things that are extremely high leverage and where was I paying to like recreate a variation of this document or fix a punctuation error and things like that. And obviously you can't see exactly but
3:13:08
And obviously you can't see exactly but I it is easy to imagine in the future where in the same way that you have a 100 100x engineer today that's using uh you know cognition devon or or and windurf or claude code or or whatever variety of cursor etc where they can be ultra high leverage because they effectively have an army of people you know working under them uh agentically.
3:13:33
I think you'll see that in in uh it's hard not to imagine that happening in in law where you have this like incredible individual player who's able to like produce potentially an order of magnitude more work uh in the very near future. >> Yeah.
3:13:49
And one thing we're also starting to think about is like it's always interesting to ask why do you have this billable model structure in the first place?
3:13:56
And I think one big problem is pricing legal work.
3:14:00
And so like the reason you have this model is like these projects are so complex that it's actually impossible to do fixed fee without you know this technology where it's just how much does it cost to do this merger.
3:14:12
It's like you're going to have all these things that come up.
3:14:14
But I think as these models get better the same way it's hard to predict like how long will it take to fix this bug.
3:14:19
But now with these models you can kind of look at a codebase and say oh actually I can tell you you know some good error bounds.
3:14:26
I think there's things like that you can start exploring that make more of these new business models interesting.
3:14:32
>> Have you seen Have you seen lawyers in big law spinning out and and building firms from the ground up to try to disrupt themselves and create new models?
3:14:39
I mean, we've seen uh we've had the founder of Crosby on which is like they're building a firm themselves and like focusing on like a few specific types of of contracts initially.
3:14:47
And I could imagine it's kind of hard if you have a a law firm with thousands and thousands of lawyers, it's hard to like totally change the business model where if three people spin off and they come to you at Harvey and say like we want to leverage this ground up, build a firm around this.
3:15:02
Are are you seeing that at all?
3:15:05
>> Yeah, one of the fastest growing I think they might be Amla 200 firms now is actually partner only and so I think this model is I think that the challenge is it just depends on the type of legal work you're doing.
3:15:17
But this is also traditionally like not traditional in the past couple years what uh firms like PWC have also been doing of how do you bundle this legal work and provide alternative >> ways.
3:15:26
So I think some of this work is is getting unbundled and with different models you can kind of tackle different parts of the legal work.
3:15:33
>> How much how much do you guys care about models getting more intelligent versus just delivering on the current capabilities?
3:15:42
Yeah, I think for us the big challenge we definitely still have is like the models aren't good enough to do the very complex legal work.
3:15:48
And so I think for us, you know, Sam has the quote of like try to build some company that like as the models get better, your company gets better.
3:15:56
And I think we are very much in that position where it's like >> I think as amazing as these models are and I think lawyers get a lot of value, we still have so many use cases where it's just like the models can't draft these very complex like merger agreements and things like that.
3:16:09
they can't look at these massive re case law research corpuses or discovery corpuses or data rooms and like really understand them.
3:16:17
And so I think there's a bunch of room both for the foundation models to get better but also we're starting to think about like can you you know custom build these reasoning models given this kind of specific data you have.
3:16:26
So I think there's huge room for improvement for the models.
3:16:30
>> What about uh what about the back office?
3:16:31
There's a lot of costs uh that go into law firms that are that are non-legal work, operations, billing, you know, all all that.
3:16:39
Uh is that something is that a focus at all for you?
3:16:41
Is that something you think about or is there just enough work uh to be done uh on the client side?
3:16:48
>> Would you do like a legal billing product too?
3:16:51
>> Yeah, I mean I think that's something we've thought about of you know partnering with the folks doing that in the future.
3:16:55
We've had law firms ask can you you know help us automate parts of how we do billing.
3:16:59
We have a bunch of firms that just buy Harvey seats to do some of this back office work again.
3:17:03
And then there's clients that have asked about, you know, can you help us build spend management, things like that.
3:17:08
But I think right now the focus is still kind of building the product for for lawyers for law firms.
3:17:15
>> Uh we have a question from the chat.
3:17:15
Is the company named after Harvey Spectre, the fictional lawyer from Suits, or Harvey Dent, the Batman villain who I think also had a law degree? >> Uh Harvey Spectre. >> Harvey Spectre. There we go. >> Makes sense.
3:17:29
It's a great it's a great character.
3:17:31
Um, I want to talk about costs.
3:17:33
Obviously, tons of revenue coming in the door.
3:17:35
Also, we're seeing this weird phenomenon.
3:17:37
Maybe it's not that weird, but like with test time inference reasoning, you want to put, you know, GBT, what was the ARGI?
3:17:43
They were putting $2,000 of inference behind every task just to crack that puzzle.
3:17:48
If I'm, you know, coming to you and I want, you know, to really make sure that the AI is checking its work fully, I'm probably want to put a ton of tokens behind that.
3:18:01
Um, what does the cost structure look like?
3:18:03
How does that evolve over time?
