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Today's Friday, October 9th, 2025.
6:56
We are live from the TBPN.
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>> Oh, it's October 10th.
6:59
I forgot to change the date on my sheet. Good.
7:01
Thank you for catching that.
7:03
Uh we are live from the TBPN Ultradome, the temple of technology, the fortress of finance, the capital of capital.
7:08
Um and we wanted to open with this post by Jira tickets.
7:12
JT says, "Don't worry about the bubble.
7:15
If it pops, we'll just make a new bubble.
7:19
We got some guys who are really good at making new bubbles."
7:21
Uh bubble talk is >> We used to pray for a bubble like this. >> We did.
7:26
That was how we started the show. We said lever up.
7:28
We said we're praying for a bubble. Well, it's here.
7:31
People are starting to level up and it's time to double down and support our strongest soldiers.
7:37
>> Uh those who are holding up the uh the global economy and we are joined by some folks who are going to be holding up the global economy.
7:45
Sam Alman's joining in just 55 minutes.
7:46
Bill >> Bill Peebles >> Bill Peebles is joining the Sora.
7:49
Uh we also have a lot Gil, Robbie Stein from Google, Morgan Cowels coming on talk about a book.
7:58
Uh we have a couple other >> which was a $2 billion round that got yesterday >> and we have Dylan Patel from semi analysis talking about inference max uh which is already putting the timeline in turmoil.
8:12
Uh folks are uh taking shots at AMD but Dylan Patel says he has the data that can that shows that AMD in some cases can be a lower total cost to own.
8:25
Um there are certain models that favor AMD.
8:27
GPTOSS might be one of them.
8:27
Uh this is all from his new benchmark called Inference Max.
8:31
Uh where he's going to take us through it.
8:33
It's a fascinating uh project.
8:34
I think something like $50 million of uh capital was kind of marshaled just to run the GPUs to run the test to run the benchmarks because they run them every single night and they vary different models.
8:47
>> That Dylan's been able to marshall this amount of resources for effectively a test. >> Yeah.
8:52
And he makes no money from it. It's free.
8:53
It obviously people will work with semi analysis at some point. It's amazing.
8:58
But >> um basically uh all the different AI companies are in helping out with this. So we'll dig into that.
9:06
>> Boston in the chat says bubble made of steel.
9:08
Hopefully >> a steel bubble.
9:10
>> What about a a diamond bubble?
9:13
>> Yeah, >> a diamond bubble. >> I like it.
9:16
>> Something something there.
9:17
>> You can still see see through it.
9:17
Uh in the meantime, let me tell you about ramp. Time is money. Say both.
9:20
He's use corporate cards, bill payments, accounting, and a whole lot more all in one place.
9:24
Um, Mark Cuban, Dylan Ebercato on our team says, "Mark Cuban is the greatest marketer of all time.
9:32
Every video generated from his cameo includes brought to you by cost plus drugs, even when it's not in the prompt.
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He baked this into his Cameo preferences."
9:40
So, every Sora post he appears in is an ad for cost plus drugs.
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>> I love how shameless Cuban is about promoting cost plus drugs.
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A lot of people become a beanire.
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They they lose the ability to just be shameless. >> Not Mark Cuban.
9:55
He at every possible chance.
9:58
Even on our show, I think he was promoting cost plus drugs.
10:00
And I do think the uh the beautiful irony here of him, you know, not too many months ago saying, you know, we need to make sure that ads aren't in LLMs.
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He's the p first person to uh incorporate ads into Sora.
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Of course, not a language model, but uh still uh brilliant.
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>> I I had this idea, too.
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I'm I'm bummed that he scooped me, did it first.
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I did go into my prompt and I put always depict me as a bodybuilder and uh >> it worked really well.
10:34
>> Yeah, I I didn't >> except to your credit, you don't look that much different. >> Thank you. Thank you.
10:38
>> The the uh the OpenAI team was playing around.
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They made a made a video with John and Bill yesterday and they texted Ben.
10:45
And they were like, "By any chance, did John like do some type of prompt that depicts him as having very large muscles?"
10:53
Because I guess they were trying >> in a suit and they're trying to make it as accurate as possible, of course.
10:56
Uh, represent me appropriately and they just keep getting results of this like extra burly businessman.
11:02
Uh, but it's having a lot of fun.
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So, yeah, I mean, if you're playing around on Cameo, I highly encourage having some fun with that with that prompt.
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Uh, throw a brand in there, throw a description.
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I saw someone that said that they always want to be depicted with an Adamar pig watch on the wrist. >> There we go.
11:19
>> So, no matter what you what you prompt, they get an AP on the wrist, which I love.
11:23
If you want an AP, you can go to bezel. com. Get bezel. com.
11:26
>> Your bezel concier is available to source you any watch on the planet. Seriously, anyone.
11:30
>> Tom Osman in the chat says, "Jent, how's the horse?" The horse is fantastic.
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Can we pull up the horse cam?
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>> Checking in on the horse. >> Yes.
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>> Never been better, folks.
11:38
uh thriving after its first uh full week in the old film with us.
11:44
>> The horse is streamed live to all platforms thanks to reream one live stream 30 plus destinations multiream and reach your audience wherever they are.
11:51
Um >> lots of good questions coming in from the chat.
11:57
>> Uh Fannis says there's a downgrade on the quality store generates the last few days.
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Uh have you noticed that? Uh >> I have.
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>> It's hard it's hard to really tell. >> I haven't.
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I I I generated a few collabs with Sam and Bill last night.
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I thought they were fine. They were good.
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They take a minute, but I it's not noticeable to me at least.
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Um I Interestingly, I have noticed that the Sora app sometimes can't just load normal videos.
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The generation actually works fine for me.
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Interestingly, it feels like there's CPU poor because just the loading the actual feed sometimes loads and then just doesn't play.
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So there's something going on there where they're just scaling all parts of the system.
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I'm sure because I've seen some videos on Sora that now have like thousands of likes, which is clearly an indication that there are a lot of people >> consuming video on the platform.
12:47
Palunteered uh says that the channel Palunteered of course says OpenAI dropping$2 billion on a data center in Argentina deserves a seen this.
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This came out this morning.
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OpenAI and su Energy weigh a $25 billion Argentinian data center project.
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>> Wasn't there also a bailout of Argentina or something? >> Well, yeah.
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So, while OpenAI and Sir Energy are working on a $25 billion data center project, uh, Bessant is like figuring out how to bail out the Argentinian government for just 20 billion. >> Yes. Yes.
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There's this hilarious post by Alpha Pix.
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This was sent into our group chat like five different times.
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Says, "Bessenton, wake up.
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espresso shot 13th on Bloomberg quiz bailout Argentina and it just says it's a shot of a screenshot of uh Bloom a Bloomberg terminal and I guess this is from the quiz that goes out. He got a 242 score. Uh he's 13.
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It just says anonymous US Department of Treasury.
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Of course it could be someone else but it's very funny to imagine that it's him. I like that a lot.
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it's him. I like that a lot. Um anyways uh this uh I guess news leaked of opening sir energy they signed a letter of intent an LOI let's give it up for LOI's carrying a lot of weight these days for a data center project in Argentina requiring an investment of up
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to 25 billion the project would involve a large scale facility with a capacity of up to 500 megawws to support advanced AI computing according to a government statement >> structured under Argentina's reigi tax break scheme which went into effect last year. The project, if completed, would
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The project, if completed, would be one of the largest technology and energy infrastructure initiatives in the country's history.
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So, I'm sure we'll get more news here, but another day, another um multi-billion dollar announcement from >> there was a there was a moment when um >> Whoa, Taylor Hodgej in the chat.
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Buenos AI race nominative determinism is going crazy.
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There was a moment when uh the the sovereign AI initiative was very much about building a data center and then running open source software on it.
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But I do think that it's not that unreasonable to say that uh it is critical to your geopolitical strategy as a country to just have an open AI data center in your country because then you have access to the open AI API at lower latency potentially.
15:07
Chad GPT runs better in your country.
15:10
better in your country. uh that could you know be uh not just profitable from like a business perspective but it's also a matter of like going where the energy is like if you're a country that has cheap energy it makes sense to kind of set up infrastructure there instead of trying to manufacture all of the
15:26
energy in America all the build all the data centers in America and then uh just have all of the tokens flowing over the internet backbone I don't know doesn't seem that crazy to me but the uh the market is selling off it's very sad I wish we could be wearing white suits today but uh it's a rough day in the market. The Dow is down 1.25% The Dow is down 1.
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25% and the NASDAQ is down like >> one member of our team who who we won't name uh was using leverage and opened up their brokerage this morning and immediately said, "I'm chopped and cooked in a very in a very Gen Z way."
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We uh at the team breakfast this morning, everybody got a got a good laugh.
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So, uh hopefully he'll be uh so back very soon. >> Yes. rough one out there too. >> Yes.
16:12
And the reason uh that most people are describing why the the stock market is falling is because of a uh news from Donald Trump.
16:22
Before we get into reading Donald Trump's statement, uh let's tell you about privy wallet infrastructure for every bank.
16:27
Privy makes it easy to build on crypto rail, securely spin up white label wallets, sign transactions, integrate onchain infrastructure, all through one simple API.
16:34
>> DJT should put ads in these posts so long.
16:37
I mean, he's really m actually maxing out the word count on some of these.
16:42
Uh but but yeah, as John was S&P, >> we talked about this yesterday in the journal.
16:47
It made it to made it to the front page of the journal today.
16:49
Uh yesterday, China squeezes the United States in rare earth move.
16:53
So, China's newest restrictions on rare earth materials would mark a nearly unprecedented export control that stands to disrupt the global economy.
17:01
That does not sound good.
17:03
uh giving Beijing more leverage in trade talks and ratcheting up pressure on the Trump administration to respond.
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So, we talked about this yesterday.
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We went through some of >> Isaac Foster in the chat just needs more leverage to come back. >> 100%.
17:19
>> Get the intern more leverage. Make it all back.
17:21
>> Always always lever up.
17:21
Uh so, yes, yesterday we read through Dean Ball's uh analysis of the rare earth move by China.
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Um there's there's some green shoots there.
17:32
We do have America does have some leverage, but it's all in the backdrop of this larger trade negotiation.
17:37
Uh, now the United States government has responded.
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Donald Trump has responded with this letter or this post on Truth Social.
17:44
I think they're just called Truths over there.
17:47
>> Uh, he uh and Kobe and the Kobe letter uh kind of breaks it down.
17:50
Breaking the S&P 500 falls 70 points in seconds after President Trump publishes the below paragraph about China.
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Trump says he is calculating interest uh increased tariffs on uh Chinese products.
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Trump also says there is no reason to meet Chinese President Cinping anymore.
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And so uh we can read through a little bit of this. It's a very long post.
18:12
He's he's he's becoming a thread boy over there.
18:15
Uh Trump says some very strange things are happening in China.
18:18
They are becoming very hostile and sending letters to countries throughout the world that they want to impose export controls on each and every element of production having to do with rare earths and virtually anything else they can think of.
18:31
Even if it's not manufactured in China, nobody has ever seen anything like this.
18:35
But essentially, it would clog the markets and make life difficult for virtually every country in the world, especially for China.
18:40
We have been contacted by other countries who are extremely angry at this trade hostility which came out of nowhere.
18:46
Our relationship with China over the past six months has been a very good one, thereby making this move on trade an even more surprising one.
18:54
I have always felt that they have been lying in weight.
18:58
And now, as usual, I have been proven right.
19:00
There's no way that China would be allowed to hold the world captive, but that seems to have been their plan for quite some time.
19:06
Starting with the magnets in quotes and other elements that they have quietly amassed into somewhat of a monopoly position.
19:13
A rather sinister and hostile move to say the least.
19:17
But the US has a monopoly has monopoly positions also much stronger and much more far-reaching than China's.
19:24
I have just not chosen to use them.
19:27
There was never a reason to do so until now.
19:29
He says uh the letter they sent is many pages long and details with great specificity each and every element that they want to withhold from other nations.
19:37
Things that were routine are no longer routine at all.
19:40
I've not spoken to President Xi Jinping uh because there was no reason to do so.
19:44
This was a real surprise not only to me but to all the leaders of the free world.
19:49
I was to meet President Xi uh in two weeks at Apac in South Korea, but now there seems to be no reason to do so.
19:56
Pulling out of the talks.
19:58
Uh the Chinese letters were especially inappropriate in that this was the day that after 3,000 years of bedum and inviting there was peace in the Middle East.
20:06
I I I wonder if that timing was coincidental.
20:08
uh putting putting on the tin foil hat.
20:11
Uh just noticing coincidences.
20:14
Uh depend dependent on what China says about the hostile order that they have just put out.
20:19
I will be forced as president of the United States to financially counter their move for every element they have been able to monopolize. We have two.
20:24
I never thought it would come to this.
20:26
But perhaps as with all things the time has come.
20:30
Ultimately though potentially painful it will be a very good thing in the end for the USA.
20:35
One of the policies that we are calculating this moment is a massive increase in of tariffs on Chinese products coming to the United States.
20:42
Uh there are many other countermeasures that are likewise under serious consideration.
20:45
Thank you for your attention to this matter.
20:47
And so um it's a uh the trade war is returning and uh we will continue to monitor the situation >> and again don't need to freak out.
20:56
The S&P's record high was just uh couple days ago. Yeah.
21:01
So, >> and with all these uh you know the the tensions can ratchet up very quickly.
21:05
We saw this with the uh the uh tariff tantrum, the liberation day, the massive sell-off and then uh quickly things were negotiated and largely reversed in many ways.
21:18
A lot of companies got through that.
21:19
I mean, we just experienced this with base power where we were like, so you're in a lot of trouble and then they got through it entirely very quickly and raised a billion dollars. >> Yeah.
21:29
raising a massively overs subscribed round. >> Yeah.
21:32
But but in in the >> I don't necessarily think that it changed their strategy. >> Oh, that was rough. >> Well, yeah.
21:37
And I don't think it changed their strategy.
21:38
I think they always intended to set up the factory in Austin, course, >> but I'm sure it certainly accelerated >> uh they have, you know, they have to get certain the supply chain is so global all over the place that uh it it was certainly a cause for concern.
21:51
But >> well, speaking of energy, Oaklo, uh the Oaklo, >> uh nuclear company that Sam Alman backed years and years ago.
22:00
I think he's no longer on the board now.
22:03
>> 2014, >> but uh Oaklo is up almost 10% today.
22:03
So little >> green in the midst of all a lot of red.
22:12
>> Well, let me tell you about Cognition.
22:14
They're the makers of Devon.
22:14
Devon is the AI software engineer.
22:16
Crush your backlog with your personal AI engineering team.
22:19
Um, Pedro Domingos has a chart from the Financial Times showing the number of years after release to scale the internet versus just scaling chat GPT.
22:30
And the internet took 13 years to get to 800 million users.
22:34
Chat GPT took a little over two, maybe three. So, >> and remarkable.
22:43
>> The internet is the greatest distribution engine for products in history. >> CHgPT. Yeah.
22:47
And so it's it is a very acceleratory effect.
22:52
>> Um, >> Tron Aries is getting some reviews.
22:53
The Telegraph had a headline today.
22:56
They said, "Tron Aries is so bad it makes you wish AI would hurry up and destroy Hollywood."
23:04
>> Long case for one out of uh, one out of five stars.
23:08
Film populated by some of the most aggressively charmless characters ever seen in a blockbuster.
23:14
>> Almost makes me want to see it now. >> I agree. I agree. I want to see it. I loved the first Tron.
23:18
I'm optimistic that uh the second Tron will deliver in one way or another.
23:22
Um either way, should we go to SoftBank?
23:26
Masayoshi Son is seeking $5 billion in a margin loan backed by ARM stock.
23:32
We know that he's uh he's flush with ARM stock.
23:35
It was the way he made his second 100 billion.
23:37
He made his first with Alibaba and his second with ARM.
23:42
Uh, so SoftBank Group is in talks to borrow 5 billion from global banks, refilling its coffers at a time Masayoshi Son is accelerating the Japanese investment firm's bets on >> We got to pause for one second and give Masa credit for not top ticking OpenAI.
24:00
He invested earlier this year somewhere around a $330 billion valuation.
24:04
A lot of people were saying this is crazy.
24:06
They thought it was bearish.
24:08
Now, OpenAI just closed uh >> yeah, >> a secondary or or a tender offer at 500 billion.
24:15
So, nice little markup for MASA.
24:18
Hopefully, he's been able to actually fund the entire investment.
24:20
I think there's a number of OpenAI investors that have been, you know, working to uh pull the capital necessary together.
24:30
>> It was also a uh >> it was it was a big jump in valuation at the time.
24:35
I feel like it was more than like a 2x step up or something from the previous round that everyone was talking about.
24:40
And so it was like, oh, okay, this is this is a big jump in valuation, but of course the business had grown.
24:45
Uh, and it was also there was also that funny picture of Masayoshi S holding a crystal ball and then dropping it and you could read all sorts of things into that.
24:54
But if you read too much into it, you would be wrong because uh it's been a tear and he's done quite well.
24:58
But now he is uh levering up further.
25:00
So SoftBank is close to signing a deal with a handful of lenders for a margin loan secured by shares of its chip of its chip unit ARM Holdings.
25:08
Um the capital will fund additional investment in OpenAI this year.
25:12
The people said uh who asked not to be identified.
25:15
A margin loan is a type of facility where you borrow money using your investments like stocks as collateral.
25:20
A representative for Soft Bank declined to comment.
25:23
SoftBank shares slid 4% on Friday, the most since September 26th.
25:28
>> And ARM is down 8% themselves.
25:28
I wonder how much that is tied to the other stuff.
25:33
>> Part of it is Morgan Stanley lowered their price target based on the 2027 >> for Soft Bank or ARM >> ARM 2027 guidance. So that's a factor. But >> yep.
25:42
>> Um >> so S has embarked on a spending spree this year to try and position the firm as a lynch pin in the global AI boom.
25:48
Uh most recently pledging as much as 30 billion towards OpenAI and buying ABB's robotics arm for 5. 4 billion.
25:55
I had no idea he bought an entire robotics division.
25:59
That's that's pretty cool.
25:59
Uh ARM's 38% rally this year has in turn granted SoftBank the confidence and leeway to grow its investment.
26:06
Warchest Soft Bank has raised a total of 13 billion in margin loans from ARM shares with 5 billion still under undrawn.
26:12
I wonder how much Elon uh took in margin loan during the uh the Twitter buyout because I feel like some of that was backed by Tesla stock.
26:22
He was saying he wasn't going to sell Tesla stock but then I think he got a margin loan against it maybe. I'm not exactly sure.
26:29
All I know is that that X the social media platform or Twitter y what was originally Twitter's like annual interest payments were north of a billion >> which was part of what what created urgency to you know merge with XAI had a
26:46
had a obviously larger valuation and again still putting pressure on the combined entity but uh at least uh the equity overall is marked up substantially I think if I remember correctly Yeah, they there was like something around I think it was like very levered. It was like something like
27:02
It was like something like they had like 30 billion >> something like that.
27:05
There were a couple different tanches and I I don't remember the exact uh details but uh I mean it was able to roll it into XAI and you know raise more money and so you know uh these things can can kind of like you can you can move the chips around the board uh for for years and and try different things to to piece together value.
27:26
Um, well, if you want something that you won't have to need, you won't have to go into debt to sign up for because you can sign up for free, figma.
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27:37
Uh, the group had secured about 8 billion in margin loans ahead of ARM's initial uh, IPO.
27:43
Uh, in 2023, 11 banks including JP Morgan, Barclays, BNP, uh, Craig Agricol, uh, Goldman Sachs provided the facilities by linking mandates for arms IPO to loans.
27:54
Um earlier this year, the group also raised a $15 billion one-year facility to help fund AI investments in the United States in what is among its largest borrowings raised.
28:05
Um Zone's insatiable appetite for deals has extended far and wide.
28:12
>> I thought I thought I was going to say insatiable appetite for leverage >> for capital deals.
28:15
I mean, when when should you have a satiable appetite for deals?
28:22
Everyone should have an insatiable appetite for deals. >> Yeah.
28:24
um centered on ideas to capitalize on the ex on the expected exponential growth of AI technologies.
28:29
His most ambitious projects include the $500 billion Stargate initiative that aims to build data centers across the United States in partnership with Oracle and OpenAI.
28:38
SoftBank is also exploring the feasibility of large-scale industrial manufacturing hub in the United States. That's cool.
28:44
Uh which would encompass production lines for AI powered industrial robots.
28:47
That's probably a little bit further out but but pretty cool.
28:51
uh SoftBank joins a wave of big tech firms and investors plowing unprecedented amounts of capital into a technology with the potential to transform industries and economies.
28:58
But the flurry of deals and partnerships, many involving Nvidia Corp and OpenAI are escalating concerns that an increasingly complex internet.
29:06
Something that I want to understand better is how much chatter there was about the circular telecom deals in in like 1999 and and early the early uh in the first quarter of of 2000 because >> Oh, I mean by the first quarter of 2000 it was like front page everywhere.
29:27
>> Well, things didn't really correct until March. >> Yeah.
29:31
But in 1999, >> the New Yorker ran a profile of Mary Mer that's called the woman in the bubble.
29:39
So like the New Yorker, which isn't in the business of like calling bubbles early, was just describing it, you know, like everyone agrees that this is a bubble and we're profiling someone who's at the center of it. >> Yeah.
29:51
>> In the New Yorker, which I feel like is still months below.
29:52
you know, over the last couple weeks, you can't scroll three posts. >> Yep.
29:58
>> Without seeing somebody, you know, posting some type of graphic or or meme or just general concern for >> the circular nature of some of these transactions. >> Yep.
30:08
>> Um the uh you know, and Doug's point is like uh from some analysis uh from Monday's interview is that you know, the next leg up in the bubble is leverage.
30:20
But here Morgan Stanley in this article is estimating the amount of debt tied to AI has ballooned to 1.
30:24
2 trillion making it the largest segment in the investment grade market. So >> pretty remarkable.
30:31
Yeah, we were talking about like when does the number actually get big in terms of total debt because if you look at like the market for treasuries that's obviously way bigger or the market caps of all the hyperscalers combined that's you know 10 to 20 trillion. It's really really big.
30:49
Uh but one trillion of debt feels like a lot. That feels like a lot.
30:51
Um and so uh I wrote >> and the but but the notable thing here is is understanding uh who is actually on the hook for the debt. Right.
31:00
A lot of I think OpenAI broadly has done >> has has made a a extremely uh made it had a focus of not tying the debt to the actual for-profit entity and then obviously not the the nonprofit itself. Right.
31:17
So the question is they can be at the center of all this, but they're not necessarily directly on the hook for >> um any of this, you know, 1. 2 trillion. >> Yeah. Yeah. Yeah.
31:28
Where where does the actual debt live? What is it entitled to?
31:32
Does it have warrants over equity?
31:34
Like all of that matters a ton.
31:34
Um I wrote about uh the bubble talk in today's newsletter. You can sign up at tbpn. com.
31:43
Uh, and I was reflecting on 10 years ago in 2015, Sam Alman was also being, you know, talked about.
31:52
A lot of people were talking about the bubble.
31:54
Vanity Fair ran a uh, an article at the time that said something to the effect of like, uh, like we talked to multiple experts in financial bubbles and they say it's going to pop any minute.
32:05
Uh, and so Sam formulated this bet and said that uh, like look, I'm the I think he was the head of YC at the time.
32:13
He was like, I don't think we're in a bubble right now.
32:18
And he framed it in three propositions that all had to come true.
32:22
So the first one was Uber, Palunteer, Airbnb, Dropbox, Pinterest, and SpaceX.
32:26
They were worth under a hundred billion at the time in 2015.
32:30
by 2020, five years from then, he said they have to be worth more than 200 billion.
32:34
And second, he said mid midsize companies, Stripe, Zens, Instacart, Mix Panel, Teespring, Optimizely, Coinbase, Docker, and Weebly together had to be worth over 27 billion.
32:46
They were worth less than nine back in 2015.
32:47
And the brand new YC Winter 2015 batch needed to be worth over three billion.
32:52
And what's crazy is that if you if you just think about those those three those three buckets, which one?
33:00
So Sam got two of them right. He missed on one.
33:03
Which one do you think he missed on?
33:07
>> The big companies, Uber, Palunteer, SpaceX, those ones needed to double.
33:09
The midtier companies, Stripe.
33:14
>> Well, I'm not going to pretend I know that he missed on the big the public companies.
33:17
>> He missed on the big companies, which is crazy because today Uber's a $200 billion company.
33:22
SpaceX and Palanteer are both at 400 500.
33:24
So you have over a trillion dollars now.
33:27
But he missed because a couple of those companies had kind of traded down that particular year.
33:33
But he hit on the second one.
33:35
Coinbase obviously went huge. Stripe as well.
33:37
And uh and in the third in the in the uh in the YC winter 2015 batch, there was a company called GitLab that's already worth something like seven or eight billion dollars in the public markets.
33:48
Uh and so he hit on all on basically all of them.
33:51
I still regard it as like he was very very close to being just completely correct. He did lose the bet.
33:57
But as we talk about another bubble, I was I was thinking about like should we have another framework for like where we expect things to go in 5 years to assess it?
34:05
And I feel like energy is where we should go with this.
34:10
So in the newsletter, you can go read it.
34:11
I tried to formulate like how much energy open AAI will be consuming in in 5 years in 2030, how much energy data centers globally will be consuming and how much energy will the United States be producing.
