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5:04
Jord's in front of the horse.
5:04
Today is Thursday, October 9th, 2025.
5:05
We are live from the TBN Ultradome, the temple of technology, the fortress of finance, the capital of capital.
5:12
>> Uh today I want to tell you about ramp. com.
5:14
Time is money, save both, easy use corporate cards, bill payments, accounting, and a whole lot more. all in one place.
5:18
That's why the horse is wearing the yellow hat.
5:20
Also, the show is made possible by Reream, one live stream, 30 plus destinations, multiream, reach your audience wherever they are.
5:27
Um Dylan Patel took to the timeline to say he's going to be dropping something huge in 24 hours.
5:32
This was um what this was 19 hours ago.
5:36
We have five hours to left to go.
5:40
4:00 pm Pacific on October 9th.
5:44
He will drop something that will reshape how everyone thinks about chips, inference and infrastructure.
5:48
It's d it's it's directly supported by Nvidia, AMD, Microsoft, OpenAI, Together AI, Corewave, Nevius, PyTorch, Super Micro, Cruso, HPE, TensorWave, V VL who >> sg Lang etc.
6:01
If you are pressed for him to drop it uh I got the whole briefing and it is very cool and I do think it will be huge.
6:08
Um, and uh, it's it's uh, in classic semi- analysis fashion, it is very uh, rigorous and detailed and uh, I think will be very very interesting to dig into when it drops.
6:20
In the meantime, I have something that's the opposite of rigorous.
6:22
Uh, it's completely it's the other side of the of the midw curve.
6:25
It's uh, just complete uh, slop analysis, but I think it's a useful >> it's a good thought exercise. >> Yes.
6:33
>> Yes. So I said uh tokenadjusted I E I E I E I E I E I E I E I E I E I E I E DA of course a nod to uh we works community adjusted IBIDA to be clear no one's doing this uh this is something you should not do you should not value AI companies as a multiple of the total amount of tokens they're generating but
6:49
as soon as I saw that open AI news they're generating six billion tokens a minute they're worth 500 billion I see 500 I see six I start dividing those I got to know what the valuation multiple is how much am I paying if I'm buying a dollar of OpenAI stock for a stream of tokens. Of course, this is nonsense
7:07
Of course, this is nonsense analysis because tokens have various values, they're growing, produce, >> different profit streams, different costs. Exactly.
7:15
There's a whole bunch of things, whole bunch of reasons why you shouldn't do this, but I thought it was interesting to do it anyway because I like silly things.
7:21
Um, and so I think of this more as like like there's a lot of bubble talk.
7:27
We aren't yet in the eyeballs phase of this.
7:29
com boom, but if we start seeing this Yeah.
7:32
If we start see bubbles so much, we just call it bub talk. >> Bub talk. Exactly.
7:37
Um, but I wanted to give a little bit of history on the 1999 bubble and uh how valuations were processed then. It's pretty fascinating.
7:48
So uh back in the late 1999 uh in the late 1990s uh eyeballs became a hilarious but deeply important KPI for tech companies. It's a very funny name.
7:58
Uh, but it was basically it was basically just audience size, unique visitors, page views, time spent on site.
8:03
These were all non-financial, non-GAAP metrics that were meant to serve as proxies for eventual earnings and value creations.
8:10
Revenues were tiny and earnings were always negative.
8:12
So, eyeballs were the best metric that folks had to understand who was growing, at least relative to other >> dropout posts back then.
8:21
Somebody sends around physical mail, they're like, "I'm dropping out of college. I have 10 eyeballs." 10 eyeballs. Yeah. >> $100,000.
8:32
>> I mean, we we we see the charts now.
8:34
Fastest $200 million in revenue.
8:36
Obviously, that's a very good, very strong business metric that uh assumes that you will be around for a while if you're generating a lot of revenue very quickly.
8:43
>> Time to 100 too is also very old news.
8:46
Obviously, everyone's focused on time to a billion.
8:47
billion in >> was recorded reported that cursor will be somewhere around there by the end of this year. >> Yeah.
8:54
And so that's like what two years maybe three from >> was it 2022?
8:58
>> They were technically any sphere before but really you should start it as like the launch of cursor the product probably.
9:03
Um but they've been on a tear and but it's way different to look at the size of a business as if I'm buying a dollar of of stock it's tied to a stream of revenues which could be very profitable uh versus just eyeballs.
9:14
But this is uh audience size has uh you know been around for decades even in the '9s at that point in the marketing world.
9:24
And so it was just kind of pulled over and a lot of this came from Mary Mer.
9:28
She's now at Bond Capital.
9:28
Uh she was the hot shot analyst of the day at Morgan Stanley.
9:34
>> And this is what's interesting.
9:34
So we think of eyeballs in the in the dotcom bubble.
9:39
We think of it as a 1999 phenomenon.
9:41
In 1996, she wrote, "What's the value of an eyeball or an ear?"
9:47
Three years before the 99 bubble got crazy.
9:50
Uh there's a that you can read her whole internet trends report on uh script, which is pretty cool.
9:55
And then three years later, she was profiled in the New Yorker.
9:58
We actually read the whole profile on this show about a year ago.
10:01
And uh that was a really interesting piece.
10:03
And the name of the piece in the New Yorker was called The Woman in the Bubble.
10:08
So, the New Yorker like the bubble talk was not like you think about the bubble talk right now on X and it's like it's bubbling up really quickly, but like the New Yorker is not writing profiles on the AI bubble yet.
10:20
They'll probably get there a few months just like what we saw with French French TV.
10:23
Like like the legacy media takes a little bit longer because they do a lot more research to write a profile.
10:26
It just takes months to write a profile. >> Yeah.
10:29
It's interesting how I mean social feeds just are are perpetually months ahead of headlines, right?
10:35
And so we're seeing every single day I see somebody outside of X or outside of Teapot or or the the tech community on X calling it a calling it a bubble saying you know when this thing blows up and you guys crash the global economy like it's all going to be so obvious.
10:54
>> Yeah, it's just it's just starting on the most bleeding edge.
10:56
It's still not in the pages of uh of the New Yorker uh yet.
11:01
It was in uh 1999 the the title of the article uh about Mary Mer was the woman in the bubble.
11:09
Uh and this is what's extra interesting to me.
11:11
It took 11 months more after that article for the stock market to actually peak.
11:16
And so in that article in that profile of her of Mary Mer in the New Yorker, she's saying it's a bubble. It's crazy.
11:24
I've never been seen anything like this in my career.
11:28
and she's kind of grappling with the fact that it's her job to analyze these dot companies, but everyone can tell, even her, she can tell that it's a bubble.
11:38
And so, you're in this weird dynamic where people can can say we're in a bubble, but they don't know exactly.
11:43
You can't stop it because it's a it's animal spirits and it's a force greater than any one person.
11:47
So, in 1999, eyeballs were highly valued.
11:50
Let's get into some numbers.
11:52
market was pricing traffic at around $700 per monthly unique visitor.
11:58
So if you got a million unique visitors on your website, you could sell that company for $700 million.
12:07
And I know people that did and they're venture capitalists now and they're retired and they got extremely lucky by some concerns.
12:14
They sold the top basically and they did very well. >> $700 per visitor.
12:19
>> $700 per monthly unique visitor.
12:19
And that's not even somebody that has an account.
12:24
>> Yeah, >> that's just somebody that visited >> chooses to go to the website.
12:28
>> I mean, you could do the math for us.
12:28
It probably be around there.
12:32
>> But, uh, >> no, it's it's worth noting that we haven't gotten there >> yet at all. >> No, not at all.
12:38
Now, to be fair, that $700 per monthly user, that analysis was heavily weighted by Yahoo, which was uh by far like the largest uh platform that was that was driving this metric.
12:49
If you pull Yahoo out, you you get a much lower number around 400 per unique visitor, but that's still a high.
12:56
Uh, and then for M&A for smaller companies, it's not like everyone is actually comping to the Yahoo number.
13:02
Um, it was more around, it was closer to $150 per monthly unique visitor, but still, you know, you get a million unique monthly visitors and you sell the company for $150 million in 1998. That's pretty good. >> Yeah.
13:17
And it's worth noting how much harder it would have been to get a a visitor back then.
13:19
And it's not like you could just run if if you were getting val if your business was being valued at just getting somebody to your site and they were putting a value on that today.
13:27
You could just run traffic to it like crazy through all of you know search engines, through social media, through organic content, through Tik Tok.
13:34
So it was much harder to get somebody to your site. >> I don't know.
13:38
There were a lot of crazy like there's a toolbar that's installed that automatically routes traffic. >> Sure.
13:44
I'm just saying it wasn't quite as programmatic.
13:46
A lot of people would pay Yahoo for a higher ranking because it was a portal, not necessarily a search engine was.
13:52
>> But I'm just saying everybody didn't have a mobile device in their pocket where now they're probably visiting order of magnitude, you know, multiple orders of magnitude more websites on a daily basis.
14:00
>> Yeah, you're 100% right.
14:00
Uh if you if you apply this uh metric to OpenAI, I had to uh OpenAI has 800 million weekly active users and is worth 500 billion.
14:13
So that's >> and I believe but but I believe they're counting this as like people that have created an account, not not just a website visitor.
14:20
>> Wildly different, way stronger uh way stronger audience.
14:23
Uh and that's still at $650 per eyeball.
14:24
That's way lower than what the Yahoo number and the average number was in the in the do bubble.
14:32
Um and you could also use the estimated 6 billion estimated visits for OpenAI uh and get $83 per visit if you're trying to get a little bit closer to the comp.
14:42
So, you're still off by an order of magnitude there.
14:43
Um, again, these are all nonsense estimates.
14:46
Uh, I did want to flip them around and go towards token generation instead of a like if you thought about a dollar of OpenAI equity as buying a stream of token generation instead of a stream of discounted future cash flow, which you should not do.
15:00
Uh, you could estimate something like a 22x ratio between valuation dollars and tokens generated per minute.
15:09
And you could also flip this around and estimate that for a $100 of equity, you're the owner of an annual stream of 2.
15:16
3 million tokens that then need to be sold and eventually drive profit from.
15:22
Uh that doesn't seem that crazy to me. I don't know. A lot of it depends. Uh 2.
15:26
3 million tokens right now would sell for what is it 10 20 bucks or something?
15:31
Is it's $10 per million tokens for the higher high end >> somewhere around there. Yeah.
15:35
Um so so like and of course like this is extremely silly because so can tokens are sold for a variety of prices.
15:41
Token volumes are growing exponentially.
15:43
Uh token generation cost is falling.
15:45
This is funny math but I like funny things.
15:49
And so uh I hope this doesn't show uh the most important thing is that I hope this doesn't show up in sellside uh analysis.
15:55
And also I also hope that I don't hear whatever the >> a founder that I saw posting in the last 24 hours that was trying to get people to focus on site visits which I don't think is >> and I'm not going to name the person but >> well >> uh but again it it sophisticated investors today or even not so soph sophisticated investors today are not going to put a lot of value on on just pure site visits. >> Yeah.
16:22
Well, uh, >> before we move on, let me tell you about Privy.
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16:33
Um, in other uh in other data point about the incredible growth of these properties, uh, Bill Peebles, who's coming on the show tomorrow, uh, from OpenAI said, uh, Sora hit 1 million app downloads in less than 5 days, even faster than ChatBT did, despite the invite flow and only targeting North America.
16:54
Team working hard to keep up with surging growth, more features and fixes to over moderation. >> It's worth noting.
17:01
So if you look at the the charts on the app store in the top free apps you have Sora Chatbt Gemini >> T Dating Threads and McDonald's >> McDonald's >> and the top paid apps are Shadow Rocket, Hot Schedules, Anki Mobile Flashcards, Procreate Pocket, Tonal Energy Tuner, >> and Auto Sleep Track Sleep.
17:25
>> Wow, I feel like app rank six apps you've never heard of.
17:28
And then and then again it's still worth noting te dating just still in the top five is actually insane.
17:37
>> I see them as like wildly different markets.
17:39
I almost see them as the free apps are venturebacked hyperscaler multi-billion dollar multi-t trillion dollar company efforts and the paid apps are much more like lifestyle businesses.
17:51
They're probably generating cash flow.
17:51
I feel like all of those founders, they might be part of a rollup or something, but they're thinking about it in much more financial terms than just go go operate in some winner take all market.
18:02
>> Seems like there's alpha right now being a ventureback business and just making a paid app.
18:06
So if you want seems way easier uh 10 times easier to >> I wonder how cheap you can make your app.
18:12
Can you make it a dollar?
18:12
Can you make it one cent? >> $2.
18:14
99 I think is what the few of these are.
18:18
>> Um Anky Mobile must be printing.
18:18
And they have their app is $25 and it's uh top three paid apps in the world, right?
18:26
>> If you're looking for an app that you can get started for free with, get Figma.
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18:32
Um, uh, Greg Brockman was talking about move 37.
18:36
This is the big question in AI.
18:38
When will we see a Lisa doll move 37, a truly novel strategy in Go that DeepMind was able to achieve?
18:47
When will we see that in text?
18:48
when will we see when will we see that in image?
18:49
When will we see that in scientific research done by LLMs?
18:51
And Greg Brockman uh was on a podcast and said uh on move 37, I do think next year we will have some incredible mo models.
19:02
The milestone I am most excited about is having models that can solve hard problems.
19:06
And the analogy that I like to make is think back to Alph Go.
19:08
You know, move 37 that changes people's understanding of the game. Imagine that in coding.
19:14
Imagine that in material science.
19:16
Imagine that in medicine having real breakthroughs that are either potentially the AI by itself or the AI assisted with top humans.
19:23
I think we'll start seeing that.
19:26
And so we've seen a few examples of now uh you know top tier mathematicians kind of going to GPT5 and saying that there's breakthroughs.
19:37
Tyler, what's your read on how close we are to uh a move 37 like breakthrough in a non, you know, sim perfectly simulated environment like go?
19:47
>> Yeah, I mean it's hard to say.
19:47
I think first what we'll see before um we see like completely novel breakthroughs.
19:52
It's just like um being more helpful to the top people.
19:54
So like you saw uh Scott Aronson talked about this a couple weeks ago. >> Yeah.
19:59
Um he said GT5 like helped him get past some roadblock that he he said he you know he he would have figured it out if he spent another hour or two or maybe ask one of his grad students um but it just like helped speed him up.
20:09
So it's always hard to figure out especially with with these novel breakthroughs because people want to like take credit for them right if you're going to if it's something that's worth a Nobel Prize >> someone is going to want to like take credit so they might try to like hide the >> the the impact they are. Yeah, maybe.
20:25
>> So, it I think it's hard to see um hard hard to figure out the exact like attribution that you can do to LLM. >> Yeah. Yeah.
20:32
>> Yeah. Yeah. It's interesting that he's kind of not drawing a a super clear line between AI by itself versus AI assisted with top humans because you have to imagine that a vast majority of no modern Nobel prizes are computer aided
20:46
just in the sense that that like the lab notebook was digital and like the pipetting machine was automatic and like anything that you're doing to win a Nobel Prize you're going to be leveraging computers now just to speed up your workflow. That's very different
21:00
That's very different than than just prompt.
21:04
>> I did get a >> figure out a novel science.
21:06
>> I got a I got a lunch uh with with a a physics professor right after the GPT5 launch and he was able to oneshot a problem that he felt uh he he estimated would have taken him three months uh to complete uh if he was just doing it himself, which uh which >> Yeah. Yeah. Like that's interesting.
21:27
It's just it's not move 37 because move 37 was something that Lisa Doll felt that he would never have come up with not in three months.
21:35
It was not something that was even on his radar. >> Totally.
21:38
So, I'm not putting it in the same bucket and and neither was he, but it was again it was uh it wasn't doing anything especially novel.
21:45
It was just doing a massive amount of work in, you know, 20 minutes. >> Yeah.
21:50
The but the impact is still massive.
21:52
Like if you even if you're just like, "Okay, we're going to speed up the the level of scientific discovery by 2%."
21:57
Like that's just massive.
21:57
So, um we don't necessarily need move 37 to justify all the work that's going into AI.
22:05
Be super excited about AI.
22:05
Uh like it's fine if it's just if it's if for a long long time it's just an assistant >> because why not?
22:13
Why why not speed things up? Yeah.
22:16
>> Anyway, if you want to speed up your development workflow, head over to Cognition.
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22:26
>> Spike is sharing there's nothing happening in America besides AI.
22:27
And there's an article that says without data centers GDP growth was.
22:32
1% in the first half of 2025.
22:36
>> Harvard economist says uh that is brutal and not super surprising.
22:40
At least uh at least we're able to admit that here that uh you know AI capex is driving GDP growth. >> Yeah.
22:51
>> Um and uh there's again that just massive disconnect between >> the real economy and our our little bubble. >> Yeah.
23:00
I wonder I I would love to know more about breaking down h how they're counting like data centers in this GDP growth number.
23:08
Uh is it specifically like the data center construction? Is it chip production? Is it energy production?
23:14
Is are are any of the like revenue streams from the foundation models actually moving GDP at this point? It seems like maybe not. Um I don't know.
23:25
This does seem like a uh like a higher level analysis, but um certainly um I don't know.
23:30
It'll be interesting to see.
23:35
>> Um well, Lewig says uh had a had a great uh post that we got a chuckle out of this morning.
23:40
You said wearing my TVPN jacket and thinking cap from Enthropic. Look at my OpenAI coin. I'm such a good boy.
23:46
Did you know I got an OpenAI coin?
23:48
It's because I gave them lots of money.
23:50
Anyways, I'm a 15-year-old dropout and I'm building the first $1 billion >> evaluation.
23:56
>> Evaluation solo company in the world. >> Evaluation.
24:00
>> Um, anyways, having having a lot of fun here.
24:03
Uh the the anthropic cap and TBPN jacket combo is is uh >> yes >> is is pretty pretty on the nose.
24:11
>> Lwig is a master of the wojack.
24:11
This reply to you is remarkable.
24:13
Not like the rest part one.
24:16
Where did you find that yellow token?
24:18
Where did you find that jacket? Thinking cap.
24:20
The the the cap with the helicopter wheel on top is underutilized. >> Yeah, underutilized.
24:27
Nobody We don't know how to make these hats in America.
24:30
Yeah, that was kind of the the the the the most iconic tell of like the I don't know 2005 nerd is very like uh I don't know just kind of like you're hanging out on some sort of corporate campus like a Google. It's multicolored.
24:44
It's very uh it's very sophomoric.
24:46
Um no one's brought that back and reappropriated it.
24:50
So maybe someone should maybe maybe someone should make it uh make it trendy. >> Yep.
24:56
>> The the spinning wheel cap.
24:56
Well, in other news, Francois Chalet uh is very impressed by the new tiny recursive model from Samsung.
25:04
Uh a tiny 7 million parameter model just beat Deepseek R1, Gemini 2.
25:09
5 Pro and 03 Mini at reasoning on both ARG AG1 AGI 1 and ARC AGI 2 and uh the model is 10,000. >> It's ARC AGI1. >> Oh, okay. Okay.
25:21
I was like I'm I'm not familiar with Yeah, it is odd because I I I felt like at the end of this it looked very AI generated because this isn't just scaling down.
25:28
It's a completely different, more deliberate way of solving problems.
25:31
So, it feels like AI generated text, but uh the the typo there is a little bit odd, >> but it's cool to see Samsung getting in the game here. >> Yeah, it is. It is unexpected.
25:39
I I feel like a lot of the labs are are are pretty excited about ArcGI.
25:44
Obviously, XAI did very well with Groc.
25:46
Uh, and it seems like the the level of respect for performance on ArcGI is pretty high right now. Yeah. Uh, Tyler had a chance.
25:56
Are you still at the top of the leaderboard or have you been unseated on RKGI?
26:01
Uh, if you're just tuning in for the first time, uh, RKGI is a is a benchmark for uh, uh, AI systems, but we we put Tyler on the task and he was able to defeat all of the systems.
26:13
actually one of the top humans >> and and and I think he was in the top 10 at the time, but he probably he should have fallen at this point because so many people >> I would hope so.
26:21
Uh liquidity says uh Prime might need to rebrand to subprime.
26:27
Uh apparently in 2023 they sold 1. 3 billion in product.
26:30
It's on pace to do only 300 million in 2025.
26:32
I don't know how this happened. How does this happen?
26:37
I mean I do know so so what Prime did which was genius was they created a >> a sports drink. Okay.
26:44
>> And then they also created an energy drink.
26:46
They look exactly the same.
26:46
And so I think that children >> were buying the energy drink.
26:50
Their parents think they're just buying a like a Gatorade alternative.
26:56
>> And meanwhile, the kid is getting ramped up on hundreds of milligs of caffeine, >> which I don't know.
27:01
I back in back in my day when I was a kid, my parents were like, "Don't do caffeine."
27:04
And I pretty much abided by it until I was probably, you know, 18 and started. >> Yeah.
27:10
I didn't really have caffeine until I was in college.
27:11
But I remember being maybe a freshman or a sophomore in high school and a friend's older brother had access to Red Bull and was talking about the experience of drinking Red Bull like it was hard drugs. It was remarkable.
27:27
>> But yeah, I don't know.
27:27
I mean, it it's still 300 $300 million is more than respectable.
27:32
Insane, >> but uh I've never seen a brand go I I I don't has has we we should actually look at the history.
27:40
at the history. do brands going to north of a billion dollars in sales and then retracing down to this level is >> I mean I worked in consumer package goods for a long time and and with my first company like it was a rough go but that the the the pattern of that rough
27:54
go was very fast revenue ramp and then plateauing >> curve it not a falling off >> because because once you have a customer on board and they're subscribed >> well it's also it's about distribution so I think in this case they basically when when you have these influencer brands. It's when you have KSI and Logan
28:11
It's when you have KSI and Logan Paul, they effectively probably put like $200 million worth of like marketing firepower into >> growing the brand initially. Yep.
28:23
>> And even the biggest influencers in the world are not typically enough to sustain a brand.
28:30
>> Uh you you need to branch out, right?
28:32
Because eventually the the the ads just become less effective.
28:36
And so, uh, again, I think this was, um, a number of factors contributing here.
28:42
>> So, you think it might have been a lot of trial that was driven where somebody sees Logan Paul viral video explaining that he launched the brand, they try it, and they're like, ah, like, it's not available in my local store, so I'm going to churn.
28:54
>> They just try it and they don't love it, they don't stick around.
28:56
I mean the the number one uh more so than like influencer partnerships, CPG brands work in the for the most simple reason because the product is great and people love the product and they come back and they buy it again and again and again >> and it becomes a part of their life.
29:10
I'm not like a DAU or a weekly active user of Red Bull, but I probably have consistently had like 10 Red Bulls a year for my entire adult life randomly.
29:22
>> How real do you think that 1. 3 billion number is?
29:24
Because you could imagine that this was like in 2023, Logan or KSI like leaked a number that was crazy as like a stunt and it was taken out of cont >> or or even someone leaked a number and then they multiplied it and it wasn't even on Logan and KSI.
29:42
It was in fact on someone downstream.
29:45
Some some you know somebody who wanted to go viral just said, "Oh, well I saw that my Shopify order number was this.
29:53
multiply it by that and and and come up with some crazy number that was never really uh what they actually did that year because I am I am shocked because typically it's like we talked about this with create once you get the the target distribution like you should be able you wouldn't necessarily just see a massive spike you might see some trial and then some drop off fall off by >> Bloomberg is who reported they reported wow 1.
30:17
2 2 billion in sales, >> not valuation. >> Yep. >> That's a lot. That's crazy.
