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[Music] [Music] [Music] one. Good morning, John Xley.
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Good morning, David Fong. Good morning, Rick. Good morning. >> Look at this crew. The chat is popping.
3:19
Thank you for tuning in on Tuesday, October 7th.
3:22
Very excited to do the show with you today. >> We're excited. Good morning, Dan Gray. We got a fantastic crew. Gabes in the chat.
3:33
Credibility is the cornerstone of success. Couldn't agree more. >> Fact. >> Fact. Fact check. True.
3:40
>> Can Moore, it's great to see you.
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>> Sounds like a new name.
3:43
I'm not familiar with Canmore.
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Excited to have them here. >> There we go.
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>> Fam, what a great day to do the news.
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>> We will start the show in 1 minute. >> Can't wait.
4:01
>> We're doing fantastic.
4:01
John Xley, >> I got food poisoning last night. >> You did?
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Jord got food last night, but he's he's uh he's toughing it out.
4:19
>> Oh, we should talk about this Rocket Lab story.
4:22
Peter Beck, let's get him on the show.
4:27
Oh, we should also talk about Caller Daddy launches an ad agency.
4:28
We got to go through some of this.
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>> Everybody's >> Maybe we should do a six-hour show today.
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I feel like there's a lot of news.
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[Music] >> Oh, to do six. May as well do seven.
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>> Locked in for the great lockin.
4:45
Thank you everyone for tuning in. We got 13 seconds.
4:47
Let me turn my headset up. >> Team deathmatch. >> You're watching team.
5:02
>> I forgot we were going to start on horse camp.
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Uh >> how could you forget?
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>> It is >> the horse has a fedor a fedora.
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Tuesday, October 7th, 2025.
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We are live from the TBPN Ultradome, the temple of technology, the fortress of finance, the capital, the capital.
5:18
>> Uh, fantastic day today.
5:18
Uh, Jordy did get food poisoning yesterday.
5:20
We went out to Can we say where we went?
5:22
Can we say who we were talking to?
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I don't exactly remember the rules, but uh >> I don't think we can discuss the discussions. >> Okay.
5:32
>> But I think we can say that we were with a a mag seven.
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>> But if we say the event that we were at, then it's obvious who we're talking to.
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We we had a magnificent evening. >> Okay.
5:42
Yeah, we had a magnificent evening with a Magnificent Seven.
5:49
And you can probably just figure out who it is by looking at what events.
5:53
>> I mean, there's a lot of companies in the Mag Seven.
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It's not not >> seven of them.
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>> Well, we did we did get to hang out with uh David and Ben from Acquired as well, which was super fun.
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Uh we're going to have them drop by the studio tomorrow for that >> which I'm looking forward to.
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>> I'm going to ask them to quickly summarize the full history of every technology company >> and every luxury goods >> and every luxury and every company ever actually in Costco too.
6:14
Throw that in quick oneliner on Costco.
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>> Um >> name every person on Costco's team. >> Yeah.
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But we did have a fantastic evening.
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Although Jordy did get uh food poisoning, I think. >> Yeah.
6:27
Ryan Ryan Walsh, how did you get food poisoning while with a Mag 7 CEO? Good question.
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There was two types of fish served at dinner. >> There were two types. >> I indulged in both.
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That was >> I skipped the fish.
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>> There was that crudeau and then there was >> Oh, yeah.
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I had a lot of the crude.
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The crudeau was not the problem. I'm fine. >> Okay. Okay. >> I'm fine.
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>> But I I I think it was because I had a glass of the sair the wine and you did not partake in the wine and I think the the alcohol punish it it served as it it detoxified my stomach and prevented me from getting sick.
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The toxins from the alcohol.
7:00
poisoning the poison food instead of poisoning them. Exactly. >> That's it. >> Anyway, what a day. Um, it did uh we Yeah.
7:08
So, we talked a lot about AI slop, AI video slop uh and I had this thesis.
7:15
It's been kicking around in my head for a while and I thought it would be interesting to kind of relay my thought process after talking to a bunch of creators and uh folks working in big tech.
7:25
So, uh, we've been talking about the AI video stuff and and the the the wave has been fascinating where Vibes was like immediately jumping to like this is infinite jest. It's terrible.
7:36
And same thing with Sora 2, like we jumped way past like any of the normal discourse.
7:41
There was a little bit of discourse about the electricity stuff and the water.
7:44
My water bill is going to go up because of this.
7:46
Um, there was some talk of as >> that discourse is still going on to be clear. It is. There's a post here. Uh, we can pull it up.
7:53
I'll put it at the top of the timeline while you continue on. >> Yeah.
7:57
Um but but I thought about uh there was a time when uh the narrative around this type of content like fake content, doctorred content, fake news, AI content.
8:10
>> It says me watching Stephen Hawking drop into a sick halfpipe McTist while my electricity costs triple. >> Honestly, so down. It's great. Um worth it.
8:21
I mean, that is one of the greatest AI videos.
8:23
And and and that gets to my point, which is that I don't regard that video as AI slop.
8:27
I would like to be shown that video.
8:29
I don't want to be shown an endless stream of AI slop that is bad.
8:34
But there are obviously creative ways to use these tools.
8:36
There are even ways to reappropriate the tools that where the joke of the video is that it's an AI video and it's like self-aware and those are very interesting.
8:47
I was watching Casey Neistat's uh video all about his reaction to uh Sora and he used a lot of AI video generated from Sora in the video and so like there was a time when the answer and the call from the public was we need to build an AI detector and we need to cordon this content off in its own tab and that's kind of what Metavibes is doing and that's what Ben Thompson was talking about.
9:12
It was like I have not been enjoying my Instagram experience because I'll be scrolling and then I'll see some AI content and I'm in this active mode again of like is this real or not?
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>> As opposed to on meta vibes to his point he was like I can just lay back and look at it and it's like a screen saver and it's chill and I know a lot right you've been vlogging it a lot.
9:32
Also, Ben Thompson kind of reversed his position and was like like because he was he was saying he was bullish on Vibes and like less interested in Sora, but then he was like, "Look, the charts speak for themselves.
9:43
Like people clearly like Sora a lot more than Vibes."
9:44
Uh, just looking at the growth of the of the app store.
9:48
And so, um, the but there was a call for like let's build a detector.
9:52
I think it's a bad idea for two reasons.
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One is it's this red queen's race between AI generation and AI detection.
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Like the original uh did you ever look at generative adversarial networks, Tyler? >> Yeah. Yeah, for sure.
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>> Um like can you describe like the thesis of a GAN and why it works?
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>> Um yeah, so it's basically that this was like the first kind of way that that generally worked of of producing images. Yeah.
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>> Um so there's like two parts and they're basically acting against each other.
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So, so one part is the the the generator.
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So, it will like create an image >> and then there's the other part which is the uh detector and it tries to figure out if it's AI or not. >> Yep.
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>> Um and then they basically go against each other.
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They're trying to beat each other at all times and they're basically you just >> um like because you're training the detector based off like sometimes you uh give it a real image, sometimes you give it a fake image and then slowly >> and if it can detect the AI image that gets negative points in the reward function.
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And if it can't and if it thinks, yeah, this is real, then it gets upvoted from, hey, you did a good job generating that AI.
10:57
So like effectively, a lot of these models that are AI generators have AI detectors like built into them.
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Like it's part of the training process.
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Uh I don't know exactly how the diffusion models work.
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I think they work similarly.
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I think that that concept from the generative adversarial network has been employed and and repurposed.
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Um, but it seems like it's kind of a it's kind of this like endless arms race between like you build a detector and then the generator gets better.
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And so I'm not even sure if technically it'll work. What do you think? >> Um, yeah.
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I mean, so so there's like a lot of people want the detectors especially for text.
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>> Um, but the text is a lot harder, right?
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Because there's just less signal.
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Like there's only in a sentence there's only, you know, >> like 20 characters or something. >> Yeah.
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You just can't get that much data out of it.
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where with video and and photos um it's actually much easier to like encode some like meaning that like like there's this thing about um like printers they have these like little dots y and it like traces the printer but you can't see it because there's just like it's super faint and very small.
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You can do the same thing with images where you can encode like you just change the images like just barely up a little bit brightness down a little bit brightness >> and you lose it. >> Yeah.
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So you can um >> like a slight crop and a slight tweak to the contrast.
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And it's probably the same thing in text where if you just add one extra space or one extra period or change one word, all of a sudden like the the the the whatever you've encoded in the overall text is just not going to read as much. >> Yes.
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So like with with text, you're basically like seeing the Yeah.
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>> you're seeing everything where with an image um you can like kind of change stuff just a tiny bit to where you're actually like seeing something else. Right.
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There's this famous example where um with image classifiers you can like um adversarily train against them to where like you have a image of a panda but it thinks it's a dog because you just updated the the pixels slightly. >> Yeah. Yeah.
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>> And even with like the Sora watermarking like immediately I saw a watermark removal tool that just does in painting just on those watermarks.
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>> But what I'm saying is you you should in theory uh it should be much easier to create like a classifier that can figure out if an image is AI or not like if it's directly from Sora >> for a while but You don't think it'll you don't think it'll be this endless race where like the AI image generators will just get better and better and better and like the AI detectors will just always be like a little bit behind. >> That could be true.
13:08
Um I think also >> uh OpenAI probably has some incentive to to have something that's like a classifier or at least something that's like able to be classified on like a watermark. Yeah.
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Um, and if you think people will mostly just be using OpenAI or Google's image video generation instead of open source stuff >> because it'll always be like a little bit ahead.
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>> Do you think that Apple will make any moves in terms of embedding anything in meta like the metadata to like prove that this was taken as unaltered video from an Apple device? >> Yep, for sure.
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Um, some of that should be fakeable, but I think that for the most part that's definitely coming. Yeah.
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um it already is there to some degree in the metadata that's maybe a little bit hard to spoof, but there's always a way around it.
13:54
Um but there's definitely some stuff that you can do with cryptography to uh to like sign basically like sign the image as like from this at the hardware level from this hardware device.
14:04
Um, I think that there will be this endless race between these two, but there will always be people that figure out how to sneak in something because it's like, okay, well then, like, you can prove that it's from an iPhone, but what if you film a screen that's AI generated?
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Well, then then you have a video on your phone that says it was taken with an iPhone, but and it's signed, but it's actually AI generated.
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So, there'll always be these ways around it.
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So, I think that it's a little bit of like like somewhat of a waste of resources.
14:30
We should probably do it to some degree, at least be able to classify, but that's not really a perfect solution.
14:34
Um the other the the other um like side of this is that uh I don't know that we need to build AI slop detectors into large media platforms because the problem isn't AI, it's slop.
14:47
Like the people enjoy seeing the Stephen Hawking at the XG games video.
14:50
Um you don't like we already have tools to filter out slop.
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They're called algorithmic feeds.
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If you don't like slop, you will swipe past it and it automatically and you automatically get served other content.
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And that just happens naturally.
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And so there is a problem with algorithmic feeds though.
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They have they're pretty far from their final form.
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And we should go through a little bit of the history.
15:12
So they used to just focus on the uh the initial action of choosing to watch a video.
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So on YouTube for instance, uh they would rank videos in your algorithmic feed based on click-through rate.
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So they'd show you thumbnails.
15:26
If you clicked, that was the only signal that went into the algorithmic feed that the video was good because it got a click.
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And so what people would do is they do clickbait and they in the thumbnail and title be like I bought a Bugatti and then you watch the video to the end and it's like actually the person just went to this store. >> Exactly. Exactly. Yeah. And so >> Mr.
15:45
Beast had this thesis of like clickbait that delivers.
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If he says he's going to crush a Lamborghini, he's actually going to do it.
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Uh and so YouTube changed to uh view duration and watch time.
15:57
So they shifted to being more watchtime focused.
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And this did really solve the clickbait problem uh because videos that earned clicks but not watch time were deprioritized.
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So you can be very high CTR but low AVD and you do not go viral in the algorithm.
16:09
So this led to relatively high user satisfaction.
16:14
But there still is the problem of being glued to your phone watching something that is engaging.
16:17
you watch all to the all the way to the end, but after you're done and you're reflecting on like that hour that you spent watching that video, you're like, why did I waste an hour watching that?
16:28
Uh because it was essentially slop.
16:28
Even if it wasn't created with AI, it was not good.
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And the signal to the algorithm right now is I love that video. I watched 100% of it.
16:37
But internally, you know that that was a waste of time. And so, you can churn.
16:41
I wound up churning from Tik Tok at one point because I downloaded the app like years ago, scrolled and was like, "Yeah, this is some good stuff. This is interesting."
16:52
But then afterwards, I was just like, "This is candy.
16:53
I'm not interested in this."
16:54
And I just uninstalled the app and I haven't haven't been on since.
16:55
And so, um, there's the there's the there's what I think is like the third phase, which is companies are starting to do now.
17:05
So, uh, phase one is click-through rate optimization.
17:07
Then you get to AVD, average view duration, watchtime optimization.
17:12
Third is ARPO, like uh average revenue per user optimization.
17:17
So it's not enough to get someone to watch a full video they hate because then they might not open the app again.
17:22
I personally turn from Tik Tok for this reason.
17:24
Um recommendation algorithm that optimizes for average revenue per user over an entire year is going to focus on mitigating app churn because it doesn't matter that you just got, you know, one really great video, they watched it all, but then they never came back.
17:37
you want to optimize for they came back a lot over the entire year, but that can still lead to brain rot.
17:43
Like you can brain rot your users into being very high average revenue per user for a year for a while, but eventually they get so brain dead that they lose their jobs, drop out of society.
17:52
Uh they become depressed, they stop being good customers, they stop being good consumers, which is something we can't have in the American economy.
17:59
Uh, and so my answer to this and my pitch for these algorithmic platforms is to optimize for LTV, true LT, LTV, the lifetime value of a user is usually estimated over a couple years.
18:12
If you're a startup, you look kind of crazy if you come in with like a 5year LTV.
18:14
But if you think about how long I've been using YouTube, it's basically been my entire life.
18:19
And it's been like 20 years or something I've been on that platform since it started in what, 2005.
18:25
Um, and so, uh, really you should be modeling the >> You just saying YouTube is 20 years old really makes you feel old. >> Totally. Totally.
18:35
Um, but you should be you should be actually considering the full human lifespan.
18:39
Like algorithmic video platforms should basically work like this.
18:43
If I show this kid a brain rot video, I might be able to show some some cheap toy ads right now or some mobile game ads or something like that.
18:53
But if I show this kid an educational video and I teach them how to program, teach them how to be a business person, then they go get a high-paying job and in 20 years I'll be able to show them ads for Ferraris.
19:03
And if I show them ads for Ferraris, I'll make more money discounted in today's dollars.
19:08
And so you should have an incentive at the algorithmic level to actually upskill, actually engage people in having like a meaningful life where they wind up generating enough.
19:20
So you're saying YouTube should actually create their own drop shipping course to help everyone become financially independent.
19:28
>> It could be a variety of things.
19:30
Anything that leads to a fruitful life, right?
19:31
Uh so the current crop >> I mean I think I think it's I think it's just that tension between you know helping create a more valuable user over time. Yep.
19:41
>> And extracting as much attention you can get value from in the short term. >> Exactly.
19:46
Shortterm versus long term.
19:46
The tension there is that, you know, all these scaled platforms are public companies that need to earnings show >> results today.
19:54
And so there's there's uh >> yeah and so none of the current recommendation algorithms are at all tuned to the average American's lifespan which is 78 years.
20:04
Uh but I think they should be they don't have enough data for this and I don't know if they will how they would solve for this before they have a full cohort.
20:11
Like it's going to take YouTube's 20 years old, but the average American's 70 lives 78 years.
20:17
It's going to take another 50 years to get a full just one cohort to be like, "Okay, now we know they now we know what happens if you show kids this video when they're young or this video."
20:26
And we saw how their entire life played out.
20:28
And turns out that this one was a better customer, so we should show them more of this.
20:34
Like that's the feedback loop.
20:35
It's a 78year feedback loop, basically. It's crazy.
20:38
May maybe not 78, but maybe 50 years.
20:40
like it's a really long feedback loop.
20:41
It's going to take a long time to get all that data, but that's how these algorithms should work.
20:44
Um, and uh, so I I have no idea how they will solve for this before they have a full cohort, it's going to be some rough estimation.
20:52
But I continue to believe it should be the guiding light of all the stewards of large algorithmic content platforms.
20:58
Like even if you don't have the data, even if you can't just train the algorithm on that, you should still be thinking >> this was the critique of bite dance, right?
21:05
people would talk about in China that the Chinese version of Tik Tok shows like science and math videos while you're getting your children are getting shown, you know, slop >> and they have like a 10,000-year plan over there.
21:18
They're thinking in decades.
21:19
And so you as the steward of an algorithmic platform should be thinking in decades and you should be thinking about if I take this, you know, quarterly earnings bump right now, but I wind up ruining all my customers lives and they wind up being bad consumers.
21:35
That's a financial issue.
21:35
Like that that that does work within the capitalist framework.
21:38
And so uh I think you should build an algorithm that optimizes for your users leading more flourishing lives so they can ultimately afford more expensive things and make you more money. It's capitalism. at its best.
21:50
Anyway, >> perfect blend of uh of techno optimism and hyper capitalism. >> Yes.
21:55
And for what it's worth, >> in one in one theory. I like it.
21:59
>> The the response to this I gave a I gave an abbreviated version of this pitch and uh the response was magnificent.
22:03
I think uh I think I I think it resonated very well, which I was excited about.
22:09
>> Well, you know what else is magnificent? >> What else? Ramp. com. Time is money. Save both.
22:12
Easy use corporate cards, bill payments, accounting, and a whole lot more all in one place. com.
22:20
>> Another magnificent thing, potentially future member of the Mag 8, Sam Alton will be joining the show on Friday to talk about Sora.
22:27
>> We're very excited for this.
22:29
>> This is a real picture of him.
22:30
>> Yes, he's been hitting the gym season.
22:32
>> This hasn't really been in wide circulation, but uh we kind of expect this to be one of the default head shots that he uses going forward.
22:38
He looks looks fantastic here.
22:40
So, >> we're very excited.
22:43
>> Very excited for this.
22:43
lots of questions that we have around Sora, what the real plan is >> and looking forward to it.
22:50
It'll be noon Pacific on Friday.
22:53
And in other news, Morgan, friend of the show, has launched his new book, The Art of Spending Money. >> Is it coming on soon? We got to get him.
23:02
>> I just sent him a message. I I kind of botched it.
23:04
I was supposed to email him a long time ago, but we'll work on getting him on uh hopefully tomorrow or Thursday.
23:10
very excited to read the book myself.
23:13
Um I'm assuming a lot of the book will be about ramp.
23:16
Um but uh but which we obviously know quite a lot about, but I'm interested to see what else he's writing about. >> Yes.
23:24
The the psychology of corporate cards.
23:27
That's the >> that's the next book. That's the next thing.
23:30
You're like, is he doing SpawnCon now? What?
23:32
That's what we should write. Um >> good stuff. >> Anyway, reream.
23:37
io IO one live stream 30 plus destinations multiream to reach your audience wherever they are.
23:41
Get signed up for free folks.
23:42
Um fabricated knowledge Doug Olaflin he was on the show yesterday.
23:47
Had a great time hanging out with him.
23:49
He says oh my god facepl plant face plant face plant.
23:51
Oracle lost nearly $100 million from rentals of Nvidia Blackwell chips which arrived this year.
23:58
That's partly because there's a period between when Oracle gets its data centers ready for customers and >> and he's bolding this part >> and when customers start using and paying for them.
24:07
The documents show it's not clear what causes the gap or how Oracle plans to shorten it.
24:14
>> And so of course he's referencing an article by the information this morning, an absolute bombshell. >> Bombshell.