34:22
And there are obviously linear projections of all of these.
34:25
But I think Sam is uh is bullish on the idea of like we're going to destroy those uh those estimates and we're going to see significant buildout and he's certainly doing deals to make that happen.
34:38
Um, but I wonder how he would quantify it.
34:40
So, I'd like to dig in there.
34:43
Um, but first, let me tell you about Vanta.
34:45
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34:48
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34:58
>> There's an article in the New York Times today, let's go through it, on uh a Singaporean firm called Mega Speed.
35:06
>> Uh, the CEO has socialized with Nvidia's Jensen Hang.
35:08
Now, the company is being scrutinized by US officials for its ties to China.
35:12
So, on a humid June night last year, Jensen Hong, the chief executive of Nvidia, held court with several of his company's major Asian customers at a bar with sweeping views of Taipei.
35:22
They stood and toasted the booming artificial intelligence industry.
35:27
Next to NVIDIA chief was a woman named Hang Lee Lei or Alice Wang, an executive of Singapore based data center company called Mega Speed.
35:36
great name which was poised to buy 2 billion of Nvidia chips.
35:38
Though Miss Huang and Mega Speed are littleknown players in the AI industry, their association with Nvidia and its CEO has recently become a preoccupation in Washington.
35:48
Commerce Department officials have been investigating whether Mega Speed, which has close ties to Chinese tech firms, is helping companies in China sidestep American export restrictions, according to more than a half dozen current and former officials and other people familiar with the companies who spoke on condition of anonymity to discuss an examination that is not public.
36:06
The inquiry inquiry uh which is active calls into question how closely Nvidia is tracking where its AI chips end up and highlights the possibilities of American export laws easily being sidestepped.
36:16
Mega Speed is also facing scrutiny from Singaporean police who told the New York Times in a statement that they are investigating the company for breaching local laws without elaborating further.
36:25
As the dominant provider of AI chips, Nvidia's annual revenue has soared.
36:29
I'm going to skip over this because I know you already know this. >> Yeah.
36:34
>> Um, so >> while you skip over that, let me tell you about graphite.
36:37
dev code review for the age of AI.
36:38
Graphite helps teams on GitHub ship higher quality software faster. Continue, Jordy.
36:41
Uh, Mega Speed illustrates the challenges facing US government officials trying to keep China from assessing powerful AI chips after splitting off from a Chinese gaming company in 2023.
36:50
Mega Speed set up a subsidiary in Malaysia that quickly snapped up nearly 2 billion worth of Nvidia's most advanced products.
36:56
Most of those chips came from the US branch of a Chinese company that has already been sanctioned for providing technology to the Chinese military according to records obtained through Import Genius, which is started by sorry >> uh Ryan from Flexport. >> Yes, that's right. uh and his brother.
37:13
>> That was his first uh David >> uh that was his first Yeah, that was his first company.
37:16
Uh it's so funny that uh the whole like pivot to AI is not just a Silicon Valley American meme.
37:21
Like it's definitely happening in China, too.
37:24
They're like, "Yeah, we're doing gaming, but like you know, this AI stuff is way better.
37:28
Let's just pivot to AI or like Highf Flyer being like, we got to we got to get on the large creating is cool."
37:35
>> Yeah, it's cool, but like let's just uh let's focus on AI. >> Yeah.
37:38
So, anyways, this this story is evolving.
37:40
Um I I'm not surprised to hear that that I mean I think it's actually good that the commerce department is like trying to figure out what's actually happening here.
37:48
I think there's been a lot of rumors floating around of like >> uh you know data center companies in uh Malaysia and Singapore you know having >> you know an extreme uh demand for chips and this sort of uncertainty of like okay who's actually uh paying.
38:02
remember one of our first episodes, we read a Wall Street Journal article on uh Malaysia, the the uh the Switzerland of AI because everyone was building a ton of data centers there so that they could uh sell inference or build token factories that would sell to both American companies, Singaporean companies, Chinese companies, and it was kind of like this neutral territory.
38:24
But as the trade war heats up, people are going to want um more answers, more um more analysis.
38:31
they they're going to want to understand exactly, you know, are any of these things fit?
38:35
Does every deal fit perfectly within the current restriction framework? Right. Yeah.
38:42
>> Because obviously diversion is a is a natural thing.
38:44
I mean, we've heard we've heard stories of this in the Ukraine Russia conflict where companies will go, you know, entrepreneurs will go buy DJI drones and then go deliver them and you know what what are the actual restrictions on that?
38:55
all gets uh when when when the economic stakes are high and things are trading at a premium, you can literally I mean we've heard this from uh there was one account of someone loading the training data onto hard drives, flying to another country, doing the training run, saving the weights onto hard drives, then flying back.
39:13
And it's like that's kind of hard to predict.
39:17
That definitely is a runaround on the chip controls.
39:19
It's not it's not the the stated goal of those chip controls.
39:23
Um, but you know when there's huge dollars on the line and training runs are extremely valuable and I think figure out a way it's fair to kind of try to understand Miss Hong, the CEO of Mega Speed's background.
39:34
She spent uh much of her career in mainland China including working as a television reporter from Chinese state media.
39:41
>> Let's hear it for television reporters. One of us.
39:43
One of us from >> One of us >> from uh being a television reporter to uh creating a new hyperscaler.
39:51
do anything in this world. >> Who knows?
39:54
I think we'll stay out of that game, but uh good to see that you can go anywhere.
40:02
>> We'll leave it to our friends.
40:02
Good post here from High Yield Harry. >> Okay.
40:07
>> It says A16Z and Seoia co leading around.
40:10
>> It's the Crips and the Bloods. Is that what this is? >> Uniting. >> Uniting.
40:14
>> Um >> is that what's happening? This is about KHI.
40:16
referencing uh referencing Khi uh who followed Poly Market who announced their $2 billion financing earlier this week from ICE.
40:25
Um not the immigration >> no >> uh uh branch of the >> not the international commodities exchange the intercontinental exchange. >> That's right. >> That's the name.
40:37
Um but uh Khi raised 300 million uh backed by Andre uh Horowitz and uh the the prediction market wars are uh heating heating up uh dramatically.
40:52
Coinbase, Google's Capital G, A16Z and Paradigm uh were investing in this new uh as well as Seoia were investing in this new round.
41:02
>> Um and so by this point everybody's sort of picked a picked a side. >> Yep.
41:07
Um, and uh, I would not want to be a net new prediction market company getting started today.
41:15
I think there's going to be an insane >> uh, the capital war is just sort of starting in the category.
41:21
>> I mean, do you remember the capital war between Lyft and Uber?
41:23
There were >> there were like three or four probably 10 other companies that were in the ride hailing industry and they like they aren't public companies today.
41:36
They they they either sold or pivoted or found some other niche.
41:40
But uh when you're when you're in this like duopoly world and this capital fight and there's maybe one that's running away one way or another um it uh yeah it's painful to be number three.
41:51
Kalshi is on track to do 50 billion in trading volume trading volume and they did 300 million last year. So a pretty wild jump.
42:00
So >> yep, >> competition uh is certainly heating up.
42:07
This will be an interesting one to watch. >> Yeah.
42:10
Um Brandon Jacobe is putting another app in the truth zone. What happened here?
42:16
Brookwell launched a uh an app, I guess.
42:20
And Brandon Jacobe says, "Hey, Brookwell app, great design.
42:24
I was proud of it when we designed it for capital in >> Yeah.
42:27
So, I guess this company um so this company uh Brandon and I obviously worked together to design the app that you can see here.
42:33
Brandon is an incredible designer and spent uh >> hundreds of hours developing uh this experience.
42:41
experience. Uh and ultimately, I think Brokewell seemingly >> same pretty much copied it to a T and then even doubled down and said like yes and >> wait really >> like the the founder replied yeah >> basically saying yeah I mean I think it's like >> it's sort of fair if it's not like fair
42:59
game yeah fair game for to pull a design off the shelf that's not actively being used as much like you know >> but uh you go further back in time like >> you can still bring your own ideas to it you know I think Brandon's frustration is probably just that you didn't bring many new ideas, just kind of copy and paste it. So,
43:19
So, >> yeah, >> a lot of that going on.
43:22
>> Uh John Titer is quoting a post uh that says, "This is a camera.
43:25
Uh it's 200 by 200 pixels, 30 frames per second.
43:28
Uh I didn't know they made cameras this small."
43:32
John says, "There are certain things you just can't learn about if you're prone to paranoia." >> It's actually crazy. >> Yeah.
43:39
Uh so the I mean the uh the community note gives a little bit more context here.
43:44
It does say that this is the camera module.
43:47
It is capable of producing an analog video output but it needs a power supply battery or storage.
43:54
And so >> yeah and the concern here is the implication is that this camera could be built into effectively just like a dot on the wall and you could store the power.
44:05
>> Oh, it's only 200 200 by 200 pixels.
44:05
I was saying, should we get these and put them all around the set and so you just walk into the TBP and Ultradome and you don't see any cameras moving.
44:13
Like we have a slider cam now.
44:15
We have a lot of different cameras around and you kind of trip over them and you know you got to cable manage them.
44:21
But imagine if we could just put one little dot on that turbo puffer fish there, one little dot on the microphone.
44:26
You can just get any any image from any place.
44:28
Uh maybe >> big debate on the timeline over whether you should have shoes on or on in the office.
44:35
Ben lying over at cursor says no shoes at cursor NYC.
44:38
Will O'Brien says if Ulisses ever ends up like this, you have permission to shoot me in the face.
44:47
Very aggressive uh response.
44:47
I I uh I I can see why companies that are just, you know, want to want to be cozy, want to have a I think wearing uh shoes in your home is insane. Okay.
45:02
>> I'm very against uh walking around the house with shoes that you wear out in the world.
45:07
Plenty of studies that just show you're just tracking in whole host of things. >> Makes sense.
45:12
>> Um and >> do you do slippers in the house then? >> I I enjoy slippers.
45:16
>> I feel like if you if you don't do slippers, then you need to keep keep the whole house warmer. You need more carpets.
45:22
But um I wonder I wonder what else went into uh the plan to make sure that Cursor HQ in New York City is fully cozy because you don't just want to take off your shoes and be around like we have concrete floors here.
45:35
We are shoes on facility.
45:37
Uh no one takes off their shoes but uh if we were to go to shoes off I think we would need to get some carpets uh keep the place a little bit toastier. >> Yeah. >> Right.
45:47
Or or maybe give everyone a pair of slippers. >> What's going on here?
45:49
this account Toys XYZ is sharing a nano banana watermark.
45:54
Have they how do you know how this works functionally? >> Yeah.
45:57
So, um >> you have to like turn like uh do you have to basically increase the saturation of the photo in order to >> Exactly.
46:04
So, this pattern that you see are are subtle changes in the saturation.
46:09
And if you go to the next image, you can see what it looks like on an actual nano banana image.
46:13
Um not just the watermark.
46:16
And so this is this is a uh a a black and white image.
46:19
This was generated as black and white, but nanobanana uses slight variations in the colors to just have a little bit of saturation.
46:30
So normally if you're looking at like u a grayscale image, basically the saturation is turned down to zero and there is no color whatsoever.
46:39
There is only uh there's only brightness, right?
46:41
you're you're going from zero to one just on the black scale.
46:46
Nano Banana, even if you ask for a black and white image, it will output an image that does have a little bit of color and it will vary this pattern.
46:51
So there's little bits of red, little bits of green, little bits of red, little bits of green.
46:56
And uh and so this is being put in every nanobanana image.
46:59
Of course, as soon as you discover this pattern, there's probably some ability to remove it.
47:06
Even just a slight edit might change this.
47:08
Um, like you could just go in and actually reduce the saturation to zero and then the watermark's gone.
47:13
Um, and I'm sure people will do that, but it's >> Yeah, there will be somebody will make an app where you just upload an AI photo and then it figures out which which uh which model generated it and then figures out how to remove whatever hidden watermark is included and you have a clean image. >> Totally.
47:29
There's already a ton of Sora watermark remover tools out there.
47:31
It's I think this is still just more useful for uh you know having a reality check on like you know was someone dumb enough to not even remove the watermark at least you can just automatically flag that and a lot of and at least it injects an extra step an extra cost into generating um you know like spam images or whatever you would want to do that's like malicious that would you'd want to discover the watermark.
47:57
Um, but fortunately I feel like even with Nana Banana, uh, you can still just look at the image and tell.
48:02
Um, but if you want to generate some generative media, head over to Fall, the world's best generative image, video, and audio models all in one place.
48:10
Develop and fine-tune models with serverless GPUs and ondemand clusters. Let's fall. >> Jared Kushner. >> Jared Kushner.
48:19
Uh they they uh Matt uh Stee uh said in an article a while back, Jared Kushner claims he can solve Israeli Palestinian conflict because he's quote read 25 books on it.
48:29
Uh and of course seems like that was hopefully >> the real reason is what will Manitis said is that >> New York real estate. >> Yes. Yes.
48:40
He's been doing New New York real estate deals and so he's ready to broker another real estate deal effectively.
48:46
Um but uh I mean we we haven't really covered the the uh the the peace deals.
48:51
The journal's writing about it a little bit.
48:53
Um there's uh I guess there's going to be a vote, but there's plenty of ser there's plenty.
48:58
>> In other news, Barry Weiss asked everyone uh at across CBS News to send her a memo by next Tuesday explaining how they spend their workday and what's working not working.
49:10
>> Is this a what did you get done this week?
49:11
Basically, >> it's a it's a what what exactly do you do here? >> You think it's that?
49:15
>> You think it's that? I I I think I mean ask it's great asking hey what's working what's not working but as a manager and you're coming into a new organiza or a leader you're coming into a new organization you want to get a pulse on okay what what are people actually doing
49:29
here >> because I think the question is >> with this with with everything that uh David Ellison is doing is is he trying to turn these into media companies that can create massive cash flow >> is or are they strateic IC enough like I don't think when Jeff Bezos was buying
49:49
the Washington Post he was thinking I'm buying this to make money necessarily >> and so the question is I think Max Tonyie here I my the way that this has been written I think uh the question is like are they going to let a bunch of people go kind of how I would I would read into it but
50:07
>> yeah I mean at the same time like if you're coming into a a if you're coming in as CEO or you know editor-inchief of a organization and you're like, I my my view on it is that they're actually severely understaffed and the first thing I'm going to do is is triple headcount. It's still reasonable to ask
50:23
It's still reasonable to ask what everyone does.
50:25
So, you understand like, oh, okay, this person's doing five different jobs and they're working 200our weeks, like maybe we need to get them some extra support.
50:34
But I agree with your your your general assessment.
50:37
Uh, and it certainly would be a little bit stressful to get this email from Barry.
50:41
But, uh, you know, she says, "Please be blunt. Just break it down.
50:45
Recommendation, don't use AI. >> Any M dashes?
50:49
>> Uh there is an M dash, but we know Barry uses M dashes.
50:51
She's been using them for decades, so there's no maybe not decades, but um for, you know, her career.
50:57
Uh it is it is the the reason that it's in the model is because it's a popular writing tool.
51:00
Um anyway, uh Cloudflare did a new uh rebrand powering 20% of >> and I guess uh Tai, former uh member of the party round team, I guess was behind this.
51:13
Why else he'd be sharing it?
51:13
Uh and he also was co-founders with Dylan on CTG, which they >> Oh, no way. That's very cool. A little bit of lore.
51:23
>> Ty is a legend, extremely talented designer.
51:27
when he he was he had reached out to >> us at Party Round and >> we didn't we I talked once with him if I remember correctly.
51:37
We didn't immediately make an offer.
51:38
We were just kind of like, "Yeah, let's keep talking."
51:41
And then he built an entire game, like a simulation of a of a of a Game Boy game uh that you could play on your phone.
51:51
And he just sent it to me. He like built it.
51:52
This was like pre pre vibe coding.
51:55
He just built it and sent it to me.
51:56
It was web based basically.
51:58
>> It was uh No, it was mobile based.
51:58
Um and I just immediately called him and I was like, "Okay, we're bringing on the team. This is amazing." >> Very cool. Very cool.
52:05
I mean, seems like good response. Thousand likes.
52:06
No one's uh people are very opinionated about branding, launches, uh you know, uh launch videos, all sorts of stuff.
52:15
So, >> yeah, he it was I found the original post.
52:19
Uh it was a Pokemon style game where you could build like a cap table basically. >> Uh collect investors. Exactly what you want. For sure. >> Great stuff. Great stuff.
52:28
Um >> um if you're just tuning in, Sam Alman will be joining you in about 10 minutes.
52:35
Uh he's on for half an hour and then we're talking to El Gil.
52:36
Um before we move on, let me tell you about Turboper.
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52:45
Um, >> you see this Reddit post circulating that lists OpenAI's top 30 customers by token consumption and apparently Dualingo is at the top of the list.
52:56
Uh, second is Open Router, but of course their platform >> doesn't really count. Yeah.
53:02
>> Routing uh routing uh uh consumption.
53:06
>> Uh, surprising to see Indeed at the top of this list.
53:10
>> Do you see number nine, baby? >> Number nine. >> Let's go. It's ramp. com.
53:13
Um, >> see Warp Dev on there. Shopify. Sure.
53:17
>> Also, >> what what so so I I when this came out uh because of their uh I I I don't know if there was this table is like a leak or something, but uh at Devday uh OpenAI put up a list of names of people that had been using over a trillion tokens, right?
53:35
And they and people kind of reverse engineered that to understand what these what the people who like what companies they work for, right?
53:41
companies they work for, right? And I was trying to make a meme that I was sending you and I it wasn't quite hitting but it was like the the Atlas holding up the world meme and it was like the entire global economy but instead of like open AI which is the
53:54
current meme it's like 30 companies in wildly different markets that are all using AI and so that like the like you would be more worried I think if this was more circular and this is the Martin Scrowley take which is that if it was if you looked at the the top 30 customers
54:12
and it was all like AI chat GPT rappers or something something very circular you would be worried um but instead it's companies like Indeed and Dolingo and ramp and Shopify and all these companies that are touching very different pieces these aren't competitors like Dolingo is
54:30
not a competitor to Shopify and so it feels like an it feels like evidence that that this is like less circular I don't know >> yeah I mean the uh it is the The Grock CEO of Grock GR OQ uh recently said that 35 to 36 companies are currently responsible for 99% of token spending in AI right now. Even among those 35
54:51
Even among those 35 companies, two are by far the most significant spenders and their openthropic.
54:57
So it's crazy that that's generation that that's buying inference.
55:03
I'm talking about the companies that are buying from open AI >> and buying from anthrop one more step >> because it's like if I'm fine with like like it's scary when you hear like open AI is buying 99% of of AI stuff but then when you look under the hood and you see like Dolingo and Ramp and Shopify it's like okay well that's actually like pretty diffuse in the economy. >> Yeah.
55:26
Um, >> so yeah, there's two significant spenders, but in those spenders are thousands of other companies, right? >> Exactly. Yeah.
55:34
And I wonder, um, just this idea of like there's a there is a trend.
55:39
We're in a trend right now, the AI wave and it's holding up the global economy like has have other trends held up the global economy successfully?
55:46
Like if we go back to industrialization, was that was that holding up the global economy?
55:54
Did it successfully hold up the global economy or like global trade, the containerization that held up the global economy and and like there were certainly like ups and downs, but like it kind of successfully held up the global economy. >> Yeah.
56:07
And certainly the I mean uh going back to that clip from Ken Griffin earlier this week, he was basically saying that in in 1999 and 2000 it was incredibly obvious that the internet would change everything. >> True.
56:21
>> But that still took 15 years, right?
56:21
Y >> so I think uh even I would say most of the bears like true AI bears still believe in the potential of the technology.
56:33
They just believe there's going to be uh a some sort of winter >> like a hiccup. Yeah. Winter. Yeah.
56:37
Hey, we haven't heard a lot of talk about AI winters.
56:40
There's been many of those.
56:40
And we uh I had a hot take that uh 2023 was an AI winter, which is like of course like the most bullish insane time possible.
56:51
But uh I but my my my riff on it was that like chat GPT launched in 22, Whimo launched in 22 and then 23 was more just like the adoption of chat GPT and at I think at dev day they launched uh maybe GPTs and it wasn't like a wild use case.
57:09
We didn't have reasoning models yet and so it was like this magical technology that launched in 22 and in 23 everyone was kind of like processing it but there wasn't like a massive jump in 23.
57:18
I mean, I guess we did get GBT4.
57:21
What do you think, Tyler?
57:23
>> LG, by the way, is quizzing you in the chat.
57:24
John Kugan, how many total tokens have been used on OpenAI year to date? Name every token. >> Name every token. Uh, well, it's odd. It's 6 billion a minute.
57:33
Uh, I think we did the math on this.
57:36
It's It's in the trillions. >> It's a lot.
57:38
So, yeah, when I calculated it, I I had like around >> uh one quadrillion a month.
57:45
>> One quadrillion a month.
57:46
>> That was also the number.
57:46
Uh I think Demos a couple of weeks ago he said uh Gemini is doing one quadrillion. >> Wow.
57:52
>> Um but yeah because OpenAI was like uh 61 per minute.
57:54
Uh but that's just on the API.
57:56
So if API is like 25% of the company. >> Exactly. Yeah. Yeah.
57:59
You have to do a lot of like dancing.
58:01
But yes >> in 2023 I mean GBT4 I think is like >> Yeah.
58:04
I don't think you should be following product releases.
58:05
You should be following >> but GPT4 was uh was trained in 22 and was released in uh Bing in 22. So it doesn't count. I'm kidding.
58:16
Of course, 2023 was a phenomenal year for AI.
58:18
Not not not a winter at all, but uh it's it's it is interesting to see like like where the growth spurts come.
58:26
How much of it is just a smooth curve of adoption and diffusion into the economy?
58:29
What's the rate at which it's diffusing?
58:31
Where are companies and individuals actually getting value?
58:37
>> Uh should we move over to the huge news in creatine? >> Yes.
58:41
>> Dan McCormick says, "Work with your brother.
58:43
go into debt if you have to because Pachy McCormack is giving a shout out to Dan, the founder of Create.
58:49
Uh he says, "My brother Dan has been writing the weekly do dose of optimism for three years."
58:52
That's uh Pachy's second newsletter aside from the one that he writes.
58:56
Uh last week was his last.
58:59
Dan McCormack is stepping down from writing the weekly dose of optimism because his company created absolutely ripping $85 million run rate.
59:06
I swear gummy vitamins are just an infinite money glitch.
59:13
>> There's a couple categories that are just doing so so well.
59:15
Stick packs and uh powdered supplements.
59:18
I don't What's What's hard?
59:21
H hard is hard is liquids, right?
59:24
Hard is >> do not try to sell liquids on the internet. That's hard.
59:28
But gummies must have a great uh you know >> invested I invested in create I think at a six cap.
59:34
I met Dan before the launch.
59:37
He was raising it even less than that.
59:37
I didn't I didn't see the vision right away and his execution in the first like >> five months was absolutely wild and I uh capitulated and uh it's been a wild ride.
59:49
The the uh execution is is insane.
59:53
>> Well, Dan, if you want to keep a hold on that uh creatine monopoly, you got to get you got to get on profound and get create mentioned in chat GPT. That's right.
1:00:04
reach millions of consumers who are using AI to discover new products and brands.
1:00:09
>> This post from frog is a banger.
1:00:09
Please make sure you are only drinking as much water as you really need.
1:00:15
We need that for the data centers.
1:00:18
If you're thirsty, Grock is thirsty, too. >> Completely agree. I completely agree. >> Uh reply here.
1:00:27
Installing a lowflow shower head out of concern for Grock. >> I love it.
1:00:32
I saw someone else was trying to put the Yes, this is it.
1:00:34
Andy Massley a couple slides later.
1:00:37
U he said, "Every day I find a new way of trying to get across just how ridiculously fake the problem of AI water use is.
1:00:45
We've talked to a number of uh Neocloud CEOs, data center builders on this show who have built data centers and they've told us, "Yeah, we use we use a decent amount of water, but once we have the water, we actually have figured out how to just recycle it in in the system."
1:00:59
And so, uh, we're we're not actually using that much water.
1:01:05
>> Even the new iPhone has a single drop of water >> and they sell a lot of iPhones.
1:01:08
So, I mean, millions of drops of water.
1:01:10
You got to answer something.
1:01:13
>> No, but but but it just proves a point that >> Oh, yeah. Yeah.
1:01:15
You can recycle it for heat. Yes. Yes.
1:01:17
No, that's a great point.
1:01:18
I hadn't even thought about that.
1:01:20
Um, >> it's not like you're you're I got to go refill my iPhone. >> Refill my iPhone.
1:01:23
Can you imagine how upset people would be like, "Yeah, I need to charge my iPhone.
1:01:26
Oh, I forgot to refill it with water at the gas station.
1:01:31
Um, so he he he shares some data here.
1:01:33
So, uh, this is a quote post uh from someone else.
1:01:36
Uh, yeah, but the form of AI that use the most water and electricity by far is chachi. You can start somewhere.
1:01:42
The whole I can't do it because I got cut off is just an excuse I don't care for.
1:01:45
Uh, and so, uh, here is some evidence, some new ways to think about the amount of water used by AI.
1:01:52
Uh, have you ever worried about how much water things you did online used before AI?
1:01:57
Probably not, because data centers barely use any water compared to most other things we do.
