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[music] >> [music] [music] [music] >> Ho ho ho. >> Merry Christmas. >> You're watching TBNN.
4:58
Today's Tuesday, December 9th, 2025.
5:04
Just a few days until Christmas. We're so excited.
5:08
>> We're live from the TVP Ultra Dome, the Template [music] Technology, the Fortress of Finance, the capital capital.
5:12
Go travel until Christmas, baby.
5:14
No travel until the [music] new year.
5:16
We're in the Ultra Dome hanging out.
5:18
We're monitoring the situation.
5:20
We're monitoring the Paramount Netflix Warner Brothers situation because this is uh one of the most fascinating deals.
5:28
The deal has gone hostile.
5:28
Paramount [music] has launched a hostile bid to acquire Warner Brothers.
5:32
Uh it's an allcash offer. 77. 9 billion. Really? Really?
5:37
And it's a fun one because uh I feel like it's it's obviously tech adjacent, but it's not it's not the story that people have been monitoring all year.
5:44
We've been talking about foundation models.
5:46
That whole story has just gotten a little bit >> media.
5:50
They got tired of not getting enough attention. Exactly.
5:52
Let's spice it up a little bit. >> Let's spice it up.
5:54
Here's something new to learn about.
5:56
So, everyone's having fun.
5:57
everyone's uh learning new things and uh I could tell because when I came in today uh I had a bunch of questions uh that people were throwing at me about how all of this works.
6:06
Why are why why isn't Warner Brothers just going with the highest price?
6:11
Like when I sell a stock, I don't care if Citadel or Jane Street's buying it.
6:16
Like if I'm selling 80 bucks of stock, uh just give me the best price.
6:20
But when you're selling an$80 billion company, there are other considerations and it goes beyond just maximizing shareholder value.
6:26
And so, uh, I wanted to break down a few of those.
6:30
So, I did that in today's newsletter.
6:31
We can run through that and then we can run through some of the news. >> Perfect.
6:34
>> But first, let me tell you about RAMP. Time is money. Save both.
6:36
Easy to use corporate cards, bill payments, accounting, and a whole lot more all in one place.
6:42
one place. So um this this question you know it seems obvious the board has a fiduciary duty to maximize shareholder value that's legal requirement to take the higher offer and yet that's not what's happening like yesterday we saw
6:59
that uh that Ellison and Paramount came in with o over a hundred billion of course that included the CNN the TV assets but even when you broke it out it seemed like it was very clear that Ellison was willing to pay more money and make a higher offer. So, under what
7:10
So, under what circumstances can a board whose job it is to maximize shareholder value not take the higher offer?
7:18
They can't just it can't just be whoever we had the better dinner with, right?
7:22
Which is part of the news, of course.
7:24
Uh they they went out to dinner and uh Paramount CEO David Ellison sent a text to David Zazov, who's running Warner Brothers after they made a hostile bid today to buy Warner Brothers.
7:35
Uh, and uh, David texts the other David and says, "David," but I guess he misspelled his name even though that's his name, which is just funny.
7:45
Uh, but anyway, he says, "I appreciate you're underwater today, so I wanted to send you a quick text.
7:49
Know that despite the noise of the last 24 hours, I have nothing but respect and admiration for you and the company.
7:55
It would be the honor of a lifetime to be your partner and to work and to be the owner of these iconic assets."
8:01
He's talking about Fogghorn, Legghorn.
8:05
>> [snorts] >> He's talking about Porky Pig.
8:05
He's also talking about Batman and Superman, obviously, and Harry Potter and Lord of the Rings and a million other iconic assets, which is true.
8:11
Um, if we have the privilege to work together, you will see that my father and I are the people you had dinner with, which I I I like that. I think that's cool.
8:21
They they they had dinner.
8:22
They >> It's a fantastic text. >> Yes. Yes. Yes. It's a great one.
8:25
Um, so um, quickly, let me tell you about Julius AI, the AI data analyst that works for you.
8:32
join millions who use Julius to connect their data, ask questions and get insights in seconds.
8:38
Um, so there are two main reasons why you don't just take why why your size might not be size.
8:45
[laughter] Um, directors at a company like Warner Brothers, they have to maximize shareholder value, but maximizing shareholder value is an expected value calculation.
8:54
So, if you come in with a hundred billion dollar offer and I think there's a 75% chance that you're going to deliver that and someone else comes in with an $80 billion offer and I think there's a 100% chance that they're going to deliver that.
9:06
Well, the expected value of your bid is 75 billion.
9:08
The expected value of their bid is 80 billion.
9:11
I go with the 80 billion.
9:11
Even though it's like a lower headline number, it has a higher >> How much of the calculus do you think is just a deal that will actually get done, right?
9:21
a deal that is going to get uh >> so a deal that doesn't get done could still have value because of a breakup fee.
9:28
So you could you could you could in theory go into a deal that you know is impossible and and the example that I gave is uh what if Bite Dance came in and they were like hey you know we're 400 billion dollar media company.
9:40
We'd love to own these iconic assets.
9:43
Let's uh let's pick up Warner Brothers.
9:46
We'd love to own CNN too.
9:47
You know who knows what we'd put on the TV.
9:51
>> You already own Tik Tok.
9:52
>> We already own Tik Tok. Why not CNN also? Why not Shark Week?
9:54
You know [laughter] >> Shark Week. Not Shark Week.
9:56
they'd have to carve out Shark Week in my book.
10:00
>> Um, but obviously the government would would block that.
10:01
And we have there we have CPHAS, which is an organization in the US government that determines whether or not an international buyer can take an American company because of intellectual property, uh, all sorts of geopolitical considerations.
10:14
We don't want another country cornering a market on a really key piece of the supply chain like the Nvidia H200 for example, which we might be talking about later in the show with Aaron Gin, uh, co-founder of Hydro Host, repeat guest on the TBP show.
10:29
Um, but, uh, then there's also just the FTC.
10:32
So certain deals like the I gave you the example yesterday like Disney.
10:36
Disney would be like so blocked I think that uh that that deal doesn't even get kicked around like no one even talks about it and because it would get blocked by the FTC.
10:47
So it doesn't even happen but it would maximize shareholder value if Disney came and said yeah we'll give you a $10 billion breakup fee and we want to try and buy you for 200 billion or a trillion or 200 million.
10:59
Like you would immediately say yes because you just want the breakup fee. Yeah.
11:02
Um but having being in this turmoil and being in this limbo and not being able to sign deals with other that has an opportunity cost, right?
11:08
And so you might want to back off of that.
11:10
And so uh basically the >> Yeah.
11:13
Look, you you look back at the Figma acquisition.
11:15
Adobe paid a a billion dollar breakup fee.
11:18
So that's effectively like non-dilutive financing for Figma.
11:22
That has a happy ending because they were able to, you know, reacelerate, get out uh into the public markets.
11:29
But uh there was another situation where they went through a rough patch and actually really needed that capital >> uh to get through. >> Yeah.
11:38
So so there's so there's there's basically two buckets of risk that I think most uh most dealmakers would be considering in this situation. First is financing risk.
11:46
Uh so will the will they come through with the money and what money are they paying with?
11:53
Because the initial offer this is the history.
11:57
There's actually been six offers put forward by Paramount.
11:59
Uh David Ellison is putting on a clinic of just not taking no for an answer.
12:03
Uh because all the way back on September 14th, he offered $19 a share and 60% of that was cash. So 60% cash offer.
12:12
Then September 30th, two weeks later, he comes back $22 a share and ups the amount of cash to 66. 7%.
12:20
>> Zazlov is doing a master class in making your opponent negotiate against themselves >> 100%. It's actually crazy.
12:27
>> And so o October 3rd, 2350 a share, 80% cash.
12:30
Then November 20th, 2550 a share, 85% cash.
12:33
Then finally, December 1st, 26. 50 per share, 100% cash.
12:39
December 4th, 30 $30 a share, 100% cash.
12:43
Now, why does this matter?
12:43
Well, it's because you get locked into owning the shares of if 40% of the shares is paramount, and then while it's closing, the the stock trades down, you wind up getting less value.
12:53
And so the 80 billion today might wind up being 70 billion later and that doesn't maximize shareholder value.
12:59
And so there's also just the the just the question of like can you actually marshall the cash just like if somebody comes to you and you're about to sell your house to them and they say yeah I'm definitely going to get a loan for this.
13:10
Well that's a financing risk. Maybe they don't.
13:11
Maybe they back out of the the deal.
13:14
>> Why cash offers often times >> exactly if you can prove that you have the cash that that makes difference.
13:17
And I mean he's effectively gone and done that because he's teamed up with Jared Kushner reportedly and gone around the world got a whole bunch of different sovereign funds and just really people any anyone with big deep pockets is has has kind of you know said yes I'm I'm down to come along on this ride and put up a bunch of the capital.
13:38
>> The capital has been marshaled.
13:38
It seems like it's ready to go.
13:40
And and then also you have Larry Ellison who has three times as much money I think than the whole deal value something like that 275 billion to his name and he's only trying to put together >> not cash >> assets not cash but >> he should not just I I know they want it but do not market sell your Oracle [laughter] position please.
14:01
>> Yeah but I'm actually actually going all cash now.
14:04
Um but but but he's he's effectively acted as a backs stop.
14:06
And so and so everyone who's come in and said, "Okay, I guess I'm good for 10 billion of that 80 billion, but only if everyone else is in."
14:17
Larry Ellison reportedly has come in and said, "Well, you know, if if there's one person in the bunch that that backs out of their slug at the last second, I'll jump in and get that."
14:27
He's not saying he's gonna put up the whole 80.
14:28
He's just saying he's backstopping it. >> Yeah.
14:31
>> And and and that's the term that's been thrown around.
14:32
So, so, uh, David Ellison feels very, you know, good because he's done what Zazlov wanted him to.
14:39
He said, "Hey, they wanted an allcash offer.
14:42
I brought them an allcash offer.
14:44
I brought them an offer that's higher and we believe that it's um there's no reason why uh factor number two should come into play."
14:53
And factor number two is regulatory approval.
14:55
And so, um, there's been this question about will Netflix get approved?
15:01
If there was a different buyer, it would have even more regulatory risk.
15:03
And so, you don't want to, even if the price is higher, you don't want to accept a higher price with a lower chance of actual um actual conversion, right?
15:14
>> Bobby thinks Choa might uh up his offer to 100K of cash and get back in the middle.
15:20
In that scenario, at least you know that the 100k cash is real and it's going to be delivered on the day of close.
15:27
>> Maybe in actual cash too >> probably.
15:29
I think that was the that is funny because that that was the joke of that meme uh was that he was giving like actual cash when we're saying cash offer here.
15:37
Of course, we are not talking about physical cash. >> Hey, you never know.
15:40
>> Are you money spread over there?
15:42
[laughter] >> Is Tyler doing money spread? What does he got?
15:45
>> Did Christmas come early for you?
15:47
>> I So I I had a question though.
15:47
Um, what makes the Paramount offer uh like hostile?
15:51
Is it that it's like reacting to the Netflix offer?
15:54
>> Is that the Netflix board or sorry, the Warner Warner Brothers board went with Netflix and they're coming.
15:58
It's hostile because they're saying >> screw the board decision.
16:01
We want to go to the shareholders. >> Okay.
16:04
Yeah, cuz the it sounds like they had a nice dinner and the texts were like kind. >> Yes. Yes. Yes. Sound hostile.
16:10
>> No, [laughter] no, no.
16:10
Hostile in the sense of like of like not accepting the final uh like the final decision there.
16:16
And then and then also there is a there is a point where you can appeal directly to the shareholders and and make the you can actually make the legal case that the board is not acting in in their fiduciary duty and in their in the interest of shareholders because um but
16:30
again these things need to be argued in shareholder lawsuits because it is fuzzy because like if if I say I'm offering you a hundred billion and someone else is offering 80 billion and the board says yeah but that hundred billion has only a 75% % chance of going through. You have to discount that now. Now the
16:48
You have to discount that now.
16:48
Now the board says it's worth 75.
16:49
But whoever made that offer can say, "No, we're actually good for it.
16:55
You need you should apply a 10% discount rate and treat our offer as if it's 90%." Or 100%. Good. Right?
17:00
And so and so all of those arguments, those can be made in the court and the shareholders can, you know, react to that.
17:08
And if the shareholders align and say, "Yeah, actually we think we'd be getting more money here with this with this deal, then they can push back against the board at a certain point."
17:16
Um, but yeah, >> friend of the show, high-powered uh media exec says Zazlov has been architecting this situation for the last 12 months, sitting pretty, and he's a wild wy old fox and has what he has been shooting for, two heavy hitters fighting over a deal.
17:35
Don't doubt there will be a couple more turns here with the price or even another uh bidder coming in sideways. >> Don't quote me.
17:45
>> Which is remarkable because the price is so high already compared to where it was 6 months ago.
17:49
Uh Zazlov, I it it really feels like it's coming together that he will be remembered as like an incredible business executive for this deal. I I want to know more.
18:01
I'm still learning about this particular industry and so I've been I've been having fun digging in.
18:04
But >> possible deal guy of the year.
18:07
>> Possible in the conversation of the He's definitely in the >> Sam Sam was Sam looked like he was running away with it over the summer. >> That's true.
18:16
>> Early fall and he lost ball control. >> He lost ball control. Yeah.
18:18
Well, uh, quickly let me tell you about Finn.
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AI, the number one AI agent for customer service.
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Automate the most complex customer service queries on every channel.
18:27
But uh there is there is a wrinkle that uh that people haven't really been considering which is um the fact that Warner Brothers Discovery holds massive a massive often underrated vault of masculine cinema.
18:43
And if this falls into the wrong hands what is masculine cinema?
18:50
>> Masculine masculine cinema would be >> dudes on film.
18:53
>> So they own they own uh a bunch of Clint Eastwood films.
18:56
Dirty Harry, uh, Magnum Force, The Enforcer, uh, Heartbreak Ridge, American Sniper, Letters from Ewoima, uh, Unforgiven, Grand Torino.
19:05
They also own the classic Steven Seagal run.
19:10
Basically every movie where Steven Seagal was a massive theatrical star before going to direct a video.
19:15
We're talking about above the law, hard to kill, marked for death, out for justice, under siege, which is Die Hard on a boat, under siege 2, on deadly ground, fire down below, exit wounds.
19:28
Uh they also own Rambo, the whole surve, the Cobra Wing, Cobra, Demolition Man, The Specialist, Tango and Cash, Bullet to the Head, Get Carter, the 2000 remake.
19:42
They also own Mad Max, Lethal Weapons, uh, all of the lethal the Lethal Weapons, The Matrix, Blade, Mortal Kombat, 300, Rush Hour, Pacific Rim, and a number of, uh, Dad and Military shows, Band of Brothers, The Pacific, Generation Kill. There's a whole host.
19:58
>> They should release the full DVD set just called Guys Being Dudes. >> Yes.
20:02
They also own some Jason Stathithm properties, the Meg franchise where Jason Staithm fights a big shark. >> Whoa. >> Uh, Wrath of Man.
20:09
Um I I guess uh most of the Guy Richie films are actually with Lionsgate MGM, but uh there are variety and and I think this could be a uh you know a big political hot button of what happens to the the Rambo franchises, the the the Hollywood hunks.
20:26
No one's talking about the Hollywood hunks.
20:27
Everyone's focused on the Looney Tunes characters, but if the Hollywood hunks fall into the wrong hands, it could be uh it could swing our entire culture potentially.
20:34
Um anyway, let me tell you about >> apparently Michael on our team worked on Wrath of Man. >> Oh, really? No way. >> First job. >> Very cool. >> Very cool.
20:43
>> Vanto automate compliance and security AI that powers everything from evidence collection and continuous monitoring to security reviews and vendor risks.
20:49
Um you're hiding in amounts of Middle Eastern funding sources in your takeover bid. Are you not? Says boring business. And not hiding it. It's out in the open.
21:01
like this is this is uh this is like the playbook for these big deals.