30:22
Um, well, I mean, still, if you're if you're, you know, just thinking about this from like an influencer perspective, launch launching a brand, uh, winding up with something that does $300 million a year is nothing to laugh at.
30:35
So, uh, still impressive run for the folks over at Prime.
30:41
>> Uh, in other news, Delta had blowout earnings and guided up. >> Oh, really?
30:45
uh while highlighting bookings have actually accelerated the last six weeks according to Elliot Capital.
30:51
Uh this is confusing because if we're if if uh you know usually you would see a recession >> in the real economy impacting >> bookings right um but uh not you know Delta's not seeing it.
31:06
So >> well >> um >> let me tell you about Vanta automate compliance manage risk improve trust continuously.
31:13
Advantage Trust Management Platform takes the manual work out of your security and compliance process and replaces it with continuous automation.
31:19
>> Well, I think I think it's time I think it's time.
31:22
>> We have an absolute legend.
31:24
>> We have John Quinn from >> uh in the we're very excited to bring him on to the show.
31:30
>> And I have here printed out. Good to meet you.
31:32
Welcome to the show, >> John. Welcome to the show.
31:36
Thank you so much for joining. >> Good to meet you. >> Good to meet you.
31:39
Um, I have here printed out one of the greatest out ofome advertisements in the history of uh, California Burbank Airport, I believe is where I saw this one for the first time.
31:50
It says, uh, Quinn Emanuel Trial Lawyers Justice may be blind, but she still sees it our way 88. 4% of the time.
31:57
Uh, did you think of this, uh, marketing copy?
32:00
Was this some genius on your team? How did this come about?
32:03
>> It was within our firm.
32:03
It wasn't some outside PR, but you know, we we came up with the copy. >> Yeah, it's amazing.
32:08
Um, talk to me about a little bit of the about of of the journey.
32:14
How how are you defining the firm now?
32:15
Has anything changed over the over your career?
32:18
Um, I mean, it's not exactly a non-traditional path.
32:20
You know, you went to law school, built the firm, but what were the key decisions along the way?
32:27
>> Well, I started out at a big firm in New York that's very well known, uh, Creass, Swain, and Moore.
32:32
Um, >> but, you know, I'm from the West. I grew up in Utah.
32:35
Uh, went to college here in LA. really liked LA. I like New York.
32:40
>> Um, but I decided I wanted to come back to LA.
32:43
Came back here, bounced around a little bit >> and we started this firm in uh January 1986 and we started with four lawyers downtown LA, not not too far from here.
32:55
>> Um, and along the way we decided to focus just on disputes work, litigation work.
33:01
So most large firms, we're now 1,300 lawyers almost. >> There we go.
33:05
>> In 34 locations around the world, most firms of that size were are so-called full service firms.
33:11
So they'll have some deal lawyers, >> corporate >> Yeah.
33:14
They'll have corporate lawyers, they'll have some tax lawyers, trust and estates, and somewhere they'll have some litigators.
33:19
And we thought we got we came to realize that this model of only doing litigation, arbitration, disputes work, government facings kind of dealing with legal risks and all its different forms was a very powerful model.
33:32
And so we decided just to stick with that.
33:36
We're not going to try to be >> and historically people would diversify because they wanted the stability of variety of different businesses or they wanted to be able to add kind of contract val effectively like add hours to existing relationships, >> you know.
33:49
So if you had >> because I'm sure you would have had pressure over time from people that say I love working with you. Can you do more for me?
33:56
>> You know I think the thought is you want to be able to service all a client's needs.
34:00
So a client may want to do some M&A work.
34:02
They may want to raise some capital.
34:04
They may and then they may have need tax advice.
34:06
Then you're effectively from time to time they'll have a a litigation.
34:10
So the thought is to cover all those.
34:13
And by the way that's how our industry is organized. We're one of one.
34:18
Yeah, I mean there is no firm.
34:18
I don't know what the next largest litigation only firm in the world is, but it's probably not more than 50 lawyers wherever it is. Yeah.
34:26
>> And we're almost >> So, you started in '86.
34:27
How long did it take you to become the most feared lawyer in the world?
34:33
>> Well, uh so what you're alluding to is uh there's a consulting firm BTI Consulting.
34:39
Uh we had nothing to do with this.
34:41
They called us up one day and told us they were doing this survey uh that they survey the general counsel at uh like 350 large corporations around the world and they asked them what law firm do you least want to see on the other side in a dispute.
34:58
uh and they were publishing a list and you know we've always been on that list of the top four they call the fearsome foresome >> and a few years ago we got them to tell us okay of the four which one actually got the most votes >> uh and they told us and for five years
35:14
running now >> we have been we say we characterize it as the most feared law firm in the world >> it's good to be feared >> what's >> well in our business we don't find clients very often that are looking for shrinking violets to represent to stand between them and trouble. >> Yeah. They're looking for lawyers that >> Yeah.
35:30
They're looking for lawyers that will cause the other side to think twice. Yeah.
35:35
You know, there's a settlement here.
35:36
This can go away for this amount or you can you see what's behind door number two. Yeah.
35:42
>> And so, you know, we think we can get resolutions that other firms can't because of our reputation and our record.
35:48
>> What's the secret to% win rate?
35:48
Is it is it case selection?
35:51
Uh, walk me through all the decisions that make sure that you're >> No, we don't we don't just select winners. >> Yeah.
35:59
>> Uh, we don't select just winners.
35:59
I mean, we're we're we're in for the hard cases, the tough cases to win.
36:05
>> And what's behind that is, frankly, there aren't shortcuts.
36:08
Doing what we do at the highest level >> uh is is labor intensive.
36:13
Uh, and it requires people who are not just smart, but truly dedicated.
36:20
>> What's the hardest case?
36:20
What's the long shot that you actually wound up winning?
36:26
>> Well, early in my career, I mean, I'd be embarrassed to kind of tell you the facts.
36:30
It was a an employment case and uh it was we were defending a discrimination case where they were two plaintiffs.
36:37
They were both African-American.
36:40
They were both, you know, over 55 years old, I think.
36:46
>> Uh and they were both let go.
36:46
And there was evidence that I mean the pliff had some evidence that the motivation behind the they had both been terminated from their jobs that the motivation you could argue. Yeah.
37:00
>> That age entered into it. >> Yeah.
37:02
>> Maybe race entered into it.
37:04
>> Uh and it was a very very tough case and I'm kind of >> embarrassed to tell you almost these 30 years later. I mean we won the case. >> Yeah. Yeah.
37:13
>> What about uh what about in tech?
37:13
uh you've been a part of some of the biggest tech cases.
37:18
Uh is that something that took you a while to get up to speed on?
37:23
Is it is there anything different about working with a big tech company from uh any of the other work that you do?
37:32
Uh so we noticed 25 plus years ago what was going on up in the Bay Area and in Silicon Valley >> and we made a decision that we wanted to be part of that and start doing some intellectual property work, patent litigation work, tech work.
37:48
So we're there for the conflicts.
37:50
We're not we're not raising money.
37:52
We're not doing the M&A work.
37:54
>> It's primarily patent litigation.
37:54
We now have the largest patent litigation practice in the world. >> Yeah.
37:59
Uh but we sent a lawyer up there to start an office.
38:02
Uh and frankly it was a little bit difficult to get traction in the beginning because there was then I think it's diluted somewhat now kind of a Silicon Valley culture and people wanted to know how much time did you how much valley experience did you have >> and we were kind of we were kind of outsiders.
38:19
We did some re recruit some people locally but it took us a while frankly to get some traction.
38:23
What's different about Silicon Valley?
38:25
I, you know, there's so much about Silicon Valley that is weird around IP.
38:29
It's like in software, you would have there's a there's a world where if somebody developed a unique user experience, you would have been able to really enforce that.
38:38
And in in the scale of time, if a big platform creates some incredible feature, it's going to get copied by every big company that that it's relevant to.
38:48
How did that kind of evolve?
38:51
Because I think early on you maybe would have expected that you could have if somebody like a Snapchat creates a stories feature that they that could have been there's another world where that could have been IP but it didn't play out that way.
39:04
There is kind of a a culture there's a feeling in many circles especially among the the biggest companies the hyperscalers and and the like that you should compete based on your business don't compete on IP um I mean there is a reluctance >> which is completely different than like
39:21
almost every other industry in the world would never say that >> well I mean you don't uh you don't see the big automobile companies suing each other either you don't see the big airplane companies oh they they'll be trade disputes between Airbus and and Boeing, >> but not so much technology disputes. >> Interesting. >> Interesting.
39:39
>> And there is kind of a feeling and you know Elon Musk has been outspoken about this that you know anybody we're not going to anybody can use our inventions.
39:48
He said things he has said things like that in the past.
39:51
>> So you don't see the big players going after each other so much. They will.
39:56
There are there are examples, but there's kind of an ethos that you compete on the business, you compete on your offering, and you don't compete with IP lawsuits.
40:05
>> What lessons did you take away from working with Elon?
40:06
Uh, is is he different than other clients?
40:09
Is is there something that you were coaching or uh advising at a various at various points in time?
40:16
>> Well, we we've represented Elon in in a number of cases, including cases uh that have gone to trial here in California.
40:23
there with that defamation case, the the British cave driver diver where there was a tweet about whether this was a pedal guy and >> and the case uh about wanting to take Tesla private for $420 a share. Funding secured.
40:37
We tried both those cases.
40:37
I was not on either one of those trial teams. Yeah.
40:41
So, I have not We have a team of people that work very very closely with Elon.
40:45
So, >> what I know about him and our experience working with him is is secondhand.
40:49
I do know, you know, he val he values his time.
40:55
He closely guards how he spends his time.
40:59
>> I don't I think it's fair to say that based on what I've heard that spending time with lawyers, preparing for depositions and trial at the like is not the top of his list of things that he likes priority. I can imagine.
41:12
>> So he he's he's a busy guy and obviously he's he's got great instincts himself. >> Yeah.
41:18
>> What about >> I can tell just one one kind of one story. Yeah.
41:21
>> So in that defamation case, he had tweeted that I assure you this British guy as a pedto guy and he came into Elon then lived in Los Angeles, sued him for defamation here.
41:33
>> We didn't have a lot of time to prepare him for trial. >> Mhm.
41:37
>> And when the trial started in federal courthouse downtown, the plainif called him as their first witness. You can do that.
41:43
You can call the adverse party, put them on the witness stand, and immediately start cross-examining them.
41:49
So the jury, the first witness they see is your adversary being cross-examined.
41:55
>> And the question to Elon was when they put him up there was, "This is a defamation case.
41:59
You're Elon Musk, so the world really cares about what you say." Not a bad question. What's he going to say? >> It's hard to deny.
42:13
>> There's kind of a beat.
42:13
And he says, "Well, well, I'm I'm not so sure. I I I don't know.
42:19
I I I've been talking about our need to get away from fossil fuels for for so long now and it it just doesn't seem to be happening.
42:26
I'm not sure people aren't listening to me at all. Listen to me at all. It was like genius. >> That's remarkable.
42:33
Yeah, it's a good argument. That's very funny.
42:35
Uh we we I mean we're tracking like a crazy AI boom, crazy tech boom right now, mostly from the financial markets. We have founders on.
42:44
I'm sure we have seven people on today that are raising a lot of money.
42:48
Um, is there a boom in tech litigation?
42:51
>> Well, maybe even before that going talking about kind of the dot era, you saw this craziness.
42:55
We opened the show talking about how people were just valuing eyeballs, right?
42:58
And there was uh aside from that, there was like you know these round trip uh you know effective uh you know commercial agreements that uh ended up getting litigated in the years following after the after the crash.
43:11
What kind of stood out from that era?
43:13
What was what was just you know I guess what were the takeaways from that era?
43:20
Did you ever think we would repeat those kind that kind of cycle because I'm sure you that you were in the uh your job even after the crash just got busier and busier. >> Yes.
43:31
uh whenever there's a crash uh as in the financial crisis for example 2008 which we weren't very involved in that plays out in the courts of course there'll there'll be people who've lost a lot of money uh there'll be claims of fraud and misrepresentation um you know in the dotcom boom there were down rounds uh there were class actions of all kinds securities class actions so every deal gets scrutinized in retrospect um in AI where we are.
44:00
Look, I'm not an economist and I'm not a prognosticator about where we are in terms of whether this is a a bubble or not.
44:09
>> I can tell you in our world, the disputes world litigation, we're seeing a lot of AI related disputes. There's no question.
44:17
>> And is that around primarily today?
44:17
I I can imagine the trajectory is like right now it's a lot around IP, right?
44:22
now it's a lot around IP, right? We saw case against anthropic around their their usage of I forget it was well there's Reddit getting litigated but then the books where they >> they just did a huge settlement it was a big settlement and so right now it feels
44:36
like we could be in the era of like litigating around IP >> and what what even is IP in in the in the world of generative AI but then it feels like the the next wave could be around >> just rehashing and and litigating it's going be a lot of lawyers looking over, you know, this this announcement that went out. It's like, yes, in the fine
44:57
It's like, yes, in the fine print, it said that it wasn't an actual deal yet.
45:00
It was just a kind of a a a general sentiment from the two companies, but um >> but I but yeah, how do where do you think um >> do you think we're at all close to having some like precedent around AI and IP or is this going to take years?
45:20
I mean AI is throwing up so many novel um legal issues.
45:23
I mean IP for for sure everybody's uh heard about the cases that have been brought relating to music literary works um uh visual works using copyrighted materials to train large language models and whether that's copyright infringement or what's called fair use. Yeah.
45:44
>> Uh so we have dozens of those cases.
45:44
Uh we finally have a couple of decisions now out of the federal court in San Francisco uh where the judges in those two cases, one case involving META, another case involving anthropic uh decided that uh it was fair use uh that it was not copyright infringement to use copyrighted materials to train large language models.
46:08
language models. although both decisions were kind of qualified >> and there were some unique facts in both cases but yeah we're we're starting to have those those decisions on various issues but there's so many things all this money is going into large language models and AI and there's a >> you think you think a lot of founders are just running the calculus of I know
46:30
that I'm going to have to eventually pay out something for what I'm doing but I'm just going to run with it because I'll I'll be able to eat the eat the cost later and and if I wait then my competitors will will >> I don't know losing one of these cases uh the copyright cases there's so much involved the the price tag could be could be very very big. Yeah. Yeah.
46:52
>> Uh so I don't know that people are sitting back saying it's just the cost of doing business. >> Yeah.
46:57
But at the same time, if your competitor is like willing to take the risk and they can ramp their market up, market cap up into the hundreds of billions, they're they know that and and the alternative is, you know, being safer around IP and then you just lose the race, then you're a zero anyways.
47:13
So, I think a lot of people are it feels like a lot of people are willing to just roll the dice and say, "We'll figure it out later."
47:20
Well, Apple in its f in its early years uh had a reputation for not being very careful with its IP.
47:25
You know, they launched the iPhone knowing they did not own the name iPhone. >> Oh, yeah.
47:32
>> It was owned by I think Oracle Oracle or Cisco. Yeah. Cisco.
47:35
And so, as soon as they launched it, there was a lawsuit filed. Yep. >> Cisco versus Apple.
47:40
And it was immediately settled.
47:41
I've never heard what it settled for.
47:43
Uh, but you know, that was Steve Jobs, you know, driving ahead and and kind of doing what you're saying.
47:50
I think they've gotten >> I think they've gotten a lot more careful.
47:53
But there's just a host of issues like you have all this money going into AI and AI inventions.
47:57
How are you going to protect it?
48:00
>> Yeah, >> you cannot patent an algorithm.
48:00
You cannot patent a mathematical application.
48:06
>> You know, it's the these come under the rubric of general ideas, laws of nature. >> Yeah. Yeah.
48:12
And then you and then in the talent the talent wars are a whole other thing.
48:15
I'm curious if what what your kind of uh view on you know over the summer we saw all the labs kind of poaching pulling talent from different places and people realizing that in this person's brain is like potentially >> million.
48:29
You think that's they're not being hired for what is in their brain?
48:33
>> Yeah, of course they are.
48:35
>> And that's an example of what I was referring to earlier where the major players >> are very reluctant to sue each other.
48:41
I'm kind of surprised there hasn't been more litigation over the this poaching, >> but I think it's this phenomenon that >> Yeah, our view is that they were very much like aqua hires, just unauthorized aqua hires where it's like this team knows how to do something really well that they've learned through spending >> tens of millions or hundreds of millions or sometimes even billions of dollars and we want what they know how to do.
49:03
We want the uh we want the process that's in their in their head basically. >> Yeah.
49:10
>> Yeah. you know that there's no doubt I mean some of the what you're referring to is trade secrets trade secret law which is another area of intellectual property and that's an awful lot in the AI world what we're talking about mathematical applications algorithms and
49:24
the like that can't be patented they can be trade secrets and they can be protected as trade secrets and if somebody has access to those and goes to work for a competitor it's not lawful for them to be using that information when they go to work for the for the competitor but then prove removing that actual use. Yeah. Yeah.
49:43
>> You know, is u is another thing alto together.
49:45
>> How often would an issue pop up and you have multiple uh let's say it's mag 7 on mag 7 and you're getting you're getting calls and texts from both of them racing to to to work with you guys and then have you ever had to make a call in the >> in that world?
49:59
Uh we never encountered that because we always and forever have been adverse to Apple, Meta, Amazon and Microsoft. >> Okay.
50:09
We've always represented Google, Nvidia, Qualcomm, Salesforce, and some others.
50:15
In our world, it seems like you come to a fork in the road and you decide we're going to go this way, and you never come back because people know you well.
50:22
You're the firm that will be adverse to Apple.
50:23
It's like being the firm in Seattle that'll be adverse to Boeing. Yeah.
50:27
I mean, that's kind of a job in it in itself.
50:30
>> Yeah, >> that makes sense.
50:31
What about um uh uh >> I mean it does happen in other areas of practice like in uh private equity.
50:37
I mean we had a situation just within the last couple of days where two global private equity firms >> Yeah.
50:46
>> who were opposite each other with respect to a particular transaction. Both of us called us. >> Yeah.
50:52
>> And we accepted the engagement from the one that called us first. >> Okay. >> So that does happen.
50:56
Is being litigation only an advantage in being able to create this patchwork of clients that you don't have conflicts because you're you're also already doing their contracts or anything so you can be a little bit more uh >> you know I think as a litigation only firm we have fewer fewer conflicts.
51:10
So um for us the world is is divided to the into uh companies and individuals we represent and those we don't and sometimes a party a company or an individual moves from one category to the other. Yeah.
51:26
But we don't have we have very few sort of lasting conflicts uh visav the business world in principle where deal lawyers you know there might be some industries that they know well we just can't be on this other other side of this issue or represent a competitor or the like because it's a little bit different in the deal world.
51:47
>> Where's your firm getting leverage from AI today?
51:52
>> We're using it uh we're using it a lot.
51:55
Um we're using it to you know not only to manage documents uh the things that are produced in discovery because we've been able to do that for a long time >> but to be a if you can imagine we tried a case in Delaware a few months ago and
52:10
we had loaded into the database all the deposition testimony all the documents and the trial testimony as the trial's going down >> and as somebody's on the stand I mean you can imagine you can query this database what is the best evidence that so and So just lied about that. >> Yeah. >> Yeah. >> Yeah. In real time. In real time. >> Yeah.
52:29
And it'll, you know, you press a button and it'll give you >> a list of things in rank order. >> Yeah.
52:35
>> Now, if you had >> before, back in back in the day, 90s, early 2000s, 2010s, you had to be >> go back to the filing cabinet. >> Yeah.
52:41
I mean, you relying on your memory. Yeah.
52:43
And what you know, and uh what you know about the case.
52:46
And still that's the most important thing I think.
52:50
And mostly it's kind of a backs stop.
52:51
You know, it's a check things you would have thought of anyway.
52:53
But it'll also come up with things that you wouldn't have thought of or maybe you would have thought of if you just had more time.
53:01
>> Uh what are your thoughts on uh resolving co-founder conflicts?
53:03
There's been a number of really high-profile cases around uh a group of people came together, started a company, the company grows and grows and grows.
53:11
Some people leave and then there's >> Vinkle Boss Twins. >> That was one example.
53:16
>> We settled that case and we didn't file the case.
53:18
We were brought in to settle it. >> Sure. >> Uh snap. >> Yeah.
53:22
There was a there was a third guy in the garage. Yes. Yes. Who got kicked out? Yes.
53:26
Uh and he he brought a claim.
53:29
>> Are there any uh like common pitfalls that you see on uh the the incorporation documents or the safe node or specific >> people start working on these projects? Sorry. All the time. Yeah.
53:40
>> And they're not thinking about >> this might become super valuable someday. >> Yeah.
53:45
>> You know, maybe they're more sensitive now in the tech world and so they >> it's easier than ever to create.
53:49
You can create a CC corp in a few clicks.
53:51
You can see >> and they don't think to lay out, okay, who owns what? What's my share? What's your share? We're friends, right?
53:57
So, they don't think to document it.
54:00
>> Uh, and it's not till later that and suddenly it's super valuable and they're getting all these views and followers and realize, wow, this is super.
54:06
Now, remember this is 1/3, right? No, no, no.
54:11
That was not my understanding. >> Yeah. Yeah. Yeah. Yeah.
54:12
>> Yeah. Yeah. Yeah. Yeah. uh h how much um in a case like this is it worth uh pursuing a settlement taking it to trial like what are the what are the key decision points where you realize okay this is going to trial >> I mean usually so there's a there's a
54:29
stage uh called summary judgement where uh a party can go to the court and basically say look on the undisputed evidence that's been developed in the course of discovery >> I'm entitled to judgment as a matter of law it's basically you're arguing to the court. No reasonable juror
54:43
No reasonable juror >> could find for the other side.
54:46
They could only find for me >> and and there has to be no disputed evidence and the judge has to find okay on the law and yes the evidence is undisputed you win.
54:57
>> If it gets if and a lot of cases are dismissed at that level.
55:01
>> If it gets past that then there's the prospect this case is going to go to trial.
55:05
There's nothing really going to stop it because that's kind of the last court offramp.
55:12
Um, a lot of cases are resolved in mediation.
55:14
In any significant case these days, the courts will expect you to go through a mediation.
55:19
That is to say, engage a neutral, professional mediator, spend some time with the mediator and see if you can resolve the case. And that happens.
55:29
Sometimes it happens right at the beginning of the case or even where there's a dispute and no case has been filed, you get a mediator together.
55:36
Sometimes it happens on the eve of trial, >> but a lot of times it happens in the course of a mediation.
55:41
So, you know, if it's gone past summary judgement, if you've gone through a mediation and that hasn't been successful, then that looks like a case that may go to trial.
55:52
>> And is that a function of uh total settlement?
55:54
How much is at stake relative to the legal bills?
55:56
relative to the legal bills? is am I more likely to settle a case if it's $1 million at stake but $500,000 in legal bills that I'm looking at versus there's a billion dollars >> I would certainly think so if the legal bills are more than uh what you would
56:12
get out of winning the case >> sometimes there's other things uh you know at stake whether ego or whatever reputation >> but it's usually a calculus I think most clients it's it's pretty much an economic calculus what you know What are my chances of prevailing uh at trial? What do I get if I what does prevailing
56:30
What do I get if I what does prevailing mean?
56:32
What will I get if I prevail?
56:32
And obviously, what's the cost to get me there, including primarily attorneys fees?
