0:13
Hey, hey, hey. Hey. Hey. Hey.
Search this video
0:33
[music] >> [music] [music] >> Heat. Heat. Hey. Hey. Hey. Heat. Heat.
2:37
>> [music] >> We came to this world to reach the stars.
3:25
We came to this world to shape a future.
3:36
We came to this world to shape our future.
3:52
reaching to feel [music] the new [music] triple blades. Feel [music] the music.
4:39
[music] Large journalistic force headed towards you. Stand by.
4:56
Market clearing order inbound. >> You're watching TVPN.
4:59
Today is Friday, November 21st, 2025.
5:02
We are live from the TVPN Ultradome, the temple of technology, >> the fortress of finance, >> the capital of capital.
5:08
Uh we got to ring the size gong for Eli Lily.
5:11
Big farmer is getting bigger. $1 trillion.
5:19
That's the new market cap for Eli Liy.
5:22
They're a $1 trillion company.
5:24
Normally, you got to be selling ads.
5:27
You got to be a tech company or you got to be an oil company to get into the one trillion club.
5:32
>> But people did say back in the day, whoever creates a cure for obesity is going to be a trillionaire. >> Yep.
5:39
>> And [laughter] they did the meme. >> They did the meme. >> They did the meme.
5:41
Uh, Eli Liy just became the first one trillion dollar pharma company in history.
5:46
Uh, I want to see the CEO Dave Ricks, you know, he went on the, uh, Cheeky Pint podcast.
5:52
I want to see him post, you know, how to run a 13f figureure business.
5:57
[laughter] >> Give me a thread. Give me a thread. I'm a 13ig businessman.
6:02
I'm a 13-figure businessman and I'm on Instagram giving you some advice. Teach a course. Come on.
6:09
Tell me how you do that >> but it is a fascinating business.
6:12
Uh it's one that I'm not super familiar with and so I wanted to understand exactly how the weight loss markets playing out earlier in the year maybe a year ago. Uh we looked into GLP1s. We talked about them. We read about Novo.
6:29
Uh of course >> we laughed a little we laughed a little when Novo failed to renew one of their one of their patents. >> Yeah, that was crazy.
6:36
And uh I think it cost uh >> I'm gonna look it up but it was something like that. >> Yeah.
6:44
So what's been fascinating to me is the is the lack of uh importance of intellectual property here.
6:49
Normally when I think about uh when I think about developing drugs all pharma I think about it as like you get a bunch of scientists in a lab they they discover something and then they patent it and you have a complete monopoly on that for years.
7:04
It's like, you know, you have the you have the patent on the intellectual property.
7:08
If I have Mickey Mouse, you can't use Mickey Mouse for decades until it enters, uh, the the the the public good, the public square.
7:16
Um, but that's not exactly how this is playing out.
7:19
So, um, Novo has been was originally the one getting all the attention for kicking off the GLP1 boom.
7:26
Uh, but over the past few years, Lily has caught up.
7:28
It's sort of a Google story, sort of like the Google narrative.
7:32
um Novo sort of raced to market.
7:35
Uh basically everyone was working on diabetes drugs.
7:38
Then they figured out that um the uh these could be used for weight loss and everyone uh rebranded, ran a few more studies and then brought the drugs to market.
7:49
So now the name of the game is uh making American GLP1s.
7:54
Uh Eli Liy is building a massive new plant in North Carolina to support what's now a 72 billion market.
8:01
the the revenue numbers are really crazy.
8:02
Uh it feels like an AI story.
8:02
Uh but in this case, AI stands for appetite inhibitor, I guess.
8:08
Uh long-term forecasts get really massive.
8:10
Eli Liy is currently expected to generate 63 billion across their entire portfolio.
8:17
Um but by 2034, they're expected to sell over a hundred billion just in weight loss.
8:22
So this new business loan is going to be bigger >> entire Exactly.
8:25
It's going to be it's going to be basically twice as big as they're existing as as as everything they are now.
8:30
Um and they're already a big company.
8:32
So, um I was I was surprised that there was not more of an exclusivity period here. I wanted to dig into it.
8:38
We were wondering like is it some sort of deal?
8:39
Are they working together? Novo and Eli Liy.
8:41
In fact, they are >> historically they did. >> No, really.
8:46
>> They were accused of working together and and that would have been illegal and they would have been colluding.
8:49
Uh they are bitter rivals going back 80 years.
8:55
they've never worked together.
8:55
They uh they do not work together.
8:57
They in fact are >> fighting over this market completely.
9:02
And so >> what happen you know the the the first drug that kicked this all off was Novon Nordisk.
9:10
They patented semiglutide which was marketed as Ompic and then Wagui.
9:12
And >> and to my point earlier yes uh referencing the Canadian market this happened around five months ago.
9:19
Novo Nordis actually lost Canadian patent protection on Ompic and WGO in Canada because a few years ago they didn't pay the very nominal maintenance fee on their >> Pra which will ultimately you know cost them billions. >> Well don't do that.
9:36
Instead get on ramp time is money.
9:39
Save both easy to use corporate cards bill payments accounting and a whole lot more all in one place.
9:44
[applause] So back to GOP ones.
9:45
No one can patent a biological mechanism.
9:49
You can only patent a particular chemical, a particular structure.
9:53
You can't just you can't patent the idea of inhibiting uh mimicking GLP-1, which is what all these drugs do.
10:01
They mimic the GLP-1 hormone, and that's what's important.
10:04
And so, Novo patented semiglutide.
10:05
Lily had tzepide already in the works.
10:08
tzepide already in the works. again they were working on uh on diabetes not on weight loss but but it was it was already kind of predicted to be a big market so they are both they both have products and then as soon as uh as soon as Novo is able to uh pivot to weight loss Lily is able to run the same uh
10:29
playbook very very quickly um and accidental discoveries and quick rebrandings are nothing new in pharma uh Viagra was initially created by Fizer as a heart medication they gave to both men and women I believe and um but male subjects obviously had a particular side effect and that unlocked an entirely new market. Uh and then that discovery came
10:47
Uh and then that discovery came out of left field completely.
10:50
So they had a true Fiser basically had a true monopoly for 5 years before Seialis came to the market.
10:56
Um this is obviously different because both companies were working on uh the the underlink structure.
11:02
Uh aderall also had a a really odd path.
11:04
Amphetamines have been around for over a hundred years.
11:06
that were used by soldiers in World War II.
11:10
Uh so obviously you can't patent them.
11:12
Uh in the 1970s they were sold as weight loss drugs and so there was a drug >> appetite suppressant. >> Yes. Yes.
11:18
So it was called Obitrol and Obitrol was sold as a weight loss pill in the '9s.
11:24
A company bought Obitrolamed Aderal meth. >> Yeah.
11:30
>> It's a great weight loss drug. >> Try it today.
11:32
>> It's actually so crazy.
11:32
I imagine that it didn't really take off as a weight loss drug because it had crazy side effects. I don't actually know.
11:39
I would imagine it was effective, but probably just very risky to use. Yeah.
11:44
But, uh, in the 90s, a company purchased Obitrol, rebranded it Aderall, and then marketed it for ADHD.
11:52
And they didn't have the patent on the chemical.
11:55
Remember, you can't patent the the chemical empetamine because it's been around for so long.
11:58
Um so what they were able to do is develop a brand and Aderall is a product that uh the brand name somehow it just completely broke through in a massive way and it's just synonymous with uh actually ADHD. Yes. Yes.
12:10
Uh it's actually broken through in such a way that it's synonymous with ADHD.
12:14
It's synonymous with like study medication even.
12:18
Um and so it's been wildly successful.
12:21
They actually did wind up getting a patent later on for Adderall XR.
12:25
So Adderall XR is a bunch of beads in a capsule and they were able to patent the delivery form factor. Exactly.
12:32
Um >> and so even even when you don't have the patent on the underlying tech, you can still patent things around it.
12:38
Patent the bio the bioimilars.
12:40
There's a bunch of different things you can do.
12:42
And so >> it is a shame that the Hila monster like never is is not really getting any upside any any of these uh weight loss drugs because that that really is is the origin, right?
12:54
They they really should do that.
12:55
They should do like 1% for the Hilo monster and just 1% off the top.
12:59
They should donate it to like Hilo Monster.
13:00
Is it >> maybe a foundation of sorts? >> Yeah. Yeah. A foundation. Uh >> a nonprofit.
13:06
>> A nonprofit that just makes the Hila monster live in absolute luxury. >> That's right. >> As a thank you.
13:10
Um, so Eli Liy will be fighting like this endless battle with every other >> and to be clear for those that don't know the the uh the it was was it it was Nova Nordisk that figured out what was happening in the Hila monster which uh was >> the Hila monster. I don't remember. >> Yeah, it is.
13:27
It's the Hila monster >> cuz there's two Yeah, there there's the Komodo dragon, too.
13:30
And I I often get those two creatures uh confused.
13:32
Uh but yeah, it's the saliva in the in the Hila monster, I believe, that uh that that uses the same pathway, the the the GLP1 uh hormone.
13:46
Uh >> so >> so basically over the next couple years, we're going to see this interesting dynamic where Eli Liy, Novo, and basically every pharmaceutical company like wants they have to get on the action because it's such a big market.
13:59
Uh obesity is a massive disease.
13:59
It really is that that trillion dollar opportunity.
14:03
It's been that for a long time.
14:04
There's, you know, hundreds of millions of obese people.
14:07
Everyone who has that, you know, doesn't want that.
14:11
Um there's the market is so so broad.
14:11
Um and so, uh what's interesting is that the patents haven't resulted in a perfect monopoly where it's not this winner take all situation where Novo is just going to run away with it, Eli Liy is just going to run away with it.
14:27
What's actually happening is that uh they it's a duopoly right now, but demand is so high that they still have high margins.
14:35
So they're in like a price war, but the price >> and that's even with the competitive dynamics of the compounders, companies like HIMS, which are are creating Yep.
14:44
>> a ton of different GLP-1 products, you know, just in their own uh in their own uh facilities.
14:50
>> And so the price has fallen 3x.
14:50
And normally, you know, if if the price of your good is falling threex, you're charging three if you're if you're selling a $50,000 car and then a couple years later you're selling it for 15k.
15:01
Uh like that's not >> cost something like in the same range to produce and so you're just getting massive margin compression but the growth is so insane that y >> it hasn't really mattered. >> Yeah, exactly.
15:13
So the the the market is growing so so much.
15:15
Uh margins have fallen from 80% to like 60%.
15:18
Um but the mass adoption just completely offsets that and so they're making way way more dollars in total.
15:25
Uh and so uh the next race now, you know, Eli Liyy's trillion dollar company.
15:31
What do they have to do next?
15:32
They have to go and uh make a make it a pill.
15:35
They're they're going to try and uh make these weight loss products in pill form.
15:40
And there's a whole new battle duking it out between Eli Lilly and Nova Nordisk again and some other players.
15:46
Uh but uh it's it's a it's a fascinating time and there's a lot of uh they have their own like little barnacle economy.
15:52
There's a lot of analogies to the to the AI race.
15:53
Uh trillion dollar companies and high margins and all this but at the end of the day uh what matters in the GLP1 market is just the actual supply like uh you have to go and build a massive facility and once you get the facility up people will buy it because um just the demand is so high that if you can make it you will be able to sell it and you'll be able to sell it at a good good margin.
16:16
>> Um anyway let me tell you about reream one live stream 30 plus destinations.
16:18
If you want to multiream, go to reream. com.
16:23
There was some interesting news in the SEO world.
16:26
Adobe is buying Semrush for $1. 9 billion.
16:30
Should we do a size gong for? >> I think so. I think so. >> I think so. Uh, >> yeah. Fantastic. Fantastic outcome.
16:39
>> yeah. Fantastic. Fantastic outcome. It was notable to me because obviously we've been tracking the generative engine optimization space and there wasn't really a great comp for a lot of those like you know I remember we were
16:54
talking about it >> and uh it's not like you hear a lot of SEO companies getting acquired in in in that range and so anyways the the geo market is still highly highly highly competitive obviously we work with uh profound uh which has been the clear leader in the market to date. Uh but uh
17:11
Uh but uh I would expect this to drive even more companies to come in and compete.
17:16
And ask any VC, they're they're getting pitched uh companies in this category multiple times a week still.
17:24
So uh people are just piling in.
17:26
And >> that's interesting.
17:27
I wouldn't think of Seamrush as a as a GEO. >> No, it's not. It's an SEO.
17:30
It it was the SEO leader. >> Yeah.
17:34
>> Uh that being said, I would expect them to also want to play in GEO.
17:37
It's not like they're going to completely ignore.
17:43
It's I would almost be thinking about Seamrush having their own build versus buy conversation. Yeah.
17:48
>> Um sort of unclear what it would take them, how much data they have, how they can uh how they can jump into the GEO market.
17:56
Um obviously a lot of companies have been able to get something up and running very very quickly. Yeah.
18:00
Um and so >> and they they do already have a tool.
18:04
It's called Semrush AI visibility.
18:04
Uh but uh but again there's so much demand for this for this kind of new product because every single company is >> uh you know spending a lot of time thinking about how they're appearing in in different LLM queries.
18:17
So >> uh still still up for grabs.
18:21
>> Reportedly Samurush did $250 million in revenue uh back in 2022.
18:25
Probably grown a little bit since then.
18:29
uh founded in 2008, a true overnight success at >> overnight success.
18:35
>> Uh 10 uh almost 20 years to to get on to the next thing with Adobe.
18:39
Um speaking of Adobe, I I I need to push their tools to the limit at this point.
18:46
Um they were so behind in terms of generative AI and their models.
18:52
They were training their own models.
18:54
But eventually I saw a demo where Nano Banana was in Photoshop and I feel like that is really uh potentially a really really big unlock just for workflow.
19:04
We've seen so many different uh examples of this in in AI where um the models are incredible but having the harness and having the wrapper whether that's a product that was introduced 5 years ago, 10 years ago, 50 years ago like they're all getting better.
19:19
Um >> uh Adobe works with fall. >> Okay.
19:25
>> So they they they can integrate pretty much any model in the world and inference it.
19:28
So I expect them to uh it is funny that that uh whatever it was two years ago every single player felt like they needed their own uh their own models and now I think the the uh the narrative is really flipped.
19:41
Well, speaking of fall, build and deploy AI, video, and image models with fall, trusted by millions to power gender media at scale.
19:49
And also, Gemini 3 Pro, Google's most intelligent model yet.
19:55
State-of-the-art reasoning, next level vibe coding, deep multi deep multimodal understanding.
19:59
We've been having a a ton of fun with Gemini 3 Pro and Nano Banana Pro.
20:02
Uh we have generated an image of the aura farm the world trying to understand map a barnyard uh sort of an AI market map but through the lens of a a barnyard because that's really what uh what is going on in AI these days. Um let's see.
20:22
I think we need to zoom this out just a little bit to get it to line up.
20:26
that uh we can show and we can take you on a tour of our our farm-based market map to uh to explain what's happening in the state of AI in November of 2025.
20:39
Tyler, do you want to take us through it? >> Sure. Yeah.
20:43
I mean, so so we like to use a lot of uh animal idioms on this show.
20:48
>> Um a lot of these you might recognize, but we've kind of expanded out to try to cover all the major players.
20:52
cover all the major players. Um and you know so yes so this was made with um uh Nano Banana Pro uh very extremely good model but you will notice uh as you get more and more complex it gets a little bit slop there's some slop in some places >> um but broadly I think it did a very
21:10
good job uh had a lot of fun making this >> yeah before Nano Banana Pro was released we would have needed to hire a uh somebody that maybe illustrates children's books and if they were an expert maybe they could have whipped something uh together in a day This took you far longer than that of [laughter] uh you know prompting over and over and over. Uh but uh I I'm very I'm very
21:28
Uh but uh I I'm very I'm very pleased uh with the outcome. >> Yeah. Um okay.
21:33
So so I guess let's just kind of go through uh each of the animals.
21:37
Um maybe maybe let's just start with with some of the more obvious ones, the ones we've talked about a lot on the show.
21:43
Uh so so let's start over here with with the piggies.
21:45
So here here we see the pigs at the at the slop trough. >> Um >> who's there? Who's there?
21:50
And so this is uh probably this is just labeled as meta.
21:54
You can imagine a lot of people here, right?
21:55
You could you could see Sora here. >> Sure. >> Um >> Bill Peebles.
21:59
>> Bill Peebles could be uh you know >> eating some slopet vibes. >> Yep. >> Makes sense.
22:06
>> I mean just like broadly AI in general, some people think basically all AI is slop. >> They do. They do.
22:11
There's been a lot of criticism. >> Yeah.
22:14
But I think that one's fairly clear.
22:15
Uh >> you don't want to be at the you you don't want to be the pig of the slop trough.
22:19
Although sometimes, you know, maybe the the profitability of being a slop farmer uh is underrated.
22:26
Obviously, uh America has a lot of pigs that live at the trough.
22:33
They eat from the trough.
22:35
They eventually the pigs go to slaughter. They become bacon.
22:37
They are sold into the economy.
22:38
You can make a good living as a farmer who That's right.
22:43
right. who maintains a >> and then there's the Jeremy Gon take which is we hate slop now because we know that in a few years it will no longer be slop out uh don't count out the piggies yet this is the sloppiest slop will ever be >> true that's true okay who else is on this
22:59
>> so then let's move up let's see we have the hen house here and so and who's in the hen house is the fox >> the fox >> right and so so this you can say is kind of Oracle in same right oracle is the is the hen house let the fox they're letting the fox in a a little bit >> potentially. >> Yeah, we we'll see what what you know
23:14
>> Yeah, we we'll see what what you know when what ends up happening.
23:15
But >> again, now that I'm looking at this image, the fox isn't actually in the hen house yet.
23:22
He's >> kind of circling it.
23:23
He's circling the hen house.
23:24
And there's a question of of how how how far into the hen house has the fox.
23:30
>> And I think it's it's notable that the chickens don't seem too disturbed yet. >> Yes. Yes. Yeah. Yeah.
23:33
They're getting along because the fox could just be browsing, could just be stopping by. Could be friendly fox. Friendly fox.
23:38
Um but but of course uh it is I if you have a if you have a lot of cash flow as a big company, if you have the ability to borrow uh billions or hundreds of billions in the debt market, uh you have to protect your hen house because that's right, foxes might come by and might want to might want to use you to cosign a loan. >> Yeah. Um okay.
23:59
So then we see the cash cow. >> The cash cow. >> This is Nvidia.
24:02
The only profits in AI >> for a long time.
24:06
I don't know if anyone has really unseated them.
24:08
They're certainly the most profitable by far.
24:10
Uh I think uh for a long time they were making more than 100% of the profits across everything.
24:18
Everyone else was losing money. >> Yeah.
24:20
Now you're starting to see maybe some cracks with TPUs, but even then I mean they're they're still >> it's still a cash cow.
24:25
We just saw they just beat Yeah. They just beat earnings.
24:28
I mean we have we have an article here from the journal.
24:30
Nvidia results fail to quell AI worries.
24:32
[laughter] >> Not enough people are milking the cash.
24:35
>> I gave you the perfect quarter.
24:36
>> Or maybe maybe the >> I gave you the perfect quarter.
24:37
I know you still sold off >> 60 billion or something in revenue.
24:41
Um yeah, I mean maybe maybe the the cash cow has been over overly milked and is out of milk at this point, but >> I think it's still producing.
24:50
>> I think it it does seem like it's still producing.
24:51
That looks like a healthy cow to me.
24:52
That looks like a the crown on the cow in particular definitely helps out there.
24:59
>> All right, moving over.
24:59
What do we have going on here?
25:01
>> So So here we have the bull in the China shop and that's Elon.
25:02
I think there's a couple ways you could read into this.
25:06
Um, so Elon, uh, one is just kind of on the maybe the the data center infrastructure side where he's he's kind of the bull.
25:12
He's, uh, imagine that you're a contractor and you're building data centers for for these companies and then you see Elon come in and he does it in in eight months.
25:19
What took you in a year and a half? >> Yep.
25:21
>> He's kind of messing up your world, right? Totally. Totally.
25:23
>> He's like, "Oh man, this this bull he's he's messing up my my business.
25:25
I need to be working way harder, way faster because >> he's also shipping features so fast."
25:30
like like before people could even have a discussion over adult content, it was like boom, Annie, here it is Valentine so fast.
25:38
>> This is the other way you could say he's the bull because there's kind of this maybe unspoken unspoken rule between the model companies where it's like okay we don't want to go too hard into the the companion uh you know space.
25:48
companion uh you know space. there were companies doing that but they weren't uh it wasn't the opening eyes it wasn't the anthropics wasn't the the Geminis and then now you see >> now you see a frontier model actually moving into their >> you know Grock is of course the
26:01
maximally truth seeeking LLM just yesterday I was asking Grock who is the strongest CEO in tech and it told me that Elon Musk is the strongest by far and it actually compared him to a bull said he was stronger than a bull and that he could beat a bull in a fight if he went headto-head with his bare hands >> absolutely Right. >> Yes. Absolutely right. >> Yes. Absolutely right.