3:18:05
Um, what is what are the relevant changes that could happen and changes in the landscape?
3:18:10
We saw the open source model come out from OpenAI.
3:18:12
At the same time, even if you're running even if you switch to open source today, you still have to pay for energy and GPUs and stuff.
3:18:19
So what yeah how does the cost side of the business evolve over the next couple years?
3:18:24
>> Yeah, I think our bet kind of from early on has been focused much more on like capabilities.
3:18:29
These models are going to get cheaper as you scale get economies of scale you can kind of solve these problems.
3:18:34
I would say right now our cost structure is similar to >> um you know if you're using like a chat GBT where >> you know that gets amvertised over the task you have some tasks that are low compute some that are a lot.
3:18:45
I think legal is actually one of the very unique domains where you have these tasks where I want to draft a motion and typically this is going to cost $250,000.
3:18:53
I want to do document review and this can cost a million dollars.
3:18:58
And so you have these specific problems where you can actually just run models over every single document, throw just a ton of compute at this.
3:19:05
And so we're starting to kind of explore like what do those different models look like if you're doing tasks like that.
3:19:10
Um but yeah, >> lessons from Atrium, lessons from Clear Spire, lessons from binding a actual law firm to a technology company.
3:19:21
Seems like it hasn't doing that certainly hasn't hurt you, but uh did you know that >> I'm sure I'm sure you had a lot of investors that don't why don't you sell the work instead of the software? >> Exactly.
3:19:35
We we actually we actually had the opposite.
3:19:37
the opposite. Like when Winston and I started the company, we talked to the founders of Atrium and like 30 of the folks that worked at Atrium and actually Jason Quan who at the time was the GC of OpenAI was at Y Combinator when they did Atrium and Sam was as well and so we kind of like mentioned that and they
3:19:56
were like you guys should focus on building tech business and for us it seems like the scalable play here is like we don't want to build a professional service firm ourselves we want to enable every law firm every professional service firm to kind of become the next generation um of firm. >> Yeah, it makes so much sense. Microsoft
3:20:14
>> Yeah, it makes so much sense.
3:20:14
Microsoft Excel, their team didn't build an investment bank and yet it's used by every investment bank and it's and that will continue for a long time.
3:20:22
Anyway, I think we have to jump to the next guest.
3:20:25
Jordan, thank you so much for coming on. This was really fun.
3:20:28
>> Congratulations on all the growth. Huge.
3:20:31
>> We'll talk to you soon. Bye.
3:20:33
>> And up next, we have another massive gong moment.
3:20:36
Let's bring in Kareem from Clay.
3:20:38
We'll get the update from him. Welcome to the stream. Kareem Clay AI. How you doing? >> Hello. >> What's going on? >> How you doing? >> Give us the latest. Give us the update.
3:20:53
What's new in your world? What do you do? Break it down for us.
3:20:57
>> Can give you all those things. Excited to be here.
3:20:59
Um, >> great to have you. >> Yeah.
3:21:01
Well, today we announced that we raised 100 million from Alphabets Capital G. Congratulations. >> Thank you. And a $3. 1 billion valuation. So, >> wow. Three Jet Blues. That's crazy. Amazing.
3:21:16
We've been dogging on Jet Blue a little bit today, but that is fantastic. Congrats.
3:21:21
>> Classic overnight success.
3:21:21
You started the company like a few months ago.
3:21:25
>> Yeah, like uh eight years ago. >> Yeah.
3:21:27
I was going to say so the story so so give us give us like the journey how you got here because I think like you guys have been a massive beneficiary >> of of LLMs from what I know over the last few years but it was not a uh was not an overnight success >> I'll call it a spiral >> um yeah I mean we started the company with the idea of how do we give the power of programming to an order of magnitude more people Mhm.
3:21:57
>> And I was saying it took me some time to reformulate that to how do we give that to what we call go to market engineers.
3:22:05
So it's like half of the company can't code but has all of these ideas of how to grow the company.
3:22:09
Um and Clay basically gives them the power to program revenue instead of just program software.
3:22:16
>> Let's make that a lot more concrete.
3:22:16
>> Let's make that a lot more concrete. uh there's been this cool wave of uh designers going from 0x engineers to 1x engineers and that's had a lot of uh a lot of benefits in organizations but what does that actually look like concretely on a go to market team is
3:22:32
that just generating emails faster managing a um a CRM like what are we actually talking about in terms of detail >> yeah the actually like most important part is who should you reach out to that's actually like I would say 60% of kind Like there there's two ways to grow your company. Either you find new
3:22:50
Either you find new customers or you expand existing ones.
3:22:53
If we just talk about finding new customers, 60% of that is finding the right person, right?
3:22:57
And then kind of like reaching them at the right time is another 20%.
3:23:01
So what we do is um let me give you an example.
3:23:05
One of our customers, they have a ton of people just going on Google Maps, looking at all the different locations that they sell to, finding warehouses, and then manually counting the number of parking spots that uh that warehouse has because that's a good indicator if they're a good customer.