56:39
fees? Do >> do you think that AI will speed up cases or is there some element to litigation that just because maybe one side realizes the longer this goes on the I the better for me I'm just going to drag it out like will it actually even even
57:00
though a lawyer could now do two weeks of work in an hour maybe if they're properly using some of these AI tools they might it might still just take the Well, you know, however many two weeks uh in order to >> because the other side's going to be using AI, right? >> Yeah. Look, I mean, cases settle when >> Yeah.
57:14
Look, I mean, cases settle when parties realize the strengths and weaknesses of their case and the strengths and weaknesses of the other party's case >> and they they assess that, you know, cards in the in the discovery process, everybody's cards are basically put on the table. Yeah.
57:32
>> And you have a you have a basis then to make a judgment about am I going to win? What does winning mean?
57:36
what am I likely to get in damages?
57:38
I think AI will accelerate that process.
57:41
There will be more disclosure and more ability to handicap the potential outcome sooner.
57:49
>> So, I do think there's a potential for resolving cases sooner.
57:51
However, I think AI is going to result in in much more litigation, >> more cases, >> more cases. Why?
57:58
There are already early stage companies out there who are putting cases together.
58:03
They have put into databases all records about permits, licenses, advertising, what parties claim is in their product, what they say their product can do, all this information and information about what is actually in the real world, what's the experience there.
58:20
They'll put that together and they will serve up to lawyers.
58:23
You can subscribe to these services and they'll come to you to say, "I've got these great class action lawsuits for you."
58:30
>> Um, and so they're finding they're finding cases.
58:33
So I think there will be more cases uh but I I think there's a potential they'll be resolved sooner.
58:40
>> Do you think the legal profession is a mentorship business?
58:41
Do like when you bring on do do you see uh you know young lawyers needing to find a mentor to establish a full career?
58:49
Is that how you is that how you think about it or >> I really think the best way to learn is working with more experienced people.
58:58
That was certainly true in my case, whether you call them mentors or just senior people in the firm who you work with and >> go to court with and see how they examine witnesses and the like. Yeah.
59:09
>> So, I I do think that's really important in terms of learning what it means to practice law.
59:13
>> What advice are you giving to young lawyers today that want to be where you are in 30 years or so?
59:20
Well, as I said earlier, I I tell people, you know, this is practicing law, litigating high-V value cases at the highest level is there's no shortcuts.
59:29
So, you have to be prepared to sacrifice >> and work super hard.
59:33
It's a it's an hour's commitment.
59:35
There really are no shortcuts.
59:39
>> Is it thrilling, though? Do you love it? >> I do love it. >> I do love it.
59:43
>> Is the case more thrilling or is it who you're working on behalf of?
59:45
Is it the partnership between you and the client?
59:48
Because >> the partnership with the client can be very very satisfying.
59:51
Uh because the >> is a team sport, right? >> Exactly.
59:55
It's definitely a team sport.
59:57
The team within the firm, the team with the client.
59:58
What I love most about it is we're constantly learning.
1:00:01
We have to be able to cross-examine experts, whether it's on biotech, steel manufacturer, AI, I mean, you name it.
1:00:09
We have to get to the point where there's an expert on the stand, somebody maybe has a PhD in something, and we're going to cross-examine them. We have to learn.
1:00:18
And that's what I love about my job. >> Yeah.
1:00:21
An expert can make some you look you you sound really silly.
1:00:22
What do you mean by that?
1:00:24
Like I don't understand what you're even asking.
1:00:26
And then they could just be you know >> you sound like an evasive.
1:00:31
That's not that's not going to be great for your credibility. >> There you go.
1:00:34
Uh what about uh how the media characterizes law?
1:00:38
Uh, is there a book or movie that stands out to you as kind of telling the story the correct way that resonates with you?
1:00:46
That's something that you don't feel like it's a mischaracterization of how you work.
1:00:53
>> You know, I there are a number of good books about uh trial lawyers and and perhaps my favorite was written by a trial lawyer who recently passed away, Jerry Spence.
1:01:03
I don't know if that's a name you know.
1:01:06
uh famous trial lawyer from uh uh Wyoming.
1:01:12
>> He did the Karen Silkwood case, that uranium Oh, yeah.
1:01:14
She claimed that she was injured by exposure to radiation.
1:01:20
She uh he represented Amilda Amilda Marcos uh in a trial in New York City.
1:01:23
I mean, he he but he was always kind of this Wyoming buckskin clad country lawyer, >> a character. >> Uh and he Yeah.
1:01:32
And he wrote a book called Gunning for Justice.
1:01:35
Yeah, >> that was about his own life. >> Okay.
1:01:39
>> Uh, and it was a very very moving moving book.
1:01:42
That's one that I really enjoy.
1:01:43
>> I will have to pick it up.
1:01:43
Well, thank you so much for coming by and doing this interview. Fantastic. >> Enjoyed it very much. >> Thank you so much. >> Thank you very much. >> Thank you.
1:01:52
>> Yeah, you're welcome anytime. >> What a legend.
1:01:55
>> That was a lot of fun.
1:01:55
Um, we have our next guest in the restroom waiting room.
1:02:00
Let's first tell you about graphite.
1:02:00
dev code review for the age of AI.
1:02:03
Graphite helps teams on GitHub ship higher quality software faster.
1:02:08
You can get started for free.
1:02:10
And our next guest is uh Martin Casado from Andre Horowitz.
1:02:13
Uh we have a bunch of breaking news.
1:02:16
We're very excited to talk to you. How are you doing? >> Welcome, Martin. >> Good to see you.
1:02:24
>> Um can we adjust the levels?
1:02:24
Make sure that we're hearing him. Okay. Uh how is your day?
1:02:28
Just tell us how you're doing.
1:02:30
>> I'm doing very well, thank you.
1:02:30
It's actually pretty chill morning cuz I had a couple meetings canceled which is kind of the best gift you can give me. >> There we go. Paradise. >> Cancelled meetings. Hop on TVPN.
1:02:37
What more could you want in the Silicon Valley life? >> Exactly.
1:02:43
>> How's uh how's your how's your Q4 been? Uh pretty mellow.
1:02:47
>> Uh most of my companies most of my companies are still in Q3 because we shift by a month. But pretty good. Thank you. >> There you go.
1:02:54
>> Wait, why why a month?
1:02:54
Is that is that standard now?
1:02:56
Is this something >> it is?
1:02:58
Well, it is very standard.
1:02:58
>> it is? Well, it is very standard. I mean listen so I did you know enterprise sales for my company for 10 years and I don't remember a Christmas or a New Year's where I could be home because uh we were like deep enterprise sales so
1:03:10
50% of the year came in in the last month and so >> everybody realized that you know if you're pushing to the end of the quarter it's probably better to do it when people are still working and so most will use uh the end of January and so that's the majority of the companies I work with by a month. Yeah. Yeah.
1:03:24
>> When how often are you uh investing in a company and and they haven't made the shift yet?
1:03:28
Are you going that early?
1:03:31
>> Honestly, if they don't, I I recommend them to them.
1:03:33
>> Yeah, I imagine that's a first.
1:03:33
You like you like the holidays at the end of the year.
1:03:37
You like spending time with your family.
1:03:39
>> I mean, I would say 2008 to 2012 of my life.
1:03:43
Maybe 2016 was me on the phone like in a beach somewhere trying to close a deal.
1:03:46
So, >> and it paid off and here you are uh leading the infrastructure practice.
1:03:51
Uh, I want to get to robotics in China, but uh, first I'd love just an update on uh, how you're thinking about infrastructure at Andre. You have 1.
1:04:00
25 billion under management for that fund.
1:04:04
And infrastructure, I mean, we're seeing deals for energy.
1:04:06
Sam Alman's doing stuff with SKH and HBM.
1:04:09
There's, you know, the the Neoclouds, there's the hyperscalers.
1:04:14
There's so much in infrastructure.
1:04:15
And then there's also just like dev tools, which I think could maybe be in there.
1:04:18
So, how do you define it? What's interesting?
1:04:20
Where are the key themes these days?
1:04:23
>> Yeah, so we do primarily software infrastructure and things that directly relate to software infrastructure.
1:04:26
So everything from like they say chips to AI models to to your point dev tools to the traditional comput, network and storage.
1:04:34
Um, a very interesting thing about this AI wave is like it's very hard to distinguish between like a like a deep infrastructure model company and like say an application company.
1:04:41
And so we're having kind of a renaissance in the field where everything has to be redone.
1:04:46
like you have to redo networking, you have to redo compute, and you have to like build new dev tools.
1:04:50
And so, >> you know, we're just trying to keep up with all of this change that is coming from from AI.
1:04:56
>> How are you thinking about uh competition from the hyperscalers when you're looking at a startup?
1:05:00
you're looking at a startup? We talked to a bunch of founders who they're going up against AWS and Andy Jassey's not asleep at the wheel, but at the same time there's this meme of like, you know, a VC would always tell you what if Google does this and then we have, you
1:05:13
know, Cloudflare and like, you know, GitLab and there's like a million companies that we could name off that are, you know, decacorns, public companies that successfully went up against the the, you know, the the public clouds and won or at least saw, you know, massive businesses built. So,
1:05:27
So, is there is it all about the founder?
1:05:29
Is it about the particular market or the technology or lock in or being programmer record or being a you know some sort of system of record like how are you thinking about it?
1:05:38
Um so listen I've been an infrastructure investor for 10 years and um >> uh listen in that entire time the public cloud has been incredibly dominant right and so I would say after reinvent which is the AWS show I have to like move into therapy mode like I've got actually I'm
1:05:55
actually on the other side of this I'm never the one that actually worries about the public clouds I'm always telling like the founders and I I have this line my my line is is like >> can you name one company that AWS has put out of business one just one >> good point like they literally have copied everything. They've hosted
1:06:08
They've hosted everything and like >> and so the reality is is that if you have an entire if if the market is large enough and you have an entire company focused on it, you're going to win and that's just the reality.
1:06:18
And AI in particular is a new behavior which you know you know companies like incumbent companies are terrible at new behavior.
1:06:28
So like this is definitely an advantage to startups like it's like a new buyer. It's a new use case.
1:06:31
It's a new way of thinking about things.
1:06:32
So they don't have the incumbent institutional momentum.
1:06:37
And so I think that like you know we're free of of a lot of the trappings of the cloud and I think the future's very bright for startups.
1:06:43
So I I I don't spend a lot of time thinking about the incumbents.
1:06:46
That said, I have to say one thing is >> listen anthropic and open AI are are startups really in the classic sense.
1:06:52
Um and they are incredibly dominant and so I would say I would put them in a different class.
1:06:59
There is there is a class of these new types of incumbents. Think like Stripe.
1:07:02
Y >> Figma where the founders are still there. They're still hungry.
1:07:05
They're executing very well.
1:07:07
I think those are much more dangerous than you know Google or Microsoft. >> Yeah.
1:07:14
>> Yeah. I was talking to a founder who was uh going up against an AWS point solution that was rolled into stuff and I was like you you are going up against Angie Jasse but you're really going up against the particular product manager
1:07:25
who's on that particular product and that product manager might not be taking calls on a beach in on December 25th, you know, like they might be taking a vacation and so if you're going to outwork them, it's possible you could beat them. >> Totally. And and like this is a company >> Totally.
1:07:37
And and like this is a company that, you know, is famous for bragging about two pizza box teams, right? Okay. Yeah.
1:07:44
So fine, you've got, you know, the 12 people on this product that's dying on the vine.
1:07:47
Like if you can't beat that, you kind of deserve to lose. >> Yeah. Yeah. Yeah. It's a great point.
1:07:53
>> Um well, I I'd love to go into uh robotics in China.
1:07:57
Uh you recently published a Wall Street Journal op-ed, which I love.
1:08:01
I read the journal every day.
1:08:02
Before we dive in there, one question around uh when you're evaluating uh how you think about uh >> how you think about revenue ramps specifically.
1:08:12
You know, there's always this question if a company's ramping revenue just just uh at at an ungodly uh rate.
1:08:19
There's a question of like how how durable that revenue is.
1:08:22
Is it is is it going to be possible for another company to come into the category and sort of pull off the same type of um pull off the same type of growth?
1:08:31
What are you evaluating for these software infrastructure companies on whether they have actually done the hard work to figure out develop something that's unique and proprietary or they're just capital or they're just like a we talk about it's like a a barnacle on the side of a whale like opener.
1:08:51
>> We're into the barnacle economy.
1:08:53
>> We love the barnacle economy >> where you just naturally grow at the growth rate of anthropic and you're like it's a miracle. >> Yeah. Yeah.
1:09:00
Um I mean listen so there's always this concern of easy come easy go which is kind of like what you're asking about like you know you got this revenue so quickly how hard could it be?
1:09:07
so quickly how hard could it be? Um but you know listen we're 3 years into this and we've got a lot of data points that this stuff is actually pretty durable right I mean midjourney bootstrap to actual scale and it still is very much a leader in image >> um you know open AAI um roared into dominance um in text and it's still the leader anthropic roared into this I mean
1:09:27
cursor roared into this and I think that these revenue ramps are much more of an indication of the size and the growth of the market which I mean these things have just been so large and growing so fast and of course like the leader that becomes the brand monopoly will follow brand effects and then people will know the name and then they'll go ahead and adopt it. So I think that you know like
1:09:47
So I think that you know like there is no indication just because the revenue ramp was quick that it's not durable.
1:09:54
That said I don't know of any endemic defensibility in AI.
1:09:57
I think companies have to figure out traditional modes and there's a lot of traditional modes we know about, right?
1:10:04
Integration modes, two-sided marketplace, brand modes, like whatever the moat is, they've got to get to that.
1:10:09
So, when we evaluate the company just because it grew quickly, we're not like, oh, easy come, easy go, right?
1:10:15
I mean, that's kind of like intellectually lazy.
1:10:16
On the other hand, we do look for like what actually is the mode, right?
1:10:20
If you're basically just, you know, reselling TPM, you know, tokens per minute from Anthropic, that's probably not as durable as if you've got an a workflow and a bunch of users that use it and, you know, they save configuration in this and you've got good retention numbers, etc.
1:10:36
So, we do kind of full-fledged investment like we always do, but I don't think it's correct to just say just because the growth is high, it must not be durable.
1:10:45
>> How quickly can a brand moat emerge >> in in infrastructure?
1:10:52
Yeah, I mean it's a good question.
1:10:52
I mean the last time I remember brand modes like this was the internet.
1:10:54
I think when markets grow incredibly quickly the like education is always kind of um out of date and so you default to brand like remember Netscape was largely a consumer phenomenon and very quickly everybody was talking about Netscape um very early on and we're seeing a very similar thing.
1:11:10
So I think it's been probably 25 years since we've seen brand effects dominate adoption especially for highly technical projects.
1:11:19
I think the last time was probably the internet and then before that like maybe the PC like Windows 95 again was very much kind of a brand name.
1:11:24
And so I think it's more again an indication the market's very large. It's growing very fast.
1:11:29
There's so much confusion in the market so that a few leaders end up becoming brand monopolies and then the adoption is literally because people can't keep up.
1:11:37
So they just kind of adopt the one that they know about. >> Yeah.
1:11:40
There's speaking of brand, there's actually a comment in the chat. A6Z blows my mind.
1:11:43
How can they be a venture fund and a brand at the same time?
1:11:45
And I feel like there's like like Andre really is focused on brand in many ways both the Andrees brand but also partnering with brands on the consumer side or or uh you know uh internet consumer side.
1:11:59
Um but do you have do you have thoughts or advice for infrastructure founders on brand?
1:12:03
Is there is there is there an equivalent of like make sure you have your.
1:12:06
your.com or make sure that you have you know a specific brand package like do you spend any time thinking on that or is is that at all relevant or is it just something that you know kind of check the box make sure it's converting customers and think about it in more quantitative terms >> yeah you know so quite frankly this is a
1:12:21
pretty new phenomenon like I am part of the nerdiest part of injury you don't really think about brand it's like not that's not the conversation we have normally it's either talking about like the mechanics of you know inbound bottoms up growth or the mechanics of enterprise sales or something like that. That said, we've all had to all of us
1:12:39
That said, we've all had to all of us the founders and the investors had to become students of this because like you'll have model companies that'll be consumer companies and those are very much brandled.
1:12:48
You'll have um I mean you know I mentioned cursor before like you know cursor is a dev tools company but it's got so many users like brand effects are at play.
1:12:55
effects are at play. brand is really important and and X now because this stuff is proliferating so quickly has become a primary distribution channel like X has its own way of propagating information that's very very different than going to like traditional press or doing like a press release or writing
1:13:10
content marketing or whatever like we're in a very different world and so I would say you know historically I personally while the while the firm has I personally have not been very focused on brand like the opposite but now I've I've had to learn a lot more about it >> used to just be make the docs dark mode. >> Do you think some of the
1:13:26
>> Do you think some of the >> But now, yeah, now we are emerging.
1:13:30
>> Sell the sell sell the thing and be technically correct.
1:13:32
I was like that was kind of my Yeah, >> exactly.
1:13:35
>> Do you think public SAS is generally oversold or people too bearish or is the is the >> is the the the conversation we keep coming back to Brett Taylor was on the show talking about how it's easier to change the the your tech stack than your business model.
1:13:54
and he was referencing, you know, the dynamic between, you know, seat based, >> but that's but that's kind of not as relevant in in public company infrastructure companies that might be disrupted by >> because because a public I I I imagine that most of the infrastructure competitors, the incumbents are already on consumption based models and so you're not seeing a dramatic shift in the business model of the companies you back.
1:14:16
It's more of a technology shift or am I mischaracterizing that? >> Uh, okay. Okay.
1:14:21
So I I definitely think we're seeing um a pricing shift from seedbased to usage based and and listen we saw that listen when I was doing my company we saw the shift from perpetual to um to uh to recurring right to SAS recurring right and so we're seeing that type of shift and that's being accelerated by AI it was started by the cloud but it's being accelerated by AI because you know the tokens are so expensive.
1:14:42
>> I don't think that alone is depositioning anybody right I think that the the SAS companies are very good at adopting that and using that.
1:14:47
I really think a lot of the story of AI is actually kind of new capabilities and new use cases and like that's kind of like the untold story.
1:14:54
I mean these things now speak English, right?
1:14:57
They develop an emotional connection.
1:14:59
They can create something from nothing. Like that's cool. That's net new behavior. That's net new budget.
1:15:04
And you can see this in this dramatic growth.
1:15:06
Now um of course budget has to shift to cover that, right?
1:15:12
And so I think we are seeing a slowing down of traditional SAS spend as you would expect when you have something super cool and new and whatever.
1:15:19
But I don't think that this spells the demise of of the traditional sector.
1:15:23
I mean it's just it's actually not even good at things like systems of record yet.
1:15:27
Now over time that will change and maybe it'll change the consumption layer and once you have the consumption layer you can change the back end.
1:15:33
But I really think the story we should all be talking about is like what are these net new use cases?
1:15:36
Like what is it enabling?
1:15:38
Where does that budget come from? Yeah.
1:15:40
Um as opposed to like who is this necessarily going to kill because a zero sum thinking I think is the biggest mistake we all make in this AI wave. >> Totally. All right.
1:15:48
Well, let's switch gears to robotics.
1:15:52
>> Yes, there is a what's the major robotics company out of China? >> Unitry.
1:15:57
>> The there there's a unitry for sale on walmart. com for like $20,000.
1:16:00
I'm hovering over the buy button.
1:16:02
Uh how unamerican am I if I pull the trigger?
1:16:08
Uh take me through the landscape. Yeah, buy.
1:16:10
I think we're gonna we're maybe gonna try and hack it and do something weird. Um but uh yeah. Yeah.
1:16:13
T take me through the current understanding.
1:16:16
Um in general it feels like maybe I'm wildly wrong, but it feels like tension between China and America is calming down almost.
1:16:26
I don't know just maybe that's just the news cycle and people have shifted to other geopolitical topics.
1:16:31
But I mean, Poly Market has the the the the the chance that China invades Taiwan by end of 2026 down at 14% from 25% and and and we're doing more trade deals.
1:16:42
There's crazy news today, but walk me through how you're understanding the the the geopolitical landscape.
1:16:49
>> So, listen, I'm not an expert on on geopolitics.
1:16:50
I will say today China put export controls on on rare earth metals that are, you know, useful in like things like lithography.
1:16:57
So, that's clearly like I would say not a d taunt.
1:17:00
I mean that clearly is kind of a more of an aggressive uh poster.
1:17:02
Probably this is because Trump is meeting with Xiinping.
1:17:06
Probably this is just kind of for negotiation. I don't know right.
1:17:08
But I I would you know again I am not an expert on these things from my perspective which is through the lens of technology like there is not a dant.
1:17:15
I think that things tend to be escalating.
1:17:19
>> Um now that said you know the the uh tactical collaboration between China and the US is the strongest it's ever been.
1:17:29
I mean, you know, uh, >> half the founders I work with are Chinese Chinese, half the teams I work with, half the papers I read, half the models I use, half the models the companies I work with use.
1:17:37
I mean, like, I think from a technical academic standpoint is the strongest I've ever seen in in the industry.
1:17:42
And so, in that way, there's very much a positive, but politically there's clearly some jocking and I think we're trying to all understand what that means.
1:17:49
And and and I'll just tell you my my very quick view is like um I don't think anybody wants a generational struggle with China, right?
1:17:59
I mean like the like the you know the hope is is that both of us collaborate together and take over the solar system, right?
1:18:05
These are two just phenomenally great countries with a tremendous amount of talent.
1:18:09
But there is some level of polyiana in that belief.
1:18:11
And so then the question is is to what extent do we want to depend on China?
1:18:15
It's not it's not about being aggressive.
1:18:17
It's not about being proactive.
1:18:19
It was like, you know, do we want to depend on them for for critical infrastructure?
1:18:22
And I I would say my position is the answer is no.
1:18:24
We don't want to depend on them.
1:18:26
In which case, it's important to understand what they're capable of, what we're capable of, and what we can do to develop local capabilities.
1:18:35
>> Do you read anything into the the fact that Xiaomi was able to be a phone company that launched a car and Apple was maybe rumored to be working on a car and never got it out?
1:18:45
Is is the is that just a market structure thing?
1:18:48
I'm interested in understanding like where is China behind? Where are they ahead?
1:18:54
It feels like Tesla was way ahead in electric cars and China's catching up there, but now Tesla's playing catchup in humanoid robots.
1:19:02
Um, and I I I'm I'm interested in the landscape of like what each country does best. >> Yeah. Yeah. Okay.
1:19:10
So, I mean, listen, this is going to be very polarizing topic.
1:19:14
So I just want to say up front that I'll send some opinions.
1:19:18
These are not rooted in fact. There is no agenda here.
1:19:20
It just you know um as far as your first question on on the structure of companies like Xiaomi and the car and Apple.
1:19:26
Um you know Asian companies just tend to do more right.
1:19:30
I mean think about the Korean cha balls.
1:19:32
There was like for a long time there was five companies that did everything like everything.
1:19:34
They did everything from the cone to the car.
1:19:36
And so like I don't think that that is like a China versus US thing.
1:19:39
I think that's something quite a bit different.
1:19:41
Um, you know, that said, we've seen China be like, you know, very very effective at a number of areas in recent memory, right?
1:19:49
I mean, 5G, China basically won, right, which is, you know, critical infrastructure communications, right?
1:19:52
I mean, for solar, they've been dramatically good.
1:19:55
And then I wrote this post on robotics where they're very, very good.
1:19:58
And so, it's clearly a country with a ton of capability.
1:20:00
Um, on the other hand, like listen, like the United States continues to like do two things that I think are are are um pretty distinct from China.
1:20:08
One, they're very good at complex software systems, right?