1:02:01
Even manufacturing most regular objects requires lots of water.
1:02:05
Here's a list of common objects you might own and how many chatbot prompts worth of water they used to make them.
1:02:13
Leather shoes are 4 million prompts worth of water.
1:02:15
Smartphones are 6,400,000 prompts of water.
1:02:20
Jeans, a single pair of jeans is over 5 million prompts of water.
1:02:25
This is such a silly metric, but I love these silly metrics.
1:02:27
Uh, t-shirt is a million prompts.
1:02:29
A single piece of paper is uh 2550 prompts.
1:02:32
If you want to send 2,500, >> imagine trying to give up all the things on these on this list because they use water. >> But you'd have Grock.
1:02:42
You'd just be naked using Grock.
1:02:44
But you'd have you'd have you need a smartphone and that's six million prompts.
1:02:47
Uh, >> Chad is going crazy right now.
1:02:49
We're we're being told to not ask him anything about Trump or crypto if you got money on it is because there's prediction market. Okay.
1:02:58
We we are not paying attention looked at any market prediction markets.
1:03:02
We will not be steering the conversation.
1:03:04
If you happen to have a bet one way or another uh well uh I believe we have our guests in the reream waiting room.
1:03:12
But before we bring them in, let me tell you about Julius.
1:03:16
What analysis do you want to run?
1:03:16
chat with your data and get expert level insights in seconds.
1:03:19
Julius is the AI data analyst that works for you.
1:03:21
Connect your data, ask questions.
1:03:24
>> Data super intelligence >> it is.
1:03:26
And we are joined by Sam Alman and Bill Peeles. Sam. Bill, how are you doing? >> What's going on? >> Hey guys. >> Hey guys. >> Great to see you.
1:03:35
>> Congrats on all the progress.
1:03:35
Uh I've been enjoying Sora a ton.
1:03:38
Uh personally, I've been enjoying making them.
1:03:41
I had a ton of fun making uh the collab post yesterday and uh I was wondering >> prompting your cameo feature.
1:03:48
John made it so that uh he always appears as a bodybuilder if anybody's cameoing him.
1:03:56
So you guys got got to experience >> led to some some chaotic results.
1:03:58
Uh do you have favorite Sora posts that you've been uh coming back to or that have you know stuck out to you as particularly uh you know creative uses?
1:04:10
I I mean definitely all of the ones of like me stealing GPUs or doing other crazy things to get GPUs have been funny.
1:04:15
Uh in in the last few days the there at least >> in my feed there have been these like very beautiful >> sort of fantastic scenes that are just not things that could have ever existed without something like Sora or wouldn't have been easy to make.
1:04:28
And watching people build those and watching as sort of the trends flow through that has been pretty awesome.
1:04:34
>> Uh what about you Bill?
1:04:34
Uh any favorite uh uses of Sora so far? Oh man.
1:04:37
Uh Mark Cuban came on the platform a few days ago and there have been some hilarious Shark Tank memes.
1:04:43
Those are probably my favorite.
1:04:45
Pitching pitching some Sora features >> also uh leveraging the the prompting function to always include an ad for cost plus drugs I thought was especially hilarious considering he's been one of the most vocal opponents of of advertising in AI.
1:05:00
He uh uh is leveraging the feature to the max. Yeah. >> Yeah.
1:05:05
I think they're going to be all of these weird new dynamics that we see emerge that just weren't possible in previous kinds of video.
1:05:11
And uh this is like a fun period because it's all going to be so different every few days.
1:05:15
Man, I'm watching this poly market ticket go by.
1:05:19
Ticker go by and it's so tempting to like say things to all these. >> Yeah. Yeah. Yeah.
1:05:23
To be clear, not we're don't don't worry about the don't worry about the ticker.
1:05:26
I don't think we're including uh I don't I don't think any of those markets are being being featured in the ticker, but uh >> Yes. >> Yeah.
1:05:33
Again, this is the the new world we're in.
1:05:36
>> Yeah, you can move the market live on TBNN, >> but today people, I'm sure, will be happy or disappointed we're here to talk about Sora, of course.
1:05:42
So, uh none of the uh other topics.
1:05:47
>> I But I I mean, I also want to know about ads.
1:05:48
Uh why no ads in Sora on day one?
1:05:52
I feel like you've laid out a really great, you know, mental model for how you think about ads on stratey on the Andre Horowits podcast. I've I I'm bought in.
1:06:02
Uh, is it a technical thing? Do you need scale?
1:06:04
Do you need uh to think about it more?
1:06:07
Uh, why no ads on day one?
1:06:11
>> This is like a 10-day old product, right?
1:06:12
Like it's hard to get anything to work at all.
1:06:14
Uh, and we we like we we don't we we don't assume success.
1:06:17
We we got to like go hard earned success and then we can then we can think about monetization for it.
1:06:22
But this is like >> it's gone great so far.
1:06:25
It's still very early and there's still a lot of work to build something that a lot of people are going to love.
1:06:30
First, >> what about uh surprising capabilities of the model?
1:06:34
You mentioned that you've seen some fantastical scenes.
1:06:35
I'm interested to know about specific like specific breakthroughs that you've noticed that Sora to the model is particularly good at.
1:06:44
I noticed one about uh reflections being great.
1:06:49
Obviously, people love the cameos, but what what has surprised you in terms of just like technically the model can do something now that it couldn't do before?
1:06:56
This model is a huge leap forward in terms of physics IQ.
1:06:58
So pretty much all past video generation models really struggled with prompts that you know involve like back flips, gymnastics routines, etc.
1:07:05
And this is really the only model that exists today which can reliably handle these kinds of really complicated dynamics.
1:07:11
Um, one of the big features that people have really loved on the app so far is the steerability of the model.
1:07:17
So, you know, if you give it like a really simple text prompt that's maybe even only a few words, this model is really good about kind of telling a coherent story with like a beginning, middle, and end.
1:07:26
And doing this like automatically in a way that doesn't require like a lot of direct steering from the user.
1:07:30
If you want to like go into, you know, a ton of detail about exactly how your prompt should be laid out and how the story should unfold, it supports that too.
1:07:37
So, it can kind of meet you wherever you're at in the creative process.
1:07:40
But really, this model is just like so hyper steerable and it's like just vastly higher physics IQ just makes it able to do things that were like not possible a few months ago.
1:07:50
>> Is that all within the model or is there some sort of like reasoning step where you're hydrating or unpacking my prompt and writing a bigger prompt or breaking down the problem in some way?
1:08:00
Can you share anything about that?
1:08:03
>> Yeah, it's a good question.
1:08:03
Um so you know the intelligence for these text conditional video models kind of lies both in the the core model itself like Sora and some amount of it also comes in through the text prompt.
1:08:12
So you know where however the user decides to kickstart a prompt you can have like a language model under the hood adds some details in.
1:08:19
But for example you know when it comes to things like again like doing these back flips or any kind of physical interactions how refraction is modeled uh you know when you're pouring water into a glass all of these details have to be captured by the core video model itself.
1:08:32
So that that's intelligence which is really innate to Sora.
1:08:34
Uh and certainly you can supplement it with intelligence from a language model as well but it's not necessarily a prerequisite to get kind of amazing results out of these things.
1:08:42
>> Are there any areas on the physics where you think that uh the model falls down and you want to improve?
1:08:46
I mean we went through the era of like six fingers.
1:08:48
It seems like reflections and water are solved but someone was saying something about doors being hard or I I haven't noticed that one personally but a lot of the stuff's great.
1:08:57
But what have you noticed is like the next version is going to be even better at >> this is still very early.
1:09:01
A thing Bill said that I appreciated is this is this is the this is like the GPT 3. 5 moment for video. >> I agree.
1:09:09
>> And if you went back to use the actual GPT3.
1:09:11
5, you'd be like, okay, signs of great promise can do the occasional impressive thing, but it was really not until GPT4 where these text models started providing real value for people.
1:09:21
And we know how to go make the GPT4 equivalent of video models and we will do that.
1:09:26
And then a lot of these things that are currently annoying like doors or, you know, once in a while something goes through something else it's not supposed to.
1:09:35
In the same way that the world, you know, love to complain for a brief period of time about where 3.
1:09:39
5 fell down and oh, it's never going to be useful, it's never going to do this, it's never going to do that, and then we were able to just keep making it better and better and better and better.
1:09:47
The model physics IQ is certainly the best I've ever seen, but it is nowhere near as good as it will be um in the future versions.
1:09:54
And I think I hope we'll see a similar thing to what happened with the GPT text models, which is people will always demand more and better and they will always find new and better things to use it for, and the world will just make ever more amazing videos.
1:10:13
>> And how quickly, >> oh, sorry, >> we're early on the curve for video here. >> Yeah.
1:10:17
um like GPT1 really was Sora one uh for this modality and the progress we've made kind of in the last 18 months getting to this 3.
1:10:25
5 moment right it's really compressed compared to how long it took to go from GPT1 to 3.
1:10:28
5 in the language domain so we're really expecting progress to continue to be meteor here in the near future >> how quickly do you expect the cameo feature to be cloned that feels like a a a equally important part of the you know the the models made a leap but the product is and the experience erience and that the the experience of creating uh these assets is uh wildly innovative.
1:10:54
We saw stories get cloned.
1:10:54
We saw saw uh you know algo video short form feeds get cloned.
1:11:01
I I expect many other platforms to be looking at this functionality and realizing that this might be uh the future.
1:11:09
You guys certainly believe uh that that it could be uh important.
1:11:11
that that it could be uh important. So how quickly >> we're actually totally okay with a world where we do the product innovation and everybody else copies and I don't think it works for them as well as they think it does like the the you know a lot of people have tried copying chatbt uh in you can go look at some of our
1:11:28
competitors apps and they even copy the mistakes they even copy the design decisions we really wish we hadn't made and maybe it's worked well for them I guess I kind of hope it has but it's been fine for us >> yeah I I think like the the the key to this is not any one innovation but it's repeatedly putting them out again and again and
1:11:46
being first to come up with them and put them into a cohesive offering and you know that's what we want to be good at and if other people want to clone the stuff that works we also sometimes clone stuff that works that's fine but but mostly we want to be able to drive the innovation and I think Bill and his team have done an incredible job of figuring out how
1:12:06
people actually want to use these video models what the models need to do really they've approached this as a full stack problem from how do you train the video model to how do you make this enjoyable for users, but cameos are one out of many ideas they have from here on the journey to like the product that we hope to eventually build. And so if people
1:12:24
And so if people take some inspiration from us and copy us along the way, I'm sure they will. It's fine.
1:12:32
>> How do you think about the like popular claim uh that we want AI detection, I want AI content flagged?
1:12:39
Is that a stated preference that's not a revealed preference?
1:12:44
Because personally, I don't want bad a AI content, but I don't want bad humanmade content either. I want great both.
1:12:52
And I'm fine when someone comes up with something genius and they instantiate it with a video model.
1:12:57
Uh, how do you think about it?
1:13:02
>> I I think that is the real thing is you don't want slop, you want great content.
1:13:07
Different people, one man's slop is another man's treasure for sure.
1:13:09
But what you care about is like good, original, thoughtful, new, helpful, whatever content.
1:13:15
And whether that is generated entirely by a human or entirely by AI or what I expect will mostly happen in the future, which is toolass assisted human-driven generation.
1:13:28
Um, I don't think you care that much if the content is great.
1:13:31
uh there's a lot of like you know stuff that is technically written or drawn or filmed by a human but is completely derivative and much less original than what an AI has generated and I think that will be what people really care about long term.
1:13:49
You just want great content.
1:13:51
Um now I also do want some human connection with it.
1:13:54
Like when I read a great book, first thing I want to do is read about the author that wrote it and what life experience went into that.
1:14:01
I don't think that'll go away.
1:14:01
But if they're using an AI as a tool to help them make the writing better, sign me up. That sounds great.
1:14:06
Similarly, I would rather watch a video about someone I know than some random AI generated character, which is part of why I think this was cool to offer.
1:14:13
One design decision the team made that I thought was really great and I I was actually pushing them in a different direction earlier on and uh then I decided they were totally right and I thanked them and dropped it was the fact that the feed is um AI only and not a mix of AI plus some uploaded videos I think is a subtle but extremely important design decision and how people are relating to this.
1:14:40
>> Yeah, it was a very weird experience for me.
1:14:42
I was I was thinking about the collab post that I was making announcing this interview and my initial thing was like well I'm going to have to think of a script or I'm going to have to think of you know what I say or I should record a piece of this and then I'll use it and it was like no I just type the prompt in and then I get the frontfacing video is remarkable.
1:14:57
video is remarkable. What are you what kind of indicators are are you guys looking at uh as Sora can transition from uh what it was the second it launched which was a creative tool into something that's more of a consump like a consumption platform traditional you know social media platform like what
1:15:17
talk about kind of what you guys are pushing for to uh because obviously you're seeding seeding the the network with with the tool uh but it's it's certainly much harder to turn it is something uh that people are spending hours a day in purely consuming content and not creating content. >> You know, we really wanted to design
1:15:34
>> You know, we really wanted to design this from the ground up to be centered around creation.
1:15:38
And a lot of the metrics that we've been focused on optimizing here are really aligned with making sure as many people as possible are actually like getting their hands on the sore model itself and you know able to create content with their friends and like for the rest of the world.
1:15:51
One metric that we're really proud of with this launch so far is that 70% of our users are actually creating content even to this day, you know, a week and a half after launch.
1:16:02
And that's like vastly higher than on any other social media platform.
1:16:07
>> And I think it really speaks to just how fun creation can be with the right tool set. Right?
1:16:12
If you look at any of these kind of legacy platforms, there's just like so much friction from like getting off the feed and like into some creative flow state, right?
1:16:19
you have to like put the phone down, you have to go get like a camcorder, start recording yourself, find your friends, like do a dance, etc.
1:16:26
It's just like a lot of work, right?
1:16:26
On Sora, like you can just pick up your phone, find a like any video you like in the feed, remix it, uh you know, cameo any of your friends.
1:16:34
And I think one insight that was not obvious to us at first, but we've kind of clearly seen as an emergent behavior of this product is just like there's there's all these people out there who would not necessarily want to be like, you know, influencers or something or have like a big social media presence, but the fact that like all of their friends can just access their cameo, right?
1:16:52
Put them in all of these crazy situations actually like kind of gets them into the playing field in a way that felt really high friction before.
1:16:59
And so, you know, we're closing in on close to like 2 million weekly active users now.
1:17:02
We're really excited that such a huge percentage of that user base to this day is like still creating with Sora and we're going to continue pushing on that direction and making sure people have even more powerful tools in the future. >> Yeah.
1:17:14
So 70% of Sora users are creating content.
1:17:18
Uh the typical benchmark that people kind of quote randomly is like uh 1% creation, 99% consumption, something like that.
1:17:26
And that certainly feels like my experience on Instagram.
1:17:28
I post a photo every once in a while, but most of the time I'm just kind of scrolling.
1:17:32
And I'm wondering if you think that that 1% will be much higher on Sora in terms of actual time in the app, time prompting versus time scrolling.
1:17:41
Uh, and if you have any data, that'd be super interesting.
1:17:45
But then also, uh, does that make it more of like a competitor to video games than traditional social media because it's such a lean forward experience versus just layback? What do you think?
1:17:57
>> Yeah, it's a great question.
1:17:57
Um, we still need to study this more exactly how creation versus consumption habits kind of change over time for folks on the platform.
1:18:04
It's still pretty early days.
1:18:05
I I do agree with your point though that I think over time this is going to feel much more immersive um in a way that like video games kind of do like you have more agency when you're actually using the platform, you know, not just kind of like mindlessly scrolling a feed uh like hours a day.
1:18:20
And like one interpretation of this product which I think is kind of interesting especially from the research perspective right is cameos in some way is like the simplest way where you can kind of like inject yourself into the model right so it's a very low bandwidth communication channel right now you know you're only giving like a few seconds uh of video footage uh of like any given individual like into the app.
1:18:41
>> Uh but like over time right you can imagine like these models know more and more about your life.
1:18:44
they really like deeply understand your friends, how you want to like show up in the world.
1:18:48
And like over time, this can almost become like a little mini like alternate reality, right?
1:18:53
So like you're not just generating like videos of yourself with your friends, like you actually just have like digital copies of yourself running in the model on the Sora platform interacting with other people with agency.
1:19:02
And so I think over time we're really going to see this platform evolve into, you know, something that feels kind of familiar today into something that really leans into like the full intelligence of Sora 2 in the future and like really leverages all the world simulation capabilities that we're working on internally.
1:19:17
>> Yeah, I I would add to that that if if you think of this like spectrum of the kind of entertainment you can have in front of a computer, at one end you have like watch a two and a half hour movie and you hit play and then you lean back and you don't do anything at all.
1:19:30
Um, and then at the other end, you have like a very intense video game and you're like, you know, sweating and your heart's racing and it's like super super active.
1:19:38
Um, AI is going to push things to be more in between there.
1:19:42
So, you'll have maybe you're still watching that movie, but now you can like say something a few times throughout the course of it and it changes what happens as the movie plays out.
1:19:52
or with Sora, you're seeing this amazing new phenomenon where most users are creating in a in a world where traditionally only 1% of them did.
1:20:01
And so you're yes, you're like watching a video feed, but you're you're doing a little bit more.
1:20:06
And it, at least for me, really changes how fun the whole thing is and how I feel about it.
1:20:09
Then maybe you'll do what Bill said and you'll have like you'll be way more actively participating in the Sora feed.
1:20:15
And I I think you're just going to see that continuum blur a lot more.
1:20:19
>> Did you see Bander Snatch by any chance, Sam?
1:20:20
Have you seen this Netflix?
1:20:20
It's like a Netflix choose your own adventure and it was really cool idea but ultimately people it never really took off and became like something they do again and again and again and I'm wondering if it was because it was like not customizable enough um or people just want to just sit back and see a director's vision. I don't know.
1:20:37
Anyway, >> I never heard of that but it sounds cool. >> Yeah.
1:20:40
How do you think uh uh question for Sam?
1:20:43
How do you think about allocate allocating compute to Sora versus the rest of the business?
1:20:48
I imagine Bill is constantly in your ear.
1:20:53
every every other uh hour.
1:20:53
But uh how are you thinking about it?
1:20:57
>> You know, my real answer is I've entirely changed my focus of how I spend my days to just go get more compute rather than have to make the comput allocation decisions.
1:21:04
Yeah, >> I still do have to make some short-term comput allocation decisions, but I hope we're heading to a world where >> I am instead telling people you got to find a way to use more compute and uh >> we're going to be we're going to be very aggressive here.
1:21:17
It feels like you're doing a great job of like bringing things within your control within the supply chain.
1:21:22
What is outside of your control at this point? >> I mean, most of it.
1:21:27
Um, >> but I feel like you have great you have great partners all up and down the stack, multiple partners in different parts of the chain.
1:21:35
Like when I think about scaling up Sora, I I I I feel like it's crazy to bet against you.
1:21:40
Like you're going to you're going to get the chips.
1:21:42
You're not going to be >> try to buy like 10 g of power for delivery next year. It's not so easy. >> Uh, it's funny.
1:21:51
>> How are the conversations going with uh with Hollywood? >> Oh, yeah.
1:21:55
>> Oh, actually, >> yeah, you take it.
1:21:56
Yeah, I I was going to say we've been chatting actually with a few, you know, very notable folks in in Hollywood over the the last week.
1:22:01
You know, I think people's first reaction to this is >> like very understandably going to involve a lot of trepidation and like anxiety.
1:22:09
um when we've gotten to just sit in a room with these folks though, you know, and really explain what we're building.
1:22:14
I've actually been pretty struck by like how excited uh folks in Hollywood are about this, you know, we were chatting with um with one actor recently who mentioned that, you know, on Twitter like a year ago saw like a deep fake of her generated with one of these like open- source models uh which really had like a lot of nasty content. Oh yeah.
1:22:33
uh created and when we really like it walked her through kind of all of our safety mitigations, right?
1:22:38
How we're making sure that we have this like very well- definfined model spec which dictates the behavior that that we allow on this platform and how we are really leaning into like full control of likeness, right?
1:22:50
More so than any other platform.
1:22:51
Like you have to come in through the Cameo process.
1:22:53
You can't just like upload an image of yourself and just like generate a video of it of like any person.
1:22:58
You have to come in through Cameo.
1:22:59
Um, I think it became clear her that, you know, we're really setting the right standard here, uh, in terms of making sure people are in full control of their likeness in Hollywood.
1:23:08
And I think that's where like a lot of this anxiety comes from, right?
1:23:08
It's this feeling that, you know, some random person can just kind of take videos or images of you and do whatever they want with them and create all of this like like like terrible content that's like outside of your purview.
1:23:19
Um, but we've really been like designing Sora from the ground up to put users in full control of their likeness end to end from the moment you sign into the app to, you know, needing Cameo permissions to like access any of your friends uh, generations.
1:23:32
So, you know, I think we need to engage more with Hollywood and we're going to continue to do that.
1:23:36
But once we really explain the story of Sora, you know, they're very receptive to it.
1:23:41
>> Do you think there's a world to add something to that?
1:23:44
I like, you know, I the team asked me before launch if they could put my cameo in their open access and I of course thought about for a second and said absolutely yes.
1:23:52
I had all these Hollywood celebrities then messaging me on the first day being like, "You're absolutely crazy. This is insane.
1:23:57
This is like the dumbest thing I've ever se."
1:24:00
And then by about the third day, they were like, "hm, that was really smart.
1:24:04
You got like a lot of, you know, free publicity.
1:24:05
Maybe we need to be doing that."
1:24:06
And I think you're now seeing actual celebrities say, "Okay, I'm going to do this."
1:24:11
And I expect a lot more of them will similar thing on other kinds of characters in IP.
1:24:16
I can totally imagine a world where our problem in a year or 6 months or maybe even less is not that people don't want their cameos or their characters appearing but they think we are not fairly having their characters or cameo appearing often enough.
1:24:34
>> Yeah, >> this may turn out to be a really big thing for fan connection.
1:24:36
Now, it may be that kind of the previous generation of celebrities don't want to do this and the influencer celebrities all do.
1:24:43
I don't know how that's going to go, but but I bet this will be like a pretty deep kind of new connection.
1:24:49
>> Yeah, it seems like it's been good for DiCaprio in the memes.
1:24:50
Like, he's not directly monetizing those when you show the champagne meme or him pointing at the TV, but like you know, it builds his aura in some way.
1:25:01
>> A friend of ours posted something yesterday.
1:25:02
This this is Jeremy Ganon.
1:25:02
He said, "The reason we're so upset about slop is because it's obvious we're all going to be going to love consuming it in 2 to 3 years.
1:25:10
It's not going to be slop for long." Do you agree, Sam?
1:25:17
>> I mean, some of it will be sloped to some people and some of it won't.
1:25:18
I I remember like there was a real reaction like this in the early GPT days where people were like, "I can't believe anyone reads this. It's like total crap.
1:25:29
It's full of hallucinations, you know?
1:25:30
It's like it's not useful to anyone."
1:25:32
And then it became more useful to some people, but they said, "I can't believe anybody like ever thinks this thing writes a beautiful sentence. That's insane."
1:25:38
And then with GPT5, you have authors saying like, "Wow, this is a useful tool.
1:25:42
It sometimes like writes a beautiful sentence." >> Yeah.
1:25:46
>> Uh and I kind of think it'll follow a similar trajectory.
1:25:49
>> What do you think about the fact that people feel at least I don't know if they actually can, but it feels like you can still clock GPT5 writing, you know, it's not this, it's that, the M dash.
1:25:58
Like will we still see these artifacts in 3 years in Sora 5 that people are like oh if you know you know you can tell but most people can't. >> Yeah.
1:26:08
It's like what's the mdash of of video because I don't think it's like six finger. >> No no definitely not.
1:26:12
That's the typo which doesn't happen anymore. >> Yeah.
1:26:16
I think right now the mdash is like this like slightly wired speech pattern in Sora where it likes to say a lot of words very quickly.
1:26:24
You know these these generations definitely have like a style to them.
1:26:26
M um I think analogously to GPT, we really want to give users a lot of control over exactly how their videos show up right on the platform.
1:26:36
Like if you really want kind of like a very soothing experience, right?
1:26:40
Not a lot of shot changes going on, we want to give users the ability to generate that.
1:26:43
Uh and we're going to continue to give more optionality to people.
1:26:46
So, you know, there'll be some default kind of behaviors and quirks of uh of Sora for sure, but uh we definitely want all power users to be able to be in full control. Random question.
1:26:55
Where did the name Sora come from? >> Yeah. Oh, this is a fun one.
1:26:58
Um, so the original Sora came out uh in February 2024, the OG blog post. >> Yeah.
1:27:06
>> We uh >> did not have a name for it.
1:27:07
I think like up to two days before you like revealed the model to the world.
1:27:11
Uh we just could not agree on the team what it should be.
1:27:16
>> Did you at least have a code word or something?
1:27:17
Like how >> we just called it like videogen. Okay.
1:27:20
Um, and so, uh, at some ungodly hour, I like just started pumping a bunch of crazy ideas into chat GPT.
1:27:27
And then like we basically ran out of like English words, so then we switched to like Japanese words. >> Wow.
1:27:33
>> Uh, and then Sora came out.
1:27:33
I was like, "Wow, that sounds really nice."
1:27:34
It means sky, you know, link with like imagination, like all the the possibilities of creation.