21:05
>> Double double that of the amount of equity that the Allisonens are putting in. Okay. Putting in around. >> Yeah.
21:11
I mean I think everyone assumes that there'd be a lot of Middle Eastern funding in this um >> that has become the standard funding instrument these days. I I don't know.
21:21
Uh like EA games, we just followed that story a little bit.
21:23
Uh that was obviously 90% >> Saudi money.
21:27
Um, and that is part of the modern dealmaking playbook these days.
21:32
Uh, every I'm pretty sure most of the a lot of venture funds have raised money over there.
21:37
A lot of the big AI companies have raised money over there.
21:40
Like that seems like a foregone conclusion that uh if you need money, you go where the money is.
21:44
Why do uh why do bank robbers rob banks?
21:47
Because that's where the money is, right?
21:50
[laughter] Well, Dylan Buyers says, "David, I appreciate you're underwater today.
21:53
So, sent you a quint quick text."
21:54
Uh, he's talking about the dinner.
21:57
Uh, oh, so that was the correct that was the misspelling. D A I V D.
22:00
He must have been texting very quickly.
22:03
It does give you >> Let's uh let's turn this into a copy pasta.
22:08
>> Yes, I enjoyed the dinner.
22:08
So, uh, Exec Sum has an overview of who who's actually putting in the money here.
22:16
Filings reveal that Paramount's bid for Warner Brothers is backed by equity commitments, including 11.
22:19
8 8 billion from the Ellison family, 24 billion from Saudi Arabia's Qatar's and Abu Dhabi sovereign wealth funds, 1 billion from China's 10 cent, additional commitments from Redbird Capital Partners and Jared Kushner's affinity partners.
22:33
That doesn't add up to a hundred billion.
22:36
So there's must be must be cash coming from somewhere else.
22:41
This is uh maybe maybe there needs to be some more reporting until uh oh they did give a give an an updated version of this post but doesn't quite add up.
22:52
So uh will be interesting to follow where you know how the deal comes together.
22:59
>> Uh and we have a few more people joining this week to help us break down the deal.
23:02
Uh Ben Smith from Semaphore tomorrow and then Dylan Buyers Puck on Thursday in person. >> I'm excited.
23:11
Oh, he's coming in person. Yes, that's great.
23:12
Well, uh, let me tell you about numeral compliance handled numeral worries about sales tax and DAT compliance so you can focus on growth.
23:22
Uh, Trump says that the United States will allow Nvidia H200 chip sales to China and get a 25% cut.
23:27
This is a pretty big change.
23:31
I mean, we were talking about um, not selling.
23:32
I mean, I guess it's not Blackwell, right? It's Hopper.
23:39
So, we're still a generation behind. Um, but was this it?
23:40
It was like a pretty nerfed chip before.
23:44
We're getting less nerfed.
23:46
We seem to move we seem to be moving in a in a more thumbs up direction, more uh let's let's actually get the chips over to China.
23:57
Uh, at the same time, AI is fake, so it doesn't matter. Right?
24:00
That's the take that the pro-China take is that is that it's like >> SAS. It's SAS or it's not.
24:06
It's not like this nuclear bomb that's going to destroy everyone. So, it's harder.
24:11
It's getting harder to make the uh the the the Manhattan project argument, right?
24:20
>> And it feels impossible to make the argument that we're going to get them addicted to the US AI supply chain and they'll never develop uh their own capabilities and so we want them >> Well, I disagree with that.
24:31
I think that that I think that that argument actually holds.
24:33
That argument holds for sure if we can >> in in the next I mean I I totally disagree.
24:40
disagree. I think they're I think China's smart enough to know they don't want to be dependent on any foreign country to produce any >> but I still think there's enough of like a market force within China that if we flood the market with cheap uh Nvidia
24:55
chips like they will there will it'll just be expensive for them to keep propping up their local industry even if they are aware of it even if they know that they have to uh it's a cost and it's something that a lot of AI researchers over there will just say you You know what? I'm already It's so much
25:11
I'm already It's so much easier.
25:12
The Nvidia ecosystem is so great.
25:14
I'm just going to stick with that. I don't know.
25:15
I'm I'm I'm a little bit I'm a little bit skeptical that like uh there isn't there there's no advantage to uh to selling Nvidia chips there.
25:25
I've become more I've become more uh uh receptive to that argument particular even though you have not. Um but that's fine.
25:32
Tyler, what what were you going to say about this?
25:34
Uh yeah, I was just going to say I mean we kind of joke about this um but it is kind of crazy the extent to which you can basically bake down all like AI policy questions to like if you are AGI pled >> because like if you are if you're Daario >> I mean you shouldn't be giving stuff to China.
25:49
China. Um, you also shouldn't you like if you are agi pill you should be thinking about safety all these things like we had Keith Ro boy on >> he's doesn't seem super agi pill he's also like oh safety is a hoax etc stuff like this >> I think basically all these questions you can just >> you know
26:05
>> well it depends because if you're super fast takeoff pled and you're super like asi it's like but you think that it can somehow be contained and whoever gets it first you actually don't mind if China's six months behind you because As soon as you hit that inflection point, you're a thousand years ahead. And so you might
26:22
And so you might as well just do whatever it takes, fund whatever, make as much money as possible as long as it accelerates you to be the first one to hit that inflection point.
26:34
So there is an argument where you can be extremely AGIEL, even superintendent. >> Well, true.
26:38
True social is creating a prediction markets product within the app.
26:43
>> I thought you were going to say AI product.
26:44
Did they launch an AI thing last week?
26:46
>> I think that was fake news. >> Oh, that was fake. Okay.
26:47
But it's possible Trump is going to use the prediction markets on truth social in order to kind of set AI policy going forward.
26:57
Say >> H200s to China, good or bad. >> That's wild.
27:01
>> I mean that that's not that like Robin Hansen says that that's like a good idea.
27:05
>> That was the whole that was the whole that was the whole pitch originally.
27:08
>> There is definitely a bullcase.
27:08
You could say like a steelman for that.
27:11
>> Yeah, it's >> there's always a steel man. >> Yeah. >> Where's your helmet? Where's your helmet? [laughter] >> Yeah. Yeah. Yeah.
27:16
I need to put on the helmet.
27:17
Um, well, let's read through this Wall Street Journal article on the on the details of the new Nvidia deal.
27:23
But first, let me tell you about Figma.
27:24
Think bigger, build faster.
27:24
Figma helps design and development teams build great products together.
27:29
So, uh, notable that this seems to have been completely priced in already because Nvidia is actually down half a half a point today.
27:39
Yes, I've it's it's been such a dramatic story all year and yet it's always felt like a complete footnote in the overall financial performance of Nvidia.
27:50
It's never felt like, okay, yeah, if this if this goes Nvidia's way, they're going to double their double their revenue or double their profits or like, you know, really move the needle.
28:00
They're growing so fast that, you know, I I don't know how many, we're going to get into figuring out how many H200s they sell, but they would need to sell a lot to actually move the needle on this behemoth of a business, what is the world's largest company in the world.
28:13
So, President Trump said he would let Nvidia export its H200 chip to China and that the US would receive a 25% cut, his latest bid to make money for the government in an unusual agreement with a private company.
28:25
I have informed President C.
28:27
Jinping of China that the United States will allow Nvidia to ship H200 products to approved customers in China and other countries under conditions that allow for strong national security.
28:38
25% will be paid to the US of A.
28:41
The move is a boon for Nvidia, which has fought for months to maintain access to the world's second largest economy.
28:48
The company had agreed earlier this year to give the US 15% of China's sales from a lower performing chip, only for the Chinese to scuttle those plans as part of continuing trade talks between the two sides.
29:00
Chips from the world's most valuable company have become a prized geopolitical tool.
29:04
The H200 has higher performance than the H20 that Nvidia was previously allowed to sell.
29:11
But this isn't as powerful as the company's top Blackwell products released this year, nor the Reuben generation chips uh generation of chips coming next year.
29:19
The move follows a meeting between Trump and Jensen Wong last week where the pair discussed H2 H200 exports.
29:25
People familiar with the matter said Nvidia shares added nearly 2% after hours. That's not too bad.
29:30
Even with the US government taking a cut, the decision could be worth billions of dollars in sales to Nvidia, which enjoys comfortable margins on its AI chips.
29:37
In the most recent fiscal quarter, Nvidia reported gross margins of 73.
29:42
4% on 57 billion in sales. That is crazy.
29:50
They can totally afford 25% for the big guy.
29:53
Uh I have no idea if it'll be legal.
29:55
We'll have to figure out um if this gets approved because in general the United States does not import uh in enforce export duties.
30:02
That's not something America's done historically.
30:07
We had some folks on the show to contextualize that and give us some background when this was first floated.
30:13
Feels like it is happening now.
30:13
Um, but we'll see where it lands.
30:15
In August, Nvidia CFO Colette Crass said that if geopolitical issues subside, the company could ship between two billion and 5 billion of chips to China per quarter, which increase uh which could increase if orders pick up.
30:30
Oh, they're doing >> right around Lutnik was on CNBC.
30:32
Uh, and this was the quote that originally ticked off the Chinese.
30:38
He said, "We don't sell them our best stuff.
30:41
Not our second best stuff, not even our third best." >> Mhm.
30:45
>> And he said, "You want to sell the Chinese enough that their developers get addicted to the American technology stack." That's a thinking.
30:51
Uh, and of course, they uh CCP basically immediately said, "We don't want any of them now uh because we're offended."
30:58
But um it does seem like yeah I I don't know we we will have to we'll have to have uh Bill Bishop or someone on the show to contextualize how China is receiving this information whether or not they will actually buy it.
31:10
Of course we are going to be joined by Aaron Gin in just 30 minutes. So stay tuned for that.
31:15
Also let me tell you about Linear meet the system for modern software development.
31:20
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31:25
So, the exports could help Chinese tech giants that have struggled to get top chips to train their models.
31:32
Wong has argued Nvidia should be allowed to compete in the Chinese market because China has many of the world's top AI researchers and the US should want them using American technology.
31:38
Uh, if you're you are not going to replace China, Wong said at an event at a think tank event.
31:45
Uh, Trump said that the government would take a similar approach to exports from Nvidia competitor AMD as well as Intel, in which the government now has a 10% stake.
31:52
The approval comes just weeks after administration officials, including Secretary of State Marco Rubio, torpedo a push from Nvidia to sell a slim down Blackwell chip to China before a recent trade meeting between Trump and Cunping.
32:07
Some officials, including AISR David Saxs and Commerce Secretary Howard Lutnik, have backed exporting the H200 because it could be a good compromise that allows Nvidia to compete with China's Huawei technologies without vaultting China past the US in AI.
32:24
People familiar with the discussion said, "I don't know.
32:26
It's such a such an interesting question that I I still I still wrestle with.
32:31
still wrestle with. Like we we exported a ton of Teslas to China and BYD and Huawei have now it >> arguably completely leaprogged >> completely leaprogged was so they were they did not become addicted to the American >> that's what that was the point I was making
32:50
>> earlier you can make the art like almost with every single product they've said >> we'll work with you to make this thing that you want to make we're really good at making things >> uh and then they ultimately just make a better version of said product and make it for >> cheaper. >> Yes. >> Yes.
33:08
>> And uh and in the case of cars right now, we're obviously not allowing these cars to be imported. >> Yeah.
33:14
>> Uh into the US, but uh you know, they they can simultaneously say, "We're happy to keep making you these things.
33:21
We're also going to compete with you directly." Yeah.
33:24
>> And constantly try to be better than what you do.
33:27
I I just wonder like if you if you play it back, you don't and you don't allow Tesla to export the amazing Model S or Model 3, um does that slow down BYD's development of their car or or or Huawei's or Xiaomi's development?
33:47
My my understanding is they were able to basically get a paid education making Teslas and they were able to leverage that into making >> but that's about making the car there if you don't make the car there which is because the >> Nvidia has a Shanghai >> but that's research that's not made there that's not made there like it's
34:06
very different when you're when you're saying okay we're going to go and we're going to go and produce this product there and like you are going to get educated there and the >> it's different but it but you remember we've gone through this before China's like five-year plans to create a domestic chip industry. >> They've been doing five-year plans for
34:22
>> They've been doing five-year plans for 60 years.
34:24
>> I know they're building. That's what I'm saying.
34:26
And I would argue that it's working.
34:27
They're not caught up, but they certainly made, you know, massive amount of progress.
34:30
They've made more progress than any other country on Earth. >> Yeah. I don't know.
34:34
What do you think, Tyler?
34:36
>> Um I [clears throat] I think if you want to think about like getting the Chinese addicted to our chips, like how addictive are the chips?
34:41
Yeah, >> because um if you can make a comparison between like you have the Nvidia chips and then you have the Chinese or like TPU, right?
34:48
Because the TPU is like in some ways it's it's harder to use the open source is not as good.
34:54
>> Um but if it's [clears throat] just more economical like if the actual hardware is just like a little bit cheaper, then it doesn't really matter how worse the software is, people will eventually move to it. Mhm.
35:02
>> So, it's like the I don't think there is actually that much like soft power in the kind of general open- source stuff like that >> in regards to like uh Nvidia.
35:14
>> It doesn't seem very addictive outside of it just being cheaper. >> Yeah. Uh yeah.
35:17
I mean it at the same time like like we are America is very much like addicted to Chinese solar panels right now.
35:23
like the Chinese solar panels come here, they're cheap.
35:25
And so we don't wind up buying or building a domestic solar panel industry because just to get anything off the ground, you have to go in and say, "Okay, we're we're going to deal with having no margin forever and no venture capitalist can underwrite it and no private equity firm can underwrite it."
35:46
And so it just doesn't really happen. >> Yeah.
35:49
But the Chinese, they do do that. >> I guess they do.
35:52
they do bear the cost more so it doesn't matter but it's like they wouldn't have to bear the cost so we're we're imposing a little bit of a cost on them.
36:00
It's like they they actually have to pay it whereas like they don't uh whereas like they wouldn't if we didn't do that right because if we if if we if we don't go in and we don't and we don't sell them Nvidia chips then they're like okay well it makes economic sense to to back Huawei and and fund them.
36:18
Whereas now they're like it it's not economically logical to back Huawei, but we have to because there's so much pressure from better chips flooding the market like Nvidia chips that if we don't if we don't fund Huawei uneconomically, if we don't lose money on Huawei, like we will never get to uh we will never get we will never be competitive. >> Yeah.
36:41
I I think it seems to me that like either way they're going to fund it, the government, the Chinese government, too.
36:47
I I don't think it actually matters that much. >> Yeah. I don't know.
36:49
Well, let's uh let's move on.
36:52
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36:59
>> Um the United States will allow Nvidia's H200 processors. It's second best.
37:04
So, this is a this is a change from what Lutnik said, right?
37:09
Lutnik said, "We're not selling the best.
37:10
We're not selling the second best."
37:11
Turns out we are selling the second best now.
37:13
Um, maybe we'll sell the first best soon. Who knows?
37:18
Well, uh, we should play this clip from Patrick Oshanaugh's fantastic interview with Gavin Baker on Invest Like the Best.
37:26
He's talking about space data centers.
37:27
We had Delian on the show yesterday talking about space data centers.
37:31
Delian still thinks >> Gavin, it's pretty far out.
37:35
>> Gavin knew we needed a new narrative.
37:35
Y said after the the fateful BG2 episode ended the AI trade, >> we needed a new trade and now we're getting the space data center trade.
37:46
>> Okay, let's hear the space data center.
37:47
>> I think the most important thing that's going to happen in the world in the next 3 to four years is data centers in space.
37:54
>> If you think about it from first principles, data centers should be in space.
37:57
What are the fundamental inputs to running a data center?
37:59
There are power and there are cooling >> and then there are the chips.
38:04
the inputs to making the tokens come out of the magic machines. Yeah.
38:07
So, in space, you can keep a satellite in the sun 24 hours a day. >> Pretty cool.
38:14
>> And the sun is 30% more intense.
38:14
And this results in six times more irradiance in outer space than on planet Earth.