1:20:11
right? like like you know not building a model but building kind of like the opening eyes and the anthropics and you know and everything around they're very very good at complex software system and two this is going to sound funny but the US is actually really good at building stuff people like >> and I and no but I I think that I think
1:20:27
there's this I think there's a specific reason for that which is um we're more like the rest of the world than China is like China like caters to a local market and the local market is just different behaviors different buying behaviors different political behaviors different economic behaviors and so like the stuff that they produce is just weirder. Um,
1:20:41
Um, and so in some way I would think like like you know there's there there's two areas where they're just not as strong.
1:20:49
very complex software systems which we historically have just not seen come out especially for B2B but also like software that the rest of us can like use and adopt outside of like these viral consumerry things like about to say yeah they boo right like this consumer thing but I'm not a consumer guy man I'm like >> there's these cars that have like uh LED
1:21:09
front dashboards and karaoke machines inside and they float and they're all very cool but I don't know if the American consumer actually wants that necessar Well, but I think I think you could reduce it to like, you know, listen, people are people and whatever, but like enterprise buyers are very different in China than they are in the United States. And like, can you name
1:21:26
And like, can you name one large >> uh Chinese enterprise software company? >> No. >> Software. Yeah. I mean, it's impossible.
1:21:35
I mean, we >> bite dance get into enterprise in China.
1:21:38
>> Does Alibaba Quen like count or like does Deep Seek count in ter I know Deep Seek's getting inferenced a lot.
1:21:44
>> I mean, I'm like, well, listen, data brick, snowflake, sales for Microsoft.
1:21:49
like the US enterprise companies and then in China you're like well you're kind of trying to like well it was a consumer company but maybe they do enterprise like there's kind of these weird telco companies that people will mention but >> sure sure >> it just you know listen I you know I built a team you know I ran a team in
1:22:02
Beijing I ran a team in Shanghai when I was working at VMware after they acquired my company and we sold software in China it's just different it's totally different like the consumption patterns are different how you sell it's different what they expect from the software is different and and and the
1:22:15
market is large enough and localized enough that any local company's going to focus on that and if they focus on that they're just like through Darwinistic focus forces of acceptance are not going to build something the rest of the world >> um really understands and so I do think this is an area that the United States
1:22:30
has a tremendous advantage is like you know >> based on your experience selling software uh enterprise software in China do you think in in our lifetimes there we will go back to American companies trying to sell enterprise software into China or Is that is that ship sail? Because I I I briefly uh lived in China.
1:22:48
Because I I I briefly uh lived in China. I studied abroad there.
1:22:52
I was at uh I I worked out of the China accelerator office in Shanghai.
1:22:57
And I there was a lot of international companies that were trying to sell into China. This was 2016 era.
1:23:04
And there was a sense that the Chinese market sort of wanted to learn about what was being sold, but they didn't actually want to adopt it.
1:23:11
And it was more like how do we learn about this so that we can just build this ourselves and utilize you know >> our networks locally to just kind of out out compete here. >> Yeah.
1:23:22
So listen I I think behavior follows business.
1:23:24
follows business. I think that there are some systems that are pretty straightforward to reverse engineer like a like a actual hardware system where you can pull out the embedded software and you can look at the chip like like you know like let's say network routers right you know classically >> you know was uh Huawei copied Cisco um
1:23:41
routers early on I think for very complex software it's just you know it's like all the operational like knowhow um is just a very tough thing to copy you can look at the code all you want but what you want to know is what it does when it's actually running and that's just not something like the state space is too charge. And so, no, I think
1:23:54
And so, no, I think behavior follows business.
1:23:56
I think there's a lot of business between the two um countries.
1:23:59
I think they're both commercial countries.
1:24:01
They're full of commercial entities.
1:24:03
I do think we're going to go back to like having a market between the two.
1:24:06
Um but I I do think like the landscape is shifting.
1:24:09
Like I do think like listen like right now, you know, we buy, you know, the majority of you know, our kind of hardware parts for robotics from China.
1:24:17
And I would, you know, assume, you know, we sold a lot of software in in China that a lot of the business software like they're adopting from us.
1:24:25
And and um, you know, that, you know, what that looks like may shift over time, but I don't think it's going to go to zero.
1:24:32
>> Do you think humanoid robots are going to start as an enterprise product or consumer product?
1:24:36
Are are how confident are you that it will start where you think it will start?
1:24:43
>> I mean, listen, I'm not an expert.
1:24:43
So, can I tell maybe can I just talk about the piece that I wrote very quickly to put this in context because I want to show like the area where I am expert versus not expert. So, like you're a VC.
1:24:52
You're an expert in everything.
1:24:52
Give yourself some >> I know politics. Yeah. Like I know human noise. I know. No, it's not.
1:24:59
So, so listen, the area I'm expert is is is infrastructure software, right?
1:25:02
I mean, that's what my PhD is in.
1:25:02
That's what my company was in.
1:25:04
what my company was in. That's what I you know and so in order to you know know what is impacting enterprise software and software infrastructure we do these market studies right so we'll study like what's going on with energy we'll study what's going on with microchips we'll study what's going on with robotics like these are
1:25:20
>> and we did this study um on robotics and it was in service to our software investing which we do even though like a lot of you know the groups in Horses do hardware investing right like I've sat on the board of hardware companies like we do it but like the purpose of this study was software investing and we We got the result of this and we're like, "Oh, damn." Like, China's kicking ass.
1:25:36
Like, China's kicking ass. We're like, "Wow."
1:25:39
They like got the supply chain locked up.
1:25:40
They're doing incredibly sophisticated stuff.
1:25:42
I think something like 50% of all deployments for the last three years were done in China for the globally.
1:25:49
And so, the purpose of the piece that we wrote was just to say, listen, you know, we do these studies normally.
1:25:55
We did tons of studies like this, but like this was so dramatic, like maybe we should kind of make it a little bit more apparent to everybody.
1:26:01
everybody. um like you know uh you know how China is doing and so I don't listen I am not an expert on any given robotics market like if it's an enterprise industrial thing I'll have more of a sense to it where like from a humanoid standpoint I think there's huge expert on on that um uh but I will say that
1:26:21
like when it comes to China and the United States I mean they're a very very real contender when it comes to you know the full supply chain all the way up to the hardware it's the software where I think you know things start to differentiate Like how do you characterize the opportunity for America America to catch up? Like should we be more bullish on
1:26:38
Like should we be more bullish on the hyperscalers, the mature companies, the Teslas of the world uh stepping up and taking it seriously or completely new startups from scratch building solutions and then kind of integrating creating their own ketssu if you will.
1:26:56
So here so here um >> let's let's talk about the areas where I think that like um uh the US has an advantage right I mean like I mentioned like complex software the the United States does a great job of um when it comes to like building products that people want I think the United States does a great job of um
1:27:14
>> uh and so I think that right now when it comes to you know Chinese hardware I think we have to really look at ourselves and say you know do we want to like start putting like import restrictions and tariffs on those not not to penalize China but to kind of incur local uh capability building for
1:27:31
these things and I think that would be an important thing for us to consider as a nation doing and there's another very interesting area which is um you know uh for a lot of AI you want big GPUs right and um so you can do a lot of robotics with smaller microcontrollers but you
1:27:44
kind of want the big GPUs for the heavy processing like certainly for AV and it's pretty well known that China doesn't do anything below 9 nanometer very well you know like seven and five they can do it but the yields are pretty low And of course they'll be subsidized by China but they're well behind. So I
1:27:55
So I think at some level like we should continue our >> um uh export restrictions onmeme like you know ASML lithography machines like I think we should do that um just because it does slow them down.
1:28:08
I think we should you know do import controls um uh you know and tariffs so that like we can do local capability building.
1:28:15
But again I like I have no interest in a generational struggle with China.
1:28:18
I just think that we need to understand where we're weak and then we need to um you know put in the controls necessary so that the United States can catch up.
1:28:27
And these are the areas I would say.
1:28:29
So I would say it's not it's not you know the big chips.
1:28:32
I think we're pretty good about that.
1:28:33
Um it's not the software.
1:28:33
I think we're pretty good about that.
1:28:35
But I think actually a lot of the hardware supply chain I do think that we should put our finger on the scale. >> Yeah.
1:28:39
To me, the interesting thing seeing uh Unitry robots selling on Walmart.
1:28:44
com when everyone in the tech community realized probably starting about a couple years ago that letting DJI flood the American market with cheap drones. >> Yeah.
1:28:56
>> Yeah. killed killed our killed our internal you know they they they were willing to sell products at a loss >> in order to uh you know subsidize these products in order to to make it impossible for American companies to compete >> and now we have you know millions of
1:29:12
drones here in America that are flying around that we don't own and they're going to continue that and allowing them to do the same thing with humanoids feels like an even bigger national security risk to me and would again just set us back in an entire entirely new crickets. It's crickets. I haven't heard It's crickets.
1:29:27
I haven't heard the implications. Yeah.
1:29:29
The implications enormous, right?
1:29:31
It's like it's like healthcare.
1:29:32
Like it's like economics.
1:29:35
It's like industrial capacity. It's defense.
1:29:37
I mean, it's like basically as broadbases software if you take the generalized form of robotics.
1:29:40
And so it's incredibly critical that we >> So we have a ge geopolitical rival and we're going to allow them to put a humansized robot that can presumably do human things like uh wait a movie about this once. >> Yeah. Yeah. They can do laundry.
1:29:56
If they can do laundry, they can do a lot of other things that maybe we don't want them, you know.
1:30:00
So So anyways, I I think this is something that uh I hope I hope it gets more attention before it's too late because they're already selling again on walmart. com.
1:30:08
again on walmart.com. I I will say one last thing too is like we kind of sometimes hope that oh like listen this is an issue of scale and like you know we want to work with our partners and our allies and so like what about EU can they help out here but like if you actually look at some of their dominant robotics companies like Cukos I think
1:30:22
it's a 100-year-old company like that's now owned by China as well and so >> I mean even on the global footprint of industrial robots China is incredibly dominant and so I think now is the time for us to map it out and figure out what we do to enable local capability building and again the point is not to penalize anybody or to have a lifelong struggle. The point is to not depend on
1:30:39
The point is to not depend on them and um and to >> what's happening uh in in India on the robotic side.
1:30:46
Obviously, Apple is trying to shift a lot of iPhone production to India.
1:30:50
Is that is that a an area that you're >> I don't I don't have any expertise on that now.
1:30:55
What's going on in India?
1:30:58
>> What about open source LLMs?
1:30:58
Um have you changed your thinking at all?
1:31:00
I know that you were pro- open source generally.
1:31:04
We had the deepseek moment.
1:31:06
Now, OpenAI has GPTO OSS.
1:31:06
Uh, Meta Lama is sort of, you know, declining in favor, but there might be a new generation of models for Meta.
1:31:15
Uh, they're certainly staffing up for it.
1:31:20
And so, uh, do you think that, uh, that market has resolved?
1:31:24
Is it calcified in any ways? Is it heating up?
1:31:27
Uh, is it something that people should be paying attention to? >> Yeah. Yeah.
1:31:31
So I you know I generally think um AI is following open source as we've historically seen it which is the closed source models get 80% of the market and open source mops up the remaining you know 20% and like that's happening now.
1:31:44
I think open source is incredibly important to the broader dynamics of markets you know like kind of anti- monopoly stuff.
1:31:49
It's good for startups it's good for pricing it's good for academia it's good for research.
1:31:53
So I maintain that position.
1:31:54
I think the Chinese models are phenomenal. I think they're leaders.
1:31:58
I think we should keep to having the academic partnerships.
1:31:59
I feel very strong about that.
1:32:01
I think any sort of import or export restrictions on software is stupid.
1:32:05
Like it just doesn't really work to begin with.
1:32:07
And so my view is software kind of, you know, let it all play out.
1:32:12
The US is dramatically ahead.
1:32:15
I would say end to end when it comes to capabilities and capacities for OSS.
1:32:18
The Chinese models are fantastic. You know, we use them.
1:32:21
It kind of will keep us honest. I think that's great.
1:32:24
Where I think that we should be more serious is import and export restrictions on hardware.
1:32:27
I mean, we've done them in the past.
1:32:28
We've done them incredibly effectively.
1:32:30
I mean, you know, especially when it comes to critical infrastructure, and I don't say this from an economic or even from a job standpoint.
1:32:37
I literally say from a national security standpoint, like, you know, do we want to run Chinese hardware infrastructure for our our internet backbone? Probably not.
1:32:44
And if you know what has happened in the last few years with the Telos in China, you can see why this is the case.
1:32:49
And so, I do think having like an aggressive posture when it comes to like what we run >> nationally, what our capabilities are.
1:32:57
Um, >> so are you not worried about the national security uh risks of running an open-source model from a nearpeer competitor?
1:33:06
There's this idea of the uh the Manurian candidate hiding inside of a the weights of an LLM.
1:33:12
It all seems fine when you benchmark it, but once it realizes that it's inside of the, you know, the NSA or something, it phones home.
1:33:20
Uh Red Star Linux from North Korea does that.
1:33:24
does that. phones home and there and you know there's there's rumors that Tik Tok and and saying is having our our physical infrastructure whether it's in manufacturing like robotics in a manufacturing context or or even a humanoid in somebody's home having that
1:33:41
not be something that is a no I I I get that the hardware but like you're asking specific question I'm asking about software like like if if hardware is like a 10 out of 10 risk where is running an open source model from a nearpeer competitor that might want to sneak something in. I don't know if
1:33:56
I don't know if technically they can, but but is it is it a one, is it two, a five?
1:34:00
How would you think about it?
1:34:02
Yeah, >> super legit question.
1:34:03
So, first off, I would say like I'm much more sympathetic to like import restrictions than export restrictions.
1:34:08
I think it's it's just a net good >> for the rest of the world to use US technology and to have that footprint, right?
1:34:14
And so, like when you talk about export restrictions, I think that like when it comes to software, like we should never have any.
1:34:18
When it comes to import restrictions, um I think that you should differentiate between what we use for like the government and critical infrastructure versus like what you have access to academia.
1:34:28
I think for example, if we if we did import restrictions of like the latest greatest models, we would be handicapping our researches in a very significant way.
1:34:35
And I I don't think that that would justify whatever gains we might have given the fact that like half of what we get is from China. >> Yeah.
1:34:42
>> Yeah. Like >> there's also like a free speech like math is should be legal argument here where uh yeah like the government and critical systems and maybe our fortune 500 companies should be very careful with what they run if they're running a
1:34:55
Chinese open source model but if you're just as a libertarian you know you could think like yeah if you want to go and run this on your local hardware in the cabin in the woods like that's pretty American in my opinion. >> Yeah. Yeah. Yeah. Yeah. I'm I'm I'm very >> Yeah. Yeah. Yeah. Yeah.
1:35:05
I'm I'm I'm very very much about never do kind of export restrictions and import restrictions when it comes to software.
1:35:10
when it comes to software. It's strictly listen I used to work for the the intelligence community back in 2001 to 2003 and like this is kind of the height of like concerns around Huawei and so maybe I'm just a little bit more >> sure >> sympathetic to arguments of not having um um you know these components in our
1:35:25
critical infrastructure >> that was the height of the concern around Huawei and it took us how many years to >> actually act on it that makes me concerned about >> the height it was one of the many one of the many peaks of of >> that makes me concerned about by by 2045 we'll get around to banning unree in the United States. Yeah,
1:35:40
Yeah, >> after they after they get a robot in every >> every home, we'll finally be like, uh, you have to pay us 10% tax on this.
1:35:48
That'll be the resolution.
1:35:48
As long as we're making money from it, maybe we'll be fine with this, uh, the result.
1:35:54
Anyway, thank you so much for coming on the show. This is fantastic. Always a good time. Always good to see.
1:35:58
>> We'll talk to you soon.
1:35:58
Have a great rest of your day.
1:36:01
And let me tell you about fall generative media platform for developers.
1:36:07
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1:36:17
>> A6Z used by Adobe Canva players complexity.
1:36:24
>> Uh did you see this post by Jacob Rintto?
1:36:27
>> He said, "Truth nuke, what are you scared of?
1:36:29
Oracle being 500% leopard and not a,000% because Larry isn't agi pill enough.
1:36:35
And tell us something tangible.
1:36:38
You want Porsche 911 that comes with a signed copy of the new Darkeesh Stripe Press book.
1:36:43
Uh we we should be able to make this.
1:36:45
Uh >> those are fantastic answers.
1:36:46
I believe that's a screenshot of the Teal Fellowship application.
1:36:49
Maybe something like that. >> That's hilarious.
1:36:51
Yeah, we we Jacob just just post more post your way to being able to cover 911.
1:36:56
You can get you can get a 97 for like payout. >> Yeah. What's the uh Yeah. Yeah.
1:37:02
What would the monthly payment be on that?
1:37:06
>> My first 911 was like $32,000.
1:37:09
Bought it on Bring a Trailer. >> Yeah. Yeah. Yeah. You finance that.
1:37:10
You pay for it with the Expost.
1:37:12
I think he's >> harder to finance a 997, but uh but yeah, just post your heart out for >> for 12 months and you'll be in you'll be in business.
1:37:22
>> Oh, we uh of course have a Substack now. You can go to tbpn.
1:37:25
com, drop your email, uh, and you can get, uh, a summary of the show, some posts that we like, some important links, the the run of show, and sort of my take, my current thinking on whatever the the current topic of the day is.
1:37:40
I'm also posting those on my personal ex account.
1:37:42
And yesterday, we got a quote post from Zephyr, uh, who kind of answered the question that I was asking, which was, uh, you know, we have to trust the Sam Alman plan.
1:37:52
What is the Sam Alman plan?
1:37:53
Are they building their own chip, their their own data center, their own everything?
1:37:57
Like how mature will this be?
1:37:59
Zephr says, "Is open AI building its own chip?"
1:38:01
Yes, they are in com in collaboration with AVgo Fab by TSMC >> uh will be available in the second half of 2026.
1:38:10
That's forever in singularity terms.
1:38:13
In my opinion, the second half of 2026 feels like it's a decade away, but uh obviously it takes time to actually design and fab these chips.
1:38:20
Uh but I want to know more.
1:38:22
I want to know more about the plan.
1:38:23
I want you doing on uh August 7th, 2009? >> August 7th, 2009. I was in college. I was Where was I?
1:38:31
200 >> Well, instead of having a couple beers, you could have bought Broadcom at the IPO.
1:38:39
>> Uh it was a $164 a share. It's now sitting at 345. >> There we go. >> There we go.
1:38:45
So, >> that would have been good.
1:38:46
>> Go back in time, John, and and figure it out. >> Indeed.
1:38:49
And uh I could have gone back in time and signed up for Turopuffer and been searching every bite, but you can do it today with the power of the internet.
1:38:57
Serverless vector and full tech search built from first principles and object storage fast 10x cheaper and extremely scalable.
1:39:02
Um a Wordle game show is in the works at NBC.
1:39:05
Jimmy Fallon is set to produce a get that size gong ready.
1:39:10
Uh, harvester salon Stallone says, "Well, you know what they say, strike when the iron's cold and has been stored in the cupboard for several years." >> Uh, yeah, Wordle.
1:39:21
That was a Was was that a uh COVID phenomenon? I believe it was 2020.
1:39:26
Everyone was doing Wordles.
1:39:26
I still hit them up every once in a while. I like a good word game. I like a puzzle.
1:39:32
The New York Times has been on a ter I like I like this.
1:39:34
Not true, but I like the meme that people will uh The New York Times makes a lot of money from their games uh and and they have a separate subscription for games and they and and everyone kind of says uh oh, the New York Times is journalism on life support by games and it's kind of uh it's kind of evolved to the point where like they make 99% of their revenue from games.
1:39:54
It's like that's not true.
1:39:56
>> They got to get into they got into getting get into gambling.
1:39:59
>> They should get into gambling. That's great.
1:40:01
>> They have an insane user base. >> Yes.
1:40:03
And you know, they're they're an eight they're a $9 billion company. >> Yep.
1:40:08
>> So, uh, basically the New York Times is valued the same as Poly Market.
1:40:12
>> And, uh, what you know what what what could the New York Times do with, uh, they could do mail order gambling? I would love that.
1:40:20
>> Mail order prediction markets.
1:40:21
>> I would love I would love a daily gambling.
1:40:23
A daily >> the daily gamble. >> The daily gamble.
1:40:28
>> Imagine the the New York Times betting podcast. >> Yes.
1:40:30
I have another idea for them.
1:40:30
Since they're into games, they're into Wordle.
1:40:35
They should do a first person shooter. >> There you go.
1:40:38
>> Don't you think it'd be good?
1:40:38
You know, we have Call of Duty, we have Battlefield. >> Yeah. Team Deathmatch.
1:40:41
You go to new york times.
1:40:43
com, it just preloads a vibe code.
1:40:46
>> You get to play as a legend of Mike Isaac. >> Yes. Exactly. Yeah.
1:40:48
You get you get Mike Isaac.
1:40:52
>> Um Russell Pollson quoted our post.
1:40:52
We were talking about the anthropic ad campaign.
1:40:57
Uh he added some insight.
1:40:57
He says, "This is all about values-based marketing.
1:41:01
It's not about the hat or what Claude does technically.
1:41:03
It's about how it makes us feel and how it elevates our inherent humanity.
1:41:07
It's a breath of fresh air to feel like an AI tool makes us better rather than replaceable." Yes. >> Very well said. >> I like that a lot.
1:41:14
And it does feel like a feels a little bit written like like Claude. It's not about the hat.
1:41:19
It's about >> You can't Yeah.
1:41:22
I like when I when I write now, I actively think like, okay, if I'm gonna if I'm going to try and put something in a it's this, not that, I'll just completely rephrase the sentence to just be, you know, just wildly different structure because uh it can just it just has a a tinge to it these days. >> Yeah.
1:41:40
>> Um anyway, >> says OpenAI plans to detect underage users and give them a model with more safeguards.
1:41:45
This may clash with Colorado's SB 205, which prohibits algorithmic discrimination based on age. What is Colorado doing?
1:41:52
Um, one of literally millions of pro-social AI uses plausibly rendered illegal by that stupid law.
1:42:00
Um, very uh, yeah, very interesting that a single state is going to be able to uh, potentially create policy uh, nationwide policy around AI.
1:42:13
I think David Sax has been kind of ringing the alarm bells about this and there's been a number of folks we've we've talked to on the show who have said that like the stateby-state stuff is going to make it really it it sort of turns us into Europe where you have like one cookie policy that then cascades all over the place.
1:42:33
At the same time, I feel like is it not possible to just like geoence a feature >> still?
1:42:39
I mean, you have 50 states if they all have different laws.
1:42:41
Colorado only has 6 million people.
1:42:43
We 40 >> I'm not worried about the technical burden.
1:42:48
Should be able to oneshot that with codeex. Come on. We're in the future.
1:42:52
But I am worried about some weird situation where one of those Coloradoins is on the border and the cell phone tower that they connect to says that they're in a neighboring state and then that creates a liability and there's a class action lawsuit.
1:43:06
or they're using a VPN and the VPN doesn't count as actually leaving Colorado.
1:43:10
And so there's a lawsuit there.
1:43:12
And and if it just becomes a legal precedent that uh requires you to to treat the entire United States populace like the the folks in Colorado, that could be very very annoying and kind of just dampen everyone's experience.
1:43:27
Because when I think about, >> you know, we have kids, when I think about if they're using AI tools, like I like the idea of more safeguards.
1:43:35
I, you know, I I like that if you open up the the Disney app on on Apple TV, you can choose don't show anything R-rated or PG-13 and just, you know, content filtering, adult parental controls.