1:27:39
And so then we just like last minute ship Sora. So >> yeah. >> Yeah.
1:27:44
It was kind of a mad dash. >> Okay.
1:27:45
Speaking of Japanese stuff, uh Sam, you said you were looking for an Acura NSX a while back.
1:27:49
Uh it's kind of this throwback car, very It's not a Whimo.
1:27:54
Uh what do you think the piece of content or format will be that uh remains loved uh in an age where everyone's taking the Whimo of video, the Sora video generation.
1:28:04
What do you think is like >> Well, first of all, I got that NSX and it lived up to all of the childhood hype. I mean, just incredible.
1:28:13
That car is so fantastic. >> And I I don't know.
1:28:20
I kind of think there's going to be a lot of stuff like that for people that generated or not where you still you want the real thing.
1:28:27
You want the thing that you had the kind of childhood connection to.
1:28:30
Uh you know, someone like a kid today is not going to want the NSX, but whatever the a cool car like that is, they will want.
1:28:37
And at some point like the fact that they can have like a crazy VR experience, they'll still want the real thing and the connection to it and everything they have.
1:28:46
So I I think there will be a huge amount of that.
1:28:48
In fact, I think the future looks like much more of that kind of stuff, not much less.
1:28:52
>> How quickly do you want to create an economy on Sora?
1:28:54
It feels like there would be a number of ways that you could create incentives for creators to create things, for IP holders, for individuals to just be passively monetizing their likeness.
1:29:12
>> Bill, what do you think for timing on that?
1:29:13
>> I mean, this is like a top priority for the team.
1:29:15
You know, there's clearly such an incredible value proposition for celebrities, for rights holders across the board here.
1:29:22
Um, we think cameo is like a great entry point for this, right?
1:29:26
You can imagine right now we have cameos for people.
1:29:27
Maybe you have cameos for like, you know, your character, uh, or like your brand or something.
1:29:32
And so, we're actively working on the team right now, uh, coming up with like the right monetization model here to get this rolled out.
1:29:39
But it's really important to us, right, that our creators on the platform are rewarded and that there are clear, you know, financial incentives um, for like the incredible work that they're already doing.
1:29:48
So, this is like top of mind for us and we'll have updates here over the coming weeks.
1:29:52
This is like something we're actively working on.
1:29:55
>> I I I will I I think it's super important and awesome.
1:29:57
I I will say I would like to know how many hours of sleep Bill has averaged for the last few weeks, but I bet it's not enough.
1:30:01
So, we got a lot of stuff.
1:30:03
The team's got a lot of stuff they have to do in a short period of time, and it's going to take a little while.
1:30:08
>> Okay, let me put one more thing on your plate, Sam.
1:30:10
Uh I mean, uh earlier like years ago, you built Looped locationbased product.
1:30:18
Have you thought about how AI and locationbased content fits together?
1:30:24
Like on most of these social apps, you can tag a location.
1:30:28
That wouldn't even make sense in the current sore app.
1:30:30
But what does the AI maps product look like?
1:30:35
>> I haven't thought about AI and location that much, but I've thought about like how AI can really change the social experience for people. Mhm.
1:30:46
>> We don't have like a for sure answer yet, but we have like a lot of interesting threads to pull on >> and I have thought back to like my days running that startup there more.
1:30:58
My instinct is it is possible to make a very interesting new kind of social experience connecting you to people, helping you find people that is intermediated by AI in an interesting way.
1:31:08
Um but you know we'd have a lot of exploration to do there.
1:31:14
>> What advice are you giving to startup founders these days?
1:31:16
Uh I remember in the GPT 3.
1:31:19
5 GPT4 days it was like don't build a company that assumes model stagnation.
1:31:25
How do you think about in the age of Sora?
1:31:28
>> That's been really great advice. >> It really has.
1:31:29
It planned out it played out exactly like that.
1:31:31
There's a bunch of great companies that aren't built that way and they've done great.
1:31:33
Uh, but if you if you were just, oh, I have a special prompt that tunes up GPT4. Yeah, bad times.
1:31:41
But how are you thinking about it now in the context of video and Sora specifically?
1:31:44
You obviously do have an API. You have dev day.
1:31:46
There's people that will build on top of this.
1:31:48
Is it a different shape of the problem? >> Totally.
1:31:52
The the reaction to um the API has been nuts positive.
1:31:56
Like I at least the fastest ramping revenue I've ever seen for one of our new models in the API.
1:32:02
I mean, maybe there was something faster that I'm not remembering, but >> congratulations.
1:32:05
>> The demand there has been just incredible and people are doing awesome stuff with it.
1:32:10
Um, >> Bill and I have not had a chance for a one-on-one since launch cuz it's been so crazy. We're doing one later.
1:32:16
We're doing one later today.
1:32:17
But one of the things I was going to suggest to him was that we given how much excitement there is to build on this stuff >> that we do something we don't usually do and put out our intended road map of the things we're going to prioritize because I can imagine really cool new startups that simply were not possible that will be possible at each of these new things we'll ship.
1:32:38
we'll ship. So I I I had a question when you guys released the uh Sora 2 via API which was that if Sora has the potential to be a Instagram or or YouTube scale business, why release part of your edge for the entire world that they can
1:32:56
integrate into other creative tools and then use >> the model to generate content that doesn't have a watermark, that's not in your feed, that you're not able to get that feedback loop on that you guys do with the SOAR for chatbt. We also put out a great
1:33:10
We also put out a great model in the API and people can theoretically compete with us on chatbt and some try to but like we are willing we're never going to build every cool use of the technology and we want the world to get all that stuff.
1:33:23
We're delighted to also get paid on people using our API but like we just want AI to flourish out in the world.
1:33:28
We're not going to build every great use of what you can do with video models either.
1:33:35
we'll build one and I think it's pretty awesome.
1:33:36
But people have a lot of other ideas of of businesses and products to go build and we'd like to enable those.
1:33:43
>> Okay, last question back to cars.
1:33:43
What's wrong with the Porsche 911?
1:33:47
>> Yeah, you said earlier the timeline was in turmoil.
1:33:49
You said if you were worth uh somebody said uh >> if you million when you buy a 911, you said no. You agreed with PG.
1:33:56
What What did you mean by that? >> Yeah.
1:34:00
>> Uh I mean it was maybe it was like a tasteless joke.
1:34:03
It was kind of like late at night.
1:34:04
I was, you know, whatever.
1:34:04
But uh I I have an unfortunate proclivity for expensive cars. >> Yes.
1:34:11
>> And and the response was like, "Would you ever spend 250k on a car?"
1:34:12
And I took that literally. >> That's amazing.
1:34:19
>> Hit the size gong for taking it literally.
1:34:22
>> No, no time for 250k cars.
1:34:22
Not >> But I probably That was not my best tweet, you know.
1:34:28
>> No, I I I enjoyed I enjoy it now that I have the context.
1:34:33
Congratulations on all the progress to both of you.
1:34:35
Thank you so much for taking the time to stop by the show.
1:34:38
>> Really appreciate the >> and very excited to see where this goes. Thank you so much. We'll talk to you soon.
1:34:44
>> I I don't think anyone read it. >> No one. No one got it that way. That's amazing. >> 250K.
1:34:49
How about two and a half? >> Very good.
1:34:52
Uh anyway, we have our next guest joining in just a few minutes.
1:34:54
In the meantime, let me tell you about Linear.
1:34:58
Linear is a purpose-built tool for build planning and building products.
1:35:01
Meet the system for modern software development.
1:35:03
Streamline issues, projects, and product road mapaps.
1:35:05
We have a lot of OpenAI builds on linear. >> Yes. Oh yeah, that's right. They're a customer.
1:35:11
Uh well, we have a lot Gil coming into the TBN Ultradome from the reream waiting room. Let's bring him in now.
1:35:18
>> Thank you so much for joining us a lot. How are you doing? >> Finally. >> Thanks for having me. Good to see you all.
1:35:23
We have wanted to do this interview since probably the very first week that we could guest.
1:35:28
Took us a while, but you have your own show.
1:35:32
>> But uh >> but thank you so much for taking the time.
1:35:34
Um what uh what what what this week has stuck out to you.
1:35:37
I'd love to just get a state of the union on how you're thinking about the market broadly and then we can zoom in on uh on individual startups and trends and subcategories that you've been focused on.
1:35:49
But have you had a reaction to this like bubble talk that's going on?
1:35:51
Have you been thinking about this?
1:35:53
Uh what's been how have you been processing the information?
1:35:57
How do you even research whether or not when something is going viral like that?
1:36:02
>> Yeah, I mean I've been looking at this stuff for a while.
1:36:03
Um because if you look at the '9s as a sort of precedent or anticedent the '90s internet bubble. >> Yeah.
1:36:11
>> I think there was something like 450 companies that went public in um 199 1999.
1:36:16
There's another 450 that went public in the first couple months of 2000.
1:36:20
And so about 2,000 companies went public.
1:36:23
>> And then you ask how many of those are still alive? Like how many survived?
1:36:26
>> And there's probably a dozen, two dozen that that are still up and running.
1:36:30
There's probably two or three of those that are really important to Amazon as an example, etc.
1:36:33
And then 1,980 out of 2000 probably died, right? Went to zero.
1:36:38
>> And they were being priced on eyeballs.
1:36:40
They're being priced on eyeballs, not not even account creation.
1:36:42
It was it was such a different time like IPOing was like doing your series B.
1:36:48
I remember there was a guy uh Bill Gross at Idea Lab in Pasadena, my hometown and I believe he took a hundred companies public and he ran an incubator.
1:36:57
It was like the Y Combinator of the day.
1:36:58
One company I believe was Adwords that went to Google and became the backbone there and he had a bunch of great outcomes but it was like a bit of a machine.
1:37:05
Uh if the IPO is no longer the metric that you we should be watching is it is it these revenue ramps? Is it churn?
1:37:13
Like how can we dig into understanding like where true value durable value moes are acrewing versus uh froth?
1:37:20
We we often call it like the barnacle economy.
1:37:23
Like if you're if you're uh you know a toilet cleaning startup and but you have anthropic as a customer and they 10x their office footprint, you 10xed revenue.
1:37:34
That's not exactly the type of business we want to see long term.
1:37:38
>> Yeah, I think durability is a great question and it's a really hard one for this era. Um for two reasons.
1:37:41
this era. Um for two reasons. One is things are changing so rapidly from a model and underlying capability perspective that if you look at every prior technology wave you look at for example Microsoft OS right they forward integrated into uh the office suite off of using Windows OS or Google forward integrated into vertical searches so
1:37:59
they killed a bunch of companies or really hurt a bunch of companies are providing those services so we should see the same thing with the foundation model companies right it's most likely if they're going to afford integrate they're already doing it in code maybe they end up doing it in customer support in sales sort of all the big categories there'll probably be some effort at some point. Now, they may or may not succeed
1:38:13
Now, they may or may not succeed with that, which is a different thing, but there's durability in the face of competition from the big folks.
1:38:18
There's durability in terms of like, well, people keep using your product or we get subsumed by a startup.
1:38:23
And then there's just things that are just running up that clearly are never going to really work.
1:38:27
And um the real question is, you know, how do you identify each one of those classes of companies and how do you think about them as either a founder or an investor?
1:38:35
Right now, we've been we've been noticing there's sort of like three types of three buckets of companies that are trying to like, you know, craft an AI narrative around whatever market they're in.
1:38:45
If we're talking vertical markets, smaller markets, not the foundation model layer, you have the legacy Fortune 500 company, uh, you know, career CEO in the seat who's maybe paying a consulting firm for some AI transformation plan and, uh, maybe the stock's not doing so well.
1:39:03
Then you have the startups that are, you know, we we we go to YC demo day.
1:39:05
We talked to five companies that are building in the same space and it's they're complete green field project. Amazing place to be.
1:39:12
Must be super fun to just have be puppeteering 25 cloud code instances and codeex agents to build your thing.
1:39:19
But then we talked to a lot of founders that have they started their company 5 years ago, 10 years ago.
1:39:26
They have a serious business, but they're still in founder mode.
1:39:27
And we always find it a little bit hard to bet against those guys who are like coming back in re-energized, they have the balance sheet, they have the customers, and they can kind of take a second crack at it.
1:39:39
Um, do you like what nuance would you add to that framework?
1:39:42
Do you think it's on a per industry basis?
1:39:44
Is it all about the founder?
1:39:46
How do you think about that?
1:39:49
>> Yeah, I think there's basically three viewpoints on that.
1:39:50
Um, I think there's a very small number of singular founders who just make amazing things happen, and that's Elon Musk, right?
1:39:55
Like who else would go to space and build cars and do all these things?
1:39:59
>> Honestly, I think Arvin to perplexity is one of those where in anybody else's hands I think perplexity would be a dramatically smaller business and I think most other companies in his hands would do better. He's very good, right? But that's very rare.
1:40:09
So I kind of put you know amazing founder aside because even great founders if they're a terrible market tend to get crushed.
1:40:14
terrible market tend to get crushed. Um and so I think there's a second piece of it which is there are a bunch of these AI markets that have recently really crystallized where you know I used to say a year and a half or two years ago that the um more I learn about AI the
1:40:27
less I know and it was the only market that I ever felt that way because you know you learn new stuff and you know more right you do better you can predict stuff um and I think that changed over the last six to nine months where suddenly at least for certain areas it's really clear who the finalists are. We
1:40:39
We may not know the winners but we know who the the final contenders are.
1:40:42
We know that for the foundation model market um we know it's anthropic, open AAI, Google perhaps XAI, Meta, a few others, MRO what but you know it's a small list.
1:40:51
We know for coding it's cognition cursor and then the foundation model companies and then Microsoft.
1:41:00
>> Um and you can go through sort of vertical by vertical.
1:41:01
There's a bunch of verticals now we know a bridge for healthcare and maybe you know there's there's a handful for each thing.
1:41:07
>> Um but then there's a bunch of markets where it's clear the market's going to be important and there's tons of players but we don't know who the winners are.
1:41:13
that's financial tooling, maybe that's sales enablement, maybe that's accounting, you know, you can come up with a list.
1:41:20
>> Um, >> legal legal feels like legal feels like it's already solidified except a handful of these more vertical specific, you know, uh, specifically we we we were joking uh there's people doing injury, you know, personal injury law agents, you know, ambulance chaser agents, but uh it feels like the categories are >> uh solidifying.
1:41:40
I guess the question I have is >> you've backed W winners and basically all these categories.
1:41:46
Where do you feel underexposed from an investment standpoint?
1:41:50
What do you think you didn't >> quite anticipate?
1:41:52
Is it is it like energy possibly?
1:41:55
I'm sure you have bets there, but where do you feel underexposed?
1:42:00
>> That's a really good question.
1:42:00
And I feel like the two big trends of this era so far have basically and by era I mean like two years you know it's not it's been your errors you know of recent last two weeks you know modern millennial last two weeks.
1:42:11
Yeah exactly the last two weeks of this era. >> Yeah exactly.
1:42:14
Um I think that there's uh the two big things are basically defense and you know I was very early involved with Anderell and Leather D and have participated basically in every round of that company and then I'm an investor in um Seronic and Helsing and then Kayla in Israel.
1:42:29
Um, but very very little defense actually over like a 10-year span of investing, right?
1:42:34
I did Ander only for like seven years because it was like the only company that I thought was just going to keep going forever and I think it's the the you know a generational winner there.
1:42:42
Um, but uh uh and then there's AI. >> Mhm.
1:42:47
>> And AI means everything now.
1:42:47
It means consumer, it means rollups, it means electrical s it means Yeah.
1:42:53
>> natural gas turbines are AI index, right? >> Yeah. Exactly. Yeah.
1:42:56
Trains have to move GPUs across the country. >> Yep.
1:43:00
FedEx throw that in there. Yeah, I love it.
1:43:03
Yeah, FedEx is my favorite AI company.
1:43:04
So, I think um you know, those are the the sort of two obvious trends now.
1:43:09
Six or seven or eight years ago, they weren't obvious. Now they are.
1:43:11
Um and you know, honestly, obvious trends often go longer than you think.
1:43:15
I remember with the social networks, there was um a bunch that didn't work out and then MySpace and Friendster and eventually had Facebook and LinkedIn and Twitter and then at that point everybody said it's over. >> Yeah.
1:43:26
>> Everything in social saturated.
1:43:26
But then we had WhatsApp and we had Instagram and we had Tik Tok and you know just it just kept going.
1:43:32
Um AI is in a much earlier version of that right now where um I think we're at the very very early days of this massive wave and so to some extent I'm underexposed to AI in general because I think it's the biggest thing that's happened in you know 20 years or longer.
1:43:47
>> Lad Gil says he's underexposed to AI. You're very very humble.
1:43:50
The chat says everything important, a lot is in. >> Yeah.
1:43:55
>> Uh what is what is uh what's not AI?
1:43:58
When do you get a pitch where they use a the word the letters AI on their website a lot, but you're just like, "Hey guys, this is >> this is just this is just regular enterprise stuff."
1:44:07
>> Well, I actually bring this back to like what's durable in the face of AI.
1:44:11
>> And a good example of that is Ripling, right?
1:44:13
Ripling is a amazing company.
1:44:13
um they uh cross- sell a dozen different HR products >> and AI can make some stuff better, but nobody's going to do like the AI first rippling >> y >> and suddenly win.
1:44:25
Right now, the the main threat maybe to a rippling or deal or sort of related companies is if company headcount actually goes down because of AI, >> then they have fewer seats they sell, right?
1:44:35
And so that's maybe how there could be a headwind from AI for these companies.
1:44:38
But >> but maybe that means AI >> maybe that means we just get a lot more companies, smaller teams, right?
1:44:43
Yeah, >> it's quite possible. Yeah.
1:44:45
So, I I just think like that's the when you see that you're like, okay, this is very durable in the face of AI and that's great, right?
1:44:52
And so, a lack of AI means AI can't displace it.
1:44:54
And so, as long as it's working, it's actually more interesting in some ways. >> Yeah.
1:44:58
>> Yeah. question I sort of ask myself is uh you know using a company like Ripling for for example uh even if companies start needing less people there's still they can they I could see them transitioning to kind of valuebased
1:45:14
pricing around what is it what's the value of like running your HR department right is it >> 3% of revenue is it 5% of revenue is it 1% of revenue like either way they're going to make money if they're providing like infrastructure that function. >> Yeah, it's a great insight because I
1:45:30
>> Yeah, it's a great insight because I think one there there's two or three things that are underappreciated about this AI wave.
1:45:33
Um I think that the first thing is that um the the capability set has shifted dramatically, not just in terms of what these models can do, but the fact that you can just ping them with an API and something that's accessible to everybody.
1:45:44
And I think that's actually very underdised, right, relative to the the prior world.
1:45:47
I think a second thing is that the markets are oddly open.
1:45:51
Like legal never bought any software.
1:45:53
software. it was really hard to sell into legal but because of AI suddenly Harvey can exist right um >> and then uh the third thing is that uh a lot of this is about what you're saying which is the tams of markets are shifting from seatbased pricing or
1:46:08
seat-based value to labor you're replacing human labor and so you're looking at for example customer support it's not zenzas how many seats can you sell to customer support reps it's how much can you augment and do work for customer support reps. It's the labor
1:46:22
It's the labor market versus the software market.
1:46:26
>> And I think that's very underappreciated when you think about market size for some of these things.
1:46:29
You're really going to miss the size of these markets and how big they are.
1:46:32
You know, the services economy that we looked at on my team in terms of like where AI could intervene is about $5 trillion, right?
1:46:40
So, it's a lot of GDP is accessible to this.
1:46:43
And so then you ask, okay, is it is it a workflow that's specialized to customer support like whatever?
1:46:49
Is it a roll up where you're buying assets and changing them?
1:46:52
Is it a different approach?
1:46:54
Like how do you sort of span all the change that's coming because of this?
1:46:59
>> Uh Ken Griffin gave a talk earlier this week and he was saying that in 1999 and 2000 it was very obvious that the internet was going to change the world, change the way that our economies run, yet it still took 15 years for it to actually have an impact.
1:47:16
>> Uh and he was comparing that to today.
1:47:19
The difference of today is that we have the internet so we can deliver these products instantaneously to the entire world.
1:47:25
Do you think that >> uh do you think that this time can be different and we can uh as an industry unlock the value of this technology on a shorter timeline than than the internet took because we just didn't have you know the internet is the greatest distribution engine in history. Mhm.
1:47:43
Yeah, it's an excellent question and I think um both things can be true simultaneously which is we're seeing real revenue for these companies, right?
1:47:50
Cursor is rumored to be in the high hundreds of millions of revenue.
1:47:52
Um you know Azure added something like two or three billion of AI revenue per quarter from sort of a cold start two or three years ago, right? That's amazing.
1:48:02
That's like $10 billion run rate plus just off of AI revenue, right? So it is working. It is being adopted.
1:48:09
But the flip side of it is it'll probably take a decade, right?
1:48:13
And so I think both of those things are true.
1:48:14
And I think the biggest impediment to adoption isn't the technology.
1:48:18
We could do so much stuff with the technology right now.
1:48:19
It's organizational process.
1:48:21
It's workflow management.
1:48:23
It's all the stuff that happens when a big enterprise uses anything.
1:48:25
And they're like, you want me to change my tooling?
1:48:28
You want me to change my people?
1:48:29
You want me to, you know, my processes?
1:48:30
And that's what's going to slow it down.
1:48:32
And that's slow down every technology way.
1:48:34
But to your point, we have massive distribution.
1:48:37
It's already everywhere in some sense, right?
1:48:39
I don't know that you guys probably know the number.
1:48:41
You just talked to Sam Alman, right?
1:48:42
What's the number of people using ChattPT per month, >> but that's a huge impact already.
1:48:47
>> Yeah, it's interesting. They haven't said that.
1:48:49
It has to be north of a billion because they're already they're reporting 800 weekly active view.
1:48:53
>> If you have 800 weekly, you have to have over a billion.
1:48:55
And that feels like such a new cycle, but maybe he's just keeping it in his back pocket for when needs a good bit.
1:49:02
>> Bit of a wild card question.
1:49:02
And I didn't plan this, so I didn't mention it beforehand, but no, it's not it's not bad, but I just think it's interesting.
1:49:09
If you couldn't be an entrepreneur and you couldn't be an investor, >> what hyperscaler would you want to work at where, you know, be an executive at? >> That's interesting.
1:49:18
>> Oh, that's so interesting. I don't know.
1:49:21
I could make arguments for two or three of them.
1:49:22
Um because I think there's such different problems to be had and different assets or, you know, Google, for example, just has such amazing assets relative to this era, right? They have the most data.
1:49:33
They have the most compute.
1:49:35
They have they have amazing cash flow.
1:49:37
I mean, they're just like input. >> Yeah. Amazing stock.
1:49:43
Um, so there's amazing things they could do.
1:49:45
Um, obviously there's uh crazy stuff Microsoft can do on the business side, plus with GitHub and uh, Copilot and everything, you know.
1:49:53
So, they should really be driving a lot of the coding future in my opinion if if they um make the right moves over time.
1:49:58
the right moves over time. um you know and so you can kind of go through one by one and say there's really interesting things meta in terms of social I think there's opportunities everywhere >> um what give us a give us an update on
1:50:12
AI rollups you have some investments here from my understanding but how how do you see the category evolving we see new com you know new teams coming together to attack various uh various markets with this strategy almost daily now But what's your view? >> Yeah, I think um so it's back to if you
1:50:31
>> Yeah, I think um so it's back to if you look at services in the US, it's 3 and a half to 5 trillion of it uh is sort of labor that to some extent could be augmented or displaced by AI.
1:50:40
And so the idea is um can you uh there's certain types of companies that are going to be very slow to adopt software or AI.
1:50:48
And so there's two things you can do with that.
1:50:51
can wait and build a software company that will take a really long time.
1:50:54
You can actually buy those companies, implement the AI changes and dramatically change their margin structure.
1:50:59
And that doesn't mean letting people go.
1:51:00
It could just mean you make people five times more productive >> for certain types of roles.
1:51:03
So you can look at different businesses where you know 80% of the cost of that business is repetitive white collar labor.
1:51:10
>> And so you can help augment or automate stuff for people.
1:51:12
Um and so I've looked at a few dozen of uh teams or companies doing this.
1:51:17
I ended up backing two of them.
1:51:19
And um really you need three things to make this sort of strategy work which is truly transforming a business with AI and then scaling it up.
1:51:27
Uh the first is you need a great um AI person obviously right you need to be able to implement the technology.
1:51:31
Second you need a great PE person.
1:51:32
You need to buy assets properly understand your envelope just like a SAS company has its ICP or like customer profile that goes after you almost have like your M&A profile like what fits in my pocket of stuff that I want to go after.
1:51:43
And then lastly, you need somebody who's operationally great, who can rework the organization against the AI because that's often the hard part, right?
1:51:50
You actually have to get people to use this stuff in order for it to be implemented.
1:51:55
And so very, very few of these teams have all three of those things.
1:51:56
And many of these teams are basically doing traditional PE rollups.
1:52:01
They're not really using AI, but they're raising at AI prices and then they're buying at PE prices.
1:52:05
And so this arbing and so I've tended to avoid arbitrage.
1:52:09
>> Yeah, it seems like a great deal with the founder.
1:52:10
In another world, they'd be doing a private equity fund with two and 20 and then here they can go out and raise and dilute 20, you know, raise 20 on a 100 and then they own 80% of the >> of the business. >> Yeah. Remarkable.