26:21
>> Exactly [laughter] right.
26:22
>> What else is going on here?
26:24
>> So then I bet Claude would agree.
26:24
If you really pressed Claude on it, they'd say, "Yeah, I I you're absolutely right."
26:30
>> You're absolutely right. Who else is going on?
26:32
>> So, let's move down here.
26:32
We We have the the lipstick on a pig.
26:34
[laughter] >> Um and I think this you could say is um Apple Intelligence, >> right?
26:40
I mean, although I feel like this is actually almost flipped a little bit, right?
26:44
Because the the pig is usually like the ugly thing and then you add the makeup to make it look nicer.
26:47
But well, I think that's what they did here, right?
26:50
They took a bad model and they dressed it up and they said it was great and they said you should buy a new iPhone because of it and the model was bad >> and and there's no amount of marketing that is going to like change public perception once the product uh hit the market.
27:04
You could also run the the the pig is the privacy focused iPhone ecosystem that is um pretty difficult to just run in and throw AI on top of.
27:15
Like Apple has been building a brand around we don't access your data.
27:20
We don't store your data.
27:22
We would never train on your data.
27:24
And and that put them in an awkward position where they couldn't just snap their fingers and deliver a great AI experience.
27:29
Whereas Google has been, hey, you know, we'll give you Gmail for free, but we'll also, you know, probably train on wherever you go on the web and try and understand and and route ads to you appropriately.
27:40
Meta was in a similar position.
27:42
And so those two companies were a little bit more equipped to just on day one go and go and deliver AI features.
27:49
Uh Apple had to put lipstick on their pig, which is their privacy focus.
27:54
>> It was definitely more of like an afterthought.
27:55
It was more of a kind of shallow integration, you could say.
27:56
And then hopefully we'll see with the marketing The marketing for Apple Intelligence felt like they were it was it felt like a lot of makeup on top of something.
28:05
It was not a lot of it was not a foundational rewrite of iOS in any way.
28:08
It was not a lot of substance.
28:08
It didn't feel like an entirely new thing.
28:11
It just felt like little lipstick all over the place. >> Yeah.
28:14
And then uh before we go over there, let's let's go up here. We have the rooster. >> Yeah.
28:18
That's >> This is Jordy calling the top >> every morning. Every morning.
28:23
>> Every morning he wakes up. He comes on the show. 11:00 a. m. Sharp. He calls the top.
28:26
He says this is it's actually over now.
28:29
It's so over it's never >> call the top every day.
28:31
Eventually you'll get >> Eventually you'll be correct. >> That's true.
28:34
>> Eventually you'll be correct. >> Okay. What else do we have?
28:36
>> So then we have the dark horse. >> The dark horse. >> And this is SSI. >> Okay.
28:40
>> Um we're still yet to see anything really from SSI >> just charging around in the background. >> Yes. >> Yeah.
28:46
Kind of this figure >> still hanging out there.
28:49
>> It's kind of I mean like so so the big kind of departures from OpenAI it was Mir Maratti and and I you could say and Miriam Marott's company think machines.
28:57
I mean they're they're >> she's raising up rounds.
28:58
They have they have blog posts.
29:00
>> Yeah, >> they do actually have a product. They do have a product.
29:02
>> Let's hear it for >> Why did you tell me earlier?
29:07
Why Why would Why'd you bury the lead? They have blog posts.
29:13
>> They They're good blog posts. I like that.
29:15
>> So, in a couple years, we could be seeing vibe reels.
29:16
Is that what you're saying?
29:17
We could be seeing launch videos.
29:18
>> So, they do have a product, right?
29:18
It's like RL fine tuning. >> Watch your head. There's a hoof.
29:23
[laughter] >> The horse is really really about to hit you. Okay.
29:25
Um, so but I mean they're not really dark horse like you can they're a bright horse.
29:31
>> I don't know if that's a a phrase but like you can see what they're doing or or a beautiful >> they're a unicorn 50 times over. >> 50 times over.
29:39
>> Yeah, >> we didn't put a unicorn on here. That's an animal. Wow.
29:40
May maybe for the next certain point I couldn't add anymore.
29:43
It would just >> it would get too sloppy.
29:47
>> Okay, what else do we have?
29:48
>> Um going on the Aura Farm.
29:50
>> So So here here we see another horse. Yes.
29:52
And there's two ways you could look into this horse, right?
29:53
One is is this phrase look a gift horse in the mouth. Yes. >> Right.
29:57
Do you want to explain this, >> John? Yes.
29:58
So, do you know this phrase?
30:01
You don't know this phrase, looking a gift horse in the mouth. Okay.
30:02
So, looking a gift horse in the mouth is uh if someone gives you >> that's like a term that was thrown around in the 80s. >> Yeah. Yeah.
30:09
This is this is back in my day. Back in my day.
30:11
So, uh obviously uh I just giving someone a horse, a horse is a valuable asset today, but also hundreds of years ago.
30:19
It's always been a valuable tool on the on the farm.
30:21
Um, and the way that you assess the quality of a horse, one way to assess whether it's been taken care of, whether it's healthy, is to look in its mouth. Look at the teeth.
30:33
>> Never look a gift horse in the mouth.
30:35
>> No, never looked to get Never look a gift horse in the mouth.
30:37
>> Oh, because it would be offensive.
30:38
>> It's offensive gift after you get the gift later. Imagine.
30:40
Imagine if I got you a GT3 RS and you're like pop in the hood and you're like, "Oh, can I track this?" >> Yeah. Yeah. Yeah.
30:48
You're feeling the tires.
30:50
Oh, I don't know about this. It's not that good.
30:52
Instead, only has it only has 2,000 miles on it, but they're around the Nurburg range. >> Exactly. Exactly.
30:57
That would be looking a GT3 RS in the in the tread.
30:59
You don't look in the tread because uh you know, yes, if I gave you a horse, just be happy that I gave you a horse.
31:05
You know, don't look don't look in the mouth. Don't assess it.
31:09
And so what's happening with that?
31:11
>> So yeah, it's like you're not expressing gratitude.
31:12
And so I think this these are just the public market investors, right?
31:17
We've been given this gift of >> why are they selling their stocks right now? They've been giving.
31:20
They need to be buying >> this beautiful gift and they just don't want it.
31:24
They're selling their videos down.
31:27
>> They beat earnings, guys. Why not?
31:29
>> They need to be buying the dip.
31:29
They need to be buying more.
31:30
They need to be levering up.
31:31
They need to be going further into the public markets with every dollar they have.
31:36
>> Not financial advice at all.
31:39
>> But instead, they were looking at gift horse in the mouth saying, "Oh, can can the can Open AI afford the all the different 1.
31:44
4 trillion the guy for the job?
31:47
Is is the Google, you know, is Google set up to to, you know, actually take advantage of AI?
31:51
They're they're digging in a little bit too much.
31:53
They should just be happy that they've been given AI the next mega trend. >> Exly. Exactly.
31:58
So, also the horse could be a workhorse.
32:01
>> A workhorse, >> right?
32:01
And so, I think you could say this is Amazon.
32:03
It's a bit hard to define Amazon's AI strategy, right?
32:05
Part of it is they're building data center philanthropic, but they're definitely not getting uh overly ambitious.
32:11
They're not like, you know, getting over their skis.
32:15
Um, but they're just doing the hard work.
32:16
They're building the data centers. They're serving >> Yeah. >> serving models.
32:20
>> Maybe not fast enough.
32:20
They might not be building the data centers fast enough.
32:23
They might not be super aggressive.
32:25
They're not they're not they're not show jumping.
32:27
>> They're just they're just dragging the plow.
32:29
They're just consistently dragging the plow.
32:31
Old reliable Amazon's cooking along.
32:34
Um, they're they're they're staying out of the they're staying out of the slop trough.
32:38
They're not doing a deal.
32:40
Amazon has not done a deal yet with OpenAI for the agentic commerce thing.
32:44
Maybe that changes, but uh for now they're just plotting along. Who else we got? >> Exactly.
32:48
Um let's go to the black sheep. >> The black sheep. >> So black sheep.
32:51
There's also a lot of people that could fit in this. Yes, of course.
32:54
Um but I think maybe Carpathy is one of them. >> Yeah, Andre Carpathy.
32:58
>> Some of these contrarian contrarian takes about um maybe just the decade of agents.
33:02
Not >> to be clear, we're not calling him a sheep.
33:04
He's not >> it should be more of a black wolf. >> Black wolf.
33:07
But the idea is that he's standing out.
33:09
a lot of people in his in his class of of ultra respected, you know, uh, technologists, some of the, you know, most experienced.
33:18
He's really been at Tesla. He's seen the AI wave.
33:22
He's been working in it for decades.
33:24
He's really worked on this.
33:25
>> He's printed off of it. >> Yeah. He's done so much.
33:27
>> He's not sitting with the rest of them saying, "Oke, but he broke rank.
33:28
Even though he's worked at OpenAI, even though he's worked at Tesla, he broke rank.
33:34
He went on the Dwaresh Patel show and said, "You know what?
33:36
I think we're more in a decade of agents.
33:38
I think AGI might not be right around the corner.
33:41
Uh he took a contrarian stance at a very uh controversial time and he uh but it was not Yeah.
33:50
>> And he popped the bubble with it.
33:51
>> He basically popped the bubble with it.
33:52
Maybe the elephant in the room the elephant in the room is is is was in my view really more of the 1. 4 trillion. Right. That was the question.
33:59
That was the big question.
34:01
That was what everybody wanted to talk about uh or or at least understand better.
34:05
Brad asked the question and it's been uh downhill ever since. >> Yes. And it is Yeah.
34:12
The elephant in the room is is in every conversation, every every financing round at this point. Exactly.
34:18
[clears throat] Uh is is this I is this deal predicated on a continuation of exponential growth in investment in everything?
34:25
Like how much more how how risky is this uh relative to the amount of froth in the market? >> Yeah.
34:33
Never never ask a a woman her age, a man his salary or a a a lab founder how they're going to spend 1. 4 trillion. >> Yeah.
34:44
>> Or how they're going to pay for it. >> Yeah. >> Yeah.
34:46
>> Y >> who else we got on here?
34:48
>> So then uh in the top right we have the bird's eye view. Yes.
34:50
>> So I thought this Yeah.
34:50
This is situational awareness. This is Leopold.
34:53
>> It's the perfect name.
34:55
>> He has the situational awareness.
34:56
>> He's seeing everything.
34:56
He's kind of the master of the board.
34:59
>> He's taking his bets and he's been doing pretty well off them. >> Yes. Yes. Yes.
35:02
Um yeah, that one's pretty self-explanatory. Yeah. >> Okay. So, so then we go down. We have uh Lion's Share.
35:07
>> The Lion Share, >> right? This is Satia.
35:08
Satia has taken great uh position.
35:12
>> I'll take I'll take I'll take I'll take a third of the company and you can give me 250 billion and I'll take 20% off the top >> and I'll take all the IP >> as well. Everything.
35:25
>> I I'll also take your chip and I'll make it my chip. >> Your chip is my chip.
35:28
The entire contract was basic the entire OpenAI Microsoft deal is basically could just be summarized in one line. I get the lion share. I get the lion share.
35:39
>> And that's what he did. It's fantastic. >> Incredible. Incredible dealmaker.
35:41
So, let's go down here and we see >> and we can zoom out a little bit. >> Yep.
35:47
>> We see uh monkey business.
35:47
These are the podcasters. >> That's us. We're having fun. We got props.
35:52
We got all sorts of stuff. Sound effects.
35:55
Um, we need we need some we need some monkey sound effects on there.
35:59
We have a bunch of uh of animal themed sound effects we need to have more fun with.
36:03
Anyway, um >> um and then maybe let's go into the pond.
36:06
We have the sitting duck.
36:07
>> Yes, the sitting duck is is incredibly cute.
36:10
>> So, so Reddit uh >> why were they why why was Reddit a sitting duck? >> Yeah.
36:14
So, I think they brought >> It's because whether or not you have a permit, you're getting you're getting like the the hunters are going to get you.
36:22
I think I think Alexis O'hane sort of laid this out saying that uh that when when Reddit did the deal to give the data to OpenAI, they didn't realize how valuable that data was going to be and that relationship has grown grown grown.
36:37
Um and so they were kind of the sitting duck just sitting there.
36:39
They didn't really kind of got caught off guard.
36:42
Maybe could have trained their own model on their data internally.
36:46
maybe could have, you know, maybe had something that was more uh more of a valuable resource uh where they they would have had more le leverage if they'd waited a little bit.
36:53
But >> it is crazy that Coreweave and Reddit are sitting at roughly the same market cap now. >> Very interesting. Yeah.
37:00
Which one is more valuable over the next couple years? I don't know. >> Yeah.
37:06
Yeah, I mean I feel like Reddit has mostly been, >> you know, they've kind of already gone out to the slaughter in a sense.
37:10
Like every model company has trained on >> you think so, but look at the market cap. It just keeps going up.
37:15
Like I Reddit's been I mean Reddit was sold for $5 million or something when it launched.
37:23
Like it's been >> it was 10 it was 10 to NAS 10 to NAS.
37:27
That's a crazy crazy low valuation.
37:27
That's a crazy crazy low valuation. and then eventually spun out and then for a long time it was in the hundreds of millions and no one was thinking this is a tens of billions like for a long time like people the narrative was not oh yeah this will be orders of magnitude more than snap >> no way no way and then and then it just
37:44
sort of finally came together >> so then >> who's the headless chicken >> yeah let's go down a little bit and we have the headless chicken this is uh perplexity >> perplexity >> uh so I think um perplexity you know they have a lot of different strategies uh some of them kind of seem opposed to each other right maybe they're doing a browser. Maybe they're doing a Bloomberg
37:59
Maybe they're doing a Bloomberg terminal.
38:02
>> Maybe they're re rebuilding Yahoo Finance.
38:04
>> Maybe they're building >> the browser.
38:05
The browser to their credit, I do see more positive reviews of their browser than any of the other AI browsers >> from independent folks or from >> Yeah, independent independent people.
38:19
>> We've had a lot of investors come on the show and say like, I love the browser, but it's hard to take that seriously.
38:23
>> Every investor that's invested in a browser says their browser is the best browser.
38:27
No, I don't I don't listen I don't listen to what they say, but I I've I've just repeatedly seen people saying like the Perplexity browser is >> great.
38:36
>> Um so whether or not that means a win, but but the headless chicken thing going over and giving, you know, $400 million to Snapchat kind of uh uh you know, I don't know.
38:46
I think a lot of people uh good good for Snapchat.
38:48
Uh maybe >> there's just a lot of stuff going on.
38:52
It's the the the Snapchat deal, the trying to buy Tik Tok, trying to buy Chrome, uh launching a venture fund, uh Bloomberg terminal.
38:59
It's like, are you competing with all of these? Really?
39:03
You're going to beat Tik Tok and Chrome and Bloomberg and the next thing and see the next great company. Uh it is just a lot. It's a lot to process. >> Yeah.
39:13
Like Headless Chicken is kind of like a fun thing to watch.
39:14
And then people, you know, love to talk about perplexity.
39:17
They love to say like, "Oh, we're all short perplexity." That's true.
39:21
>> It's become consensus. Yeah. But let him cook. We'll see what happens. Be fun.
39:25
>> So then if we go down a little bit, we have the snake in the grass.
39:27
Have you guys ever witnessed a a headless chicken? >> No, I haven't.
39:33
>> Growing up in the country, I have.
39:33
It's >> You grew up in the country.
39:35
What are you talking about?
39:36
I thought you I thought you grew up with the East Bay Rationalists.
39:40
>> I was born in Berkeley, but I grew up in wine country. >> Oh, okay.
39:42
And I uh have uh fortunately unfortunately watched my father uh take one of the chickens, you know, every now and again.
39:51
A chicken needs to uh be >> uh to move on to the next chapter.
39:54
And as a [laughter] child, >> you sound like you're firing the chicken.
40:00
Like a very amicable split.
40:03
>> I mean, >> we're wishing we're wishing the chicken the best.
40:05
>> I mean, yes, it's it happens.
40:05
And I will say that that it is a real thing.
40:08
They run for, you know, at least uh 20 seconds or so. Yes.
40:17
Um and uh >> I'll never forget it.
40:21
>> Well, before we move on, let me tell you about cognition, the makers of Devon, the AI software engineer.
40:24
Crush your backlog with your personal AI engineering [applause] team. Okay, let's continue.
40:30
>> Okay, so next we have the snake in the grass. >> Snake in the grass.
40:32
>> This is the Chinese open source models, right?
40:34
These are kind of lurking.
40:34
Um I still don't really see that much coverage of Chinese open source models outside.
40:40
Nobody wants to talk about it.
40:41
>> Well, no one has bags, so they can't pump them.
40:44
>> It's kind of it's almost an it's a it's a elephant in the room to some degree.
40:48
>> Uh so so this is where I sort of disagree with you because uh snake in the grass feels like it's going to attack.
40:53
Uh elephant in the room means we got to address it.
40:56
It's like it's totally possible that the entire open-source LLM ecosystem is just like yeah, there's like a 10 billion dollar business there.
41:03
It's sort of like, you know, a a stalking horse.
41:06
another another animal-based analogy, but it's sort of a stalking horse for like, hey, uh, Gemini and and Anthropic, like if you guys don't lower your prices, we will go to the open source option.
41:19
And that's sort of what Linux how Linux works.
41:23
It's like that that you can kind of bid the closed source models against the open source models.
41:27
But for all like the doomer takes around like oh Chinese open sources like one day they're just going to snap their fingers and all the manurion candidates are going to activate in America and everyone's like I didn't realize I was using quen and now I believe that nothing happened on TN Square.
41:43
It's like I don't believe that.
41:45
>> It's more of a threat to the it's it's it's a it's a very real threat to the the business models of some of the closed closed source models >> maybe. I don't know.
41:55
>> It I I I I again it's putting a it's certainly a pressure.
41:59
It's it's uh Kimmy is hot on everyone's tails.
42:05
>> I mean Brian Chesky he was talking about >> Yeah.
42:07
Brian Ches the other thing is a soft power thing, right?
42:08
Ask it ask a Chinese open source model about Tanaman Square.
42:14
>> I just don't think that's going to be that big of a deal.
42:15
Like I I I don't I don't I don't I don't see those are two very different things.
42:19
like one is like Brian Chesky inside of open inside of Airbnb >> becomes a big deal if they proliferate all over the world and it's and and I'm not saying it's the end of the world. >> No, no, no.
42:31
>> No, no, no. What I'm saying is that is that with Tik Tok >> if you're a business owner like Airbnb and you're like Brian Chesky Airbnb if and you're deciding between Kimmy you know some open source model like deeper in the stack like you're not you're not surfacing something that has like
42:47
cultural relevancy or like or like uh some sort of like you know where American values come through like you're using it for like fraud detection or you're using it to like transform every Airbnb listing into like grammar check every listing that comes through like
43:03
spellch checkck it all like you're doing something that's very commoditized and it's not it's not this weird thing where you're going to inject the the like the the values of the Chinese people I I I I just see that as two separate things now now if you had a whole bunch of >> I just think that LM will be the new are
43:19
effectively globally going to be history books and if you have some control >> so that's true as the application layer I think at the application layer that matters so I would be maybe more worried if it was Oh, it turns out that uh OpenAI is going to just use DeepSeek now under the hood. >> Sure. I'm even talking globally. A bunch >> Sure.
43:36
I'm even talking globally.
43:36
A bunch of different application layer companies. >> Okay.
43:42
>> Use these models because they're they're cheap and good. >> Yeah.
43:45
>> And then they have like a a very specific point of view that's not necessarily aligned to the west.
43:50
>> I just think that point of view is irrelevant in many many automation uh use cases for business.
43:55
cuz I'm not worried about I'm not worried about Airbnb using Chinese models for for like business process automation. >> Yeah.
44:04
>> I also think you can I think you can probably kind of fine-tune a lot of that stuff out. >> Totally.
44:08
>> Um because like the the you know >> back to Perplexity they did it didn't they do Deep Seek 1776 or something like that. >> I also did that.
44:15
I did that actually before then but [laughter] so it's whatever but um >> it's whatever. Okay.
44:19
Now we see it's personal.
44:21
That's why you put perplexity there cuz you you got you got an axe to grind. >> Yeah.
44:26
I did it before they did.
44:27
>> But but like see square stuff is probably just a fine tune that they like made it more Chinese. >> Yeah. Yeah.
44:32
>> So you can just undo that. >> Yeah. Exactly. I agree. >> One would assume. Anyway, but uh Yes. >> Okay.
44:36
So we agree it's a snake in the grass, but unclear how poisonous the snake is, unclear the size of that snake. >> Yeah. >> Anyway, let's move.
44:44
>> Um let's move to >> who's the early bird that got the worm.
44:46
>> The early bird that got the worm. There's no sign here.
44:47
That's kind of an artifact of the of the Nano Banana Pro.
44:52
But um early bird that got the worm. This is Josh Kushner. >> I think so. >> Right. I like that. >> He got the worm. The worm was open AI. >> Yes.