1:43:49
Like, these are good tools that should be in the hands of parents and they should be in and they should be surfaced by the tech companies.
1:43:55
Also, I don't really want if if uh you know, my son's very into dinosaurs and if he's someday talking with chat GPT about dinosaurs, I don't really want don't feel like it's necessarily fully appropriate for the to for him to feel like he's becoming friends with the dinosaur machine.
1:44:14
>> Yes, I would also I think we're probably years and years and years away from him using LMS.
1:44:18
Um >> I would also just be worried about annoying uh syntax leaking into his vocabulary.
1:44:24
is like, "Dad, this isn't a Tyrannosaurus Rex.
1:44:27
It's the king of the jungle." Like, "Come on, dude. >> It's not bedtime. It's playtime. >> It's play time."
1:44:37
>> Which is basically the constant debate.
1:44:39
>> Uh, anyway, did you do we mention Profound? Get your metal.
1:44:42
Get your brand mentioned in chat GPT.
1:44:43
Reach millions of consumers who are using AI to discover new products and brands.
1:44:47
Um, we always got to mention them.
1:44:49
Uh PE Cooper >> at the timeline built his own TBPN meme template and he's putting it to use. >> What is this picture?
1:44:57
Is this just how he sees himself as a royal lord?
1:45:03
>> I love the >> very base.
1:45:05
>> I love the enthusiasm to just hardline that you're a 18th century or 15th century king or something. I like it. It's very royal. Very >> real.
1:45:15
You can go check out he he has a he has a meme maker you can make your own.
1:45:20
People have been adopting the uh TVPN trading card aesthetic.
1:45:22
Uh thank you for to Tyler Cosgrove for I believe inventing that whole like strategy or something like that.
1:45:31
I think you made the first one of the AI researcher that got 5 million views on X and then was shared all over the internet and wound up wound up getting us on French TV.
1:45:40
>> Did you wind up talking to the French journalist by the way?
1:45:42
Uh, I talked to them, but I I don't think they wanted me as like an actual interviewee. >> Okay. They didn't film you.
1:45:48
>> They I think they want uh people that work.
1:45:50
>> They're not real fans of the show.
1:45:51
Clearly, >> a true fan would have said >> that you're uh yeah, a heavyweight in the industry.
1:45:56
We we we tried to pitch them this idea that that Tyler was uh was was beyond the metal the Met list, the zeroith. >> Yeah.
1:46:05
>> AI researcher since of course lists are indexed at zero.
1:46:08
>> Uh Bill Aman says in one week Jared Kushner pulled off the biggest LBO of all time.
1:46:12
That is EA and that negotiated one of the biggest peace deals of all time. A pretty good week. Uh that's wild.
1:46:18
Really just running the art of the deal playbook.
1:46:21
>> We have been so behind on our EA coverage.
1:46:23
Uh would love to have Jared on the show.
1:46:25
Uh in the meantime, you can listen to his interview on Invest Like the Best if you want to understand more of his investing philosophy.
1:46:30
Uh the EA uh Take Private is fascinating. It's a massive deal.
1:46:35
Uh EA has so many interesting properties from Battlefield to they have Madden, right?
1:46:40
And FIFA, they have all the sports.
1:46:43
Um and uh it's just a very interesting business.
1:46:46
We've talked for a long time about uh what it takes to pivot a business model in the public markets, how difficult that is.
1:46:55
Will they be pivoting the business model to what?
1:46:58
If so, will they be doing that? Is that the point?
1:47:00
Or is there some other restructuring that will happen while the company's private?
1:47:03
That's fascinating to me.
1:47:05
Ben Thompson had an article in Stretchery today, which of course you should go subscribe to, um, all about, uh, the the the basic basically the failure of Xbox Game Pass because Microsoft uh, paid something like $70 billion for Activision.
1:47:20
They got Call of Duty and the idea was they would put people on a Netflix-l like subscription and you'd be able to play any game you want.
1:47:28
And according to some, you know, rumors and talking to some Microsoft employees and some leaked data, it seems like the LTV went down.
1:47:39
So, it seems like it was actually better to get people to shell out 60, 70 bucks a couple times a year for the big games that they want as opposed to putting them on a $10 a month plan and then they're playing all these games for much cheaper.
1:47:52
And so, uh, it's been, you know, the the conclusion is that it's it still isn't working.
1:47:57
Um, we'll have to keep checking in on it, but uh it'll be interesting to see does EA go private and then find land with Sony or something like land with another another, you know, gaming platform?
1:48:08
Does it create its own store or, you know, pivot into, you know, buying other companies and getting into mobile gaming?
1:48:17
Is there some sort of uh other monetization microtransactions?
1:48:20
Like, what are they going to ramp up?
1:48:22
Uh, they've tried a lot of stuff, but it'll be interesting to see where it goes.
1:48:26
would love to talk to the folks over at Silverlake and uh Jared Kushner's firm. >> Will understand that.
1:48:32
>> Manitis says it's genuinely nuts that if you get good enough at New York City real estate that the only other place where those skills are useful is negotiating world peace.
1:48:41
>> I didn't realize that these two these two were connected, but of course it's about Jared Kushner.
1:48:43
That's >> and Trump, of course. >> Yes. Oh, yeah. Trump. It's very funny.
1:48:50
Uh should we cover the the China news today?
1:48:52
So uh Dimmitri Alperovich says huge escalation by China Mofcom Moffcom announces new export controls taking effect after December 1st of rare earths to anyone anywhere in the world producing chips or equipment to make chips below 14 nanometer and 256 layer memory due to military applications.
1:49:15
And so uh Dean Ball had a big take on this that we should probably read through to get up to speed.
1:49:23
I'm not an expert on this, but uh I hope to be after talking to Dean.
1:49:27
Uh we're hoping to have him on the show soon.
1:49:29
Uh Dean says, "This is a very big deal.
1:49:31
China has asserted sweeping control over the entire global semiconductor supply chain, putting export license requirements on all rare earths used to manufacture advanced chips.
1:49:42
So we have the design firms with Nvidia.
1:49:44
We have TSMC kind of on our side. We have ASML.
1:49:47
There's a whole bunch of American IP that goes into the western semiconductor supply chain, but China's upstream of all of that with their rare earth supply chain.
1:49:56
There was a comment in the chat earlier about um about what um uh did like does China control all of the rare earths?
1:50:04
I think the the the the commons cited metrics are that they control a huge portion of the of the rare earth supply today, but they don't actually have all of the rare earths in >> more processing than supply.
1:50:19
Rare earths aren't as rare.
1:50:23
>> We just call them earths. >> Yeah.
1:50:24
And around here we call them earths >> because they are in fact all over the place.
1:50:28
And you hear about these rare earth deposits being found in Ukraine and in various parts of the United States. We have them.
1:50:33
we just haven't actually gone built the mine and processing and that takes years and so uh in the short term putting an export restriction on uh the actual processed rare earths is very geopolitically significant.
1:50:46
So Dean Ball continues he says if enforced aggressively this policy could mean lights out for the US AI boom and likely lead to a recession/economic crisis in the US in the short term.
1:51:00
the short term. remember this wouldn't be the first time they tried to I mean the deepseek moment felt >> at the time very calculated let's ramp this app up the charts that I didn't still didn't know a single person >> that was using deepsek it felt entirely
1:51:16
>> uh that that that the chart run felt entirely manufactured uh and that the immediate effect on markets was insane remember >> counterpoint maybe they were just trying to take a little bit of air out of the bubble to create a bull catalyst I mean everybody if markets go down that's a bullish catalyst. >> Yes. It's also inspires us to grow grow >> Yes.
1:51:35
It's also inspires us to grow grow grind harder.
1:51:37
Y uh Tyler do you know ball >> Dean Ball? >> Oh I know. Yeah. >> Oh you do? Okay cool. >> Oh he knows. Okay >> good. Uh do you know linear?
1:51:48
>> That's why we hired you.
1:51:50
>> It's a purpose-built tool for planning and building products.
1:51:51
Meet the system for modern software development.
1:51:54
Streamline issues projects and product road mapaps.
1:51:55
You can start building for linear.
1:51:57
Uh some thoughts and recommendations from Dean Ball.
1:51:59
Uh many things are unclear including how intensively they will enforce this.
1:52:04
This is a costly decision for them too and not without risk.
1:52:09
These controls are being imposed on the whole world, not the United not just the United States.
1:52:14
Uh my current assumption is that China is doing this to gain leverage over the US in advance of the president's upcoming meeting with Cinang at APEC.
1:52:19
Uh it'd be very funny if they just put the controls in the United States and then you had a bunch of startups that were like, I'm going to do diversion and I'm going to go set up a a uh uh a rare earth uh you know buying and selling operation in uh you know Dubai or Malaysia or somewhere.
1:52:38
Uh that'd be very interesting.
1:52:40
Uh number three, I do not think they are doing this to get the US to relax its export controls on Nvidia Blackwell chips.
1:52:47
In fact, my guess is that they want us to think that's their goal.
1:52:51
We buckle by relaxing Blackwell controls and then the PRC shrugs and says, "No thanks.
1:52:55
We're very confident in our domestic chip industry."
1:52:57
That is a message I'd want to be delivering to APEC if I were advising the PRC.
1:53:02
Four, further relaxation of export controls is therefore unlikely to be a useful policy lever here.
1:53:10
Instead, it is time for the US to get serious about export controls on semiconductor manufacturing equipment. Five.
1:53:16
Because we have been mostly uncserious about this issue, China has stockpiled most durable equipment needed to make semiconductors.
1:53:24
So most controls will not have an immediate effect. Six.
1:53:26
He really ran through this. This is great. Um, six.
1:53:32
However, there are some uh there are there are some consumable materials needed for semiconductor manufacturing that ch China cannot make domestically.
1:53:39
Even better, those consumables are often degradable, meaning one can only stockpile so much.
1:53:42
These would be on the top of my list if I worked at BIS.
1:53:44
Uh I would strongly I would retaliate strongly but in a targeted manner.
1:53:48
The ultimate route to deescalation here is tariffs and broader trade war policy moves not AI compute.
1:53:54
This only underscores the urgency for the US plus allies and partners to accelerate domestic efforts to mine and refine rare earths. Let's hear it for that.
1:54:02
Uh the Trump administration has been especially strong here and Congress allocated serious money to this goal in 03B.
1:54:08
But all options must be on the table including the defense production act.
1:54:15
policy will be important here, but remember that these rare earths are essential to the functioning of the global economy.
1:54:19
It has heretofor been hard to solve with markets alone because China already supplies these commodities in abundance and at low cost.
1:54:26
But they are fundamentally just commodities. We can make them.
1:54:30
And 10, to the extent China enforces this policy, they will have made the price of these essential goods infinitely high.
1:54:37
Remember most of all that supply is elastic not on arbitrarily short time cycles but faster than most people think.
1:54:45
So we if the prices is is infinitely high there will be a huge incentive to go start mining rare earth elements in the United States. >> Interesting.
1:54:55
MP materials is actually down6 of a percent uh in the last 5 days which is of course a company that the Trump admin took roughly a 15% stake in. Yeah. uh in rare earth.
1:55:09
>> Well, Peter Heg says, "Sir, a second whispering to the president meme has hit the timeline." Is this a real photo?
1:55:16
This feels like something that someone would have AI generated, but it looks real to me. It's from Reuters.
1:55:19
Uh, and sir, a second ad read has hit the timeline with numeralhq.
1:55:24
com sales tax on autopilot.
1:55:26
Spend less than five minutes on sales tax compliance.
1:55:30
Um, I screenshotted that one twice. It was so good.
1:55:33
Uh Andy Jasse says Joseph Carlson the current CEO of Amazon has been with the company for 28 years. Wow. Andy Jasse what a run.
1:55:41
In 2003 he played a pivotal role in creating and scaling AWS which is the most valuable part of Amazon.
1:55:48
A significant portion of the modern internet is powered by AWS.
1:55:52
Amazon today is worth $2.
1:55:52
4 trillion and is one of the most critical companies to the United States and the world.
1:55:57
Yet the CEO makes less money than many YouTubers, comedians, podcasters, professional athletes, and actors that don't manage or guide anything nearly as important or critical to the US or have millions of employees.
1:56:10
We need to stop pretending that the CEOs of Fortune 10 companies who have helped build trillions of dollars worth of value for investors should have their salary compared with the delivery drivers working their way through the through college.
1:56:24
This trope is old and should be retired.
1:56:27
Yeah, Josh Holly, uh, senator for Missouri says is firing shots at, uh, Jasse, saying, uh, why how is it proworker or pro-American that he makes at least 40 million a year while the average American Amazon worker makes less than 38K a year?
1:56:45
Um, >> well, he needs to go on a campaign.
1:56:49
Bobby in the chat says Andy Jasse doesn't even have 200,000 Twitter followers. That's rough.
1:56:53
He's also never streaming on Twitch.
1:56:56
Get on Twitch, Andy Jasse.
1:56:59
We'd love to see >> that's your product. >> I know they own it. Amazon owns Twitch.
1:57:04
And so that's where he should give his press releases. >> This is wild.
1:57:06
Chip Wilson, Lululemon founder, takes out a full page ad in the Wall Street Journal to roast the brand that he started.
1:57:14
>> When was this in the journal?
1:57:14
Was this >> Lululemon in a nose dive?
1:57:15
He says, "When I founded Lululemon in 1998, it was built on a relentless focus on innovation, product culture, and customer experience.
1:57:22
We invented a quote unquote technical product business model, created a new apparel category, pioneered community marketing, and developed uh system processes so simple a refrigerator could manage them.
1:57:33
Uh by its 25th anniversary, Lululemon should have been a hundred billion dollar market cap company.
1:57:39
Instead, its trajectory has declined. Why?
1:57:41
Lululemon directors have system systematically dismantled the business model and lost employees who held the institutional knowledge that made the company great.
1:57:51
Like a plane crash, decline rarely happens because of a single failure.
1:57:55
It's a series of mistakes.
1:57:55
He's adding uh some different sections here. One, the founder leaves.
1:57:59
When a founder leaves, boards tend to fill committees with operators or finance focused directors who are beholdened to quarterly commitments.
1:58:06
A company bereft of a visionary loses its singular voice for product and long-term strategy.
1:58:10
A strategy that builds a mode around success.
1:58:13
An operation/finance-driven board lacks the moxy to understand the market pulse.
1:58:20
uh uh gap gapivization, loss of creative to the merchants.
1:58:24
Every few years, a design team will stumble.
1:58:27
When that happens, merchants and MBA swoop in, claiming to be the adults who can deliver consistent quarterly projections for Wall Street.
1:58:32
To meet those projections, merchants follow algorithms and double down on what sold the year before.
1:58:37
This kills risk-taking and prevents new innovative product from emerging.
1:58:40
As a result, innovation dies, the brand becomes predictable, customers drift, and the best creative people leave. The domino effect.
1:58:46
As top talent leaves, short-term results often look strong.
1:58:50
The board harvests brand value by rapidly growing store count while margins expand through economies of scale.
1:58:55
Wall Street is ecstatic and the egos of directors and management sore.
1:59:00
Meanwhile, operate owner operated competitors seize the opportunity producing better product.
1:59:03
Lululemon's institutional knowledge walks out the door often to competitors and is replaced by Nike executives.
1:59:09
Shots fired who failed business model.
1:59:12
Desperate for growth, Lululemon squandered 1 billion on Mir and wiped out 10 billion in market cap with a widely wildly inappropriate Disney collaboration.
1:59:21
To squeeze margins further, directors cheapened store design and shifted to non-technical fabrics, eroding the brand's premium positioning. Cultural erosion.
1:59:31
New executives from old school companies chase short-term margin growth and resume building.
1:59:35
directors unwilling to confront their own role in the decline and attempt to replace a CEO only to realize for the third time that they've failed to develop an internal successor with the brand faltering.
1:59:45
No capable candidate wants a CEO job.
1:59:47
The nominating committee struggles to attract directors because no great leader wants to join a sinking ship. Uh loss of cool.
1:59:54
The board insists on operator finance CEOs who can speak Wall Street, rejecting the idea of a product-driven CEO.
2:00:00
These types of finance focused CEOs don't know how to attract or motivate creative talent.
2:00:04
Or even worse, they think they understand how great product when they don't.
2:00:08
Without an eye for outstanding design, the company dies a slow death.
2:00:10
Lululemon forgot its muse.
2:00:13
The woman who inspires culture, not just follows it.
2:00:15
By drifting toward the mainstream and trying to appease everyone, Lululemon lost 50% of its market cap earned from brand power.
2:00:24
It's it lost its edge and with it the ability to hire the best people.
2:00:28
The result on paper, Lululemon still looks good, but it's losing its soul.
2:00:32
The deeper issue, $20 billion company >> that is getting absolutely smoked by Aloe in their core segment, which is the muse that he described above >> and founders back at Outdoor Voices, too. >> Yeah.
2:00:44
So, he says, "The deeper issue is not just management.
2:00:46
It's a disengaged nominating and governance committee that has failed to safeguard the company's long-term vision.
2:00:50
The path forward, I believe Lululemon can recover, but survival requires courage.
2:00:54
Put product and brand back at the center.
2:00:56
Rebuild the knowledge and systems that deliver product in nine months, not two years.
2:01:01
Bring entrepreneurial ownership back onto the board.
2:01:03
Three, empower creative leadership over merchants.
2:01:05
Four, stop chasing Wall Street at the expense of customers.
2:01:09
Five, recommmit to the muse, the woman who inspires the brand.
2:01:12
The world doesn't need another bland, quarterly driven apparel company. It needs bold vision.
2:01:16
It needs Lululemon to fly again.
2:01:18
Lululemon can keep growing, but growth alone is not a healthy measure of success.
2:01:22
The true measure must be innovation and brand reputation.
2:01:27
When those are strong, growth comes naturally.
2:01:28
When they're not, growth halts.
2:01:30
The path the path is clear, but only with a revitalized board of directors with diverse capabilities.
2:01:36
Sincerely, Chip Wilson, founder, Lululemon. >> Chad Wilson.
2:01:40
>> When uh when did he actually >> step off the board? >> No.
2:01:45
When did when did this actual article come out?
2:01:47
>> It feels like I mean it's not it's not in today's paper. I checked every page.
2:01:51
So, >> but I think it but it must be recent. >> I think it came out. I'm on the journals. >> Yeah. >> Yeah.
2:01:58
I think it came out yesterday.
2:02:00
>> What's interesting is like I'm surprised he had to pay for this.
2:02:01
Like this would just be a good opad to throw in there.
2:02:05
But uh it does hit >> it's kind of it hits harder that he's paying out of his own pocket.
2:02:10
>> And the layout also just feels very I don't know iconic.
2:02:13
It looks a lot different.
2:02:15
So >> we should get Chip on the show.
2:02:17
>> I'd love to talk to him about that.
2:02:19
>> Um yeah, I mean they're just being competed from every possible angle.
2:02:24
There's new brands all the time that are more kind of core Lululemon customer.
2:02:28
You have Aloe, you have Vory, you have Skiims from Kim Kardashian, right?
2:02:34
And all these brands are just uh better serving that that uh initial cohort.
2:02:39
So, >> y >> um >> well, let's get him on the show. Let's pitch him Finn.
2:02:46
ai, the number one AI agent for customer service.
2:02:48
Morris, >> number one in performance benchmarks, number one in competitive boffs, number one ranking on G2.
2:02:55
Uh, did you see Wayi Capital uh taking a shot at Samuel Gibson?
2:03:02
We'll hold our we'll hold our uh judgments until we uh actually meet him.
2:03:09
So, uh, Wayi Capital says, "Incredible things are happening in the nuclear grift space.
2:03:14
Meet Samuel Gibson, Zoomer, who graduated from college in 2023.
2:03:19
>> Let's give it up for Zoomers. >> Yes.
2:03:21
And is now co-founder and CEO of Hadron Energy, a nuclear vaporware company going public via spa at a $1. 2 billion valuation.
2:03:29
Uh >> they have uh according to LinkedIn between two and 10 employees. >> Okay.
2:03:37
>> So, >> but 11,000 followers.
2:03:39
>> Everybody starts uh everybody starts somewhere. >> I don't know.
2:03:42
I mean, you got to get the money to build a nuclear reactor.
2:03:43
at some point >> and they raised they a $900,000 preede according to crunch base that's also >> you went from 900k preede to 1.
2:03:51
2 billion spa I mean built different gen Z really on a tear he had a 3.
2:04:00
4 four GPA at University of Nebraska link Lincoln Lincoln. Um, >> not bad at all. >> I don't know.
2:04:06
Get the get the bag, get the get the cash, build the thing hopefully. >> Got to build.
2:04:11
You got Yeah, you can't purely cash out and then ride it down. You got to turn it.
2:04:16
You can spack it, but you got on their website.
2:04:19
>> You got to deliver the actual energy.
2:04:21
>> On the website, they just have they have like a bunch of renders. >> Yes.
2:04:25
>> And one of the renders just says data center one on it. >> Okay.
2:04:29
They got So they got data centers. Data centers. Yeah.
2:04:32
But they're saying the world's smallest, lightest, most versatile micro modular reactors. >> This Yeah.
2:04:39
>> And the design is awesome. The renders are awesome. >> Yeah. Lot of lot of work.
2:04:41
Uh I mean I I I feel like >> and they have a Tesla Cybert truck render pulling a render of their >> micro reactor.
2:04:52
So it's uh >> it's looking it almost looks kind of like Fortnite.
2:04:57
huge question on who's actually underwriting the spa, who's running this thing, how did the cap, who's how did the capital go into the pipe, like what what actually happened here.
2:05:07
Um, you know, there's the spaxs are not inherently bad.
2:05:11
Uh, you can raise money uh in a variety of ways and if you go and actually deliver and generate a lot of cash flow, at some point you'll be worth way more than what you spacked at.
2:05:22
So, um, good luck to him, but it does seem like a tall order in one of the most heavily regulated capital.
2:05:30
>> Gig Capital Global is putting up, uh, >> how much >> some of the cash here >> and they also, uh, you might remember they are investors in Big Bear AI.
2:05:42
>> I don't know Big Bear AI.
2:05:44
>> I didn't I didn't think you would. >> Okay.
2:05:46
Well, >> uh, but anyways, we'll we'll see here.
2:05:48
I think I think we should withhold uh judgment.
2:05:51
I I uh >> the renders look cool. >> Plug it in >> there. Plug it in. Plug it in. Plug it in. >> Just plug it in. Plug it in the reactor.
2:06:00
Generate some electricity profitably. >> It's time to plug.
2:06:02
Tyler, you should talk to him >> and uh see see how real it is. >> Yeah.
2:06:09
>> I mean, I I've been thinking about getting into the Spack game. >> Oh, yeah.
2:06:11
What are you gonna spack?
2:06:13
>> Uh I think I'll I'll probably figure it out later on.
2:06:15
I'm kind of started the the motions already, but >> just empty shell for now. >> Yeah. >> Selfack.
2:06:20
Cabal Raza >> could go any direction.
2:06:23
>> Yeah, I'm surprised somebody hasn't tried to spack themselves with some type of income share agreement yet.
2:06:30
>> During the NFT boom, someone did. Wasn't it Alex token? Am I getting that wrong?
2:06:34
Some >> Yeah, but a lot of that he definitely, I think, started a trend of people, >> isn't this the Ben Pastnack thesis as well?
2:06:40
You will, everyone will have a uh a coin attached to them or their project.
2:06:45
>> Nathan Summers in the X chat, are you guys hiring for a narrator intern? I have great cadence. He's a drummer.