38:21
So, you're getting a lot of solar energy.
38:23
Point number two, because you're in the sun 24 hours a day, you don't need a battery.
38:26
And this is a giant percentage of the cost.
38:29
So the lowest cost energy available in our solar system is solar energy and space. Okay.
38:38
Second for cooling in one of these racks a majority of the mass and the weight is cooling >> and the cooling in these data centers is incredibly complicated.
38:48
You know I mean the HVAC, the CDUs, the liquid cooling.
38:53
In space cooling is free.
38:53
You just put a radiator on the dark side of the satellite >> and it's [laughter] as close to absolute zero as you can get.
39:01
So all that goes away and that is a vast amount of cost.
39:06
And then >> how is a bit more complicated than that?
39:11
>> The the dissipating uh heat in space.
39:14
>> This is what everyone's fighting about.
39:15
I'm not exactly sure uh how it how it plays out like the physics of it.
39:18
But a lot of people are saying like, uh, yes, it's in a vacuum, but because it's in a vacuum, you can't just you you can't like it's not as passive of cooling.
39:30
It's more of a material science problem.
39:32
Like there's more physics uh physics problems there.
39:34
Um, also like I don't know.
39:36
I feel like you might need some uh I I feel like you might need some batteries because um I think there are there are orbits that are effectively in the sun all the day, but I think that the Earth's shadow like hits them not like every day, but like every once in a while you'll be uh you you'll you'll be caught in a shadow almost in like an uh in a uh what's it called?
40:00
in a uh what's it called? um I don't know some sort of uh you you know you just get caught in the shadow not every day but uh like every 12 days or every 30 days or something like that and so in that scenario I mean maybe you maybe it'd be fine if you're doing inference
40:16
and you don't and and you can just turn off the whole system for a little bit and there's some redundancy >> I just texted our resident spaceman Dian yeah >> I said >> answer answer this >> I just said quick take >> yeah on this >> it's urgent >> it's urgent well we'll we we'll get back from him. There there's more to that
40:32
There there's more to that clip though.
40:33
We should play this because there's a funny part in here.
40:36
>> Going to collect those racks. Well, it's funny.
40:38
In the data center, the racks are over a certain distance connected with fiber optics.
40:43
And that just means a laser going through a cable.
40:45
The only thing faster than a laser going through a fiber optic cable is a laser going through absolute vacuum.
40:50
So if you can link these satellites in space together using lasers, you actually have a faster and more coherent network than in a data center on Earth. Okay.
41:02
For training, that's going to take a long time. Yeah. Just cuz it's so big.
41:07
But for inference, so let's think about the user experience.
41:11
You know, when I asked Gro about you and it gave the nice answer. >> This is crazy though.
41:16
They've done a podcast together five times.
41:19
Why is he asking Rock about Patrick?
41:22
[laughter] >> I was like, what is going on?
41:24
>> Went to some sort of metro aggregation facility in New York, probably within like, you know, 10 blocks of here.
41:31
There's a small little metro router that's routed those packets to a big >> XAI data center somewhere. >> Okay.
41:39
And then the computation was done and it came back over the same path.
41:42
If the satellites can communicate directly with the phone. >> Mhm.
41:49
>> And Starlink has demonstrated direct to self this whole thing.
41:53
>> I would like to I would like to know how much uh SpaceX >> exposure Gavin has because >> if this does become a dominant at least narrative over the next few years. >> Yeah.
42:06
A lot of the people that we know that have computers in space >> are not exactly bullish on data centers in space on a short time horizon. Yep. >> We have not.
42:15
We had the founder of StarCloud on.
42:17
He's obviously bullish, but I don't believe he has any >> satellites in orbit. Yep.
42:22
>> Uh we've had Delian on.
42:22
He puts things into orbit.
42:25
He brings them back down.
42:27
He's talked about having he technically has >> I mean a hilarious position because Founders Fund has a huge position in SpaceX obviously, but also Delian has had to do the hard work of like getting something in space and probably understands like how much of a grunt work it is and how much of a grind it is to get even just like something as small as like the pod into space.
42:45
And then he's also seen at Crusoe like what a real data center looks like and the idea of putting something so massive into space.
42:56
Like it's bigger than the Hubble.
42:58
It'd be bigger than the ISS.
42:58
Like what are you thinking about this space data center thing?
43:02
Have you evolved on this?
43:03
>> Yeah, I mean I don't know.
43:03
To me it seems just kind of uh impractical.
43:05
Like >> if you think about um if you're doing inference or something >> uh like how much of the cost of the token is actually in the energy, right?
43:15
Because like I feel like one of the main uh benefits of having the the data center in space is that energy is basically free, right? It's right there. >> Sure.
43:22
>> Um but if you think about like I think Casey Han has talked about this.
43:24
Um like if you think about an inference when you're doing inference the the portion of the the cost that's actually the energy it's like very tiny. Yeah.
43:34
Because it's like the chip is expensive or doing like it's like not that expensive.
43:38
Um, so it's like, okay, the cost gains overall are like not that great and then it's like, well, what if you want to change the chip to the next generation or what if you need to do some kind of like mechanical work?
43:50
Are we ignoring how a broken cluster would take some sort of intervention to fix as well as the cost per kilogram in fuel costs?
43:58
Um, yeah, just just for context, so Gavin was at Fidelity >> and led a $900 million investment in SpaceX at a 12 billion post money valuation. >> That's amazing. Wow. [laughter] What a goat. That's incredible. >> Um, okay. Actually, yeah.
44:18
So, may maybe they didn't do the full 900 million. Grock isn't sure. >> Sure. Sure. Sure.
44:22
Um, but but I mean either way, like you can you can be pro or con on space data science.
44:26
also says SpaceX has been a trades largest venture capital position as of 2022, comprising an estimated 30 to 40% of its VC portfolio. Feels wild.
44:36
So anyways, Gavin is uh is set to on one hand, >> yeah, >> Gavin could know things about space data centers that the rest of us don't know because of his position >> uh and and and proximity to SpaceX.
44:49
At the same time, SpaceX, if they go public next year, would benefit a lot from having a space data center kind of like narrative as part of this.
45:02
>> It's crazy because the business is so solid.
45:03
I feel like you don't need a fourth act or whatever. >> Okay.
45:06
Wait, so what about this?
45:06
So, if a lot of the gains of space data center are just because the energy is free, >> why don't we just But then there's this hard part about having like different satellites everywhere.
45:14
Put the data center on the moon. Mhm.
45:17
>> There's no atmosphere.
45:17
So, you don't get the 30%, you know, reduction in energy from from the sun >> and just put data center on the moon.
45:24
>> Well, don't you get a 50% uh reduction because there's like there's a dark side of the moon like like the moon, >> you wouldn't put on the dark side. >> I know. I know.
45:35
>> But what I mean is that is that our our dark side sometimes gets light from when it's not facing us, right?
45:40
And so so you only if you're on the moon, you only get light 50% of the time.
45:52
>> Whereas whereas if you're a satellite and you're flying out in space and you're kind of orbiting the Earth like but at a weird axis so that you're not constantly in shadow all the time, you're getting sun. He says 24 hours a day.
46:03
I I think it's I think it's like 99.
46:05
9% of the time, but regardless it's like almost always.
46:08
Whereas if you're if you're actually like on the moon, you don't get sunlight >> 100% of the time.
46:14
You get it 50% of the time, I'm pretty sure.
46:18
>> I don't think it's because maybe there's Yeah, the sun's not the sun's not like uh or the the moon's not sunlocked. It's it's earth locked.
46:26
>> Put up this po pull up this post.
46:26
I put it at the bottom of the stack from Joe Morrison. Uh he's over at Umbris.
46:32
>> While we pull that up, let me tell you about Reream.
46:33
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46:36
com and we will pull up this next post.
46:41
>> Uh Joe says, >> "You just put a radiator on the dark side of the satellite."
46:45
And he says, "Thermal engineers in absolute shambles right now." >> Yeah, people are not. It's I don't know. People are so smart.
46:53
>> Casey Hammer says, "To be fair, this is a big satellite."
46:57
Joe says, "Many big satellites."
46:59
>> Big satellite makes it easier. I don't know. I I don't know. Yeah.
47:01
I think I think you need I think you need like like a lot of >> Yeah.
47:06
>> Like you need you need basically a lot of uh mass in order to dissipate enough >> sure >> uh heat >> from a from a GB 300 or something GB 200 >> 200 >> somehow as a as Space Mobile Inc.
47:18
is up 27% in the last 5 days.
47:21
So [laughter] >> exciting.
47:25
>> People are people are uh quite excited. >> Yeah.
47:30
Well, should we head over to GFream news?
47:32
There's some massive news from GFream Aerospace.
47:35
The G400 introduces NextG Gulfream tech to its class.
47:40
Sound on to learn more with GFream [music] President Mark Burns.
47:43
How has Mark Burns not been on the show yet? Here we go.
47:50
Clearly don't have a no render policy over here.
47:52
They're they're rendering.
47:56
This >> You think they're just not You think they could just be adding special effects? What do you mean?
47:59
This is the most rendered video I've ever seen.
48:02
This looks like it was rendered. Okay, but here is 2010.
48:08
>> You think this is real, though?
48:10
>> Bring GFream performance standards cabin class.
48:14
>> Fulfilling our customers needs for a product line.
48:16
>> I knew it was too good to be true.
48:18
>> And enhance every journey. >> Like this is real.
48:19
This is what it looks like. >> It's far away.
48:23
>> It does look like an airplane though.
48:25
With GFream's signature combination of range, speed, and cabin comfort, the G400 will provide unrivaled efficiency thanks to the combination of the advanced practical.
48:37
>> This is going to be a hot Christmas gift this year. >> Absolutely.
48:40
People wondering, >> I think this will be top of this will be under the tree for a lot of people.
48:45
>> It's not ideal to do like a pre-order as a gift, you know?
48:47
It's nice to have something under the tree, but I think people would make an exception here. It's so funny.
48:52
I was talking I was talking with a a mutual friend of ours, a a a guest who's been on the show many times, and uh they're planning to purchase a jet at some point in the relatively near future.
49:06
>> And he was so fixated on like needing to be able to it's his first it will be his first jet.
49:12
He was so fixated on like I need to be able to stand up at at like like it can't have uh like the cabin needs to be big enough that I can like walk around freely.
49:21
>> [laughter] >> I was like, "Come on, for your first jet, can you not just like, you know, uh tolerate like slightly lower height in the cabin?"
49:30
>> He was like, "No, I got to be able to I got to be able to move freely.
49:34
[laughter] >> Go straight for the 747, the BBJ." Yeah.
49:37
>> Get the the the VIP VIP package.
49:40
[laughter] The one that only thearis have for some reason.
49:43
Uh well, >> uh Casey Hanmer, >> okay, I got it back.
49:47
I got a text back from Delian. I won't read all of it. >> Okay.
49:54
>> Uh there's a line here.
49:54
This is from someone else.
49:56
Dude, all this data centers in space stuff.
50:00
>> Also, I'm not going to read that.
50:00
You need 1 million 100 kilowatt SAS to generate 100 gawatts in orbit.
50:04
100 kilowatt SATS uh weighing 1,00 kilogram including payload would mean a 5x increase in power density.
50:13
and you can't just not have batteries and slap a radiator on the back, lol.
50:18
And then uh there was some uh choice words exchanged that I won't [laughter] I won't read on the show, but uh anyways, um I think we should host the data center in space debate. >> That sounds good.
50:33
>> We should get a few people on here.
50:34
Somebody to be bullish, uh somebody to be bearish.
50:37
I think we want somebody to be bullish that has put things into orbit and taken them down >> many times.
50:45
>> I think it's hard to um it's hard to lean on on somebody's kind of take or opinion if they're not actually participating uh in in [snorts] space.
50:55
They're just sort of speculating. >> Yeah.
50:57
Um let's read through a little bit of what Casey Hammer had to say.
51:00
He said, "Here's one idea about SpaceX's next big thing.
51:03
next big thing. AI computing inference again not training on orbit but how the hell can SpaceX do this cheaper than just building more data centers on the ground from first principles it's an attractive position proposition because the GPUs have extremely val have
51:18
extremely high value per kilogram and extreme revenue per kilowatt both of which are relatively expensive that is the value prop somewhat washes out the pain of operating in space uh so I took a closer look if anyone can make this work it it is a Starlink derived system. So, I started with the Starlink V3
51:34
So, I started with the Starlink V3 satellites with some highfidelity CEO CAD below. Um, orbital parameters.
51:38
Pick a sun-synchronous orbit.
51:41
So, we're in full kilowatt uh 1400 kilowatt per meter squared sunlight at all times. No need for batteries.
51:48
Deploy the solar array in sun slicer mode facing full sun, but the edge is pointing in the orbital direction bottom right in these images to minimize drag.
51:59
But the inference starlink star thought satellites don't have to scrape the atmosphere um being in sunsynchronous orbit they'll need to use the rest of the Starlink constellation for back haul via laser links anyway and higher orbits actually improve worst case latency uh very slightly too high though and SSO is relatively full of debris. Let's pick 560 km.
52:25
A Starling satellite in this orbit has full sun.
52:28
So the back half is always shaded and relatively cool.
52:30
The next hottest thing in the sky is the Earth taking up almost half the sky to the bottom left in these images.
52:37
And so what what does he conclude?
52:39
He says, "I've seen a bunch of high inclination Starlink launches from the Vanderberg recently, but I don't think any of them were going to sun-synchronous orbit.
52:46
In any case, a ring of inference satellites visible at dawn and dusk running north and south will be awesome.
52:53
If one starship can launch a 100 tons to LEO, then that gets close to 30 megawatts of inference per launch.
52:59
A thousand watts is 300 gawatts.
53:02
Now we're talking real scale.
53:05
We're doing one launch of Falcon 9 per day.
53:09
That was delions loosely.
53:09
You know, we're now one a day, so 300 in a year.
53:15
So you get to, you know, a thousand over three years if you're on a one a day cadence or if you can wind up getting more.
53:22
The math is not that crazy, but uh it it it does seem like Delian was pushing more towards like, hey, this is maybe 10 or 20 years, not the next three years.
53:32
But uh it certainly will be fun to follow the story.
53:36
[laughter] In the meantime, let me tell you about cognition.
53:37
The team behind the AI software engineer, Devin, crush your backlog with your personal AI engineering team. Jordy has survived.
53:44
I keep like getting the this the podcast can like down the wrong.
53:52
>> They should really make a make a drink specifically for podcasters that has no carbonation that cannot be choked on in any way.
53:58
Mark Benny off says LLMs are the new disc drives.
54:01
Commodity infrastructure you hot swap for whoever's cheapest plus best.
54:05
The fantasy that the model is the moat just expired.
54:12
H Mark Beni off having fun on the timeline.
54:14
I love that he's having fun.
54:14
I love that he's uh he's taking shots.
54:19
>> Don't they have an AI lab to be clear?
54:21
>> Uh they were working on Einstein for a while, but I think that they they are very much happy to be a rapper, happy to be a buyer of LLMs at this point.
54:28
Um it certainly has penciled out that way.
54:31
We we can talk more to Mark about that. >> It's feeling good.
54:36
But [clears throat] >> stocks up 10% in the last 5 days.
54:37
Let's hear it for >> best salesman history.
54:45
Um, [clears throat] uh, what what do you think about Michael Bur?
54:50
I think the whole industry needs a $500 billion IPO ASAP.
54:56
>> So any everyone that knows anything knows this.
54:59
OpenAI is the next Netscape doomed and hemorrhaging cash.
55:02
Microsoft is still trying to keep it afloat while keeping it off balance sheet and sucking out the IP.
55:08
So why do they keep getting funded?
55:11
The whole industry needs a $500 billion IPO ASAP.
55:16
[clears throat] Um the whole industry needs to go away and sit in a corner for a couple of centuries and think about what it's done, says Jeffrey Miller. Wow. Um I don't know.
55:22
This is People want extreme takes.
55:26
He's >> This post would go super hard if you don't understand the Microsoft OpenAI relationship.