24:21
>> They dropped internal Oracle data show financial challenge of renting out Nvidia chips.
24:25
And obviously Doug is highlighting that. Yes.
24:26
uh it's possible uh to lose money between the time when you invest a lot of money in something and when you can actually sell the service. >> Yeah.
24:36
>> So um uh not not a huge surprise there.
24:40
>> So Joe Weisenthal had a little take on this.
24:42
He said in the uh is is this uh is this from him?
24:45
This is this is from a Bloomberg terminal, but I don't know if it's an information article put into a Bloomberg.
24:50
>> There's another post here from Dolly Ball.
24:51
You >> want to read that one?
24:52
>> Uh he says information article is stupid.
24:55
If you look at the beginning of a site ramp, obviously there's no margin, lol.
25:00
>> So anyways, timeline uh putting this one in the truth zone.
25:04
>> Indeed, >> I think we need to ourselves.
25:07
>> Indeed, the uh the the Financial Times had an interesting breakdown of OpenAI's current corporate structure, which >> not enough uh string here. >> Yeah.
25:17
>> Yeah. every time you think it can get it's like oh oh well Open AI has 12 different organizations within uh OpenAI um >> it it can't get any crazier than this well they go and do deals with every single company in the world apparently so uh this uh >> yeah every time I list off how many
25:36
companies are riding with OpenAI and how many companies current market caps depend on their partnership with OpenAI I always leave off too I'm always like think of like Nvidia Oracle and Core weave and then it's like oh there's actually Broadcom and AMD there's also SoftBank and there's also Microsoft. >> Yep. >> Yep.
25:53
>> And uh it's just all over and the interesting thing that you know we had been talking about off air yesterday is this dynamic where >> uh you kind of have to assume there'll be some type of correction in the coming two years.
26:06
Not a super bold statement to make.
26:08
Yeah, we'll get into that.
26:10
>> And Open AI could very well be the only company in this crazy web that's private, >> which could be an advantage in an environment where we're seeing, you know, massive draw downs and just just due to OpenAI effectively controlling your share price, right? >> Yeah. I I like this take.
26:28
I thought what's interesting is that like being being public during a major correction is not a death sentence.
26:36
like Amazon got through it.
26:38
They saw a massive draw down.
26:40
But is being private during a massive draw down an an asset?
26:44
Is that something that you should be optimizing for? Does it matter at all?
26:48
Um because in some ways, if you if you go out, you're public, uh you raise a ton of money, you have a fortress balance sheet.
26:56
Yes, you might have employees who are disappointed because their their their personal financials are being marked to market and there's and there's and they're way down.
27:06
That would be emotionally rough, right?
27:08
Uh but at the same time, it is possible that uh at least it's public and at least you know there's some liquidity and you're not sitting there wondering like am I is this company actually worth zero?
27:24
this company actually worth zero? like you're being marked to market and it's like if you're at Amazon in 2000 2001 and you're down I think they went down like 80 90% right >> yeah Oracle with withtood a more than 80% draw down between 2000 and 2002
27:40
>> I really wonder how that works as an employee like if you were if you were there at Oracle and you were like I'm about to buy a house and then you're like I'm about to buy a shack like was it that like was it that rough like did Like were like did that emotionally affect it? >> But do but did it emotionally affect
27:59
>> But do but did it emotionally affect your work?
28:00
Were you like ah I'm too depressed to do the database migration like I'm too depressed?
28:06
>> I have a family I have a family friend that retired in their early 40s kind of after the after the dot craziness and they sold >> not at the top they sold about they they exited the majority of their position.
28:18
I I won't name the company >> prior you know 6 months out from the top. Sure.
28:25
>> And so for a while they looked really silly. >> Yeah.
28:28
>> And ultimately they were telling me all the peers that they had >> Mhm.
28:34
>> were still working to achieve like the wealth that they had on paper >> during 2000 >> 20 years later. Right.
28:42
And so you can uh again going through these is is I feel like the venture industry broadly had to go through this somewhat obviously in 200 uh 2022 2023 right everybody had these crazy paper marks that suddenly were were not um not living up to expectations. >> Yeah.
29:04
>> Uh or or at least um >> there are some crazy crazy examples.
29:07
I don't know if Akami is one of them.
29:10
There's a few companies I think AI was actually it it still is not at its all-time high of the dot boom because it IPOed at 300 in 1999 it was at $327 a share and uh now it's at 76.
29:23
I I I never know if uh if the if the the splits are accurate and whatnot, but uh there's been a bunch of companies that uh traded down.
29:33
I mean, Akami went down by 99%.
29:35
And then built back up and saw, you know, 50x gain over the next 20 years as they built back and it was like, it was always a real company.
29:44
It was just massively overvalued in the do boom.
29:47
Um, but it will be a uh Oh, this is a funny post you just put in the timeline.
29:53
There is a bubble in people calling for bubbles.
29:55
Calling for bubbles or calling bubbles.
29:58
Are you calling for a bubble? We pray for a bubble. You don't.
30:04
>> We used to pray for a bubble like this. We did. >> We did.
30:07
>> Anyway, >> I do remember in 2023 during, you know, post SVB, I >> I wouldn't go so far as to say I was actually praying for a bubble, >> but I thought it'd be crazy if our industry went through something like that, quite that crazy again.
30:23
And sure enough, we got it.
30:25
And AI, the current AI hype cycle, hasn't even got to dance with low interest rates yet.
30:33
>> It hasn't gotten to dance with low interest or leverage. Really? >> Imagine that. >> Or leverage. Yeah.
30:37
Uh yeah, everyone's everyone's saying it's 1999.
30:40
Not many people saying whether or not it's January, December of 1999 because that is important.
30:47
What day did the actual stock market peak in 1999?
30:49
I have I have a shirt search here.
30:53
It was actually March 10th, 2000. March 10th, 2000.
30:55
So if it's January and you're like, "Oh, I'm call it's it's 1999. I'm going bold. I'm calling the top."
31:03
It's like, "No, you're calling if you're calling Jan if you're calling it January of 1999, you're calling yourself 15 months out from the top, which is a wild amount of time.
31:12
A lot of room to make money. Who knows?" >> Yeah.
31:15
There was uh who was it yesterday?
31:17
Paul Tudtor Jones was saying he feels like there he was on CNBC yesterday saying, "Hey, things feel overheated, but he was basically calling for like a blowoff top."
31:28
Like he says, in his view, it can get a lot crazier before a correction.
31:34
So, and again, that feels like the the the general sentiment right now is, you know, Doug on the show yesterday was saying like, look, we're not even most of these companies are not even levered yet.
31:44
And like that is >> like almost certainly going to happen. >> Yeah.
31:49
Uh >> except Oracle, they're >> they're pretty levered, but not that crazy levered.
31:54
Like there there is some fake news around the the 5x leverage that's going on over there.
31:58
Uh it's not quite uh that big of a deal.
32:00
Um >> but uh let's switch gears, but first let's tell you about Privy Wallet infrastructure for every bank.
32:08
Privy makes it easy to build on crypto rail, securely spin up white label wallets, sign transactions, and integrate onchain infrastructure all through one simple API.
32:17
Uh Joe Ldale is celebrating one of his portfolio companies.
32:20
He says he's blown away by the talent behind some of these great companies, just a casual Nobel Prize.
32:25
Uh so Sonoma Bios Fred Ramsdale won the 2025 Nobel Prize in medicine for his work on regulatory TE-C cells or T-regs which act as an emergency break on the immune system.
32:40
T-regs are a critical link in understanding autoimmune disease and advancing immunotherapy more broadly. So congrats to him.
32:47
He's the co-founder, former chief scientific officer, and a current adviser to Sonoma Bio, a trailblazer in cell cell therapies and an 8bc portfolio company that ABC has proudly supported from the beginning.
32:58
He led the team that discovered and characterized the gene Fox P3.
33:01
Talk about a cool name for a gene, FOXP3. I like that.
33:08
Uh, which plays a critical role in T-Rex's development, leading to a new field of amunotherapies.
33:12
Um the thesis continues to be validated with portfolio companies like Orcabio which recently received FDA acceptance priority review of its BLA and Orcat in hemologic malignancies. See below.
33:26
>> Joe just comments cool. >> Cool. Yeah. I like that. >> Did he comment cool?
33:29
No, I think I clicked in. I think I clicked in.
33:31
I was wondering if he commented cool on his own post which would be some some king a king move.
33:37
Anyway, uh another ABC portfolio company, Cognition. >> Boom.
33:42
the makers of Devon BI software engineer crush your backlog with your personal engineering team.
33:45
Uh Martin Skrowley has been on a tear.
33:47
Guyer Capital breaks it down.
33:49
Says Skrey does it again.
33:51
Uh he picked a stock that went up 1,400% today. That is an insane pop.
33:55
Uh Martin Skelly says long SPB.
34:03
His price target is $500.
34:06
It was trading at 25 at the time and or I guess even less.
34:10
It was trading at 8 uh and it went up to 152 >> scrow on on Friday you could buy one share Bruce Biosciences for $8. 78.
34:17
It's now trading at $197 >> per share.
34:27
Still sitting at a at a $111 million >> market cap.
34:31
So >> is I I I still don't understand like can he can't run a fund but he can trade this like is this financial advice?
34:37
like he seems like he's playing it really fast and loose, but uh he's clearly calling good stuff and doing research.
34:45
So, appreciate the the work.
34:47
>> He's been I think making a lot of people a lot of money. >> Yeah. So, everyone's happy.
34:50
He says his price targets $500.
34:52
Rare disease is his specialty.
34:54
The ERT for San Philippo will be approved.
34:57
CMC notwithstanding and be the new standard of care.
34:59
He said, "I was working on a presentation when the news was scooped, but this drug restores the abnormally high levels of heperin sulfate to normal.
35:07
Without this drug, patients will die at 18, the normal ranges of HS.
35:11
They may live a normal life.
35:14
Oh, that's really exciting. That seems really good.
35:16
TJP says, "I'll pass already up too much." Um, >> just who knows?
35:24
>> If it goes up a lot, it there's no way it could go up more. >> There's no way.
35:26
Well, uh, let me tell you about Figma.
35:29
Think bigger, build faster.
35:30
Figma helps design and development teams build great products together.
35:34
>> Get started for free, brother.
35:34
Tyler, start playing around with Figma make in Chad GBT.
35:40
I want I want you to test out the uh >> the integration.
35:43
That's very interesting >> at dev day. >> Yeah.
35:46
Do you know if those agent builder tools are like general availability already? >> Uh yeah.
35:52
So I I tried to use the agent builder earlier today.
35:54
Um and then you have to I couldn't get it to work because you have to verify your organization. Okay.
35:59
And then I it I tried to put in my ID and then it just like said failed. >> Interesting. >> So I don't know.
36:06
Yeah, but I'll try it again.
36:06
But they are generally available.
36:09
>> Okay, well that's good.
36:09
Well, um Max Meyer is uh breaking down the free press acquisition.
36:14
This uh was announced yesterday.
36:16
Barry Weiss's free press was acquired by Paramount.
36:18
Um uh Max says, "Seeing so much cynicism and bitterness on the timeline about the free press.
36:25
So let me tell you why I love it as a contributor and why it means so much to many people.
36:30
The FP is a match made in heaven between writers and readers.
36:33
We writers can't leave live without readers.
36:38
And the FP readers are amazing, savvy, thoughtful, opinionated, but kind.
36:41
I can't tell you how many emails, texts, phone calls, DMs I've received every time I put a piece in the FP.
36:47
These are Americans I want to know.
36:47
And the FP is their gathering place.
36:49
Um, I've written pieces about very random things.
36:53
Warren Buffett, my brother, not he's not Warren Buffett's not his brother. There's a comma.
36:58
He says, "I've written about Warren Buffett.
37:00
I've written about my brother. I've written about Yeah.
37:03
a Missouri resort town, the Latter-day Saints Church, and SpaceX, which is an amazing blessing.
37:08
And a credit to their smart editors, the FB team, and their readers care deeply about America, even if they disagree about politics.
37:15
Some just scroll some of the comment sections on Trump related articles, and you'll see the amazing bites and disagreements.
37:20
What Barry Nelly and the entire FP team have done in three years is now the model for media.
37:25
make something so good that people would walk over glass to pay their hard-earned money for it.
37:29
Not to get through some terrible payw wall, but to be part of something.
37:32
The free press is worth every penny paramount paid, probably more.
37:36
How often does a talent like Barry come along?
37:38
And people who work in the world of talent should know this rather than be cynical or conspiratorial.
37:43
Barry and team have a long way to go from here. This is the beginning.
37:47
The complainers should watch and learn, which is exciting. Um, >> yeah.
37:52
I mean, I I just looked at this as a way to make CBS news relevant again. Yep.
37:58
>> To a new important class of readers. >> Yep.
38:03
>> Uh, a much younger demographic than the CBS audience today. >> Yep.
38:07
>> And you look at it as like a trade deal, right?
38:09
This is a talent acquisition. Yep.
38:12
>> Barry Weiss will probably create far more than $150 million of value just by being a part of CBS. >> Yeah. Yeah.
38:21
>> Also, I mean, I do think that like I mean, we talk about this a lot, but like audience quality is like still deeply misunderstood.
38:28
A lot of people just look at uh total audience size, impressions.
38:34
They see every reader as the same value.
38:37
Uh and that was certainly true in the days of uh the three major networks, CBS, NBC, ABC.
38:42
Um but we're just in a completely different, much more fragmented world.
38:47
And so I don't know if they had a million subscribers or something like that, but uh the people that opted into the free press's funnel are uh probably way more monetizable than the people that are uh you know turning on late night CBS for the you know 50th time.
39:05
Um and so they definitely pulled in interesting people.
39:09
Uh pulled in me when they signed Tyler Cowan.
39:11
Uh and I've been enjoying his column there.
39:14
He wrote a wild one about how his favorite new actress is AI. Very controversial.
39:20
He's really leaning into it. It's great.
39:21
Um but uh Alex Broini Bronzini vendor is a perfect example of someone who's a little bit of a free press hater.
39:30
So the free press on October 6th said the free press is joining Paramount and they share a link to the fp. com.
39:37
They put the link right in there.
39:40
And uh Alex says, "This post has acred 147 likes in four hours.
39:46
Nearly one for every million dollars Paramount thought the free press was worth."
39:50
And honestly, 147 likes on X with a link in there to a Substack is uh it's a miracle. It's a miracle.
39:59
Um but uh yeah, people are people are laughing.
40:02
But yeah, uh Nick says, "The the New York Times gets similar likes on Twitter.
40:05
you're not saying anything meaningful.
40:07
Um, and yeah, uh, I don't think anyone it believes that Barry Weiss has as big of an audience as Mr.
40:15
Beast, >> but that doesn't quite matter because it's a different audience.
40:19
And, uh, and hitting certain audiences is more valuable than other audiences.
40:26
>> Um, where else should we go?
40:26
The entrepreneurial tech, the hat is back in the news.
40:30
The hat is back in the news. Anthropic hat. Break it up. >> Yeah.
40:34
Jordan says, "The tone of the quote entrepreneurial tech glaze makes me sad for the whole world and all of history."
40:40
That is a bold statement. Uh, I don't know.
40:42
I mean, did we talk about this yesterday?
40:44
I think the I think that Anthropic's campaign is good.
40:50
>> I don't think it's and I can see why people want the hat >> and Anthropic is a great brand and they have a great team and they have a unique culture and they've been able to retain people.
41:00
It's the place that many >> of uh the brightest minds in AI want to work at. >> Yeah.
41:07
>> That said, I I don't think this is an award-winning campaign.
41:10
It's like they put a verb on a dad cap, right?
41:12
We've we've been doing this since like >> 2016.
41:17
>> 2016 is kind of how I clocked it.
41:17
Um it they're they're selling coffee.
41:21
A lot of a lot of people in tech have done this. Yep.
41:24
I think this is more just excitement around Anthropic's overall positioning, right, as like the anti-Slop AI company. Sure.
41:30
So people are are choosing to side with them and there's they've built up a cult around what they're doing which is very powerful.
41:40
But again, uh I'm not uh I'm not uh blown I'm not blown away by the I'm I I love the anthropic team and and I think their products are amazing.
41:52
But >> personally, at no point was I thinking I need a liner up around the block to get this hat, you know, and and I actually wouldn't I wouldn't wear the hat, but um um so anyways, I think >> I would be caught dead in that hat.
42:08
>> I wouldn't be caught dead in the hat.
42:10
No, >> don't even try to put one of these on my head.
42:12
>> I I I think the hat is kind of >> No, they're cool. They're cool. It's fine.
42:15
It's just that you put a verb on a dad hat. >> Okay. Yeah.
42:20
>> Do you want a >> Sure. >> Do you want an award?
42:24
>> No, they didn't ask for award.
42:24
People are just excited about that. I know.
42:26
But that's So Jordan Castro is reacting to the reaction.
42:29
It's not like Anthropic went out there and was like, "Please like glaze us."
42:32
You know, it's just like they got glazed and then Jordan is like, "Stop with the glaze."
42:36
And it's not really their fault.
42:38
But I I I I think the bigger question is like is like is I >> I just think the question is can they get a true foothold in consumer because this >> That's a great question. That's a great question.
42:50
>> This campaign is very consumer focused.
42:52
I saw these keep thinking billboards on uh I don't know not not Melrose Sunset Boulevard in West Hollywood >> sandwich in between two friend. com billboards. >> Yeah, probably.
43:04
I'm surprised they could even buy that for you.
43:07
>> John and I John and I drive John and I drive around.
43:10
>> You see friend billboards everywhere. >> You can't go towhere.
43:12
You cannot go two blocks.
43:15
It's like every other block >> the most massive billboards.
43:18
I saw we saw a friend on billboard that is like basically behind the building and I was like avi >> why didn't he even pay one did you just really hit market buy >> he bought everything >> um >> he went on adqu.
43:31
com out of home advertising made easy and measurable say goodbye to the headaches of out of home advertising only adqu uh get on quick because they will help you pick billboards that are not directly up against walls >> yeah no you you no in in no circ circumstance would an entrepreneur with limited resources look at this billboard and think, "Yep, I got to have this one."
43:54
Because it's like more than twothirds of it was covered by a building.
43:58
You had to be at the most insane angle while you're driving by.
44:02
You have to >> you have to peek around out your window. >> Yeah.
44:06
So, I mean, uh, >> but so here's what I'll say about Anthropics campaign. Yeah. >> Breath of fresh air. >> Yep. >> It's quality. >> Yep.
44:14
>> It's not award-winning. >> Yep.
44:16
And I think that the people that like it, I totally get why they like it. Breath of fresh air.
44:20
I understand why other people that are not in tech are thinking this is the best that you got. >> Yep.
44:28
>> This is this is >> this is your hero. >> Yep.
44:32
>> It's like the bar is just pretty low, right? The bar overall is low.
44:34
And one of the challenges is that AI the brands of AI companies get tied to the outputs.
44:42
And sometimes the outputs are great and often and most often they're not so great. Right.
44:47
And so, um, I'm interested to see how aggressive OpenAI gets with that video campaign they did with the, um, what's the Tele Euphoria? Yeah, the Euphoria.
44:58
>> I thought those videos were great.
44:58
Um, and >> what's interesting is that, uh, Anthropic did a video series that was very similar aesthetically.
45:06
uh warm tones, highly cinematic, shallow depth of field, uh very emotional, like just a few weeks or months earlier.
45:14
I can't even keep track at this point.
45:16
Uh so both of them were experimenting in the same brand landscape.
45:20
Um I I personally would like, you know, our sponsor Vant to do a hat that's actually just a huge llama helmet and it says automate, compliance, manage risk, proof trust continuously on it.