2:06:50
And tonal variety for an exciting viewer experience.
2:06:53
I also would hate to see a vocal cord strain cut down on your ability to run the live show DM.
2:06:59
>> Imagine being able >> Tyler, reach out to Nathan.
2:07:00
We we got to talk to this guy. >> Okay. Yeah.
2:07:03
He's just sitting here and we say, "Read read me this Wall Street Journal article." >> Yeah.
2:07:07
a narrate uh >> narrate and we will just do the reaction, but we want you in person live to read us this story from the Wall Street Journal on can Ferrari persuade the super rich to buy an EV sports car that won't rev.
2:07:20
We're going to read this article, but first I'm going to tell you about Adio customer relationship magic.
2:07:26
Adio is the AI native CRM that builds, scales, and grows your company to the next level.
2:07:28
So, the brand Ferrari is planning to unveil its first all-electric model next year and uh it's a bold move. It's a bad time.
2:07:39
Probably something that was uh green lit years ago.
2:07:41
Uh but we will dive into it in this Wall Street Journal article.
2:07:46
>> And uh some backstory here.
2:07:46
Ferrari just updated guidance.
2:07:49
They had a capital markets day.
2:07:52
Wall Street was not excited about it.
2:07:55
The stock is down 18% in the last five days.
2:08:00
>> Okay, >> let's get into uh their next vehicle, which I think is something no one wants. >> We will see.
2:08:08
Uh extravagantly powerful and noisy engines helped make Ferrari the ultimate sports car brand.
2:08:13
Now, the company wants to persuade the super rich to buy a model with no engine at all.
2:08:20
The Italian car maker this week started lifting the hood on its first electric vehicle, a yearslong project that has cost the brand hundreds of millions of dollars and promises to set a benchmark for how batterypowered sports cars should look and look sound and drive.
2:08:33
At a glitzy launch event at its headquarters in Marinelo, Italy, Ferrari showed off the technology that will power the EV, including a new electric axle, motor, and battery pack set to be made inhouse at its factory. Wow.
2:08:46
going vertically integrated all the way down to the battery on day one.
2:08:50
That's both, >> which is wild because Ferraris have uh always been known to have electrical issues, including the Ferrari that I owned that uh I I think I replaced the battery, forget exactly how many time, but I had to replace the battery multiple times in a single quarter. So, >> skill issue.
2:09:11
>> Um >> it it said the vehicle called the Ferrari Electrica.
2:09:16
>> What do we think of that name?
2:09:16
Uh, >> it's not quite there.
2:09:20
>> The Dol Trindi hits, you know, the Electrica maybe.
2:09:24
>> It feels like a name that somebody that was like trying to come off as an Italian >> maybe >> brand would would use.
2:09:31
>> Well, it'll be able to go from 0 to 62 mph in 2. 5 seconds.
2:09:33
Uh, which is fast, but not as fast as a Model S Plaid that you can get on Bring a Trailer for 50k now.
2:09:45
So, um, it has a top speed of 193 mph.
2:09:49
The range on a single charge will be at least 329 miles. That's not bad.
2:09:53
Uh, the company won't reveal what the model looks like until next spring with deliveries slated to start later.
2:09:59
>> Apparently, the Model S Plaid does 1.
2:09:59
99 seconds, although >> 1. 9999.
2:10:06
>> I would try that out to be honest.
2:10:09
>> You wouldn't or you would?
2:10:10
>> Maybe on a Maybe on like a runway. Yeah.
2:10:12
But on a on a normal road, I wouldn't want to I wouldn't >> You wouldn't want to go that fast.
2:10:17
>> I just uh >> Well, maybe when you're an adult, when you're when you're a man. Yeah.
2:10:21
>> Then then you can do it.
2:10:22
>> When I finish growing. >> Yes.
2:10:24
Uh the debut comes as a as the global auto industry adjusts to a slower transition to EVs than expected when Ferrari announced the project.
2:10:31
So when Ferrari started working on this, everyone was saying everything's going to be EV. EV is going to dominate.
2:10:36
It's not just going to be some like subcategory of the market.
2:10:39
It's going to be everything.
2:10:40
So, you got to get in on it.
2:10:42
And of course, other sports car makers such as Porsche, Lamborghini, and McLaren have delayed plans to build electric models, citing weak demand.
2:10:50
While Ferrari is committed to launching its first EV on schedule, it has scaled back its wider bet on the technology.
2:10:54
At an investor day Thursday, which you mentioned, uh the company said EVs would account for 20% of its vehicle lineup in 2030, half the share previously indicated.
2:11:04
Uh we know that this path is not easy.
2:11:06
Ferrari chief executive Ben Benadetto Vigna said in an interview, "But we also know that we as a leader need to show the entire world that we can harness this technology."
2:11:16
At the same time, the company plans to release many new vehicles with traditional engines.
2:11:21
According to its latest product roadmap, the Ferrari Electrica is one of 20 models set to launch through 2030, more than previously planned.
2:11:28
Uh despite the new models, Ferrari issued c a cautious sales forecast 5% annual revenue growth through 2030 and the stock fell 12%.
2:11:37
Uh since being spun out of fiat a decade ago, Ferrari has become Europe's most valuable car maker by persuading uber wealthy gear heads to splurge hundreds of thousands of dollars on meticulously crafted sports cars.
2:11:52
EVs pose a particular challenge for luxury sports car brands which say Roar and Rumble are central to their identities and appeal.
2:12:01
Ferrari perhaps more than any other automaker.
2:12:04
>> Imagine Nathan in the chat narrating this right now.
2:12:08
>> I know it could be so much better.
2:12:08
Uh the brand is known for its noise.
2:12:10
The Dolce Trillindri is naturally aspirated, meaning it doesn't rely on a turbocharger to push air into the cylinders.
2:12:18
An old school approach credited with a more natural open roar.
2:12:22
Ferrari said its EV wouldn't mimic engine sounds as some competitors have like the Kia EV6 GT.
2:12:27
I forget what it's called, but uh >> yeah, that was a engineer from the M series, right?
2:12:34
That >> that's Hyundai actually.
2:12:35
So, the the the engineer who created the M division at BMW went over to Hyundai and created the N division because N comes after M and uh tuned up a bunch of the Hyundai to be performance cars.
2:12:50
And one of them is the Hyundai EV6 or something.
2:12:56
I'm getting the the exact model name wrong.
2:12:59
that uh it has not only uh engine noise that comes through the speakers, but a simulated dual clutch transmission that you can operate via paddle shifters that are entirely digital.
2:13:10
And so you can essentially be rev limited and be redlining the car even though it doesn't have a real red line.
2:13:17
And a lot of the super old school car lovers tried it.
2:13:24
Doug Demiro and a bunch of other po folks uh Matt Farah uh from Smoking Tire all tried it and they were like this is amazing.
2:13:31
Like I forgot that I was driving an electric vehicle after just a few minutes in the car.
2:13:35
And so the prediction at the time was that every electric vehicle car maker would adopt that same simulation technology because it was popular and it's pretty easy feature to add.
2:13:47
Seems like Ferrari won't though.
2:13:49
They're going natural EV.
2:13:49
Um, instead it will pick up the sound of what it calls the electric engine and amplify it into the cabin to give the driver feedback when required.
2:13:58
So, you'll hear the electric engine woring.
2:14:03
The company compared the difference between its conventional sports cars and the EV to the difference between an acoustic and electric guitar.
2:14:07
Ferrari also faces the risk of EVs losing value faster than traditional models as the battery degrades.
2:14:13
The promise of timelessness is a selling point for Ferrari buyers.
2:14:17
company leans into the economics of the luxury industry, carefully limiting supply to ensure that its top models retain their value over time like like Rolex watches or Hermes handbags.
2:14:28
And if you want a Rolex, head over to getbzel. com.
2:14:30
Your bezel concier is available to source you any watch on the planet. Seriously, any watch.
2:14:35
>> So, uh, Elen also recruited Johnny IV to work on the brand's first electric model. Oh, interesting. I didn't realize this.
2:14:45
We talked about this with love from having a Ferrari partnership.
2:14:46
This is the car that was designed by Johnny IV. That's fun.
2:14:51
Uh to make its electric cars, Ferrari built a state-of-the-art factory uh which ca which became known as the ebuilding after heavy investment.
2:14:59
The question now is whether Ferrari's wealthy clients will want to drive the new model.
2:15:03
Imagine, imagine, you know, spending your whole life as, you know, being obsessed with the Ferrari brand, learning to work on on uh on these engines and then getting the tap on the shoulder and saying >> you're actually going over to the E building. >> Yeah.
2:15:18
And I think there's there's also this factor that um the it feels like the really highly engaged Ferrari buyer maybe doesn't care about straight line speed that much.
2:15:31
It's never been a muscle car.
2:15:32
Uh the more exciting number that folks track is like the Nurburgring time and the gas cars are still performing extremely well. >> So just the feeling. >> Yeah.
2:15:44
>> The the factors that for sure. >> Yeah.
2:15:46
Just the feeling of driving the car.
2:15:47
What the the ownership experience, right?
2:15:50
The the the main critique of Ferrari from some of the more I would say casual clientele is like the depreciation recently.
2:15:59
I think the cars are just losing value far more quickly than they historically did.
2:16:04
Part of that is already because uh the hybrids, right, the the SF90s, the the S um the 296 is also a hybrid, right? >> Is that depreciating?
2:16:13
I thought that one was kind of holding its value a little bit more >> a little bit better, but I mean you can buy them for less than sticker with like three, you know, way less than sticker for like 300 miles on them.
2:16:22
Um, I would have expected Ferrari to try to go more towards something like a Nissan cross cabriolet. >> I would love that. Take the pur top. >> Yeah. Iconic silhouette.
2:16:36
>> A rag top puranguay might be the move for them.
2:16:40
>> Um, this is interesting though.
2:16:40
Uh Canadian collector Luke uh Porier uh who owns 38 Ferraris said he was open to the idea of buying the EV having found the company's hybrids engaging and emotional to drive.
2:16:53
See the SF90 is a wild driving experience.
2:16:57
I was in uh Dubai uh and rented an SF90 and took it out. Um it's pretty funny.
2:17:05
They they give you tickets in uh the UAE based on uh you'll get uh they have cameras.
2:17:11
They'll they they'll give you tickets without you even having any sense of it.
2:17:16
So you can actually go out on a drive and get multiple tickets if you're not safe.
2:17:19
Uh I was uh so the so the the rental service was uh they keep like a deposit like long after you've returned the car and insured that they're like okay the car is good >> but you might have gotten like five tickets and so we need to hold this.
2:17:35
>> Um but uh Luke uh Luke says my only hesitation is reliability since it will involve so much new technology.
2:17:42
>> Ferrari started dabbling in hybrid technology on the racetrack in 2009 and hybrids now account for almost half its output.
2:17:47
Uh, Vigna said Ferrari would apply lessons it is learned from hybrids to its EV.
2:17:51
We will not sell an electric car without considering the expiration date of the battery.
2:17:55
Uh, many EVs and hybrids haven't performed well in the secondhand market, a problem typical fastmoving technologies.
2:18:00
SF90 and SF90 Spider, for example, have depreciated faster than comparable models with conventional powertrains, according to Hagerty.
2:18:10
Uh, again, there was a lot of people that bought SF90s at the top for way over stickers.
2:18:15
It also came out during like the zero interest rate sort of bubble.
2:18:19
So the auto loan rates were really low and a lot of people were flush from various uh crypto schemes and all sorts of froth in the market.
2:18:26
It was easy to buy it over sticker.
2:18:29
Uh do you know David Lee the Ferrari collector?
2:18:31
He has over 40 Ferraris I think are all in red.
2:18:35
He has all the supercars, the F40, F50, the La Ferrari, the Enzo.
2:18:38
Um, he says to be a top client of Ferrari, you you buy every car that they introduce.
2:18:47
And he says he's planning to buy the EV. Yeah.
2:18:49
But I wonder how many how many of those collectors will stick around if they just took a bath on an SF90.
2:18:56
They're not doing well in their 296.
2:18:58
>> Yeah, but the I mean uh so city analyst Harold Hendriski says it is somewhat surprising that Ferrari is going ahead.
2:19:05
Overall demand for those cars is minimal.
2:19:07
Uh we were talking earlier off the air just saying they had such an amazing opportunity to let the rest of the automotive industry go.
2:19:14
You know, Porsche went heavy into EVs is now pulling back.
2:19:20
>> Ferrari could have said, "We never wanted to go into EVs.
2:19:22
We like, you know, uh uh naturally aspirated V12s.
2:19:28
We're going to continue to focus here."
2:19:29
>> If they were the one that never did the EV, >> it would have been crazy.
2:19:32
>> It would have been a very special thing to the brand.
2:19:34
And now they're they're still they're still like in the same conversation as Porsche and Lamborghini and McLaren.
2:19:40
>> But again, if you're a client and you want access to uh the F80, you can better you better believe that you are pick up a couple of these.
2:19:49
>> Get go into your dealer, get pre-order a few of the Ferrari Electricas, you know, show >> at the same time like I I feel like if you're David Lee, you own 40.
2:19:56
Like you definitely want to own the first EV just because it's going to be interesting to see what Ferrari does with an EV.
2:20:01
like it will be a different experience.
2:20:03
It will be there will be a Ferrari twist or take on even though that's >> I'm still interested to see what happens with the poor Sangu from a depreciation standpoint.
2:20:13
They're holding up well now.
2:20:15
It's a naturally aspirated V12.
2:20:17
>> I think it looks uh you know people debate the the looks all the time, but >> you can always put a Monsur body kit on it and get the Puganator and then you're good.
2:20:28
>> But uh yeah, we'll see how these hold up.
2:20:29
lower it, make it off-road edition, edition. >> I I don't know.
2:20:33
The Urus has held up incredibly well because it still looks exactly the same as it did in 2019.
2:20:38
So, people will >> uh happily buy happily, you know, continue to uh purchase a older uh Urus and and use it to sell courses or whatever whatever they do.
2:20:53
Um but uh I don't know about the it's hard for me to imagine people paying half a million dollars for a Ferrari SUV or even $400,000 >> in a few years, right?
2:21:06
Um, so >> well, if you want a Ferrari for your bedroom, get an eight sleep pod five, five year warranty, 30 night risk free trial, free turn, free returns, free shipping. >> I'm back on a roll.
2:21:16
I got a 93 8 hours 23 minutes.
2:21:19
>> Let's read this post from uh SMB attorney who says, "Wait, what'd you get?" >> I got a 93.
2:21:25
Oh, I got 99 290s back to back.
2:21:29
>> SMB attorney says, "People keep telling me the American dream is dead, but every day I meet entrepreneurs who know more about SEC football than accounting, drive trucks, and think getting dressed up means a good pair of jeans, who've made millions running businesses that clear land, trim trees, and install equipment.
2:21:46
The American dream is alive and well.
2:21:49
It's just hidden behind hard work and a little bit of sweat.
2:21:52
>> We have to get a plumber or an electrician on the show."
2:21:54
that's cashing in on the data center boom.
2:21:56
There has to be some guys that are uh that are on their way to uh at least getting a a PC12, you know, turbo prop.
2:22:08
>> I wouldn't be surprised.
2:22:08
Um but I I think that this post is more just about like you don't you don't need to be a janitor at a data center to to experience a boom if you're just running a well-run operation, have scaled it.
2:22:22
There's a reason, you know, the meme is the private equity guys will come and buy these companies, but the reason they do is because they're good companies.
2:22:27
And so maybe there's still still an opportunity there.
2:22:30
And there's also opportunity in the public markets on public.
2:22:33
com investing for those who take it seriously.
2:22:35
They got multiass investing, industryleading yields.
2:22:38
They're trusted by millions.
2:22:39
>> They now have direct indexing.
2:22:39
Yes, >> I am playing around with.
2:22:43
>> Well, um, >> what do you got?
2:22:45
>> Willitis on the timeline with a longer post.
2:22:48
take us a minute to read through this, but should be fun. >> Get started. I'll be right back.
2:22:52
>> He says, "You can leave the kingdom, but you're still paying tax.
2:22:54
Incumbents realize their industry is too regulated or and too consumer, unfriendly for growth.
2:23:01
So, they build a parallel, less regulated, often cash pay alternative next door.
2:23:06
The parallel system is easier, but causes massive consumer harm. I've seen this myself.
2:23:10
Um the prime example of this over the last 5 years is the rise of tele medicine pill mills in health care.
2:23:18
Think of the healthcare industry as defined by two factors.
2:23:22
One extremely limited supply.
2:23:25
Medical doctors are scarce and costly and two a principal agent problem with payments.
2:23:30
Your insurance pays and you don't.
2:23:32
Um this has allowed the industry to behave in incredibly weird ways.
2:23:37
Costs can constantly grow.
2:23:37
patient experience can constantly degrade and clinics will still fill up with weight lists because patients trust it, need it, aren't paying for it and have no choice.
2:23:49
As a result of this, we saw a world where patients replace their primary care doctor with a fleet of tele medicine pill mills for lifestyle drugs.
2:23:57
Further, lacks regulations during the 2021 era allowed for these tele medicine services to offer things the traditional system could never offer.
2:24:05
fund lifestyle drugs with limited medical supervision.
2:24:10
Sure, it was a better experience, but that patient went from having 75% of their care subsidized by insurance to having 0% of their care and drugs subsidized.
2:24:18
The par the parallel system passed costs on to the consumer.
2:24:24
Furthermore, the consumer is likely harmed in the form of lower coordination and regulation, opening the door to all kinds of harm, bad drugs, conflicting drugs, etc.
2:24:32
How many people do you know that are now on four, five, six, or seven drugs of dubious medical need?
2:24:37
I actually don't know that many people that are on that, but I certainly hear stories about it. Um, flip a coin.
2:24:45
Either way, the percent of your income spent on healthcare is going up. That seems true.
2:24:49
We see this playbook across industries.
2:24:51
When the kingdom was built, the merchants paid taxes, coordination, regulation.
2:24:55
They hated paying taxes and boxed themselves in via regulatory capture.
2:25:00
So they pushed it onto the consumer.
2:25:02
Unable to conduct business, both the merchant and the consumer leave the kingdom.
2:25:06
Things are easier outside of the kingdom walls, but the merchant gets richer faster and the consumer gets harmed.
2:25:13
You see this in options markets today.
2:25:14
You see this in defense procurement, which I don't know what he's talking about.
2:25:18
I I've never heard of defense procurement happening outside of a regulated environment.
2:25:23
I do see it in healthcare. You see it in crypto.
2:25:26
That seems like a great example.
2:25:26
Uh you see this everywhere.
2:25:28
I would love to know what he's thinking on defense procurement specifically.
2:25:31
We build palaces of regulation to pursue to prevent consumer harm and force consumers into unregulated legal gray area systems in order to conduct business.
2:25:42
It's easy to see why this is a durable economic effect we see across economies.
2:25:46
You can simply squeeze more growth out of an unregulated market. Look at rising Asia.
2:25:49
And the US has allowed for a continuously developing set of emerging economies by its glacial pace of gray market regulation.
2:25:56
We should view this as an incredible indictment of a regulatory state.
2:26:00
The solution is to overregulation of essential industries isn't to allow the progressive construction and delayed regulation of legal gray areas.
2:26:08
The solution to overregulation is to remove regulation on existing industries.
2:26:14
Parallel construction of regulated system harms consumers.
2:26:16
And I have a great example of this that I've lived for years, but I can take you through.
2:26:24
So, uh, Juul started 10 years ago, got immensely popular and was so regulated by the FDA that at one point they were banned and then they finally got approved and all of this was justifiable in the micro.
2:26:39
But during the time that they were banned and going through all this, guess what happened?
2:26:43
There was an entire massive gray market of illegal vapes that weren't even trying to be approved by the FDA.
2:26:50
They weren't participating in the regulated structure.
2:26:53
They were not in the kingdom.
2:26:56
They were just out in the gray market.
2:26:58
And they >> saw that video too of like a of a child testing the vape like they were coming off the line.
2:27:03
A child in China's hitting them all to make sure they're they're they're working and then before they ship them out to America. >> Yep. So crazy.
2:27:10
So the market moved to gray market and and I I don't know what the stats are most recently but at at one point illegal vapes mostly imported from China were the second largest category of nicotine consumption after cigarettes.
2:27:24
So it was much much bigger than Juul and and the and the companies that were trying to be regulated.
2:27:29
There's obviously regulation that needs to happen in this category, but if it takes 10 years, yes, there is a gray market that's going to develop.
2:27:36
And so I I firmly agree with Will.
2:27:38
I've seen it in in the business that I know best.
2:27:40
Uh and he's obviously seen it in the medical space.
2:27:43
I have no idea what he's talking about in the defense space.
2:27:45
But uh do you have any uh thoughts on Will's latest long post, the Yuga, as he puts it. >> The Yuga. Uh I don't know.
2:27:51
I think um it's interesting that we haven't seen more about the pill mills and all the tele medicine shops from the from the 2021 era working through the courts. Yeah. Yeah.
2:28:05
We were hearing rumors of like uh ATF getting involved or the government going getting involved.
2:28:09
Some of these companies going bust.
2:28:10
A lot of them they kind of had legal problems and then they just kind of melted away and they just became quiet.
2:28:17
And I haven't heard from these companies. Maybe they still exist.
2:28:21
Maybe they just kind of quietly stopped doing the bad thing.
2:28:24
>> Yeah, I'm sure they're all doing it again or they're being reborn to do uh various peptides and semiglutide and all those.
2:28:32
Well, we heard about a fantastic company, biotech peptides.
2:28:34
com or No, don't do not go there.
2:28:37
I don't know that that's the website.
2:28:39
>> Yeah, we saw someone >> saw somebody friend of the show shopping for uh Chinese peptides off offline and the website was just called biotech peptides.
2:28:50
Like uh doesn't seem like the most legit.
2:28:55
>> It seems extremely legit legit. I love biotech.
2:28:57
It's it's it's the most important technology, you know.
2:28:59
It's like It's like reliablemed. com, does it?
2:29:05
>> No, it's called medicinemed medicine. com. >> Yeah, basically.
2:29:09
>> Uh we didn't we haven't talked about this first Brands bankruptcy. Did you see this?
2:29:13
>> I don't know anything about this.
2:29:14
>> Uh I I'll read through a piece in the journal from yesterday.
2:29:16
So, uh First Brands uh uh auto parts supplier First Brands crashed into bankruptcy last month.
2:29:23
Now, banks are sifting through their exposure to the company and its chain of customers and suppliers.
2:29:27
Jeffre on Wednesday said funds run by an asset management unit point Bonita Capital are owed 715 million from companies that bought First Brand's parts UBS in bankruptcy court filing said funds it operates including through its Okconor hedge fund unit which the bank agreed to sell earlier this year have around 500 million of exposure.
2:29:48
The exposure is also mainly to customers that owe first brands money.
2:29:52
A person familiar with the matter said the twin disclosures from the banks illustrate the tangible the tangle of financing that flowed through First Brands which collapsed in late September owing more than 10 billion in a messy and sudden unraveling.
2:30:03
Newly appointed directors have said they're probing irregularities in its financing arrangements.
2:30:10
Jeffree said it doesn't have any information yet on what the probe has found and it would also act to enforce investors rights.
2:30:15
UBS also said in a statement that it was working to protect investors interests. Of course they are.
2:30:21
Uh neither firm indicated any significant direct exposure.
2:30:23
Analysts at Morgan Stanley calculated Jeffrey's possible total exposure as an investor in the funds at 44 million.