44:58
>> He was very >> early investor. >> Early with size. >> Early size. Doubled down many times. >> He got the worm. He's the early bird. >> Incredible. [laughter] Yeah. >> Okay.
45:07
Uh why is anthropic donkey work?
45:11
[laughter] >> Donkey work. Donkey.
45:11
100% sure that this is like a real phrase, but apparently I was asking I coinage. >> I asked GT 4.
45:19
5 and I asked Gemini 3 Pro. Okay.
45:22
>> And they both said it was a real thing. >> Okay.
45:23
boring or laborious part of a job.
45:26
It's drudgery, donkey work. >> Yeah.
45:27
So, I I think there's a lot of ways you could do anthropic. >> Yeah.
45:31
Anthropic is all over the place.
45:32
>> So, so in this case, I I think it's kind of that Anthropic has gone very hard on coding >> um and API and enterprise. >> Okay. The laborious work.
45:41
>> It's kind of laborious. >> Yeah. Yeah.
45:42
They're not doing like the the really hot sexy like a browser solving science. >> Yeah.
45:48
They're not doing consumer science stuff. Yeah.
45:50
They're doing the donkey work. This is good. Okay.
45:51
I think it's some of the more laborious stuff, but but there's a lot of ways you could do >> Daria sitting there being like, who's going to take all the jobs?
45:56
[laughter] >> Who's going to take but you could do anthropic as um the scapegoat, right?
46:06
Uh David Sax really does not like anthropic. That's true, right?
46:10
They're kind of scapegoated a little bit.
46:12
They never get invited to the to the White House, right?
46:15
>> They're the the lame duck. >> Lame duck.
46:17
>> Is that a >> No, lame duck is when the president is a second term.
46:20
Forget about ugly duckling.
46:22
That's >> ugly duckling a little bit.
46:22
That's the one I'm thinking.
46:24
>> There's a little bit of chicken little the sky has fallen.
46:26
Scaredy cat about safety.
46:29
>> There's a few of these, but I like donkey work.
46:31
That that feels the most accurate for what they're doing.
46:33
They're going after the entry level white collar workers.
46:36
They're they're they're doing the donkey work.
46:39
Uh Google, I just love this image.
46:41
I >> This is the last one.
46:42
Uh Google is the fat cat.
46:45
>> Google is the fat cat.
46:46
>> Before we had Google snails pace, I think this would have been true maybe a year ago.
46:50
Fat cat's so much funnier. Look at that cat. It's so fat. >> I love it. >> All the cash flow. All the TPUs. >> All the TPUs. They're GPU rich.
46:57
They're they're they're rich in every in every sense.
47:01
They have a ton of researchers. >> They're releasing.
47:02
I mean, now they have the best image model, the best text model, depending on what what bench product you look at.
47:08
>> Um, >> they're on top of the world. >> Yeah. >> Okay. Slightly concerned.
47:10
We have a sign for golden goose, but there's no golden goose.
47:15
>> Goose was removed, but who stole the golden goose? >> Yeah.
47:19
Who killed the golden goo?
47:20
>> Or is there just no gold?
47:20
If there's no golden goose on the a in the AI barnyard, is that is that is that bearish?
47:27
>> I think one take uh maybe the golden goose. >> Wait.
47:30
So So first establish what the golden goose is.
47:32
The golden goose is a goose that lays a golden egg one every day.
47:36
And in the parable in the story, the farmer kills the golden goose to get all of the gold inside.
47:42
But it is revealed that by killing the goose, you no longer get the the uh the passive income from the golden eggs.
47:50
So it's uh >> Jack from the Beantock studied.
47:55
>> It's being it's being a little bit too greedy.
47:57
Uh but we couldn't land on who the golden goose was.
48:00
>> Maybe one take is the golden goose.
48:00
They were the neoclouds and then the market >> is hurting hurting is taking the goose away. Yeah. Right.
48:08
Cororeeve not in the past past what month they've been selling off a little bit.
48:12
continues to lay golden eggs, but the market got overheated and so that that that sort of killed the gains or something.
48:22
>> And the gold is the GPUs, subsidized GPUs.
48:24
>> I don't know >> in the data center.
48:26
>> It's not quite there's something with with the Bitcoin miners that just had a lot of energy that they that they had, you know, effectively prepaid for that they're unlocking some value from. >> Oh well. Oh well.
48:36
Uh >> but I think that's all them.
48:39
>> I think this is a Yeah, this is a pretty now it's pretty clear.
48:41
Th this helps you understand how AI is playing out.
48:45
>> There's no more questions. >> No more questions.
48:46
If you if you can if you can see this infographic, it really makes uh everything crystal clear. Crystal clear. [laughter] That's great.
48:54
Well, thank you for taking us through that.
48:55
Um, >> great work, Tyler.
48:57
>> And let me tell you about Adio, the AI native CRM.
48:59
Adios, scales, and grows your company to the next level and get started.
49:03
Um, one company that didn't make the cut for our infographic uh was of course AMD.
49:09
And fortunately, there is a great profile in the Wall Street Journal of Lisa Sue, the CEO of AMD.
49:16
>> And let's pull this up because this is a fantastic picture minus >> a very weird reflection going on.
49:22
Weird reflection in the glass.
49:25
And so if you zoom in on this, uh, it it there's something that is right in her nose that looks like a bugger or something.
49:31
It's a very odd choice of image.
49:34
Of course, it's just a reflection on the glass.
49:36
it's just a reflection on the glass. the the photo otherwise the the st like like her the way she's positioning herself >> it's powerful >> she did her job everything else everything looks great from her perspective she looks great the but the photographer just like didn't quite
49:51
catch that one reflection and so it it just gives a very odd look but anyway uh let's dig into the article the chip CEO staring down Nvidia and talk of an AI bubble uh at a board meeting in late 2022 Lisa Sue Chief executive of chip designer AMD announced that she was radically changing course. Quote, "I'm going to
50:12
Quote, "I'm going to pivot the entire company."
50:15
She told the directors gathered around a boardroom table at the company's Austin campus.
50:22
The rise of AI was a once in a-lifetime opportunity, she said, and the company had to put AI at the center of its entire product line.
50:28
Three years later, the Santa Clara uh Californiabased company has nearly quadrupled in size.
50:35
its market value rising from 90 billion to more than 335 billion despite a recent pullback.
50:41
AMD's strategy of positioning itself at the center of the global AI race has paid off handsomely, making Sue into a billionaire and her company into one of the only viable designers of powerful chips needed to power advanced AI models.
50:54
In a market that has recently been complete completely dominated by Nvidia, Sue is showing that there may be a place for a strong number two that can compete on >> insane flow.
51:05
By the way, check this out. >> Yeah, look at that. Uh, she's 56 years old.
51:10
She has a PhD in electrical engineering from MIT and a deep understanding of the physics behind her company's products.
51:15
She developed a reputation as a giant slayer by out competing market leader Intel a decade ago to take the lead in producing central processing units or CPUs.
51:24
Now she's staring down the ultimate Goliath in Nvidia, the world's most valuable company and the foremost maker of the chips that power AI data centers.
51:33
AMD will have to deliver on its promise to produce chips that are comparable to Nvidia's most of the >> staring down her own cousin. It is course true.
51:43
Investor investors bid up AMD's stock price in October after the company announced a marquee deal with Oracle and OpenAI which have both agreed to buy tens of thousands of AMD's newest generation of chips known as the MI450.
51:57
>> Ma says the Jensen Sue Thanksgivings must be wild.
52:01
>> I I I wonder if they're if they're close enough to actually have Thanksgiving.
52:04
>> Their first cousins once removed.
52:06
>> Yeah, I think at that point it just depends on how hard you go for Thanksgiving.
52:10
Some people have, you know, How big is your Thanksgiving? >> Do you go home?
52:14
>> I have I have a pretty small family.
52:15
>> I have a pretty small family, too.
52:15
On my uh my in-laws, but we're still doing we're we're talking 20 people, maybe is like a typical Thanksgiving.
52:22
Um >> and but I know there are some people that are like, "Yeah, let's get let's get a hundred people together.
52:27
Let's turn it into let's turn it into Woodstock."
52:30
Uh which which I'm down for, honestly. It's fun.
52:32
Maybe you need You know what you need to do this Thanksgiving?
52:36
You need to get everyone who's cooking for your Thanksgiving dinner on linear.
52:40
It's the It's the system for modern software development.
52:45
It's a purpose-built tool for planning and building products.
52:46
The product you're building this Thanksgiving is a beautiful, bountiful feast. It's a feast, folks.
52:52
And you need linear to help you plan who's doing what, who's making the pumpkin pie, who's making the cranberry sauce, can you assign tickets?
52:59
Can you close those tickets? >> Are you using AI?
53:01
>> Are you using AI agents?
53:01
Are you I think that there's something here.
53:07
Everyone wants to build coding agents.
53:08
Nobody wants to build feast agents.
53:08
And I think that's wrong. >> Get on linear. I love it.
53:12
Uh the OpenAI deal turbocharged the road map, said Sue.
53:17
Uh it represents a huge vote of confidence in the MI450, which of course we've seen from semi analysis is is performing very well.
53:23
Uh and AMD has caught up a ton this year.
53:26
They've just been on a tear.
53:27
uh taking feedback from all over the tech industry, integrating it very quickly and actually outperforming NVIDIA on with certain models and uh um uh all of that's been chronicled by the folks over at semi analysis in their inference max model.
53:44
So the growing AI market is a huge opportunity and we want to make sure that we have deep partnerships that enable to get us a big piece of that.
53:50
The rest will handle itself.
53:50
Uh the dealmaking was on display again this week when the company said it would work with Cisco and Saudi Arabian AI venture firm and a Saudi Arabian AI venture firm to build a large cluster of data centers in the kingdom.
54:02
Uh Sue attended a black tie I think so uh Sue attended a blacktie dinner for Saudi crown prince Muhammad bid Salman uh alongside other executives at the White House Tuesday and AMD sent a representative to a US Saudi Arabia investment forum on Wednesday.
54:19
Until now, data centers have mostly been entirely Nvidia's market.
54:23
Uh, one tech analyst said AMD is in a position to take a more meaningful piece of that.
54:28
So, one trillion dollars a year. Here, let's get into it.
54:30
At the heart of Sue's strategy is her belief that there is insatiable demand for computing power and that as the a as the market for AI grows, the companies offering the best and most reliable AI infrastructure will thrive.
54:42
She said she believes AI is a is not a zero- sum game and that recent concerns about an overheated market for chips and data centers are exaggerated.
54:54
In recent weeks, the massive spending on data centers have intensified concerns that an AI bubble is building.
54:57
AMD's stock, which had jumped nearly 60% in October, has fallen about 20% this month.
55:03
I'm not concerned about an AI bubble, Sue said in in the interview.
55:05
I do think that those who are thinking that way are a bit too shortsighted.
55:12
they don't really see the power of the technology.
55:15
>> It's actually only only down uh I I don't know exactly when this article was released but uh 13 and 3/4 uh in the last month. Yeah.
55:24
So >> better than better than uh some others.
55:28
>> This is not the time to stay on the sidelines and worry, hey, am I overinvesting?
55:32
She said it's much more dangerous if you underinvest than if you overinvest in my opinion. Let's go. I love that.
55:41
A year ago, [music] she predicted that the market for AI chips would hit 500 billion in sales annually by 2028.
55:47
At an investor presentation last week in New York, she was even more optimistic.
55:52
The market for AI and data center computing, she said, will reach one trillion a year.
55:56
Yeah, it's interesting that that she underpredicted or seemingly underpredicted because Jensen by himself is saying that he's >> that Nvidia has a line of sight to 500 in by in 2026 >> half a trillion and that's just for them revenue full year.
56:14
>> Yeah, >> that is a lot of money. Wow, very exciting.
56:17
Well, speaking of Nvidia, uh Sue is also helping to capitalize on an inflection point in AI.
56:21
Many executives in the chips industry, including Nvidia chief Jensen Wong, expect demand to shift from clusters designed to assist in large training runs uh to inference.
56:32
Um and they uh inference doesn't require chips with as much computing muscle as training does according to the Wall Street Journal.
56:38
Uh as AI models like Chacht and Gemini become increasingly integrated into daily life and as companies design thousands of enterprise software tools that rely on AI models, demand for inference functions is about to go up by a billion times.
56:50
Swang said last month, "Swang and Sue and Wong are distant cousins, but they didn't meet until both were established executives." That's interesting.
57:01
So, I don't think they'll be hanging out at Thanksgiving together if they're if they're if they just met recently.
57:06
But maybe maybe >> unless that's just a story and they've their entire both their family lines have been colluding to corner the the AI chip market for generations.
57:17
>> It it does feel like a a story line from Dune or something.
57:20
AMD has a strong line of inferencing inference computing chips, but has struggled to design chips powerful enough to compete with Nvidia in training. Um, let's see.
57:28
They're they're going uh they go into a little bit of her backstory.
57:32
She was uh Taiwan born, Queens raised.
57:35
Uh she worked for IBM where she focused on designing products according to the needs of big customers.
57:41
When she took over as CEO of AMD in 2014, the company had a market value of less than three billion. It's up 100x since then.
57:48
She did deals with Chinese partners that helped stabilize the company's finances and move the chip designer deeper into the processors that powered PCs and data centers, capitalizing on Intel's weakness.
57:56
Today, AMD sells an estimated 41% of data center CPUs, up from essentially 0% 5 years ago. What a run.
58:04
It was that success that allowed AMD's board of directors to trust Sue when she proposed in that fateful board meeting in 2022 to pivot the company to go head-to-head with Nvidia.
58:15
One of the board members attended said uh told this story.
58:17
She had a vision around our ability to be AI from endpoint to data center and everything in between said Tall Walker one of the board members who attended the meeting.
58:30
Uh she had the conviction of the need and the need to move fast.
58:35
What do you think about vision Jordi?
58:35
Is it good that she had vision?
58:38
>> I think vision is still underrated. >> You're pro vision. >> Pro vision. >> It's a hot take.
58:42
People Some people don't like vision.
58:43
So people are anti- vision these days.
58:45
Um I I think I land on the side of provision. I think it's important.
58:49
>> Uh Sue was able to dispense with Intel as a competitor because Intel had self-inflicted wounds, said Daniel Newman, CE of research firm uh Futurum Group.
58:59
That's in sharp contrast to Nvidia, a company that's expected more than 200 billion in revenue next year that has gotten thousands of AI developers hooked on the proprietary software that Nvidia chips rely on.
59:08
But Nvidia can't make enough chips to keep up with demand.
59:12
and the OpenAI deal proved that large AI companies are eager to diversify their supplier base.
59:19
>> We got some we got some major major update here on Lisa Sue as a celebrity.
59:24
Uh as AMD's become a bigger player, she's begun to embrace the spotlight earlier this year at an industry summit in Paris.
59:30
Sue was treated like a celebrity with many young women asking her to take selfies and sign autographs.
59:38
That's uh that's amazing.
59:38
We uh Jensen Wong was signing autographs a couple uh couple months ago.
59:44
That was this year maybe.
59:46
>> It was like five, six months ago. Yeah. That that one year.
59:49
>> Well, now she's now she's uh also signing um also signing autographs um as as the as the industry grows, more and more celebrities are minted.
59:57
Um well, in July, Sue attended an AI summit where Trump rolled out his AI strategy.
1:00:04
When she addressed the audience, Sue pulled out one of the company's chips out of her pocket and said it had 185 billion transistors and took him nine months to make.
1:00:12
Such chip can can cost tens of thousands of dollars.
1:00:15
Trump later mentioned her in his speech as one of the notable executives in attendance.
1:00:19
Uh she was still in the shadow of Wong, however, who Trump asked to stand while the crowd applauded.
1:00:26
"What a job you've done," the president said to the Nvidia CEO.
1:00:29
So he's like he's like thanks for Lisa Sue for being here but let's give it up for Jensen.
1:00:35
Well he's given it up too much for Jensen.
1:00:37
He's not having uh you know balanced approach.
1:00:42
>> Well I don't think it's it's necessarily his job to >> well 10 times the market cap 10 times the applause perhaps. >> That's right.
1:00:48
[laughter] >> Appla market cap weighted by applause. Um uh let's see.
1:00:55
Over the next decade, AI will transform every industry, every business, every product, every interaction.
1:01:00
Our chips are enabling this massive new revolution.
1:01:02
Um well, very very interesting.
1:01:06
Uh I'd like I would like uh to learn more about Lisa Sue as a celebrity.
1:01:10
I want to see more uh more deep dives, more page six style writing is what I'm looking for.
1:01:18
>> Maybe a New York Post cover. >> Exactly.
1:01:20
A lot of lot of caught on the street.
1:01:22
A lot of like you know uh like what what type of coffee does she like?
1:01:26
That's what we need to know.
1:01:26
Uh we need to get we need to get her in the mansion section.
1:01:29
Should we do some mansion section? >> We do. We should.
1:01:32
>> There's a big question in the mansion section today.
1:01:33
Uh first let me tell you about graphite.
1:01:35
dev code review for the age of AI.
1:01:37
Graphite helps teams on GitHub ship higher quality software faster.
1:01:40
The question I know everyone has been asking is is 200 million the new 100 million in luxury real estate? What do you think?
1:01:48
>> Many people have been asking that.
1:01:48
So, there's a $200 million house in Indian Creek, a $250 million house in Bair, a $300 million house in Aspen, and a $25 million house in Palm Beach.
1:02:00
And this is funny because I um we have uh we've reviewed like almost all of these houses.
1:02:06
We've actually >> Old Rock says Lisa Sue on Hot Ones. >> That would be great.
1:02:10
Uh maybe on Theo Vaughn as well.
1:02:12
A surge of ultra rich buyers has pushed asking prices to new extremes.
1:02:16
Yet many headline grabbing mega mansions languish on the market or trade for a fraction of their debut numbers just a decade ago.
1:02:22
The 100 million price tag was still considered a new frontier for luxury real estate.
1:02:26
The first nine figure home sale occurred in 2011. Wow.
1:02:30
Uh by 2019, there had been about 20 sales recorded at that price point.
1:02:35
Now, real estate insiders say a new price pricing benchmark is setting the tone for the high-end market, 200 million.
1:02:42
Uh, since 2025, at least five major US properties have listed for 200 million or more, mostly concentrated in South Florida.
1:02:49
On Indian Creek, a private island near Miami Beach, Florida, often called the billionaire bunker. Cosmetic surgeon Dr.
1:02:54
Aaron Rollins and his wife Meen Rollins listed their unfinished waterfront estate for $200 million earlier this month.
1:03:02
About 70 miles north in Palm Beach, a circa 2005 mansion, once owned by the late Frank and Moren Wilkins, is asking 205.
1:03:12
in Aspen, the longtime home of California billionaire Steuart and Linda Resnik, listed for 300.
1:03:15
The listings raised the question, is this aspirational pricing, or as the ranks of the global billionaires expand at a rapid clip, is the it possible that the market that the top of the market has actually doubled?
1:03:28
I would say yes, it's totally possible.
1:03:30
Look at the runup in the stock price.
1:03:32
The assets are uh more valuable than ever.
1:03:35
There's going to be a massive wave of wealth created from the AI uh boom.
1:03:39
Uh, and >> I would not want to be in the market for a single family home uh within 20 square miles of OpenAI. >> Yeah.
1:03:51
Uh, there was some post, I don't know if it made it in the timeline, but there was some post about uh there's like 40 people that are looking for houses in the 5 to7 million range in in North San Francisco and there's none for sale because >> all cash offers, >> I'm sure.
1:04:06
I'm sure from the from the liquidity.
1:04:08
Um, also Porsche allocations are going to be pretty rough out there. So, I I I expect it.
1:04:16
In the chat says, "Lisa Sue is a car enthusiast, drives a metallic blue graphite Porsche." >> I like that.
1:04:22
>> Um, she apparently names them after her uh after her chips.
1:04:28
>> So, she has cars Ryzen, Epic, and Radon. >> That's cool. That's very fun. Um, yeah.
1:04:35
This uh Resnik uh this Bairhouse that's 250.
1:04:38
I I remember digging into him and he was uh part of the telecom build out in 2001 and so uh even though his company went bankrupt, he still wound up with a fortune that allowed him to buy a huge house.
1:04:50
You could think about the same thing happening in the AI.
1:04:53
>> Well, here's another note.
1:04:53
A AMD sponsors the Mercedes AMG F1 team >> uh which has a new co-owner uh the CEO of Crowd Strike.
1:05:08
Um, so all eyes uh on uh George's team this weekend.
1:05:13
Uh we'll see how they do under uh with their new co-owner.
1:05:19
>> Before we move on to their next story, let me tell you about Finn.
1:05:21
AI, the number one AI agent.
1:05:24
>> AI that handles your customer support.
1:05:26
The number one AI agent for customer service.
1:05:28
Uh Silicon Valley estate sells to mystery buyer.
1:05:30
I want you to guess who it is, Jordy. I don't know.
1:05:32
I want you to make wild guesses.
1:05:35
Wild >> in California Silicon Valley, a roughly 12 acre estate designed in classical Italian style has sold for more than uh for sold for 56 million.