45:32
And it should also say, you know, the anthropic hat is so simple. It just says thinking.
45:37
It doesn't even say anthropic on it.
45:38
I think the Vant hat should say Vantis's trust management platform takes the manual work out of your security and compliance process and replaces with continuous automation.
45:44
Whether you're pursuing your first framework or managing a complex program, like all the way around the hat, just put the entire landing page on the hat.
45:50
I think that would be innovative.
45:52
Um, >> I uh there's also >> I was thinking uh somebody needs to make a uh nobody's made the AI smart helmet yet that you can wear all the time from the moment that you wake up to the moment you go to bed potentially even when you're sleeping.
46:07
Think about how much comput and so much battery you could have all day battery all month battery.
46:13
Also, wearing a motorcycle helmet is incredibly cool.
46:16
you I mean I know you haven't seen Kill Bill, but the bride played by Uma Thurman in Kill Bill uh Tarantino Tarantino classic uh wears this motorcycle outfit with this motorcycle helmet and just looks so sick.
46:32
>> So next time we talk with Zach that's going to be my pitch >> AI motorcycle helmet that you can daily >> imagine you're just like just rocking in the workplace and you're just like I'm locking in. I don't >> know.
46:44
We're joking about it, but I could see this actually being created.
46:46
It's like a good helmet, >> dude.
46:50
It's more comfortable to wear a ski helmet or a motorcycle helmet than an Apple Vision Pro.
46:54
Yeah, >> let's just be honest about it. >> Yeah.
46:57
>> Uh and so why not strap that whole thing on your on your head? I love it. >> Uh it's amazing.
47:02
Uh I have a couple rebuttals to you.
47:03
First, I'm going to talk about graphite.
47:05
dev code review for the age of AI.
47:07
Graphite helps teams on GitHub ship higher quality software faster.
47:10
Um but so uh anthropic inconsumer uh they're clearly behind but it's very interesting because they have a fantastic model that can instantiate code very quickly.
47:19
You could do all of this like on the-fly app development basically.
47:25
So when you ask a question it actually builds a piece of software for you that's interactive.
47:31
There's so many cool things that they can do with their foundation model.
47:32
Also they have my Kger and so you I I just feel >> I was trying to push him on a little bit.
47:38
What what can you do on the social side to catalyze >> Claude's growth?
47:43
>> Yeah, like when I think of the backlash to Meta Vibes, the backlash to Sora 2 and Sora.
47:48
If I were to try and build a team that would not face backlash to a consumer product, to a new consumer product, I would back Claude with Mike Kreger, right?
47:59
Because he's going to build something that's like delightful, just like the early days of Instagram.
48:02
I would think that he would inject that kind of like simplicity and beauty into the product that they build. Who knows? Maybe it's coming.
48:10
Maybe every foundation model company needs an answer to the AI slop Tik Tok feed.
48:15
Uh and I would be very excited to see what comes out of Enthropic.
48:20
Uh the other take on this hat is hat aside, I think that keep thinking is a good phrase.
48:28
I think thinking is a good phrase.
48:30
I think it's a good word.
48:33
I think they picked that word well and it excites me and it actually hits like you can talk a lot about it like oh they just a word on a hat but of all the words to pick it feels more human.
48:46
It feels less uh less cyber punky.
48:50
cyber punky. It feels less like super in super intelligence feels like okay maybe that's opposed to my interests like fast takeoff all these scary AI doom things which anthropic is like honestly famous for >> everybody is loving this campaign but
49:08
thinking machines lab >> that is true >> absolutely brutal >> but I thought it was interesting that that the message is keep thinking if you're a human keep thinking don't stop thinking Like what we do here at Anthropic is not think for you. That's
49:23
That's an interesting message because for a long time people were saying >> they say we here for you.
49:32
>> A lot of the what's that from? Is that >> way star Roy? >> Oh yeah.
49:35
So, so a lot of uh like a lot of the AI like a lot of the AI rhetoric has been the AI will be able to think for you.
49:47
>> And Anthropic is specifically putting on a billboard whether they believe it or not or whether that's where AI actually goes.
49:53
They're encouraging you to say, "Hey, keep thinking because that's not our job.
49:57
Our job, you do the thinking and we do the coding and all the boring."
50:02
>> Are you sure they're not just worried?
50:03
It's like, "Hey, you guys are relying on cloud a little too much.
50:04
cloud a little too much. But keep thinking buddy and and and so that is the question is like is this Daario's new view because the view that Daario has espoused on many a podcast is yeah you're not going to be thinking because
50:19
there's like a 45% chance that everyone's dead cuz you know he's like he comes out with some hardcore rhetoric that does not feel extremely warm or human or anything about like hat like are you going to be wearing hats if we're all paper clips like no. And so
50:32
And so like is this a is this the marketing team at Anthropic saying like let's let's step away from Daario's viewpoint a little bit or is it more Daario has actually shifted his thinking and is saying like no I actually feel like what we are building is complimentary to humans that would be exciting and I feel like that would be inspiring to me and I would be I would be excited about that.
50:57
Um, and so I don't know where all this goes, but uh, it's I think it's a step in the right direction.
51:03
There there there are so many other campaigns that could have been less human, more clankercoded and would not have hit.
51:12
And this one clearly hit to the point where it got so much positive attention that there was a backlash to the positive attention, which I think is >> it's kind of the best case scenario for a really positive ad campaign is that people get sick of people talking about how good your ad campaign was.
51:27
So, >> I think it was pretty good.
51:30
We need to react to the AI homeless man prank on someone's dad. >> Yep.
51:37
>> Uh we've been instructed that we must deafening.
51:40
Uh, can we pull this video up?
51:44
>> While we pull it up, Avi Schiffman has hit the timeline again.
51:46
He says, "Every single available bus shelter in LA now has a friend ad."
51:51
So, apparently there weren't enough ads.
51:56
>> That's what people were saying.
51:56
They were like, >> they said more.
51:59
>> We need more billboards.
52:01
You got to push this campaign further.
52:03
There just aren't enough billboards.
52:04
People aren't aware of your campaign.
52:07
You're barely baking through, buddy. Step it up.
52:09
Uh, let's watch the AI homeless man prank on my dad video.
52:16
Okay, so you take a picture, send it to the dad.
52:19
I can't read any of this. This is too small.
52:25
[Music] Is this add is this like Nano Banana adding the dad to the to the pictures of the actual house?
52:37
>> Seven phone calls from the dad.
52:40
So he's bring he's he's pitching I'm bringing in the homeless person into my house. No. Oh, in the bed. 13 phone calls.
52:46
Do you think this is at all real or do you think this is all theater?
52:51
Do you think this is all created? >> All theater. >> All theater.
52:57
>> But it's mildly entertaining. >> Yeah, it is.
52:59
Uh it is an interesting case study in like AI slop in the sense that like it's using AI to create you know Photoshop text messages I suppose.
53:10
Um and uh and and getting a laugh out of that but >> yeah it's like using AI to lie for entertainment >> to lie. Yes.
53:18
But but it's it the lie is like a meta commentary on the nature of AI slop, right?
53:24
because it's it's the the the joke is on the dad or the the theoretical the hypothetical dad in this the character of the dad.
53:32
Um anyway, let's talk about Julius.
53:36
What analysis do you want to run?
53:38
Chat with your data and get expert level insights in seconds.
53:42
Ask Julius to an uh to analyze your data.
53:46
>> Uh images make feel pain.
53:46
There's a post here from Aishwaria who says, "Lowkey, the anthropic NYC popup hype is proof a lot of tech people have never been invited to a fashion week event or a real brand activation before. Keyword being invited." >> That's probably true.
54:04
I mean, these are wildly different worlds.
54:05
Uh >> uh Hayden Johnson has a post here that says, "Every AI ad is like, "Hey, Gemini, what would I have for lunch?"
54:16
And then the phone is like sandwich and the guy is like wow. >> That's so funny. >> Wow.
54:23
>> Okay, we need to watch the video of Ken Griffin uh giving some hot takes about the AI.
54:30
>> This is this should be the most near-term bearish thing you watch today.
54:35
>> Let's see from Bourbon Capital.
54:35
Bourbon Capital highlights it.
54:36
Finally, someone isn't afraid to speak the truth.
54:38
People have been speaking the truth or, you know, giving hot takes for months now.
54:43
Let's just make that clear.
54:43
But let's hear it from Ken Griffin himself at the future of global markets 2025 citel securities conference.
54:51
>> Large language models particular have been in existence for a few years.
54:53
I think there's a real chance that when we think about the the forms of of AI that are alluded to by many of the markets leaders today that their dream for the future may not take three to five years to play out. It could be 20 years. It could be 30 years.
55:16
>> You know, it's like the internet and I I people hate this analogy, but like the.
55:19
com moment >> back at the start of this century.
55:25
Did anyone have any doubt that the internet was going to change the world? No.
55:28
Has the internet changed the world? Absolutely.
55:31
But did it take longer than anticipated?
55:36
And was there a period in which which there was a real sort of sorting of the winners and losers that took place unequivocally? Unequivocally.
55:44
And I think that the AI story will have many of the same components.
55:52
>> There's a bubble and people calling for bubbles.
55:56
Tyler, >> but I think this is this is this is just ultimately a very sound analysis and it's coming from somebody who is >> highly intelligent, highly accomplished, highly invested and yet doesn't personally, to my knowledge, have a
56:13
billion dollars of >> equity in a lab who's incentivized >> to keep the part like >> well he might have a billion dollars like this second and then not tomorrow and then no not the next second and then this second and then this. Ken Ken Ken's
56:23
Ken Ken Ken's going to make money no matter what. >> Yeah. Yeah.
56:28
>> He doesn't, you know, I'm sure he's making a lot of money now.
56:30
Maybe maybe in a correction he makes less, but he's going to do fine no matter what.
56:35
>> And so Citadel got roasted in the financial crisis.
56:39
>> Yeah, they drew down 50%. >> Yeah.
56:41
Didn't he almost like wind down the fund? >> Bad.
56:44
But but it's important to not just listen to the predictions and opinions of people who have the heaviest bags sure >> that are dependent on keeping the party going long as possible.
56:59
>> Uh Tyler, what you got?
57:00
>> Um so it could also be that his competitors are invested in the AI labs, right?
57:05
I think Jane Jane Street is big in >> Yeah, big in anthropic. Oh, >> okay. Yeah.
57:10
>> So maybe it's really he's >> lack of bags problem.
57:11
He has lack of bags, so he's bearish. >> Sidelined.
57:16
>> Lack of bags is is as much of a conflict as not having conflicts is a conflict because you don't have bags and so you're incentivized to be bearish on people that have bags.
57:26
>> Yeah, >> this is a fact.
57:26
He wants to crush his enemies.
57:28
>> Tyler, how many days until the singularity?
57:31
>> We're still we're still at 3650.
57:31
I guess it should have >> 36.
57:35
>> There wasn't a lot of big news since I changed it last, so I guess it should have gone down every day.
57:38
But >> so 10 years until the singularity.
57:39
Uh, we need to be updating that daily so at least we're ticking down.
57:43
But watching that Ken Griffin clip, are you adding days? Are you removing days? What are you thinking?
57:51
>> Griffin is like kind of boomercoded.
57:51
So I'm saying I'm saying we're closer to AGI after watching this. >> Okay.
57:57
You think you think he's a contraindicator for AGI progress? >> Yeah. Yeah. >> Okay.
58:01
So you're so you're removing days.
58:04
So we're down to like 3,000 days now. Just nine years.
58:06
>> I mean 600 days I think that that's almost two years, right?
58:08
That's a little too big of an update. >> Yeah.
58:10
But >> yeah, did did either of you watch the Dark Cash Sutton reaction? The apology video.
58:16
Someone said, this is so funny.
58:19
It was not apology video.
58:19
Uh Dark Cash did apologize in the video, but only saying, "I apologize if I'm mischaracterizing your your statement.
58:26
I and I have some of the ground truth wrong."
58:29
But I I thought it was interesting.
58:30
interesting. I I I felt like I came away originally thinking that the that the bitter lesson was poor endless commu compute behind any algorithm that's working and scaling when Sutton kind of reclassifies it as like like the game of
58:44
the AI researcher is to hunt for the next algorithm that will scale with compute and he's not saying that any algorithm will necessarily scale infinitely with compute and so he like my my takeaway was that he was he's if He looks at LLMs. He's like, "Good
59:00
He's like, "Good progress for fours.
59:05
Maybe need a new thing to go for the next five or something like that."
59:07
Was that your Was that your read? >> Um, yeah.
59:11
I mean, the thing about LMS is like >> you like the scaling like you there's just no more data to scale with.
59:17
So, it's like not kind of bitter listen in that sense anymore because you can't just keep throwing more compute at the same LMS because if you just make the models bigger or whatever, it it's not like it's not going to get better.
59:27
the model won't be better because the because the data is is constrained. >> Yeah. Yeah.
59:31
It's this weird thing where like on like you can zoom out and look at like computing power over the past 50 years and see a very very smooth curve.
59:43
Then you can look at like the AI winters and see that there's like these huge steps in progress.
59:48
steps in progress. the transformer paper um the uh I don't know there there's been a whole bunch of like uh image net right >> reasoning models >> reasoning models big big step forward and those are like those are like a decade apart sometimes um and so you get
1:00:05
these like qualitative bumps where you're like oh wow like this feels different but then in that interim you might not see a lot of like qualitative jumps in clear progress clear new capabilities but the diffusion of that economic value is immense. And so we
1:00:18
And so we like technically pre LLM we were kind of in an AI winter I suppose where like you know self-driving cars were like 10 years behind nothing was really like popping in AI AI was not a buzzword uh people weren't using AI domains but in that in the in the period of time from like call it 2010 to 2020 like what was the economic impact of AI like it was insane right because Netflix was doing recommendation algorithms.
1:00:49
Amazon was doing recommendation algorithms.
1:00:51
The Facebook algorithmic ad feed, Tik Tok feeds, like like AI wasn't transformer based LLM, but AI was a massive driver of economic growth.
1:01:03
>> Will created the AI hype cycle >> probably >> in order to sell more.
1:01:07
AI domains >> isn't like 50% of their GDP AI domains.
1:01:12
>> 50% of their like >> budget >> basically like budget comes from >> it's remarkable. ai domain. >> It's remarkable.
1:01:18
Well, if you want to generate some media, head over to Fall, the generative media platform for developers, the world's best generative image, video, and audio models all in one place.
1:01:27
Develop and fine-tune models with serverless GPUs and ondemand clusters.
1:01:31
>> And if you want to bring our soundboard into your team meetings, team Zooms, your team Hangouts, go to tbpn. com/sounds. Brought to you by Fall. >> Yes.
1:01:41
Uh Chubby says, "I double checked.
1:01:44
You can already buy Unit's G1 at Walmart.
1:01:47
Only $21,000 shipping in one week.
1:01:49
Tesla must hurry to deploy their offers. >> Do we buy one? >> Do we buy one? >> We got to, right?
1:01:57
>> We have to buy one of these and have >> It's such a wild thing to let a fox into the hen house.
1:02:04
But sometimes you got to do it, right?
1:02:05
The global economy let Sam and the fox into the hen house. >> Fox.
1:02:12
>> Uh, and uh, we'll see what happens.
1:02:16
The hen house analogy is like amazing.
1:02:18
But I don't think of the >> house G1 basic.
1:02:20
This is the CCP Fox into the Ultradome and just >> I think of the TBloo less as a hen house and more as a bull ring. >> It's more of a fox. We're still on the farm.
1:02:34
>> But over here you have the bulls jacked fighting.
1:02:36
You get mess with the bull, you get the horns.
1:02:38
Unitry, you're on notice.
1:02:41
If you send over unit G1 basic for $21,000 with shipping in one week and you try any funny stuff, you're getting the horns because this is not a house.
1:02:49
>> I would say this is like letting a clanker into the fox house. >> We're all foxes now. >> In the fox.
1:02:56
>> I think we I think I I >> This is a head in the fox house. >> The foxhole.
1:03:03
>> I I'd be kind of worried leaving the G1 basic with Tyler.
1:03:06
You know, I presumably Tyler would be tasked with setting it up, but then you're thinking about, okay, the G1 is going to be here with Tyler.
1:03:16
>> So, >> potentially after hours and I should be a little bit worried about >> So, we can So, we can train it to swipe ramp cards or something.
1:03:22
What What can we do with this?
1:03:25
>> You could uh automatic gong hits.
1:03:27
>> Ooh, automatic gong hits sounds good. Put me out of a job. Wow.
1:03:30
Real real black fell economics. >> Daario was right.
1:03:36
>> Automate white collar worker work and I hit a gong.
1:03:40
Uh that is uh remarkable.
1:03:43
>> I can't believe we're doing this again like we did with drones where we're just going to let Uni Tree just flood the market. >> Yes.
1:03:49
Where is uh where where are the hawks on?
1:03:53
>> I'm normally normally, you know, against government intervention, but uh >> two hour battery life. Look at this thing. We got to get one. Tyler wants it so badly.
1:04:03
I wonder I wonder what else you can do with it.
1:04:06
like how strong is the API?
1:04:07
Does it have like the ability to issue voice cards swiping everything? You get dangerous.
1:04:18
Um anyway, we are being joined by Shane from Polymark in just a few minutes.
1:04:21
In the meantime, let me tell you about what uh Buco Capital Bloke is saying on the timeline.
1:04:26
He says, "We had a good thing, you stupid son of a.
1:04:28
We had 98% gross margins and LTV to CAC ratios above five.
1:04:33
We were considered safer than first lean debt.
1:04:35
Nobody questioned our terminal value or stockbased compensation.
1:04:38
We had everything we needed and it all ran like clockwork.
1:04:42
You could have shut your mouth, funded a few new SAS companies each year and made as much money as you needed, but you just had to blow it up.
1:04:47
You and your pride and your ego talking about AI.
1:04:49
Uh lots of people having fun.
1:04:52
Well, in the uh in the rest of this world, >> uh obviously OpenAI sent around a bunch of uh basically uh deal toys for people that spent over uh or used a trillion tokens with OpenAI.
1:05:05
Uh Notion got one, Ramp, a bunch of others.
1:05:08
Y uh Lauren Good says, "This is sort of like spending a million bucks gambling and the casino gives you a free hotel room for the night." >> It's close.
1:05:17
I think I think that's the next that's the next leg up in the in the cycle.
1:05:21
Cognition got uh got one one trillion hacking. Uh ramp got one.
1:05:25
And I was trying to do the math on how much a trillion tokens actually cost so I could clock how much these companies are spending.
1:05:34
Uh chat GPT uh clocked it as if they're doing GPT 3.
1:05:38
5 Turbo uh that's the cheapest cheaper case. That's a million bucks.
1:05:44
If it's GPT4 standard, that's $45 million.
1:05:46
Um, so potentially hitting I mean notion has talked about how this hit their gross margins.
1:05:51
It's not a immaterial cost but a lot of value to the customers and uh Tyler what's the cheapest way do you have a do you have an update on how how cheaply you could acquire one of these uh deal toys? >> Yeah.
1:06:04
Um well so so the main thing you would do is you can do a batched uh API calls.
1:06:09
So instead of just doing like one and then you you get the response you send like a ton and then it get I think it's like within 24 hours you'll get the response back.
1:06:16
Do you actually do that when you when you run your examples? >> Uh, no.
1:06:19
None of the stuff I do is >> Oh, so money just doesn't matter to you around here.
1:06:22
You just don't care about cost optimization at TV. >> I got to be timely. >> Oh, yeah.
1:06:26
>> But I I think that is money.
1:06:28
>> I think that's either 50% or 90%.
1:06:28
And then the other thing you do is you can do cached inputs, which is like I I forget which one is which, 50 or 90%.