2:30:30
Um so the timeline is getting uh uh into a junk bond analyst on X says uh Jeffre is in the crosshair as the main investment bank behind first Brands with a history of bringing risky capital markets deals.
2:30:47
New facts are coming to light.
2:30:47
The unraveling of first brands comes just one month after Jeffre was pitching investors on a $6 billion debt refinancing deal.
2:30:54
Investor uh investor concerns caused the refining refinancing efforts to fail as Jeffre struggled to get diligence information from First Brands.
2:31:04
Uh a chapter 11 bankruptcy filing followed weeks later.
2:31:07
New information about Jeffrey's level of involvement.
2:31:10
uh First Brand set up a so-called side letter with Jeffre for an additional trade financing facility which enabled First Brands to raise funds at uh at an interest rate above the limits permitted by its loan documents.
2:31:22
The workaround First Brands paid Jeff a supplemental incentive fee instead.
2:31:27
This new disclosure caught investors by surprise, increasing financing costs and breaching rules on existing loans, which Jeffre helped arrange and syndicate.
2:31:35
So >> on their website, they have a list of brands.
2:31:39
I'm I'm I don't know that many of them, but I do see the Michelin logo.
2:31:43
Uh they don't actually own Michelin.
2:31:43
I was thinking that they might also own the Michelin guide.
2:31:46
Uh but they do license Michelin in in tires, I suppose. Uh or wipers, actually. Michelin wipers.
2:31:55
They they sell they don't sell the tires. Uh interesting.
2:31:56
I I was not familiar with this company before we we pulled. >> No.
2:32:01
Anyways, still um still sort of uh unraveling.
2:32:05
uh there's a bunch of different groups uh that uh there's other reporting that says 2.
2:32:10
3 billion has simply vanished from >> first brand's accounts.
2:32:15
So, uh, again, um, people, uh, >> there's a there's a an an email here from someone at Oric that says, "We team, thank you for your help yesterday in in respect of the orders and our clients comments.
2:32:31
We would like to set up a call with you today to ask two question which our clients needs forformational purposes.
2:32:36
First, do we know whether FBG actually received 1.
2:32:38
9 billion no matter what happened to it?"
2:32:44
like we got one almost $2 billion just missing.
2:32:47
Second, would you tell us how much is in the aggregated accounts in respect of the factored receivables as of today?
2:32:54
And they answer one, we don't know.
2:32:57
Two, zero in their accounts.
2:32:57
So, um, big, uh, multi-billion dollar mystery here.
2:33:06
And, uh, yeah, we'll see how this, uh, how this turns out.
2:33:10
Well, uh, Clark in the chat says, uh, is is talking about the example I gave about vapes.
2:33:17
Uh, he highlights that something similar happened in THC with Delta 8 and THCA. Uh, I completely agree.
2:33:22
It was the same thing that there was for a decade or longer like people were saying, "Oh, there's going to be like a federal bill on on, you know, where do where does America stand on THC?"
2:33:36
and it just kept being kicked to the states and was legal and medicine in some areas and then recreational in others.
2:33:43
And in that time, uh, basically you go to one of these trade shows and every gas station owner is there buying like basically whatever they want.
2:33:50
And, uh, it's it it's just like a complete failure to just have clarity around what the market structure should be.
2:33:56
So, uh, lots of work to be done on the regulatory side, unfortunately.
2:34:00
Um, >> well, without further ado, I think we have our first guest in the stream waiting room. Let's bring them in.
2:34:10
>> Let's bring in Preston. >> Here we go. Welcome to the show. Preston from Relays.
2:34:15
>> Hey guys, it's great to be on. >> Great to have you.
2:34:17
Uh, give us a quick introduction on yourself and the company and then we'll get into the news. >> Yeah, of course. Uh, my name is Preston.
2:34:25
I've been working on Relay with my co-founder, Eton Bourne.
2:34:27
Um, and we've recently raised $23 million uh as a series. And >> there we go.
2:34:34
Uh, when John gets back, we'll we'll hit the gong.
2:34:36
But, uh, how did you get into building relays? When did you start it?
2:34:40
What were you doing before?
2:34:43
>> Yeah, that's a great question.
2:34:43
Um, before this, we were both PhD students.
2:34:47
So, I was doing my PhD in physics.
2:34:47
Uh, my co-founder at students PhD um in machine learning. >> Same college.
2:34:56
No, I was at um Harvard and he was at Chicago.
2:34:58
Uh but we went to Caltech as undergrads together. >> Very cool. Very cool.
2:35:02
So straight from PhD program into relays.
2:35:04
Did you did you drop out or did you guys actually get your degrees? >> Yeah, we dropped out. >> There you go.
2:35:13
>> Um there just come out and we were like this is the time to do it. >> Amazing.
2:35:18
what uh uh obviously hyper competitive category, tons of activity.
2:35:24
What uh what's been your guys's initial edge and focus?
2:35:30
>> Yeah, so we've been really focused on approaching um the developer experience from but from the experience of the agent itself.
2:35:38
Uh and so um we don't consider ourselves um like competitors with like cursor or cognition or anything like that.
2:35:46
um we're building the infrastructure that someone would want to use when they're building AI agents.
2:35:51
Uh and so what we've focused on to start are all these auxiliary models that make these AI agents more reliable.
2:35:59
Um for as an example, if I'm a human, I love my autocomplete.
2:36:02
I love my tab autocomplete.
2:36:04
Uh if I'm an agent, I have a different set of models that are really useful to me.
2:36:07
Um so this is like what we've started out with.
2:36:10
Um this is like our fast apply model which applies diffs.
2:36:14
uh and our embedding and re-rank models which is able to find the relevant code in your codebase um in less than a second.
2:36:21
Uh and this is used by 40 companies including like lovable and Figma etc.
2:36:27
>> How do you think OpenAI's agent builder product is going to is going to play out?
2:36:31
Um, it seemed like a cool like like new capability and but I'm not sure I haven't had the pull like the other products that they've released in the last couple weeks to just like jump in, try it, play around.
2:36:43
Uh, what what's been your read on agent builder from OpenAI? >> Yeah.
2:36:49
Um, I've heard good things.
2:36:49
I mean, it looks very beautiful.
2:36:52
Um, it's >> it's a definitely a different category than what we've been building in.
2:36:57
Um but I think the launch went really well. >> Yeah.
2:37:02
Uh what does uh success look like over the next 12 months?
2:37:09
>> Yeah, for us uh we really want to now with this raise um optimize the infrastructure along with the models itself.
2:37:15
Um I think as an example like cursor has done such a great job of optimizing the product with the models.
2:37:23
uh and so all the models that you have within your IDE uh the ply model and the tab autocomplete uh make this product work very seamlessly.
2:37:30
We want to do the same thing for the infrastructure and so we recently also released uh relays repos along with our series A announcement.
2:37:38
Um it means that you can now have retrieval embedded directly into your source control.
2:37:43
Uh, and we're really trying to like reimagine like hey like what does source control look like when you have access to models to make it better and when you're like exclusively focused on um building it for the agent uh code agent.
2:37:57
>> What's the biggest company that you've pitched or talked to in customer development?
2:38:01
I'd love to know the mood and the receptivity.
2:38:04
We've seen some uh some news about like the Fortune 500 trying a bunch of AI stuff and then kind of pulling back from it.
2:38:11
Have you talked to any big companies and and can you share any context on how bigger companies are thinking about adopting AI broadly? >> Yeah.
2:38:20
And have you even been focused there?
2:38:21
Are you focused on uh scaleups like lovable and sort of founder mode companies like Figma? >> Yeah.
2:38:28
Um I mean we're talking to all of the big uh vibe coding companies.
2:38:31
Um you know lovable figma are some of the examples.
2:38:36
Um I think the way we think about this is that uh these LLMs are going to continue to increase in capability.
2:38:44
Um we're seeing kind of what dominoes fall in the first say like year year and a half of uh like models that are like reasonably good at coding.
2:38:55
So already if I need a um marketing website or or a simple presentation I can actually like b code that on like replet or lovable.
2:39:05
Um I think over the next year two years 3 years as we continue to see um the capabilities increase uh more and more things that are now traditionally software will be able to express uh in code and and this is like what we're very interested in.
2:39:23
This is why uh we're saying that we're building the rails for software on demand.
2:39:26
Um it's because things we've seen people build like PowerPoints and decks in Typescript and React instead of using PowerPoint anymore.
2:39:35
Uh we've seen people use like consumer Tik Tok filters that are entirely expressed in code.
2:39:40
This one of our customers, Gizmo.
2:39:42
Uh, and we think that a lot of what we might not consider software today will end up being software and the thing that runs and creates it is going to be a coding agent.
2:39:55
>> Well, congratulations on the round.
2:39:55
I'm going to >> hit that gong. >> Boom. >> Awesome.
2:40:01
Congratulations on the raise.
2:40:04
I'm sure we'll have you back on again soon for the B uh with the way things are going currently and congrats on uh all the initial traction.
2:40:12
>> Have a great rest of your day. We'll talk to you soon. >> Cheers.
2:40:14
>> We have a review from Trip Carolyn that we got to read through.
2:40:19
>> Uh he says, and of course, as a reminder, if you leave us five stars on Apple Podcasts or Spotify, put an ad for your business in that >> review >> review.
2:40:28
We'll read it on the show.
2:40:28
Uh Gulf Streams, wrist hitters, impeccable ad reads, the daily coverage of technology news.
2:40:34
Uh what more could one ask for?
2:40:37
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Putting the TB in capital G journalism.
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2:40:50
Cannot recommend more to anyone interested in business technology or loud opulence.
2:40:54
Wow, he really >> I'll take over now.
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com and tell them the technology brothers sent you. >> Thank you. >> We love you, Trip.
2:41:28
Uh fantastic trip truly has been uh a fan on the show, fan of uh of uh Technology Brothers since the very beginning.
2:41:37
So, thank you for riding with us and excited to get the update on Flux.
2:41:41
You guys have been >> uh cooking uh over the last uh nine months or so.
2:41:47
>> And without further ado, our next guest is in the Reream waiting room.
2:41:49
We'll bring Scott in to the TVPN Ultradom.
2:41:50
How are you doing, Scott? Good to see you. >> Fantastic. Uh thanks for having me.
2:41:56
uh give us give us an introduction on yourself and the company and then we'll get into the news. >> Sure.
2:42:04
I'm Scott Stevenson, co-founder and CEO here at Spellbook.
2:42:06
Uh we launched one of the first Gen AI products for lawyers back in the summer of 2022 uh a little before ChachiBT.
2:42:15
We're an AI contract review tool.
2:42:15
So we allow 4,000 law firm and uh in-house council teams to uh draft and review contracts uh with AI.
2:42:24
Uh my background is in engineering.
2:42:26
My co-founder Daniel is the the lawyer of the team and uh yeah, we're based in Canada.
2:42:32
>> Give us the news today.
2:42:35
>> Uh we've raised 50 million um led by Keith Boy. >> Oh yeah.
2:42:40
Keith uh he's a lawyer, right? >> Yeah.
2:42:44
He he >> he was a lawyer.
2:42:46
>> He was a former lawyer. Yeah. >> He knows that.
2:42:48
>> He doesn't love to admit it. >> Yes.
2:42:51
>> Um >> what's it like uh what's it like building a point solution these days?
2:42:56
We've we've uh I feel like this month that there's just been so many different announcements for for different legal AI tools.
2:43:02
Some are are legacy platforms that are launching AI features and have a bunch of different workflows across the the law firm.
2:43:09
We had Crosby on uh yesterday who's taking a different approach obviously building the act the entire firm.
2:43:16
And then we talked to other we we we we had someone on the show last week who was building uh you know AI legal but just in >> ambulance chaser agents basically. >> Yeah.
2:43:27
Personal injury uh which is a very small niche.
2:43:29
So when I hear cursor contracts that makes sense but it's like a different slice of the market. How do you settle there?
2:43:34
Why are you confident about that slice? >> Yeah sure.
2:43:37
So I I guess there there's a couple questions there.
2:43:39
Like one >> yeah we like being a point solutions.
2:43:41
So we think of our product often as like a toaster.
2:43:45
Like there's a lot of broad AI solutions for enterprise right now.
2:43:47
For the beginning, we're like we're going to be a toaster for contract review.
2:43:50
So really easy to use, really easy to adopt.
2:43:54
You know, we don't even do a sales call most of the time.
2:43:55
It's just like welcome aboard.
2:43:57
Let's let's get you using Spellbook in 5 minutes.
2:44:01
>> Um I think there's a bunch of advantages and I think there's a lot of opportunity to build these kind of I would say like point solution products.
2:44:07
Um and there's a lot of very like broad AI solutions out there.
2:44:13
um why we chose contracts specifically.
2:44:17
Um yeah, I mean the story of how I started the company is I had a small business before this and then one day I had a a legal bill that took like half the cash out of our bank account to do some like very minor things.
2:44:25
Now I didn't have much cash. I was like a a new grad.
2:44:29
Um but uh you know I thought that it was hugely painful to just do like simple transactional work um as a small business and I thought you know we could do it uh much more efficiently.
2:44:39
Um but then the reason we settle on contracts is because the contract market size and and the contract pain goes way beyond just lawyers like 30 trillion is estimated to flow through contracts in the US alone every year.
2:44:53
Um it's happening very inefficiently. There's a lot of risks.
2:44:58
There's a lot of litigation from bad contracting which uh you know Keith used to clean up as a litigator.
2:45:03
And um you know when when you look at the actual overall size of contract pain in not just for lawyers but in procurement and HR and sales um that market size ends up being really really big.
2:45:16
really big. Whereas if you if you just look at the market size of you know x number of lawyers times y dollars per month um it's actually a much smaller market than when you look at like the the overall pain of contracting and you
2:45:27
know I see like the millions of transactions that happen around the globe every day and contracts often being the bottleneck and you know what is it worth if we could speed up all those transactions if we could remove that bottleneck. I think um so much of
2:45:39
I think um so much of commerce of the last 20 years has sp has sped up like we have credit card networks, we have you know we have stripe uh we have digital payroll um but contracts have largely remained the same except for Microsoft Word um and so they've become a bottleneck.
2:45:55
So our our mission is to make contracts move at the speed of commerce so we can all transact and work together much more efficiently.
2:46:04
How often is a a lawyer or a firm signing up for Spellbook when they have like when they're bringing basically like, "Hey, we we we have this contract that we're working through right now.
2:46:15
We're trying to create or or provide feedback on.
2:46:18
We want to use Spellbook like this afternoon.
2:46:20
Are you a what's like the time to value between signing up and actually being able to leverage the product?"
2:46:27
Yeah, I mean it's it's it's close to zero and and that was our design philosophy from from day one is that a lawyer should be able to adopt this almost instantaneously.
2:46:35
Um so yeah, I mean they they can adopt it in almost 5 minutes without having to do a big roll out or a ton of training and we've optimized almost the whole company with with that in mind. >> Yeah.
2:46:48
And do law I'm not uh nowadays engineers at every software company have the ability to just sign up for tools themselves?
2:46:57
Are law firms at that point yet where they have some amount of discretionary software budget that they can allocate as they see fit or are they still uh or is it still maybe like you know Silicon Valley engineers in in the 2000s?
2:47:14
>> Uh it it depends on the segment.
2:47:14
So 70% of lawyers work for small and mid-size law firms.
2:47:18
So uh when you envision lawyers, you usually think of big law, but actually 70% of lawyers are working at these much smaller firms where they actually have a lot of autonomy.
2:47:26
They have access to a credit card.
2:47:27
They might be one of the founding partners of the firm.
2:47:31
Um so in that segment, yeah, it's very much you can do self-signup.
2:47:34
Um and then we also serve in-house council teams.
2:47:39
Uh in on in-house council teams like we have customers like Nestle and eBay.
2:47:43
um you know the decision-making power is still very concentrated.
2:47:45
Um I think like with with whiz one of the reasons why they cited it was such a great motion is because you know the the buying the decision-m power for was like with the the CIO or chief security officer and you know they're sort of the technical buyer they're also the user they're also the check signer.
2:48:02
Um, similar thing happens uh in these in-house legal teams where there's often a GC who's the user, they're the check signer, uh, they're like the sort of the the domain expert and they're the champion allin-one.
2:48:15
So, you still get these, I think, really fast um, buying cycles in these large enterprise in-house legal teams as well.
2:48:24
>> What does growth look like?
2:48:28
>> Uh, we are growing very quickly. Yeah.
2:48:30
Um, so we launched >> Let's give it up for very quick. very quickly. >> Yeah, quickly. >> Put it in your Excel.
2:48:39
>> Yeah, we launched we we launched in 2022.
2:48:40
We have 4,000 customers today.
2:48:40
Um we're tripling this year.
2:48:43
We're over tripling this year uh for sure.
2:48:45
Um you know, hopefully even more.
2:48:49
>> Um yeah, it's been uh it's been pretty wild.
2:48:52
Yeah, I think yeah, over the last two and a half years, I think we did something like 7,000% growth. Uh something like that.
2:48:59
So yeah, it's been it's been >> up and to the right. Up to the right. Well, congratulations.
2:49:05
>> Well, I'm sure we'll have you back on again soon for the C. >> Have fun out there.
2:49:08
>> Thanks very much on the show.
2:49:08
We'll talk to you soon on Scott. >> Bye.
2:49:12
>> Uh if you're looking for cursor for billboards, head over to adquick. com.
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2:49:24
We are joined by George from Monk.
2:49:26
Next, >> the monk himself.
2:49:29
Welcome to the show, George. What's happening?
2:49:33
>> Hey guys, how are you? Thanks for having me.
2:49:35
>> Uh, you kick us off with an introduction.
2:49:36
Uh, you launched the company.
2:49:38
How are you, uh, positioning uh, the value proposition, the business?
2:49:43
How are you explaining the business these days? >> Yep. We're monk. com.
2:49:45
We help businesses save time and make money by solving invoices and collections, which, now that I say this in the show, kind of sounds like a ramp. >> Yep.
2:49:57
Um, wait, what is the what is the typical collection process?
2:49:59
Is that is this like uh just automated emails?
2:50:01
Is that an important part of getting paid as a business?
2:50:07
>> Yeah, it's a huge part. It's a huge part.
2:50:08
I mean, most of it is email and and and up until now it's all been like these very boring dy emails that get sent and then get ignored. >> Yeah.
2:50:16
>> Um and then like statistically a big piece of delays is just an error in these emails.
2:50:21
It's like a tiny thing that we accept, but it's like a three trillion dollar problem, right? >> Yep.
2:50:26
uh uh what were the legacy solutions uh in the category?
2:50:30
Why why start this business now?
2:50:34
What was kind of the key unlock?
2:50:36
I when I when I saw the launch made a lot of sense, but at the same time, you know, you look at a business like this.
2:50:42
I think every business owner can go to monk, you know,.
2:50:44
com and think, okay, I'm having these problems.
2:50:46
This feels like uh an elegant solution for it.
2:50:50
But but why was this not a solved problem yet?
2:50:55
Yep, it's a good question and it's it's a red ocean.
2:50:58
Like there's a ton of players before OL and now every person with a Wi-Fi connection is going to rip a competitor.
2:51:05
Um it's >> just diving into you're a real shark.
2:51:07
It takes a real shark to dive into >> I like the honesty. I appreciate this. This is much better.
2:51:12
We're the only person that thought of this.
2:51:16
>> Cap, you know, capitalism is it's inevitable. You know, a few things.
2:51:17
a uh the selling into the office of the CFO changed twice since the Zer.
2:51:23
So like a there was a Zer and like it was super frothy um and then and then and so and then and then there was a lot more financial rigor and then now with post LLM there's just a lot more appetite to experiment.
2:51:36
experiment. So like I think the the uh GTM motion got easier and then the onus on the CFO or like the business leader even the founder the solar founder get like a lot a lot harder like they have to do a lot more with less and then B
2:51:50
like when Sim Alman and Satia compete and they pour billions in capex and opex and R&D we at the app layer just get to rip that into advantages and so like we are applying LMS in three parts of this workflow and it just works and like every every week that they improve we improve. proof before. Obviously, not proof before. Obviously, not possible. >> How'd you get monk. com? That's a great domain. What's the story?
2:52:13
>> Uh, wanted a poker game.
2:52:15
>> You wanted a poker game.
2:52:15
You're a pro poker player, right? >> No, I'm kidding. I'm kidding. I bought it. I bought it. >> Okay.
2:52:19
You But you made money in poker and then so you paid for it.
2:52:22
So, you kind of wanted a poker game. I like that.
2:52:25
>> Kind of wanted a poker game. Kind of.
2:52:27
Shield at BTV gave me some money.
2:52:27
No, it we used to be called Atlas cuz I think Greek philosophy is cool and I thought, you know, a fiance function like holds up the the world, >> but then there's like 50 atlases. >> Oh, sure, sure. Stripe.
2:52:38
There's a bunch of other >> What makes poker players so elite at uh at the sport of business?
2:52:46
>> I know a buddy of mine uh uh >> still plays like pro proam pro poker.
2:52:54
>> Business is basically degenerate gambling professional. Just kidding.
2:52:55
But I mean, don't you think you can sort of like cross apply from I mean, you run a business and now you run a very popular you cross apply like a lot of the same principles govern all these domains, right? >> Yeah, totally. >> Totally.
2:53:12
>> Um, is this founder bluffing or will they come on the show?
2:53:15
Will they come answer hard questions in the TBP Ultradome?
2:53:19
>> Will they have a poker face on?
2:53:23
>> Expected value thinking, you know, risk, discipline, etc. , etc. , etc. >> Totally. Totally awesome.
2:53:26
Uh, take us through the round real quick. What happened?
2:53:31
>> You mean like the money? >> Yeah. I want to ring the gong. >> How much from who? >> Greenbacks.
2:53:38
>> Uh, led by Sheila Nihar on BTV. >> Yes. Thank you. Thank you. Thank you. >> We love Shield.
2:53:44
Is this from his new fund?
2:53:45
He he came on the show just like a week ago.
2:53:47
He's already deploying, ripping checks.
2:53:48
Or maybe you were the last one in fund too. I don't know.
2:53:51
>> I think I'm the last one in the fund too. Fund. >> Okay.
2:53:54
Uh GTM Fund and V Rail also helped Buil and Yehar. >> Very cool.
2:53:59
Uh and tell us about the last company. Super interested. >> The last company one. Oh, Streamlabs. Yeah. Yeah.
2:54:08
>> It's uh it's a big business.
2:54:08
It's a creator economy business.
2:54:10
It's like we were a big developer for Twitch and YouTube.
2:54:14
So like if you're a content creator and you live stream on Twitch, YouTube or like back then when Facebook was Facebook, you're using our tools. Yeah.
2:54:22
>> So, live streaming, patronage, moderation, etc. , etc. , etc.
2:54:27
>> Um, and we sold because we're a developer and like Twitch was just ripping our road map, which is fine. Like, yeah. >> Yeah. Who'd you sell to? >> Logitech. >> Okay. >> Logitech. There you go. >> Awesome.
2:54:40
Well, uh, yeah, congratulations on the raise.
2:54:42
Uh, and, uh, yeah, it seems like there's quite a lot of demand, so good luck keeping up with it.
2:54:49
>> Thanks for the support. >> We'll talk soon.
2:54:50
Our next guest is in the wrist room waiting room.
2:54:53
But first, let me tell you about Wander. Find your happy place.
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2:55:02
We have Zack from Meanwhile coming into the TVP and Ultra Drum. Zach, how are you doing? It >> is. Welcome. Great. Happy to be here. >> Great to have you.