1:05:46
You can take out there known as Via del Porato.
1:05:48
The property is located in Portola Valley, one of the country's wealthiest towns.
1:05:57
The sellers are venture capital investor Bandel Karano and his wife Paula Carano who built the estate after buying the land in 2013 for 13. 625 million. Property records show. Hm.
1:06:10
Have you looked up Bandel Karano and what deals he did to be able to afford such a wonderful house?
1:06:18
I would love to know the story of his venture capital work.
1:06:24
Uh the Kronos put the home on the market for $85 million in February.
1:06:26
Uh the most recent that was asking price was 65. It went for 56.
1:06:31
Uh it's the priciest home to sell in Portola Valley to date.
1:06:34
The prior record was 35 million for a 13acre estate.
1:06:39
The buyer who currently lives in San Jose searched for several years before purchasing the Portola Valley property.
1:06:45
Uh the but they didn't want to name the client.
1:06:48
The Coranos didn't respond to request for comment. Massive mess.
1:06:52
You got to get >> And Del Corano was an investor in Polycom, Inc. >> Wait, the Polycom? No way. That's amazing. Welld deserved.
1:07:00
Uh, one of the one of the most iconic conference call phones. >> We used to have one.
1:07:07
>> We used to have one on our desk.
1:07:07
It's probably in the studio.
1:07:09
It was a prop that we used for a long time.
1:07:10
I think it's in the back. We got to bring it back.
1:07:13
>> We never actually used it. We wanted to have it.
1:07:16
>> How long until somebody creates like an AI polycom? >> I don't know.
1:07:19
Um, yeah, we uh that's so crazy.
1:07:23
He he he did the deal in Polycom and made a bag. I love it.
1:07:26
Uh listing agent said uh okay, they built um after raising an old home, completing the project in 2021.
1:07:34
In addition, the roughly 23,000 uh uh 12,300t main house uh property house has a pool and pool house.
1:07:43
And then another unfinished 5,000t building has a ballroom and a wine celler. Wow. There we go.
1:07:50
>> Uh they designed property.
1:07:50
Uh he's a general partner at Oak Investment Partners, a venture capital firm with offices in Wilton Wilton, Connecticut, Menllo Park.
1:07:59
In 2024, the Coranos listed a nearly 2,000 acre ranch outside of Bosezeman, Montana.
1:08:05
Portoola Valley had a median sale price of 5. 5 million. Interesting.
1:08:10
Um what else is in here that we wanted to look at?
1:08:13
So there is there is some articles on San Francisco.
1:08:18
Uh what's going on there?
1:08:18
San Francisco is back after pandemic related struggles and growing up.
1:08:22
Affluent young families demanding space have elevated the 94127 zip code which is anchored by the walkable West Portal Village center uh and encompasses desirable residential neighborhoods such as San Francis Wood.
1:08:38
This westside pocket reliably offers a rare San Francisco luxury.
1:08:41
Detached single family homes with yards.
1:08:43
The suburbia in the city lifestyle has recently propelled the zip code to rival historically more expensive city enclaves. In October, its $2.
1:08:52
5 million median listing price was second only to the $2.
1:09:00
7 million median price in Premier Address Pacific Heights. Interesting.
1:09:08
So, there are a bunch of shops. People are moving in.
1:09:10
The median price per square foot is $952.
1:09:16
And the houses are moving.
1:09:16
37 days on the market is all it takes for the median house to find a new buyer. >> Pretty good.
1:09:23
Let me tell you about profound.
1:09:25
Get your brand mentioned in chatbt.
1:09:26
Reach millions of consumers who use AI to discover new products and brands.
1:09:31
Should we let AI ruin the M dash? I think the game's over. I think it's over.
1:09:38
I think AI has already ruined the M dash. I think it's ruined.
1:09:40
I think we have to move on from it entirely.
1:09:42
But Joel Stein at the Wall Street Journal has another take.
1:09:47
Joel says, "Don't let AI ruin the M dash and writes a defense of the newly controversial punctuation mark."
1:09:57
So, >> it's so funny because I m dashes are not even the way that I first identify a lot of AI writing.
1:10:04
Like, it it's often the >> it's not this, it's that that that hits uh way harder. >> Totally.
1:10:12
>> Uh Joel says, "A few weeks ago, my 16-year-old do 16-year-old son Llo, a student journalist, received a tip for his school newspaper.
1:10:19
A source had told him that the administration which had banned all use of AI had used it to write an email to parents.
1:10:25
The email in question was certainly boring enough to be written by Chat GBT, but it was also boring enough to be written by a school administrator.
1:10:33
We ran the text through two AI detection tools and both determined that there was a 0% chance a computer wrote it.
1:10:40
I don't know how a computer figures out if it's dealing with another computer, but I'm guessing it asks which of of nine photos are motorcycles.
1:10:48
So, why did this source think AI had written it?
1:10:50
Because the email contained M dashes.
1:10:52
The M dash, a punctuation mark a bit longer than a hyphen that denotes a long pause, has become the black light on the hotel sheets for AI shamers.
1:11:01
A sign that an >> black light on the hotel sheets is a good turn of.
1:11:06
>> Uh, a sign that an essay, a letter, or any kind of written work was written by a machine and not a human. >> Yeah.
1:11:12
>> The Mdash is now a GPTism and is not advisable unless you want people to think you're writing as an output of an LLM. Yep.
1:11:17
On Instagram, the beauty influencer Lux Jen warned that if people don't want to be accused of using AI, they should take out the chat GPT hyphen.
1:11:26
>> They just call it the chat GBT hyphen.
1:11:28
>> Last week, OpenAI CEO posted on X uh the following brag. Small but happy win.
1:11:30
If you tell ChatGpt not to use M dashes in your custom instructions, it finally does what it's supposed to do.
1:11:37
It's It's interesting that they just didn't release an update that eliminates it.
1:11:42
like they they seem to think it's a feature, not a bug, and they're asking people to kind of opt out of it by doing custom instructions, which I'm sure like one one% of the user base actually uses. >> Yeah, it's weird.
1:11:52
It's weird that they couldn't just uh have a custom instruction that goes over all of ChatGpt that just says like you don't need to not never use the M dash, just let's turn it down by 90%. >> Yeah.
1:12:04
Uh, all this M dash shaming has been upsetting because I, a professional writer, love, love, love an M dash.
1:12:12
>> And he uses a lot of M dashes.
1:12:13
>> In my writing, the chat chatbt tells me I use 11 M dashes every thousand words. >> Wow.
1:12:19
>> Other professional writers use them a lot, too. Four.
1:12:24
These numbers upon investigation could be highly inaccurate since I got them from Chad GBT, which explains one reason why my son's schools bans it.
1:12:30
But the point is M dashes are loved by professionals.
1:12:35
This is starting to make a lot more sense.
1:12:36
What is Chat GBT trained on?
1:12:39
A lot of professional writing.
1:12:41
>> They literally have a deal with the Wall Street Journal.
1:12:42
>> And so if it's used 4.
1:12:42
4 times more than in everyday writing, it's just going to come up a lot. >> Yeah.
1:12:49
I mean, if you if you tried to you have to give it some direction on like where what it's going to sound like. Yeah.
1:12:55
And if it just winds up being like, yeah, make it sound like a like a Reddit comment, it's like, okay, well, that could go all over the place.
1:13:00
That could be very very weirdly worded and it just would not be very consistent. >> Yeah.
1:13:06
Uh so the point is M dashes are loved by professionals. Why?
1:13:09
Because more than any other punctuation mark, the M dash is deeply human.
1:13:14
>> It's the breath marks of Emily Dickinson, the stream of consciousness of Virginia Wolf, the headclogging maximalism of David Foster Wallace, or the self argrandizing aides of Joel Stein.
1:13:27
It's also the mark of discretion.
1:13:29
When Holden Cfield tells his writer that he loves it when his classmates digress during a presentation, he says, "I don't like it when somebody sticks to the point all the time."
1:13:38
>> The boys that got the best marks in oral expression were the ones that stuck to the point all the time. I admit it.
1:13:42
And he admits it naturally with an Mdash.
1:13:47
Large language models consume a lot of the best writing out there, which is why they use Mdashes.
1:13:50
Unlike most people today who think a period is a rude way of screaming, AI believes in punctuation.
1:13:56
If there's anything to take away from the M dash scare, it's that we should use more of them because while most people can't find one on their keyboard and wouldn't know when to use it if they did. That's pretty funny.
1:14:05
Uh the mdash requires more nuance than a thumbs up, a heart, or an eggplant. >> Okay.
1:14:14
>> It's less jarring than parenthesis, but a bigger interruption than commas.
1:14:17
It's the length of an M which sets it apart from the boring, shorter N dash.
1:14:21
Oh, >> in the men's locker room for writers, we make fun of M dashes. >> Interesting.
1:14:28
>> Most of all, we should use M dashes because they are a declaration of humanity in the face of AI's onslaught.
1:14:34
If only ordinary people would learn how to use them.
1:14:38
>> Do you do you see this link shorter N dash?
1:14:42
For some reason, it linked to n-.
1:14:42
in and that website just goes nowhere. >> N dash. >> I don't know. >> Indian domain. >> I don't know.
1:14:52
That's just like a a mistake or something.
1:14:55
>> They they should correct that because n dash. in doesn't go anywhere.
1:14:57
Um yeah, I I I have never really used m dashes. I also I like this take.
1:15:04
I I I mean I agree with this. This makes sense.
1:15:07
He should defend the defend the castle.
1:15:08
Um the maybe the bigger tell to your earlier point is around that uh contrastive parallelism that it's not this, it's that.
1:15:19
That's what that's called.
1:15:20
and that uh contrastive parallel parallelism.
1:15:24
I was wondering about that and I went through a bunch of the old scripts that I'd written for YouTube and I couldn't find a single example of ever using that that style that structure.
1:15:33
I I would I've written a lot about a lot of different tech companies and I'd never said, you know, uh I've made a whole video about Nvidia in my Nvidia video.
1:15:44
I never say Nvidia isn't just a GPU company.
1:15:46
It's >> Google isn't just a search company.
1:15:48
I've never folding company of the future. >> Yeah. Yeah. I don't know.
1:15:52
I don't know how that got baked in.
1:15:54
I think that's maybe from marketing uh from like marketing lingo because I was trying to run the benchmark of does this uh contrastive parallelism creep in um more when you ask uh when you ask the uh let's see what is it?
1:16:13
It's uh antithetical parallelism or contrastive construction or correlative conjunctive conjunction pairs.
1:16:21
This is the term I learned this from from them.
1:16:23
Um but uh that antithetical parallelism.
1:16:26
It's not this, it's that.
1:16:28
Um >> we're not writing a story. We're never legacy.
1:16:33
And it just it has a sound that sounds like marketing.
1:16:35
It sounds like it sounds like marketing.
1:16:37
Like I feel like you could probably go through the New Yorker or the Wall Street Journal and you'll see a lot of M dashes market but you won't see a lot of antithetical parallelism and so I feel like the antithetical parallelism is an even bigger tell.
1:16:51
And Tyler, what do you think?
1:16:53
>> I also think it's interesting um like you would imagine that a lot of these like GPTisms Yeah.
1:16:56
uh would be um >> uh they would only be like with one model, right?
1:17:02
It's like just 40 does that work? Totally. Totally.
1:17:05
>> Uh but it's like not that at all.
1:17:05
It's also not um just like OpenAI models.
1:17:10
>> Uh like I yesterday I tried the Gemini 3 Pro and I asked write an ad for GT3 RS. >> Yeah.
1:17:16
>> And then [clears throat] so I I'll just read the start. Listen to this.
1:17:18
>> There's a moment at 9,000 RPM where the world stops.
1:17:21
The noise isn't just sound M dash, it's frequency.
1:17:23
The vibration isn't just an engine mash, it's a heartbeat.
1:17:28
Like it's like the exact same.
1:17:31
>> It's the very similar. >> It's very strange.
1:17:32
I I wonder um like why this is.
1:17:35
I like there's a case you could say that models are just like training off each other, but it seems that seems like not something that they're doing.
1:17:43
>> Um >> yeah, I don't know.
1:17:44
It's just kind of landed in this zone where that is what is seen as good or something. I don't know.
1:17:53
And and it's just like sort of decided that antithetical parallelism is the greatest thing.
1:17:57
So, uh, uh, thank you to, uh, Joel Stein at the Wall Street Journal for writing this article.
1:18:04
I will support you in your fight to keep the M dash, but I want to hear your take on contrast, >> but actions construction.
1:18:13
>> Actions speak louder than words, John.
1:18:14
Are you going to are you going to just rip like 20 m dashes in your next essay?
1:18:19
>> So, the the problem is that I I have never I'm the guy I'm the one who doesn't know how to find it on my keyboard.
1:18:24
I'm I'm who he's talking about.
1:18:27
>> Just hit dash dash space.
1:18:29
>> I find it on your keyboard and wouldn't know when to use one if they did.
1:18:30
I don't know when to use it.
1:18:32
I don't know where to find it.
1:18:33
I wasn't It wasn't taught to me in English class. I just never learned. >> I'll teach it.
1:18:38
You know, I'm teaching it to you right now.
1:18:40
Go on your keyboard dash space on iMessage and it will create it for you. >> Okay.
1:18:45
But when you >> do shift option dash >> shift option dash I don't know.
1:18:49
I think you can't teach an old dog new.
1:18:51
I don't think you can teach an old dog new tricks. I don't know.
1:18:55
I don't know if it's possible to to teach me to use an M dash uh like reliably.
1:18:58
I think I might just throw them in randomly.
1:19:01
What if I What if I start using like two M dashes next to each other? Just throw people off.
1:19:09
No one would expect that, right?
1:19:10
It's completely unexpected.
1:19:11
So, you'd be like, "Oh, well, like this looks like AI, but it's something weird.
1:19:16
>> Be a really bad model."
1:19:16
[laughter] >> Whatever model you used was terrible. GBT2 for this.
1:19:22
Uh anyway, uh let's move on.
1:19:26
Let's do some timeline and then I think I think we can come back to this article on solveny if we have more time.
1:19:32
But first, let me tell you about turbo puffer serverless vector and full text search build from first principles and object storage >> used by cursor notion linear anthropic >> 10x cheaper extremely scalable.
1:19:40
I like when we're talking over each other during the ad reads that that's really the flavor we want to bring through. I love it.
1:19:48
Okay, so there's a major shakeup going on at TBD Labs.
1:19:51
Medic Augustus Odina is out and I'm giving him a follow for this.
1:19:58
He's going he's going independent free agency.
1:20:01
>> Yesterday I resigned from TBD Labs uh/ MetaAI.
1:20:04
I wasn't there for very long, but I think I got a few useful things done.
1:20:07
an impressive group of people and it's especially impressive that it got assembled as quickly as it did with such a high talent bar at a large company.
1:20:16
Quote unquote founder mode is real and good.
1:20:19
I will certainly miss my co-workers there.
1:20:21
I think now is an unusually high lever time to pursue ambitious new projects at the intersection of AI and other technologies.
1:20:29
Please reach out to me if you're interested in that sort of thing.
1:20:33
and I expect I will have something more detailed to share in not too long.
1:20:38
>> Is that the sound of a thousand venture capitalists writing term sheets with blank numbers on them?
1:20:44
>> Um I I messaged him yesterday and he said of the show would be honored to be on the show uh when ready to talk about it. >> Yeah.
1:20:53
>> Uh so looking forward to that. >> Uh Bernie Sanders. >> Okay.
1:20:57
What's happening with Bernie >> firing shots?
1:21:00
>> He's taking shots of the AI oligarchs.
1:21:02
He says, "Here are some of the most powerful o AI oligarchs in the world enjoying a private dinner with a dictator who murders his own citizens with a bone saw." Whoa.
1:21:09
Uh, "Does anyone really believe they want to wipe out poverty or improve life for ordinary Americans?" I don't.
1:21:16
And he's sort of mogging Greg Brockman here because he leaves Greg Brockman's net worth.
1:21:21
He doesn't even try and estimate it.
1:21:23
He just says question mark question mark.
1:21:26
>> What's Bernie Sanders age? >> Uh, 75. >> Guess again. 78. >> Guess again. >> 77. >> Guess again. >> 80. >> Guess again. >> 82. >> Guess again. >> I have no idea. >> 84. >> 84. Oh, he's up there. >> He's up there. >> Oh, wow. Okay.
1:21:45
>> So, grandpa is he's [laughter] pissed. >> He's pissed. >> He's absolutely.
1:21:50
>> What does that do with him not not being able to look up Greg Brockman, the CTO of Stripe?
1:21:54
Do a back of the envelope.
1:21:56
What's Stripe trading for in the private markets?
1:21:57
Call some secondary brokers.
1:22:00
get if you're Bernie, you just need to call a bunch of secondary brokers, understand where Stripe is trading, then work backwards from what his what his uh Stripe stake is, then call Sati Nadella, ask him based on are you marking OpenAI at 500 or do you think you should mark it more at like 400 or maybe 600? Are you bullish on that?
1:22:18
All of that goes into the DCF build a spreadsheet and then you would have a fair market valuation for Greg Brockman's net worth and you would need to use >> got pretty check got pretty close. 83 8 95 good work.
1:22:28
Um uh but you know if he really wanted to stick it to these American AI oligarchs, he could have used like Kimmy >> uh to yeah do the kind of analysis that you were talking about.
1:22:40
He would have gotten a lot closer. >> Yeah.
1:22:43
>> Uh I think we need I think we probably need to do more to define uh oligarch in the AI era, right?
1:22:50
the AI era, right? is does does uh >> does a does a a billion dollar >> people would use plutarch pluty plutoaucracy >> is a a person >> but what's plutoaucrat uh there's one that that's just means >> technocracy >> technocracy there's one that
1:23:08
specifically means wealth that's like wealth where the plureaucrats that's it right putoaucracy is >> I think plutoaucracy is uh plutoaucracy >> but also I mean does does Bernie not realize that Greg Brockman Government by the wealthy is plutoaucracy. Oligarchy is something else. Oligarchy
1:23:24
Oligarchy is something else.
1:23:24
Oligarchy >> that's just ruled by a few.
1:23:27
I think >> ruled by a few. Interesting.
1:23:29
A small people, a small group of people having control of a country, an organization or institutions. Well, um you know what?
1:23:38
You know what Bernie's got to do? He's got to start a lab.
1:23:39
Start a foundation model company and uh compete in the free market. >> I like it. I like I like that. Uh active retirement. >> Yes.
1:23:50
and then start trading on public. com.
1:23:51
Investing for those that take it seriously.
1:23:53
Multiass investing, trust is by millions.
1:23:54
Uh >> yeah, I don't I don't blame Bernie for being a little bit salty at this point because he's never on those uh charts of of the best political traders in history, right? He's true.
1:24:07
>> He's been having to sit there and watch Nancy Pelosi the most insane runs >> and he's just missed out. The FOMO must be crazy.
1:24:14
Every day he's opening up and Nancy's up another mill and he's just sitting there like, "Ah, I missed it. I missed it."
1:24:20
The trade of the century. >> Uh, >> Sam 3D. >> Meta.
1:24:24
We We talked about this a little bit. What? >> Yeah. A Tharva. Yeah.
1:24:28
>> Is uh hyped on Meta's uh new model, SAM 3D.
1:24:33
>> I I I forgot about this.
1:24:33
So, >> this was purposely released at the perfect time because we were just earlier accusing Meta of slopping it up at the slop trough with Meta Vibes.
1:24:41
You know, there's a little bit of a narrative that was emerging, which was like, okay, you know, Zuck did this whole talent war.
1:24:49
He acquired a ton of talent, clearly invested crazy amounts, huge gigawatt, 5 gawatt plan, Hyperion, uh, Prometheus. He's going all in on AI.
1:25:00
And then the first thing that he came out with was like Meta Vibes, this sort of like sloppy Tik Tok AI clone that didn't really break through and just kind of frustrated everyone.
1:25:09
on the timeline did not appreciate it, did not like it.
1:25:12
Um, and so at that point, I think everyone was was calling for, okay, you got to you got to deliver something that's actually solid.
1:25:18
You got to deliver something that's useful, that's valuable.
1:25:21
Maybe it's a contra contribution to open source.
1:25:23
Maybe it's a, you know, even just an API for coding that's really good or a model that does something unique, uh, you know, special or >> free ASI for everyone.
1:25:35
>> That would also be acceptable.
1:25:35
Yes, that would definitely reset the narrative on is is Meta slopping it up at the trough.
1:25:41
But this is an example of them not slopping up at the trough. This feels elevated. This feels useful.
1:25:46
I'm very excited for where this gets implemented all over the place.
1:25:50
This feels like a very serious organization, like the work of a serious organization, the work of a group that's taking uh their work seriously and not just trying to, you know, score points, go viral, just make a couple extra bucks.
1:26:02
They're actually doing some real research.
1:26:03
So, I was excited about this. What was your take?
1:26:06
>> Yeah, I mean this is really cool.
1:26:06
I think people have probably just overindexed uh too much on Vibes.
1:26:08
Y >> um because like I don't even really think of Vibes as being like an Alexander Wang project.