55:33
Yeah, >> but uh >> yeah, it's just it's just uh >> what was what was Netscape's peak revenue?
55:40
>> What was what was Netscape?
55:42
>> If I remember correctly, they IPOed with like 15 million of revenue.
55:45
>> That feels a little bit different.
55:47
Netscape's peak peak revenue 1997 was 500 million.
55:50
I mean, we're up at 220 billion this year for OpenAI.
55:56
Yeah, their total revenue before IPO first first two operating quarters, Netscape reported total revenue of 16. 6 million. >> Just odd.
56:05
I mean, did Netscape have like an enterprise business?
56:06
Like um >> should ask Mark. >> Yeah. I don't know.
56:10
I mean, even even if there's a uh Yeah. Yeah.
56:15
Like even if there's more commoditization, like it's going to take it's going to take time.
56:18
it's going to take time. And I don't know the the dynamics of the of the of the competition here uh feels like there will still be a lot of value even if even if there are even if it is somewhat commodity infrastructure it's like you know what else is commodity
56:32
infrastructure like AWS GCP Azure like you you get you get a you know an like a a server with some hard disk on it like that is commodity and yet they all have 30% margins and they're all massive businesses and when AWS when Amazon broke out AWS as its own line. It was
56:49
It was like an IPO of its own company because it was so big.
56:53
It was such a massive business and it should be completely commodity because it's just servers in a data center and yet >> Yeah, it's it's it's interesting.
57:01
Yeah, it's interesting too.
57:03
I mean uh Bur uh has has uh you know positioned himself of of uh just hating any company that's overheated.
57:12
uh but uh chat GPT having close to a billion weekly activives uh and ultimately even if they just compete in search right >> uh at least it's a tr you know multi- trillion dollar opportunity uh whether or not they you know fully execute against that is another thing but >> are you buying are you buying the IPO timeline of uh cohhere then anthropic then open AI or do you think they will be sorted in a different uh in a different pattern. >> What was the order? >> Cohhere first.
57:46
That's Aiden Gomez's uh foundation model lab.
57:50
He's of course on the transformer paper.
57:52
Also a dripped out technology brother. >> That's right.
57:56
>> With a fantastic uh uh set of outfits.
58:00
Um then then anthropic and then open AI. Open AAI third.
58:07
>> That's that's the rumor. >> Hard to say.
58:09
I have no idea how the market will react to cohhere.
58:14
>> Yeah, Coher has has has shifted more into like the business the enterprise >> market fully enterprise >> not in the timeline at all.
58:20
that could very well be intentional, but it would be >> uh >> it'll be interesting how much excitement they can build around the IPO, assuming they're losing a lot of money, >> assuming the enterprise is really competitive and they're competing with anthropic and open AAI and open source models.
58:40
If the narrative changes to the point where, you know, this this idea of of every enterprise is going to need a a basically a custom LLM that's fine-tuned or pre-trained on their data like what uh AWS CEO Matt Garmin was uh talking to us about about these pre-training checkpoints where you can go in and say, "Okay, I have a business and I absolutely do not want to upload my data to Enthropic.
59:05
I don't want to update it.
59:06
I don't want to upload it to OpenAI, but I want a model that understands my business's data at a core level in the pre-training step and Coher can offer that and so show traction there.
59:16
That that feels like that could be the next wave.
59:21
We've talked to like a number of founders that are are building those sort of like custom pipelines and there's not really a public company that is even anywhere in that narrative.
59:32
And that narrative does feel very nent.
59:34
It feels like it has not percolated through the public markets yet. So, um I don't know.
59:40
It could be it could be uh you know exciting for for for them.
59:42
Um well, let me tell you >> they only raised they've only raised 1. 4 billion.
59:49
>> I did not realize they >> Sorry. 1. 5 >> 1. 5 billion. >> 1. 54 billion. Very modest amount.
59:55
>> Uh especially when you have seed stage companies raising half a billion.
59:59
>> We got one of those on the show today. >> Dean joining later.
1:00:03
He kicked the hornets's nest on the timeline >> a little bit.
1:00:06
People were people were pushing back >> because of his his racing history. >> No, no, no.
1:00:12
>> Oh, people people show respect. >> Love that. Show massive respect.
1:00:14
No, but uh I think uh I think uh Jack at Slow was saying that Nvidia was valued at at 500 million when they IPOed.
1:00:23
Of course, that was very long time ago. Mhm.
1:00:27
>> Uh but uh anyways, people people were just saying like it feels pretty potentially overheated, but we have Naveen coming on the show today and I'm excited to hear >> about the opportunity from him directly.
1:00:39
I >> I'm ready to say it's overvalued unless he's unless he's built a company previously and sold it >> twice maybe. >> Yeah, twice.
1:00:47
If he's done that, then he's then he's off the hook.
1:00:48
But he's got to prove it to us because if if he's just some new grad, some dropout >> like a waterlue >> Yeah.
1:00:55
If he's just if he's just like if he shows up on the show and he's just like, "Yeah, I had this idea in my garage. I didn't go to school.
1:01:00
I've never done in business before and now I then I'm gonna I'm gonna call him out and I'm going to say you're overvalued.
1:01:08
You you raised too much money."
1:01:08
But if he can prove to us that he's done it once or twice before, then I'll let him off the hook.
1:01:16
>> Yeah, >> I'll let him off the hook.
1:01:18
>> Anyway, >> I think that's fair.
1:01:19
>> Let me tell you about Privy.
1:01:19
Privy makes it easy to build on crypto rail securely spin up white label wallets, sign transactions, and integrate onchain infrastructure all through one simple API.
1:01:28
Uh let's read the semi analysis post says important.
1:01:31
A common misconception about OpenAI's upcoming custom chip is that since it's a custom chip, it won't be flexible and will be a dataf flow machine.
1:01:38
OpenAI has recognized that the 100x efficiency gains for training and inference happen at the algorithm layer and the hardware chip needs to be flexible enough to accommodate these algorithm changes.
1:01:49
We went from just pre-training transformers to now doing RL post-training on transformers.
1:01:55
We went from dense transformers to mixture of expert transformers and soon ultra sparse transformers that will have four active experts per token out of 2,48 total experts.
1:02:05
We went from casual MHA attention to MQA and GQA to attention sync sliding attention to now even learned sparse attention despite AI tourists think >> the chip open AI is building with Broadcom will be far more flexible than TPUs interesting despite most of OpenAI's chip team being poached from Google's TPU team. Hm.
1:02:27
The the semiconductor horse race continues to fascinate me and I'm so glad that we have uh the good folks over at semi analysis coming on the show regularly to help us understand it.
1:02:39
I always enjoy talking to them.
1:02:41
Uh and we have uh two uh two folks from semi- analysis joining the show next week.
1:02:46
So we will be having a great time.
1:02:48
Let me tell you about turbo puffer serverless vector and full tech search built from first principles and object storage.
1:02:52
[music] Fast 10x cheaper and extremely scalable. Of course. >> That's right. It's scalable.
1:02:57
A hedge fund was ordered to pay a bonus to a trader who made 97% of its revenues.
1:03:05
>> This is hilarious cuz when I read this at first, I thought it was he had made he like his target bonus was, let's say, 10 million and he brought in 9. 7 million.
1:03:16
And so he was 97% of the way to his bonus.
1:03:19
And they were like, "You didn't you didn't hit your bonus, buddy.
1:03:22
You you don't get the bonus at all."
1:03:22
And I was like, "Oh, that sucks."
1:03:24
But like that's kind of the deal.
1:03:26
That kind of makes sense.
1:03:27
But uh Evolution Capital Management has to pay him because uh he >> Yeah.
1:03:33
So a hedge fund that was sued by a trader for refusing to pay a performance related bonus despite him making 97% of its revenue has been ordered to pay him 5.
1:03:41
4 million plus interest by the high court >> in London.
1:03:45
Uh when I read the headline of the story, I expected it to not be uh in the mid7 figures.
1:03:50
Uh but >> what' you expect?
1:03:53
I mean, I I was hoping at least eight.
1:03:56
I was hoping at least eight.
1:03:58
>> He's not getting a G400 off of this. >> Come on. >> Not even close. >> Not even close.
1:04:03
>> Uh, Robert Gagliardi sued his former employer, Evolution Capital Management in London, alleging that it acted in bad faith by denying him a $7.
1:04:10
5 million discretionary bonus after he had generated more than60 million for the firm. >> Wow.
1:04:18
>> Wait, does this mean that every other >> trader lost money was just >> something like that?
1:04:23
I don't know, >> heavily.
1:04:24
Uh, >> so he was at the fund, brief stint, he made 12 million.
1:04:28
He was already paid 7 million, including a $625,000 signing bonus.
1:04:34
Base salary was $425K and a $6 million new issue bonus.
1:04:38
Uh, so he he needs to get out of this.
1:04:41
He needs to go into AI research ASAP if he wants to be putting up real numbers.
1:04:45
Y uh this is rough, but there are some there are some harsh words here.
1:04:49
He [laughter] said, uh, Gagiardia, a block trading specialist, alleged that he was told in early 2021 that a return of $10 million over the rest of the year would be an excellent result.
1:05:03
When Gagiardi asked the fund's founder, Michael Lurch, for the payout in 2022, he responded, "I'm not going to pay you the bonus if you sue me." >> So, Gagi already did. >> And he won. >> He did. He did.
1:05:17
Uh although Evolution did not dispute his extraordinary returns, the fund argued that the damage done to its reputation as a result of dealing with a US uh SEC probe into some of Gagliard's trades at his previous employer outweighed his performance and that the bonus did not need to be paid because it was discretionary.
1:05:35
There's no question that Mr.
1:05:37
Gagliardi made exceptional profits for the funds and Mr.
1:05:40
Lurch frequently praised his performance in that respect.
1:05:42
Had Evolution properly performed the contract, Mr.
1:05:46
Gagliardi would have received a discretionary bonus of 5. 3 million.
1:05:50
Uh the judge also said that Gagliardi was Lurch's prize asset at Evolution.
1:05:56
That's a good goal for everyone that uh is, you know, maybe working at a company become the prize asset.
1:06:02
Uh hopefully that doesn't result in >> in a lawsuit like this.
1:06:05
Um but uh they're feeling they're feeling Gagliardi and his lawyer feeling very vindicated.
1:06:12
>> Well, we have our next guest here in the reream waiting room.
1:06:14
Let me tell you about Gemini 3 Pro.
1:06:16
First, Google's most intelligent model yet.
1:06:19
State-of-the-art reasoning, next level vibe coding, and deep multimodal understanding.
1:06:23
We have Aaron Gin, the CEO and co-founder of HydroHost. Good to see you. It's been too long. How you doing? >> Welcome back. >> Doing all right. Yeah. Yeah.
1:06:32
I just got back from Southeast Asia. >> Oh, yeah. >> Well, yeah.
1:06:35
And uh despite what some of the critics were were saying, I wasn't I wasn't smuggling anything I shouldn't have been smuggling.
1:06:43
>> [laughter] >> Are you getting accused of smuggling? Um, that is wild.
1:06:45
Well, uh, give us the, uh, give us the update on, uh, your interpretation of the H200 deal, where things landed, where you think the next, uh, debate points will be. I'd love to hear that. >> Yeah.
1:07:02
Like the I mean, as you know, I've said a number of times that the even though I am a China hawk, that we have to realize that Trump fundamentally is a pragmatist. >> Sure.
1:07:11
>> Sure. and he is not interested in the ideological warfare and I think that him taking over the Republican party proves that and the orientation of restoring to America which we all know like I wrote one of the first arguments for a new Monroe doctrine so now you saw that the department of war has been putting that out the white house has been very clear
1:07:31
that it's trying to reshore its emphasis back to uh left in South America and to build up the ring of fire from you know South Korea down Singapore essentially uh to be more sovereign essentially NATO as we've approached ourselves with uh having them uh spend their own money to support their own military that the expectation is that Asia would do the same thing. Um, so a deal with China on
1:07:53
same thing. Um, so a deal with China on trade was always on the table and was very likely because both parties actually want this to happen and and I I do believe that with uh like with Huawei that that yes, it is the national
1:08:09
champion and they do want to proliferate it, but they are but they're more interested in selling it to other people and promoting themselves as a means of trade like they did with the Belt Road initiative >> than they are for internal uses like that. That's just kind of my uh
1:08:23
That's just kind of my uh estimation talking to people in the region and I mean just came back from there.
1:08:30
So So Nvidia being in in that region and being sold particularly China I think is important for American interests whether it's an H20 or B30 or H200 I'm kind of less opinionated on.
1:08:42
I just think that we need to be there because half of all AI engineers are Chinese and and we can go through any list of anyone scrolling at the bottom of this uh you know this this broadcast and you can see that the probably the majority are Asian descent you know minimally and and as America we just have to realize that like we're good at certain things and we're not good at certain things.
1:09:04
So, we're very good at commerce.
1:09:05
We're very good at free markets.
1:09:08
We're very good at enterprise.
1:09:09
We're very good at creating the default framework, the rules of the road for the world to transact.
1:09:14
I I think when it comes to trying to do these other strategies, I think we're we're not very good at it.
1:09:20
And we just kind of have to realize that also that the president of the United States is interested in making deals.
1:09:25
He's not interested in trying to get involved in other people's business. >> Yeah.
1:09:29
Uh let's I mean there's like a million different pieces here, but uh let's start with uh uh the fact that there are so many fantastic genius AI researchers in China.
1:09:38
Uh why is it in the why is it in the interest of the United States to help them?
1:09:45
Is it that if they start developing on Nvidia chips, it gets the e the Kudo ecosystem stronger and we will actually get more open- source software basically for free from China that will come back to America and make our AI efforts stronger or is it we want them to be familiar with Nvidia when ultimately they come over here on 01 visas and start working for American companies?
1:10:13
>> I I think that that's too narrow focused.
1:10:15
It's sort of like Boeing.
1:10:15
Do you want Boeing in China?
1:10:20
>> I mean, yes, because I want Boeing to be a thriving American business.
1:10:22
I want Boeing to maximize profits, and I don't see the the 747 as a piece of I don't I don't see this the 747 as a nuclear bomb.
1:10:34
the Yeah, I mean I mean I think that that that's the key brier on the second one is like do you think that >> an H2 H200 is a is a I don't know like a like a some form of missile technology. >> Yes. Yes. Yes.
1:10:47
Increasingly I increasingly I I I have I have backed off the idea that that uh these chips should be viewed as uh as weapons >> like a defense technology. >> Yes.
1:10:59
I backed off and >> yeah because I view it much more like telco technology. I agree.
1:11:05
>> And and and like and we did not win at that. We lost that.
1:11:07
And and that was because we didn't offer the world an alternative.
1:11:10
We just were like, "Hey, don't use don't use Huawei." >> Yeah.
1:11:14
>> And then it's like and they were like, "Okay, well, give us something else."
1:11:16
And we were like, "Well, I don't have anything to give you." >> Right. Well, so what are they?
1:11:21
>> We're we're sort of separating things out here because on on the one hand like there's give the rest of the world something and then there's other which is like give China something which is like there is a difference there, right? >> Uh >> yeah. No, no, no, that's true.
1:11:31
I I'm totally down to go belt for belt and road for road all over the all over the globe, right?
1:11:38
Uh but the question of like can like is there any world where we could get a different cell phone tower deployed in Beijing that's not a Huawei tower? Like no way, right? It's just impossible.
1:11:51
>> But but but then you go back to the fact of like you're right like is you know all metaphors fail.
1:11:55
That's why they're metaphors.
1:11:56
So, so the the the other exogenous factors you got to think through that's different from Telos's is the fact of like the level of AI engineering talent and fact like it's funding in as in like you know propelling forward American AI.
1:12:08
That's just the reality of of where we are.
1:12:10
The the second is the fact of like they do not have the foundry capacity or the foundry skill set to produce similarly level at scale.
1:12:20
Uh scale absolutely is true.
1:12:23
they could be at some point uh be approaching some form of like five nanome process and there's like rumors around that.