2:55:12
>> Please kick us off with an introduction on yourself and the company. We'd love to learn some.
2:55:17
>> Uh yeah, my name is Zach.
2:55:17
I'm a longtime fintech entrepreneur.
2:55:19
Uh, I've built Meanwhile, Meanwhile is the world's first Bitcoin life insurance company, but our intention is to build the world's largest life insurance company.
2:55:30
>> How does Bitcoin and life insurance fit together?
2:55:33
How's the normal life insurance market? How is this different?
2:55:37
Um, walk me through um just the like one step deeper in the thesis or the product. >> Yeah.
2:55:43
So, the normal life insurance market, you know, this is about 3% of global GDP.
2:55:46
You've probably never talked about it once on the show, but it is gigantic.
2:55:51
>> Um, it is not just life insurance.
2:55:51
It's about retirement savings.
2:55:54
It's about uh, you know, protecting your family when you die, but what also happens to your family when you live longer than you're supposed to.
2:56:02
That's deferred annuities. It's insurance bonds.
2:56:04
It's all sorts of saving products.
2:56:07
Um, it's a huge, huge market that is completely untouched by technology.
2:56:12
And the reason it's untouched by technology is because you need to be big for technology to matter.
2:56:18
So that is why you have a bunch of companies who have like built marketing engines on top of the global life insurance ecosystem.
2:56:27
Uh what we've done is we have built a full stack vertically integrated life insurance company in Bermuda.
2:56:35
It just happens to entirely be denominated in Bitcoin.
2:56:37
And what that means practically is if you want to save for the long term, uh, you can now do it in Bitcoin.
2:56:47
And there are tax advantages and there's estate and, you know, tax planning reasons to do that.
2:56:53
But fundamentally, what we see is that >> if I bought a life insurance policy in 2018 when my son was born, I've seen the purchasing power of that dollar policy go down 25 30%.
2:57:04
Whereas if I had done that in Bitcoin, I've seen the purchasing power go up hundreds of percent.
2:57:09
And we want to bring that not just to everyone in America.
2:57:11
But if you're a middle- class person in Argentina, you don't save for your retirement because you are going to live longer than the Argentinian peso.
2:57:19
>> So that person should save in bitcoin. >> Okay.
2:57:21
So uh you want a million dollar life insurance plan to >> Yeah.
2:57:26
>> Yeah. walk 10 bitcoins by paying in bitcoin because most people think about their life insurance policy is okay it's going to be $100 a month I have a job I can pay that if it's in bitcoin it goes up and then all of a sudden I can't make the payments like how does all that flow
2:57:45
>> yeah so the current product that we do direct to consumer but this round's actually about all this other stuff we do uh is uh it's called whole life so it lasts your whole life it's very well named Um you uh in our case you might pay I'm going to use big round numbers. You might pay one bitcoin a year for 10
2:58:00
You might pay one bitcoin a year for 10 years.
2:58:02
So you've paid us 10 bitcoin and then whenever you die you get 15 bitcoin. >> Okay.
2:58:07
>> But yes, you're absolutely right.
2:58:07
In a way you're short bitcoin.
2:58:08
So I suggest do not buy a policy bigger than your existing amount of bitcoin. >> Interesting.
2:58:16
>> Uh what you mentioned some you you just raised uh 82 million.
2:58:18
So, we should acknowledge that >> $82 million >> from Bane, Apollo, >> Northwestern Mutual, that's big.
2:58:27
Han Ventures, and uh Pantara, a couple others.
2:58:32
What uh what was the catalyst for this round?
2:58:34
What are you working on outside of the direct to consumer product that you just mentioned? >> Yeah.
2:58:40
So, actually, uh we raised a series A in February that was $40 million >> from Framework and Ful and Wes. Okay.
2:58:49
And what happened after that round is that a ton of the largest life insurance and retirement companies in the world approached us and asked us if we could work with them to bring these products to their markets if we could help them do indexed annuities, index life insurance that had exposure to Bitcoin.
2:59:11
Uh and that is how this $82 million round came about is that Han and Bang Cap Crypto in particular um they had sort of been hovering around.
2:59:18
They reached out to us in the summer.
2:59:20
They said, "You're one of the most important companies in going to be one of the most important companies in crypto. Can we invest?"
2:59:28
And I said, "For a large enough check, you can do it."
2:59:33
>> I love the uh love the honesty.
2:59:33
What uh what is it about uh give give us the lore Bermuda lore?
2:59:39
Uh I've only been there on vacation, but uh >> it sounds unamerican to me, but I'll let you defend it.
2:59:46
>> Well, it's it's a it's it's long been a a sort of, you know, financial hub and has like some deep history and ties between, you know, tradition, you know, Wall Street and and Bermuda.
2:59:57
>> You're not winning me over. It's not in America. >> Yeah.
2:59:59
So, the fundamental history is that Bermuda used to be a tourist destination when you had to get on a boat to go to your vacation spot.
3:00:03
And once there was an airplane, you're like, I'm going to go to the Bahamas or I'm going to go to Jamaica.
3:00:09
Bermuda is actually like way out in the middle of nowhere in the ocean and it's just not as hot as you'd like, right?
3:00:16
>> So, and it's the Bermuda Bermuda Triangle out there.
3:00:19
>> Bermuda Triangle, you know, not not a great uh history on boats.
3:00:21
So uh basically they had some really enterprising people in the ' 50s and the 1950s and60s who decided to make it an offshore financial hub and now it is like the insurance capital of the world.
3:00:36
So I'm surprised you went there on vacation because there is about as many actuaries, lawyers and accountants on Bermuda as there are Bermudans.
3:00:41
uh you walk around and it's like Munich, Chub, Swiss, it's like huge financial institutions and I guess the next huge financial institution there is going to be meanwhile. >> Congratulations.
3:00:55
>> That is >> that's amazing.
3:00:55
Is is the Bermuda Triangle fake news or are you taking a wild route when you go there? Are you avoiding that?
3:01:04
>> I'm going to call it fake news, but uh they're actually Bermuda has this really crazy history.
3:01:09
They did a lot of things.
3:01:11
They like ran a a ruthless salt monopoly over the Caribbean.
3:01:14
They were like gun runners in the civil war.
3:01:15
They had ran a penal colony.
3:01:18
They >> like why not finance?
3:01:20
>> They have found ways to um be innovative for hundreds of years.
3:01:27
>> So if uh so if me and you are flying in a Cessna to Bermuda, you're not telling me to fly around the fly right through the through the triangle. >> That's right.
3:01:37
I've only been there on commercial jets, so I'm not prepared to support the Cessna plan.
3:01:40
But >> But you're fearless.
3:01:42
Generally around the triangle. >> Generally fearless. >> That's great to hear.
3:01:46
>> That's what it takes to take on a $3 trillion industry. >> I like it. I like it.
3:01:49
You shouldn't be afraid of the triangle.
3:01:50
You shouldn't be afraid financial markets.
3:01:54
>> How are you innovating on the direct like the actual experience?
3:01:56
I got a uh I I got life insurance through my neighbor who happened to be an agent.
3:02:02
it was kind of this weird uh you know it's it's it's not a um it's not a didn't feel like the most seamless digitally native process.
3:02:12
So there's also I think a lot that you can do on on the actual >> yeah fundamentally look we want to do with a thousand people what Alian does with 100,000 people.
3:02:19
Um our we didn't mention it but Sam Alman actually led our seed round and our pitch to Sam was this is a once in a century opportunity that we can use digital money in the form of bitcoin and stable coins to reach billions of people with these savings products and then we can use AI and automation to serve them profitably.
3:02:39
So we have built everything from the ground up.
3:02:42
We are a fully vertically integrated lifeurer.
3:02:44
Uh so yeah the the experience of uh filling out the application is quite seamless.
3:02:49
People can get underwritten and we can close policies in a single day.
3:02:54
We do all our actuarial we close our books.
3:02:57
This sounds so boring but we close our books in like 2 and 1/2 hours at the corner end.
3:03:03
Most insurance companies we're talking like 45 days >> but we do all of that.
3:03:07
Like we have a chief risk officer, we have an enterprise risk manager.
3:03:12
We have all this boring stuff.
3:03:13
But because we've built it, you know, feature by feature, step by step, system by system, uh, we are building a durable advantage in the life insurance space. >> Fantastic.
3:03:25
Well, congratulations on the progress.
3:03:28
>> Hope to see you out in Bermuda one day.
3:03:30
Uh, have a great rest of your day.
3:03:30
We'll talk about to host a show there sometime if you'd like, gentlemen. I would love that. Awesome.
3:03:37
>> Get my Bermuda shorts. >> Thanks for joining.
3:03:38
Have a great rest of your day. >> Progress.
3:03:39
Uh, speaking of life insurance, Dylan Patel over at semi analysis says life insurance in Taiwan is delaying Nvidia's expansion in Taiwan.
3:03:48
Remember Sam Alman was talking to Ben Thompson just earlier this week about wanting TSMC to ramp up.
3:03:53
He obviously wants more chip production.
3:03:58
And so semi analysis tells the story.
3:04:00
They say at Computex this May, Nvidia announced plans to establish its constellation headquarters in Taiwan.
3:04:07
However, the project now faces uncertainty.
3:04:09
The proposed site for the Taiwan headquarters was the T17 and T18 plots in the B2 Shillin technology park.
3:04:21
Nvidia had signed a memorandum of understanding, anou with the this life insurance company, a Taiwanese company with total assets exceeding a hundred billion dollars USD.
3:04:29
But theou expired on September 30th and is no longer valid.
3:04:36
The key obstacles are as follows.
3:04:39
Shin Kong Life completed the registration of building rights for the T17 and T18 plots in February of 20 uh 2022, securing a 50-year lease hold.
3:04:47
Uh Shing Kong expressed willingness to directly transfer the rights of T7 and T18 to Nvidia.
3:04:54
However, the Taipei city government opposed this, arguing that Shin Kong must first construct the buildings and obtain an occupancy permit before transferring the rights.
3:05:03
The government is concerned that if Shing Kong gains additional benefits from Nvidia through a direct transfer, that may be seen as favoritism.
3:05:09
So furthermore, Nvidia requested the that the road between the two plots be incorporated into the site.
3:05:15
They want the road as well, not just the buildings.
3:05:18
Uh and that would require changes to the urban planning regulations and it would increase the value of the land rights and again the concern of favoritism.
3:05:25
So Shing Kong proposed constructing the headquarters for Nvidia and transferring it afterwards, but Nvidia said no.
3:05:30
Nvidia wants full control over the design and construction of its headquarters.
3:05:34
You got to get a nice corner office for the big man.
3:05:38
Who knows what Shing Kong's going to do if you let them build.
3:05:41
>> Closet for leather jacket. >> Yes.
3:05:42
A massive walk-in closet that makes a >> entirely the same jackets.
3:05:46
Lots of leather jackets and the jackets come flying out of every every possible closet.
3:05:52
Uh the Taipei city government suggested terminating the existing contract and signing a new one directly with Nvidia.
3:05:56
Shin Kong opposed this, citing its 50-year lease hold and expected rental income.
3:06:00
The city's proposal did not account for Shing Kong's anticipated future revenue regarding rumors that Nvidia may abandon its Taiwan HQ plans and move to India.
3:06:12
Uh semi analysis is uh has the following view.
3:06:14
Taiwan supply chain remains more concentrated and efficient than any of the other countries.
3:06:18
And with theou expired, Nvidia is free to seek alternative locations or quit the site entirely.
3:06:23
Therefore, we believe Nvidia will not give up on establishing its headquarters in Taiwan.
3:06:27
That's where they want to be.
3:06:29
The city government is reportedly leaping toward persuading Nvidia to give up sites T17 and 18 instead and instead accept a different site T12 along with surrounding private land.
3:06:40
Discussions with Nvidia are expected soon.
3:06:42
They believe the likelihood of Nvidia accepting the T12 proposal is low as the site is similar and surrounding private land involves many owners which would drive up costs.
3:06:52
So Nvidia is duking it out with life insurance provider in uh in Taiwan.
3:06:58
>> In other news, uh REI uh announced it's shuttering its Soho flagship.
3:07:02
It's also closing flagships in Paramise, New Jersey uh in Boston.
3:07:08
These shores will shut down in late 2026.
3:07:11
Also, apparently OpenAI is opening an office uh in the same building, the Soho flagship.
3:07:16
Uh I think Michael uh mirror floor was was saying that uh on X something about that being like very symbolic, right?
3:07:27
>> I have a lot of uh uh happy memories of of being in visiting REI as a kid.
3:07:30
It was a wonderful wonderful place.
3:07:33
So hopefully >> uh hopefully this isn't a sign uh that it's so over and hopefully someday soon we can be so back.
3:07:42
Uh, I did want to close out.
3:07:44
There's uh the figure three robot.
3:07:48
>> Okay, let's have a video.
3:07:50
>> We should pull up the video.
3:07:51
>> I'd also like to pull up the video of uh Mark Zuckerberg talking about uh the barbecue because isn't isn't it the anniversary of that video at some point?
3:08:02
Let's watch those two videos and then we'll get out of here.
3:08:03
U but first >> while you pull it up. >> Yeah.
3:08:07
>> Uh apparently so Mark Cuban went in Sora. Yes.
3:08:10
and said uh free free-for-all with his likeness.
3:08:14
>> I went free for all as well.
3:08:15
>> He did something that was even smarter than you, which you prompted it to always depict you as a bodybuilder.
3:08:21
>> Uh Cuban uh added a tag somehow that says brought to you by cost plus Drugs.
3:08:27
>> I was going to do that with the Ramp logo on my forehead. He did that. That's amazing.
3:08:30
And it looks >> Yeah, it works beautifully.
3:08:32
Dylan posted a couple different screenshots. >> Very clever.
3:08:37
Okay, let's watch this video.
3:08:38
Thank you for pulling this up.
3:08:41
Uh, we were just talking about humanoid robots with Martin Casado from A16Z.
3:08:47
>> Nobody trying to do it.
3:08:49
>> Nobody does videos like Figure.
3:08:49
Got to give them credit for that.
3:08:52
>> Fantastic launch videos where this is the third.
3:08:57
So, this is version three, but they're still in alpha and they haven't they haven't shipped these or or they they installed some into a demo plant with BMW, right?
3:09:05
So, what's notable here is they're not that I I I scan the video.
3:09:08
I don't think there's any they're not just depicting it in a factory setting at all. Okay.
3:09:13
Seems like this is a pivot away from >> going more consumer >> commercial, >> which was one of my questions for uh Martin.
3:09:20
What do you think, Tyler?
3:09:21
>> Uh right at the end of the video, it's in a factory.
3:09:23
>> Oh, it's in a factory at the end.
3:09:24
>> And the other thing here that's notable, they followed 1X Robots using the fabric covering.
3:09:30
>> Fabric looks way better, I think, than the hard metal.
3:09:32
It just looks Yeah, it looks >> I can see why >> Oh, there there's a house. Okay.
3:09:38
>> I can see why the retail army just loves figure.
3:09:41
>> It's not It's not a retail army.
3:09:41
We're seeing the emergence of a new army.
3:09:43
The private market retail army.
3:09:48
>> Yeah, we need a new word for it.
3:09:48
It's not It's not retail necessarily if it's private, but uh people have been pumping for timeline.
3:09:54
It's a special purpose vehicle army.
3:09:57
People have been asking questions about how much pumping is going on on the timeline uh and whether it's too much, but uh I mean it's a great video.
3:10:06
>> It's a $39 billion company, John. >> Is it still? Wow.
3:10:10
>> Still, yes, >> that's remarkable. Hey, look that dog.
3:10:16
>> That was an opportunity to make that a robotic dog.
3:10:18
It is interesting that they're not they're only focused, you know, straight shot to humanoid robot.
3:10:23
No Boston Dynamics uh project.
3:10:23
No, no four-legged friend first.
3:10:26
Um, a lot of the other uh robotics companies have kind of taken a more incremental uh uh like prog progress.
3:10:36
>> Do you think they trained on Biden's uh >> It does it does seem like an the walk of an elderly man, >> but it's a start.
3:10:45
>> It's not It's not I mean the Boston Dynamics demos are always like way more agile and and same with the Unit demo.
3:10:55
in space is going to come down to one, how effective is it, right?
3:10:58
If uh we both have kids, kids tend to like destroy the living room, create a lot of chaos, a bed, you got to clean it up and stuff.
3:11:06
So, >> humanoid should be able to clean it up.
3:11:08
You'd think >> the question is >> it's a little slower.
3:11:11
>> How effective and what's the cost, right?
3:11:12
Are people going to buy if can they come in anywhere near unitry at 20k for a comparable robot?
3:11:20
>> Yeah, >> seems unlikely.
3:11:20
I mean the big the big debate here is just how how much does this stuff generalize because I mean we've seen in all sorts of other AI applications like it's simple to RL on one certain you know one certain problem and get really good at it but then does that learning generalize and so um you can have a model that's fantastic at IMO level math but can't but can't complete ARGI which is so simple that a 10-year-old can do it. >> It's doing dishes.
3:11:48
Um, and so you know, if it's if it's trained to be really good at this one dish with this one um with this one faucet system, can it generalize to your faucet system or or when will that generalization happen?
3:12:00
It certainly happened in LLM, so you would hope that it happens in humanoid robotics very quickly.
3:12:08
It's uh it's an interesting time.
3:12:10
>> Brett shared that none of this is teaoperated. >> Okay.
3:12:13
Yeah, none of this is teleoperated, >> which I still think tea even a tea operated humanoid would be very cool.
3:12:19
That would be >> Yeah, I mean you're still paying by the hour more than just power.
3:12:21
Uh that there is something that's very important economically about getting away from teleoperation over the long term, but I don't see a problem with teleoperation as a as a data flywheel, as a way to actually get these into people's homes.
3:12:37
You're teleoperating them.
3:12:37
you're collecting more feedback and data and you can train that and roll that into reinforcement learning.
3:12:42
Um I do yeah the the the the question is like did he comment on whether or not this is scripted because it could be recorded motion right because that would not be teaoperated.
3:12:55
It would be running on the robot locally, but it could have been uh you know teller operated at one point and then memorized and then um and then uh you know played back effectively like is this there's a big question about like how long has this robot been in this particular environment? >> Yeah.
3:13:14
figure to uh develop like legitimacy within >> like our bubble.
3:13:20
Like people are going to need to >> be able to do some type of live demo setting where they can be in the house with it and they can task it with doing things that aren't necessarily pre-planned, right? >> Yeah.
3:13:33
There's something about like with the other AI companies and the LLM world like the models go out, the APIs are available, the benchmarks are inended.
3:13:42
If if you can just walk into a room with a figure robot, dump a bunch of laundry on the bed and it just folds it and puts it away, >> that is going to be mind-blowing.
3:13:49
But I don't know how how >> I mean to be fair, uh, Gnome Brown, I think at OpenAI was uh was saying like, okay, like this is a nice example of the robot folding laundry at a table.
3:14:00
What happens if you raise the height of the table six inches?
3:14:06
And Brett Oddcock raised the height of the table six inches and posted another video and said it still works. It still works.
3:14:11
So he is uh he is uh duking it out on the timeline >> more commercial setting delivery robot.
3:14:19
They had it at the opening of a hotel.
3:14:22
>> I wonder I wonder what makes it so much slower than the the Boston Dynamics example.
3:14:29
Like it feels in some ways more advanced than what Boston Dynamics does.
3:14:35
Certainly uh the demos here are more generalizable.
3:14:38
Like I haven't seen a video of a Boston Dynamics robot doing any of these like useful tasks.
3:14:42
It's always just like dancing and doing parkour which doesn't seem very commercially viable.
3:14:46
Um but uh but the Boston Dynamics like the actual motion just feels so much smoother and so much more fluid.
3:14:55
And same thing with the unitary robots.
3:14:57
Like the room the unitry robots you kick them over and it does a 360 to jump back up.
3:15:01
that doesn't feel very economically useful like folding laundry or delivering packages, but it's certainly impressive.
3:15:08
>> PhD responded and said, "I have so many questions."
3:15:11
>> Um, I wonder what do you how long how long do you think until MKBHD can can uh do a review?
3:15:19
>> He did a huge review of the Boston Dynamics dog that he got one.
3:15:21
I think he might have even paid for it himself and like been able to play really play around with it and really put it through its paces. And I love that.
3:15:28
I I would love for him to uh do a proper review on on a figure robot. That would be very cool.
3:15:35
Um there was something else that was that was top of mind on the on the MKBHD thing. Oh yeah. Did you see that?
3:15:43
somebody posted their product and MKBHD responded with a meme that said like interesting and it was like a funny just gif or image and the company took the text out of the uh out of the meme and put it in quotes on their website and attributed to MKBHD and was like he said
3:16:04
it looks interesting and it was like a meme that he sent and then MKBHD was like this is ridiculous like I didn't give you a quote like you can't just use me on your website and the founder of the company was like, "Oh, well, we also emailed with your team and they said like it looks interesting. Like we'd
3:16:18
Like we'd love to, you know, like like hear more about it."
3:16:22
And then they took that as an example.
3:16:24
It's like that's not quite the same as like >> we'd love to hear more about it. >> Yeah. Yeah.
3:16:28
It's like they were just being nice >> chat right now.
3:16:30
It's AV says it's slow for dramatic effect. >> Yeah.
3:16:36
It's actually moving at five times to do back.
3:16:39
>> They filmed it with a slow motion camera.
3:16:43
They they filmed it with a slow motion camera to make it look more sci-fi and cinematic for sure. I like that.
3:16:49
>> But anyway, anyways, no more information on on when uh when it'll be available for sale.
3:16:53
Um but uh I'm sure somebody at the right point will pit the >> I mean, the first thing somebody's going to do is pit the tree G1 against a figure and just make them >> uh compete in a variety of contests. Looking forward to that.
3:17:06
I mean, Christopher Mims has a whole deep dive on uh America's manufacturing resurgence and uh the robots that are doing that.
3:17:14
More focused on cobots, which we've talked to some companies around, less on the humanoid side, but uh it's a it's a fascinating deep dive if you want to go check that out.
3:17:21
Maybe we'll cover it on the show at some point.
3:17:24
>> Is there anything else you want to react to? >> That's it. That's it.
3:17:27
>> We can react to this iconic >> video. Let's head out.
3:17:29
Let's head out >> on this day.
3:17:31
>> Friend of the show, Mark Zuckerberg, TVP.
3:17:33
Hey everyone, we are live from my backyard where I am smoking.
3:17:40
>> Imagine Andy Jasse doing this on Twitch.
3:17:43
It would be so much better than another conference call for earnings. >> It's smoking.
3:17:47
So, >> is this the edit where they just show the smoking meats?
3:17:51
>> Yeah, someone asked me, "Do I smoke meat?" Smoking meat.
3:17:55
>> This is This is the least You can edit. Yeah, I saw lesson.
3:17:58
You could edit any video.
3:18:00
You could edit us to look like idiots, too.
3:18:01
If you took our 15 hours a week of content and dialed it down to all the times we say something similar, you'll love it.
3:18:12
>> And and he went so much farther.
3:18:12
He has his own cattle ranch.
3:18:14
He didn't he vertically integrated his meat smoking operation.
3:18:18
So, cheers to Mark Zuckerberg.
3:18:20
>> Uh thank you for tuning in today.
3:18:20
Uh we hope you have a fantastic afternoon and evening wherever you are in the world and we will see you tomorrow >> here in my garage.
3:18:30
live on TVPN noon Pacific. We'll see you then. >> See you tomorrow. Goodbye.