1:06:35
But if you combine those, then it's like massive savings.
1:06:37
So then I think if you combine those with >> is it is 3.
1:06:40
5 triple the cheapest or I feel like it's GPT5 nano.
1:06:44
>> Yeah, something like that.
1:06:44
Um, but I think you could probably do it for a couple thousand dollars.
1:06:48
Get the >> I think I saw someone maybe they were talking about 10 million tokens, but they 10 billion tokens, but they said $25 for 10 billion tokens.
1:06:57
So, for two grand, you could potentially get one of these deal toys that are pretty rare.
1:07:03
You might be able to flip these. Who knows?
1:07:04
This is a piece of uh this is a piece of lore.
1:07:06
>> Did you see Matt Lavine's summary of AMD and OpenAI? >> Yes.
1:07:09
Martin Scrley put this in the truth zone to be clear. Let's read it.
1:07:11
But first, let me tell you about Turbo Puffer. Search every bite.
1:07:14
Serless vector and full text search build from first principles on object storage fast 10x cheaper and extremely scalable. Uh read Matt Lavine.
1:07:21
How do these negot negotiations go? Uh like schematically. Open AAAI.
1:07:26
We would like six gawatts worth of your chips to do inference. AMD. Terrific. That will be 78 billion.
1:07:32
How would you like to pay open AAI?
1:07:34
Well, we were thinking that we would announce the deal and that would add 78 billion of to the value of your company which should cover it.
1:07:39
AMD dot dot dot openai dot dot dot AMD.
1:07:41
You know, I'm pretty sure you have to pay for the chips. Openai, why? Uh, AMD, I don't know.
1:07:47
It just seems wrong not to. Open AAI.
1:07:49
Okay, why don't we pay you cash for the value of the chips and you give us back stock and when we announce the deal, the stock will go up and we'll get our 78 billion back. AMD. Uh, here we go. AMD.
1:08:01
Yeah, I guess that works though.
1:08:03
I feel like we should get some of the value opening. Okay, you can have half.
1:08:06
You give us stock worth like 35 billion and you can keep the rest.
1:08:11
>> Martin Crowley didn't like it.
1:08:11
He said this is not at all what happened and Matt Lavine is stupid. You shouldn't read him.
1:08:16
Zero days Wall Street experience word cell. He's not happy about it. >> Moged. >> Moged.
1:08:21
But uh >> um this is interesting.
1:08:23
I think it's funny from uh >> J Bowl on X.
1:08:29
How hilarious is this Oracle move?
1:08:34
Oracle makes all the AI names rip on some madeup capex guide using revenue that doesn't exist from OpenAI and now it sinks the entire space with bad news regarding AI capex not working. What a joke.
1:08:48
>> I mean, how how quickly do you expect the capex to pay off its >> Oracle sold off hard this morning?
1:08:52
Uh went from $290 a share to $270 a share, but it's climbing back up.
1:08:59
We may be back to where we were.
1:09:01
I think that's because people are reading into the uh that that that article about the information new Hindenburg research >> potentially but I think people corrected the record pretty quickly on that.
1:09:13
Uh you were expecting high margins what it's like two weeks out from the Oracle news maybe a month.
1:09:20
I mean I guess we were at the stock exchange for uh for the CLA IPO when the Oracle news broke right or what it was then right? Yeah, that week.
1:09:31
So, that was just a couple weeks ago.
1:09:33
weeks ago. And uh and um I mean it was definitely like the most aggressive deal ever and it was a crazy deal but uh people are potentially reading too much into the near-term uh the near-term financial impacts because it just like takes time to understand like if the
1:09:52
demand shows up and more people pay and the ads monetize and more people are you know seeing ads on Sora or paying for credits like there is a world where the economy keeps flowing back and forth and people consumers are putting money into the system and so even these circular deals work out. So
1:10:08
So >> you want to know something bullish >> please? I'd love a bull.
1:10:13
>> Russia's flagship AI product is called Giga Chat.
1:10:17
>> That's bearish because Russia is the bear, right?
1:10:22
>> That's a crazy mascot to pick.
1:10:22
Russia instantly bearish your entire country. >> Wait, what? What is it?
1:10:30
>> It's called Gigachhat. >> Giga Chat.
1:10:31
That's a pretty good name.
1:10:34
All the different countries are really leaning into their sovereign AI.
1:10:38
>> You don't hear much about Russian AI though.
1:10:40
>> No, I was wondering when they would get around to announcing something like because they have all these incredible math uh like math experts.
1:10:46
You'd think that they would be like really really good.
1:10:50
Um but maybe they would have been preoccupied with a bunch of other stuff going on. >> Certainly. >> Yeah.
1:10:56
I mean, they lost uh Nebius, too, which would have been a national champion had they not gotten into a >> That is crazy story.
1:11:03
Yeah, we got to have the Nebia CEO on and dig into that.
1:11:06
It's what what a wild wild time.
1:11:08
>> Uh good morning, Nat Ellison. Uh is it Elias? How do I pronounce that? >> Nat Elias. Good morning. Remember the name? >> Remember the name.
1:11:18
>> Do we have time to get through this Wilmanitis post?
1:11:19
This looks a little long.
1:11:21
I don't >> Yeah, this is the new meta.
1:11:22
I think I I I think the algorithm has changed on X.
1:11:27
It used to be all about short, piffy, punchy posts, but now the 500word long post is doing really well.
1:11:34
And so we're seeing a lot more of those.
1:11:36
Uh Jeremy Gon has dropped a couple that have done very well.
1:11:40
Will Manitis is now getting in on the action.
1:11:42
Uh let's read through it.
1:11:44
Uh he says, "Every few weeks now, a feeder drunk allocator declares a company going from 0 to 2 million is not interesting.
1:11:51
only the ones that go from zero to 500 million.
1:11:53
This is of course a very silly idea, but it is proximal to an important one.
1:11:58
We are returning to a much older model for growth of internet companies.
1:12:03
Welcome to the deal, Yuga.
1:12:06
Following the crash, the modern internet company was defined by sales as its fundamental motion for growth.
1:12:10
Scared of the business development of the 90s, companies would hire farms of thousands of SDRs to smile, dial, and build pipeline.
1:12:19
ACVs across the businesses fell steadily over the decades as we realized if we lowered the contract pipe uh the contract price collective delusions like productled growth allowed increasingly lower and lower individuals on the totem pole to sign software contracts when cold called and thus increase the speed in which a business could grow albeit in smaller and smaller steps.
1:12:40
As the discretionary spend capabilities of a random software engineer increased, this is like the bottom up uh adoption of software, so did the viability of productled growth.
1:12:51
And thus we cargo culted a set of growth metrics built around it.
1:12:53
Time to 100 million, cloud 100, etc.
1:12:55
Some good businesses were built alongside many bad ones.
1:12:59
It's easy to think of PLG as a trauma response to the dot and subsequent SAS bubbles.
1:13:04
If you lower your engine of growth to only grow in humansized chunks, you can both grow increasingly predictably that revenue and decrease the damage of any given customer imploding has on one on your entire book.
1:13:17
Uh the best way to think of PLG perhaps is to perhaps imagine it as the golden calf of Exodus 32.
1:13:22
If we had the real god enterprise and we we had the real god enterprise and we and we decided to take the easier path after we stopped after he stopped when he stopped speaking momentarily.
1:13:35
The shift we are watching today with many companies growing quickly$1 to hund00 million in 48 hours and many companies growing in massive chunks.
1:13:43
OpenAI owning AMD etc is not a new model but instead a return to the origin of this industry deals.
1:13:49
Deals are of course the origin of the internet business itself.
1:13:55
The internet business as originally built raised money exclusive to conduct deals.
1:13:58
The '9s were a wash with channel partnerships, leasing agreements, customer book buyouts, IP sharing and washing and all kinds of beautiful deals. >> Deals in all caps.
1:14:10
The incredible Alex Dank Denko speaking on Jackson Doll's podcast put this well.
1:14:14
quote, "One of the interesting hallmarks of that era was that much of the genuinely forward progress a company had to make was by doing deals.
1:14:22
The incredible stable surfaces and platforms we enjoy today from which you can just build and get growth didn't exist.
1:14:28
Companies were ultimately dependent on business development at a much earlier and more critical stage.
1:14:32
The path was much more milestone driven involving major deals.
1:14:38
For instance, you had to secure vendors for compute, buy computers, buy a database from Oracle, and also arrange distribution deals priced in then it ought to have been. Sound familiar? It certainly should.
1:14:50
Even Oracle is still the same.
1:14:52
These 100 to500 million stories are not software companies growing fundamentally quicker than their predecessors.
1:14:58
They are software companies growing in fundamentally different ways.
1:15:01
As we return to the deal yuga, we should expect the shape of these companies and the teams that run them to change even further.
1:15:07
The teams and investors that learn from history from the first great deal age will avoid the many pitfalls that come from this kind of growth.
1:15:16
Chief amongst them, the idea that partnerships and infrastructure providers much larger than you are somehow win-win altruistic arrangements and not having you the device of your underdog, of your undoing uh and hoping for the best.
1:15:29
Welcome to the second deals era.
1:15:31
We've never been more back. It's fun.
1:15:35
Very similar to what >> Yeah.
1:15:37
I mean, this is what people say about, you know, in another life, Sam Alton would be on Wall Street being as a banker, right? Doing deals. Yeah.
1:15:44
So, >> it is uh even his critics should admit that uh it's remarkable. >> Fantastic deals guy. Remarkable.
1:15:50
And like I I think people have been so skeptical of the early deals like the Microsoft deal.
1:16:00
Like it seems like that deal completely saved OpenAI.
1:16:02
They were never going to get compute as a nonprofit.
1:16:06
They had to do this insane deal to create this for-profit entity. Very complicated.
1:16:11
Something that requires an immense amount of uh you know greasing the wheels.
1:16:15
And we're just seeing more and more of these uh like foundertofounder deals.
1:16:20
no investment bankers involved.
1:16:22
Uh it really is the era of the high agency dealmaker.
1:16:24
Uh Jeremy Kon was talking about this.
1:16:27
I asked Patrick Hashanosy about this on the show.
1:16:30
the show. um this idea that in the future folks with private equity backgrounds, investment banking backgrounds might be better as founders because they are more set up to to be deals guys on day one as opposed to the uh the the more product focused, PLG focused, engineering focused founder of the YC 2010 era that was focused on
1:16:53
building a product that was sticky, had a viral loop, would grow and kind of, you know, just compound and then and then eventually they would learn to do deals at some point, but that was something that they would add on later, like uh learning financial engineering uh in in the second decade of your company. Now, companies and founders
1:17:09
Now, companies and founders seem to be adopting these ideas on day one. >> For sure.
1:17:15
>> Well, uh there's a video that went quite viral yesterday that we can pull up in the timeline.
1:17:18
Another uh uh illustration of the deals between Nvidia, AMD, and OpenAI.
1:17:25
>> While we pull that up, let me tell you about profound.
1:17:27
Get your brand mentioned in chat.
1:17:29
reach millions of consumers who are using AI to discover products and brands and we will pull up this video. Let's see it.
1:17:41
>> Who uh where did this come from?
1:17:41
You just saw this on the timeline.
1:17:42
This is >> this AI generator. >> Okay, let's see.
1:17:47
>> We need some audio here. >> Let's see. AMD, Nvidia.
1:17:48
Is this the Three Stooges? >> Here's 10. I owe you it. >> Uh you owe me 20. Here's 10. I owe you 10. Here's a 10 I owe you. Here's a 10.
1:17:58
Speaking of money, how about the 20 bucks you owe me? >> Oh, yeah.
1:18:00
Well, I only got 10, so here's 10 I owe you 10. >> Thanks.
1:18:03
>> Hey, Mo, you owe me 20. >> Well, here's 10. I'll owe you 10. >> Uhhuh. You owe me 20. Here's 10 I owe you 10. Here's the 10 I owe you. Here's the 10 I owe you. Here's the 10 IU. Good. Now we're all even.
1:18:16
>> And speaking of money, how about the 25? >> Just keeps looping.
1:18:22
Uh >> uh somebody quoted this and said CPY says 25 years ago this was called roundt tripping and was considered illegal after investors suffered trillions in losses it will probably be considered illegal again.
1:18:34
So uh we will see it's kind of the wild west right now.
1:18:40
>> Well uh in uh nonI news for once we have Shane from Poly Market joining the show.
1:18:48
He's in the reream waiting room.
1:18:48
We'll bring him into this Ultradome.
1:18:50
Shane, how are you doing? >> Look at that setup. >> Fantastic.
1:18:55
>> Shane, can you hear us? >> I can hear you guys. I cannot see you guys. >> Okay. >> Okay.
1:19:00
Well, trust that we are looking at you and smiling at you and >> you look fantastic. >> You look fantastic. Today's about you.
1:19:09
>> Break down uh the news.
1:19:12
>> It's It's hard not to look fantastic with this backdrop. >> This backdrop. >> Yeah. >> Right there.
1:19:16
Um, I had to FaceTime all my family members be like, "Hey, look at that."
1:19:21
You know, now with uh with all the AI stuff, you gota you got to show that it's true.
1:19:26
>> You got to break through.
1:19:26
From the from the bathroom office in 2020 to the nice seat in 2025, anything is possible. >> What a run.
1:19:34
Take us through the deal today.
1:19:36
Take us through the news.
1:19:36
Uh what's the what are the key points in the announcement?
1:19:44
Yeah, I mean, look, it's um I've never been really like a deal guy or a guy that's very focused on um you know, I would say a lot of entrepreneurs, they're very optimizing around fundraising, etc.
1:19:55
I really just like building things.
1:19:57
And usually what I found is when you get traction and when you get motion and when people start taking notice of what you do, the money usually follows.
1:20:04
And uh in this case, there was a lot of interest from people who um wanted to invest and I'm very grateful and humbled by all of it.
1:20:11
Uh and then Jeff reached out to me and it was kind of like we got we got to talking.
1:20:18
He has he knows markets and and traditional finance better than anybody.
1:20:22
He runs his own company that he started solo founder like myself.
1:20:28
>> And there were all these ideas that we had that we could do together and we were very like-minded on it and he was a big fan of Poly Market.
1:20:33
So when when he started saying hey let's do something it uh there were a lot of synergies that came together quickly.
1:20:39
So it's very exciting >> and this is not a token strategic investment.
1:20:44
I mean this is very very meaningful.
1:20:48
I think I I correct me if I'm wrong but this is like the single this is the single largest investment in a in a in a cryp crypto company ever. >> Okay that one. Yeah.
1:21:03
>> Give us the actual numbers.
1:21:03
What's the structure of the deal?
1:21:05
Is this uh this is a strategic deal.
1:21:08
It's not like a Are you giving it a series number like a letter?
1:21:12
Like like how are you actually describing the deal?
1:21:13
I want to ring the gong for you. I want the numbers. >> Yeah.
1:21:19
Um they're investing $2 billion. >> Let's go. >> Hit that gong. There we go.
1:21:27
>> Oh, the gong's from your side.
1:21:27
I thought the gong was like a periodic uh New York Stock Exchange thing.
1:21:32
>> The gong is from our side.
1:21:32
We have everywhere studio.
1:21:35
>> Uh what what are what can you share about uh what the partnership will actually look like over the next 12 24 months and beyond?
1:21:45
Like what's most exciting about it to you?
1:21:48
>> I mean look, it's right now such a moment for prediction markets.
1:21:50
Um, it's been exciting for us to sort of be like, you know, sit there and even two years ago, it really was a category that people kept writing off and saying, "Oh, yeah, it's an idea that makes so much sense, but it's never going to work."
1:22:07
>> Um, we're really excited that we were able to buy QC and be set up to go to enter the US market.
1:22:12
I think, um, it's lining up perfectly. The stars are aligning.
1:22:16
The timings the timing is about as good as it could be.
1:22:17
Uh so on that side there's a lot in terms of data and in terms of distribution and and sort of who can have access to poly market particularly in the US but also globally uh because ICE has you know exchange assets all around the world.
1:22:30
Uh but also Jeff in particular as he mentioned on CBC earlier is like he's a big believer in tokenization.
1:22:38
He's a big believer in all assets are going to be tokenized.
1:22:42
It's a superior technology for the exchange of assets and Poly Market is the biggest consumer product that's built on on tokenization under the hood.
1:22:53
For every prediction market, it's actually tokenized.
1:22:54
There's a yes token and no token.
1:22:56
Um, so there's a lot of ideas we've kicked around there.
1:22:59
And I think ICE has incredible savvy and Jeff is incredible savvy about how you can do these things.
1:23:06
um utilizing existing assets and and understanding sort of the existing matrix of US regulation and then where there could be pockets that there may have to be collaboration between the regulators and the innovators um for how to basically do things that exist but in a more efficient way utilizing new technology.
1:23:27
So that's the thing that I'm definitely going to be leaning on him for.
1:23:29
That's not the thing that I'm uh that that you know I can't say that I'm the best at that like he is.
1:23:34
But in terms of the consumer side and building the products, uh, ICE doesn't have any consumer properties, right?
1:23:40
So that's where we come in and that's where I think him and I, we have this mutual understanding, common ground of how these products could work.
1:23:46
He's a very innovative guy, very forward thinking and um, you know, we can kind of see the vision in terms of polymarket.
1:23:52
com, how it can look there, and he can understand the the infrastructure and how to make it happen from the regulatory and infrastructure side.
1:24:00
Did you ever expect Prediction Markets to be in South Park to have an episode edit?
1:24:06
Was that on your bingo card for this year or did that was that still a surprise?
1:24:13
>> Yeah, I mean I love South Park.
1:24:13
Like I grew up a South Park kid.
1:24:15
I remember watching the the original movie.
1:24:17
I remember being a Best Buy and buying season 2, season 3 on VHS.
1:24:21
season 2, season 3 on VHS. Um, and look, I think that uh it's funny because the geopolitical markets on Poly Market have have proven to be extremely useful like in the WhatsApp groups from people in the Middle East and um people who are into open source intelligence oent they really watch Poly Market like a hawk and the sort of crux of the the episode being this idea of like uh you
1:24:48
know this sort of u will the mother in the Jewish family uh you know bomb Gaza like that kind of being it's this play on on those markets like it's it's definitely pushing it but it's also just so South Park and you know it's obviously all in good fun but the way that they interpreted the situation and distilled it into a South Park episode you know you wouldn't expect anything less from them. What
1:25:13
What about uh just uh the inter intercontinental exchange ICE uh founded in 2000 uh backed by Goldman Sachs, Morgan Stanley, Shell, Dutch, Deutsche Bank, uh Sock General, like it is the ultimate bridge to Wall Street.
1:25:30
How important are those connections?
1:25:32
Are you already plugged into all the Wall Street firms?
1:25:36
Is this a is this a a new a new pipeline for you to uh just Wall Street generally and uh professionalization?
1:25:45
Like how does that all play out for you? >> Absolutely.
1:25:49
Look, I've historically been more of a a cold email guy, so I don't think that would get me that far on this street.
1:25:56
Um, and yeah, you know, when I talk to Jeff and Co about this, like they know everyone and um, everyone's a text or an email or phone call away.
1:26:04
And that's really exciting because there's a lot of interest.
1:26:08
Every time I meet somebody who's um, you know, from the traditional world high up, they they love Poly Market. They love what we do.
1:26:15
They're obsessed with the data and they oftentimes track it.
1:26:17
And, you know, it's something Poly Market is something that they look at frequently.
1:26:21
And you know now one having the bridge but also having the credibility of of such a great partner uh it it's probably hard to underestimate how important that will be in terms of us bridging the gap especially as we render the US market and we open up for institutions. >> Fantastic. Anything else?