1:52:25
>> Yeah, it's a it's a very smart thing to do and if I was a PE person, I totally could do that and start doing AI, but most of these things aren't doing AI, right?
1:52:32
And so, but a handful of them that are are going to be massive, right?
1:52:35
Imagine an AI dener, right?
1:52:35
It's just >> it can really be transformative to big sectors. Yeah.
1:52:41
>> And it changes something from a services margin to a software margin.
1:52:43
Business with software leverage. >> Yeah.
1:52:47
>> So it changes the characteristics of the of the business.
1:52:49
>> Sort of sort of flashing back in your career.
1:52:51
One of my questions I've always had on my mind is uh uh that you kind of like created the solo capitalist idea.
1:52:58
People have kind of, you know, put that label with you.
1:53:00
Was that just a happy accident?
1:53:01
Did you were you deliberate that you didn't wrap what you were doing in a firm?
1:53:06
There's obviously people that start with similar scales but wrap it in a firm with a brand and uh like how thoughtful was that?
1:53:14
What were the considerations?
1:53:15
Do do you like what how that play?
1:53:18
>> Yeah, I think um you know for a while it really was just me.
1:53:20
So it wasn't some strategic move to you know >> do something.
1:53:25
It was just I was on my own doing stuff and I you know um and then eventually I brought on people for back office and finance because like I think that's really important right? You want compliance.
1:53:32
You want things to be proper and all that.
1:53:33
Um uh and then I got this moniker and I never asked for it, right?
1:53:37
Like I actually am happy to be called whatever as long as I get to be involved with the most interesting technology and technologist in the world.
1:53:42
You know, they could call me >> I don't know what a carpenter.
1:53:45
I don't care what >> they could call you big VC, big venture capital.
1:53:50
>> That's the one thing I don't want to be called.
1:53:51
called. Other than that, I think um >> what we do is different from like traditional VC too, you know, like I don't I I uh we do traditional investing and we do traditional venture, but I actually think we do a bunch of other stuff and we do interesting projects around um
1:54:06
>> you know, things like uh one person on my team who's working as an investor as a technical background is actually driving >> uh uh AIdriven translation of the world's thousand most important books that are off of copyright and we're working with um a few really big foundation mobs on that. So we do stuff
1:54:19
So we do stuff like that too just >> because it's interesting.
1:54:23
So I hope it's never just a venture fund.
1:54:25
But >> do you think when do you expect >> uh AI to transform venture capital?
1:54:30
I think it's notable that the firm >> today and the activities of the firm look quite similar to prehat GPT.
1:54:39
Maybe you can write a investment memo faster.
1:54:44
Maybe you can uh seem like you prepped for a board meeting better.
1:54:47
you know, if if you just drop the deck in and and ask for a summary, but uh it doesn't feel like it has changed the profession at all yet.
1:54:56
It's still uh finding and winning allocation and and um >> you know, but >> yeah, I think it can help with some aspects of diligence to your point like it can pull competitors and things like that.
1:55:08
Um to some extent it depends on the market, you know, there may be weird uses that nobody's done yet.
1:55:12
So, an example would be, have you ever done the prompts where you ask the um AI to like uh cold face read somebody and tell you about their personality? >> No. You you upload for this? >> Yeah.
1:55:25
I mean, just just analyzing somebody's personality with a picture, even just any picture of their face. Yeah.
1:55:30
It's it's pretty I mean, this is like the the skits is called physomy. >> Sure. Sure. >> Yeah. Yeah. Yeah.
1:55:36
But there's stuff like that where I've I've done that just for fun with my friends, right?
1:55:39
I'm like, "Hey, what what is this person like?"
1:55:42
and my friend's sitting there with me, right?
1:55:43
I'm not secretly trying to psychoanalyze them or something.
1:55:47
>> And then I'll ask it to give me a detailed breakdown of those characteristics and why.
1:55:50
And it'll say, "Oh, this person looks like they have a genuine sense of humor and they're warm because of the way that the crow's eyes >> around their eyes exists in this way versus somebody who fake smiles because it doesn't get to the eyes, so there's no wrinkling."
1:56:02
And you're like, "Wow, that's actually like super interesting, right?"
1:56:05
And so it'll break down the sense of humor.
1:56:07
It'll break down >> uh how likely that person is to be loud or quiet.
1:56:11
the like the aggressiveness like all this stuff.
1:56:14
>> Yeah, you can imagine there's there's a somebody could create an EQ co-pilot for the new like meta display glasses.
1:56:18
You can just walk around >> and I and if I'm maybe I'm really high IQ, but I don't read people that well, I could look at John and say, uh, which is probably probably inverted, but I could look at John and be like, "Oh, John is John's very interested in the conversation, and he he clearly wants to be friends."
1:56:38
>> So, I think there's more more to more to build there.
1:56:39
uh give us the update on on uh on your your company with Jared Kushner.
1:56:44
I know he's been very busy.
1:56:44
Uh but uh but I'm excited to to hear the latest. >> Oh, sure. Yeah.
1:56:50
So, um we recently launched a company um that's called Brainco, which is focused on using AI uh as basically a platform to help transform the world's largest institutions.
1:56:59
And so, we've been working with a number of large enterprises um some private equity um and other firms around this.
1:57:06
And so, um, it's just been a fun project to do, uh, with him and with Eric Woo and Lewis Vidigray and a few other people.
1:57:12
Eric was the former CEO of Open Door.
1:57:15
And then Lewis, uh, is, uh, the former finance minister and foreign minister of Mexico.
1:57:20
So, it's kind of this interesting group of people coming together to try and solve really big AI problems.
1:57:25
So, that's been really fun.
1:57:26
fun. So is this realizing how much uh the Accentur and the McKenzies of the world were were getting paid to make pitch decks on basically here's here's what you should know about AI for your business and realizing hey we could probably do that a lot better and then ultimately build software >> within these organizations like what is the actual >> it's much more focused on the yeah it's more focused on the software side of it
1:57:48
so basically there's a common platform that's involved in terms of dealing with different forms of data dealing with eval dealing with a lot of the things that every enterprise needs to build in order to >> um really adopt AI and then we build vertical specific applications on top of that or in some cases horizontal applications that can be reused over and over by um similar companies in the same vertical. So you could imagine for
1:58:06
So you could imagine for example for a financial industry company there's like a dozen things that every single one of them needs to build and there's some customization around it.
1:58:15
It's kind of funny because if you look at very large deals, right, if you're Dell or your VMware or your Oracle and you do like a tens of millions of dollar deal with with a customer, you're going to have customization against that customer.
1:58:26
You can afford to do it, but also it's important enough to do that for them.
1:58:29
And so it's similar in that regards where we have common infrastructure, common platform, the same vertical applications, but then there's going to be some customization per yeah >> um per client just like any other giant, you know, enterprise company.
1:58:42
Have you thought about slicing the target customer either across vertical like we're not doing healthcare because of HIPPA just yet or we're not doing defense because of Fed ramp just yet or we we think we have a lot in industrials that we can go after or or are you more focused on uh slicing by you know market cap or size of business like yeah we're not going to work with mid-market companies.
1:59:05
How do you think about like where the wheelhouse customer will be?
1:59:09
Yeah, it's very much um the the goal is to work uh almost solely and there's going to be some counter examples of this uh with companies that are truly the the world's biggest institutions in terms of revenue, market cap, and then potentially impact, which means sometimes you work with somebody a little bit smaller, >> but the goal is to ask how can you use AI to really get leverage on things that are important at at sort of a massive scale.
1:59:32
Yeah, there was a report that JP Morgan is spending $2 billion a year investing in AI to effectively save $2 billion a year from automating.
1:59:41
It's like when there's that much. >> Yeah. Yeah.
1:59:44
They're breaking even basically.
1:59:46
I mean, it presumably like some of those savings are durable, but >> um but certainly there's a lot of money.
1:59:53
Um, what do you how how how good do you think you've gotten at clocking uh AI pilot revenue as nondurable?
2:00:03
Because there you I'm sure you saw that that headline an MIT study came out that said basically 95% of pilots are are not actually delivering in value.
2:00:11
This this felt like the year the year of the pilot.
2:00:15
Next year is maybe the year of reality.
2:00:18
>> Uh but I don't know how you see it.
2:00:20
Yeah, I just view that as a standard technology cycle.
2:00:22
I thought that was a very overstated article.
2:00:23
So, um, you know, this happened with mobile.
2:00:26
You do the kind of crappy mobile app.
2:00:28
I don't know if you guys remember the first BFA mobile app.
2:00:32
>> It was basically like a >> Yeah, it was just like a web page. >> Yeah.
2:00:36
>> Well, the the current BFA app is still still pretty rough.
2:00:39
So, >> I actually think it's pretty good.
2:00:40
Like, you can go to an ATM, you can take out cash.
2:00:43
I think I'm the only person who still does that.
2:00:44
um you can take pictures of checks, you can pay with zel, you can do all these things, right, that you couldn't do before.
2:00:51
>> Um but you started off and you tried to log in and the thing would crash.
2:00:52
So I just feel like we're kind of in that era of AI implementation. People will get it.
2:00:57
It'll take a decade to fully sort of propagate to your earlier point, but it really is the big wave that we're living through right now and I think it's truly transformative.
2:01:05
Would you ever uh would you ever uh have you ever considered an LBO of any of these companies that are in the the SAS apocalypse in the public markets that clearly have >> some you know you know super meaningful customer relationships and a ton of potential important place in their market but just aren't evolving their business model quickly enough.
2:01:28
>> Yeah, we've looked at that actually.
2:01:28
>> Yeah, we've looked at that actually. I think there's a few really interesting things to be done at scale and to your point I think part of it is just driven by can you actually implement AI and I think the if you look at the private equity industry in general they've talked a lot about um tech transformation that was a prior wave
2:01:44
right like 10 years ago and you had all these tech based rollups like Compass was supposedly a technology company and it's a great company but it's not really a tech company right and so I think um >> we've we've kind of lived through the cycle before where people do almost like tech fake tech tech implementation where They claim they're doing it, they get a higher valuation and it doesn't quite happen. They still load up the company
2:02:02
They still load up the company with debt.
2:02:04
They still run it a certain way.
2:02:05
They, you know, the the drivers are different.
2:02:07
The CEO is the wrong person, etc.
2:02:09
I think there's a good version of that to be done.
2:02:11
I don't think it's easy, but if you do it, I think you can unlock an enormous amount of potential in companies that won't make it otherwise or won't go there.
2:02:16
And so, yeah, I think that's a super interesting area and we we've looked at a few things over time.
2:02:22
Um, and part of the decision sometimes is like do you want to try and do that or you just fund a startup that you think will get there instead >> and uh it's a little bit of that it's kind of easier to just fund a startup because buying a company and transforming it is quite hard.
2:02:36
Yeah, it has to be a company that is I mean is is uh at a sufficient scale.
2:02:41
Obviously, we just saw that the EA LBO.
2:02:44
You don't need to go that big, but finding something that's like really a whale.
2:02:51
>> Can't hurt to go that big, though.
2:02:52
>> Yeah, I would like we would like to see you go that big.
2:02:54
>> I would love to see >> I feel like that's the next that's the next >> I feel like you've done it all at the early stage.
2:02:58
You've done it all in growth.
2:03:00
I feel like just get into the >> How about an Activision spin out? Activision spin out.
2:03:04
Take Microsoft Game Pass, Xbox lagging. Come on. I know. I'm moving too slow. You're like my mother.
2:03:11
You're putting all this pressure on me. >> I know.
2:03:13
That's that's our small ask is set the record. >> Wait, wait.
2:03:16
Do you have Do you have any We like to ring the gong for people around here when they show a number.
2:03:19
Do you have any number you can share?
2:03:22
What's your favorite number of deals?
2:03:23
Number aum number I don't know anything.
2:03:26
Do you What's a number that that quantifies your your corpus of work?
2:03:31
Number of startups founded. my corporate.
2:03:32
Oh, I've started um well, I've started two companies directly and there's two I've incubated.
2:03:37
So, four of us is >> that's a lot of business.
2:03:42
>> Relatively modest amount for the amount of EV created.
2:03:44
So, >> it's good good hit rate.
2:03:47
>> Well, thank you so much for stopping by. This was a lot of fun.
2:03:49
Really glad we'd love to do it again. We'll talk to you soon. Have a good day. >> Really appreciate it. >> Take care.
2:03:55
>> Uh before our next guest joins, let me tell you about numeralhq. com. Sales tax on autopilot.
2:03:59
spend less than 5 minutes per month on sales tax compliance.
2:04:03
>> I hate to pick favorites. I hate to say it.
2:04:05
I that was I was I was more I was more engaged for for a lot than uh >> Aladd was great >> then was great.
2:04:12
>> Sora But uh his book High Growth Handbook Yes. is >> fantastic.
2:04:16
It's a series of interviews. >> Yeah.
2:04:19
Is my >> favorite uh favorite business book. >> Yeah.
2:04:23
No, it's a great >> high growth handbook.
2:04:24
Scaling startups from 10 to 10,000 people.
2:04:26
interview some timeless bunch of great interviews and uh yeah, you should go pick it up.
2:04:32
I need to I need to relisten to it.
2:04:36
>> Well, without further ado, we have Robbie Stein from Google in the reream waiting room.
2:04:41
>> Welcome to the show, Robbie. How you doing? >> Welcome. >> Good to see you. >> Hey. >> Hi. Can you guys hear? >> We can hear you. We can hear you.
2:04:49
Um, I I know people are going to be confused, so why don't we just get out in front of it and explain your role at Google relative to Gemini, relative to AI.
2:04:58
Uh, take us on a little, uh, Game of Thrones HBO intro of the map of Google and where you fit in. >> Sure. Yeah.
2:05:08
So, uh, I work on the Google search team. So, it's the search bar. You type things in. Yep. >> Yeah.
2:05:13
I was going to ask, could you could you What is Google? >> Yeah, it's a thing.
2:05:16
You could type a question in.
2:05:17
Sometimes you could, uh, use a camera.
2:05:19
I don't know if you've used Google Lens.
2:05:20
You can also Google that way too.
2:05:22
There's a there's this app. It's also called Google.
2:05:24
All that kind of stuff is is where I focus my time >> consistent.
2:05:28
And the don't forget about the I'm feeling lucky button.
2:05:29
It's still on there, right? >> Yeah. >> Yes.
2:05:34
>> So So, so how do you think about integration with the Deep Mind team, integration with the Gemini team?
2:05:38
Um how do you think about bringing AI to search? Yeah.
2:05:45
So we work very closely with the Google DeepMind team, Demis, Corey, that whole group.
2:05:49
And the way you think about it is we want to have frontier models right in search.
2:05:52
So you can really ask anything and have the the ability to use all of Search's incredible knowledge, real-time information systems and context of the web to help give people this incredible information.
2:06:03
And that's really where the two come together. >> Yeah.
2:06:06
>> Yeah. there there was this uh question this like you know chattering class being like oh well Google's uh you know it's such a different paradigm chat versus a search 10 blue links but have you drawn on the fact that uh Google's search started with two modalities the I'm feeling lucky button was a different
2:06:25
way to interact with Google search uh the 10 blue links was one way uh are you how are you thinking about how you like kind of level up or educate the consumer consumer to use the all the different tools since now there's not just you know search results and and and AI overviews but there's so many
2:06:43
different things how do you think about ramping those up >> yeah so there's always been many ways to use search actually Google lens is a good example you can take a picture of something you can ask what is going on with this plant that seems to be dying and you can get information from that right from the camera and that happens
2:06:57
in the app so there's always been different ways that you could access and tap into the search knowledge base >> um but I think increasingly it feels like you want to go to search ask whatever you have in mind, you only want to think about where you're going to ask that question. And then if you have
2:07:09
And then if you have something where AI is really helpful, you get this little AI preview that's starting to show up now around AI overviews.
2:07:15
And if you click into that, you're in this AI driven experience.
2:07:17
And we've now through a new new project we launched called AI mode allow you to follow up, go deeper, and have a full generative end-to-end chat like experience right within Google search. >> Yeah.
2:07:29
Uh walk me through the international expansion.
2:07:31
I'd love to know if legal or engineering is more rate limiting there.
2:07:37
It feels like it's it's got to be incredibly complex to uh check all the boxes when you want to expand. You've obviously expand.
2:07:47
So, what's the secret to uh taking over the entire world so quickly?
2:07:52
>> Well, our newest our newest product um AI mode, which is the thing that lets you really ask anything and within Google search using frontier state-of-the-art models.
2:07:59
you know, we we launched in the US and then quickly in India, a couple countries, UK, um, over the summer, I think May, June, July timeline.
2:08:07
And then just a couple months later, now we're at over 200 countries, 40 languages.
2:08:11
We moved really fast, >> uh, to ship that.
2:08:14
And so, we're now basically everywhere except for a couple countries.
2:08:18
And there's certainly a bunch of considerations, policy, >> uh, and infrastructure.
2:08:22
Honestly, they both affect the timeline. >> Oh, yeah.
2:08:24
Because there's actual inference going on.
2:08:26
So you need local compute basically more than >> there's also there's there's we want to make sure do quality checks because in every language you have different permutations or you have multilingual with people moving between English and other languages.
2:08:37
Just want to make sure everything is doing what you expect it to do.
2:08:40
You know this is also a multi-turn conversational experience.
2:08:41
So when you evaluate it you want to make sure that it's dialed before you go.
2:08:47
>> Um and so each of those just takes time because I know I know everyone's always frustrated like why can't I use it today?
2:08:51
It's the main thing I see on X.
2:08:53
>> Um but hopefully now almost everyone can.
2:08:54
How are GPUs allocated at Google? You have or TPUs.
2:08:58
You have TPUs in the cloud. You're selling them now.
2:09:02
Obviously, DeepMind wants for research.
2:09:05
Gemin equally, >> but I imagine that, you know, is is there a spreadsheet like what's the process to actually uh to figure out where to allocate GPUs or TPUs? >> GPU.
2:09:18
I mean, there's a there's a there's an allocation process.
2:09:19
I mean, everyone needs TPUs.
2:09:21
needs TPUs. It's just comput is by far the most important thing in driving um infrastructure right now and there's lots of needs but they're they're important things we want search the search is one of the largest ways people interact with AI so that's like a it's very important one obviously we're doing
2:09:37
frontier modeling work we've got a bunch of things happening in cloud so that that's there's a process by which you do those funny I did an event and a Google team actually gave me like a old Ironwood like gen prior gen single TPU in this little case >> and I was joking if somehow I could like crack it open and like refurb it and like get it up and running. I can
2:09:54
I can somehow like >> improve improve my standing in the on the team.
2:09:58
But uh I don't think it's going to happen.
2:10:01
>> How how often do you guys come back to Google's mission when when thinking about product decisions?
2:10:08
We've talked about this on the show before.
2:10:10
There's always, >> you know, you I'm sure you wake up every morning, there's a new headline.
2:10:14
What is Google doing in a uh in AI?
2:10:16
Why haven't they released this faster? Etc. , etc.
2:10:22
But I, you know, we were never uh we never really stressed about it too much because when you look back, I'm I have a AI overview here.
2:10:29
I said, "What is Google's mission?"
2:10:30
My AI overview says, "Google's official mission is to organize the world's information and make it universally accessible and useful and it feels like LLMs are just so aligned.
2:10:40
It's the perfect technology >> to to carry out the mission.
2:10:43
And so it's like relax everyone.
2:10:46
I think this is uh this is like a natural evolution for the company. >> Yeah.
2:10:52
I mean we talk a lot internally actually about how the mission has never felt more relevant and it is really incredible to work somewhere.
2:10:58
I worked at Google in 2007 for a while did some startups and you worked in some other companies too.
2:11:04
companies too. I'm back now and it's it feels that same level of entrepreneurialism in 2007 where it's like you're building all these new things for the first time except you're kind of building them again because AI allows you to say what does search look like if you could really ask literally any question and have created an AI that's the most knowledgeable AI out
2:11:22
there that could understand all of Google's information the context of the web and you could talk to it and by the way you could talk to it live like we just announced search live that's available so if you're driving you could just talk to Google literally like on in your car you could take a picture and have this multimodal conversation back and forth now. Like this is all stuff
2:11:36
Like this is all stuff that talked about a long time ago but was limited because of technology.
2:11:40
So that is incredibly exciting.
2:11:42
It's it's very motivating and I do feel like is one of the reasons people on the team are fired up.
2:11:47
>> How do you think I mean it it's it's so interesting that uh as LLM's boomed AI search overviews uh made a ton of sense were baked in adopted loved uh but now we're already in the next phase which feels like agentic purchasing agentic checkout.
2:12:02
uh how do you think evolving how do you think about evolving the product even further to go from knowledge retrieval to taking action? >> Yeah.
2:12:11
Um we have a bunch actually active there and we recently launched in the US an agentic experience where you can book um restaurants um and local services through Agentic.
2:12:22
So it's actually really neat like you through AI mode now um you can just have a conversation.
2:12:26
Hey, what's a good date night place? It'll do all the thing.
2:12:28
It'll tap into the knowledge of Google.
2:12:29
It'll look up Google places. It'll do research. It'll do whatever.
2:12:32
But then if you want to start a task, it'll also go bring back availability across talk and opent like right in the experience and you can just book it and it's awesome. I've been using that.
2:12:42
It's just a small example of what's possible.
2:12:45
>> You know, people come to Google >> not just for information but to get things done.
2:12:48
It just materializes itself as a query.
2:12:50
But you're not like >> I don't like want to just know restaurant reservation availability and like oh sweet.
2:12:55
I'm glad to know there's a table available.
2:12:57
I'm going to go back to my day.
2:12:58
Like you're trying to do something.
2:13:00
We think about that a lot and that's just the you know the surface that there's so much people are trying to do but they're just kind of getting started with those journeys on search.
2:13:08
What could we do to really help you? Shopping is a big one.
2:13:10
Um so we have an we just launched a new visual uh way to do AI which like is one of the first ways where AI can be helpful with inspirational tasks.
2:13:17
So now in AI I mode if you ask to design a bedroom or look up landscape lighting it actually finds you beautiful inspirational imagery >> and products in a grid. You could click on it.
2:13:26
You can imagine getting much more help finalizing those purchases, doing, you know, being reminded of price changes and it's much more of this interactive version of search that can do things for you and you can you can really connect with versus just a pureformational experience.
2:13:42
Uh right now my my mental model for is like google.
2:13:47
com the search bar then AI mode almost as a vertical product like flights like uh images uh like shopping where it's sort of a portal or subproduct that I get uh you know I I go down a funnel and I wind up in um do you see that holding or do you think that AI mode acts as a wrapper on top of all the different sub search products.
2:14:16
>> Yeah, I think what's going to happen is you have this AI mode which is going to hopefully be this most knowledgeable AI possible.
2:14:21
It knows everything in Google, billions of products, million hundreds of millions of locations, all of the web and it has access to all of it.
2:14:28
Knows how to use Google as a tool and it's super powerful, >> but not necessarily the best thing for all things.
2:14:34
Like if you just need a specific phone number, you probably get that in like 50 milliseconds right at the top of the page.
2:14:38
You just want to know a sports score.
2:14:40
know a sports score. what's what's literally the sports score right now just works you just you know you put it in Google or if you're just looking up a musician's name for the first time you're trying to get a browsier experience like you actually want to kind of see images you want to see what's going on on what are people
2:14:53
saying on X which shows up in the search page so I think what happens is you have this incredibly knowledgeable system that we feel like is designed for more complex tasks more of this like how do I do this what's my advice for this I'm doing this trip I need this restaurant I'm trying to buy some jeans how do I get started with that and that if you
2:15:08
have knowledge baked into that that's really powerful but then people need how do you how do you bring that to people and there's basically two ways one is you just search and through AI overviews we will show AI where we think it's useful >> and for many queries it's not useful actually which is why it doesn't show up the system learns that um but for these
2:15:25
longer queries where you have a specific question typically shows up there um then the other way is for power users we feel like they kind of have this mental model of like oh like this I'm doing this planning thing or like oh I'm like I'm really curious to know like um what a stock price difference between these three stocks are over some period of time. You wish you could just type that
2:15:42
You wish you could just type that in natural language and have the thing generate a chart and look at use Google Finance as a tool which it will do and for that you can go right to AI mode.
2:15:49
So if you can do that through the mode you can do it on mobile through those direct um kind of buttons to go right to AI mode.
2:15:56
You can go through Chrome now we announced like a way to just type and go right to the eye mode in Chrome and um you could also just go to google.
2:16:03
comai now which is kind of fun.
2:16:05
What anomalies are you seeing?
2:16:08
Uh have you seen any of these screenshots of uh of Google trend data?
2:16:14
People are are posting, you know, people forever have been posting screenshots of effectively search data and uh using them to infer what's happening in in the world, right?
2:16:26
And so over the past few months, we've seen people posting uh search queries like help with my mortgage.
2:16:34
and it's just like a crazy uh ramp uh up and to the right.
2:16:37
Uh my uh my intuition is that it's potentially uh a bunch of different keywords are seeing these crazy uh ramps because there's potentially agents sort of like leveraging Google search to uh to drive a higher volume of searches on potentially a search that's happening maybe in an LLM.
2:17:00
Have you seen any anomalies there?
2:17:02
or is that something you're uh aware of?
2:17:07
>> Um haven't personally seen any anomalies there.