1:12:30
So that's a little bit of an obsession because it's it is a barrier of technology that like we uh isolate the west has been skilled at not particularly America, Japan and the Dutch but but that's there we don't want to fund that enterprise.
1:12:44
>> Y >> and I think that that's where the pragmatism comes into play.
1:12:45
It's like if we don't offer them something, they'll just do it themselves.
1:12:49
And I'd rather take money from them and build our own sort of re resuring in America.
1:12:55
>> But but to be clear but to be clear, they're still going to do it everything themselves, >> right?
1:12:59
It's just going to take them >> how how does >> I don't think so.
1:13:04
>> You think that China will happily be dependent on foreign product.
1:13:08
>> I mean, last time there were rumors of this sale, they they were putting out press releases saying like, "Hey, if you're gonna buy Nvidia, you got to prove it.
1:13:15
you you got to prove that you need it.
1:13:16
You got to prove that Huawei won't work.
1:13:18
It felt like there was a lot of push back from the CC.
1:13:19
I don't believe buying NVIDIA.
1:13:23
>> I don't believe at all that they're just going to be like, "Thank you for the H200's.
1:13:26
We're going to stop investment in our domestic uh chip uh manufacturing." >> Yeah.
1:13:33
So, but so but but the the problem like in that flow one, you assume a level of CCB control that's just not realistic. Sure.
1:13:39
that that that it's it's a country of like 1.
1:13:41
3 billion people with very successful entrepreneurs. >> Yeah.
1:13:45
But they've been ripping five year they've been ripping fiveyear plans for over and over and over and over.
1:13:52
>> I mean like like Yeah.
1:13:52
But but that stuff doesn't matter.
1:13:53
Like you have to understand that like that there's lots of propaganda that think that they say that they actually never happens in real world. Go look at Africa.
1:13:58
Go look at all the airports and see actually how what actually happened. Go look at the ports.
1:14:03
Yes, there are certain example of ports actually being transferred like the Sri Lanka port, but go look at the rest of ones like they didn't happen.
1:14:08
So, so they say lots of things, but the question is like what matters in terms of the national security orientation of America.
1:14:14
And I would much rather take money from their economy and put it back into our economy than trying to give them both the demand side and the supply side argument.
1:14:23
You're you're making a supply side argument, which I think is very much how CCB thinks about the world, which is like, oh, we need to build our own chip supply.
1:14:29
But in the orientation, I think that Jordy, you're more biased towards, which is like, well, let's also give them the demand argument.
1:14:36
I'm like, no, I don't want to give them the demand argument.
1:14:37
give them the demand argument. like like I I I I would rather mitigate that as much as possible to say that yes like they have uh you know probably like five or six multi-billion dollar operations that like want to have these types of chips that are non-military oriented and by applying these export controls that
1:14:54
are overly extreme you're basically giving them a demand argument as well and I'm saying I don't want the demand argument like they're still gonna have a supply argument that's fine like go buy a BYD you know car and hopefully it doesn't catch on fire like so like you know like like just Because by >> Are you Are you Are you bearish on BYD? You're You're They're catching strays
1:15:10
You're You're They're catching strays right now.
1:15:13
>> Uh I saw one of them on fire in Hong Kong. No joke.
1:15:15
[laughter] >> Yeah, I have video of it. I texted you.
1:15:20
>> Wait, yeah, let's go let's go to the cars and talk about what we were debating earlier.
1:15:23
Um, if if you're if we are just talking about cars instead of chips, of course there's going to be a metaphor here, but if we're just talking about cars and we want and and the frame is like we're we're all China hawks and we're putting on like rah rah, we want America to win the electric car race.
1:15:42
Should Tesla have sold Teslas into China?
1:15:46
because it feels like they did and then China was able to make the a whole bunch of cars that compete directly with Tesla and are it feels like maybe better maybe cheaper maybe better and cheaper on some sort of paro frontier.
1:16:02
Um, if if we run that experiment, we try and think through the counterfactual.
1:16:06
If Tesla had never sold a car in China, where would the the the Sous7 be, the jumping Huawei car, the Xiaomi car, the BYD Han, the one that has the karaoke machine in it?
1:16:19
Like there's some crazy cars. Would those exist? Would they be delayed?
1:16:22
Would they be would they happen faster?
1:16:24
How how do you think about that? >> Yeah.
1:16:28
So, so I I think this is where there is a reality, right, which is that they they're going to copy and but I don't think that that is something we can change. Yeah.
1:16:35
Speaking as a half Chinese American.
1:16:37
So, so it's just the nature of what what is the way they think about >> competition. It's just competition.
1:16:43
You're going to want >> Yeah.
1:16:44
They view competition as copying.
1:16:46
And and importantly like like like the there there's one world where you know they need the industrial power of like 1 million H200's and there's another one where if you give them a single H200 they can tear it down and like try and reverse engineer it as much as possible and then they can also do all the learning curve stuff on their on their companies on their national champions on Huawei.
1:17:09
I I think it's it is reasonable in terms of an argument against expert controls if you view this as a means of trying to slow down their own model level progress >> like like I can at least cogently understand what's being presented.
1:17:22
I do not agree with this from the perspective of hardware engineering >> because again if you don't have the ability to make a car >> Yeah.
1:17:31
then then what's the risk, right?
1:17:34
like like like just mitigate their ability to make a car >> which has generally been my my my position is like I I want to mitigate their ability to make chips and and and so in a world where there's a demand and supply right they in SECP because they're they're communists so they loves focusing on supply solutions to
1:17:52
everything which by the way doesn't work as I mean we're all free marketers here we're all a biased towards Austrian like we know that their philosophy of the world doesn't work so so they they can talk about supply side engineering all they want but again they they don't have the ability right now to aggressively
1:18:09
address their levaker problems and so in that world I want to just win because if they can't if if we remove the demand stuff because all other companies want to use Nvidia >> if we remove the demand stuff we're removing one of the biggest parts the uh that would give them justification to accelerate on the SMIC side but if
1:18:28
they're just going to go and play around and be like hey we're going to dump money into SMIC because we want you local but we're everywhere It's it's like the fast food thing of like sure they have local fast food but McDonald's and Starbucks crush and and so like that that that's more how I think about it. They're still going to
1:18:41
They're still going to try to copy, but if you don't give them the ability to actually have the toolkit, then it's a much safer transaction.
1:18:47
And I think I think I think John what what you said is is important is that the the debate is highly uh mixed up between you think an H200 is an F-35.
1:18:59
If you remove that as an a prior then the world becomes significantly simpler to understand.
1:19:04
But if you view what you know the the the H2 under black wall or whatever as a as a patriot missile then then like there's no real place to like have a conversation to be rational. >> Yeah. >> Yeah.
1:19:17
Because my view is like you know I don't have as much of an opinion on you know GB or B >> that kind of like debate.
1:19:24
I I just I think American companies need to be in China because and because we want the ability to not only address the second uh largest economy in the world and like have access to like that is the Trump position and that's my position like we should sell to the world but we should be an export nation >> but but the other is like China is going to coffee and it's just part of the equation.
1:19:46
Flip flip around for me and give me the sorry >> uh I I wanted to hear flipping I I wanted to hear more shifting to domestic semiconductor supply chains.
1:19:55
Uh what is your theory of the current horse race between uh tranium TPU and Nvidia?
1:20:01
It felt like Nvidia was dominant last year the year before.
1:20:10
Then we were hearing rumblings of like hey maybe AMD is getting it together on the software side.
1:20:15
Hey, maybe this TPU thing could be used to train a decent model.
1:20:18
The Deep Mind team seems to have been able to do that.
1:20:22
Uh, are we moving towards more of an oligopoly?
1:20:24
What are you thinking about how the the you know American semiconductor AI accelerator horse race is playing out?
1:20:35
>> Uh, my my view from the the on the TPU side, I don't really know who would buy that as like just like a product.
1:20:44
I I think Meta is the closest one that kind of makes sense, but why would any of the cloud companies do it?
1:20:49
Because they are in a position right now trying to build their own and they're trying to dele why they're building.
1:20:57
They're trying to delever from Nvidia.
1:20:57
So why would they want to omingle themselves with an actual direct comp, you know, like a a direct competitor and sell their stuff and and then there was [laughter] >> Yeah.
1:21:09
Like like there's there's also this like weird zealatry around TPUs.
1:21:11
I may cuz we had Thanksgiving there.
1:21:13
It's not going to happen.
1:21:15
But to say that like there's like minimal switching costs is absolutely absurd and insane.
1:21:21
There's significant switching costs and and so if you're of the mindset of like hey well we have all this capex and it kind of makes sense and I that's justifiable like I can understand that but that's like the same reasoning that you could apply to uh the multiloud argument and we didn't really see that happen at all >> uh basically until GPUs.
1:21:41
Now, now you're seeing much more multicloud products because GPUs made everyone multicloud.
1:21:47
So, and if you were multicloud before GPUs, >> you were as a function of an acquisition, it was not generally intentional.
1:21:55
>> So, so I think TPUs makes sense for Google just as a like vertically integrated strategy because that's what they like to do.
1:21:59
Y >> and and like there probably some other companies that maybe like maybe Apple I could maybe see that because they love lowc cost chips just in general.
1:22:06
Um, but I don't really see it breaking beyond Google because I just don't know who is really incentivized to buy that.
1:22:13
Uh, and then I agree with you on AMD side.
1:22:15
Their software is getting better.
1:22:16
I think that's just the natural um orientation of of just they they like Lisu is the most reasonable you could say competitor to Nvidia's general purpose computing dominance.
1:22:27
Um, I'm pretty bearish on tranium uh and uh TPUs just from a from a chip perspective I'm bearish on.
1:22:35
But as an integrated strategy, it like it makes sense for them as a company.
1:22:40
Nvidia, that's not really it as >> we're running out of time, but I wanted to ask you about one other thing.
1:22:43
Uh there uh seems to be a number of people trying to manu manufacture a space data center pump. >> Oh yeah.
1:22:52
>> As somebody uh and even Nvidia was posting from their corporate account uh uh uh some renders of a company called StarCloud, some space data centers that they're working on.
1:23:03
As somebody that has spent a lot of time uh in data centers or around data centers all over the world, uh what are your timelines?
1:23:09
Are we talking uh Gavin Baker was saying uh the most important thing in the next 3 to four years is data centers in space?
1:23:18
Had plenty of people on the show that believe that it's an exciting possibility or opportunity, but maybe their timelines are more like 10 to 20 years.
1:23:25
How do you think about it?
1:23:28
>> Uh most of the stuff that has been announced will not happen.
1:23:31
I there'll be >> uh no like then think of it as like a 50%.
1:23:36
So if they announce like 5 gawatt probably going to ding like two and and because this stuff's really building this stuff is actually quite hard and America has not really behaved in a manner to me that believes it's that serious of a of a thing like this is a very niche issue and and one reason why the the going by the H200 the reason why it's making less noise now is because it is it is a niche issue.
1:24:02
is it is a niche issue. It is something that maybe a couple hundred thousand people really care about and and the data center it affects even though it does bring jobs it does bring the these types of opportunities to uh cities that previously never had a position to support a data center which is great it is really kind of a narrow set of people
1:24:21
that are really benefiting uh and if you go look at uh you can go read the bills that are in consideration across America I it the America is not acting like it's very serious about building day centers the power profile files, the approvals that are happening, like it's it's just not happening versus the other countries, they they're generally more serious about it. Um, and many of these
1:24:39
Um, and many of these announcements that you as as Jensen disclosed, they they're they're fundraising announcements.
1:24:47
They're actually not actual projects yet.
1:24:51
>> So, so they're trying to let's say they have an equity already lined up, but but the equity generally is like 10 to 15% of these projects.
1:24:57
So, you got to go raise the other portion of it.
1:24:59
and and the offtake side outside of the hyperscalers there's not a lot of confidence the credit side has outside of the the those hyperscalers.
1:25:09
So so the so the debt side of the world actually has been quite conservative on the these these and the private credit.
1:25:15
So that's why I never really thought like you know the quotequote bubble talk and bursting it it like we're nowhere really there if you go talk to lenders like we're nowhere even close.
1:25:25
nowhere even close. uh the type of capital that's being deployed has actually been very conservative has been aligned with contracts has been associated with high paying credit you know top tier customers we're not seeing you know the Jordy credit union in the middle of uh you know SoCal doing black
1:25:42
you know B300 loans and that happens then I'll be like yeah you know >> working on the like with the so so so [clears throat] that's that that's where if you look at the legal side if you look at the power profiles If you look at what's happening and the political nature of it, I I don't think many of these projects actually scale to what they need to. But
1:26:01
But I do agree with Gavin that like we actually do need to get serious about it because it's not like the world would be worse off with more power, more comput capacity.
1:26:11
If everything all of all those things get cheaper, our entire life gets better.
1:26:16
>> And just as it's cheaper today to get a banana than it was 100 years ago, and that means there's more bananas.
1:26:22
That means people consume more bananas.
1:26:23
So, so the logic will still apply.
1:26:27
>> Let's give it up for bananas. >> We love banana.
1:26:30
>> I'll give you a layup for that. >> I love banana.
1:26:34
>> Uh, great to see you, Aaron.
1:26:35
>> Software is eating software is eating bananas.
1:26:37
Thank you so much for coming on the show.
1:26:39
We We always We shouldn't have booked 15 minutes.
1:26:40
We should have booked two hours cuz it's always a fun chat.
1:26:44
Uh, thank you so much for taking the time. We'll talk to you soon.
1:26:45
Have a great rest of your day. Merry Christmas. >> Merry Christmas.
1:26:51
>> Merry Christmas to graphite. dev.
1:26:53
Code review for the age of AI.
1:26:53
Graphite helps teams on GitHub ship higher quality software faster.
1:26:57
What's under the tree this Christmas? It's graphite. dev, baby.
1:27:03
Put it in your It's a great stocking stuffer.
1:27:05
Um, up next we have Matt Callish, the co-founder of DraftKings.
1:27:10
He's a board member at DraftKings.
1:27:13
He's also a board member of FaZe Media and he's the founder of Hard Scope, which launches today.
1:27:18
Let's bring [music] him in to the TBP and Ultradome. How are you doing, Matt?
1:27:24
Great to thanks so much for taking the time. >> Hey, guys. How's it going today? >> It's going fantastic. Merry Christmas. >> Good to see you. >> Merry Christmas.
1:27:33
>> Uh please, for those who don't know you already, I'd love to kick off since this is the first time on your show with a little bit of your background.
1:27:39
You have uh one of the more interesting backgrounds with DraftKings.
1:27:42
H how do you tell the story in, you know, in just a few minutes?
1:27:49
Well, I had a couple friends from some early corporate jobs in my career.
1:27:52
You know, I came up through analytics technology and then over the years moved more into marketing and uh you know, I met some of uh you know, my two partners, Jason and Paul really at those jobs.
1:28:06
You know, Jason at Capital One.
1:28:06
We were early stage business analysts >> and then uh went to a company called Vista Print.
1:28:14
That's where we learned direct marketing and >> you know we all had this entrepreneurial bug and we're really looking for the right opportunity to go and spin off and do something kind of in the startup world >> which you know we had no experience doing but um >> you know we we had that drive.
1:28:32
So we looked at a million ideas and then DraftKings kind of stumbled along.
1:28:36
um we just felt like there was a lot of people that like predicting things in sports but didn't really have a great way to do it.
1:28:44
So >> that was back in 2012.
1:28:46
We launched the daily fantasy sports platform.
1:28:51
>> Um over the course of a few years grew that to over 10 million registered users and it became just kind of a big cultural phenomenon.
1:28:59
And then uh come 2017 that's really when sports betting started opening up in the US.
1:29:05
So, DraftKings was in a really great position to extend our product.
1:29:08
Um, launched a sports betting platform first in the US uh outside of Nevada and uh became a market leader in that space and then over the years just kept developing out the product, went public in 2020 and you know, it's been a really amazing ride.
1:29:28
I mean, a growth story that um you know, I'm really proud of. >> Yeah.