1:26:41
>> Well, absolutely iconic image today of you outside the exchange. Congratulations.
1:26:47
>> You know it's funny like we've had so many misconnections, right?
1:26:49
Like there were so many times we were going to hop on and I was going to be in a little booth or like a little chair in the back and >> I said, you know, one time if I'm going to go on Y, >> if I'm going to go on your guys pod, >> it's got to be special.
1:27:01
>> I got to figure out how to mo one way or another.
1:27:05
>> Well, Mog, you did Shane. So, here we are.
1:27:07
>> Thank you for everything that you do to make this show possible. >> I appreciate it.
1:27:10
I'm a huge fan of of of what you guys do and it's awesome to see right there that uh >> the Poly Market ticker. >> There it is.
1:27:18
You know, you guys are are real uh real champions, pioneers.
1:27:23
>> Thanks so much for having me. >> Have a great rest. >> Great to have you on.
1:27:25
Congratulations to you and the whole team.
1:27:27
>> We'll talk to you soon. >> Cheers.
1:27:31
>> Those cute are fantastic. >> Absolutely mogging.
1:27:34
Uh we have another uh post here.
1:27:38
Blake Robin said yesterday, "OpenAI is operating on a different level.
1:27:43
The amount they have shipped in the past few weeks and months is incredible." True.
1:27:46
Eric says, "Indeed impressive, but the scattershot nature raises questions about the company's discipline and ability to support these desperate uh desperate initiatives.
1:27:55
Is OpenAI a frontier research lab, a social network operator, a commerce engine, a hardware company?"
1:28:01
Because it's hard to do all of that.
1:28:03
Well, I would say they are a hyperscaler.
1:28:06
If you look at any of the hyperscalers, they have a frontier research lab.
1:28:12
They usually have a social network. usmerce.
1:28:17
They usually have a hardware division and it is hard to do all of them.
1:28:19
Well, I think that Sam is playing for keeps, right?
1:28:23
He's he's um you know, there's a lot of founders that wouldn't have launched Aora as a standalone app, right?
1:28:30
Uh there's a lot of founders that wouldn't acquire a company for $6.
1:28:35
5 billion that doesn't have a working product yet and just kind of an idea of what they want to build, right?
1:28:42
But he is incredibly aggressive.
1:28:45
He's uh fast becoming too big to fail.
1:28:48
And you know I think that put differently if you asked okay this company has 100 800 million weekly active users.
1:29:00
Do you think it's fair that they would get experiment with a social network?
1:29:01
get experiment with a social network? Do you think it's fair that uh so there's there's a lot of companies with far less scale that are doing this kind of range of activities but you have to uh my framework for OpenAI now is looking at them as as a you know as a hyperscaler
1:29:19
that's going to launch products all the time some of which will work some won't and that's totally okay they're just um they're experimenting they're shipping and they're taking big swings because at this point for them to take uh for them to create something that's meaningful to their business, it has to be a billion dollar opportunity. So So >> I agree.
1:29:41
I have a rebuttal, but first I'm going to tell you about linear.
1:29:44
Linear is a purpose-built tool for planning and build products.
1:29:46
Meet the system for my software development, streamline issues, projects, and product road maps.
1:29:51
Back in GPT3 launch 2020, I was playing around in the playground and I was writing video essays at the time about companies and I wanted to create a list of companies that I could potentially profile.
1:30:04
And so, uh, back in the day, there was no prompt. There was no RL. Uh, there was no RLHF.
1:30:08
And so, you had to, uh, as Rune told us, like the foundation models are complete hallucination.
1:30:15
And so, you had to write a prompt that would really set it up to just continue what you were saying because it was just guessing the next word and it was not very good at it.
1:30:24
word and it was not very good at it. Um, and what I did was I went to GPT3 in the playground and I typed out like uh some of the most interesting business stories in history and I put one Theronos, two Weiwork, three Lehman Brothers, four spa dot space and then it would continue to fill in based on your prompt that you had written and it's just trying to guess the next word and it actually did come up with some interesting companies
1:30:51
that weren't on my radar and I was able to go and Google them and and fact check them and understand those stories never really became part of my workflow, but I thought it was interesting and at the time I was thinking like this is a
1:31:04
search engine like it's just it's just something that I I would normally have gone to Google and searched for like top 10 most interesting companies and I would have gotten a listical but GPT3 just gave me the text itself. And so for
1:31:13
And so for a while my model for chatbt and and uh open AI has been like they're just the new Google.
1:31:22
And um and my and my my wondering is like how much of the culture of Google has, you know, as a natural outgrowth of just having a fast growing consumer, you know, web app.
1:31:35
Uh and if they're if they're if ChhatP is growing, then will they have a bunch of 20 20% time projects?
1:31:43
And so the social network operator, the commerce engine, the hardware company, like Google's tried a bunch of those.
1:31:48
They tried uh Google+, they tried Google Glass, those didn't work.
1:31:53
But uh YouTube's a great social network loosely.
1:31:55
And uh their Android phone ecosystem is a successful hardware bet.
1:32:01
Uh commerce engine certainly that's cooking at Google.
1:32:03
And so, um, I I do wonder how much you like like I agree the scattershot nature raises questions about the company's discipline, but we've seen it play out before where if you have an engine that's growing, growing, growing, you can actually go and do a bunch of 20 percentile projects.
1:32:21
Some of them hit, some of them don't.
1:32:23
>> Also, Sam Alman has never come out and said focus is our highest virtue and we're just going to work on chat GBT.
1:32:30
just going to work on chat GBT. It's like okay they're research they're you know an infra they're becoming an infrastructure player right they're going to experiment in all the different areas >> they have an API cloud business they do right I think I would be interested to see if they do
1:32:50
>> again like do they acquire someone like a Snapchat at some point does that does that happen >> yeah I I don't know if they'll do >> suggested >> at some point they have to do a bunch of acquisitions I would imagine they're already doing some of them didn't they buy Statsig uh and obviously other other companies as well. Um
1:33:05
Um >> they announced a acquisition of a company called Joy >> today >> the other day which was like a finance tool. >> Oh yeah. Yeah. Yeah.
1:33:13
So they're they're adding a bunch of stuff.
1:33:15
I mean other hyperscalers have done this in the past.
1:33:19
Um I I wonder you know obviously there's always a risk of being too scattered but uh it is a large company and it's also interesting to look at the time frame like a lot of people are viewing open AI as a company that started in 2023 essentially even though CHP launched in 2022 um they really feel like the open AAI story started in 2023 it did not the company did start in 2015 uh and it was a frontier research lab for now a decade.
1:33:50
And so if you look at the timeline for Google, well, Google search launches in 1998.
1:33:54
And then six years later in 2004, they're launching Gmail and that's a great product and it worked out.
1:34:01
And so should you give them credit for the time they were wandering in the wilderness as a nonprofit or should you comp them just to when they got product market fit on on Chat GPT?
1:34:09
um maybe something in between, but uh there's certainly a lineage of companies that find really strong internet product market fit, scaling, growing, and then doing other projects and not having those not getting over their skis.
1:34:24
A social network operator, what's the real cost if Sora blows up and it never goes anywhere and they light a bunch of GPUs on fire?
1:34:33
Well, if it fails, they won't be lighting that many GPUs on fire because nobody will be generating anything.
1:34:36
um if their hardware project goes south, like yeah, that's probably multi-billion dollar investment, but a company of their scale at $500 billion with billions coming in from all sorts of different deals can probably take that hit on the chin and keep keep moving and keep refocusing on the on the main on the main uh main project.
1:34:54
So, I don't know how how uh how big of a of a worry it is, but uh um they certainly don't seem to have been uh you know, massively falling behind in the core product.
1:35:09
We're not seeing uh you know huge churn or anything like that.
1:35:14
>> Um >> Doug from semi analysis says, "Open AAI is tweeting about real interest rates.
1:35:19
We get a new Fed chair that's whole job is to lower rates to as low as possible. OBB means no taxes.
1:35:23
Money becomes really cheap.
1:35:27
You got to invest in America at all costs. Wow, it's so clear.
1:35:32
>> Yeah, people are excited.
1:35:33
>> DJT certainly wants you to invest in America. >> Yeah.
1:35:36
Well, let me tell you about numeralhq. com. Sales tax on autopilot.
1:35:41
Spend less than five minutes per month on sales tax compliance.
1:35:42
Um Peter Wford uh has a forecast on how AI infrastructure spending goes over the next four years and what kind of models we'll see as a result.
1:35:51
Uh this is a very bullish take on AI infrastructure that I thought would be interesting to read through.
1:35:57
I continue to assess that we are on track for models that can replace a wide variety of human labor sometimes four to sometime four to 15 years from now.
1:36:06
>> A big gap right in that singularity uh calculator we have going.
1:36:10
He says uh currently the world does not have any operational 1 gawatt plus data centers.
1:36:17
However, it is very likely that we will see a fully operational 1 gawatt data center before mid 2026.
1:36:24
This will this likely will be a part of a 45 to 60 gawatt of total compute across meta, Microsoft, Amazon, AWS, Anthropic, OpenAI and Oracle, Google and DeepMind and XAI.
1:36:34
So, everyone's building huge clusters.
1:36:37
They're all investing a ton in capex and it will net out to something between 45 and 60 gigawatts next year.
1:36:44
uh his median expectation is that these largest 1 gigawatt data center facilities will hold uh between 400 and 500,000 Nvidia Blackwell chips and be used to train 4 to the 27th uh flops or 4 E27 so 4* 10 to the 27th flop model sometime before the end of 2027.
1:37:04
Such a model would be 10x larger than the largest model today and 100x larger than GPT4.
1:37:12
uh each individual 1 gawatt facility would cost 40 billion to manufacture with 350 billion total industry spend across 2026.
1:37:19
Now the big question is how confident are we are are we on scaling up those models.
1:37:25
There's a wide range of takes around um how easy it is.
1:37:27
Clearly we saw with GBT 4.
1:37:30
5 and uh Llama Behemoth that um just scaling up you have to be very careful about what you're scaling up the actual underlining design of the model matters a lot.
1:37:40
Um by the end of 2027 he expects a fully operational 2 gawatt facility with total AI compute across all companies raising reaching 90 gawatts.
1:37:49
Uh that'll be a lot of inference.
1:37:52
These two gigawatt facilities would cost 95 to hundred billion dollars each and total industry spend would reach 500 to 600 billion by the end of 2028.
1:38:03
>> I expect the large the largest single facility to be a 3 gawatt facility holding 1 million NVIDIA Blackwells Reuben mix >> three nuclear reactors >> something like that. Yeah.
1:38:13
uh costing 150 to$165 billion dollars to build capable of a 128 flop training run.
1:38:23
A one a onee 28 flop training run represents a computational effort thousands of times greater than what was used to create GPT4 allowing the AI to process and learn from vastly more information.
1:38:34
Total AI data centers would reach 130 gawatts combined with 900 billion to a trillion spent by the AI industry over 2028. That is a lot.
1:38:45
But that matches up what everyone's saying.
1:38:46
Everyone's marshalling the capital.
1:38:48
Everyone's planning to do this. >> Yeah.
1:38:50
I think we we want to look to Meta's earnings next earnings call October 29th. Yep.
1:38:56
>> Zach is going to feel pressure to say the biggest number. >> Yep.
1:39:00
>> And uh we should probably we should probably stream that live. Do a a companion stream. It'll >> be fine.
1:39:06
Um I'm I'm look I mean I just think that's going to be a big indicator of do they push all the chips in >> literally. >> Yeah.
1:39:15
>> Uh by 2029 it starts to get very fuzzy to predict and his forecasting powers break down.
1:39:19
How AI continues to scale whether we've encountered data related or other algorithmic bottlenecks.
1:39:23
What AI capabilities have already emerged and how economically valuable those AI capabilities are will be key to whether the economics favor continued scaling.
1:39:34
Needless to say, building $150 billion individual data center campuses and spending a trillion on AI infrastructure would get very difficult to sustain financially, let alone to increase dramatically year-over-year.
1:39:45
I feel like the trillion dollar cluster is within reach.
1:39:50
I mean, it it needs to be probably distributed across all the different companies, but these numbers don't they're not as scary as I think when you think about like across the >> hyperscaling doesn't scare you.
1:39:59
No, because the across across the hyperscalers you have almost 20 trillion of market cap, maybe 10 trillion of market cap.
1:40:08
And so you're looking at Okay, so they need to move 10% of their market cap into this project.
1:40:17
That's not 50% of their market cap.
1:40:17
Can they liquidate 10% of their market cap and and put it towards this?
1:40:24
>> It's at current prices and they would have to lever up. >> Yeah. >> Significantly.
1:40:29
>> No, not significantly. 10%.
1:40:29
like they would need to take 10% of their of their equity of their >> I know but but if you have a massive correction between now and then it starts to be starts to be quite a bit more than 10%. >> Sure.
1:40:43
But I mean a trillion dollars spread across the Mac 7 isn't it isn't actually that much.
1:40:47
I mean Nvidia is a $4 trillion company.
1:40:52
They're they're all they're all a trillion dollars, right?
1:40:53
So I mean it it I I I agree with his conclusion. 2029 it gets crazy.
1:40:59
gets crazy. And then the real question is like okay what about the $5 trillion training run or the $10 trillion training run but uh the just purely like like is the money there like the money feels there the the less clear thing um to me is this question of how AI
1:41:14
continues to scale whether we will en encounter data related or other algorithmic bottlenecks and and then the question of thousand times more money are you actually getting a thousand but when you look at this it's like it's it more likely that it'll be an energy bottleneck, right? >> Yeah. Yeah, that's another good one is >> Yeah.
1:41:31
Yeah, that's another good one is just going to get you three nuclear reactors worth of energy in one year in two years from now. >> Yeah.
1:41:37
When it takes us 30 years to build them.
1:41:39
>> So, yeah, there's a big big question there.
1:41:42
>> We got to check in with the nuclear bros >> because a lot of Wasn't Wasn't it the last time we had >> Isaiah?
1:41:48
Uh he he he was saying he was going to have the first reactor in like 12 months or something like that.
1:41:54
>> Yeah, he's working on it.
1:41:54
So, >> uh, I mean, a lot of the he he was going kind of midscale, I think 10 megawws.
1:42:00
And so, if you're like you're talking about him not just making the first one, but then making 10,000 of those, which is a lot uh to to generate this much electricity.
1:42:11
Um, we did talk to the nuclear company at Palanteer Dev Day and he was saying that he's much more encouraged by uh bringing you know nuclear like like the the original like GE plants online the one gigawatt like the large scale nuclear reactors. >> Yeah.
1:42:28
And Doug's point is like energy when when when a premium is placed uh uh when there's more demand there's more capital chasing energy energy will come out of the woodwork. Yeah.
1:42:38
>> Um, so there's >> um, uh, Gabe in the chat says Buffett is good for 400 billion.
1:42:43
Uh, he >> he does have a lot of cash right now, right?
1:42:46
>> He has I think like 350ish billion of cash on hand. >> Can you imagine?
1:42:50
He just gets super AGI pills.
1:42:52
>> Sam if Sam does a deal.
1:42:55
>> If Sam if Sam can do a deal with Buffett, I mean >> I mean is is the final boss. It's the final boss.
1:43:03
There's no one bigger that he hasn't been able to do a deal with.
1:43:05
I mean, he even did a deal with with Elon back in the day.
1:43:09
You know, he's done deals with every single person at various times pretty much. >> Yeah.
1:43:15
>> What if Buffett ends up owning all the data centers because they just get super levered up and just go bankrupt. Buys them for pennies.
1:43:22
>> I because I mean he loves rail. He loves infrastructure. >> I become compute. >> Yeah.
1:43:29
>> Birkshshire just becomes the next hyperscaler.
1:43:31
It would be so insane if Buffett's vindicated and just like his model holds forever.
1:43:39
>> I mean, it's pretty much Lindy.
1:43:39
It's held for his whole career.
1:43:41
It's pretty Lindy at this point. >> Can you imagine?
1:43:44
He just winds up owning every power plant in America. >> It's so crazy.
1:43:50
So, >> Birkshshire is up 2% over the past uh 6 months. >> Let's go. >> So, uh 2. 2% to be clear.
1:43:56
Hit that gong from Buffet. Congratulations. 2% gain. Sent on a lot of cash. >> Lot of cash.
1:44:07
They're the the market cap is just just basically three times their cash on hand. >> Wow.
1:44:14
>> Three times their cash on hands.
1:44:14
Uh in other news, >> Elon names Anthony Armstrong as a new XAI CFO. >> Strong name.
1:44:25
>> Armstrong strong arms the financial markets. That's right.
1:44:27
during complicated fund raise at XAI.
1:44:29
The uh New York Post headlines write themselves.
1:44:33
Let me tell you about not XAI but Finn.
1:44:35
AI, the number one AI for customer service, number one in performance benchion, >> number one in competitive bake offs, number one ranking on G2.
1:44:44
>> Um chat, Mark in the chat is asking about TBPN merch.
1:44:47
Uh we this first merch run we did, we we didn't sell, we just gave it away uh somewhat randomly. Uh we're making more.
1:44:56
uh we actually have a design meeting uh right after the show today to get into it.
1:45:00
So it is coming this next time we will make it available for the world and uh the chat will get first access to it.
1:45:09
So >> um >> yeah, we'll drop it right at the end of an episode.
1:45:13
>> I got to stop wearing it so that >> I know you're teasing everyone. >> Stop teasing.
1:45:17
>> Got to throw on the suit.
1:45:17
Uh, David Holes, the founder of MidJourney says, "My previous startup, Leap Motion, made the best hand tracking to this day and an amazing open-source AR headset, Northstar.
1:45:28
Now the tech is getting deployed by Globus Surgical Surgical."
1:45:34
>> I work for Globus Corp. >> Globus. >> Oh, what?
1:45:37
Oh, I work for the Globus Mega Corp.
1:45:42
>> I work for the Globus Center of International Business. Globus is a great name. >> So good.
1:45:50
It's like, well, we do business on the around the globe and in the United States. Globe, US. Globus. >> Globus. >> Globus. >> Globus.
1:45:58
>> We got to get the CEO of Globus on.
1:45:58
This sounds like a great company.
1:46:00
Uh, they are deploying these AR headsets to surgical theaters around the world.
1:46:07
>> Globus is$8 billion company.
1:46:07
Undervalued just on the value of the trademark alone. Globus. >> Great. Very good.
1:46:16
>> Let's hear for Glovis.
1:46:19
We're huge Globus fans here.
1:46:19
This is a very cool tech.
1:46:21
It makes a ton of sense in a uh medical setting.
1:46:22
Obviously, you're not wearing the headset for fun all day.
1:46:27
It's a professional environment.
1:46:28
There's always been uh enterprise applications here.
1:46:30
And uh of course, if it's a medical device uh and it's adding a ton of value to a high paid doctor's routine, you can probably put the best most cutting edge technology in there.
1:46:41
If it's 10K, it's probably cheaper than the, you know, the chair that you sit on in a medical setting.
1:46:47
So, uh, congrats to David Holes for being on an absolute run.
1:46:49
The, uh, the Leap Motion story is fascinating.
1:46:53
I dug into it a little bit.
1:46:55
It seemed like they were about to sell the company to Apple and then Apple had printed like welcome letters to everyone on the Leap Motion team and then something happened.
1:47:06
The deal fell through at the last minute.
1:47:08
Uh, David was like, you know, in and out.
1:47:11
had a really rough run with venture capitalist, then went back to midjourney, didn't raise the dime. You love to see it.
1:47:16
Bootstrap founder um and him and uh him and Mark Andrees were going back and forth.
1:47:21
Did you see that yesterday? >> No, I missed it.
1:47:24
>> So, uh David Holes posted something to the effect of like, hey, uh any other bootstrap founders in SF?