2:17:09
I I don't I haven't really heard of that before.
2:17:12
Um so wouldn't look I wouldn't buy too much into that.
2:17:16
Um we do have protections for those kinds of things.
2:17:20
>> Um I think in general what we're seeing is people who are using Google very differently and at a at a very fast growth.
2:17:27
So people are asking very specific questions of Google.
2:17:29
They're they're using Google Lens and asking multimodal questions.
2:17:32
They're asking follow-ups.
2:17:34
I mean, those are kinds of things that we're just seeing we're seeing in such a broad way.
2:17:36
Um, I think that's the thing that we mo mostly focus on.
2:17:41
Um, but yeah, I can't speak more to some of the trends things that you're mentioning. >> Yeah.
2:17:45
How do you think about uh advice for brands?
2:17:48
Uh, I've I've run brands and uh, you know, grinded my way up the SEO rankings.
2:17:54
I never did a ton of uh, optimization.
2:17:57
Mo most of my strategy was just uh try and make something eventually that people talk about and it gets written about and those websites have you know ranking power and then you kind of rise to the top of that keyword.
2:18:10
Is any of that changing in terms of uh in the AI shift?
2:18:14
What advice are you giving to uh brands that want to perform on Google these days organically? >> Yeah.
2:18:22
But what's really interesting is I think the core Google search ranking is more relevant than ever because it turns out that one of the best things that every AI model does now is they kind of like search the web.
2:18:34
It's like I don't know like what are you trying to do? Oh, I don't know.
2:18:37
I'm trying to figure out if like I should go to this hotel. All right.
2:18:40
Well, like parametric knowledge.
2:18:42
Do you like know the rates of those hotels?
2:18:43
Like can't okay I'm going to search the web, right?
2:18:45
And and even AI mode is is special in that we're Google and so it uses Google really effectively and it creates these query fan outs.
2:18:52
It does dozens of queries but it effectively is googling stuff, right?
2:18:57
And everyone's googling stuff all the time.
2:18:59
So for a given question, >> what are the things that show up as highly relevant to a given question, those end up getting absorbed into the context window and have a high probability of being displayed to the user.
2:19:10
And so if you are just thinking how do I build great original content that's trusted and author and and authoritative for specific kind of query.
2:19:18
Turns out that's still going to likely be very valuable.
2:19:22
>> Um and you can go read the Google guidelines on content and um human raider guidelines.
2:19:26
I think they're super interesting.
2:19:28
There's lots of detail in there around how Google evaluates trustful high quality content and scoring systems that are used.
2:19:34
Turns out that's a really good investment because every other system is is kind of proxying for the info that's most useful for a question. >> Yeah.
2:19:42
>> Um so that's my main advice is to kind of like dig in more on understanding how those systems work because it's largely going to apply later. Yeah.
2:19:48
>> And then the second one is what are people using AI for?
2:19:49
Those are the growing >> kind of needs. Oh, sure.
2:19:53
>> And there's a disproportionate amount of use case in different types of domains now with AI because it allows complex needs and it allows for things like advice.
2:20:02
It allows for things like really nuance troubleshooting with stuff.
2:20:04
It allows for these emotional needs to be satisfied differently. Mental health. Y.
2:20:10
So those are areas that are probably growing markets of use cases.
2:20:12
And I would be I would be a student of those as well.
2:20:17
>> What about Sorry, can I have one more on that?
2:20:19
So uh what about uh content that was previously buried to Google that is now available uh for search rankings because of artificial intelligence?
2:20:28
I'm thinking about like literally this show it will be a three-hour video on YouTube that you know a a buried mention previously probably wouldn't be perfectly translated indexed etc etc but uh I would imagine that the the strength of like video content and audio content gets relatively better over time in the AI era.
2:20:52
I mean honestly you guys have been doing this for probably a decade but uh take me through a little bit of that.
2:20:57
Is that is that a reasonable thesis?
2:20:58
I actually we are it is a reasonable thesis.
2:20:59
We have been seeing an increased diversity of the kinds of pages and sites that show up within AI because people are asking these nuanced questions.
2:21:06
A lot of times there isn't even like a single web page that has this information. Yep.
2:21:10
>> But if someone I don't know sometime in the future this this uh video gets segmented and scanned and understood by Google and someone asks for like I don't know uh >> an interesting conversation on Google's AI journey recreating search the AI era. >> Oh sure.
2:21:24
Maybe it's like here's a cool conversation you could check out and this this like clip will show up now in a way that would be very difficult for that to happen unless you search for like TVPN like interview of whatever which was like very specific keyword based on >> or or we'd have to go manually create a transcript and then get that into like the text SEO world.
2:21:43
So yeah, very different uh era. Sorry.
2:21:45
uh what are what are the plans around giving uh if there are any giving publishers control over whether or not their content is used in uh various AI functionality.
2:22:00
>> Yeah, we have a bunch of publisher controls we we have.
2:22:01
So there's an over there's an overall opt out and training side, you know, on search you can opt out of crawling, you can opt out of this other thing called snippets where you can you can show up in Google but you won't show up in these rich these rich experiences if you want.
2:22:13
experiences if you want. Um and so there's there's a bunch of things that you know publishers can do and um can look at there but you know I think ultimately the belief I have is that to the prior conversation you know AI should be this massive um discovery
2:22:29
engine over time because if you think about it >> these complex needs we're getting growth like we're we're seeing 10% growth for instance in large markets like like India and uh the US for these really specific questions which at Google scale
2:22:41
is like enormous enormous number um where you have if you have a really specific question people are doing that more and more and more and more because you can get AI to go deeper multimodal right you're asking taking a photo of something and you want to shop it seeing
2:22:57
70% year-over-year increases in those kinds of questions and these are billions and billions of queries like so this is these are huge numbers >> wait how many queries >> billions are billions >> billions so good >> the sneaky It's always fun. Sorry. Sorry.
2:23:16
>> No, that was totally worth it. I'm glad you did that. >> Thank you.
2:23:19
>> Um, so like these are big numbers and each of those generate AI experiences with links to go deeper on stuff.
2:23:24
Every single one of them.
2:23:26
And so theoretically >> you should have this like unique opportunity to say, "Oh, did you take a picture of your bookshelf?
2:23:33
Go, what book should I read?"
2:23:34
Oh, well, here are cool reviews of other books that are like things you've liked.
2:23:37
It's like, I could never Google that before.
2:23:38
And so theoretically, you should have because it's such an expansionary moment, we're seeing that this is an expansion more than anything.
2:23:45
Like the old like the way people, they're googling >> and they're using it in all of these new ways.
2:23:51
Um, and so hopefully over the long term that's that produces growth.
2:23:56
>> I have a lot more questions, but >> we'll have to follow up time. Yeah. Yeah.
2:23:59
We could go way deeper here.
2:23:59
I would love to even even just dig into how TBPN shows up on Google.
2:24:03
It's such a fascinating content because we create so much content all over the web.
2:24:07
Uh but thank you so much for taking the time to hop on the show. >> This is fantastic.
2:24:12
Uh and congratulations on the progress. We'll talk to you soon. Cheers.
2:24:16
>> Have a great rest of your day.
2:24:16
Uh >> before we bring in our next guest, let me tell you about Finn. ai.
2:24:20
The number one AI agent for customer service, number one in performance benchmarks, number one in competitive bake offs, number one ranking on G2.
2:24:27
And we have Morgan Hzel in the reream waiting room.
2:24:32
We're going to bring him into the TBPN Ultra Dome.
2:24:34
We're very excited to catch up with you again.
2:24:36
One of our earliest and just most enjoyable guests.
2:24:38
I I such a favorite conversations ever across a thousand plus interviews. >> Remarkable.
2:24:46
So, thank you so much for taking the time to >> especially in a huge huge week.
2:24:50
Congratulations on on the launch. >> Big shoes to fill. Thanks, guys. Nice to see you.
2:24:56
>> Uh yeah, give us the give us the updates. Set the table.
2:24:58
What's going on this week? that gong ready. >> Get this gong. >> I uh Yeah.
2:25:03
So, my my my third book, The Art of Spending Money, came out this week on Tuesday.
2:25:06
You know, it's a tough thing with uh There it is. Thank you. Thank you.
2:25:10
It's a weird It's a weird thing with books.
2:25:12
I think I feel like it's almost like a startup where I I've been a writer for 20 years, >> but you get like three shots on goal when when a book comes out.
2:25:18
And when when when when you're writing a blog post, >> if it sucks, and at times they do, there's always next week.
2:25:24
It's not not that big of a deal.
2:25:26
When when when when you write a book, you really got to be like, "This is this is it."
2:25:29
you really got to put your best foot forward.
2:25:30
So, there's it's always a a stressful thing to go through.
2:25:34
>> Was the process different for this book from the other ones?
2:25:36
Do you've heard from authors who like go lock themselves in a cabin?
2:25:39
Uh like what what's your process like and has it changed?
2:25:43
>> It's usually it's it's usually roughly this.
2:25:45
It's it's about a year of very uh informal noodling where it's like I'll be going for a walk and it'll be like, "Oh, that would be a cool chapter and I could use this story."
2:25:52
It's a year of that like like just just no effort and then three months of part-time writing and three months of full-time writing.
2:25:59
During the last two weeks of the full-time writing, the world does not exist outside of my keyboard.
2:26:02
That's usually how it works. >> Yeah.
2:26:05
And are you like uh combing like like front to back of the manuscript uh like every day?
2:26:09
Are you focused on like a single chapter for a full day?
2:26:14
Like h how do you actually like chop through like what becomes a full book?
2:26:19
>> It's it's usually it's usually the latter.
2:26:21
There's not much going through everything end to end until the very very end of the process.
2:26:24
So it's usually just focusing on one chapter and very roughly.
2:26:27
This is not a hard and fast rule, but when I was writing it, it was like I want to focus on one chapter per week.
2:26:33
>> And normally I I'd say if there's one thing that I've gotten a little bit better at over the years, just a little bit better at, not perfect by any means, is that I think my first draft is closer to my last draft than it used to be.
2:26:41
Not necessarily because I'm a better writer, but because I'm better at knowing what writing is not going to work and then stopping it very quickly.
2:26:49
And so I think when I when I go through a chapter, by the end of it, I can go back and scan it and be like, "Oh, this is pretty good.
2:26:55
I'm going to set that aside."
2:26:55
And then when I do my little self-edit at the end, that's that's usually where where it where most of the work happens.
2:27:02
>> So it's uh much easier to write a book now that that we have AI. Is it >> Yeah. What was your problem? >> I'm kidding. I'm kidding.
2:27:09
>> No, here's here's the thing. Share the promp.
2:27:11
>> I've I've I've talked to >> Just share the prompt. Just give me the prompt. >> Yeah. Come on.
2:27:15
What's share your prompt? >> Come on.
2:27:18
just >> I was talking to a guy the other day who just finished his manuscript and he said without Chachi PT he would not have been able to write the book and I'm like I love hearing that.
2:27:26
I love that if we can have a tool now we're going to have more books being published cuz I think there are people who have very good ideas who have a story to tell but are too intimidating to write a $50,000 a 50,000word uh manuscript which is not an easy thing to do.
2:27:42
>> So if we can just get more people out there because they have chat GBT to get them through writer block awesome. I think it's wonderful.
2:27:46
I'm still I'm still old school because I've been doing it for long enough that I want to write every single one of my words for better or worse.
2:27:52
Even if I could have done a better job with some LLM like getting me through those blocks, I'm still going to try to power it through myself.
2:27:59
>> I'm sure you saw uh David Simon, the creator of The Wire.
2:28:02
There was a screenshot from an interview.
2:28:03
Uh someone asked him, "Okay, you've spent your career creating te television without AI, and I could imagine today you thinking, boy, I wish I had that tool to solve those thorny problems."
2:28:12
David Simon says, "What?"
2:28:14
And the interviewer says, "We're saying dot dot dot."
2:28:17
David Simon goes, "You imagine that?"
2:28:19
And the interviewer goes, "Boy, if if that had existed, it would have uh screwed me over."
2:28:25
Simon says, "I don't think AI can remotely challenge what writers do at a fundamentally creative level."
2:28:30
And then he says, "I'd rather put a gun in my mouth." >> There. There you go. Yeah.
2:28:35
Just just get right to it. Here's what I think.
2:28:36
I've always thought that writer's block is actually a symptom of your idea sucks >> and it's not working.
2:28:43
And the reason you can't find the words to get through is because you know in your soul that this idea is not working. >> Yeah.
2:28:50
You fundamentally don't you don't care about what you're writing about. Right.
2:28:53
And I think as a like when I think about the points where I've been writing >> that I cannot get fig get myself moving.
2:29:00
It's like writing that essay.
2:29:00
I had to take a class in college about dinosaurs and I had to write a paper about dinosaurs.
2:29:07
>> You studied dinosaurs.
2:29:08
>> It was an actual class that fulfilled some sort of like science some sort of requirement.
2:29:13
how your son is obsessed with dinosaurs.
2:29:14
Apple doesn't fall far from the tree. That's incredible.
2:29:17
>> No, but you're writing you're writing about a topic that you don't care about.
2:29:21
The words do not come easily.
2:29:21
You're not >> if you don't care. Of course.
2:29:25
>> Jord is secretly a PhD paleontologist.
2:29:27
I'm finding this out for the first time. Sorry.
2:29:30
>> No, I would say the the flip side of that is when you know you have a good idea and it's a right idea, the words just tend to fall right out and and it's no problem to get them on the paper.
2:29:37
And so I bring that up because I think if you have writer's block and you're like, "Oh, let me use chat GPT to get me through it, it will find a road through and it will help you on the next paragraph, but then you're probably ignoring the signals of your idea not working and you're much more likely to get to the bottom and finish the essay or whatever it is, even if your idea sucks and it didn't work." >> Yeah.
2:29:58
I've noticed >> writer's block is just this divine presence that's telling you, you don't need to make this.
2:30:03
It's not it's not it's not needed.
2:30:06
It's not needed by the world.
2:30:08
and you can force through it.
2:30:08
But what did you actually what did you actually do?
2:30:11
>> I've been writing a >> I think there's a Oh, sorry. >> Oh, sorry.
2:30:14
I was going to say I think there's a similar analogy with music where I've heard from many musicians, I am not one of them, of course, that their best songs were the easiest to write and like the tune, the lyrics just flowed right out.
2:30:24
And if they are struggling to figure this out, figure out the tune, figure out the lyrics, it's probably because the song's not working. It's usually the same. >> Yeah.
2:30:32
I've been writing a daily newsletter for this and to prep the show about 500 words and uh I've noticed that I haven't been using AI for anything other than knowledge retrieval.
2:30:41
If I have to look up what what's the market cap of this company, of course I go to chatbt and then I also noticed that uh a lot of times I'm kind of just reiterating like a discussion that I had with Jordy earlier in the morning.
2:30:51
And so I'll use dictation sometimes to just get some of the words down and then I'll kind of write from there.
2:30:58
But I'm never crafting a prompt for what I'm writing, which I think is just interesting because the models have gotten so much better and yet there's still something about like I got to come up with the own idea or like the seed of the debate. >> Yeah. >> What do you think? >> Yeah.
2:31:10
It's also very difficult to really make it right in your voice.
2:31:12
So you can prompt it and say write it like Jordy like do it exactly, but it's not it's just it's it hasn't hasn't gotten there yet.
2:31:20
I feel super grateful that it's still easy to clock uh AI generated text because if I'm scrolling on social media, maybe I see a post and then I'm in the comments like interested to see what other people think about it and I can just easily clock.
2:31:34
Okay, AI generated, I'm just going to skip it because it's probably just like summarizing it and asking a question, but uh I I worry we'll lose that ability to filter like in the next iteration of the models.
2:31:46
It's definitely made me a sloppier writer and I'm I'm I'm like deliberately not trying to craft the perfect sentence structure constantly because I feel like the like the rigidity is just an extra layer that I impose on myself and if I take that away it just kind of feels more stream of consciousness and is just actually a better product. I don't know. >> Shifting gears. >> Yeah. Yeah. >> Sorry. >> Go ahead.
2:32:11
>> I was going to say shifting gears to the book. >> Yeah. Yeah.
2:32:14
thesis and >> do you think uh well maybe a kickoff question do you think tech has figured out how to spend money because there was always this there's always this critique that uh tech people don't know how to
2:32:26
spend money and I think part of that was the >> the tech uniform was not maybe like the east you know the west coast tech uniform jeans and a t-shirt and sneakers people sort of came you know participated in this industry in a very sort of plain way. >> Pattygonia jacket's like 200 bucks.
2:32:44
>> Pattygonia jacket's like 200 bucks.
2:32:46
Okay, >> it's reasonable.
2:32:48
>> Well, let's let's compare tech spenders to Wall Street spenders.
2:32:50
The major difference is most tech wealth is not liquid and Wall Street was paid in cash every year.
2:32:56
So, so I mean that's that that that's the that's one of the biggest like tech wealth is a lot of paper wealth relative to Wall Street wealth.
2:33:02
That was so much more liquid.
2:33:03
You can go buy the Rolex, you go buy the house in the Hamptons cash.
2:33:04
And so I think that that was that was that was probably that was probably part of it.
2:33:09
But yeah, there's a culture of like buying the the the watch based on the, you know, a banker buying deciding what watch to buy based on the size of their Q4 bonus, right?
2:33:18
Just like it's going to be some percentage of that.
2:33:21
So, the watch I get will, you know, maybe it'll be a Submariner, maybe it'll be the Daytona. I don't know yet. >> Yeah.
2:33:28
I I do think there's something to be said that on Wall Street, your value and your success was was how much money you made.
2:33:33
And in tech, it is much closer to towards the product that you built and the intelligence that you have and whatnot.
2:33:39
And and so there is less desire to show off wealth in tech because that's not what people get valued for.
2:33:46
And I I can't think of hardly anyone in Wall Street outside of maybe Warren Buffett who is very well respected and admired and wears a t-shirt and lives in a modest house. It doesn't happen.
2:33:56
But you can but but you can name a hundred of those people in tech who do that because they're valued for their ideas, not just their annual bonus.
2:34:04
>> On that illquidity question, uh Paul Graham had a take recently that a lot of uh a lot of tech people, they're locked up and then by the time they can afford art, they struggle to like get up to speed on the art world or something.
2:34:17
Does that resonate with you at all?
2:34:17
Just the fact that if you come on Wall Street and you can afford like the the Rolex and then the AP and then the FPJO eventually, like it just ladders you up the luxury ladder easier than just having all this money and being like, well, do I really want to jump to the top of this luxury ladder that just put the hydonic treadmill on 15 miles an hour on the first run?
2:34:40
>> Yeah, I think it's very difficult for people to know what they want.
2:34:41
They're very good at knowing what they need and they're very good at knowing what they don't want.
2:34:45
Knowing what you want is actually very difficult.
2:34:47
And and part of the reason is because what I want might be totally different from what you want.
2:34:52
People have completely different needs and whatnot.
2:34:53
I think if you are thrust into wealth very quickly.
2:34:55
Um there is a there is knee-jerk reactions of what you think you should want. I want a mansion. I want a fast car. I want art. I want the plane.
2:35:02
Whatever it might be, >> and sometimes it's true and sometimes it's it's very not.
2:35:06
And I think if you I think if if I can predict all of your spending habits based off of your income, there's a very good chance that you're not doing it right.
2:35:13
Because there's a very good chance that you are just buying and spending your money in the way that that society told you to do.
2:35:19
If you earn this much money and your net worth is this, you should have this house and this car and this art and travel this way and whatever it might be.
2:35:25
And and most of the time it just doesn't work that way.
2:35:27
People have very unique spending preferences.
2:35:29
The people who I've seen, the wealthy people who I've seen who've done the best have a lot of really extreme quirks in their spending where they spend, they're very wealthy, but they spend no money on on cars or no money on travel, no money on food, whatever.
2:35:42
it it's very unique to them, whatever it might be.
2:35:44
Uh you're I'm I'm not a wine person in in the slightest.
2:35:48
I'm not I'm not even necessarily a travel person, but a lot of people would be the exact opposite, and that's fine.
2:35:53
So, I think it takes a lot of looking in the mirror, so to speak, to figure out who you are and to go down the path of trying to figure out what you want, which is not easy.
2:36:02
I I feel on a personal level that my relationship with money has been very distorted because the business that I started building in college ended up you know has cash flowed every month for my entire adult life which has been a tremendous benefit but it's also
2:36:21
completely uh it's just distorted the way that while in tech the primary way you generate wealth is you get a measly salary for a long time and then you get a whole lot of money at once or maybe you sell some secondary along the way and get some liquidity. But it's been
2:36:36
But it's been this weird dynamic where it's like I remember >> well so so the first time I took a meaningful profit share from from my company.
2:36:47
I bought a 9 I took the entire amount and I bought a 911 because I was just like well I'm going to get the same amount next month and then I'm going to have this 911 for a long time.
2:36:54
And so I had to kind of like I it's taken it took me a few years to kind of like >> learn >> such a fascinating psychology >> learn that uh lesson whereas I I I wouldn't think like oh that's a lot of money.
2:37:09
I would just think of money in increments of basically months of cash flow basically.
2:37:15
>> I think I think there's there's good mental accounting there of like rather than thinking about the 911 costing 120 grand you think of it as one month.
2:37:20
It cost me one month or something like that.
2:37:23
I think that's that's actually a smart way to do it.
2:37:25
And and even even I I value a month even more now.
2:37:28
Even though monthly income has like increased throughout my adult life because like I'm like a month as a kid you're like I got all the time in the world.
2:37:35
Now I'm turning 30 at the end of this year.
2:37:37
I'm like oh time is a real thing. It goes by.
2:37:39
You don't it's not you don't have a infinite supply. >> Do people come?
2:37:44
>> How do you how do you think that makes me feel when you say time's time's like running out because you're turning 30?
2:37:49
How how does it make everybody else feel?
2:37:51
>> I would I would kill almost 30 years.
2:37:53
Well, are you are you uh are you are you spending a lot of money on your health because you looked younger than the last time you came on the show?
2:38:00
>> May maybe I just hadn't showered last time I was on on on on the show. I don't know.
2:38:04
But um no, I I I I do think there's there there is a real thing where there it's a fine balance between spend for today, live for today, and save for tomorrow.
2:38:13
Both of them are really great ideas, and it's never as simple as yolo or or you know, save and and and and save for the future.
2:38:20
It always just comes down to what are you going to regret?
2:38:23
What are you most likely to regret at some point in your future?
2:38:27
And and it it goes both ways for people.
2:38:30
You could easily imagine looking at yourself 20 years from now and regretting the trips you didn't take, the 911 you didn't buy, the house you didn't buy.
2:38:37
You can so easily imagine too looking back at some point in your life when you're tired and your career is not working out, whatever it might be, and saying, "I am so grateful that I saved the way that I did.
2:38:46
It gave me a sense of independence that I value more than anything right now."
2:38:50
What are your take on the Oh, sorry.
2:38:54
>> You you said you said a lot of a lot of uh successful people have, you know, quirks in their spending.
2:38:58
Do you I imagine you understand your own at this point? >> Yeah.
2:39:02
I mean, this is this is a trivial and small thing, but I love this heristic by Rob Henderson.
2:39:06
He's a great uh great academic.
2:39:08
And he says uh rich people food looks better than it tastes and poor people food tastes better than it looks.
2:39:14
And on that spectrum, I love I love cheap food. I love Taco Bell.
2:39:18
I love I love Jimmy John's.
2:39:20
I can't get enough of it.
2:39:23
And I've had I've had some very expensive meals, whatnot.
2:39:27
>> And I I I have enjoyed them marginally at best.
2:39:30
The best meals I've ever had tend to cost the cheapest.
2:39:32
And so that it's it's such a trivial thing, but never would I want to be like, "Oh, I can afford to eat this way, so let me abandon all the food that I love and go eat some food that is subpar because I'm supposed to like this stuff better when I don't." >> Yeah.
2:39:45
Did you uh did you cover private aviation at all in the book?
2:39:48
We had a funny conversation with a friend this morning.
2:39:51
He basically said, "I'm my house is going to be paid off by the end of this year, and after that, I'm giving all my money to netjets."
2:40:00
>> He's not getting a second. I love it.
2:40:02
>> Which is a quirk in itself.
2:40:04
>> He finds uh commercial aviation to be very dehumanizing. Yeah, man.
2:40:09
>> I would I would if if you had a choice between two houses and commercial or one house and net jets a thousand times out of a thousand, I would do the latter. >> Yeah, >> absolutely. >> Totally agree.
2:40:18
>> Two houses are a giant pain in the ass anyways.
2:40:20
>> But I I to answer your question, I do cover private aviation in that because I made this this observation that like having a a a a private plane is like the ultimate luxury.
2:40:29
If you talk to wealthy people, they're like that's the only thing that you get pleasure out.
2:40:32
That the house, the yacht, the car doesn't do you much.
2:40:35
the plane will change your life forever.
2:40:36
And I think part of the reason we love it so much >> is because the vast majority of people in that situation remember what it was like to fly commercial.
2:40:43
Now, here's the the observation is nobody thinks it is an ultimate luxury to have a private car, >> but virtually all of us do.
2:40:51
And the reason we don't think about it is because we've always had private cars.
2:40:55
And so there's nothing to compare it against.
2:40:57
Now, you you could imagine that if you spent your entire life on a train, on a public train or a public bus, and then you got a quote unquote private car, it would feel like the ultimate luxury, but we have nothing to compare it to.