1:26:13
It's like it's not like they trained a new model. That's not their model.
1:26:16
It's just like a project manager made a new app. >> Yep.
1:26:20
>> So I I think um there's still like a ton of really good researchers.
1:26:22
I'm very excited to see what they actually put out because I I assume that it's going to be great.
1:26:27
>> And I and I it's hard to know without uh actually knowing the the usage of Meta AI.
1:26:32
You can you can look into it a little bit by just looking at the app store charts and seeing the kind of traction they have.
1:26:37
But I think in hindsight they would have just been much better off not releasing that or not making it a moment.
1:26:43
>> Dude, you you're telling me you don't like Meta Vibes, dog. What are you doing?
1:26:49
>> That is Trump in an orange uh and rainbow suit dancing. >> I thought we had PTZ.
1:26:54
I thought we could zoom in on this.
1:26:55
Uh yeah, I mean uh there's some there's some golden stuff.
1:27:01
You know what I was actually thinking about was um uh they kind of it's kind of a do nothing win situation, right?
1:27:07
Because I feel like uh at least this year the vast majority of AI slop will be consumed on Instagram.
1:27:12
Like no matter if even if it gets made in the Sora app, like it's coming over to Instagram if it's going to do well and it's going to be distributed on the other platforms.
1:27:22
And so, um, I I would be very closely watching the, um, the actual, uh, user minutes, the time on site, but I would imagine that the amount of Sora generated content, the the user minutes is like a hundred times on Instagram than on than on the actual Sora app just because it's such a bigger bigger audience.
1:27:43
And so even if even though it's made by Sora, it's distributed elsewhere.
1:27:46
Um anyway, um >> yeah, let's check in with the >> what's going on genius.
1:27:54
>> Sora is still number nine uh in the charts.
1:27:57
Uh Cap Cut and Teimu Shop like a billionaire are sitting just ahead alongside >> go wish your digital wish list.
1:28:07
>> Um >> well let me tell you about numeral. com.
1:28:11
Let numero worry about sales tax and VAT compliance.
1:28:14
Compliance handled so you can focus on growth.
1:28:16
Um >> luxury watch guy is concerned uh about the Bitcoin selloff because he says there going to be so many effing APS on the market. Face pal. [laughter] >> Oh no.
1:28:31
>> Uh flooding uh flooding uh the aftermarket.
1:28:35
So we'll see how that nets out.
1:28:38
But uh the cryptocurrency industry certainly has been known to enjoy an AP. >> Yeah. Uh Google's genius.
1:28:45
By not selling TPUs, Google allows Nvidia to maintain high GPU pricing which in turn props up price of inference.
1:28:53
Google then captures that inference price premium by running TPUs for inference on GCP.
1:28:58
This is a conspiracy theory by Dave 3 and 30 ter.
1:29:05
Um I'm not sure how real that is.
1:29:09
>> Yeah, there's there's also >> they are going to sell TP.
1:29:12
>> Just because you have two players in the market like doesn't mean you can sort of have a you know what happens in the soda industry, right?
1:29:18
But effectively like >> GLP1 market like there's just a lot of demand.
1:29:22
You don't need to cut prices the price. >> Yeah.
1:29:25
And you also understand that you can get in there there's uh can be reason not to get in a race to the bottom dynamic and effectively have a gentleman's agreement to keep prices in a certain range.
1:29:36
Of course that can go too far but >> well let me tell you about Vanta automate compliance and security.
1:29:41
Vanta is the leading AI trust management platform.
1:29:46
Um, do you mind doing some timeline while I quick break?
1:29:51
>> Uh, uh, Pier uh from cal.
1:29:51
com says, "Showerth thought.
1:29:56
Why is no one doing outbound for pizza?"
1:29:58
Hey, this is Gigi from Gigi's Pizza calling. You ordered last week.
1:30:03
We have a pepperoni pizza ready and could deliver it in 10 minutes. Are you hungry?
1:30:07
Tech sales guys has trillion dollar idea and of course uh it goes viral again.
1:30:13
some uh ideas uh and bangers are evergreen.
1:30:17
Uh Morgan Hel yesterday was saying, "I think the majority of societal problems right now are all downstream of housing affordability."
1:30:28
Austin asks, "How would you fix housing affordability?"
1:30:30
Uh uh the uh current admin has suggested uh uh uh 50-year mortgages.
1:30:37
We'll see uh how much of uh of we'll see if those go through and how much of an impact that they have.
1:30:43
But Morgan Hel says uh build more homes, plenty of demand, plenty of capital, mostly a local zoning issue.
1:30:49
Uh and that certainly certainly tracks living here in California.
1:30:57
John Palmer, dear friend of the show and somebody that we are actually working on a little project with, uh, says, "This might sound crazy, but they should pivot."
1:31:07
Uh, he's talking about Sunday Robotics, which make the, uh, cute new robots with, uh, with fantastic little hats.
1:31:15
He says, "This might sound crazy, but Sunday should pivot to a consumer app where you just teaoperate your own memo, which is the name of the robot, and meet up with your buddies and do fun stuff as robots." Uh, I agree.
1:31:28
I would uh I would love uh to meet up with the lads uh in the real world in robot form.
1:31:35
I think uh I think he might be uh on to something.
1:31:38
Um, uh, there was a story coming out, uh, earlier this week.
1:31:45
An investigation from the lever found that a PE firm is buying hockey rinks and banning parents from recording and taking photos of their kids' games.
1:31:56
>> Based >> this story broke [laughter] >> uh because they tried enforcing the rule on the wrong person, US Senator Chris Murphy.
1:32:03
Um uh so a little excerpt here.
1:32:08
As the $40 billion youth sports industry comes under private equity control, [laughter] corporateowned [music] facilities and leagues from hockey rinks to cheerleading arenas have begun prohibiting parents from recording their own kids sports games.
1:32:22
Instead, parents are forced to subscribe to these companies exclusive recordings and sc stream streaming service which can cost many times more than the streaming cost for professional sporting events.
1:32:33
That's so funny because uh I think this is >> I was thinking about how how like I uh I'm such a gear nerd that oftent times when I'm watching my four-year-old play soccer, I'm like, "One of these days I'm going to bring out these like PTZ cameras out here and like get the most cinematic footage and uh uh they're going to have to go up against me.
1:32:56
I'm going to be uh fighting them." >> Yeah.
1:32:59
Every kid sport team should have a a dad or a mom that's the CTO and their job is just to rig the entire uh uh uh field with cameras and then provide crazy edits for each kid after even if they lose.
1:33:14
It's like the one the [clears throat] one moment that they had, you know, they they finessed someone.
1:33:20
>> Um you still think this is bass, Tyler?
1:33:22
You still saying hello bass department?
1:33:25
I mean I I don't my mind's >> You appreciate value creation.
1:33:30
>> How else How else do you expect private equity firms to make money? Yeah.
1:33:32
How how else do you expect them to make >> hardworking private equity firms?
1:33:34
They need to make ends meet >> build uh you know afford their interest payments.
1:33:40
Uh in some instances parents have been threatened that if they chose to defy the rules and record the game, they may end up on a blacklist that punishes their kids.
1:33:48
Well, what they need to do is they need to form some sort of like union basically where they all say, "We all are going to film or none of us are going to attend and we're going to take our business elsewhere."
1:33:58
>> Those threats were even reportedly made to a US sitting a sitting US senator.
1:34:00
I was told this past weekend that if I live stream my child's hockey game, my kids team will be penalized and lose a place in the standings, said Chris Murphy at a public event. Why is that?
1:34:12
Because a private equity company has bought up the rinks.
1:34:14
So this he was trying to live stream his himself like he was just trying to set up a camera and live like how does that like at some point at some point I I I think the obvious solution here is parents can >> take as many pictures as they want. >> Yeah.
1:34:32
>> If I'm a parent I'm going to take some pictures but I would probably still get the recording.
1:34:37
>> I would probably still subscribe so that family members could watch. >> Yeah. Yeah. Yeah.
1:34:40
It doesn't compete in the free market. Let us both film.
1:34:45
Whoever gets the better vibe reel, whoever gets the craziest edit out of it is going to be able to sell it.
1:34:48
And if I can outedit you and I bring better gear than your than your private equitybacked, you know, videographer, um, you're uh I'm not I'm not paying I'm not paying for it.
1:35:00
Um, let me tell you about Figma.
1:35:03
Think bigger, build faster.
1:35:04
Figma helps design and development teams build great products together. You can get started. Uh, >> triple glaze.
1:35:09
Uh the uh every time OpenAI says anything, it gets turned into a headline these days.
1:35:17
Uh the latest one is that uh that the keyword start using sign lang.
1:35:22
But I guess even that >> even that would would still potentially get turned into a a headline. >> Yeah. I I don't know.
1:35:30
No, it's very finding something to I feel like I feel like people use I feel like if you went through um >> if you went through a variety of like earnings call transcripts from plenty of public companies.
1:35:45
CEOs say the word headwinds all the time.
1:35:47
They're like, "Oh yes, like this particular thing, the the tariffs, that's a headwind. Oh, this is a headwind.
1:35:54
Interest rates might be a headwind.
1:35:55
That might be a headwind.
1:35:57
Competition might be a headwind."
1:35:57
Like people throw this out all the time. >> Yeah.
1:36:00
If you say as a business that we don't have headwinds, you're not going to be taken seriously. >> Yeah. Yeah.
1:36:05
Um but Opening Eye has is somehow wound up in a situation where they're so priced to perfection that even just admitting that there might be more competition is like a massive news cycle now.
1:36:17
It's uh pretty remarkable.
1:36:19
But uh the the actual quote here is that uh uh Sam Alman warned of headwinds from resurgent Google.
1:36:25
This of course is a story that uh we've all been tracking through.
1:36:29
Gemini 3 temporary economic headwinds for our company.
1:36:34
>> Economic headwinds is pretty wild.
1:36:37
>> Didn't have to say put that part in.
1:36:39
>> I wonder how that's going to manifest.
1:36:41
Are people going to be unsubscribing from chatbt going over to Gemini as an app or are they going to uh is this on the API side?
1:36:47
The API side seems a little bit more like easy to like like slide around from one to the other.
1:36:52
It feels like OpenAI certainly caught up very quickly with uh with Codeex.
1:36:57
They were behind for a while then they caught up.
1:37:01
But now uh Google's um you know sort of out in front although anthropics doing very well.
1:37:06
It's all just like a variety of horse races some of the revenue should be stickier than others.
1:37:12
But uh when when the when the goal is 100red billion in revenue so fast um with with this serious of competition it is it is very very difficult.
1:37:20
He also said Chad GBT is AI to most people and I expect that to continue.
1:37:24
So Brand >> that is 100% accurate >> powerful element but uh not enough to eliminate all competitive threats. >> Okay.
1:37:35
>> He added I don't want this to be note to be a downer.
1:37:37
We are doing remarkably well as a company and I expect that to continue.
1:37:41
>> Um >> let me tell you about Julius AI the AI data analyst that works for you.
1:37:43
join millions who use Julius to connect their data, ask questions, and get insights in seconds.
1:37:52
Uh, what is this story of the FBI raising a bounty for a former Olympic snowboarder who turned alleged drug kingpin?
1:38:01
>> We love uh we love these stories.
1:38:01
We covered this guy on the show before. >> Okay. His name's Ryan Wedding. >> Ryan James Wedding.
1:38:09
>> He's married to the game, [laughter] >> is he? What does that mean? >> No. What? Ryan Wedding. Oh, Ryan wedding. Okay.
1:38:16
Yes, he's married to the drug deal game.
1:38:18
I suppose >> he's a former Olympic snowboarder from Canada.
1:38:21
He represented Canada at the 2002 Winter Olympics and men's parallel giant slalom. >> Whoa.
1:38:28
>> Uh after the Olympics, it is alleged that he became a transnational drug trafficker and orchestrated the murders of various witnesses. >> Whoa.
1:38:36
>> And he's only 44, so uh he's kind of uh just kind of hitting his stride.
1:38:40
Um he was added earlier this year, March 6, to the FBI 10 most wanted.
1:38:47
So he's in the top 10 >> from uh they have >> any idea where he is?
1:38:52
I wonder how we'd found hunt this guy down.
1:38:55
>> And and they they're saying he's running one of the largest drug trafficking operation and is believed to be the dominant cocaine distributor in Canada.
1:39:06
Um, so from the Canadian Olympic team to the Canadian nar narcotics trafficking MVP status uh and Bondi every the hard thing the hard thing is when they talk about like >> because drug kingpins have just been the stars of uh of of so many different great uh television show uh TV shows and movies.
1:39:31
Pam Bondi said he's the modernday iteration of Pablo Escobar.
1:39:36
[laughter] >> It's like somebody was about to turn him in, but they hear that and they're like, "He's too cool to turn in. Can't do it. It's not worth it.
1:39:43
I just got to be friends with this guy.
1:39:44
I'm living through history." >> Um Oh, wow.
1:39:47
So, after the 2002 Winter Olympics, he moved back to Vancouver and attended university.
1:39:52
He got into bodybuilding and started working as a bouncer.
1:39:55
After two years in university, he dropped out and began to speculate in real estate, which he financed by growing marijuana >> uh in a massive warehouse.
1:40:05
Uh he eventually expanded his operation and joined up with Iranian and Russian smugglers. >> Yeah.
1:40:14
>> And uh in 2010, he was convicted of attempting to buy drugs from a US government agent. >> Yeah.
1:40:21
>> And he went to prison for You know, there are so many startups these days that are going after Palunteers market, competing in enterprise software, enterprise AI for deployed engineers.
1:40:32
It's all a bunch of memes.
1:40:32
Everyone's everyone's keying off of the uh the Palunteer strategy.
1:40:37
I think if you're trying to play in that market, you got to take down a most wanted fugitive. >> Yeah.
1:40:44
>> You get the 15 million, that's your seed round, and you use this as marketing.
1:40:49
the company that finds this guy, I'm gonna believe that your model's pretty good.
1:40:53
Whatever you whatever you're doing, if you if you can find this guy, I'm gonna be like, "Yeah, yeah, that's a good that's enough of an eval for me. You pass the benchmarks. I don't care.
1:41:03
Your MMLU tell me how many how many fugitives have you checked off the FBI top 10 most wanted list?
1:41:09
That's what I want to see."
1:41:12
>> Uh, well, there's a documentary series in the making titled Snow King: From Olympian to Narco. >> Okay. Yes.
1:41:17
based on a on a rolling stone investigation. >> Okay.
1:41:22
>> So, >> Jack Alman says, "I heard the term forward deployed VC meaning investor who's helping a company and now I'm logging off for the rest of the year."
1:41:31
What's funny is like there used to actually be forward deployed VCs.
1:41:33
Uh what what's that uh Janentech story, right?
1:41:38
Uh who was the VC in in Janentech?
1:41:41
It was uh [sighs] uh who was it? I don't remember.
1:41:45
Um, Robert Swanson, a venture capitalist, met with biochemist Herbert Ber in 1976.
1:41:51
Um, there was I think it was either Sequoia or Kleiner Perkins.
1:41:57
Um, but one of >> Bob Swanson, I I believe was uh at Kleiner Perkins. >> Okay. Is that is that right?
1:42:03
>> Okay. Is that is that right? There was there was one example of of a VC who basically was in the office of the company every Friday and was basically just like their financial back office the entire time because the the team was a bunch of scientists who understood the
1:42:20
technology but did not really understand how to how to build the business and the forward deployed VC did really go in that's a lost art because we are in the era of like founder friendly let the engineer figure out everything let them hire like kind of hands off from the venture capital community. Um, so I'm
1:42:35
Um, so I'm I'm actually okay with the term forward deployed BC if it's actually forward deploying like like you can't just be like helpful.
1:42:45
You need to be like actually in the office >> of the show who's like basically like probably doing like actually 20 hours a week for one of his portfolio companies and has been for years.
1:42:56
I would I would give him the for deployed VC, >> but he would never call himself [laughter] VC.
1:43:04
>> Yeah, it would be a very bad >> matters.
1:43:06
>> Uh how about for deployed privy because privy helps you build on crypto rails securely spin up white label wallets, sign transactions, and integrate onchain infrastructure all through one simple API.
1:43:18
Peter Reinhardt uh is in the news.
1:43:18
This this article might be a little bit too long, so we might tell you to go read it.
1:43:24
But uh Peter Reinhardt says, "My lobbyists are very nervous about me posting this, but overregulation is working against us.
1:43:30
All the costs are astronomical to all to us all but hidden."
1:43:34
>> Uh there's one excerpt that I'll read. >> Yes.
1:43:36
This is the CEO of Charm Industrial.
1:43:38
Um and he has been uh going viral with a new uh new article about overregulation.
1:43:46
>> Uh and so he's giving an example.
1:43:46
So, as one example, one state agency asked Ravoy to do certified engine testing to prove that the Ravoy doesn't increase emissions of semi-truckss and that Ravoy must do the certification across every single truck engine family.
1:44:00
It costs $100,000 per certification and there are more than 27 270 engine families for the nine engines that our initial partners use.
1:44:11
That's 27 million for this one regulatory item.
1:44:14
And keep in mind that this is to certify that a device whose sole reason for existence is to cut pollution by 90% and which is uh uh done so across nearly 100,000 miles of testing and operations is not increasing the emissions of the truck.
1:44:30
It is a complete waste of money for everyone.
1:44:32
Um so so the Ravoy system attaches to the truck and adds as an extra battery pack.
1:44:40
It's a way to retrofit a a gas powered truck to uh to you know in include an extra electric engine.
1:44:47
Um there's something where I guess if you're if you're claim that you're reducing emissions, I don't have that much of a problem of you trying to certify that you're not increasing emissions because that's the base level for your claim.
1:45:04
Like your marketing claim, you're claiming that you're reducing emissions.
1:45:07
If you're increasing emissions, then you're doing the opposite of your claim.
1:45:10
Um, so there is something about like whatever claim you're making, you should be able to back it up.
1:45:14
But, um, the main thing is that, uh, 27 >> any type of system that requires you to spend $27 million just to get in the game. >> Yeah.
1:45:25
>> When you're, >> you would think that there'd be a better way to understand um the >> uh the actual impact of this.
1:45:32
I mean, there's so many maybe more efficient ways to deal with this, whether it's just like, okay, uh, how how widely deployed are these?
1:45:42
If they're making a hund00 million a year, take the taxes, do some independent analysis, pay for it yourself, and then decide. Okay.
1:45:50
>> Also, the question in this case is why does it cost $100,000 per certification?
1:45:54
Is there like a monopoly in the certification market? >> Absolutely. It's the government.
1:45:57
The government's the one that does the certification, but yeah.
1:45:59
Well, oh, oh, I I I thought it was an external I thought it was an external partner, but even then, it's hard to imagine that there's like a $100,000 of cert of services that goes into this.
1:46:09
So, you you should be able to cut that, you know, cut that cost >> uh pretty dramatically.
1:46:16
>> Um, >> before we move on, let me tell you about adquick. com.
1:46:17
Out of home advertising made easy, measurable.
1:46:19
Plan, buy, and measure out of home with precision.
1:46:24
Casey Hanmer has a big post here.
1:46:24
Should we run through some of this or Oh, you want to skip down to this one? Okay, here we go.
1:46:32
>> Got another one off cockroach.
1:46:32
Uh the uh private credit cockroaches have been scuttling around.
1:46:40
>> Uh this time, private lenders are swapping debt for equity in uh distressed 4840.
1:46:49
Um I am >> logging into Bloomberg so that I can actually read the article. 4840.
1:46:58
>> Private credit lenders are poised to take control of pallet company 4840 solutions about a year after providing 1.
1:47:06
75 billion of debt to support Summit Partners acquisition of the business.
1:47:09
A group of lenders including Antares Capital are set to take equity in 4840 under a proposed restructuring.
1:47:15
Other lenders include KKR, Black Rockck, Carile Group.
1:47:19
Uh the deal would shed 1 billion of liabilities from 4040 4840's balance sheet.
1:47:24
Uh in cases where borrowers were struggling with their liabilities, private credit firms are more frequently swapping their debt positions for equity stakes to try and prevent losses.
1:47:32
While swaps can produce upside, they also offer more unpredictable returns than direct loans.
1:47:39
Uh pretty crazy to be set up to to get a payment for the debt and then be like, "Yep, actually we're just riding with you on the equity side."
1:47:45
But it's happening more and more because it's better than the alternative of watching the company go out of business.
1:47:50
Uh, and so this is uh this was originally uh the cockroach phrase is uh that this poster is riffing off of is of course from Jamie Diamond who uh was >> uh identifying first brands as the cockroach and was saying usually when you see one there's more there are more cockroaches.
1:48:11
That was his whole point.
1:48:12
and uh and the Blue AL uh CEO, co-CEO uh executive team kind of fired back and said like, "Yeah, maybe [snorts] at JP Morgan, we're we're we're good."
1:48:21
Um and so they've been kind of duking it out, going back and forth here and here is highlighting another >> fairly concerning conversation with a buddy who has a uh pretty scaled company in the uh consumer package goods manufacturing space.