1:47:28
And it's like to call Midjourney a bootstrap company.
1:47:33
And it is a bootstrap company.
1:47:33
They haven't raised venture, but it's like the biggest company ever. >> Mark, oh, I did. And Mark's like me.
1:47:37
I I bootstrapped A16Z like I own >> hundreds of millions revenue. Love to see it. >> Yeah.
1:47:46
>> Uh I didn't see this yesterday either, but US is taking a 10% stake in Trilogy Metals.
1:47:53
Haven't heard of this company.
1:47:55
>> It was a $480 million Canadian dollar uh market cap company. >> Okay.
1:48:01
>> Uh yesterday it is now 1.
1:48:01
63 billion >> Canadian dollars metal. So that's exciting. How many?
1:48:08
I don't know what the exchange rate's probably pretty rough. >> I have no idea.
1:48:13
>> Well, let me tell you about Adio.
1:48:14
Customer relationship magic.
1:48:14
Adio is the AI native CRM that builds, scales, and grows your company to the next level. >> Next level CRM.
1:48:22
>> Um Tim Cook is likely to step down as Apple's CEO.
1:48:24
According to Bloomberg, John Turnis, who I'm dying to have on the show. Got to make it happen.
1:48:29
Uh get to him before he becomes CEO potentially.
1:48:33
uh Apple's senior vice president of hardware engineering is expected to take over.
1:48:37
Interesting because you don't see him in all the keynotes.
1:48:41
He's not the biggest face, but he's clearly doing something right at Apple.
1:48:45
And you know, for all the discussion over do they get AI right or whatever, like the hardware is good.
1:48:51
>> Nominative determinism turn us turn us around. >> Turn us around.
1:48:56
Okay, I see what you're doing there. Yeah, like it.
1:48:58
Bloomberg notes that Apple will now likely >> Johnny Apple Seed >> Tim Cooked. We know this Tim Cooked.
1:49:08
>> I saw a graphic of like all the different products that that Tim Cook has like s you know o overseen y >> and it's actually remarkable.
1:49:17
I think he will be uh while he certainly isn't being celebrated in the AI era he will be celebrated in the fullness of time. Yeah, there's two.
1:49:30
>> And while I think he's dramatically underpaid, >> Yeah.
1:49:33
>> Um I hope that the history books will remember his name for just uh exceptional execution on >> um >> Steve's vision that was Steve's Steve's visible vision. Totally. Totally. So >> yeah.
1:49:50
Uh well, whatever your view on Apple, whether you're long or short, get on public. com.
1:49:54
investing for those that take it seriously.
1:49:56
They got multiasset investing, industry leading yields, they're trusted by millions.
1:49:58
I have some >> They just launched uh direct indexing which is very cool uh specifically because it allows you to, you know, if you have outperformance with one stock, underperformance with another, you can actually recognize those losses. >> Oh, interesting.
1:50:16
>> And so it can be more tax efficient way to get exposure to >> to a broad swath of companies. Interesting. In one go. Cool.
1:50:22
Um, I have a bit of cognitive dissonance about Apple.
1:50:26
On the one hand, apparently they have this like belief or something that uh that Bloomberg was reporting that they don't believe like chat bots are going to be a dominant form factor.
1:50:34
Like they've really leaned it back in terms of chat bots.
1:50:38
Siri has kind of been slow.
1:50:41
I've been trying to use Apple intelligence to query chat GBT and it's still like it's I have to click a button every time.
1:50:47
It's very like it doesn't seem like they're really moving quickly and it's been like years now since ChachiPT has come out and I would have liked a deeper integration on day one.
1:50:58
They could have bought something.
1:50:58
They could have trained their own model.
1:50:59
Like there are so many companies that have been able to catch up.
1:51:03
It doesn't feel like it's complete rocket science.
1:51:05
the narrative of like the foundation model commoditizing uh even even if they have something that's not at GPT5 or claude 4.
1:51:16
5 sonnet or even Gemini 2.
1:51:16
5 level like I it would still be better and it would improve my experience but they've really leaned leaned back on that.
1:51:23
So uh so that's like a really really clear like bare case for like they're not winning AI.
1:51:29
And then at the same time whenever we talk about hardware and the next the next devices we just keep coming back to well not only is the hardware extremely good and sticky and you know just like the best devices and the best supply chain and Tim Cook's done a fantastic job of man managing the the tariff battles and whatnot.
1:51:50
But they also have iMessage which feels like an incredibly powerful social network that is very very hard to rip people out of >> social graph. >> Social graph.
1:51:59
And so when we when we demo yesterday somebody was posting yesterday Apple better start moving faster and it was in reference to chat GPT's like booking. com integrations. >> Yeah.
1:52:12
And it was fairly, you know, it was getting quite a lot of engagement, but I was surprised by that considering that Apple's never been able to really directly tax like retail, right?
1:52:21
That's they don't they don't get a percentage of every spend on Meta.
1:52:29
>> Well, they do take a cut of Booking.
1:52:29
com in the sense that booking pays Google, Google pays Apple, right? >> Yeah.
1:52:34
But it's way less that that revenue is not necessarily directly threatened because if Google has more >> Yeah.
1:52:42
>> You know, they're they're happy to keep paying the their version of the Apple tax.
1:52:46
But again, it's it's not like >> Apple is getting billions of dollars a year from Amazon and they're they're they would suddenly not be getting that if Chat GBT starts dominating in retail, right? >> Yeah. Yeah.
1:52:59
Maybe maybe what the move internally or the mood internally is uh at Apple is something like they don't see AI or LLMs or chatbots as disruptive to Apple's hardware plans.
1:53:11
They think that even in a post AGI world, people will still be carrying iPhones.
1:53:16
And so they can just sit and wait until they get some foundation lab to come to them and say, "We're going to pay you10 billion dollars a year to be the default."
1:53:26
and they're just like, "Yeah, we'll just wait and you you can come to us today, but we're not we're not doing the deal until" and so like it's it's going to be uncomfortable for customers until someone ponies up. >> Yeah.
1:53:41
It still feels hard for me to imagine a world where Siri is just replaced by another brand like what Siri does functionally in terms of being an assistant layer on top of the hardware device.
1:53:54
It feels would it feels very unbelievable to me that Apple would say like we're going to let this other assistant directly integrate throughout the entire device.
1:54:05
Like that feels like a big step.
1:54:05
It does >> because the phone in many ways already was operating as like an assistant, right?
1:54:10
It's like the center of your world.
1:54:13
It can do >> it can do anything you want to do in your digital life on your behalf.
1:54:17
It's sort of um and so giving up that uh giving that up feels major.
1:54:22
Um but yeah, I think we have to see more announcements out of Apple this year on this front.
1:54:31
I know based on the last uh they still have longer time horizons internally around their like AI turnaround, right?
1:54:38
They're not saying we're fixing this this year. Yeah.
1:54:42
>> It's very much >> like we're we're fixing this over the next 24 months, right?
1:54:48
Um, and again, I I still stand by Apple and and believe that the competitive threats um, OpenAI just doesn't feel like a legitimate hardware threat today. >> No, not at all.
1:55:02
Uh, because of the lock in around the Apple ecosystem.
1:55:04
And it does feel like Apple might be looking at AI more as a profit pool.
1:55:09
And once that profit pool gets really big, then they're going to want to go after it.
1:55:16
and they have they will have a ton of leverage at that moment and so they'll be fine.
1:55:19
But um just chat interactions are not generating tens of billions of dollars in profit yet.
1:55:27
And so but Google search is and so Apple says hey we got to go get a cut of Google search.
1:55:32
They did and they've been very successful there.
1:55:35
uh once the profit pool of chat interfaces becomes really big, Apple will probably say, "Hey, we got to get a cut of that."
1:55:42
And maybe at that point we will invest, but we understand the the economics and we're not supply constrained on data centers and so we don't have to pay a high margin.
1:55:49
We can do Apple silicon chips for you know our inference or something or our own custom model.
1:55:55
there's a million different ways that they can uh that they can like get their fairish share of that market when the time is right because they will still have the leverage and they don't see that their leverage is decreasing because people are not churning from iPhones uh based on the lack of chat integration or the lack of LLM integration.
1:56:15
Even though it's like a pretty crazy feature to be missing in 2025, it just still hasn't really hurt them. I bought a new iPhone. I didn't sweat.
1:56:23
I'm still waiting for my iPhone that I order.
1:56:25
I'm waiting for my iPhone that I ordered weeks before John just walked into a store and bought an iPhone off the shelf. >> Skill issue. Skill issue.
1:56:34
>> Unbeliev Unbelievable.
1:56:35
>> The iPhone was delivered to >> here.
1:56:37
Here I am thinking like, wow, there is so much demand for Apple, the new iPhone that that they can't deliver me at one.
1:56:45
I mean, to be clear, like there was only one in stock that I was able to purchase and uh it just happened to be a model that I was happy with, but uh I didn't get to pick a color or anything like that.
1:56:55
Um I was just like, "Yeah, just give me what you have."
1:56:59
Uh anyway, speaking of iPhone apps, open up your eight sleep app and tell me how you slept last night because you had a tummy ache from lack of alcohol consumption.
1:57:10
I was boozing it up with the white wine at the luxurious event and I slept for seven hours and got an 84. I did pretty well.
1:57:21
>> I slept for 5 hours 5 hours 56. >> 5 hours. Wow. >> Oh, 56 minutes.
1:57:27
Okay, that's close to six hours. Yeah.
1:57:29
>> And my eight sleeve is very concerned about my health. >> Oh no.
1:57:34
>> Well, did you get over I got a I got a 75.
1:57:37
>> And you know what you got to do, Jordan?
1:57:38
>> I know what I got to do. >> Let's go. Oh, I win.
1:57:41
>> Credit where credit's due. >> I've been on the run.
1:57:42
I've been doing very well recently.
1:57:43
Uh, and anyway, uh, Mick Franchisee shares, I remember this happy meal promo back in 1991 for Earth Day.
1:57:52
Uh, you could ask for a free tree at McDonald's, no purchase necessary, and they would give you a sapling, I guess. Uh, pretty cool to see.
1:58:02
Apparently, some of these Mick trees over three days later, 30 years later, have uh have grown into behemoths.
1:58:07
Uh, and so after 50 years, this man's family is moving out of his childhood home.
1:58:12
In the '9s, McDonald's gave out pine seedlings for Earths. And look at this tree. It's now 30 years old. What a beautiful tree.
1:58:21
>> My happiest childhood memory. >> Yeah. >> With McDonald's.
1:58:26
>> They had a deal with Sugar Bowl that if you bought anything at McDonald's and you brought the receipt to Sugar Bowl, you could get a $5 lift ticket. >> Okay.
1:58:35
>> And I was doing that all day.
1:58:35
I mean, that was like the greatest trade of all time.
1:58:38
You get a m you get like a McFlurry thing and then you get a $5 lift ticket.
1:58:42
>> You used to be able to take a cola and go to uh you used to be able to take a Coca-Cola can and go to Six Flags for cheap.
1:58:49
There were a bunch of these like cross promotional uh like deals that were going on.
1:58:53
Um I think this is a great merch idea.
1:58:56
I think some startups should do this.
1:58:58
If you're super not AGI pled, give away a tree sapling and be like, "Yeah, this tree is still going to be around.
1:59:04
It's not going to get paperclipipped. I'm long humanity." Keep thinking, folks.
1:59:08
Um, this also reminds me of our idea for merch, the bonsai tree.
1:59:12
I really like the idea of sending everyone a bonsai tree to remind them that progress is measured in decades and you should never stop working. Keep grinding.
1:59:21
Um, anyway, uh, what else is going on? Uh, did we recover this?
1:59:28
>> This is this is, uh, something that's probably worth mentioning.
1:59:30
Jay B says, "Here's the thing with today's OpenAI pump.
1:59:34
Elon is uh b u t h u r t. He hates Sam.
1:59:40
Sam is getting all the attention these days and nobody cares about Elon anymore.
1:59:43
I fully expect the mother of all pumps from Elon sooner than later because he's a narcissist and no way he doesn't do it.
1:59:50
>> What a funny way to frame like what happens in the capital markets like like oh yeah like like they're going to do a pump because they're spite or something. It's like >> spite pump. >> Spite pump.
2:00:01
What what about just like building something that delivers value >> and Tesla's at an all-time high right now.
2:00:08
>> I mean, the Roadster the Roadster video dropped yesterday over the weekend.
2:00:10
It looks I'm 100% going to get one. I'm so excited.
2:00:15
A roadster me having the the aesthetics of a super car but having like great self-driving is that's a recipe for a hit.
2:00:25
>> Wait, we have the perfect guest to talk about the Tesla Roadster.
2:00:26
We have uh the is it the CEO of Dupont Registry joining us?
2:00:32
>> Uh corrected uh Tesla's not at an all-time high peaked last year. Uh but getting close. Getting close.
2:00:38
>> Well, we have our next guest in the re room waiting room. We'll bring him in.
2:00:41
>> Absolutely pumped for this. >> Oh, look at this. >> What's happening? >> Fantastic background.
2:00:45
>> Great uh great setup for having me. >> How you doing?
2:00:49
>> We couldn't have said yes faster to having you on the show.
2:00:52
I think I'm I'm I'm a I'm a daily active user.
2:00:53
100% registry >> of the products and uh yeah, super excited to to get the update from you.
2:01:03
>> Thank you for having me guys.
2:01:04
>> Yes, please uh kick us off with an introduction on yourself and actually describe the company for anyone who might not know. >> Yeah, sure.
2:01:11
So, uh I'm I joined the company two years ago as you will uh you will hear from my accent.
2:01:15
I'm not from Paris, Texas.
2:01:17
I was born and raised in France.
2:01:19
I came to the US 16 years ago.
2:01:22
started my career with in the luxury and tech world with uh Louis Vuitton uh and moved two years ago to uh to lead registry group.
2:01:32
Um we're going through a major transformation.
2:01:34
We're disrupting the luxury automotive industry.
2:01:38
>> Uh the group has been building for the past 40 years amazing trust uh towards the audience of you know car enthusiasts and car collectors.
2:01:47
Today we're the only one place where any car collector can find the product of their passion.
2:01:52
Um, and we're transforming the industry.
2:01:56
We're building a brand new tech platform to have a for ecosystem of dealership and clients a way for them to transact online.
2:02:04
Uh, we're very excited about it.
2:02:06
The market opportunity is huge.
2:02:06
Um, and the group is uh is moving in the right direction.
2:02:12
What uh what's the shape of the business now and then how much do you want to move to online platforms?
2:02:16
Uh is is >> I want oneclick checkout. >> Yeah.
2:02:21
Like like how far does this go?
2:02:25
>> I want one click check out too and this is what we are working towards. Great.
2:02:29
>> So the group has been the foundation of the group is again 40 years of legacy and trust.
2:02:33
Uh we have today amazing brand within our portfolio uh events that are gathering all the enthusiasts and car collectors some of them the uh the most uh affluent car collectors in the world.
2:02:47
Uh and we want to use that foundation and the data that we've been accumulated for years to uh to build really an omni channel tech platform that will allow anyone uh when they see a product and a car that they want to be able to purchase it online and get delivered at their home.
2:03:02
uh this is what we're building on right now.
2:03:04
Uh and the recent investors that we announced today uh that brings capital to uh to the company uh we're going to use that capital to build that tech platform.
2:03:13
So expect a lot of new uh changes in the in the next few years.
2:03:21
>> Um what uh any you know what is what I kind of you mentioned events more seamless transactions that all makes sense.
2:03:30
Are you guys planning anything on the auction side or you feel like that is well served by the industry today? >> No, no, no.
2:03:38
It's uh it's definitely something we have in mind.
2:03:40
Uh it's part also of our uh where where I came from in the luxury world, it's it's all about the omni channel and being being taking care of our clients wherever they want to buy and whenever they want to buy.
2:03:51
Uh so if you look today in the car space, the uh the auction piece is quite important.
2:03:58
Um and we are launching in a in a few weeks uh uh our own Dupon Registry live auction platform uh that will support uh our audience and and allow us and our dealers to sell their cars.
2:04:11
It's going to be a disruptive one.
2:04:13
You will see a couple of announcements are coming in the next few weeks.
2:04:17
>> How do you think about defining uh the like the the the tone the vibe around what type of cars make it onto the platform?
2:04:26
It feels like uh you know a dollar is a dollar.
2:04:29
You could you could have every car on there, but you have to define the the brand somehow.
2:04:33
So, how do you think about what is an appropriate car to work with?
2:04:38
And and how do you uh how do you let someone down if they bring something that's just not quite there, a little bit too not special enough?
2:04:48
>> To me, we don't let anyone down because at the core of our audience is there is passion.
2:04:53
Uh so whether you're you're talking about uh and we had we had someone the other day from Eastern Europe that rebuilt the Dacia from his father.
2:05:03
>> There was a strong passion about that Dacia and we actually talked about it and with Petrolicious one of our brand we we we did a movie about this this guy.
2:05:11
Uh so to me it's it's it's all about that passion component.
2:05:13
Of course for the past 40 years we've been the leading marketplace and our positioning is luxury and highend luxury and we want to continue to go there.
2:05:21
Uh but my job is not to say no to my clients.
2:05:24
It's to be able to welcome them in our ecosystem and serve them and make sure that they evolve with us throughout their their collector's journey.
2:05:33
>> Give us uh a highle view of the current state of the automotive industry.
2:05:36
We obviously are we're car enthusiasts ourselves but uh cover uh tech about a thousand times more closely than the automotive world.
2:05:45
But seems like we're at a very interesting time right now.
2:05:49
You have pressure from on on the Chinese market.
2:05:51
You have trade wars, you have forth on electrification.
2:05:56
>> Yeah, electri electrification that uh enthusiasts have certainly uh not, you know, overall not not been huge fans of.
2:06:06
You've also seen, you know, the massive depreciation on that front.
2:06:08
If you're an automotive enthusiast, nobody wants to buy a car that uh that might look pretty and drive well, but if it's going to depreciate 40% in the first year, it's just not you're never going to really get that uh enthusiast love.
2:06:20
So, I'm curious, what kind of trends are you tracking most closely and and uh kind of um uh new activity over the next 12 months?
2:06:32
>> Yeah, it's very good question.
2:06:32
So, all you mentioned does not really affect us today.
2:06:36
We're in the used cars luxury space and uh and and we're in the business of our clients are looking for something they want, not something they need.
2:06:45
So from a from a pure purchase funnel standpoint, they're not really affected today by tariffs and uh and otherwise.
2:06:53
>> Um you will see in the next few weeks we're partnering with Boston Consulting Group and we're going to release a luxury car market report. >> Oh, cool.
2:07:01
>> We've seen first few thing in that in that report.
2:07:03
We're talking about hundred billion dollar market.
2:07:05
So it's going to be a uh it's quite interesting.
2:07:07
There is a huge market opportunity not at all digital today.
2:07:12
Uh what's interesting too is that we see that electrification is not there.
2:07:17
>> Uh there is nothing in if you're looking at the luxury car market.
2:07:20
People are looking for performance. They're looking for fun.
2:07:23
They're not looking at their daily drivers.
2:07:25
So they will look more for that car behind me. Yeah.
2:07:29
>> A 2001 Ferrari 550 Marinelo >> than an electric car. >> Yeah. >> Yeah.
2:07:35
The other the other thing I think is worth calling out part of your guys's opportunities uh is like I have bought I've purchased a number of cars site unseen online and maybe that's just because I was born in the you know I was born in 1995.
2:07:50
I grew up purchasing everything on the internet.
2:07:53
I have no problem seeing a video of a car.
2:07:55
I might get a remote PPI done on it to have that confidence.
2:08:00
But I continuously am happy to purchase cars out of state, you know, wherever.