2:41:07
Another example, so much of their lure. >> Yeah.
2:41:10
If you're if if if you uh if someone's lucky enough to be born into a family that uh only flies private, can you imagine their experience of flying?
2:41:20
They're like, "Ah, I don't want to fly.
2:41:21
It's going to uh you you can imagine they don't even have a positive feeling associated with flying private because it's all they know cuz if you actually you know it's like okay I'm going to be up in the air and like the bathroom's small and I don't have that much access there's not that much there's some food but it's not my my favorite food.
2:41:37
>> I can't get Taco Bell delivered. >> Yeah. Exactly. >> Exactly right. Right.
2:41:40
Uh, do you think people Oh, I I I want to hear your reaction to Jord's take that uh buying physical things is actually an experience dichotomy between I just want to spend money on experiences.
2:41:56
So, I uh growing up as a kid, I always I always loved brands and I would get obsessed with different things, whether it was mountain biking or snowboarding or surfing or anything.
2:42:06
And I would get uh fixated and obsessed with like a certain kind of surfboard, right?
2:42:13
As a kid, I wanted to surf Mayhems, but I couldn't really afford them.
2:42:17
They were super expensive, and I worked at a surf shop.
2:42:21
I could get these other boards for a lot cheaper, so I'd always get them.
2:42:24
Now, as an adult, I only surf mayhem.
2:42:26
Um, and I always, we grew up in this era, our generation was told constantly, don't spend money on things, spend money on experiences.
2:42:35
I never understood that because in my view, I was like, when I put on a jacket that I love and it's a thing and I wear it for the day, it's an incredible experience.
2:42:46
Or if I take this surfboard that's incredible and I go out surfing with it, that's an experience in itself.
2:42:52
So, what do you what what what's the verdict on things?
2:42:55
Can things make you happy?
2:42:57
I've found that things have uh have and continue to make me happy in my life. >> Yeah, totally.
2:43:03
Because I think I think what you broke down there is if nobody were watching and nobody could see your surfboard, nobody could see your car, you would still buy them.
2:43:10
And therefore, you're doing it for something that actually makes you happy rather than trying to signal for the attention of strangers.
2:43:15
If you use like a fancy sports car for example, there are some people who own Ferraris because they love the artistic engineering of it. They love the line.
2:43:23
They love the beauty of it. They love the growl. They love the engine.
2:43:27
They work on it themselves. They wax it themselves.
2:43:28
They love the art of owning it.
2:43:30
They love the acceleration. They love driving it. That's one group.
2:43:33
Another group just wants to get the attention of strangers and they just rip it down the road just trying to turn as many heads as they can.
2:43:39
Yeah, >> the former is going to get way more happiness out of it than anyone else because they would still do it if nobody was watching.
2:43:46
I think that's the the framework is like if if nobody was watching how you lived, what would you spend your money on?
2:43:52
And as you just described it, I know you would still buy that surfboard.
2:43:55
And so it's it's it's the right thing to do.
2:43:57
I think the uh stuff versus experience tends to go astray, too, because particularly in the social media world, a lot of experiences that we want to spend money on are literally just to impress other people.
2:44:09
It's where should we go on summer vacation that's going to generate the best Instagram pick.
2:44:12
>> This is this is John's on Europe.
2:44:12
He's like, I don't need to go to Europe. We have lakes here. We have oceans here. We have mountains here.
2:44:18
Why why would I why would I leave the the great uh United States?
2:44:23
>> You know what my example of this is? Bali.
2:44:25
I don't know if you've ever been to Bali. It's a dump. It is a Thank you. Thank you.
2:44:30
I did my my my wife and I took our honeymoon to Bali and uh it's a dump.
2:44:35
So, so I went there on a on a on on multiple surf trips >> and I I only cared about the waves, but the funny thing is people go out there on surf trips and like the actual best surfing in Indonesia is really not in Bali.
2:44:50
There's a handful of solid waves.
2:44:53
The downside is there's actual trash in the water.
2:44:55
You are just swimming in this like supposed like idllic reef break and you're just swimming through plastic bags.
2:45:01
It's just absolutely disgusting on a half the island and the water's just like brown and dirty.
2:45:07
>> And people surf in America, too. >> Yeah.
2:45:09
And it's like, you want Do you want to say that?
2:45:10
You want to take the picture and say, "I'm I look Look at me.
2:45:14
I'm in Bali in my trash." >> I think that's it.
2:45:16
I think that's No, I think I think Bali becomes a popular tourist destination because people love to say, "I went to Bali."
2:45:21
And post that on social media.
2:45:22
The whole time I was there, my wife and I kept saying we could have flown to Maui, which is a 5-h hour flight.
2:45:27
Instead, we flew 20 hours to Bali. Yeah. And it's 97% worse. >> Yeah.
2:45:32
>> And like, why would it?
2:45:32
But I I I think honestly, we were attracted to it back in the day before we knew better because it sounded like a cool thing to do.
2:45:39
Like, oh, we get to tell our friends we're going to Bali.
2:45:40
We didn't know anything else other than it was a cool It sounded like I don't want to I don't want to I don't want to uh uh say too dump too hard on on Bali.
2:45:48
Part of why it's not as great as the hype is that there's too many people there.
2:45:57
I sort of like created the problem.
2:45:57
I think it is, you know, probably is as nice as Maui just just uh physically, but the challenge is again the infrastructure, the the traffic is uh number of times I've almost died on a scooter in Bali, too.
2:46:12
I'm surp I'm surprised I'm here on this podcast.
2:46:15
>> Safety is real, >> right?
2:46:16
And so then it's like if if nobody could if nobody got to hear where you're going on vacation, you can't post it and you can't tell anyone else.
2:46:23
>> Never would I want to go to Ma to Maui.
2:46:25
I'd be like, "Ah, let's just go to Santa Barbara or let's go to Maui or something like that."
2:46:28
It's so much better and easier. >> Yeah, that's funny.
2:46:30
Uh, I want to talk about like the the I mean, maybe the frame is like do people ask you more questions about or how do you see the job to be done by the book?
2:46:39
Is it more about how to is it more about money or just happiness?
2:46:46
>> It's definitely more about happiness.
2:46:47
And one of the big points in the book is there is no formula for how to do this.
2:46:51
And so that's why when you have a formula like spend money on experiences, not stuff, it tends not to work because I'm different than you are.
2:46:56
And and people from different generations, different countries, different backgrounds, totally want different things.
2:47:01
And I think it is immature to say that because I like spending my money on this, you should too.
2:47:06
Or because I don't value this, you shouldn't either. It's not.
2:47:10
But it's it's an innocent mistake to make.
2:47:11
And a lot of people make it in finance.
2:47:13
the assumption that there is a right answer to earning, saving, spending, investing when like it's a very individualistic endeavor.
2:47:22
And so a lot of this when the the the question you ask like do people ask me for advice on this?
2:47:26
The advice I have and people don't like to hear this is like you need to figure it out for yourself.
2:47:31
And so the book is about the psychology of envy and contentment and social aspiration which tend to be universal.
2:47:38
But there's nothing in this book that says you should spend your money like this.
2:47:41
And so it's not called the science of spending money because I don't think that exists at all. >> Yeah.
2:47:47
>> Uh what about uh what do you what kind of uh things that you can spend money on have the worst value?
2:47:52
Because when I talk about uh when when you look at uh luxuries like maybe staying at an Aman property man is maybe 10 times as expensive as like the average four seasons, but I think it's >> it's probably like five times better in my opinion. Um >> Yeah.
2:48:11
So, so it's not it's not it's not per like a perfect trade, but but it it's at least if you only have a limited amount of vacation time a year and you want to have the best possible experience, I think it's a it's a trade worth take, you know, a trade worth making.
2:48:24
But where where do you think um maybe is on the opposite side of that?
2:48:28
Things that are 10 times uh do you think it do you think it's you you mentioned food. Is there anything else?
2:48:35
I >> I'll tell you one like little spending quirk that I have.
2:48:37
This is slightly off topic, but I think it's when when when I grew up, I I was a I was a a ski racer, and I always felt that everyone else on my team had better gear than I did.
2:48:47
>> They had they had they had nicer skis, they had a nicer jacket, they had they had all of that. And it drove me crazy.
2:48:52
And so when my son, he's nine now, when he started skiing, to kind of make up for the the hole in my soul that I had when I was a kid, I was like, I'm going to buy you the best of everything.
2:49:02
You're going to get you're going to get the nicest skis, the nicest everything.
2:49:05
And the the quirk is he could care less.
2:49:07
He could not care less about any of that about having the nicest stuff.
2:49:10
And so that too was like a realization of like that would have meant more to me than anything that I could have ever had.
2:49:16
And he could not care less because everyone has their little spending quirks about them. >> Totally.
2:49:23
>> Last question from me. I obviously we're here.
2:49:26
I want to celebrate the book.
2:49:26
I want to promote this book, but I'd love to know about another book that you think uh serves as uh just something you enjoy, something that you an author that you respect, maybe someone from the 20th century or 21st century author, uh someone who you've pulled influence from or just have respect or just a book that you keep coming back to. >> Yeah.
2:49:50
I mean, two non-fiction authors that I think are the greatest of modern times, they're both still living, still writing.
2:49:56
One is Eric Larson and the other is is Robert Kersonen.
2:49:57
Uh they've they've both written some very famous books and some very successful books and I think their ability to craft a sentence and tell a story is unparalleled.
2:50:07
And even if I were to compare them of all the writers of the last 200 years or so, I'd put them near the top there.
2:50:13
It's just so it's effortless to read their their work.
2:50:17
Never do you have to reread a paragraph and say, "What are you trying to say here?"
2:50:20
You can just kind of glaze your eyes over the page and completely understand what they're saying.
2:50:23
And what I love about what Eric Larson in particular does, so he's a non-fiction writer, writes books about like World War II and all these these these different events.
2:50:31
Some of his chapters are half a page.
2:50:33
And so some of his books can have 200 chapters.
2:50:35
They're each a page or two because he's so good at just being like, "Here's my point.
2:50:41
I'm going to make the point, use an example, and boom, I'm done.
2:50:42
I don't need to ramble for another 17 pages.
2:50:44
I'm just going to move on."
2:50:46
And that to me is the key of good writing.
2:50:47
It's like the person who can say the most in the fewest words wins, and he's the best at that. >> Yeah.
2:50:53
Yeah, I read Devil in the White City a while, maybe a decade ago. Uh, fantastic book. >> Loved it.
2:50:58
And and perfect example of that.
2:51:01
Thank you so much for coming on the show. So fun. Always a great time.
2:51:03
>> Let's do it again soon.
2:51:03
We're going to this time we're just going to send a recurring slot the calendar.
2:51:06
You can move it if you want.
2:51:08
Uh, but uh we love we love talking. It's always fun.
2:51:11
Hit the hit the gong again for being number one uh in the business uh section on Amazon.
2:51:19
>> Uh business decisionmaking. See you at number one.
2:51:21
and I'm sure uh many other uh charts uh to come. >> Thanks. >> Congratulations. >> Fun as always. >> We'll talk soon. Great to see you.
2:51:29
>> Before our next guest joins, let me tell you about Adio.
2:51:31
Customer relationship magic.
2:51:32
Adio is the AI native CRM that builds, scales, and grows your company to the next level.
2:51:35
CRM started for free, >> super intelligence.
2:51:39
>> And we have another gongworthy guest.
2:51:42
Let's bring in Misha from >> Reflection. How are you doing? >> Boom.
2:51:47
>> Hey guys, good to see you again.
2:51:48
>> Good to see you again. >> Good to see you.
2:51:49
You've been uh busy raising billions.
2:51:53
>> Jordy has this habit of telling people when they come on and they do a great interview, we'll see you soon. But you delivered.
2:51:58
I think you're the first person that roll the tape.
2:52:00
Jordy probably said we'll see you back.
2:52:03
>> We got to we got to roll it back.
2:52:03
I bet I said you called it.
2:52:06
>> Knowing knowing the progress you've made and the progress you will will make.
2:52:08
I bet you'll be back on here with more news.
2:52:12
>> But quickly give us a reintroduction to the company and of course give us the news.
2:52:18
Uh a quick reintroduction to the company. Uh I'm Misha.
2:52:20
I'm the co-founder and CEO of Reflection together with Giannis.
2:52:24
Uh we started the company about a year and a half ago and uh we were formerly at DeepMind.
2:52:29
Giannis was uh one of the founding engineers at DeepMind.
2:52:33
Uh contributed to a lot of projects uh like AlphaGo and Gemini and recruited a team of about 60 I would say uh researchers and engineers from Frontier Labs.
2:52:43
uh and the charter of the company um has opened up since we last spoke.
2:52:50
We are we've raised this capital to really build out the frontier open intelligence um based in America and export it to the rest of the world.
2:53:01
>> So before we get >> that is kind of the focus of the company. >> Yeah.
2:53:03
Before we get into the details, how much did you raise and who did you raise it from?
2:53:09
Uh we raised uh in total of uh $2 billion from a syndicate of investors.
2:53:15
Uh oh, this this has a gong hit from a syndicate investor. Let's go. >> Everyone's excited.
2:53:23
>> Give it up for disruptive >> um DST 17 B Capital a bunch of uh existing investors as well like Lightseed Sequoia and CRV and so forth.
2:53:35
So it was quite um you know we're we're very grateful for the support from uh the syndicate. >> Okay.
2:53:40
Get uh get uh even more kind of granular with what the focus is today.
2:53:43
I my read on it is open source is the focus is that >> putting deepsee out of business.
2:53:51
That's what I want to hear >> finally. >> That's right.
2:53:54
Uh yeah maybe the short of it is that uh right it's US deepseek. >> Yes. >> That's what we want. Thank you. >> Yeah.
2:54:01
Frontier open weight models uh >> that we train here. Yes.
2:54:04
In America and export uh to the rest of the world.
2:54:07
So this is meant to be a global technology.
2:54:11
We have a big presence in the UK. We have a team there.
2:54:13
And so this is not just you know even though it's American built, it's really built for the world uh more broadly.
2:54:20
>> Can you share anything that you think you'll be able to uh do to outf fox deepseeek and GPTOSS?
2:54:25
deepseeek and GPTOSS? We're having Dylan Patel from semi analysis come on next and he's talking about uh inference max he's benchmarking and I learned so much that you know it's not just the model it's how you run it the batching the the the the different GPUs sometimes Nvidia is better sometimes AMD is better like
2:54:43
how are you understanding because I imagine it's not enough to just say it's American deep it's got to be better so what's your plan to actually beat them >> it's a really good question and I think it actually falls in two parts um First, actually just having an American compliant uh deepseek would go a really long way. Yeah. Yeah.
2:55:02
>> Because a lot of enterprises are basically locked out from using those models because um of various uh legal marketing provenence data provenence risks that are associated with uh Chinese models.
2:55:13
So uh from a commercial standpoint, just having something that is as good but kind of compliant um and built here uh would be really powerful.
2:55:23
Uh but of course there is um you know an aspect that you want to uh leaprog and really be the leader in open intelligence across the world and we do have some tricks up our up our sleeve.
2:55:35
Um obviously a lot of >> we can't share them yet but I mean hopefully eventually they'll be out. Yeah. >> Yeah. Yeah.
2:55:42
But you know we have um some great work happening on reinforcement learning within the team.
2:55:46
Um the other thing that you know the Chinese labs don't have access to is obviously uh the same level of chips that American companies have access to.
2:55:54
And so what I think Deepseek did really well is co-designing their algorithms together with the chips they had access to.
2:56:02
>> And so there's some really interesting stuff that you can do with co-designing algorithms with Frontier chips that are going to be accessible to us as well. >> Interesting.
2:56:10
Um quickly talk about the business model.
2:56:13
I could imagine this turning into sort of like a Red Hat Linux play where uh there's an open source model but you're implementing it working with enterprise working with the government and there's a contracting piece a SAS layer on top.
2:56:24
Is that logical or or are you thinking more like you you nail open source and then you can do a closed source model sell API you could go and own the whole token factory the inference stack like where do you see the business looking in a couple years?
2:56:42
Um I think that uh the primary thing you need to set first is um how do you build the kind of open intelligence open models and the sets of tools around them for um you know you partner with some inference providers you uh you know set up um you know make it easy to customize things you make it easy to build agents out of these models and um ensure that that kind of spreads like wildfire.
2:57:06
So I think that having an open some sets of open models that are really fully permissive is really important.
2:57:12
Um but the pull from a from you know for this kind of model really comes from large enterprise.
2:57:20
Uh that's when does it you know make sense for you to move from closed to hybrid to open models.
2:57:23
Um, it's really once you're a very big consumer of intelligence and that's basically large enterprise sovereign and scaled up startups that are spending crazy amounts of money on closed APIs. >> Yeah.
2:57:38
>> And so the way you kind of commercialize it, yeah, you want you want them to be building on top of your models and there's all sorts of services and products that you can uh build out on top of it to effectively solve their problems end to end because just providing an openw rate model uh is not enough.
2:57:55
These things are very hard to customize.
2:57:56
These things are very hard to build evaluations around.
2:57:58
They're very hard to do anything useful with if you don't help a customer end to end.
2:58:02
So I think that there's a lot of opportunity for commercialization, but you really need to be the core intelligence that others are building on before you can really um be useful at the next layer as well.
2:58:18
uh why uh why do you think the dialogue around open-source open AI models went from you know up to a fever pitch people demanding it then they release it and then now uh you don't hear it talked about really uh at least online in the timeline much at all >> clearly clearly and and and and I would
2:58:42
say like what what I'm trying to understand is like clearly there's massive demand for open source models But I have a feeling that developers would like to be leveraging uh the technology of a company like Reflection who's dedicated to open source and and and dedicated to commit, you know, and and really committed to it. Whereas it's
2:59:03
Whereas it's hard to, you know, we we had Sam on today.
2:59:08
We've had a bunch of people on from OpenAI. It's hard.
2:59:10
It It'd be hard for anyone at OpenAI to say like open source is our top three priority, right?
2:59:18
Uh maybe it's in the top five. >> Exactly. Exactly.
2:59:22
It's it's really hard for you to both be the world's open model and open intelligence provider and it for for it to be the number two, number three or number five thing, right, that your company is focused on.
2:59:32
And the reason is that what what matters is capability.
2:59:38
You want highly capable open models and the only way to get that is if your commercial incentives are fully aligned with open intelligence as the first and primary thing that you're doing.
2:59:49
>> Um now when you release something like this you can't just release the model.
2:59:52
I mean I think that that's one part of it and then you know inference providers can take that model and optimize their stack around it.
3:00:00
But these models are so big and hard to do anything with unless you are an expert that you really need to help with that as well.
3:00:09
>> Uh the models seem to be exhibiting spiky intelligence.
3:00:12
Where are open-source models particularly best or demanded to be best like the the customers of open of of open models what do they want to do that uh might not be as relevant in a closed source ecosystem?
3:00:29
closed source ecosystem? I could imagine that agentic payments is maybe not the hottest thing in open source models or or IMO level math that might be maybe that's really important in open source but what what is unique about the customer of the open source model what do they want it to be best at
3:00:47
>> yeah there are basically two things that as customer uh you are looking at looking to do and achieve when you when you adopt an open model um the first thing is suppose you have good performance on something >> from a closed model but it's ludicrously expensive which is very common then you
3:01:05
want to drive down right the cost while keeping the performance so you want to customize the model for those tasks uh the other way around is that yeah you have some finicky data distribution that was not represented when the closed model was trained and the closed model is spiky but not on the data that you
3:01:22
need it to be good at and so then you want to drive performance on that and so then you want to post train and customize for that so it's really you're customizing for driving extra performance or you're customizing for driving down the cost, but it's really important to have control over both. >> Yeah, that makes a ton of sense. Uh
3:01:36
>> Yeah, that makes a ton of sense.
3:01:36
Uh well, thank you so much for coming on the show.
3:01:39
Congratulations on the huge raise.
3:01:41
I'm sure we'll see you back here in a couple months.
3:01:43
>> Yeah, I I uh I'm so curious.
3:01:43
I I imagine you guys are thinking about >> uh how you can create your own Deep Seek moment.
3:01:51
So, uh looking forward to it.
3:01:54
When the time is right, come back on. We'll pump it. >> Looking forward.
3:01:57
>> Play that eagle sound. Thank you.
3:01:59
Have a great rest of your day.
3:02:01
>> Thank you so much for having me. >> Of course.
3:02:02
>> Great to great to catch up. >> Talk to you soon. >> Congrats to the team.
3:02:05
>> How did you sleep last night? I woke up way too early. I woke up at I woke up.
3:02:10
>> I'm physically unable of a 38. >> Oh no. This is so bad. >> I have not gone.
3:02:14
You're >> You're still back to back with with a 90. >> What you got? >> I got a 79. >> I got a 69. You beat me. >> There we go.
3:02:23
>> You've beat me almost every day this week or maybe the last two or three.
3:02:24
I got I got >> So you got your three Pete. You got your three Pete. >> Got cocky.
3:02:29
>> So play play some side effects. Do something.
3:02:31
Let me also tell you about public.
3:02:32
com investing for those that take it seriously.
3:02:34
They got multiasset investing industry leading yields and they're trusted by millions.
3:02:38
>> Please take seriously. >> Did you see that?
3:02:41
>> Uh marginal revolution is calling for Vitalic Buterine, the co-founder of Ethereum to win the Nobel Prize in economics. >> Really?
3:02:48
>> I think that'd be very very cool. It's a wild card.
3:02:50
Tyler Cowan's mentioned it a few times that Vitalik would be kind of the outside the box pick.
3:02:54
But in terms of advancing economic theory, designing Ethereum, I mean, it's it'd be remarkable.
3:03:00
Uh, and uh, and he also advocates for Robin Hansen, the father of prediction markets to win the Nobel Prize. I don't know. We'll see.
3:03:08
Um, it'll be it'll be fun to track the Super Bowl for economics grads, I guess.
3:03:12
Um, I want your take on this.
3:03:15
Luke Kawa is quoting the Pepsi CEO.
3:03:17
I think fiber will be the next protein.
3:03:20
Consumers are starting to understand that fiber is a benefit that they need.
3:03:24
Uh we we we put creatine in everything.
3:03:27
We put protein in everything.
3:03:29
Is fiber the next thing >> caffeine and everything?
3:03:33
>> I mean you why not just add them in?
3:03:34
>> So the thing here is that uh fiber gummies. Is that a thing?
3:03:37
>> Lollipop already like leaned heavily into >> Okay.
3:03:41
So it might already be happening and maybe the Pepsi CEO is a little behind the times game.
3:03:44
He might also be Did Pepsi buy Lollipop's competitor? I don't know.
3:03:49
I mean, Kyler Scandlin in the in the reply says, "Didn't we already do this with the rise and fall of Fiber One?" Um, so I don't know.
3:03:56
Maybe maybe it's too late. >> Pepsi Co. acquired Poppy.
3:03:57
I think Poppy includes fiber. >> Yes.
3:04:01
Oh, I have a reaction for you want to keep you want to keep going on that. You have anything else? >> No. Okay.
3:04:08
>> Um, I have a reaction to Rune who put us in the truth zone.
3:04:10
So, on a previous show, we said that we said incorrectly that during the Alph Go game between Lisa Doll and and DeepMind, um, Alph Go dropped the 37th move, move 37, that iconic moment that kind of scrambled Lisa Doll's, uh, brain.
3:04:27
Uh, we told the story such that move 37 happened.
3:04:31
Lisa Doll was so racked by it that he stepped outside to smoke a cigarette.
3:04:39
Apparently, that's not true.
3:04:39
Apparently, he smoked a cigarette before move 37.
3:04:43
And so, it's just more cinematic to tell it that way.
3:04:45
I think it's uh I think it's actually maybe even more dramatic because potentially move 37 was so crazy that he couldn't even bring himself to smoke a cigarette.
3:04:54
You think that's what happened? >> Maybe. >> No, I don't know.
3:04:57
But thank you, Rune, for doing the fact check.
3:04:58
Obviously, you are correct.
3:05:00
You know story more and we always appreciate the truth zone.
3:05:02
Um, well, we have our next guest, Dylan Patel from Semi analysis with some massive news.
3:05:08
Dylan, how are you doing?
3:05:10
That is a cinematic shot.
3:05:13
>> Is this AI or something? Where are we?
3:05:15
>> That's called >> This is a orura farming.
3:05:19
>> I'm literally in America, bro. >> That's amazing.
3:05:21
>> Out of the back of the truck.
3:05:23
>> You're the bald eagle. You're the bald eagle. He's not a China hawk. He's a bald eagle.
3:05:27
>> This is proof of work. You're You're out.
3:05:29
>> You're out at the cluster.
3:05:29
You're cluster maxing truck.
3:05:30
your inference maxing, your podcast maxing.
3:05:32
Thank you so much for taking the time.
3:05:35
Uh give us your breakdown quickly on uh on the launch today.
3:05:40
Inference max launch yesterday.
3:05:42
Uh I went on your Zoom call at 10:30.
3:05:45
I was laying in my bed listening to you.
3:05:47
It was very interesting, but I'd love to hear you kind of break it down first.
3:05:51
>> Wait, first Jack wants a uh can we get a sho?
3:05:54
Are you Do you have cowboy boots on or or what?