1:48:39
And he was saying that around a number of the people that he competes with in his category have have uh uh taken on so much uh debt from various private credit players over the last like five six years >> and a lot of that uh you know at least a number of them he thinks are just not going to make it uh out of the next two years without uh without a restructuring. >> So we will see.
1:49:06
Uh I'll let you read through this post from Will and then uh I'll be right back.
1:49:13
>> Will Manitis is on a generational run of long posts.
1:49:15
He says, "On becoming legible to capital, the most underrated factor in the success of firms is the degree to which they are legible to capital."
1:49:26
Defining this precisely is hard.
1:49:29
You know when you see it.
1:49:29
But an idea, a firm or a person is legible to capital, which he spells with a capital C, when by dent of their existence, capital forms behind them in excess.
1:49:42
Think of an idea being legible to capital as being magnetically charged to the capital markets.
1:49:46
Dollars are just attracted to you.
1:49:48
Allocators discuss it at co at cocktail parties.
1:49:51
Funds market it at their AGMs.
1:49:53
And Twitter discusses novel financing schemes to get more dollars behind the idea.
1:49:58
Becoming legible to capital is the single greatest superpower for a fledgling firm. Look at Ramp. Look at Cognition. Look at Leopold.
1:50:06
Look at Tony and Dan at Danny.
1:50:09
They these are all superhumans at being legible to capital.
1:50:12
It's worth noticing how ideas and people become legible to capital.
1:50:17
First, there's no divide between the CEO, management, and the idea.
1:50:22
The story is not that of an individual successfully and impressive uh of an of that of an individual individually successful and impressive individual bringing their talents to a new platform.
1:50:36
You can see these kind of puff piece stories in many companies that are illegible to capital.
1:50:40
The company is never about you.
1:50:42
For a founder to be legible to capital, there can be no air between them and the expression of the idea.
1:50:48
Their lives only matter in so far as they are building with intensity towards the pure form of the idea.
1:50:54
Second, the company can be understood fundamentally as an equation trade.
1:50:59
In a best case, the most legible companies grow as a superlinear function of dollars in the founders are highly verbal and can clearly articulate and understand the inputs to this growth equation.
1:51:11
Talent, capital, management, etc.
1:51:13
The companies that are most legible to capital and the management that runs them at their best feel like clockwork toys in the hand because by looking at them the levers of progress and output become immediately clear.
1:51:23
They are immediate smack you in the face expressions of an idea that is both small enough that you can feel the thing click around in your hand but cosmically large enough that the feel that the idea feels true in some sense beyond literal.
1:51:36
When the trade is immensely clear, every capital provider across the stack can immediately understand their role today.
1:51:42
but more more importantly their ability to scale to putting 10 100 ax the number of dollars into the thing as it reaches maturity.
1:51:50
Finally, a company becomes legible to capital when it is clear the entire firm from capital to management to talent is singing from the same song sheet.
1:51:57
They are all living their lives in expression of the same exact idea.
1:51:59
An idea I've stolen shamelessly from is is from Phineas Barnes, Finn Barnes, uh who was over at First Round now. He's at the GP.
1:52:09
uh is the chocolate cake problem.
1:52:11
Many firms have great inputs, eggs, chocolate, flour, some beautiful icing.
1:52:16
But management thinks they're cooking a sule.
1:52:17
Investors think they're getting cupcakes and talent thinks they're getting pound cake.
1:52:22
The companies that are most legible to capital are obsessive about chasing the tolerances between competing ideas of the firm to zero.
1:52:30
By becoming legible to capital, a firm not only can achieve singularity in the private capital markets, i. e.
1:52:37
unlimited free capital forever.
1:52:39
But more importantly, it can unify the secret that ignites it internally with the world outside.
1:52:43
When that secret is shared, there is truly no limit.
1:52:48
Jordy, what's your review?
1:52:51
>> Uh, I think of this in the context of like when you think about Elsagundo specifically. Yes.
1:52:57
and watching companies become more legible to capital over time and the momentum that starts to build where >> early on at the seed stage there's just like excitement around an idea in a team and then you watch as these companies like basically bifurcate into sometimes you can have a incredibly talented founder that really stops accumulating capital because the the sort of potential still remains unclear and they're not building that momentum. Yeah.
1:53:27
whereas another one that has the same quality of founder starts to build that legibility.
1:53:33
>> Yeah, I think there Yeah, Tyler.
1:53:35
>> I there's something kind of interesting.
1:53:37
We've been talking about this a little bit where um I think Jordy basically said this thing where it's like maybe the the the role of the CEO is actually to to separate like the valuation from like what it like kind of really should be.
1:53:47
So it's it's almost like it's uh less legible, right?
1:53:48
where like if you have um if you're in a sector like quantum or something and it's kind of very actually it's quite hard to understand what the fundamentals are.
1:53:57
>> That's actually where you get uh like higher multiples. >> Interesting.
1:54:01
>> Um so maybe that's like kind of uh against what Will's saying. >> I don't know. >> Yes.
1:54:07
How does the how does the how does the meme stock craze fit into that?
1:54:09
Uh the memeto the memeto craze is legible to a form of capital.
1:54:18
is legible to retail capital.
1:54:21
It is legible in the sense that the the retail stock trader, the meme stock trader understands how the stock will move on the basis of press releases, on the basis of uh viral moments, CEO comments, uh you know, enthusiasm like if you are if you are in a memetock army, the the legibility is derived from the power of the community.
1:54:48
The apes strong together.
1:54:50
Well, how many apes are there and how strong are they?
1:54:52
If you notice that your apes are growing >> roaches strong together strong together.
1:54:58
Um, as you as you um as you grow your ape army and you get get stronger and stronger, that's the nature of the legibility.
1:55:08
When I think of the examples that he's using, I I think of it almost more like just uh the the the checklist of questions about a business and the inputs and outputs with regard to the capital, but also, you know, once the TAM is so well established, there's no more questions about it.
1:55:27
It's like, well, of course, this is a trillion dollar industry if things execute well.
1:55:34
Well, of course, the team is the best one in the market.
1:55:35
We've we've we've tested every other team.
1:55:37
we've tested this idea and we've seen we have full coverage of the team.
1:55:42
There's no incumbent that's coming behind them.
1:55:44
We know we have the leading team and we know the market's huge.
1:55:47
And then also, are we sure that the gross margins are great forever?
1:55:51
Are we sure that this is monopolistic and or or not super competitive?
1:55:55
Are we sure that Google won't copy this and and successfully compete in that space?
1:56:00
compete in that space? Like so just getting super high confidence about you know however whatever framework you want to use whether it's all the questions in 0ero to one or five forces or whatever business whatever whatever spreadsheet or slide deck you want to see at your
1:56:17
firm when you're making an investment once you've checked that off with a company so many times that everyone's like yes this is the winner they're pulling away they're doing great they're a compounder the legibility of capital thing is important because you don't have earnings. You don't you're not in
1:56:32
You don't you're not in the public markets yet.
1:56:34
And so you need to become this like foregone conclusion and then run from 1 billion to 50 billion in the private markets.
1:56:42
And if you're if you're illeible and there's still this question about oh well like when are you shipping or what are you doing like how does this how do I put my money in and get my money out?
1:56:51
Um that and it's more of like a moonshot.
1:56:53
it gets a lot harder to just stack up.
1:56:56
>> And even at the early stages, it's still underappreciated that people will say like, "I have zero faith in this idea, but I'll still back the founder just because they're great."
1:57:07
And >> there is one way to become more legible to capital. Go to getbasel. com.
1:57:14
Shop over 26,500 luxury watches, fully authenticated in-house by Bezel's team of experts.
1:57:20
Get a hitter, put it on your wrist when you walk into that asset management firm.
1:57:23
They're going to whip out their checkbook.
1:57:25
[snorts] >> You know, you know that.
1:57:27
You know it's going to work.
1:57:28
You know it's a secret hack for >> um should we bring in our our first >> Let's do it. >> guest of the show.
1:57:34
>> We have Julia Steinberg, >> the legend.
1:57:38
>> Welcome to the show from Arena Magazine.
1:57:40
Everyone, good to see you. >> Good to see you.
1:57:44
>> Thank you so much for stopping by.
1:57:46
Thanks so much for coming down.
1:57:46
Nice to see that the studio is real, that it's not AI generated. >> It is real. It is real.
1:57:51
We are here in Hollywood bringing media back to Hollywood.
1:57:55
We appreciate you uh Are you the only ones left? >> We really are. >> We are.
1:58:01
>> We're in a huge com like complex. >> Yeah.
1:58:04
>> And not a to our knowledge, not a single other firm actually shows up every day.
1:58:10
>> I do have there is a there is a one benefit.
1:58:12
There are many benefits to being in Hollywood.
1:58:13
One is that it's in between where Jordy and I live, so it splits the commute.
1:58:17
The other uh benefit is that I think it should dramatically increase our chances of winning a uh a star on the Hollywood Walk of Fame because if the if there it is a lifetime achievement award, [laughter] you're truly in in incredibly rarified air.
1:58:31
You know, Frank Sinatra is there, Leonardo DiCaprio is a star.
1:58:36
You truly have to be at the pinnacle of your craft.
1:58:38
But if there is some bonus point for actually being in in Hollywood, I think we get we Yeah.
1:58:47
It increases our chances dramatically.
1:58:49
>> Lifetime Achievement Award of of Animal Analogies applied to artificial intelligence. >> Yeah. Yeah.
1:58:55
>> I wonder if they'll just start putting influencers on there. Like where is Alex Earl?
1:59:00
Why is she not on the Hollywood Walk of Fame?
1:59:02
Because that's what Hollywood is at this point.
1:59:05
>> Portoy made the most people angry of anyone ever.
1:59:08
Yeah, Portoi is I mean uh as you walk down the Hollywood Walk of Fame like yes, there are some absolute legends, but there are some other folks who are you know more mid-tier. Yeah, I would say mid.
1:59:19
[laughter] Uh and and so I would put influencers there.
1:59:21
The weird thing is that the influencers aren't in Hollywood.
1:59:24
So the question is like does the Hollywood Walk of Fame just wind up reflecting what's happening? Is it geoence?
1:59:30
Are the star Are the stars >> like when when does Mr. Beast become eligible?
1:59:35
Because he's in North Carolina.
1:59:36
Well, when are they going to do a Saudi Arabia? >> Oh, yes.
1:59:39
>> Hollywood Walk of Fame.
1:59:39
That's what I'm looking for.
1:59:41
>> Don't give them the idea.
1:59:41
They will definitely do one over there.
1:59:44
>> They should hire and open.
1:59:46
>> I bet the H I bet Hollywood as a Is Hollywood a city? I don't know.
1:59:48
But >> I don't think it's an independent city.
1:59:51
I think that's I think Hollywood.
1:59:53
There's obviously folks here that want to raise money.
1:59:55
They should franchise the name.
1:59:57
They should sell the rights to the name Hollywood and put a Hollywood in >> Saudi Arabia.
2:00:00
Saudi Arabia should just recreate every city in the world in the desert and then use it and then use it to incentivize movies to get made there. >> Yeah.
2:00:12
>> Bring uh bring culture to the desert.
2:00:14
>> Um >> that's what LA did. >> Yeah. >> Yeah. Yeah.
2:00:16
No, we've been to we've been to New York on the Fox lot here in LA.
2:00:21
They have basically a mini New York >> full re uh full like representation of of New York.
2:00:25
You can go film whatever you want there.
2:00:27
Uh anyway, give us uh give us an update since you've been on the show a few months ago.
2:00:30
What's latest in your world?
2:00:35
>> I you're fulltime at Arena Magazine.
2:00:37
>> I am full time at Arena Magazine.
2:00:37
We're getting ready to launch our upcoming issue 006 ode to Capitalism.
2:00:40
And that's all I can say.
2:00:43
More will be out next week.
2:00:46
So keep your timelines open.
2:00:46
I remember I was talking with Max.
2:00:48
I was like, "Oh, is like Thanksgiving week, is that a good week to launch?
2:00:52
will like more people be online or will fewer people be online because they'll be with their families.
2:00:57
And we had this whole debate about how online people were going to be during Thanksgiving week.
2:01:02
And the >> answer that we came down to is actually people are going to be more online during Thanksgiving week >> I think.
2:01:08
So >> they, you know, they don't want to be responsible for getting the turkey in or out of the oven.
2:01:13
They they don't want to argue with their family about Epstein files or whatever. So, >> yeah.
2:01:19
I wonder I [clears throat] wonder what the online behavior is because uh over Christmas uh like we noticed that that's when like the really crazy H1B dust up happened. >> I know. Well, I I'm Jewish.
2:01:27
I don't celebrate Christmas.
2:01:29
So, I was I had, you know, I had plans.
2:01:31
I had to go get Chinese food.
2:01:33
I had to go to movies and I was just totally offline.
2:01:35
And all my Christian friends or my friends who celebrate Christmas, they're hyper aware of the H-1B discourse.
2:01:39
or they could recite, you know, this person.
2:01:43
>> It was very odd timing because a lot of the tech podcasts were off for the holidays and didn't need to comment on it even though it was this like hot political issue that you would have expected most tech podcasts to touch on.
2:01:53
But then by the time everyone got back from New Year's like the whole the whole like you know dust had sort of moved on.
2:02:00
So >> well maybe that's good because the H-1B issue is just you shouldn't touch it.
2:02:03
It's too controversial if you want to be monetized still like >> Yes. Yeah.
2:02:07
>> So maybe that was some like very clever like Jewish marketing gimmick by putting the H1B discourse on Christmas so only the Jews could participate. >> Maybe. No, I know.
2:02:14
I So I I do think everyone participates in in the timeline over holidays.
2:02:19
I think it's uh but but maybe it's more phone time, less computer time.
2:02:25
Like people are milling about.
2:02:27
They're stepping away from the turkey, but they're not necessarily sitting down and writing.
2:02:32
>> More good screen, less bad screen.
2:02:34
>> Wait, which one's the good screen?
2:02:34
I mean, that's the that's the joke.
2:02:35
It's like I close my bad screen.
2:02:38
>> The bad screen is the computer. >> Yeah. Yeah. >> I I have it.
2:02:40
I think my my good screen is the computer.
2:02:42
My bad screen is my phone.
2:02:44
>> I would agree with this.
2:02:45
>> On my phone, actually.
2:02:46
>> You guys are I mean, you guys are not working an office job. >> Sure. Sure. Sure. Sure. >> Yeah. >> Yes. >> Yeah.
2:02:52
I I I think there will be people uh milling about reading posts, but they won't have time to sit down and really uh we we were debating this over the stream.
2:03:01
Like, will anyone have time to watch like a three-hour stream uh on Thanksgiving?
2:03:04
Of course, we're taking Thanksgiving off, but um uh but not Black Friday, but we are we are going to be the most important, Dave.
2:03:10
We're going to be open for business.
2:03:11
We're going to be celebrating.
2:03:13
>> Tell me what deals tell me what to buy on Amazon. >> Yeah, we will.
2:03:15
We have some good people lined up. Um so, yeah.
2:03:16
What uh what what uh what did you write about last magazine and uh did the California Forever piece line up with it's going to publish in the next B? >> Yeah.
2:03:30
So in the last magazine I did the review of Dan Wong's Break Neack. >> That's right.
2:03:34
You talked to him too a little bit. What was your takeaway?
2:03:37
>> I think I really like Dan.
2:03:37
I think he's a really smart guy.
2:03:39
I've hung out with him a few times.
2:03:40
Uh he gave me a huge stack of the London Review of Books and he's like this is just like the greatest thing ever.
2:03:45
So it was nice bonding over print media with him. >> That's great.
2:03:48
Uh, I do think that it's just I like I'm very skeptical that the United States government should get involved in these huge infrastructure projects in its current state.
2:03:56
Like I like the idea of engineering, but what makes American engineering so spectacular and so amazing is that we do it in the private market. >> It's distributed. >> It's distributed.
2:04:06
And if we just said, okay, we're the United States government is going to do this huge engineering project.
2:04:11
It's like, >> do do we trust the United States government to do this huge engineering project?
2:04:16
I like I I drove down uh to LA yesterday from San Francisco and it's like half the roads were terrible and it's like you know what I sort of wish this whole thing was a toll road. Yeah.
2:04:26
Maybe I'm not like that like dieh hard libertarian where I'm like government shouldn't do roads private >> at least not yet. Uh give me like 5 years.
2:04:33
>> I I joke that the G Wagon is so popular in LA because you actually need a 4x4 to like get around some of like crazy >> Well, yeah.
2:04:40
Well, it was raining like crazy yesterday on the freeway and I was driving down and I was like, "Thank God that my beautiful, beautiful Rav 4 has four-wheel drive or else I would die because these roads are terrible and no one knows how to drive in the rain."
2:04:52
>> Yeah, I was I was reflecting on that.
2:04:54
There are so many interesting anecdotes about like is the government equipped to take on the project that you are interested in whatever your pet project is whether it's healthcare or space exploration or whatever you want.
2:05:05
And uh yeah, I I I keep I keep coming back to this part of like like step one in any of that is like fix the productivity problem in government projects. >> Yeah.
2:05:19
I think the for the la for the next issue of Arena >> [clears throat] >> 006 that's coming out December 1st, I wrote about California Forever, which is the project to build a new city in Salona County, which is about an hour northeast of San Francisco.
2:05:30
northeast of San Francisco. And it's it's sort of like an interesting concept to me because it's like oh it's this privately funded city you know all of the like the who's who of Silicon Valley Loren Powell Jobs Collison brothers Reed Hoffman not Freriedman Mark and Dreon all these people put money into this it's a privately funded city
2:05:48
>> but so much of the struggle with getting California Forever off the ground is just because of government and I remember I was factecking the essay and I was communicating with Julie Julia Bleststone who's the California Forever head of comms And I was said like, "Okay, well the next step is there's this like 1,200 uh page environmental review." And she's
2:06:06
And she's like, "No, it's actually 12,000 pages."
2:06:10
I don't think I've read 12,000 pages in my life.
2:06:12
I don't think anyone in this room has read 12,000. And I read a lot.
2:06:15
Maybe I have in my life, but me not at once.
2:06:19
And definitely not environmental review report. >> Yeah.
2:06:21
>> Especially a report that somebody's just going to drag into Chat GBT and say, "Uh, turn this into five bullet points, please.
2:06:29
>> [laughter] >> turn this into one image.
2:06:32
>> My favorite memory from college actually is this is actually when uh Peter Teal was co-eing a class and I my sophomore year of German 266 and it's a class of like you know 60 people you have to fill out a form to get in.
2:06:43
It's supposed to be like you know a good class and it is a very good class.
2:06:47
It's a fascinating topic.
2:06:48
But my favorite or one of my favorite memories from the class is the kid next to me who had the startup that was worth like that millions if not tens of millions of dollars >> put in chat summarize Hegel in three bullet points.
2:07:00
[laughter] I >> love that. >> One shot it. >> Yes. >> Don't make mistakes.
2:07:06
>> That would be Yeah, that's that's >> Well, maybe maybe I mean >> Stanford Whiz Kid his startup's only worth a couple million bucks.
2:07:12
Maybe he's actually not [laughter] that not that elite. Who >> knows? Yeah.
2:07:17
what what is the uh what is the mood in the the Stanford alumni uh world right now?
2:07:22
Uh there was this question I was sending you this post from Delhi and this question about like uh the age-old question of like is this next generation cooked?
2:07:30
Is there is is is AI actually turning off folks brains to the point where they can't sit down and read Hegel all the way through that everyone is doing this?
2:07:40
Is it a systemic problem or is this you know uh just canankerous old millennials shaking their fist at the younger generation?
2:07:49
>> Well, I will say this at Stanford there's a thing called co-terming.
2:07:51
It's like a fifth year masters you apply.
2:07:55
Most of the time people get in and you just sort of stick around for another year, finish up a masters and you get two degrees at the end in five years.
2:08:02
>> Apparently a third of my class the class of 2025 co-termed whereas it's co-terming right now. >> A third 33%.
2:08:08
>> Yeah, we we've seen this a lot.
2:08:08
We saw some data that more people are applying to law school.
2:08:12
>> Oh yeah, the law school thing is terrible.
2:08:13
The law I have a few friends who are studying for LSAT right now and I'm like hitting them in the head with their huge LSAT books.
2:08:19
>> Is that because you think they won't be a it won't be a career path?
2:08:22
>> There there aren't going to be associates.
2:08:22
Maybe they're going to be like five associates, but there aren't going to be 50 associates because it's interesting because >> if you genuinely are excited about devoting your life to understanding and finessing the legal system, it's probably as good of a time as ever because you're going to be able to learn a lot faster.
2:08:43
You're going to be able to be more productive.
2:08:46
like if you're super high agency, you'll find the right firm and attach your career to that and and probably uh be able to have a wonderful career.
2:08:53
But deciding to do law school because you don't know what you want to do and you trying to buy time uh and you want to do something that's sort of like high like on a on a high status track uh and hopefully high earning without without being necessarily high agency just feels like a a train wreck uh an inevitable train wreck.