2:08:05
I don't need to see them.
2:08:05
Um, I've done that, I think, at least three or four times at this point, and I expect to do that many more times in my life.
2:08:13
Do you think that that is part of your guys' opportunity and that the the new generation of of car owners and enthusiasts are just willing again, it doesn't matter if the car if the spec you want is out of state, great.
2:08:24
I have no, you know, no problem kind of purchasing.
2:08:28
>> Yeah, it's actually very interesting.
2:08:30
Today we see that about 99% of the purchase decision starts online.
2:08:33
Uh it takes couple of months for anyone to decide which cars they want to buy and there is a lot of online research yet less than 1% of those transactions are happening online.
2:08:46
>> Uh so there is there is a lot of potential to disrupt the market and disrupt the industry.
2:08:49
Uh when you're talking about buying a car site unseen uh and this is the power of our brand and our ecosystem.
2:08:56
We have the trust from millions of people that have been, you know, looking at our brand and coming to our brand for the past 40 years and they trust the brand to show them the right product with the right condition and be transparent about the product.
2:09:09
And this is what we're offering at the national audience for the US.
2:09:13
You'll be able to buy a car from uh California, get it delivered in New York uh and behind the scene, we will be the intermediate to facilitate that transaction and make sure that you trust the seller and the buyer and trust both parties.
2:09:25
How do you think about the the next generation getting into cars?
2:09:31
What's different about Gen Z or millennial car collectors?
2:09:33
Uh, are are they going as are they going less far back into historical or retro cars or or does every generation just love the car that they had on the poster in their bedroom forever and you're kind of locked in a time capsule?
2:09:53
Or or is there something unique and different about the millennial generation or the Gen Z generation as opposed to the Gen Xers or the boomers?
2:10:05
I think there is there is something unique is that they're discovering the they're discovering the luxury car market through experiences and and and community.
2:10:12
And that's what we're doing at the group.
2:10:14
We're organizing many events every year uh to build that community to continue fostering the dream within the community.
2:10:20
Uh from a purchase standpoint, as any as any other car enthusiast, you will start with the car that was that you had as a poster in your in your bedroom when you were 14.
2:10:34
uh and that will be your first car, but then you're going to evolve throughout your collection.
2:10:37
The good thing is that today we're seeing a transfer of wealth between generation.
2:10:40
The passion is also transferring.
2:10:42
So, we're actually seeing that our audience is getting younger. >> Yeah.
2:10:46
>> And definitely to your point, the audience is ready and they they're used to buy those products online and luxury products online and this is where we're going to offer them that ability.
2:10:56
>> How are you thinking about marketing and content production?
2:10:58
Uh I engage with DuPont registry on Axe actually.
2:11:01
I see every new auction and there's a lot of facts and interesting details in there.
2:11:08
It's very interesting to me.
2:11:08
Um but there's so much that you can do with cars when you're marketing a platform because the cars themselves are interesting.
2:11:15
Like that car behind you, I could watch a 20-minute video about it. Uh it's fascinating.
2:11:19
I probably have uh by other creators.
2:11:21
Have you how are you thinking about partnering with creators uh either sponsoring content or bringing people inhouse agencies like how do you think about the correct shape for just raising the awareness of DuPont?
2:11:37
>> It's it's it's all about stories to me.
2:11:39
Uh we need to tell stories between a driver and his cars.
2:11:42
That's what we're doing with one of our brand Petrolicious.
2:11:44
Every Friday we have a new movie about a car story. >> Cool.
2:11:48
>> Uh this is what we want to do.
2:11:48
We want to make sure that we we tell the story of the enthusiast community.
2:11:52
We tell the story of the car collectors and how they build their collection from the first purchase until uh until their their latest investment.
2:12:01
Uh and this is really how we're today how we're targeting our content strategy is really focusing on that. >> Very cool. Jordan, anything else? >> Amazing.
2:12:10
Uh we'll we'll send you some posts after this, but we've featured DuPont thousands of times.
2:12:16
thousands of times in our in our early episodes.
2:12:18
It was a a core part of the content.
2:12:22
>> Please like never stop posting on X.
2:12:22
It is the best little drip feed.
2:12:24
It just it just sprinkles itself in with all the other tech news and I see it and I love it and I usually tag a friend and I say you should get this car. >> Well, yeah.
2:12:33
I can't I'm very excited you guys have again, you know, it's just a daily active user.
2:12:37
I'm very happy that you guys will have more Yeah.
2:12:39
you know, investment and and uh let us know if we can help you recruit anybody in on on the technical side.
2:12:47
>> Uh I'm sure >> the terms of the deal, how much was raised, anything like that?
2:12:50
Do you have any numbers to share for us?
2:12:54
>> No, unfortunately, we we don't disclose financial numbers.
2:12:56
What I can tell you is Francois is a is one of the top collectors in the world as well as a very well-known race car drivers.
2:13:03
Uh he brings a lot of validation of our strategy.
2:13:09
He's a big uh he's a big tech guy and he loves tech as well.
2:13:12
Uh he he sees what what we are building from a tech and AI standpoint with the data we have.
2:13:18
Uh and we're very happy that that he's on board with this.
2:13:23
>> But one number you guys reached unicorn status. That's correct, right? >> Yes. >> Yes. There we go. Hit that gong, John. >> Congratulations. >> There we go.
2:13:33
Uh you'll uh you'll appreciate this. We got we're waiting.
2:13:37
We were getting waiting for the right car to put this on.
2:13:38
So, this just came in the mail. >> Maybe it's the 599. >> Yeah. Yeah. >> Well, thank you. >> Not for sale, though. >> No. >> Yeah. >> Another one.
2:13:49
>> They're they're rare these days. >> Awesome.
2:13:51
Uh, thank you so much for coming on and congratulations. >> We appreciate it. We'll talk to you soon. >> Cheers. >> Bye.
2:13:58
>> Uh, and if you're looking for a luxury watch to go with your luxury car, you know where to go. Bezel. com.
2:14:01
Your bezel concier is now available to source you any watch on the planet. Seriously, any watch. Um, add cars bezel.
2:14:11
>> Tyler, what do you think about this GPT image one mini post?
2:14:13
Uh, Angel is saying they didn't fix consistency.
2:14:17
Apparently, the prompt was, "Remove all the ingredients from the burger and keep only the top and bottom buns.
2:14:24
Leave a gap between them.
2:14:26
Keep keeping the same spacing as if the fillings were still inside." Why are you laughing?
2:14:30
>> Sorry, Taylor with a deep cut.
2:14:30
He says, "DuPont Registry is going to love my Nissan Morano crossplay." >> Let's do it. >> Let's hit the gong.
2:14:37
This is most underrated car on.
2:14:42
>> Uh I think >> What other convertible SUV twodoor are you getting a a Range Rover? Evoke. >> We really botched it.
2:14:50
Not there's one for sale right now with almost $100,000. >> They're available. >> It's for $10,000.
2:14:55
And >> it's honestly a great production car.
2:14:57
or you lean out the corn, you lean out the side, take some video of the other cars. It's a great production.
2:15:04
>> We got to pick one up. >> Wild car. It's a V6. Give it up for V6s. >> That's not bad. >> Underrated. >> Four cylinder.
2:15:12
>> Um but Tyler, did you see this post about the the remove the toppings from the burger?
2:15:17
What What do you think's going on here?
2:15:18
Is is this uh does this push your AGI timeline out or pull it in?
2:15:23
>> Um what's going on here?
2:15:23
I I mean I think just from this like >> I I think it's we can probably just assume that like nano banana is there's some kind of like architecture difference where it's not just like doing diffusion on the entire image. >> Yeah.
2:15:36
It might be it might have like tool use and I feel like tool use has got to come to uh image generation soon to just be like for this prompt you actually just need to cut one half of the image out and cut the other half and just stitch them together using basically like Figma or something like basic lasso tool is like what you need.
2:15:55
So just give the AI image generator that instead of trying to rerender the entire image. >> Yeah.
2:16:02
And like maybe that like kind of tool use was only in the training step and it's like kind of been distilled into the weight somehow. >> Yeah.
2:16:08
>> But it does seem like there's some it's like it looks like it's just like segmenting something out. >> Yeah.
2:16:13
>> And then it just does kind of inainting on that part and then it just gives you the new image where where GPT is like very clearly it's like you're it's doing the whole image all. >> Yeah. Yeah. Exactly. Yeah.
2:16:21
Sean says vision reasoning is far from a solved issue.
2:16:25
Uh I'm I'm very excited to see where where that goes.
2:16:28
It feels like tool use and reasoning all that's coming to image but just uh just slowly it's going to roll out slowly.
2:16:35
Um I I demoed one uh image generator project that was clearly cutting out pieces of the image because the grain was even the same and it wasn't rerendering the face.
2:16:45
And so you could say make this a gigachad or a bodybuilder and it would add the muscles but you'd look at you zoom in on the face and it would be pixel perfect and it's like that's not rerendered. like I can just tell.
2:16:57
Um anyway, uh Grock is still on a tear on, uh on open router.
2:17:04
One trillion tokens every three hours. That's a lot of plaques. Um they're doing well.
2:17:08
We already dug into the Gro stuff. Uh that's fun.
2:17:10
Uh and KSA says, "The dumbest person you know is currently being told you're absolutely right." Absolutely right. >> By Chachi PT. This is a repost.
2:17:17
Someone else posted this. We we talked about this.
2:17:21
Uh somebody just found a banger and just re re uh reappropriate.
2:17:23
I told you that yesterday.
2:17:25
You said you said October hits and suddenly I'm craving pumpkin everything, binge watching horror movies and planning the ultimate costume.
2:17:34
Who's with me on turning this month into pure spooky magic?
2:17:36
I said, you're absolutely right, John. >> Yeah.
2:17:40
Uh, compound 248 says, "If I am Sundar Pachai, I will bury all competing foundational models in negative gross margin tokens for eternity.
2:17:47
I will never take my foot off the price and gas. to merely compete.
2:17:52
I will force you to dilute your equity into oblivion.
2:17:54
Sam will drown in my tsunami of cogs.
2:18:02
>> It's a very wellwritten piece. >> The delusion is real. >> Delusion seems real. Uh certainly. Yeah, it's interesting.
2:18:09
it's interesting. I talked to somebody a long time ago who was like there was a moment at maybe AWS or maybe GCP or one of them where there was the option to to get in a price war and they chose not to and so all of the hyperscalers all of the clouds have
2:18:25
>> it's like the soda company right if you if they got in a price war >> it would suck all the profits out of the industry >> for sure there's that there's also just uh the way I heard it described to me was uh like if you're a CFO you're just kind of like but I want but I want 30% margins. Like that's my goal. So like Like that's my goal.
2:18:41
So like why would I do why would I do low margins when my goal is 30% margins and so it's almost just like kind of hardcoded into the fabric of these financial institutions or the the finance functions at the large companies is that it's like yeah there's like this world where we get into this price war and there's risk like maybe we could win but we could also just continue to get 30% margins.
2:19:02
I don't know if this will play out this way.
2:19:04
Maybe maybe on the on the API side, but uh Tyler, have you noticed any uh any like real price fight going on in the foundation model layers?
2:19:17
They're all pretty price competitive, right?
2:19:18
On a per million token basis, right?
2:19:20
>> Uh yeah, they're all pretty close.
2:19:20
Um I would say maybe Enthropic is a little bit more expensive. >> More expensive.
2:19:25
>> Um >> but it's supposed to be a better model, right? >> Yeah.
2:19:27
And and it's like it feels if you look back it's like oh the models are are staying the same price but it's just because you're you keep updating to the new model. Yeah.
2:19:34
Like if you're using >> GPT 3.
2:19:36
5 Turbo it's like obviously super super cheap now compared to what it was. >> Yeah.
2:19:41
>> So there's some something there but I don't know.
2:19:44
>> Well, uh Barry Weiss dropped a letter to all CBS News employees and there's some debate in the comments as to whether or not this was AI generated.
2:19:53
Uh >> really what was what was the call out?
2:19:59
>> There are m dashes but that's it.
2:19:59
And so I'll read it and I I think she wrote it herself but uh she says dear colleagues I am thrilled and humbled to be writing you as a new editor-inchief of CBS news.
2:20:09
Growing up CBS was a deep family tradition.
2:20:12
Whenever I hear that tick tick tick or trumpet fanfare it sends me right back to our den in Pittsburgh.
2:20:15
The opportunity to build uh on that legacy with you hyphen.
2:20:20
and to renew it in an era that so desperately needs it.
2:20:23
Hyphen is an extraordinary privilege.
2:20:26
Right now, I imagine you all have some questions. I do, too.
2:20:29
My goal in the coming weeks, days, and weeks is to get to know you.
2:20:32
I want to hear from you about what's working, what isn't, and your thoughts on how we can make CBS News the most trusted news organization in America and the world.
2:20:39
I'll approach it the way any reporter would.
2:20:41
Hyphen uh with a new with an open mind, a fresh notebook, and an urgent deadline, she drops the Oxford, comma.
2:20:47
This feels extremely human written to me.
2:20:49
And of course it should because she's been a writer for a decade way before LLMs were a thing.
2:20:54
So why would she lose that ability to do that?
2:20:56
Um she has a couple uh she has 10 points that she defines journalism around.
2:21:02
Uh it reports on the world as it actually is.
2:21:04
It's fearless and factual.
2:21:08
>> You can say journalism.
2:21:09
>> Journalism uses all the tools of the digital a lot.
2:21:13
journalism uh that understands the best way to serve America is to endeavor to present the public with facts first and foremost.
2:21:20
I look forward to meeting many of you in the days ahead and listening and learning to you.
2:21:24
I am profoundly honored to join you Mdash and I can't wait to get started with gratitude and excitement.
2:21:31
Barry seems very uh uh seems very like well written. I don't know.
2:21:34
Uh gold is up at $4,000 for the first time ever.
2:21:40
It's a record run for futures.
2:21:42
Comes amid concerns about the economy's outlook.
2:21:44
Um, gold has been on such a run since 2000.
2:21:48
A little bit of a sell-off post GFC, but has been on an absolute tear, going from $2,000 per troy ounce uh to over 4,000 in just a few years.
2:22:00
um gold soared to 4,000 a troy ounce for the first time signaling an investor rush into alternative assets at a time of concern about the outlook for the US economy.
2:22:10
The price of precious metals has surged this year more than it did during some of America's biggest crises raising more than 50%.
2:22:17
Futures run up in 20 25 has outpaced rallies during the pandemic and the 2007209 recession.
2:22:24
Not since the inflationary shock of of 1979 has gold catapulted so much higher in a year.
2:22:32
There's been >> I think uh I look at the gold chart and I think I'm in danger.
2:22:34
The US dollar is in danger. >> Yep.
2:22:40
>> Um so >> Bitcoin was at an all-time high last year or yesterday too.
2:22:42
Uh everyone is uh flying to other other assets whether it's AI stocks, energy, Bitcoin, gold, everyone wants something else.
2:22:55
Um, but what what a run for gold.
2:22:57
>> We have our next guest in prestream waiting room.
2:23:00
We have Ramy from Evenup. Let's bring him on in.
2:23:04
>> Bring him in >> to the TV film. How are you? >> Welcome to the show.
2:23:09
>> Hey guys, how's it going?
2:23:11
>> Uh, it's great to see you. We're doing great.
2:23:12
We got our we got our gong ready for you. >> Yes.
2:23:14
Uh, introduce yourself, the company, and any of the news today. >> My name is Rammy.
2:23:20
I'm the CEO and co-founder of Evenup.
2:23:21
We are happy to announce our $150 million series E led by Bessemer. >> There you go. >> Congratulations.
2:23:31
>> Uh yeah, break down the company history.
2:23:35
Uh yeah, how you got into uh the category.
2:23:40
>> Yep, we started Even Up about 5 years ago.
2:23:42
This is before legal tech or generative AI was all that interesting.
2:23:45
And the premise was to ultimately even up the playing field for personal injury victims in the US. >> Yeah.
2:23:51
So every year there's about 20 million injury victims where often these cases take a lot longer than they need to to settle or settle for a small fraction of what they're worth.
2:23:59
And so our goal is to even up that distribution by helping ultimately their attorneys. So it's a B2B startup.
2:24:08
>> We're helping them across the whole life cycle of their injury cases.
2:24:09
Think of it as doing the heavy work for these attorneys for them at what I call superhuman quality.
2:24:14
We're helping them settle their cases faster, helping them settle their cases for larger amounts, and removing a lot of the manual work as we go through a lot of these workflows for these attorneys and their staff.
2:24:27
>> Uh how are you guys already running up against the the oppositions uh or or the defenses AI themselves?
2:24:34
How how is the battle evolving?
2:24:40
>> Yeah, we we don't really see too much of that.
2:24:42
Um, the crazy thing is this is our fourth round of financing in the last two years. >> Wow.
2:24:49
>> And we're on this really rapid growth trajectory where we see about 10,000 cases a week.
2:24:54
But when you think about just the TAM here on 20 million cases, we're about 1% penetrated today.
2:25:00
So in a way, even though we're it's a big number, it's still very early days in our space.
2:25:06
So we haven't seen any of that come through.
2:25:07
What we have seen is ultimately being able to change some of the operations of these law firms for the better.
2:25:13
So, one of our firms has scaled revenue by about 70% year-on-year on a base of over 100 million of revenue without adding headcount. >> Mhm.
2:25:22
>> Another one of our firms have used one of our products in mediation in real time where they turned a $50,000 offer into a multi-million dollar offer.
2:25:28
So, it's kind of crazy to see the impact we've been able to have, but it's still early days.
2:25:34
>> Is plaintiff screening a different business? So yes, not fully.
2:25:42
The way you can think of this is the way we help is, you know, imagine somebody gets injured.
2:25:46
They would typically call an injury attorney. They would sign up. >> They see a billboard.
2:25:49
They see a billboard and the billboard says injured. Call this number.
2:25:52
They call that number and they describe their injury and then someone needs to qualify that and it's probably not the most highest paid lawyer and it feels like those intake forms could be processed by AI, but is that something you're looking at doing?
2:26:05
>> So yes, it's really interesting.
2:26:05
So we we don't do the intake call themselves, but as soon as the intake call is done, the transcript of those calls is something that we would analyze. >> Sure.
2:26:13
>> To say, "Hey, law firm, you need to prioritize this case."
2:26:16
>> Y >> or this might be a case you want to draw. >> Yep.
2:26:18
>> We don't do the signing up of the case, but as soon as there's any information, whether it's audio or document based um info in these cases, we read that, we scan it, and we ultimately make decisions off of that with the obviously with the with the attorney hand in hand.
2:26:32
uh how are like hallucinations and and uh how are you thinking about like lawyer in the loop?
2:26:37
Uh Jordi was talking about this uh there was some case about uh uh a consulting group that turned over an analysis to a city and had to give them a huge refund because >> it was delight delivering uh a a a study that was just inventing like judgments that no judge had actually >> Yeah.
2:26:59
it wasn't grounded in like the ground truth of case law.
2:27:00
And uh I I imagine that like I I mean the stakes are pretty high.
2:27:06
>> The model just had a really >> but also I mean you you you could you could wind up in a situation where like your firm is like forever tainted by a certain judge and the judge is like I remember what you did. That was really sloppy.
2:27:17
Uh I imagine that your clients and your customers uh care deeply about that.
2:27:21
Like what are the what are the strategies for avoiding those types of situations?
2:27:25
you you both brought up, you know, really great points here and and it's it's a really funny thing because folks are always like, "Hey, generative AI and legal tech are all shoeins for each other, but folks generally tend to forget accuracy really matters."
2:27:38
>> These cases, >> you can't be 90% of the way there in a legal letter.