3:23:22
And so we can use Google Maps API and LLMs to do that counting for them.
3:23:27
>> Oh, that makes a ton of sense. >> Yeah.
3:23:28
So really most of it is about like account selection and finding the right people.
3:23:33
And then the second part is, you know, did they just raise a round of funding like us?
3:23:37
Was there some kind of new news story that uh did they just hire a few people in a department that you're selling to?
3:23:44
And it's very specific to what your company does in their product. >> Got it.
3:23:49
Is this uh every I've I've asked this question on the on the show before, but uh it feels pretty common that you know some random private equity firm will just be spamming people on the internet trying to buy their companies.
3:24:03
Oftent times there's probably good targeting.
3:24:05
Oftent times there there's bad targeting.
3:24:06
How close are we to just like eliminating those those emails that are just kind of uh those out that outreach the spray and prey outreach?
3:24:15
When when is spray and prey gonna gonna going to end? >> I hope not.
3:24:18
I mean, I think that that's kind of like one of our top goals is if you actually I think you could think of it as what if you actually put in the effort um and the thoughtfulness into figuring out who actually wants your product.
3:24:35
One, you reduce spam and two, you actually increase like your own productivity.
3:24:40
It's just that that's hard to do at scale.
3:24:42
And the best companies like RAMP, like there's a lot of companies who figured out how to do that internally.
3:24:49
What Clay is doing is giving that to every company.
3:24:50
And really what that means is that businesses can find each other um faster and more accurately.
3:24:58
So I think it should end up benefiting everyone. >> That makes sense. Anything else? >> $100 million.
3:25:05
Where how are you going to spend it?
3:25:09
>> Um hopefully we don't spend it.
3:25:13
Yeah, always a good clay.
3:25:14
>> Yeah, I think that um one of the key like really exciting things about clay is that we have this huge community >> um that has emerged around us.
3:25:22
So there's uh clay agencies, so people who implement clay. >> Oh, that makes sense. Yeah.
3:25:29
>> There's like 60 clubs in 29 countries where people meet up to talk about different techniques because if you think about it in sales, like you're always figuring out how to be creative, how to be unique.
3:25:38
Um, and Clay is a tool that lets you do that.
3:25:41
I almost think of it like Ableton is for music or like you said, Figma is for designers.
3:25:45
Clay is for go to market teams. >> They're doing deals. >> Interesting. >> Exactly.
3:25:50
So, we want to use that money to support that community.
3:25:53
So, we're having a conference actually sculpt um in uh September in San Francisco.
3:25:58
So, we need to we're going to do more events like that.
3:26:03
Um, and then there's a lot of investment into the product there.
3:26:05
We're just touching the surface of what we can build. >> Yeah.
3:26:09
Are is there any functionality to share workflows or create some sort of marketplace for workflows like uh you know yes there are agencies on top of Shopify that do uh design but then there are also templates and so you gave some examples of you know uh new funding announcement in my category that seems like something that I could be able to just pull off the shelf and not even not even build from scratch within Clay. >> Yeah, totally.
3:26:35
I feel like you you should really join our team.
3:26:36
This is >> this is exactly >> where you're going.
3:26:40
I'm leaving your road map. Yeah, >> sorry. We'll leave it there.
3:26:45
>> Yeah, we'll leave it there. >> Well, good luck.
3:26:46
Uh very exciting time and congratulations on the massive round. >> Awesome. >> Appreciate it.
3:26:51
Thanks for having to talk. >> Bye. >> Good stuff.
3:26:54
Well, John, I got to get on with London and I'm sure you got to get on with Taipei.
3:26:59
>> I do have to get on with Taipei.
3:27:01
>> Why don't we end it there?
3:27:01
Thank you for tuning in to the show today.
3:27:03
Thanks to everyone in the chat. I agree.
3:27:05
The deeper the V-neck, the more funding you get. So, >> good strategy.
3:27:10
>> It's a good good I didn't say it, but I think it's true. $100 million deal.
3:27:16
Really deep V looking good.
3:27:16
I I you know, >> the next round is >> Yeah. Yeah.
3:27:21
It was funny because we I clearly you could see the bottom of the V-neck if we had shown the full screen, but we had a ticker and so the ticker made it look like you don't know where that thing ends.
3:27:29
It could just keep go forever.
3:27:31
Um, but Palmer Lucky has made a vest.
3:27:34
>> Palmer Lucky has made the Hawaiian t-shirt iconic.
3:27:36
Maybe Kareem makes uh the the Deep V iconic at Clay. He's a good energy. I I was I was into it.
3:27:44
>> Anyway, >> awesome folks.
3:27:46
>> Thank you so much for watching.
3:27:46
Leave us five stars on Apple Podcast and Spotify. Leave us some reviews.
3:27:51
>> Leave us some reviews. Uh send us some notes.
3:27:53
Send us some reply to some threads.
3:27:55
Whatever you want to do, >> whatever you want. >> Get in touch. We'll talk. >> Have a great evening. Back.