2:09:13
train wreck. Well, how it seems to me my dad actually he just retired from a legal career and he was the first person to say like yeah all the associates are sort of screwed because they're like they just can't out can't out compete the AI and law especially how it's
2:09:27
structured because there needs to be like a partner on the case as per like this weird agreement that was reached I think in the early 2000s associates can't really be on cases anymore so there's even less of a need for associates and this is going to be true in all fields and I think obviously
2:09:43
there like these in law specifically there are these you know 100 200 year old firms that really care about legacy they care about reputation so they're like okay we need to have like some young people to carry the firm on but it's just the question of like how are those people going to learn anything if
2:09:59
chatbt is just doing all their work or Harvey or anything like that >> I think how I like I I think for if you're like the top like 5% of like law students you're probably going to be fine >> uh we're still going to have judges is judges are one thing and I'm like maybe AI should just replace judges. We have a
2:10:14
We have a lot of bad judges.
2:10:17
>> That seems like a that's a crazy idea.
2:10:19
Before of of the courtroom, the thing to replace you would think would be the stenographer.
2:10:24
Like we have dictation and yet and or all the time. It's not that great. Okay.
2:10:33
Uh we can get into the bear the bear thesis for AI in a minute, but uh the the the court uh the illustrator, what do they what are they called?
2:10:40
just court >> courtroom illustrator.
2:10:42
>> Courtroom illustrator. We have cameras.
2:10:45
Why don't we just take a picture?
2:10:46
>> Like the the downside of if you actually use Nana Banana >> or any other image model. >> Yeah.
2:10:51
>> It would it would not it would just be like good enough to not produce a funny result.
2:10:55
And I feel like there's so much humor.
2:10:57
>> It has to be like Studio Gibli like murderer or murder like defendant. >> No, that would work.
2:11:01
But I'm saying like sometimes that sometimes the illustrators like botch an illustration so badly that it's funny or something.
2:11:09
That's what you're thinking about. Yeah.
2:11:11
Um, yeah, I I I was shocked by how resilient that uh job was to automation since we do have the camera and we've had the camera for a hundred years almost and it's stuck around as a real >> I think I don't know like a lot of court or a lot of law is like ritual like and
2:11:26
I think in the UK the judges still have like the weird head things that they need to wear the wigs >> um or even like the judges robes and my dad like he had to wear a tie >> around for a really long time even if the AI can do so much it just we will do
2:11:41
it out of procedure we will we will have these conversations with humans for for uh whatever reason I don't know >> yeah procedure is very inelastic and also I think just you know lawyers it's a very easy like cast of person to demonize and I think just as you know
2:11:58
McKenzie will stick around so they can say oh sorry about the layoffs Mackenzie made us do it it's going to be the same with the evil lawyers >> yeah sure yeah yeah you want the buck to stop with someone and not necessarily an AI >> no >> not necessarily >> because if you say Oh, sorry. The AI The AI said this.
2:12:10
Well, they said like, "Well, you use Grock instead of Chad GBT.
2:12:11
Can you ask Chad GB's T?"
2:12:13
Because that's my preferred AI model. If it's just McKenzie. >> Yeah.
2:12:17
What's the uh um I feel like I feel like there's still there's still probably some alpha in uh becoming a lawyer or going down the legal path in 2025.
2:12:28
uh if you are basically setting yourself up not to just be uh you know associate fodder for you know high margin billing but in fact you are setting yourself up to gain control over an institution that would be harder to build independently.
2:12:45
Well, I think with young people especially, law it's because you have, you know, you make like good money in your your like late 20s and 30s, but you start to make really good money in your 50s and 60s.
2:12:58
>> And I think for >> sort of like an MLM, [snorts] >> yeah, a little bit.
2:13:02
But it's also for people my age who it's like, oh, I could either like work really hard for like 30 years and maybe if I make partner and I'm one of the really good partners, I can make >> a ton of money, >> like a good amount of money.
2:13:13
It's like why do that when it's like oh if I learn how to code and after like 10 years I can make this much money.
2:13:19
>> Y four years with vesting. >> Yeah. With vesting.
2:13:21
All you need is the four years. >> Yes.
2:13:23
At the right hot company at the right time. >> Yeah.
2:13:26
So it's it's interesting to me because I feel like with the Gen Z financial incentives.
2:13:30
It's so oriented around like make money now. Yeah.
2:13:34
>> Uh or even like the oh you have x amount of years to make money before AGI hits and the economy is permanent underass. >> Yeah. Permanent underclass.
2:13:40
I'm still waiting for the the gam g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g g gambling on your student loan debt, you know, the double or like double your debt or pay nothing, you know.
2:13:50
>> I I've become I've become very skeptical of the permanency of the underclass phenomenon.
2:13:54
I I feel like there will be like the the the strength of the underclass is growing in number, but the permanency is decreasing.
2:14:01
permanency is decreasing. uh because at any moment someone can be plucked from the underclass into the global elite through just one right like parlay or one right actually like building a company joining a thing um like
2:14:15
distribution on the internet is so so aggressive that you can be languishing in the underclass and then go viral and launch a DTOC line and if you just have like a few things go your way you become like the the the market just gives you $10 million basically. >> Yeah. I think it's very rare. It's >> Yeah. I think it's very rare. It's random, too. >> It's random. Yes. Yes. Yeah. Yeah.
2:14:34
It's like you were on that plane and you screamed at that person and then you went viral and you became and then you started a podcast. >> Exactly. >> Yeah.
2:14:44
>> Don't give people ideas.
2:14:44
I I think it usually goes the other way.
2:14:48
>> Girl, for example, I don't know exactly know how it all played out for her, but Haley Welch like like >> Well, she she she was stupid with it. >> Yeah.
2:14:54
I think she like she launched a coin and it did not execute well.
2:14:56
But that type of opportunity is entirely random and every once in a while the market just comes around.
2:15:04
It does not feel permanent to be in the under.
2:15:07
>> So when I start yelling so on Wednesday when I fly to see my family for Thanksgiving, when I start like really aggressively yelling at people on the plane, you know it's time to buy Juliacoin. >> Yes. Yes. Yes.
2:15:17
You got to get in early on that for sure.
2:15:20
>> You have to get in early before I have my like tantrum on the plane. >> Yeah. Yeah.
2:15:22
Um, what else is uh uh has has anything updated you on the get your bag culture?
2:15:28
Are people now self-aware of it?
2:15:30
Uh, we were talking to Jessica Livingston and she was referring to the concept being actually not very new.
2:15:34
She was saying uh carpet baggers.
2:15:38
>> Well, yeah, that was like a term for the Civil War and it was like anti-N northerner.
2:15:41
It's like these people are just exploiting business opportunities which I don't know.
2:15:45
It's like >> I I don't like the term like exploitative business opportunities. I think we have enough.
2:15:55
>> But I don't think a lot is so we're in LA right now.
2:15:58
I went to high school like a few miles from here and I think like a very like core memory for me and it was a college >> memory. Shout out Ashley Vance. >> Yes.
2:16:08
Uh the ad the college admission scandal varsity blues.
2:16:11
I >> I was a junior in high school when this happened. >> Okay. So you experienced Wow.
2:16:14
I so my school actually the whistleblower's daughter was a senior and she was gonna go to Yale for soccer and we're all like oh it's sort of weird that this girl I'm gonna call her Susie. >> Sure.
2:16:24
>> Susie is going to go to Yale for soccer but she's not on the soccer team at her school and there's not really evidence that she plays soccer but she's going to go to play soccer at Yale.
2:16:33
>> One of the most elite teams in women's soccer. >> Sure.
2:16:36
I don't know anything about soccer but uh this girl was going to go to Yale and you know at my high school it was very like elite.
2:16:41
Everyone was concerned with if they got into Yale or not.
2:16:43
with if they got into Yale or not. So it was all sort of like oh like this is important like everyone flagged that Susie is going to Yale but we all sort of knew that she didn't play soccer >> and I remember my my high school was very small and you know it was a college prep school and the day before the news
2:16:58
came out I had a meeting with the head of school to talk about like where I should apply to college uh what my SAT scores was blah blah blah privilege blah blah blah acknowledged that I had a very elite upbringing >> but I remember I the principal was late and this never happened >> there seemed to be something very wrong
2:17:15
and I was like I don't know what's happening and she was late to the meeting and it was fine and I was told that my SAT scores were fine blah blah blah blah blah I the next day first period I have a moral philosophy class I'm the only junior in the class it's all seniors I petitioned to say I can take this elective and we're talking
2:17:31
about meritocracy >> and whether meritocracy is real yes in the class we have a reading about meritocracy it's is it meritocracy just is it something that we should optimize for is it something that's unjust because you know intelligence is heritable, so it's it's not earned, >> blah blah blah blah blah. >> And we get to the class and, you know,
2:17:48
>> And we get to the class and, you know, at 7 a. m.
2:17:49
that morning or whatever, we all woke up, we all saw that this girl's dad was, you know, he was arrested for securities fraud and part of his plea deal was that he was giving up his college admissions scandal where this guy, this college admissions coach was telling people to put that there were black on their college apps, that they were faking associations with various sports teams at all these elite schools.
2:18:12
So, we go in and it's like, okay, like we're talking about meritocracy. What about Suzie?
2:18:16
What about the college admission scandal?
2:18:18
Because we're all sort of fed up with the whole college admissions process.
2:18:21
It's a dog and pony show.
2:18:23
My little brother's going through it right now.
2:18:24
And I'm like, why are they asking you what three words you are?
2:18:28
What could this possibly have to do with how good of a student you will be or anything like this?
2:18:33
>> But I remember going through the college admission scandal firsthand, just seeing like how corrupt it is, but also in a way it was sort of like an equalizing form of corruptness.
2:18:40
M >> because like if your family can donate $50 million to Harvard, you will get it.
2:18:46
Like you have to be like really really really really bad to not get in if your family donates 50 million.
2:18:51
>> What if your family doesn't have 50 million to donate to Harvard?
2:18:52
What if they only have $500,000?
2:18:55
>> Well, then you have to make 50 million before you apply.
2:18:58
>> Or you can use the $5,000 to buy your spot on the sports team. >> Oh yeah. >> Five grand. >> 500. >> Oh, 500.
2:19:04
>> But it's that's a lot less than 50 million. >> Yeah. Yeah.
2:19:06
>> So it's sort of more equalized.
2:19:06
So it was for it wasn't like the like.
2:19:08
1% but it's still like 1%. >> Sure. Sure. Sure. >> Corruption.
2:19:12
Uh so I think that experience >> isn't there a pro libertarian hot takeake that says like you should just auction off every slot.
2:19:20
>> I I've said this before like I well my my sort of take on this is that college admissions office should just be sold to the highest bidder. >> Yeah.
2:19:27
Um it would be a lot more honest than what's done now because right now it's they sort of they give you the spiel about like oh we need to have a super diverse class where we have one chist and one person who's really good at like studying molecular bio and like >> and a sailor.
2:19:40
We have to have a sailor. >> The Michael sailor.
2:19:43
>> We actually don't have enough sailors there.
2:19:45
They're doing walk-ons in the sailing team at Stanford.
2:19:46
My best friend in undergrad did that.
2:19:48
But >> uh yeah, I think we should just auction off the college admissions office.
2:19:53
>> We don't have enough sailors in this country anymore.
2:19:55
>> We don't have enough sailors in this country. so bearish.
2:19:57
>> We got to get back into sailing. >> That's hilarious.
2:20:01
>> But yeah, I think it's this is actually something I was talking about with my boyfriend is like how much would it cost >> if you just auctioned off a slot?
2:20:06
Maybe if you only auctioned off 10 if you limited >> Oh, I would think you would you would auction off literally every slot, all of them.
2:20:14
Like what is the market clearing price?
2:20:15
Because you know uh in the luxury watch world like there will be a certain number of uh I mean this happens with like the market what is the market clearing price for Taylor Swift tickets but like you know there are if they if Porsche comes out with a new a new uh GT3 RS there might be you know 5,000 made and they will try to find the market clearing price as close as possible to what the market will bear.
2:20:38
Sometimes they overpric them.
2:20:38
They don't sell them all.
2:20:39
Sometimes they underpric them and they immediately trade up on the secondary market.
2:20:42
But you could even have a secondary market that you know, okay, yes, I bought my slot at Harvard for 2 million, but they're going to three million now, so I'm going to sell that, go to NYU instead.
2:20:52
[laughter] Like you could have you could have an entire entire process uh just to maximize the price. >> I just don't know.
2:20:59
It's like if that happens, what percent of the Stanford class would be international, which is a good question.
2:21:04
>> It'd be hugely international, of course.
2:21:05
I mean, it would be it'd be across the entire world.
2:21:08
Everyone would just pay to go.
2:21:09
And I mean there's already a little bit of that, but it's it's definitely like there's more design to the system than that.
2:21:14
There's certainly I I would imagine >> how how do you how do you uh how do you defend that against uh you know just eliminating an entire track for uh young people that maybe have uh negative capital within their family systems.
2:21:29
And uh even if you tell them even if you tell the family at birth like you know expect to be able to purch if you want your child to go to Stanford or the auction range at that point counting in inflation will probably be you know 70 to 80 million to get into the school.
2:21:47
probably what we'll have is >> and then and then it ultimately actually destroys uh would would naturally just destroy I think some of the the uh would certainly be valuable for uh students from elite families to network with other uh students from elite families but ultimately would would uh kill a lot of what makes universities great.
2:22:08
Yes, I I I agree that it would kill a lot of that.
2:22:12
But probably what would happen is, you know, now you have a lot of scholarships.
2:22:15
Uh when you apply for college, you know, the Coca-Cola scholarship is a very big one.
2:22:19
A lot of these are sort of mostly like full rides to college, like the very like prestigious scholarships.
2:22:24
And so probably what will happen is that instead of having these scholarships to college, it's like, okay, we young people of America whose family can't afford the like $50 million sticker price of college admission, apply and we will give you the $50 million to pay your way for this price.
2:22:40
But yeah, it's obviously a very flawed system, but it's interesting.
2:22:45
It's interesting like mental model about how much we value college admission especially because you know at a place like Stanford there are like what like 1,700 to 2,000 graduates in a year.
2:22:55
Not all of them do fascinating things. >> Yeah.
2:22:59
Uh what's uh where where what city are you living in these days?
2:23:04
>> I live in San Francisco.
2:23:05
>> What is the mood in San Francisco?
2:23:05
Do you think it's getting better? >> I don't know.
2:23:08
I've only lived there since August, so I can't really say.
2:23:11
There was this narrative in the uh in the mansion section today about uh about it cleaning up its act.
2:23:16
There's >> I have a fun story.
2:23:18
So >> there's more uh there's more demand for West Portal Village Center.
2:23:22
I had never heard of that.
2:23:25
>> I don't know what that is.
2:23:26
>> It is now more expensive to live there than in uh Pack Heights. Apparently $2.
2:23:28
5 million median list price.
2:23:31
There's also the the story about like the Open AI secondar is driving up real estate prices.
2:23:36
Um, but it's always it's always interesting to feel what's actually happening on the ground.
2:23:41
>> So, I live uh I live in Pack Heights.
2:23:41
I live in Lower Pack Heights. Yes.
2:23:43
And a few weeks ago, there was a homeless guy who's just totally passed out on my doorstep.
2:23:50
>> I It was a Saturday morning. I woke up late. It was like 9 or 10.
2:23:52
I checked my phone and in our apartment WhatsApp, it's like, "Hello, there is an unhoused person on our doorstep.
2:23:58
Please don't disturb him."
2:24:01
And then in this group chat, we had this huge debate over whether we should call the cops.
2:24:04
And the the conclusion is just the cops won't come.
2:24:08
You can't really do anything about it. He seems nonviolent.
2:24:09
Maybe we should wait for him to leave.
2:24:14
>> So I left my apartment at like, you know, 10:30.
2:24:16
I was back at 3:00 and he was gone. >> Yeah.
2:24:19
>> But it's still like a weird thing to account for.
2:24:21
Like >> you sort of want to call an ambulance for >> you want to call Well, you just want to call someone. >> Yeah.
2:24:26
>> And have And in my building, you know, there >> probably like 30 people who live in the building.
2:24:31
So, it's like someone could have called someone or maybe if all 30 of us tried, >> but it it was very disconcerting because it's one of those things where it's like, oh, everything's better.
2:24:41
Everything >> was everything noticeably cleaner during uh uh Salesforce this year, Salesforce's conference because a few years ago, Beni off like just completely cleaned up the entire city.
2:24:52
And then the other time that they cleaned up the city was when Cian Ping was visiting your >> Cian Ping.
2:24:56
I was in as of that week and it it felt like it was a different place. >> Really? >> Mhm. >> That's funny.
2:25:00
I think SF generally or urbanism generally it's just it's so hard to justify living in one of these places.
2:25:08
I think for most people >> I think I I I I agree but it's almost the flip side where it's it's so easy to justify living in a suburb because yes you're in the city and it feels like ah this is like like we got to clean this place up.
2:25:20
We got to clean this place up.
2:25:21
But then uh you you sort of work on that and then you also work on your life and your company and your business and whatever.
2:25:27
And then as soon as you have money in a family, it's just so easy to go to a suburb.
2:25:32
And there's so many fantastic suburbs.
2:25:33
And that's always it was always the thing that annoyed me about the discourse of like San Francisco has fallen or San Francisco is such a bad place to live.
2:25:40
It's like, well, people live in Palo Alto, they live in Atheertton, they live in, you know, up north in wine country, they live in Incline Village, they live all over the place, and they live in these wonderful luxurious places that have no crime, no homelessness.
2:25:52
Like they have they have like fantastically managed cities just a commute distance from San Francisco. >> Yeah.
2:25:59
I think San Francisco it's always sort of been like a young person city. >> Totally.
2:26:03
When I lived there it was super rough but I was like I'm young. It's fine. >> Yeah.
2:26:07
I saw a guy on Twitter who's going to give me a taser. So thank you.
2:26:08
Um >> but I think weapons on the internet. >> Yeah. Giving away weapons.
2:26:16
>> You can buy a taser on Amazon.
2:26:16
It'll show up this afternoon.
2:26:19
>> It's like a taser gun.
2:26:19
So I think it'll be easier to use.
2:26:20
I was going to buy a taser.
2:26:22
This >> Well, those are Yeah, those are legal.
2:26:24
You can also just buy this.
2:26:26
>> Yeah, it's >> someone's going to give you a free one.
2:26:28
>> Yeah, someone's going to give you a free one.
2:26:29
So, SF is sort of it's it's, you know, the duality of San Francisco is it's great because some random stranger on the internet will give me a free taser gun, but the sort of negative part is that I need this taser gun to stay safe. >> Yeah.
2:26:40
Uh, it's always been so fascinating.
2:26:42
I mean, I wonder I wonder if the OpenAI wealth will meaningfully change the uh the budget of the city.
2:26:46
I you know you there's just so much and it's actually the company's actually in San Francisco.
2:26:54
It's not a Mountain View company.
2:26:56
It's not a Palo Alto company.
2:26:57
It's not a you know Menllo Park company.
2:27:00
It is a San Francisco company and you have 500 billion dollars of wealth loosely with you know tens of billions in the pockets of employees right there.
2:27:08
Like that should w wind up doing something even if it's just some renovations some private security.
2:27:14
>> How good are OpenAI employees at spending money? >> I don't know.
2:27:18
>> How would they spend it?
2:27:18
How how would you recommend this?
2:27:20
>> I have I have a friend who works at OpenAI and you he just like you know I don't really know how to spend my money and I was just like >> do you want like I can yacht? >> Yeah.
2:27:28
[laughter] >> Get a yacht. I don't know.
2:27:29
There is a marina in San Francisco. >> There is. Yeah. Beautiful.
2:27:33
>> I like to go over and walk around there.
2:27:35
There are these like cool boats and yachts.
2:27:37
It doesn't need to be like a super ostentatious one, but >> I don't know.
2:27:41
>> Yacht is secondary to uh to cleaning up the streets, you know. >> Yes.
2:27:44
But all of like even buying a yacht would help clean up the streets because it is some simulation of the city's economy. >> Okay. >> Uh I don't know. >> I suppose. Yeah.
2:27:52
>> Speaking of boats, it's like waters uh high tides uh rise all boats. >> Sure. Sure. Sure. Yeah. >> So I don't know.
2:28:00
It's I guess it's sort of it's silly to say like rise or like raise the economic output of San Francisco because it's one of the most economically like intensive regions in the country.
2:28:08
But I do very strongly believe that, you know, just >> let market forces do their thing, things will get better.
2:28:15
>> Well, uh, thank you so much for stopping by the Ultradome. This is fantastic. >> Yes.
2:28:19
Thank you for having to get the update. Excited for 006. >> 006.
2:28:24
>> Yeah, 007 is next after that. >> Very exciting. >> Amazing.
2:28:27
>> Uh, where can people get it? >> People can aramag. com. >> Arenamag.
2:28:30
com and at Barnes & Noble near you.
2:28:34
>> Yes, there's a Barnes & Noble deal now. IRL.
2:28:37
Well, >> so if you want to buy any romanty books, which I think is is the new genre.