1:29:32
uh take me through I I'm sure there's a ton of questions that we can kick around around prediction markets and sports betting and what's going on there, but uh first take us through the launch today.
1:29:42
Take us through hard scope.
1:29:44
How are you positioning that?
1:29:47
>> Yeah, I had a 14-year uh run at DraftKings that, >> you know, we've seen it all, the ups and downs, and you know, built a really amazing team over the years.
1:29:56
I have, you know, the type of team at DraftKings where if I don't come to work for a week, things are amazing and fine.
1:30:04
I'm telling you, like the caliber, the people, the leadership there, the team has been built out just so well.
1:30:10
And >> um, you know, I'm a builder at heart. I like starting things.
1:30:17
like starting things. I like participating in industries that are disruptive, you know, um that are in the middle of a lot of displacement change and a couple years back I worked with one of the original founders a phase to buy the
1:30:33
company off the public market and bring it back private >> and it's kind of a space that I'm just super intrigued by the massive amount of disruption in media moving from traditional forms into creatorled to community um this sort of
1:30:51
decentralized media through social channels and uh I've also found it really intriguing how content discovery has changed so much like short form clipping and you know the Tik Tok the shorts that's how people are really
1:31:05
finding content these days and phase is really one of the best in the world at that so just kind of jumping in >> uh rebuilding the business side of that team and uh kind of relaunching and bringing FaZe back to number one in creator media. That was a you know
1:31:20
That was a you know initial focus and um I decided to leave DraftKings and transition out to do this full-time to launch Hearts Scope which is um kind of the platform that FaZe operates on.
1:31:33
It's a talent and brand platform to access the creator economy at scale and it's a space I just think is tremendously underserved and a really massive market opportunity.
1:31:44
So, um, you know, I felt like it was the right time for me to go all in on that and I'm really excited to be doing it.
1:31:52
>> So, what's the like like walk me through how to actually use the pro uh the product if you're a brand?
1:31:58
Does it feel like just a autonomous marketplaces where brands are meeting creators?
1:32:02
Are there >> Yeah, I guess I guess a better question is like there's probably there's probably been >> How much handholding is going on?
1:32:11
There's there's been maybe hundreds of attempts at building these sort of like brand creator marketplaces.
1:32:15
A lot of them uh haven't uh some have turned into great businesses.
1:32:22
There's been um >> well we were just talking >> little to no like venture Friday Shopm is is is like sort of in the same space. Correct. >> Yeah.
1:32:31
Greater commerce tool but this is more advertising focus. Is that is that correct?
1:32:40
What's special about hard loop is the the impossible part is building the actual valuable content assets that you know brands want to be a part of and reach the audience and that's what our team for talent does really well.
1:32:53
It's a full stack operating platform like you literally don't need any other resources.
1:33:01
We do it all inhouse production, socials, clipping, all the distribution side into commercialization like brand partnerships, e-commerce, uh access to capital and venture for initiatives and the reputation really of phase as the number one creator collective in the world is the proof.
1:33:20
collective in the world is the proof. I mean that's a group that operates with this team on this capability set and so hard scope is really bringing that to new creator collectives in more verticals really high potential talent and platforming them to really make the most of you know the opportunity that
1:33:40
they have which is really unprecedented like the level of power and control over um the content their community and how to commercialize it that talent have today It's um it's a totally new age really and some creators have built out great teams but most really have under represented teams in particularly the commercial side. You know like how do I
1:34:02
You know like how do I take my great content and then maximize the opportunity as basically the CEO of a media business and special for talent.
1:34:14
>> I yeah I think I think I was a little bit confused.
1:34:15
So you're effectively like a back office for personality personalities, content creators, whatever you want to call them, to help manage everything from ad ad sales to editing to clipping, content distribution, effectively social media management, like kind of uh am I saying that correctly? >> Yeah.
1:34:39
I mean, the the landscape is laden with middlemen.
1:34:42
Let's just say like the LA ecosystem is unbelievably brutal.
1:34:49
There's middlemen for everything and we're trying to provide really a full stack solution where you don't need all of this noise to run a really successful business.
1:34:59
You need a great business partner, a great team and we've proven that with the operations of Faze Clan and how that's come back into, you know, prominence as the number one creator collective.
1:35:10
I mean, you're talking about a group that had the top seven accounts on Twitch last month that's growing in an unprecedented rate and people thought it was dead two years ago.
1:35:19
So, like we came in, relaunched the brand and totally turned that around and that is the proof, you know, that's the proof of concept really that I think is attracting so much interest from other talent in other verticals.
1:35:31
And um, you know, you had asked about the brand side, that's more my background.
1:35:38
You know, I was a large media buyer at DraftKings.
1:35:42
We have, you know, as you've probably seen a lot of advertising out there in the world, probably bought every channel you can think of.
1:35:48
And the one channel that's hard for everyone is creator direct partnerships. >> Yep.
1:35:55
>> Nobody does this well.
1:35:55
And unless you are a pure play specialist where your number one marketing strategy is through creator, you probably are doing this not so well right now.
1:36:06
and traditional agencies who try to tack on things like YouTube buying or other, you know, creator products tend to not do that very well at all.
1:36:16
So, um, we're seeing a lot of opportunity on the brand front to be almost like a new kind of agency of record, right?
1:36:24
where we can focus just on creator direct partnership help kind of bifurcate that channel out from a lot of people just lump it in with audio or other other kind of traditional definitions of channels.
1:36:36
Um the opportunity is really breaking out creator direct into its own lane and maybe it's 2 or 3% of media mix today but the landscape is changing.
1:36:46
This channel might be 20 30% of people's media mix in the future.
1:36:52
I think Unilever said it's over half of their media mix in the next year they're planning.
1:36:58
So like a lot of companies are seeing like we are just not reaching Gen Z audiences that are diverse under 30 are just not watching traditional media and this is the way to reach them. >> Yeah. >> Yeah.
1:37:12
Makes makes a lot of sense.
1:37:12
How how are you uh how are you like financing hard scope?
1:37:15
Do you have outside investors?
1:37:17
Was it >> uh am I hearing it correctly?
1:37:20
it was you effectively took phase private and is it the same entity or I'm curious how uh like how you're planning to scale is this something that you want to just operate profitably uh indefinitely or or is this you know something that uh you would one one day want to you know take public again?
1:37:43
>> Yeah, look I mean I've been funding it.
1:37:45
I led the acquisition initially and the biggest reason was it was a kind of a mess.
1:37:50
mess. I mean the public company of phase was in really rough shape and it needed a lot of work and putting in the two years to really rebuild the entire operation and also to relaunch the brand of phase have that you know in such a
1:38:06
great place today that was the upfront investment I viewed as getting the ball rolling kind of building the initial momentum and uh I didn't think it made a lot of sense to you know involve a ton of people in that I thought it was something we had to prove as a team here. So there's no noise in the
1:38:23
So there's no noise in the company.
1:38:25
There's no outside you know in investors funding.
1:38:28
I do think in this next stage now that we've launched as we scale up there's a lot of interest I have and the team has in certain strategic partners.
1:38:37
So I think in including people that can be helpful to us. Um absolutely.
1:38:43
I mean that's something that we're going to be looking to do in the next year. >> Makes sense.
1:38:47
Um little bit of a connection issue by the way. Sorry. Sorry if there's a lag.
1:38:51
Uh have to ask you about your kind of personal views on the state of both uh traditional sports books, online sports books, gambling platforms as well as prediction markets.
1:39:06
Uh it's absolutely uh bloodbath on the timeline right now.
1:39:09
Uh everybody involved seems to hate each other.
1:39:11
Both the even the even the investors on every side of it.
1:39:16
uh and uh it's an absolutely wild time right now.
1:39:19
Uh how how do you think this kind of category evolves over the next 12 to 24 months? >> I mean I love it.
1:39:29
It's this is one of the most competitive spaces in the world, right?
1:39:34
Like you had mentioned with with the creator economy, it's very competitive.
1:39:38
All these different companies doing this or that. Like great. I love that.
1:39:42
Like there is nothing better than having a super vibrant competitive marketplace for products, having to compete and win for customer engagement for loyalty.
1:39:52
Um there's always some curveball in in gaming, in gambling, in sports betting, whatever.
1:40:01
Something new every year, some new competitor, some new kind of product variant.
1:40:06
And uh I think the exchange like how fast that's kind of come in since the election and evolved into a sports product.
1:40:14
Um you know it's it's a fascinating thing and uh I think it'll be very competitive.
1:40:21
You know DraftKings obviously announced they're launching an exchange.
1:40:25
Um pretty much everybody I think in the sports betting space has some plan here.
1:40:29
And then there's the cowshi poly market, you know, that uh rivalry.
1:40:34
And um we just look forward to competing.
1:40:38
You know, I feel like DraftKings has proven world-class technology team.
1:40:42
We deliver leading products.
1:40:45
We have the best customer satisfaction in the market. We pride oursel on that.
1:40:49
So, um competition's our favorite.
1:40:53
It's like something that drives us. >> That makes sense.
1:40:57
Uh what what percentage of uh content targeting men online do you think is entirely dependent on either gaming uh ad revenue?
1:41:08
It feels like there's huge swasts of the internet that uh honestly like wouldn't really exist or creators who uh I'm I'm curious if you have any kind of internal estimates even >> like creator media.
1:41:21
Oh yeah, it just feels like I I can think of a lot of >> soccer was on the show talking about like he he was saying like there's a bubble in sports podcasting specifically because of all the sponsorships that come from uh sports books.
1:41:33
It's actually made it's made a lot of people in the creator economy be able to go full-time because they've been able to have >> I just think a lot a lot of creators where you look at their business and you're like okay >> 90% of your revenue >> uh is from uh you know either yeah some type of you know online casinos or sports books etc. >> Yeah. >> Yeah.
1:41:55
>> Yeah. It's such a valuable category that you know going back to hard scope and expanding beyond just Faze Clan which is a sort of >> mass market super mainstream media business you know going into verticals
1:42:11
like sports really aggressively you know sports food like the content verticals that have a lot of really attractive partnerships is that's kind of the whole purpose here is to represent the creator economy across all of the verticals at scale for brands. And in sports, you can
1:42:26
And in sports, you can build out entire content properties and [snorts] invest in them knowing that it's going to be supported through some kind of deal, some kind of partnership.
1:42:39
It's one of the sure things.
1:42:39
So >> yeah, >> I feel like as a company that builds assets, that makes content from scratch, puts together creator collectives from scratch and scales them, like um we can invent these things knowing that the sports landscape it's so vibrant that there's going to be deals there.
1:42:59
like the idea [clears throat] of betting on food.
1:43:00
[laughter] You said that you're working on food channels and I think that uh like that that's one area of the creator economy that has not been financialized yet and that feels like fertile ground to me.
1:43:11
Uh obviously business >> don't threaten me with a good time. >> Exactly. Exactly. I don't know.
1:43:15
I don't know exactly how it would work.
1:43:17
It's like I'm going to bake this cake.
1:43:18
We're going to do a blind taste test.
1:43:20
Whoever likes this more, they win.
1:43:21
But uh I'm sure there will be an attempt at at at financializing baking channels in the future.
1:43:28
Uh the great British bake off.
1:43:28
I mean there's probably a prediction market on.
1:43:32
>> Will I burn the cookies or not?
1:43:34
>> Will you burn the cookies or not? That's a good question. I don't know.
1:43:35
Anyway, thank you so much for coming on the show. This is a lot of fun.
1:43:38
Congratulations on launch and uh we will talk to you soon.
1:43:42
Have a great rest of your day and merry Christmas.
1:43:45
>> Hey, thanks for having me.
1:43:45
Merry Christmas and you know love to come on again in a year and give you some updates on all the great stuff we're up to. >> That' be fantastic. >> That'd be great.
1:43:52
anytime you have hot takes too on uh anything gaming or prediction markets related.
1:43:56
I know it's a little tough since you're still on the DraftKings board.
1:43:59
You got to keep that in mind.
1:44:01
But uh but we appreciate the insight and uh congrats to the team on the launch. >> Thanks so much. >> All right, guys.
1:44:07
>> We'll talk to you soon. >> Cheers. >> Goodbye.
1:44:09
>> And uh let me tell you about public.
1:44:09
com investing for those who take it seriously.
1:44:12
They got multiasset investing.
1:44:14
They're trusted by millions. Public. com.
1:44:18
Uh, in a groundbreaking endeavor, the University of Utah Athletics is entering into what could be a $500 million equity partnership with Oatro Capital, featuring the creation and shared ownership of a for-profit entity to operate athletics.
1:44:34
Sources tell Yahoo Sports.
1:44:37
So, college football is going to the big leagues.
1:44:40
They're going to the private equity leagues.
1:44:41
Private equity is now going to own your local college football team.
1:44:46
Oh, people absolutely hate this. >> The problem. I I know. I hate it, too.
1:44:52
Because here's what Why are they stopping with college football? Please.
1:44:57
High school football, >> lower school, little league, >> preschool, >> preschool. Let's financialize that.
1:45:04
Let's get Let's roll them up.
1:45:04
We actually, this is happening.
1:45:06
We talked about the We talked about the uh the hockey rinks that have been sold to private equity rolled up and then you can't film your own children without paying for the the >> Somebody out there that really hates private equity just yesterday was saying, you know, private equity has come for everything, but at least you can still go to a college football game. >> I don't know.
1:45:25
>> Uh and and uh again, so how do we think they're going to you know, so uh sounds like they effectively sold for half a billion dollars. They just sold.
1:45:33
billion dollars. They just sold. You remember it was Chicago I think sold all their streets or their parking meters sovereign back in the day it was like for like 75 years you got to get the you got to get the money you got to get the deal right
1:45:48
>> yeah so so they they they basically buy a college team >> you can say that it's some more sophisticated structure than that but effectively that's what happened >> uh they'll have to immediately put draft kings or prediction market logos all over the helmet [laughter] and all all over the jersey. So that's that's
1:46:04
So that's that's probably that's probably uh that's probably like a $50 million uh new new revenue line that the college could never do. >> Yeah. >> Uh what else?
1:46:14
They could >> So the current mascot for the University of Utah is Swoop, a rail a red tailed hawk. >> That's pretty cool.
1:46:21
>> They could change it to drafty [laughter] >> drafting off the draft.
1:46:25
Okay, so another thing they could they could increase if you want season tickets to the game and you're a student, >> they could of course they're going to jack up the prices.
1:46:34
They're probably going to make it like $20,000 a year. >> Let me steal, man.
1:46:37
You're being too negative here.
1:46:39
>> $20,000 a year and they're going to offer the private equity firm can bring a private credit partner into the mix and and help finance the season tickets.
1:46:48
So, you don't just graduate with student debt, you actually graduate with uh game day debt that will stay with you for decades. >> It's ridiculous.
1:46:55
I mean, there there are so many reasonable ways to monetize a football team over, you know, the entire life of of of ownership for this firm. >> Sell the windshield. They could sell. >> Yes. Yes.
1:47:04
It's very funny to sell everything, but uh I mean, there is something that actually could be very good for academics at this school because if you have $500 million in cash, you can go and build a new library, a new science lab.
1:47:16
You can go build like actual academic buildings. Yes.
1:47:20
You don't really need to and you don't need to worry about like, okay, we got this donor.
1:47:24
Somebody went to the University of Utah. They hit it big. They're a billionaire.
1:47:28
They want to donate $500 million, but you know what?
1:47:31
They just like football, so they're going to build us a new stadium.
1:47:32
And you're like, but wait, wasn't the point of this whole thing uh you know, unrestricted gifts?
1:47:36
Wasn't it wasn't the point academics?
1:47:38
And uh and that might not that might be less of an issue now.
1:47:43
So they might be able to fund more great academic uh activities and endeavors with this money. So I I don't know.
1:47:48
It's very funny to make fun of.
1:47:51
It's very funny to to riff on, but there are some there are some potentially really good uh really good outcomes that could happen.
1:47:59
Um anyway, we have our next guest in the reream waiting room.