3:05:57
>> We need the full fit check. >> The full fit check. >> The full fit check. Oh, okay. >> Looking good. But cowboy boots. Cowboy boots next time. >> Okay. Anyway, sorry.
3:06:05
Uh, please give us the give us the high level.
3:06:10
>> So, I'm at a This is a fire >> uh station behind me by the way, just so you you know. Uh, but um in Tennessee.
3:06:17
Anyways, uh yesterday we launched Inference Max, which is a humongous release for us.
3:06:22
release for us. it is running it is a benchmark that's doing cost per million tokens and uh how many you know cost per uh tokens per megawatt across all major AI infrastructure AMD Nvidia all the newest GPUs um and and and on all the latest models GPT open source llama
3:06:42
deepseeek etc right and so the reason why this is so important is you know throughout the industry people are always like oh our chips are great at cost this way our chips are more efficient that way well it turns out to actually measure inference, you have, you know, a variety of different uh metrics. Like you can always just
3:06:58
Like you can always just cherrypick something, right?
3:06:59
It's some vendor saying some BS.
3:07:02
>> Y >> and so that there ends up being a cherry-picking and then it's also on some super hyper optimized software stack that's not real, right?
3:07:07
It works for that one specific cherrypicked use case. But guess what?
3:07:11
When I'm running inference at a major company, sometimes I have big requests, sometimes I have small requests, sometimes I'm outputting a ton, sometimes it's like an agentic workflow, sometimes it's this model, sometimes it's that model.
3:07:21
So, what really matters is the real software that people are running and it's on, you know, the latest drivers, the latest um open source, you know, PyTorch version, latest VLM, latest SGLAN, all these things matter because at the end of the day, software changes every day, performance changes every day, models change all the time, right?
3:07:37
and and to actually get, hey, there's trillions of dollars of infrastructure investments being made over the next few years.
3:07:43
How do you actually measure what's the best uh hardware?
3:07:48
What's the what's the most efficient hardware? What's it cost?
3:07:49
And that's that's what we're aiming to do with Inference Max.
3:07:53
And so we're supported by um Nvidia, AMD, Microsoft, OpenAI, Oracle, Corewave, Dell, Super Micro, HPE, and all sorts of vendors that I I can't remember off the top of my head.
3:08:06
>> Well, you're not making any money on this, right?
3:08:08
It's uh it's all uh open source, but there was a ton of capital that came together, a ton of people that did put up money.
3:08:14
Uh what's the scale and the scope of the project?
3:08:20
>> Yeah, so Semi analysis has multiple engineers that I'm paying full-time.
3:08:22
So I'm I'm losing like, you know, a million dollars a year on this or a bit more obviously because engineers are expensive.
3:08:28
Um but on top of that, it's it's you know, the the vendors are contributing and the cloud companies are contributing tens of millions of dollars of GPUs.
3:08:36
Um, and there's no >> congratulations.
3:08:39
That's that's fantastic news.
3:08:42
>> So, so you know the the the thing is I'm I'm not necessarily like sure how I'm going to make money on it, but I am aura farming as I am with this background, right?
3:08:49
All that matters is you know what's what what what you know how do we deploy AI efficiently across the globe and you know perhaps by aura farming in this way we'll figure out how to you know people will buy our other stuff right is the hope.
3:09:01
Um, you know, not exactly sure, but this needed to exist and there was no way for it to exist unless we did it. >> Yeah.
3:09:08
>> What's What's your life been like the last few weeks?
3:09:09
How often are billionaires calling you asking you specifically for financial advice saying, "Hey, I'm thinking of putting, you know, a billion into this one. What do you think? Should I do it?
3:09:20
Should I Do you find yourself having to push back and say like the second trillion dollars of debt to flow into this?" Yeah. >> What do you think?
3:09:31
Um, you know, the the the crazy thing over the last few weeks is that, you know, companies that you would have never expected to need debt are in the debt markets, right? You mentioned debt.
3:09:40
Um, you know, people like Meta and Oracle, you know, who three years ago you'd have been like, these are the most profitable companies on the planet.
3:09:45
Well, they're in the market for debt cuz they're they're building.
3:09:47
Um, as far as like how often are people in the DMs or calling me, you know, that's what the company does.
3:09:53
We provide services around this.
3:09:55
Uh, so, you know, I'd like to say the company and business is taking off like a rocket.
3:09:58
And so, you know, the whole point is inference max aura will increase the aura of like other people like you know uh you know doing this.
3:10:06
But I will say it's just like we've hit terminal velocity, right?
3:10:08
It feels like we're building a like like Matrioska brain.
3:10:12
Um you know like I don't I don't know what people are trying to go. >> That's great.
3:10:18
Uh what's the biggest uh debunk that's come out of the results of inference max?
3:10:22
Is there some narrative out there on the timeline or in the AI community that you feel like you've kind of you're able with this data to turn things around? >> Yeah.
3:10:33
So, I mean, there's there's tons of people like, "Oh, AMD is best. Oh, Nvidia's the best. Oh, this is better. That's better."
3:10:40
Um, it turns out like everyone's statements are sort of like, you know, there's got to be a lot more nuance to it.
3:10:45
Um, and so my favorite thing is yesterday I saw a Twitter war between two accounts with like 5,000 followers each.
3:10:52
So, these weren't like small accounts, per se, and they were going back and forth posting data from Inference Max saying, "No, you're wrong. You're cherrypicking. No, you're wrong. You're cherrypicking."
3:11:01
And it's like >> the reality is it's a little bit more complicated and they're debunking each other. >> Yeah.
3:11:07
>> Um but I think what's relevant is that, you know, Nvidia is not the only game in town.
3:11:12
Um a lot of people uh thought that they were.
3:11:14
they were. um you know between the OpenAI AMD deal uh that happened and then the results that we've shown and we've been working with AMD and Nvidia on this for many many months um it's clear OpenAI I mean Nvidia is definitely ahead right but there's certain use cases where AMD is better right if
3:11:30
you're running GPT open source uh that model's exploding in usage then hey guess what actually AMD may be a better uh hardware for on a dollar basis it's not better on a watts basis and you know those are the two things right so why maybe I'm in test is you know there's a
3:11:45
lot of watts here that we could put on AI infra um but it's it's it's a challenging sort of uh you know thing is sometimes your capital constraint sometimes your power constraint and what you should do uh maybe you do actually think you know maybe you should deploy AMD right maybe you should deploy Nvidia
3:12:02
um the default is Nvidia but actually in many cases it makes sense and the software works the open source software works it's not buggy completely it is if you're training and doing other things but if you're running inference on specific models it works uh what's the biggest risk to the overall buildout? Is it energy capacity? Is it energy capacity?
3:12:21
Like what what's what's top of mind for you uh over the next 12 to 24 months?
3:12:27
All these deals have been announced, but a lot of people are asking where is the energy going to come from once you once you start talking about, you know, gigawatt scale clusters. >> Yeah.
3:12:40
So, it's it's it's not even it's not even uh you know, like you've got all of these like dudes in suits like you, you know, in in their little cushy little offices signing these big checks of of fake money on bank accounts.
3:12:51
But the reality is is like, hey, um I can buy the GPUs.
3:12:56
I can get them made and import them from overseas.
3:12:58
I can buy uh you know like the sheet metal.
3:13:00
I can buy all these different things.
3:13:02
But you know what you can't do is there's not enough in cowboy boots in middle America um deploying and building these things, right?
3:13:11
Like it turns out electricians wages are skyrocketing, right?
3:13:15
It turns out like plumbing wages are skyrocketing because data centers need liquid cooling and and so like how I think that's the biggest risk is you know >> where is the skilled labor going to come from in in the West. >> Interesting.
3:13:26
Um because the West has not built at this scale before. >> Yeah.
3:13:30
Uh chat says that uh Regav in the chat says you're the only 10 IC.
3:13:33
So he's having fun that you're out in Tennessee.
3:13:37
Uh is there any uh is what is the long-term vision look like?
3:13:40
Is it relevant to think about adding TPU gro like like what is the shape of the of the road map?
3:13:50
Are you sharing that yet or how can or is that even relevant? >> Yeah.
3:13:55
So, Inference Max is amazing because it runs every single day on the latest software.
3:13:59
But right now, we've only got tens of millions of dollars of GPUs.
3:14:02
You know, we got we got to hit the the hundred million number to actually get everything right.
3:14:06
So, so what that means is more models are being supported and we we we've got that in the works.
3:14:11
Um we've got uh adding TPUs and tranium.
3:14:14
Um this is a real big difficult engineering effort.
3:14:15
Google and Amazon are excited.
3:14:17
Um you know, we'll see how long it takes us, but it is a difficult thing, but you know, they've got to put up the capacity.
3:14:22
We've got to get the capacity somehow.
3:14:24
um and add those those chips.
3:14:27
And then if you do that over 99% of the flops are around the world, maybe we add Huawei um maybe we add Groer Cerebrus.
3:14:35
It's really a lot of engineering is going to be required and so that's all on the road map is to add more hardware um quality.
3:14:40
It turns out there's a lot of innovations that people are doing on uh model inference beyond just quantization, right?
3:14:48
You can do 8bit or you can do four bit.
3:14:49
But let's say everyone's doing 8bit.
3:14:51
you can still do certain innovations that make to performance better but quality worse.
3:14:57
And so there's these tricks that people are implementing that you know actually >> it's it's completely unknown to people.
3:15:04
And so you know measuring quality as well is really really important.
3:15:06
um and and and you know continuing to mo run it every single day in an automated basis um and continuing to get more people pushed behind it so we can get you know TPUs, traniums, GPUs on as many models as possible um >> with quality as well measured.
3:15:24
>> Well, that's fantastic Jordy.
3:15:26
>> One more question from my side.
3:15:26
Uh it seems like the debate is heating up around depreciation schedules for GPUs.
3:15:33
Like what's your what's your framework on on that front?
3:15:35
on on that front? uh a lot you know Neocloud wants to say five to six years but maybe that's not realistic how how are you thinking about it >> so every company uh major company in the world the Googles the Microsofts Amazons etc do six years right that is the
3:15:53
industry standard um but that may also be erroneous and the reason why it may be erroneous is because the reason it's it got pushed up from you know four or three years to six years over the last decade was CPU storage um you know that sort of uh was not advancing that fast. Now
3:16:07
Now we've got AI, we've got it advancing like a rocket ship.
3:16:12
Um and it's faster than ever.
3:16:15
And so the question is you there's two points on useful life, right?
3:16:19
One is does the thing still work in six years?
3:16:21
And the other one is is it even useful to run it in 6 years, >> right?
3:16:26
And these are two very very different questions.
3:16:28
Um you know for will it still run in six years?
3:16:30
The answer is most likely, but these things are running super fast. GPUs, TPUs, etc.
3:16:36
are way less reliable than CPUs and memory.
3:16:38
So, it's a very high likelihood that may not work in 6 years.
3:16:40
Whereas CPU servers, they'll actually run like 10 years. It's fine.
3:16:44
Um, but may not, you know, GP may not last the full six years, especially the new ones that are super hot, liquid cooled, etc. Right?
3:16:50
A lot more complexity, a lot more likelihood it could break down within the six years.
3:16:55
The other side, is it economically useful?
3:16:57
Well, if Nvidia is releasing a new GPU that times as fast for 50% more money every year and a half, well then in six years you're at like 20x improvement in performance, right?
3:17:09
And it maybe only costs like three times more.
3:17:11
So, so you're like, okay, well, yes, the old GPU still, even if it still works, is it even useful or should I throw it out and in with that power, should I feed the new thing? Right?
3:17:21
Um, and so that's the big question is, you know, is it useful to keep using the newest GPU or the old GPU or should you buy the new thing?
3:17:27
You know, as Jensen says, the more you buy, the more you save, right?
3:17:31
And so maybe maybe his argument is correct, right? >> Yeah.
3:17:34
And does that present a real risk?
3:17:37
You know, a lot of people are levering up and and raising, you know, debt and and against GPUs that and and assuming that that five, sixyear useful life.
3:17:46
How how big of a risk is that is what I'm trying to understand.
3:17:53
>> Um it depends entirely on the company, right?
3:17:55
So for example, Oracle is raising debt and they're building out Stargate and all these things, right?
3:18:01
You know, they've got this $300 billion deal with OpenAI.
3:18:03
Their biggest risk is not that hey, you know, our depreciation schedule is six years and OpenAI's contracts are five years, right?
3:18:10
And they still make money if they they don't they aren't able to last a year, right?
3:18:13
Because they've got the contract with OpenAI.
3:18:16
The real challenge is where the hell is opening I going to pay $300 billion, right?
3:18:20
Um, you know, I'm a believer. I'm a believer.
3:18:22
I think you guys are believers, but a lot of people aren't.
3:18:25
Uh, for other folks, it's like, hey, I'm out here deploying GPUs.
3:18:28
I'm just putting them out there, right?
3:18:30
Hey, anyone want to rent them? Please rent them.
3:18:32
And maybe you only sign a six-month contract, maybe sign a three-year contract.
3:18:35
That's where it gets more risky because at the end of the term, I haven't paid off my GPUs.
3:18:37
I haven't paid off my debt.
3:18:40
Um, where where am I going to uh sell it? Does the price fall?
3:18:44
where does the price end up being in that after after a year?
3:18:49
>> Um, and so we saw that with Hopper GPUs, right?
3:18:51
The people who signed the long-term deals initially weren't making as much money because they were selling them at $2.
3:18:56
Whereas, you know, other people were out there like, oh yeah, six months I'll sell it to you for $3.
3:19:01
>> That was amazing money for that first 6 months.
3:19:02
And then on renewal, it's like, oh it's only $250.
3:19:04
And then on renewal, it's like, oh wait, now I'm selling it for less than $2.
3:19:06
And who knows, as Nvidia's black ball comes out, as Ruben comes out, as AMD's new chips come out, as Google starts selling TPUs, all these things keep driving down the the cost performance and how many tokens you can get per dollar and per watt.
3:19:17
So then all of a sudden, is a hopper still worth $2? Is it worth $150? Is it worth a dollar?
3:19:22
For the people that are locked into a 5-year contract, that's one thing.
3:19:26
for the people who are, you know, just yelling and don't have a long-term contract, it's very possible that, you know, the GPU works, but it's not able to produce economic value worth actually put into it. So, that's the big risk. >> That makes sense.
3:19:40
Uh, Oracle sold off earlier this week based on reporting from the information.
3:19:45
Any what was your immediate reaction to that uh piece?
3:19:50
There was a lot of push back on it. >> Yeah.
3:19:54
So they said that Oracle's margins were low.
3:19:57
Um Oracle's margins are not that low.
3:19:59
They're higher than that at that exact point in time.
3:20:00
Their reporting is accurate, right?
3:20:02
Uh but that what they what they deduced based on the reporting what the numbers they saw were not accurate, right?
3:20:07
Which is that Oracle's margins are low for the deals they've signed. That's not accurate.
3:20:11
What's accurate is that Nvidia's GB 200 NVL72 has a lot of issues, right?
3:20:15
Um they're mostly being solved and and have been solved, but there are a lot of issues.
3:20:20
It's it can be unreliable because of how complicated of a of a thing it is.
3:20:24
So so much power uh liquid cooling it's got the back plane.
3:20:29
So there's a lot of difficulties with the hardware because of how complicated and how fast it is uh that are being solved solved already.
3:20:34
Um the other one is hey Oracle has to rent these massive data centers before they fill them up with GPUs.
3:20:40
So Oracle's paying all this money for these data centers for Stargate right like in Abalene Texas that aren't necessarily generating revenue yet.
3:20:46
And when your revenue goes from like this to rocket ship up because you've got Stargate, um you know what happens is you've got all this cost right before the revenue comes in, right? You've bought the GPUs.
3:20:56
Um you're trying to figure out how to make them to work, you know, because they're a little bit unreliable. You're replacing things.
3:21:01
You're building out the data center, you're renting the data center.
3:21:04
All these costs are hitting their books, right?
3:21:09
>> That doesn't necessarily mean that they can uh rent them.
3:21:11
I might get be getting kicked out. >> You're all good.
3:21:14
This has been a pleasure.
3:21:16
Uh Dylan, next time you're in Los Angeles, we'd love to have you at the TBP and Ultra Dome in studio.
3:21:19
Uh everyone's a huge fan here.
3:21:23
Congratulations and thank you so much for stopping by. >> Yeah, massive launch.
3:21:26
Excited to see how it plays out.
3:21:29
>> All right, see you folks. >> See you.
3:21:30
>> Thank you so much for having me today.
3:21:34
>> We got to get uh Dylan.
3:21:34
Uh Nick, reach out to Dylan. Get his shoe size.
3:21:37
We'll get some uh we'll get him some cowboy boots. That sounds great. Good uh use out there.
3:21:47
You got something on your mind?
3:21:48
>> There's some big news going on.
3:21:48
So So one is um about 30 minutes ago, Trump put out a truth.
3:21:52
He said 100% tariffs on China starting November 1st. >> What?
3:21:57
>> Um so since then uh I think broadly today um 250 billion has been wiped out from crypto. >> Okay.
3:22:04
>> Yeah, Bitcoin is down 5%. >> Oh no.
3:22:08
>> Yeah, >> we have to check in on our on our retail trader.
3:22:12
>> Our retail trader in resident.
3:22:12
Another white pill though. White pill.
3:22:14
Deis just said they did uh last month they did 1.
3:22:17
3 quadrillion tokens on Gemini. >> Congratulations.
3:22:25
>> That'll that'll fix the global economy. That'll fix the trade. Congratulations. >> Uh absolutely wild.
3:22:29
Um our retail trader and residence is um probably put a hole through the wall by now.
3:22:37
Uh thankfully the markets are closed for the week, but uh my portfolio on public is looking looking rough.
3:22:47
>> It's a rough day, but we're happy to see that.
3:22:50
>> Hey, it's a rough day, but Monday will probably be rougher. >> Maybe. We'll see.
3:22:53
It might might be a white suit day.
3:22:56
Everything could get resolved over the weekend. You never know.
3:22:58
>> We have to figure out uh what our bare market suits are.
3:23:01
Maybe maybe suits that are like actually look like bare kind of like fur fur suits. That would be good. Yeah.
3:23:08
Uh, you know, in Hollywood they have uh there's there's a certain synthetic tears.
3:23:13
It's like uh propyline glycol or something. I that's what in vapes. That's not it.
3:23:18
But there's some sort of uh eyropper that you can put in your eye.
3:23:22
They they put in eyes of actors when they have to cry.
3:23:24
And so maybe we should just be applying those the entire show so that we're just crying constantly.
3:23:29
Um, well, in some uh much better news, of course, if you want to get away from all the chaos, you can get you can book a wander.
3:23:37
You can find your happy place. That's right.
3:23:38
Book a wonder with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, 24/7 concier service.
3:23:42
It's a vacation home, but better.
3:23:46
>> Uh, Joey in the chat says, uh, Fartcoin is down 73%. I don't know. I don't know why. >> No, no, no. That's got to be a joke. That's impossible. >> I looked it up.
3:23:55
I mean, I'm looking at a chart right now.
3:23:57
says today and so maybe it's rallied a bit >> today.
3:24:01
>> Yeah, that I mean I guess >> I can't believe that something like a household name in tech is actually down that much. That's absolutely crazy.
3:24:09
>> Um well uh in in in some more serious news, we have a new partner at TVPN.
3:24:17
We're partnered with Gemini, uh Google AI Studio, the fastest way from prompt to production with Gemini.
3:24:25
Um, AI powered coding, ease of use. It's built for everyone.
3:24:28
You've been a power user.
3:24:31
We're friends with Logan.
3:24:31
We're very >> Logan is a dear friend of the show.
3:24:33
Uh, and works around the clock to make this.
3:24:38
>> He's done a fantastic job over there.
3:24:40
Supercharger your creativity and productivity chat to start writing, planning, learning, and more with Google AI.
3:24:46
So, you'll be hearing more about Gemini uh in the coming weeks, in the coming shows.
3:24:50
Not tomorrow because tomorrow is a Saturday, but I can't wait for Monday. John, >> uh yeah. Um what else?
3:24:57
Oh, uh Sheil had a take on Sora, which is interesting.
3:25:01
He says he personally got bored of Sora after a day, but a surprising number of my friends are still posting 10 plus videos a day.
3:25:09
Maybe this AI slot thing has legs.
3:25:11
I have been I haven't been consuming a lot of Sora.
3:25:14
I've been generating a lot, but I haven't been posting a lot.
3:25:17
I started posting and once I got over that threshold of like, yeah, I'm just going to put my came up.
3:25:22
Yep, I'm just going to post. It's going to be fun.
3:25:24
I think I'll be experimenting with the actual feed.
3:25:26
I only have 20 followers now.
3:25:28
But I think that there is some fun creative stuff that you can do there.
3:25:31
It's definitely a different tool to pull off the shelf than the video camera or the text post on on X or the email.
3:25:39
But I've been having fun and I think I will.
3:25:41
Apparently, I didn't catch this when you said it, Tyler, the 100% tariff on China is on top of all current tariffs. >> Oh, wait.
3:25:50
Wasn't it already at 100% or something like that?
3:25:52
We had Ryan Peterson on a few times and and the tariffs were like up and down and up and down to the Ultra Dome.
3:25:56
Ryan, >> seriously, we got to check in with Ryan back on.
3:26:00
Buco Capital says, "I legitimately cannot believe we are doing this again.
3:26:06
>> Tremendous nukes have hit the cryptocurrency charts," says Joey in the chat. Did you read that? Uh, it's very funny.
3:26:12
Thank you, Joey, for your service as the resident crypto bro. Um, one last note.
3:26:17
You know what hasn't changed with a tariff?
3:26:20
Out of home advertising in America, baby. Out adqu. com.
3:26:22
Out of home advertising made easy and measurable.
3:26:26
Say goodbye to the headaches of out of home advertising.
3:26:27
Only about tariffing our billboards.
3:26:31
>> Do not tariff our billboards. >> That is my notice. Yeah.
3:26:32
Single issue voter on billboards.
3:26:35
Honestly, >> um, Liquidity says there won't be a second date, but at least she now understands why the AI circlejerk deals are quickly becoming a major systemic risk.
3:26:48
>> Wait, wait, can we pull up this picture of this 8-year-old building in Kazakhstan from offsite?
3:26:51
This is This is a This post made me laugh out loud. It's page 70. Do you see this, Jordy?
3:26:57
Look at this picture of this eight-year-old building and and offsite and offsite that quote twisted and says that MF on Roblox left hand on AWSD because if you look at his hand >> it's like >> caught caught gaminghanded for sure.
3:27:15
Uh very funny post but that would have been me at 8 gaming and you know who knows if he's on Roblox now maybe he'll build a Roblox game.
3:27:24
Maybe he'll build a startup, but yes, eight years old is might be a little bit young to take a company public unless you're a 23-y old and then apparently you can spack a nuclear company. >> Be fun.
3:27:35
>> Anything else you want to cover?
3:27:35
Any other breaking news before we log off for the weekend?
3:27:39
>> No, I'm going to miss being here at this table with these mics, this team, this chat.
3:27:45
>> We missed Dave Portoiy's mansion.
3:27:45
He Dave Portoi made the mansion section in the Wall Street Journal.
3:27:49
I'll read you one line of it uh because it is iconic.
3:27:53
Dave Portoi adds record-breaking home to his $95 million property portfolio.
3:27:59
Inside the Bar Stool Sports Founders collection of luxury houses, they break down all of his different houses.
3:28:03
They're all beautiful, but uh this is what made me laugh out loud because it's printed in the Wall Street Journal in the mansion section.
3:28:09
Barstool Sports founder Dave Portoi has been dogged by champagne problems at his Miami mansion.
3:28:16
From construction delays to losing his coffee because the waterfront home is too big.
3:28:20
Last year, a more serious issue emerged.
3:28:23
And we've talked to some founders about this. Mold.
3:28:24
And he, as he often does, Portoy turned to social media.
3:28:30
Quote, "I need the best mold company in the history of Miami to come look at my moldy ass house." And he wrecks.
3:28:38
He posted on X in August of 2024.
3:28:40
I just thought that was hilarious that he uh that one of his ex posts made it into the Wall Street Journal.
3:28:44
So, you can post your way onto a private plane.
3:28:47
You can post your way onto the Wall Street Journal.
3:28:49
you can post your way on this show.
3:28:50
So, enjoy the weekend and stay locked in on the timeline.
3:28:55
>> Catrini says, "Can we change the channel?
3:28:57
I've seen this movie before." Uh >> oh.
3:29:00
>> Our retail trader just posted his portfolio.
3:29:02
He's down >> uh 12% on the day.
3:29:04
He says, "I'm so cooked." >> I'm so cooked.
3:29:09
>> You're cooked and chopped. >> Cooked and chopped.
3:29:10
But we love >> Get the Dylan Cam. Get the Dylan Cam.
3:29:14
>> No, he doesn't want to be on TV.
3:29:14
Thank you so much for tuning in.
3:29:16
We're going to set up, we're working on setting up a retail corner here at TV about it.
3:29:19
We're going to give We're going to give Dylan, not Dylan Abishcato, the other Dylan.
3:29:25
We're going to give him a public account, some funds, and he'll just he'll just trade.
3:29:30
>> This is just crazy enough to work.
3:29:32
>> He won't be cooked or chopped.
3:29:34
>> Thank you everyone for tuning in.
3:29:34
We will see you on Monday.
3:29:35
Have a great >> Have a great weekend, folks. Bye >> bye.