2:28:43
>> Yeah, there's romantic fantasy, right?
2:28:44
Okay, >> that's a new genre that won't it's not my type.
2:28:47
I will see you have to get on that.
2:28:49
>> Uh well, thank you so much for this is great. Great to see you. Cheers.
2:28:52
>> Uh [applause] >> let me tell you about eight.
2:28:53
com exceptional sleep without exception.
2:28:58
Fall asleep faster, sleep deeper, wake up energized.
2:29:00
Uh we have our next guest joining right now.
2:29:05
We have uh Bob Brushaw from Dupe.
2:29:08
Uh this is a very fun company doing welcome to the show. >> What's up? Thank you. We made it guys. We made it. >> We made it finally.
2:29:16
Uh great great setup here.
2:29:20
You got you're just daily driving that for Zoom. >> That's it. Yeah. I mean, >> fantastic. >> It's comfortable. It's cozy.
2:29:27
>> Introduce the company.
2:29:27
Uh I remember when uh you launched, I remember seeing a whole bunch of posts go viral, but uh how are you describing the company today? Yeah.
2:29:34
So, so Dupe is used by millions of people to find the products that they want or similar products for less.
2:29:43
>> Uh, it's a search engine.
2:29:43
It's a generative marketplace.
2:29:46
I could throw a whole bunch of buzzwords.
2:29:47
It's AIdriven this and that, but ultimately it's a shopping companion.
2:29:51
It's a shopping app that helps give people a confidence pill, a little bit of a boost to know that what they're buying is at the best price and is the right product. >> Mhm.
2:30:02
Agentic Commerce, OpenAI is talking a big game about it.
2:30:05
Uh, is that a headwind for you? >> Yeah.
2:30:12
You know, it's first of all, uh, nothing's set in stone yet.
2:30:15
Don't don't count us out.
2:30:17
We're also talking to them. Sure.
2:30:20
>> Um, we're we're building we're building an app, uh, that would be native to ChatGpt. Okay.
2:30:25
uh you know it's like the the thing I like to say about chat GBT Google all these tools is that >> they can do everything >> and that is the problem.
2:30:36
>> Um it's like you can if you're a chef you can use a Swiss Army knife to to cut a tomato but why would you?
2:30:41
I think verticalized AI tools are are very powerful because they are single purpose uh and they solve a problem in a in a in a in a more precise way. >> Yeah. I mean I it's odd.
2:30:51
I have like no doubt that there's people out there that are making tens of millions of dollars on uh Studio Gibli apps, right?
2:30:58
Or, you know, uh different animation apps, different uh different sub apps that maybe could be done in chat GPT if you know the right prompt, but because it's lower tier on like the prompt ladder, you kind of got to know to go there to get it.
2:31:15
Uh it's not coaching you through it.
2:31:17
it's not actually giving you uh all the different uh harnesses and and wrapping uh that you need to do it.
2:31:24
>> How hard has it been to actually build the ex like the product experience?
2:31:29
because I'm assuming you're effectively like browsing the web on behalf of, you know, if I upload a a product or I paste in a link and then you guys are browsing the web or you already have and you're and you're uh sorting products to find uh products that look the same and or maybe uh from a different manufacturer or the same uh end manufacturer, different brand.
2:31:49
But uh how hard has that product experience been?
2:31:50
because I've been continuously disappointed by uh computer use and just web browsing from a lot of different LLMs at this point.
2:32:02
>> When you say computer use and you're talking about things like uh the browser is doing the browsing on your behalf basically. Yeah. >> Yeah.
2:32:08
Go out and find this thing.
2:32:08
The the example that he gives is >> I use it for cars.
2:32:10
That's my >> find me a GT3 RS. It's a rare car. It's a specific. It's a great car.
2:32:15
Uh, but it's not it's not uh like find me someone who sells Diet Coke.
2:32:22
Like Diet Coke is a commodity. It's sold everywhere.
2:32:25
A GT3 RS uh there might not be one for sale right now.
2:32:28
Like it's possible that there's just none for sale. And so >> Well, yeah.
2:32:32
GT3S quite a bit more common, but there are certain cars you look for >> and it'll say I found you this one.
2:32:38
And it's like it sold two years ago. >> Yeah.
2:32:42
And so and so on that eval of like go hunt around on the internet, find this particular thing that's not particularly funible, not particularly commoditized.
2:32:50
Uh at least agent mode, these agent these a uh these agentic commerce products have not been uh up to Jord's standards at least.
2:33:00
>> I take it you haven't bought the the GT3 RS yet. Like >> not yet. >> Not yet.
2:33:05
And the only reason is uh just the AI is not good enough. >> Yeah. Yeah. Of course. Of course. That's the only reason. Come on, guys.
2:33:10
Uh so so so first of all I think it's I I too have been fairly disappointed with with these like browsers that that browse on your behalf.
2:33:19
That is ultimately not what we're trying to do with dupe.
2:33:21
AI has some flaws in like the shopping universe and maybe that you know it it speaks to some of the pain points you're finding with you know finding your perfect car which is they don't have uh live inventory, they don't have live price, they don't have product cataloges, they don't have customer preferences, they don't have customer behavior.
2:33:40
There's a lot of data that is missing in the shopping journey.
2:33:44
So ultimately what you're left with is the best guess.
2:33:46
So to answer your question, how hard has it been?
2:33:50
It's hard because the way you do it, the way you do it right, is you got to do it the old school way, all right, in the shopping world, you got to go press palms, kiss babies, hug people, take them out to, you know, to a drink, meet them at conferences.
2:34:02
You got to know their names, you got to know their kids' names.
2:34:05
It's like a lot of trust building in person.
2:34:07
It's not as simple as just kind of plugging it in because when you build that trust, they then trust you with their product cataloges and they give you a commission for sales because you know you turn out to be a partner that drives a lot of sales for them.
2:34:20
So it has been it has been pretty hard but the the tech that we have is product ingestion from these partnerships but also live scraping.
2:34:26
So it's you know in a sense it is browsing >> and it's scraping this data for you.
2:34:31
We have vectorized millions of products or tens of millions of products at this point.
2:34:38
So we can do kind of a live assessment of what products look like each other, what products should go together, stuff like this.
2:34:44
Um, ultimately the way to solve it, you can't, it's AI is not sort of a panacea.
2:34:50
You have to pick your battles.
2:34:50
So Dupe, for example, for the last year and a half has been focused solely on furniture. Why furniture?
2:34:56
Well, turns out unlike the GT3 RS, a lot of furniture is made in the same few factories, sold back to brands under different names.
2:35:05
the brands, then upload them to their website under different names, different prices, but it's the same furniture.
2:35:11
And I know this because I got scammed uh with buying furniture online, and it really pissed me off because I found the same product I wanted for about 40% less.
2:35:19
Exact same same spec, same color, everything, exactly the same.
2:35:23
And so that ultimately is like the lore of what spawn dupe.
2:35:25
Uh and I've seen these factories in person. I've visited China.
2:35:30
How do you think about uh incorporating human feedback?
2:35:35
That feels some that feels like something that would be a really valuable resource.
2:35:39
I was thinking about like on Instagram you see a lot of ads for a bunch of different stuff.
2:35:43
Some of the stuff is is like it really grabs your attention.
2:35:46
People just buy it, but then it's really low quality.
2:35:48
And if you could actually have some sort of, you know, okay, feedback.
2:35:52
Hey, we we we you know, we we shipped you this dupe, this product.
2:35:57
um we think we got you the lowest price, but like tell us how the product actually performed because that better informs our our our our decision-m uh are do you think that'll be like a compounding advantage?
2:36:08
Do you think that's valuable over the long term?
2:36:11
>> It's so it's so uh it's so valuable.
2:36:14
>> Uh and we don't even need to ask the customer.
2:36:16
First of all, we have access to all these reviews.
2:36:18
We also have access to the checkout data and we have access to the return data because if if someone returns something, we don't get paid. Yeah. >> All right.
2:36:25
So these brands pay us four months after the sales happens, three months after the sales happen, after that return window is set.
2:36:32
So we know which products get return the most.
2:36:34
So absolutely that's a compounding effect.
2:36:37
>> Yeah, that makes a ton of sense, Jordy.
2:36:39
>> Uh you get a lot of hate mail >> from from certain brands that uh that that uh kind of realize like you're providing a service that consumers love and then certain brands out there that that are sourcing products and setting whatever price they feel like is relevant.
2:36:55
And then you're actually in >> blowing up my spot.
2:36:57
I had an I had 99% margin on this couch.
2:37:01
>> Yeah, we basically like killed shop drop shippers like for sure.
2:37:03
Like the drop shipping industry is a is a total scam. Um and and they hate us.
2:37:07
But ultimately our brands the part our partners love us.
2:37:12
We drive millions of dollars in sales for them every every single month. >> And so why is that?
2:37:17
Well, let's say like let's take a partner like Walmart.
2:37:20
So some people think Walmart has thousands of products. They don't.
2:37:24
They have millions of products, right? Millions of products.
2:37:28
They're not always in store because a lot of those products are drop shipped.
2:37:31
So, what we do is, you know, let's say you guys are looking for, we'll take a piece of furniture, for example, that chair right there.
2:37:37
I mean, that's that's not being sold at Walmart, but let's say you want something like that, and you upload an image to dupe, or you tell Dupe like, "Hey, that's a Herman Miller.
2:37:46
Find me something like that for less."
2:37:48
Walmart has 15 versions of that chair. You don't know that.
2:37:52
You would probably never even think to look at Walmart for that chair, but Walmart has a great version of that chair and they love us because we merchandise their products at that exact high intent moment where the customer knows what they want.
2:38:07
They just want a great deal on it.
2:38:09
>> We surface the partners up.
2:38:09
Now, there are some brands, for example, we were sued uh last year and >> Yeah. Yeah. We we we were sued.
2:38:15
I'm not going to name the brand.
2:38:16
It's very easy to find the brand.
2:38:18
They are the largest largest furniture brand now.
2:38:23
the lawsuit essentially like it tried to kill our company.
2:38:25
It was it was like a pretty tough uh a pretty tough lawsuit that we that we had to fight.
2:38:29
We settled it uh to both parties content.
2:38:31
Like it it it's fine now.
2:38:34
Um but >> what was the what was the claim?
2:38:40
>> The there are a couple claims.
2:38:40
So copyright infringement.
2:38:42
They were pissed that we were using or letting our customers use images from their website to find similar products.
2:38:47
Uh they were they were pissed that like they were part of we went super viral when we came out.
2:38:53
I did all these like post-it note ad campaigns and stuff that went super they were pissed that they were in some of those some of those uh >> social kind of Tik Tok videos. They weren't even ads.
2:39:02
They were literally just social content talking about our our website.
2:39:05
They were they were really really upset about that and ultimately they were pissed that uh we were >> unfairly competing essentially.
2:39:11
Uh, I obviously, you know, we we we have a a public statement on how we felt about all of these claims.
2:39:21
Um, and so they basically said we were falsely advertising, you know, that they were white labeling stuff that we that we were unfairly competing and also infringing on their copyright.
2:39:31
So ultimately, you know, cold water under the bridge. We're we're here. Dupe is alive.
2:39:36
It's well, it's working exactly as we wanted to and it's crushing.
2:39:38
And so there are some of those partners, but those are very few and far between.
2:39:43
And it tends to be like the almost the monopoly type partners, you know, uh that that are that are upset.
2:39:50
Everyone else Everyone [snorts] else and most of the Fortune 500 that we work, they are thrilled that Dupe exists. >> That makes sense.
2:39:58
How'd you get the domain? >> It's absolutely fire.
2:40:02
>> We So the company was called Carrot before it was called Dupe.
2:40:04
We uh had three months of runway before we pivoted the company to Dupe.
2:40:08
We worked with Nikita Beer on it. Uh he was a total goat.
2:40:12
Helped us find >> You spent your last your last 20 grand on intro. co.
2:40:16
[laughter] >> Well, we had we had more than 20 grand.
2:40:21
We had about three months of runway.
2:40:21
But yes, we definitely spent more than 20.
2:40:24
>> Speaking of numbers, yeah, >> just with Nikita.
2:40:25
Probably the best money probably the best money I've ever spent. Saved our company.
2:40:30
Let's be completely honest.
2:40:32
>> That's actually crazy. I love it.
2:40:33
>> It it it like to total bananas moment for us.
2:40:36
But um the the domain was a very last minute decision.
2:40:39
We we knew we needed a great name to stand out in the in the kind of shopping space.
2:40:43
I did a bunch of Google research on keywords.
2:40:47
One of the words was dupe and I saw dupe was on on Google Trends 100 rated Google Trend keyword and growing. >> Mhm.
2:40:54
>> And I saw that no one used no one was using dupe. com.
2:40:56
We reached out to a broker that was sitting on that name.
2:41:01
They wanted just the most insane price.
2:41:03
We then negotiated >> a a far lower price for dupes.
2:41:05
com >> went back to the owner of dupe.
2:41:08
com and said if you don't sell this domain to us in like 5 minutes with this price which I thought was a fair price.
2:41:15
It was all of our money and we gave them all of our money. Wow.
2:41:19
>> And you know that we're going to pull the trigger on dupes.
2:41:20
com and they sold it to us like on the spot.
2:41:22
Basically said okay fine go for it. Smart. >> That's great.
2:41:27
>> That's how we that's how we negotiated it.
2:41:29
[laughter] >> I love that. That's great. Thank you. That's a good story. >> Very cool.
2:41:32
Yeah, that that was like a bet the like a literal bet the company moment.
2:41:35
And then Nikita did the most mench thing ever.
2:41:37
He put out a tweet about us and instantly blew us up. >> It was crazy. I remember that tweet.
2:41:41
He he he framed it very very well.
2:41:43
And then you can imagine this just works on social.
2:41:47
>> What other categories do you think are most ripe other than furniture? >> Yeah. So we do fashion now.
2:41:51
Handbag, shoes, >> clothes.
2:41:54
Uh really big one that we don't do very well yet because AI doesn't have a sense of smell.
2:42:00
You know, it's looking at kind of vision.
2:42:02
Perfumes, perfumes are huge in the >> Yeah, it's basically I look at as anything without a logo.
2:42:08
So, like furniture like there's iconic shapes and silhouettes and and uh you know, materials that get used along that, but ultimately people don't have, you know, you're not like you don't have a couch that has like a restoration hardware big logo printed on it.
2:42:23
The challenge with fashion is that people want like the association with a specific like brand and that can come through a logo or a or a silhouette that actually can't be uh implemented without getting um you know uh kind of >> you're right. You're right.
2:42:42
Except we're going through this like bizarre moment in shopping where brandless is a thing and not showing logos is a thing.
2:42:49
and not showing logos is a thing. like this this kind of quiet luxury movement like people people want something to feel good and that butresses >> like even the brands that you love >> they're white labeling guys like they are they are none of this stuff is like custom made specifically for a single
2:43:07
brand maybe if you're going into the couture world of course that stuff is is custom made but ultimately you know when someone sees Skiim's leggings like yeah they they want the look >> people shop people shop the like that's what they're shopping ultimately and it's it's less about like you know people often misconrue what dupe.com is
2:43:25
com is like we're not trying to sell you replicas we actually ban replicas across the board >> and all those sites >> we are trying to get you that look that garment you know that furniture for less and and most people shop for the look now especially in this market.
2:43:44
>> Yeah, that makes sense.
2:43:44
Uh what uh how do you are do you think you'll have enough leverage at some point to get to get uh the underlying brands to pay you at the time of sale?
2:43:58
>> Is that even >> It's actually very important.
2:44:00
I'll tell you why it's important.
2:44:01
If we were growing 100% month over month and we weren't seeing our cash flow for 3 months, it stifles our marketing budget.
2:44:09
We would have to then either raise credit or go raise a massive round just to pay down the marketing.
2:44:12
This is actually like the biggest risk uh that I that I think about.
2:44:17
that I think about. So one of the things we're partnering with the largest payment network to do uh Aentic checkout global checkout um and you know we're not announcing the the name yet but we are working through that tech and the idea being >> you know most of these brands are really upset with a gentic checkout because
2:44:36
they they don't get the customer information but we do it in a way where the checkout would happen on dupe but the brand retains >> the customer information and the customer relationship and the the only reason we want to do that is so that we can you know go from net 90 payments to net zero net one you know instant payment uh back to to our company. >> Uh so yeah this is this is very top of
2:44:56
>> Uh so yeah this is this is very top of mind for us and it's it's definitely a risk that I think a lot about.
2:45:00
>> How how big uh how big do you want do you want dupe to get?
2:45:05
>> I think dupe uh we we often talk about a road to a billion shoppers.
2:45:07
The way that we're going to do this is we have an MCP.
2:45:11
Uh so we any LLM can plug us in.
2:45:14
you know, the the largest LLMs and the longtail LLMs, they can plug us in.
2:45:18
Ultimately, we want to be the canonical answer engine for how do I get this for less or find me something similar to this.
2:45:25
We want to be that answer engine for these websites.
2:45:27
The beauty is because they don't have access to the behavioral data, the shopping data, the product cataloges, the product pricing.
2:45:35
The moment they plug us in, it's basically zero effort.
2:45:36
It's just, you know, a few lines of code.
2:45:38
the moment they plug us in, any click going out from our answers that gets monetized, we split that commission back with the LLM.
2:45:49
So, it's like instantly monetizing their user base in an entirely uh entirely new way.
2:45:54
>> Um, so that's that's something that we're very excited about.
2:45:55
When you think about how like the the growth potential of that and the tailwinds for any LLM to really consider partnering with us uh for our links and for our expertise and the ability to monetize instantly, I think we can get to hundreds of millions of shoppers on our infra.
2:46:12
They might not be on dupe.
2:46:14
com, but they'll be >> you're still monetizing them.
2:46:17
>> Yeah, >> that's right. That's right. >> That's very exciting. >> That's right.
2:46:20
And in the last 18 months, we, you know, we're right around sub 20 million users. Uh, between Let's go. Oh my god. Do I get the con? Let's >> go.
2:46:32
Not even sure if you're going to give us a number, >> but we got >> Yeah. Yeah. No, no, no, no, no.
2:46:35
So, so I'll give you a few numbers.
2:46:37
I mean, we're we're rounding a corner.
2:46:38
We're going to come up on 100 million in GMV sold through dupe. com. >> 18 million shoppers. Fantastic.
2:46:45
uh between one and two monthly uh one and two million monthly shoppers which we just launched our app last week.
2:46:51
Went number one in the app store by the way super stoked about.
2:46:54
Please everyone listening go download dupe dup look for it in the app store.
2:46:57
Leave us leave us a review and rating. Got to put in the plug.
2:47:00
Uh went number one in the app store and of course we had a lot of fun with that.
2:47:04
We've been putting a lot of fun content out.
2:47:06
>> How did how did you go number one?
2:47:06
Was it content or or some type of like viral incentive?
2:47:12
We have a lot of we have a lot of users like these people they want our app like they you know they use our website to shop and have used our website to shop for for many months.
2:47:20
Um they want they wanted our app and you know the way the app store works is on a 24-hour clock.
2:47:26
So the the number of installs you get in a 24-hour period if it's more than any other app you rock it up to the top.
2:47:30
I didn't think it would happen on day one.
2:47:34
I actually had a whole I was convinced that we were going to go number one.
2:47:37
First of all I called this shot in August on Twitter.
2:47:39
I said we are going to un unseat dethrone chat GBT when we launch our app in November.
2:47:44
So we we shot our shot and we we kind of netted it but it happened within a couple hours of us going live. I didn't expect that.
2:47:54
I expected it to be about 48 hours.
2:47:54
So it happened very very quickly. >> Wow. >> Very cool.
2:47:59
>> We still have a lot we still have a lot of work left.
2:48:00
I mean you know obviously we're at the beginning of our journey. >> Call your shot again. 100 million in GMV.
2:48:06
When are you going to uh or when when are you going to hit it?
2:48:11
>> We're a couple months away from that. >> Okay.
2:48:12
Well, we got the gong ready for you. >> Amazing. >> You're in LA, right? >> Uh New York. >> Oh, okay. Okay.
2:48:19
>> Well, well, >> we we should we we should be able to get to that.
2:48:21
I mean, this this shopping season.
2:48:23
Let's see how Black Friday goes.
2:48:25
Make sure none of our systems go down.
2:48:26
But that that would be pretty dope. >> Yeah.
2:48:27
Really, this is this is your Super Bowl. >> Very cool. We'll talk to you soon. >> Great hanging, dude.
2:48:32
Congrats on all the progress. Congratulations. We'll talk to you soon.
2:48:37
Uh, let me tell you about wander. com.
2:48:39
Book a wonder with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, 247 concier service.
2:48:42
It's a vacation home but better.
2:48:44
And that's our show for today.
2:48:47
That's this week um in TVPN. Thank you for tuning in. Thank you for listening.
2:48:54
Thanks for hanging out in the chat if you've been chatting this week.
2:48:58
Uh we love you and we'll see you on Monday.
2:49:02
>> Have a fantastic weekend. >> Have a great weekend. Goodbye.