1:48:02
We have Emil Michael, the under secretary of defense for research and engineering of the United States. Emil, good to see you. Merry Christmas. How are you doing? >> Welcome to the show. >> I'm doing great. >> Thanks for having me.
1:48:16
>> Thank you so much for taking the time. You look fantastic.
1:48:17
Yeah, I would say thank you for wearing the suit, but unlike a lot of our guests, this is a daily driver, I'm sure. >> Yes. Yes.
1:48:25
>> Uh, >> well, we were buying a high school football team today, so I had to dress up. >> Oh, nice.
1:48:29
That [laughter] that that would be a real treat.
1:48:30
Uh, well, you're not you're you're [clears throat] Is it Is it fair to say that you're buying Gemini? Are you buying tokens?
1:48:38
or is this one of those deals where uh it's the partnership is structured so that it's not really uh you know a major cash infusion for Google or it's not a burden on the taxpayer uh it's a little bit more of uh just two great American institutions working together.
1:48:54
How are you framing the deal?
1:48:55
Um it's it's uh making to three million Department of War employees that includes military members. Yeah.
1:49:05
>> And civilians access to Google uh Gemini on the our network which is a private network, right?
1:49:12
So it's you actually have to port it over. >> Okay.
1:49:15
>> And they gave us a great deal for the first year. It's like 47 cents.
1:49:17
So [laughter] >> So they're very patriotic.
1:49:20
I'm super excited to to have that in the hands of everyone at the Department of War.
1:49:26
It's never happened before. >> Yeah.
1:49:29
Um were there historical examples that you were pulling from like like because I imagine that service members have been googling things for a long time.
1:49:38
Uh I've heard stories about I mean even during the during the war in the Middle East uh the war on terror there were using Google maps just to see satellite imagery.
1:49:47
Uh, and there are a whole host of reasons why a war fighter might want to use a Google product.
1:49:50
Uh, is this a new structure?
1:49:53
Are you building on the shoulders of giants?
1:49:55
Do you feel like when you came in there, the Department of War had uh, a good a good reference point for how to work with a big tech company like Google or was it sort of new territory?
1:50:06
Uh, how did you think about actually interfacing with Google?
1:50:12
>> I mean, it's entirely new territory, right?
1:50:13
because you could get those apps off the app store or on a web browser.
1:50:18
So to get AI in there's a lot of sort of fear about AI what it could do and then you have to remember when you're doing a Google search like yeah it it kind of records where you're searching but if you're putting stuff in AI >> you don't want that to leak back into the model so you have to architect it in a unique way.
1:50:36
So it's kind of new territory and we did it all in like three months. >> That's amazing.
1:50:40
Uh yeah, what did the team on the Google side look like?
1:50:42
Is this I mean I imagine that they have a you know a large uh team just for working with the government.
1:50:49
Um uh you you mentioned a few uh it was a few weeks of work.
1:50:55
Uh but what what did they bring to bear to actually deliver this on their side?
1:51:00
I mean they they had a ton of engineers >> um because you got to put it you know in our networks which are not simple right and you have three thou three million people all over the world all kinds of um devices and so on.
1:51:13
So they really brought the heat right they and they had a you know for today for launch they had a a room or they you know war room if you will no pun intended and as did we to make sure that it launched it launched correctly.
1:51:27
I mean, we got a lot of a lot of flack on Twitter today. >> Yeah.
1:51:30
Because So, yeah, I saw these comments, but it was very obvious if you used one brain cell that you needed to be on a on a on an actual approved device on a military network if you wanted to access the service.
1:51:41
So, uh I didn't I didn't I didn't get the flack. >> Yeah.
1:51:46
Well, people want to give flack just to give flack, right?
1:51:49
>> [laughter] >> Well, I think some people wanted to they wanted to try it out themselves and it's like, well, if you want to do that, you can join uh become a service member. >> Yeah. >> Yeah.
1:51:59
We put a we'll put a we put a link on the error message a few hours ago for job openings at Department of War if they want to join.
1:52:05
So, they get access to Gemini for government. We're open for business. >> Yeah.
1:52:10
What what what else is uh have been the highlights of the year as you look back on the year?
1:52:13
Uh obviously confirmation took time but then uh there was this big uh White House AI action plan.
1:52:21
Uh what are some key moments that you feel like uh have been maybe under discussed or under didn't get enough appreciation at the time?
1:52:32
>> I mean you know there have been like three AI executive orders which is a big deal right and Jensen said the other day that no other administration has ever done this much for the AI companies.
1:52:42
So we're really championing championing like these four national champions, right?
1:52:48
Google, OpenAI, Anthropic, and XAI.
1:52:52
>> Um, and giving them like we're talking about, you know, data centers on military land.
1:52:56
We're talking about how do we get more power to these uh these companies because it's it's a race and I think we're the first group in the last six months to to really realize that we better get great.
1:53:08
We better [clears throat] get better and stay great and ahead of everyone else on this because it's really the next generation of tech.
1:53:16
>> On the subject of data centers uh on military bases or land, what kind of comps have you looked at on that side?
1:53:21
I know there's like a historically in in weapons manufacturing you have like go which seem like you know they would provide some framework.
1:53:30
Uh but how how have you thought about that?
1:53:35
>> We haven't thought about that yet.
1:53:35
>> We haven't thought about that yet. we're we haven't broken ground yet or to the business models we just had the executive order said we're going to do it >> and then we got to figure out um how do you prioritize who gets what right and we may reserve some of that data center capacity just for the government to use
1:53:51
for our own purposes but the point was to send a message that we're all in on AI companies all in on the data center power chip needs of these companies in a way that the last administration we think was just trying to constrain everything with these orders to to really uh you know have one company win and that's it so they can control sort of the outputs. We're not we're going
1:54:11
We're not we're going the other way.
1:54:13
We're going to have all the national champions.
1:54:14
We're going to support them all the way.
1:54:15
You know, David Saxs is out there making sure the American tech stacks and all other, you know, as many other countries as it can be.
1:54:23
>> And that's a big deal, right?
1:54:23
It's, you know, if anyone's going to be using AI, we want them to be on our stack. >> Yeah.
1:54:28
How do you think about the the the the fact that uh all of the big tech companies uh seem to be working with the United States government effectively for free? 47 cents.
1:54:38
I've heard of deals of of a dollar as as high as a dollar.
1:54:41
Um but then I think back to, you know, a few decades ago where Microsoft had a deal to develop virtual reality headsets, augmented reality headsets for the US government and I think it was like a10 billion deal.
1:54:54
And I was really excited when that project went over to Anderl because it's a lot, you know, younger faster moving company. Now I love Microsoft.
1:55:02
I love them as a infrastructure provider and the and the fact that they have OpenAI's IP is amazing.
1:55:08
There's so there's a ton of great things that that uh that Microsoft does.
1:55:11
But developing an AR headset that always felt like it was going to be a rough go.
1:55:16
It was such a big such a big burden on the taxpayer at10 billion.
1:55:18
uh much better to see it in a different uh in a different uh land in a different company.
1:55:25
How are you thinking about when the how the government is working with big tech, when to open up the pocketbook and write a billion dollar deal or when to ask for, you know, 47 cents?
1:55:36
>> I Yeah, I think, you know, we want these companies to be successful, so we're going to pay them market rates eventually.
1:55:41
It's just >> how do you get out out of the gate?
1:55:43
you get out of the gate by giving 3 million people access and not having to worry about like a token count every every day, right?
1:55:53
And then that's exciting to them because >> now they get 3 million more customers, right?
1:55:58
And they get to learn use cases and so on.
1:56:00
So, >> um it kind of works for them, works for us, but we need to pay them fair fair rates, but they're going to be commercial. >> Yeah.
1:56:06
>> Yeah. And I imagine that uh there like when a new technology comes up like you know Gemini uh there's just a lot of service members that are just you know not uh by no fault of their own just like accidentally using it a little bit too cavalierly and this is an initiative
1:56:25
to actually refocus on security refocus on privacy but can you take me through some of the you know I'm not particularly worried about about uh Google having you information from the American war fighter, but I am worried about some of the international uh chat bots having access to the American war fighters prompts. Uh can you take me through how
1:56:45
Uh can you take me through how the Department of War is thinking about uh LLMs like Deep Seek, Alibaba, these other AI models?
1:56:54
Um are those just banned everywhere?
1:56:57
How do you think about actually um you know banning different uh different you know vectors of attacks from a security perspective? >> Yeah.
1:57:06
Well, I mean first of all we're going to train you everyone is going to train if they want to use it for like you know higher risk use cases, right?
1:57:14
But this is going to be on their devices just like the web browser is and they could still search Google.
1:57:18
Um, but when it comes to the foreign companies like DeepSeek and Chinese, like in the bill that was just released by Congress, I think yesterday, we're going to ban, you know, Deepseek and all these uh foreign models from use by do members and contractors and anyone who touches it because last thing we want is for those models to get data on how we're using uh AI, right?
1:57:42
That would be that would be a a tragic mistake.
1:57:44
So, uh, I think we're we're already there, but we're going to it's going to be in law pretty soon. >> Yeah.
1:57:50
>> Uh, what's your what's your pitch to, uh, talent to come work with the Department of War, uh, specifically in AI?
1:58:00
It's like the craziest talent war, uh, of our lifetimes, most likely.
1:58:04
you know, you're trying to recruit people that can go get uh I don't know, anything from a million dollars a year to $100 million a year to a billion even [laughter] up to some people literally a billion dollars.
1:58:18
>> And so and so I imagine you have to have a, you know, pretty dialed in pitch to recruit people and it's and and maybe that pitch is you're going to be able to work on I mean the H200 news today says that, you know, we aren't the you know, the H200 is not like a F-35.
1:58:29
It's not military technology yet, but I'm sure there's a pitch >> to work with you and your team on applied AI in a military context, but what do those how do those conversations go?
1:58:44
>> Yeah, so I I call them recruiting Tuesdays, right?
1:58:47
I spend all afternoon Tuesdays calling, dialing for dollars, emailing, referencing, interviewing, and my whole team does that.
1:58:54
my whole team does that. and uh like the pitches like you know okay you have to have some patriotic instinct obviously but then maybe you're in between companies or you're just motivated I mean Elon has five companies and he still worked at the government for like seven months and brought a ton of Doge
1:59:11
people who are motivated by the mission so I'm trying to motivate people by hey this is the biggest technology deployment in the world there is no bigger organization than department of war there's no more exquisite crazy interesting use cases is whether they're intelligence, war fighting, you know, even corporate use cases and you get to be part of creating that. It's never
1:59:30
It's never been done before.
1:59:32
It's a pretty good pitch.
1:59:33
And then if you when you leave the Department of War and you've done that, uh I think you get more valuable in the private sector, right?
1:59:39
All these big AI companies now have big federal businesses.
1:59:43
they all have sort of um cooperating with like the government in different ways and you're even you have another notch on your belt of good stuff that you've done and been an innovator on which is pretty rare in government to like literally innovate while you're sitting in the job on something that's never been done before that's that big. >> Yeah.
2:00:01
How how do you uh >> how do you think about the um the different levels of AI diffusion, AI integration where AI can actually help the war fighter in the American context.
2:00:15
I mean a lot of people uh kind of watched the Palunteer story evolve over the last few decades.
2:00:20
this idea of of analytics, just putting dots on a map, sometimes that being enough to identify where an enemy threat might be, for example.
2:00:30
How do you think about integrating AI from the most mundane use cases of just speeding up a little bit of paperwork here and there to some of the bigger questions that will be ultimately face the the the war fighters of today? >> Yeah.
2:00:45
I mean, imagine on like the most simple use cases just like any big organ like an employee in any big organization, right?
2:00:52
You're it's writing PowerPoints for you, writing job descriptions, like making spreadsheets, the basics. Yeah.
2:00:59
>> Then there's like the cool intelligence use cases.
2:01:00
Imagine that we've got decades of satellite imagery, decades of that or sensors that we've had or, you know, all all kinds of things.
2:01:08
And now you could instead of one human analyst having to go like I think I see that there you you can go back through 50 years train a model and say look for things you've never seen before right >> um and then on war fighting logistics planning you know all kinds of uh simulations if you want to simulate a war game >> and a really incredible way with all the data and all the stuff in there.
2:01:30
So it's like pretty pretty compelling, you know, and exquisite to mundane that you could do with this stuff when you deploy it the right way. >> Yeah.
2:01:39
How do you think about the I mean this partnership with Google?
2:01:42
Uh it it feels very much like giving you know the almost the consumer product of Gemini to everyone in the military.
2:01:50
Uh how how are you thinking about larger projects that might require bring together custom code, multiple systems, multiple pieces, you know?
2:02:00
I mean just as a consumer we're running into things where anthropic might be better for coding and one day and the nano banana is better for this and chatd is good for deep research and if you want to build a business we see a lot of startups pull three different models off the shelf uh is that are is that something you're starting to look at as like a phase two of AI integration into the military?
2:02:22
Yeah, I mean we're so ideally we'll have all all four models >> and all four of the newest versions like uh all the time at every classification level. Wow.
2:02:33
>> And the reason you want to go up through the classification levels is so you can do more exquisite work, right? More complicated stuff.
2:02:38
Um and then the reason you want all models is just what you said.
2:02:43
If you're trying to write code, maybe you want to use claude if you're trying to do these other things.
2:02:46
So as they compete, we want to benefit from it.
2:02:49
And we've never had that here before.
2:02:50
So it's it's trying to consumerize it, give choice, but then give more and more capabilities as you go up the chain of like uh of security classification. >> Yeah.
2:03:00
Who who who owns the data?
2:03:00
Does the taxpayer own the data?
2:03:04
Does the government own the data?
2:03:05
I see a lot of stuff where it's like, oh, this this company now owns Google's going to have your your government data.
2:03:09
Google's going to have the the data.
2:03:11
It seems like they might be storing the data in some points, but they don't have authority over it.
2:03:18
How do you frame to like the American who's maybe worried about government overreach or or or wants to understand where important critical military data is living? Who has control? Who has final say? >> Yeah.
2:03:32
So taxpayers own the government.
2:03:35
Government owns the data on behalf of the taxpayers. Google does not own it. We control it. Yeah.
2:03:40
>> Uh it doesn't leave our control.
2:03:43
>> Um and that's that's why it was complicated to actually launch, right?
2:03:47
because you like AI models are built so that they learn as you continue to query them, right?
2:03:51
And and to make it such that the model we got the latest model and it took in queries but then the learnings from that don't go back into the general model y >> is a form of making sure that the American taxpayers data doesn't leak anywhere else and just use for the purpose it was intended. >> Yeah.
2:04:08
How many other organizations globally, you know, allies, things like that need to take on pro like a project like this?
2:04:16
Like it feels like you clear clearly it's very important to move quickly because if you if 3 million people can't use the latest AI models uh in a in a secure way uh you know that that it's not it's not super sustainable.
2:04:31
They'll eventually you know go elsewhere to get these products.
2:04:33
uh do you think a lot of other kind of groups need to you going to pursue a project like this and are you guys trying to help create kind of a framework so others can can benefit?
2:04:45
>> Yeah, I mean any well so we all know and you guys know any large organization needs to be using AI just for efficiency purposes right and and just you know dollars and cents if your competitors you know showing more profit in in Q1 relative to you because they have too much overhead that could be solved with AI you're going to be in trouble.
2:05:03
So when you talk about governmental organizations, should every government be using it in some degree? Yeah.
2:05:08
I mean it's it's sort of like an economic imperative, but it's like a strength imperative too.
2:05:13
Um it's sort of like the way I describe it to people is you're opening the human context window.
2:05:18
So we're not replacing a war fighter, but we're allowing the war fighter to be to do more with the same amount of time, right?
2:05:25
To analyze more intelligence, to do more scenario planning and all that.
2:05:30
So, I can't imagine any other organization like ours that wouldn't be thinking about this.
2:05:33
Um, but hopefully I think we we are setting the pace here.
2:05:38
We're going to be the pace setter here for the US government and for governments around the world. >> I love it.