2:27:41
That's how you get this, >> right?
2:27:43
Or that's how you get those again some of those headlines that you guys just mentioned. >> Yeah.
2:27:47
>> And so the way we think about this internally is you need to have done a lot of cases >> because every basis point of accuracy matters. Mhm.
2:27:56
>> And so another way of thinking about it, we do a number of different legal workflows for these attorneys.
2:27:58
But if you think of one letter called a demand letter, that's one of the documents we prepare for our for our firms.
2:28:04
The quality from this in us being able to repair this two years ago versus today was very different. >> Yeah. >> Right.
2:28:11
When we started, keep in mind this is before GPT3 and and the big, you know, all the craziness around AI two years ago, we had to have a human in the loop to QA these letters. >> Yep.
2:28:23
And if you think about the inputs in these cases, and we're at a point now where we're going to be millions of pages of medical records, u medical bills, police reports, raw underlying documents, we've had to fine-tune these models, one to be able to get a much higher level of accuracy than what you typically see off the shelf.
2:28:39
And so it's what's a simple example of this is if you think of something as intuitive as, hey, list me all the medical visits that a plaintiff has seen in a case.
2:28:50
If you just go into any of your, you know, models today that are, you know, publicly available, ask it to do it for you, you'll see the accuracy is just not good enough.
2:28:57
And so this is where we had to train our our own data service model just to do something as intuitive as be able to pull out a date.
2:29:05
>> When you look at these case files, you get to see timestamp dates, signature dates, date of birth, etc.
2:29:10
>> There's so many different dates.
2:29:12
>> It gets pretty complic complicated with even just one piece of extractions.
2:29:14
And that's how we had to build this with time.
2:29:18
You've had to do a lot of you got have to get your reps in to get the quality of where it needed to be.
2:29:22
>> How are you growing the business?
2:29:22
Are you running billboard ads?
2:29:24
If you're an injury attorney, call this number.
2:29:25
Or or are you doing uh state?
2:29:30
>> You should really you should really do that on the 101. That would be great.
2:29:34
>> Uh or or or are there like legal tech conferences that you like what does the top of funnel look like for you? >> Yeah.
2:29:41
This is the the crazy thing as well about our space is this is such a massive space that folks just don't necessarily know too much about.
2:29:47
But when you mention those billboards >> Yeah.
2:29:51
>> and you folks are kind of saying this in just but when you see one of these firms >> has a thousand billboards in California. >> Yeah.
2:29:57
>> That's I don't know any of any SAS business that has a thousand billboards. You know what I mean?
2:30:01
Like massive marketing machines and they're based on our math there's around 300,000 of these injury attorneys. >> Wow.
2:30:08
>> And there about 20 million cases and they're all over the place. Right. >> Yeah.
2:30:12
>> One of our largest customers, as an example, is in Alabama. >> Mhm.
2:30:16
>> You would have never thought it would be in Alabama.
2:30:17
We have massive firms in California.
2:30:19
Massive firms on the east coast.
2:30:21
And it really follows population. >> Yeah.
2:30:24
>> Where there are people, there's going to be injuries because it can mean anything from motor vehicle accident to a dog case, even police brutality cases.
2:30:30
There's many different ways folks get injured.
2:30:32
>> And so, as long as there's people, there's going to be personal injury attorneys.
2:30:34
As long as there personal injury attorneys, they're all B toC.
2:30:37
They're all kind of like they want to be found.
2:30:38
Because if you think about our go to market approach, we have a over 100 person go to market team that's territory based.
2:30:45
>> So this is where we would go local in LA, in SF, wherever it might be to be able to get these folks.
2:30:49
And that's where, you know, a lot of this is outbound as opposed to inbound.
2:30:53
>> Did you ever think about the Atrium Clear Spire model of like bolting an actual law firm onto your software company of an LLC bolted to the uh to the CC Corp with like an MSA?
2:31:02
Uh that was a model that's been tried a few times.
2:31:07
They they think people are trying it again.
2:31:08
But did it ever occur to you to try and try your own cases, team up with a lawyer, build a firm? >> Yeah.
2:31:15
For us, like we we we want to the way at least I see this space evolving >> is I see this as very much a win or take most.
2:31:24
And even though we're in vertical SAS here, it there's like elements of Uber andyft that feel true to our space where the first startup that gets 10% of LA will win LA. >> Yeah.
2:31:34
because every time you see these cases, the better this whole system gets.
2:31:37
And I'll just I'll elaborate on that a little bit more and that should hopefully explain why we're doing this in a very B2B fashion.
2:31:42
But the one thing you folks should know is even though there's 20 million cases, 99% of them are settled privately. >> Mhm.
2:31:49
>> And so there's a real wide gap in performance in terms of how long these cases take to settle and how much they settle for.
2:31:54
And generative AI alone can't solve that problem.
2:31:57
You need to be able to see a lot of cases for you to be able to do that because most of this data is sitting in the inboxes of a very fragmented industry.
2:32:04
And so for us, the goal is how do we expand our go to market, you know, as quickly as we can to be able to go from 1% to 10% to 30% market share.
2:32:13
And the want to think about as a key metric, more cases we see, the better the system ultimately gets.
2:32:20
And if we're just very focused on I mean we we'll never do this but like competing against our own customers you get of the cases that are out there.
2:32:28
>> Yeah that makes a ton of sense.
2:32:29
>> Do you think that legal AI is underhyped as a category?
2:32:34
Obviously there's a ton of funding flowing in but there's not you know on the code generation side it's sufficiently hyped right every researcher at every company you know is talking about the the leverage they're getting.
2:32:46
Every startup founder is talking about the leverage they're getting.
2:32:49
every CTO is talking about the leverage they're getting.
2:32:50
Public company CEOs legal is like, you know, just happens.
2:32:54
Uh, you know, there we certainly have plenty of lawyers in tech, but they're not, you know, they just don't tend to be in a position where they can talk about stuff in the way that regular software engineers can.
2:33:07
So, it feels like you could be seeing the same type of revolution happening, but it just would be much uh get much much less coverage. >> No, for sure.
2:33:17
I I think that there's obviously been when we started um even up a couple years ago you folks can imagine it's like legal tech sucks, AI sucks, personal injury sucks.
2:33:26
Like my background is I used to work at Whimo and I used to work as like a tech investor before that >> and so it's definitely a lot there's a lot more attention today in legal tech than there's ever been before.
2:33:36
Is it again is it overblown or not?
2:33:38
I think in the end of the day, the thing that makes our space so different when we're selling to these injury attorneys, the thing you folks should know is it's a very fragmented, highly competitive, and most importantly, commissiononly industry.
2:33:49
These folks make a percentage of the value of the cases that they settle.
2:33:53
So unlike other parts of, you know, AI or legal, there's no experimental ARR, right?
2:34:01
These are not like big firms where they can afford to spend a million dollars on something and because of how competitive it is like you better believe this thing can actually help their case operations otherwise they'll turn they don't have the luxury of you know being able to have big IT budgets etc.
2:34:14
And so in that sense, if you think about our 2,00 customers, they wouldn't be around if they're not seeing real demonstrable ROI in terms of increasing case outcomes or reducing duration of these cases.
2:34:24
And in that sense, you know, I do think it is call it it's still early days.
2:34:28
And and if you think about the mission of the business, it's not um I I think it's just going to be it's inevitable in terms of those 20 million cases being able to be settled not again all over the place, but as fast as they can for the fair amount.
2:34:42
And so in that sense when we're just 1% penetrated it's it's not over I at least in my mind it's like clear ROI.
2:34:48
Well, yeah, and there's that that customer alignment where they're incentivized to adopt as much AI as they possibly can because they're not billing hourly, right?
2:34:58
They're just getting paid when these cases settled.
2:35:00
cases settled. uh versus you know a traditional law firm if you if something they used to be able to build 10 hours for suddenly takes 30 minutes and they had a lot of margin in that 10 hours there's not there's not the same incentive to adopt uh as as what you're seeing >> you nailed it and and the other thing
2:35:20
that's also different about this wave and it's funny because I was having a conversation with one of our um one of our customers about this some of these folks are still on prem but they're one of our biggest customers and So when you go to a law firm and you're like, "Hey, you got to be on the cloud." They're not
2:35:34
They're not going to understand what you really mean.
2:35:38
>> When you're going to these law firms and you're like, "Here's a legal letter.
2:35:39
It was drafted instantly."
2:35:41
You can evaluate the quality of this thing relative to your own staff because you're a subject matter expert.
2:35:46
You know what it, you know, this legal letter does.
2:35:47
And that's what allowed the space to adopt a lot quicker than anything that we've seen before in legal tech.
2:35:53
And and again, I I think again you really pinpointed it, but they really genuinely care a lot about being faster, settling settling quicker, spending less time on review because anything that they save, they get to keep, right, as their own margins. >> Totally.
2:36:09
>> One of my first jobs ever was uh doing paper filing at a law firm as an intern. I was like a kid.
2:36:15
And >> you were a paper boy then, you're kind of a paper boy now.
2:36:18
We're still paper enthusiasts.
2:36:20
I I hadn't I hadn't put it together until I until I actually just had this conversation and reflected on like how crazy that was that I mean I guess the cloud like barely existed then but yeah it was paper back then it was wild.
2:36:33
I mean computers were around but like my job was sort of like yeah inventorying this stuff.
2:36:37
So yeah, law moves slowly.
2:36:39
Like the like a lot of the law firm partners that get like effectively tenure are like my process works and I like it printed out or I like I like you know having the network the internet at my office is reliable.
2:36:51
I don't know about putting it in Google.
2:36:56
So like people got to figure it out.
2:36:57
>> When do you when do you expect the first AI uh legal company to IPO? Hm.
2:37:05
>> Still feels like we're probably couple years out, but I imagine the revenue for you or some some of these other players could get there uh you know get to that $500 million mark or wherever whatever the >> uh wherever it needs to be to to be interesting to to Wall Street. >> Yeah.
2:37:24
So, this my um just on the paper piece real quick, then I'll answer the other question.
2:37:28
And it's it's so funny the way you can kind of think of this.
2:37:32
There's been so much innovation in more of the consumer >> like how to get leads like the consumer uh part of personal injury where like you know attorneys are advertising on Tik Tok on social etc.
2:37:44
>> But on the operation side there's been very little innovation back to your paper days.
2:37:48
They're still doing stuff on paper.
2:37:50
>> We've had some of our folks asked to pay our our annual SAS subscription with monthly checks to give you a sense of how cool the ops piece can be in this space.
2:37:59
And so this is the first time really in history that these operations of these firms >> are changing pretty substantially, right?
2:38:06
Because you now can do a lot more with a lot fewer staff. >> Yeah.
2:38:10
>> And if you think about again like where we're going with this, you're going to see these firms be just be able to handle a lot more volume.
2:38:18
And and if you think about the the amount of cases that person attorneys take on today, you'd be surprised at how many cases they're not taking on because they just don't have capacity or they can't make the math work because again of their of their model. >> Yeah. >> Yeah.
2:38:32
>> So I think I missed the other question.
2:38:34
What was the other question again?
2:38:35
>> Oh, I just kind of Yeah.
2:38:35
IPO timelines for the category.
2:38:37
When when do you expect the first companies to get out? >> Yeah.
2:38:41
It does feel like an entirely different like market.
2:38:42
Like there's no like clear comps that everyone knows.
2:38:47
It's not just like, oh, another like, you know, SAS company that we can just immediately comp to.
2:38:50
So, it would be like a new >> Yeah.
2:38:52
In the legal industry, law firms can't go public, right? >> Yeah. Yeah. Exactly.
2:38:56
Financial got to be different. Yeah.
2:38:58
I would love to hear some color on like how the public market might receive some of these. >> Yeah.
2:39:03
>> Yeah. I I mean in terms of like timeline I would say again the 500 million of ARR median ARR um you know business going public the threshold there I think we're a couple of years away but you know I mean we're we're scaling super fast we're more than doubling yearon year on a on a meaningful base so I do think
2:39:20
we're maybe two three years not us but >> for one of the companies us as well two three years out before going public >> in terms of like how the markets might receive it it's so interesting right that these are such different businesses where you're going to see a lot more TAM >> Y >> than you've seen in traditional software. And so I I I kind of say this,
2:39:37
And so I I I kind of say this, one of our one of our biggest customers is is paying us 4 million a year and they have 100 employees at the firm. >> Wow. >> Think of the >> Yeah. 40,000 value per head. Yep. Exactly.
2:39:50
So you're delivering a ton of value to this. >> Yeah.
2:39:53
Because one of the things that comes up with with some of our investors, hey, is like you're focused in a very niche part of personal >> and 300,000 attorneys out of, you know, over a million, it's maybe 30% of the base in the US.
2:40:03
But when you're making 10x more revenue per head than traditional SAS, >> Yep.
2:40:07
>> your T is actually meaningfully bigger than a lot of these SAS companies. >> Sure. Sure. >> that are out there.
2:40:11
And so again, I do think it'll be interesting to see much more rapid growth, much higher base SAS businesses than you've ever seen before and how the market would would be able to evaluate that because it is it is going to be different than traditional SAS. >> Totally.
2:40:27
>> Well, congratulations on the funding milestone.
2:40:29
I'm sure we'll see you back here again soon.
2:40:30
Maybe one more round before the end of the year.
2:40:32
You've already done a couple, you know, uh but uh looking forward to the next conversation.
2:40:38
>> Have a great rest of your day.
2:40:38
Thank you so much for hopping on. >> Cheers.
2:40:41
>> We'll talk to you soon.
2:40:43
And now it's time for our song.
2:40:46
>> Find your happy place. Find your happy place.
2:40:50
>> Book a wander with inspiring views, hotel, great amenities, dreamy beds, topic cleaning, and 24/7 concier service.
2:40:54
It's a vacation home but better. Folks, go to wander. com.
2:40:58
Uh when Lisa Sue took over as chief executive of chip of chip company Advanced Micro Devices AMD in 2014, the company's market value was just under $3 billion.
2:41:12
Decade later, today it's worth more than $330 billion. little hundredx. >> There we go.
2:41:19
>> The more than hundfold increase that reflects how deafly AMD has pivoted its strategy from mainly producing graphics cards for gaming and personal computer processors to more tightly focusing on the data center chips that power power the artificial intelligence revolution.
2:41:35
Uh the share price rose 24% on Monday after the company announced a partnership with OpenAI um to build six gawatts of power for inference.
2:41:42
The deal has given rocket fuel to AMD share price and the company's ambitions to complete to compete with rival chip designer Nvidia, which is by far the dominant competitor in the AI semiconductor industry at more than 10 times the valuation.
2:41:55
Now, the AMD share price is kind of up and down and and we're we're we're now at all-time highs, but just barely.
2:42:02
Uh March 8th of 2024, the stock was trading at $27. Now it's at 211.
2:42:06
And so, uh, they they've already ridden an AI boom from $50 a share, $60 a share, up to 200, then back down to $80 a share, and then back up to 211 shares, uh, 200 $211 a share.
2:42:23
So, uh, Monday's deal specifics uh, specifies that OpenAI will be issued warrants for $160 million shares of AMD stock at a marginal price of 1 cent per share once OpenAI hits certain deployment targets.
2:42:35
And once AMD share price rises, the final trunch of shares will be granted only if AMD's stock hits $600 a share.
2:42:43
So it needs to uh 3x and become a trillion dollar company.
2:42:48
Basically uh for now the market capitalization with a market capitalization of four and a half trillion, Nvidia is nearly 14 times the size of AMD.
2:42:56
And most analyst estimates peg the market share for graphics processing units or GPUs as they're known.
2:43:03
Thank you, Wall Street Journal.
2:43:05
uh that power AI training and inference at more than 75%.
2:43:06
So 75% of the market is is Nvidia.
2:43:09
Um and they're trading at 10 times the price of AMD.
2:43:12
Uh AMD faces pressure from companies such as Broadcom which produces application specific custom chips for for customers such as OpenAI.
2:43:20
Uh and so the OpenAI deal might have shifted the balance in AMD's favor somewhat.
2:43:25
How AMD got to this inflection point is a is a combination of careful strategic planning and being in the right place at the right time.
2:43:31
quote, "Over the last few years, what's been important to us is to understand the workloads that would really drive the next generation AI training and inference."
2:43:40
Sue said in an interview, "This deal is a huge expansion of the work that we're doing."
2:43:44
Uh for much of the past decade, AMD's arch rival has been Intel, the troubled chip designer and manufacturer that recently received major investments from Nvidia and the US government on the strength of popular designs for the graphics chips used in the PlayStation and Xbox gaming systems and the CPUs or main computer brains.
2:44:04
Thank you for explaining what CPU is, Wall Street Journal.
2:44:05
Uh used in consumer PCs, AMD has steadily eaten away at Intel's market share.
2:44:09
For years, Intel's been bogged down by a costly effort to turn around its chip fabrication business.
2:44:15
AMD, however, spun off its manufacturing business, now known as Global Foundaries, in 2009.
2:44:20
While Intel has continued to pour money into its unprofitable foundry segment, even as even as it fell badly behind the more technologically advanced rivals such as TSMC.
2:44:32
And so, this is where everyone always says Intel should have gone fabulous.
2:44:36
They should have split the companies off. That's what AMD did.
2:44:37
They split off Global Foundaries, became a fabulous semiconductor design shop like Nvidia.
2:44:44
The business is similar to Nvidia, and now this seems like they're catching up.
2:44:48
I mean, the stock's up 100.
2:44:50
>> Somebody uh asked Lisa Sue if they were going to partner with Intel.
2:44:53
Buco Capital says they they gave a very she gave a very awkward and funny response.
2:44:59
She says, "Well, um as you know, the supply chain is something that we work on um you know, very uh very uh meticulously.
2:45:06
I think we have a very strong supply chain.
2:45:08
Uh we're certainly partnered with you know TSMC across the supply chain.
2:45:12
Uh you know just to that um earlier question uh we're absolutely prioritizing building in the United States because I think that's super important.
2:45:21
This is the um the US AI stack.
2:45:24
We want to have as much of it in the US as possible and you know we continue to really look at you know how do we ensure that there will be a strong supply chain you know going forward.
2:45:32
So, when you have it uh typed out, it really uh you can tell she's trying to uh >> it's always tough to stuff a mic in someone's face and then transcribe it. Who knows?
2:45:46
We've been going back and forth on the AI bubble.
2:45:48
I think we should close out with the clearest evidence that we're not in an AI bubble from Trunk Fan.
2:45:53
He says he's not worried about the AI bubble bursting until corporate social accounts start having these exchanges again.
2:46:03
And uh he back in 2021, December of 2000, uh December of 2021, Meta says, "This is going to look great in the metaverse."
2:46:11
And the official Pepsi account says, "You know it, friend."
2:46:14
And Budweiser Beer chimes in says, "Welcome brand friend. Wag me."
2:46:19
And then Pepsi says, "Thanks, friend.
2:46:22
Wag me with the rocket emoji."
2:46:25
And uh this was a >> that was a moment. This is a dark time.
2:46:30
>> That pretty much was that was actually two weeks or about a week after the actual top was in the top. >> Yeah. Yeah. Keith had called it.
2:46:39
>> Keith called it perfectly.
2:46:39
Everybody should have post notifications on for Keith.
2:46:44
>> He's probably gonna uh uh if he if he makes a call again.
2:46:47
Uh I think people will be listening. >> Yes.
2:46:51
Anyway, keep monitoring the situation folks.
2:46:54
Stay sharp and we will see you tomorrow. >> I cannot wait.
2:46:57
gave us five stars on Apple podcast and Spotify and tune in Friday for our interview with Sam Alman who's CEO of OpenAI >> Sama. It's time. >> Thanks for watching. >> See you tomorrow. >> Bye.