2:05:42
Well, thank you for setting the pace.
2:05:44
Thank you also for coming on the show today. This is fantastic.
2:05:48
>> It's fantastic to have you and thank you uh thank you for all the work that you're doing. >> Yes.
2:05:52
>> On behalf of you guys. Thanks for having me on. >> Every citizen. Come back on anytime. >> Anytime. Always. >> All right. Thanks a lot, guys. Have a great meal. Goodbye. Bye.
2:05:57
Let me tell you about profound.
2:06:00
Get your brand mentioned in chat GBT.
2:06:01
Reach millions of consumers who use AI to discover new products and brands.
2:06:06
Um Patrick Collison had a post that hit the timeline rocked the timeline with 1. 3 million views.
2:06:12
He says, "Two conversations this weekend make me think that there's a vibe shift a foot in Silicon Valley around what one should work on and what is worthwhile.
2:06:24
Culturally, it feels like the moment is ripe for new frameworks.
2:06:26
One Davos expert morality is stale and >> discredited.
2:06:31
>> Let's give it up for the experts.
2:06:31
Joe Rogan, [applause] Andrew. >> Yeah, Lex.
2:06:36
>> Those guys don't podcast Davos. They don't. They're not Davos.
2:06:39
>> It's very possible the next Davos could just be a round table between Joe Rogan, Andrew Huberman.
2:06:45
>> Yes, >> the real expert Chris Williams Freedman. We'd love that. That would be fantastic.
2:06:50
Uh, it's also apparent that the quote just be superbased counter enlightenment is not really an answer.
2:06:57
Yes, woke went too far, but simply inverting it does not work. Good point.
2:07:02
Uh, effective altruism is no longer the automatic default for smart people. They pushed it too far.
2:07:07
They tried to save too many shrimp from the their farming fates and now they are cooked. >> Sorry shrimp.
2:07:15
There is increasing skepticism of slot and slot machine dynamics.
2:07:21
People don't want to work on a slot machine.
2:07:24
They don't want to work on a slot machine.
2:07:25
They want to work on something worthy and valuable.
2:07:27
The question is overall, what is worthy and valuable?
2:07:32
It feels like this question is becoming more central.
2:07:34
What do you think is worthy and valuable?
2:07:38
>> I think uh it's worthy and val valuable that OpenAI hired Slack CEO Denise Dresser as chief revenue officer. Hm. >> It's the scoop.
2:07:47
It's happening right now. >> Wait, what? What?
2:07:50
>> OpenAI has hired Slack CEO Denise Dresser, chief revenue officer.
2:07:54
>> That's that that that really flipped me for a second because they have a CFO.
2:08:00
They have a CEO of applications.
2:08:00
Uh I don't know where CRO fits in, but they got someone.
2:08:06
And that's very exciting. Um is that gongworthy?
2:08:08
Let's >> I think it's very gongworthy.
2:08:12
Uh, and in other news, we got some new SpaceX news from Bloomberg. The chat had it first. Thank you guys.
2:08:19
We were in the middle of chatting with Emil, but uh SpaceX plans to go public at a $1.
2:08:24
5 trillion valuation up from the rumored 800 billion uh just uh last week.
2:08:29
Uh they plan to raise uh $30 billion raising I guess far above $30 billion.
2:08:40
Uh anyways, so this is a reporting SpaceX is moving ahead with plans for an IPO that would seek to raise significantly more than 30 billion >> uh in a transaction that would make it the biggest listing of all time. Uh I'll hit this.
2:08:52
Uh the Elon le company is targeting [music] valuation of above 1 and a half trillion for the entire company which would leave SpaceX near the market value that Saudi Ramco established during its record 2019 listing.
2:09:06
The oil major raised 29 billion at the time.
2:09:09
Space X's management and advisers are pursuing a listing as soon as mid to late 2026.
2:09:13
Um, the timing of the IPO could change based on market conditions.
2:09:18
Let's hope the window stays open, folks.
2:09:20
We will do our best to hold it open.
2:09:24
>> Uh, I hate when the IPO window is closed.
2:09:26
Uh, but uh, anyways, no comments from the SpaceX team.
2:09:29
Uh but they uh junk bond analyst says of course congratulations on saying >> the biggest number.
2:09:38
>> Always great when you can say the biggest number.
2:09:41
>> Do you think do you think uh uh you think that the the timing uh here uh with uh Gavin going on about space data centers is uh just a coincidence or is this part of a a uh allocator conspiracy?
2:09:55
I I still I still believe the primac that Elon has ran has run the AB test on public companies. Tesla was miserable. SpaceX was great.
2:10:07
And so you want to stay private as long as possible.
2:10:11
There's no funding is not drying up for SpaceX by any means.
2:10:13
Uh there's no real requirement to go public.
2:10:18
There's no reason why he has to take that company public.
2:10:21
Um, this I I I I don't know why stuff is leaking right now.
2:10:25
It might just be some sort of head fake, but it doesn't seem critical uh to me. I don't know.
2:10:33
>> Certainly doesn't seem critical that they go public.
2:10:34
I would just say you have two major leaks in the span of a week.
2:10:40
>> It's just very different than the OpenAI thing where OpenAI like in order to win they need to like marshall all this capital.
2:10:45
They need to, you know, make become GPU rich.
2:10:47
They need to the the GPU prices to fall.
2:10:49
They need energy to get cheaper.
2:10:52
They need everyone to do everything.
2:10:54
They need everyone to get in line.
2:10:55
Whereas SpaceX is very much like established.
2:10:58
They have their supply chain set up.
2:11:00
They've been in this business for 20 years.
2:11:02
They're they're just like cooking and compounding.
2:11:04
And I just don't see a need for them to to, you know, marshall more capital or do anything really special.
2:11:11
I it it it it does seem like there's something going on with like okay we're talking about a second third act here but at the same time it's not like Elon needs to take this company public. I don't know. >> Do you think he does? >> No.
2:11:26
A lot of great companies don't need to go public but there's still a lot of reasons to go public. >> Yeah. Yeah. Yeah.
2:11:31
>> Yeah. Yeah. Yeah. It would certainly be it would certainly be exciting and I think it would be a good like it would just be a like there's a lot of people that are you know into space and can't get you can't get any uh like allocation
2:11:43
into a into space generally you know they just can't they can't participate in the economic >> up mobile that's it that's you can't echoar is the hold >> I wonder I wonder uh this is the the market's closed now but I wonder >> Echoar which owns I think it's 10 12 billion of of SpaceX stock. >> Yeah, I wonder what that's doing.
2:12:03
>> Yeah, I wonder what that's doing.
2:12:04
>> Up 6% today, but it's been fluctuating.
2:12:07
So, I mean, back to the Patrick a lot at the close.
2:12:10
>> Back to the Patrick Collison post, like what is worthy and what's valuable?
2:12:14
Like, I I still honestly feel like SpaceX is one of the worthiest and most valuable missions and uh in terms of just it has no slot machine dynamic.
2:12:22
It has it does not create slop. Uh it is I don't know.
2:12:29
It's it seems above enlightenment, counter enlightenment, woke, super base, like yes, Elon runs it, but just as a company, just the idea of like let's go to the moon, let's go to space, that should be apolitical.
2:12:38
Um, it doesn't it it doesn't even have the Davos expert morality impact on the environment.
2:12:45
It's just like one of the it's one of the purest missions in my opinion.
2:12:49
And I feel like it the the reason I I think there's there's not like there's something interesting about what Patrick is saying here where there is this highly worthy, highly valuable mission, but it's only there's only 5,000 people that can really play in that game.
2:13:08
Maybe like 10,000 or something.
2:13:11
Like it's just not it's just not a career path in America.
2:13:13
It's not like I'm going into real estate.
2:13:16
I'm going into lawyer legal. I'm going into medicine. I'm going into lawyer.
2:13:21
Um >> going into big oil.
2:13:25
>> You can't you you can't just say I'm going into the orbital economy.
2:13:26
I'm studying and I'm going to you know maybe I'll work at SpaceX, but there's a whole there's a whole host and like going you can go into tech.
2:13:34
It's very it's very accessible.
2:13:36
You can just like go and get a job in tech.
2:13:38
It's very hard to do that in space and make make a career for it's nowhere it's nowhere near as easy as it is for tech because tech broadly >> I just say you just go you go into aerospace engineering and then you have you have optionality try to land a job at at a >> yes through space company or you can >> so yes but what if you're what what if you're not cut out to actually go do aerospace?
2:14:01
What if you're what if you're actual skill set is marketing?
2:14:05
>> Well, you can go and be a marketer in tech.
2:14:07
You can't go and be a marketer in space. It just doesn't happen.
2:14:10
They hire like two marketers. >> Okay.
2:14:14
>> There's no there's no marketers. >> Why? Why is that?
2:14:17
>> So, what I'm saying is that like is that like this question >> you're saying we need a federal backs stop on marketing jobs in the oral economy?
2:14:22
[laughter] >> No, no, no.
2:14:25
>> I just don't see what the problem is. >> No, no.
2:14:26
What I'm saying is that is that there's a vibe shift because like like so Patrick Collison is asking the question, what is worthy? What is valuable?
2:14:34
What is a valuable mission?
2:14:36
And I'm saying I know what a valuable mission is.
2:14:37
Going to Mars, going to the moon.
2:14:40
SpaceX is a valuable mission, but 99% of people can't participate in that.
2:14:47
They can't make that their life's work because if they're not cut out to be aerospace engineers, aerospace designers, you know, if they're not if they're if that's not what they're great at, they just can't participate.
2:14:55
Whereas when previously in previous eras like tech was organizing the world's information, don't be evil. It was just cool. Tech was the mission.
2:15:04
Tech was the thing that was worthy and valuable.
2:15:06
And so you could show up and say, "I'm a finance guy. I got a job in tech. I'm a lawyer. I work in tech. I'm a marketer. I work in tech."
2:15:15
No matter what your actual skill set was, you could you could come to technology, the technology industry, and have a career.
2:15:21
And you can't do that in the orbital economy yet.
2:15:25
You can't do that in space because there just aren't that many jobs.
2:15:27
And so there I I think that there is something that's worthy and valuable.
2:15:31
It's just not able to absorb the actual demand for worthy and valuable career paths.
2:15:36
And so for a lot of the marketers, for a lot of the lawyers, for a lot of the financeers, they wind up being forced to work in slot machine companies or slop machine companies because those are the ones that have the jobs.
2:15:50
They have 10,000 jobs available. I don't know.
2:15:54
That's my sort of a hot take.
2:15:58
>> Yeah, I think that's fair.
2:15:58
I just would I I think you could you could you could also make the argument that many people are looking at jobs at say like a boom supersonic and they're choosing they're just making the choice to work at the infinite slot machine company. >> That's fair. That's fair.
2:16:14
Well, hopefully they'll read Patrick Collison's post.
2:16:17
They'll say what's worthy and valuable.
2:16:19
I got to work for Boom Supersonic.
2:16:20
I got to work for Blake Schaw who's our next guest.
2:16:22
So, while we bring him in from the reream waiting room, let me tell you about getbzzel. com.
2:16:27
shop over 26,000 luxury watches.
2:16:30
Fully authenticated in-house by Bezel team of experts. We have Blake Shaw. Look at Blake Schaw. Wow. He is in a jet.
2:16:37
[laughter] Oh yeah, he can fly. I forgot. You can fly, right? >> Hang on, guys.
2:16:42
I got to shut the engines down. >> This is crazy. What is going on here? Wow. Look at this.
2:16:51
>> It's been a complete rat race to try and put on the most insane performance during a TBPN interview.
2:16:55
I think this is going to take the cake.
2:16:58
Blake, how are you doing? Introduce yourself. What's going on today?
2:17:02
>> Hey guys, it's good to see you. Thank you for having me. It's a big day at Boom.
2:17:06
>> This is a huge day at Boom.
2:17:06
I'm so >> This is amazing. Look at this. Okay, where are we? Take us through this.
2:17:10
So, we are in the Boom Supersonic factory.
2:17:15
This, of course, is the XP1 airplane.
2:17:18
This is the airplane that broke the speed of sound in January.
2:17:20
The airplane that resulted in supersonic flight being legal again in the US. Amazing.
2:17:27
>> So, it's blown wide open.
2:17:30
>> Uh, but you know, a year ago, a year ago, we were joking that um it would be way easier to fund this company if we were an AI company. We were laughing. >> Yes.
2:17:40
I talked about that on the show. That's right. >> Yes.
2:17:42
It It turns It turns out we are.
2:17:45
So, uh, the engine that we're building that we've been building for almost four years now to power our overture supersonic airliner >> makes the perfect ground power turbine for AI.
2:17:56
And so that's that's today's news.
2:17:58
We've got a product called Super Power 42 megawatts natural gas.
2:18:00
It's going into data centers.
2:18:03
Cruso is our launch customer.
2:18:05
We're going to be generating tokens and uh, quiet sonic booms. >> That's amazing. That's amazing.
2:18:11
>> So So you guys want to see the factory? >> Absolutely. >> Give us a tour. give us a tour.
2:18:15
>> So, one of the one of the things that anybody building in uh in hard tech learns quickly is that the legacy aerospace aerospace supply chain is just really screwed up.
2:18:26
>> And so, we are building this factory to go from raw materials in one side of the building and completed jet engines out the other side.
2:18:33
So, this is uh this is some of the raw material that's just come in.
2:18:36
This is uh 17 pH uh hardened stainless steel. It's heat treated.
2:18:41
This is the This is what they call the hot stuff.
2:18:45
>> And uh you know, I don't I missed the gym this morning, so do a little bit here.
2:18:50
But this is going to turn into stage five stator veins that go inside the uh the Sony uh engine and the super power gas turbine.
2:18:59
Um so one of the most amazing surprising things is the technology that is ideal for supersonic passenger flight is actually the same thing you need to power a data center. >> Yeah.
2:19:11
So this is uh Elon pioneered this at Colossus.
2:19:14
Uh Sam's doing the same thing at Stargate.
2:19:16
These large arrays of what are called aerodyivative jet engines.
2:19:22
>> And uh it's like the they're like the blade servers of the energy world.
2:19:24
I put a lot of them in array.
2:19:27
Uh and just the same way blade servers beat mainframes, uh aerodynam uh gas turbines.
2:19:34
So let's tell how they work.
2:19:36
This is a one-third scale model of our engine.
2:19:38
It works on a complicated principle.
2:19:41
Suck, squeeze, bang, blow.
2:19:45
>> All right, so let's break that. Break that down. Air comes in this way.
2:19:46
This thing spins super high RPM, compresses.
2:19:51
You can see the blades get smaller as you go in getting the air down to about a 20 to1 compression ratio. >> Burners in here.
2:19:56
This can run on jet fuel.
2:19:58
Can also run on natural gas just with a different fuel nozzle.
2:20:00
And it goes out the back here.
2:20:02
So the model you're looking at here is what powers the airplane.
2:20:06
>> The model that powers AI is very similar.
2:20:08
We basically take the fan off the front, we lose these two turbine stages, and then we have what's called a free power turbine on the back.
2:20:14
Three stages that extract energy, spin a second shift uh second shaft. >> Yeah.
2:20:20
>> And uh and that powers a 42 megawatt generator. >> Yeah.
2:20:23
>> So, like I said, the vision here is we're going from raw materials in one side of the building, completed engines at the other side.
2:20:29
The facility we're standing in now is going to do the first 200 megawatts uh over the next uh about 18 months. >> That's pretty.
2:20:36
We're building a much larger factory that's able to do 2 gawatt a year and we're just going to scale from there. >> Wow.
2:20:42
>> So, um let's go inside the shop. >> Yeah.
2:20:44
And this is all um on the back of you they it was it was seen as controversial that boom did not just white label another engine from another company. Correct.
2:20:54
Uh and now it's sort of come back to benefit you.
2:20:56
Is that is that the correct narrative?
2:20:59
>> I I think that's correct.
2:20:59
I mean people called us crazy. Yeah.
2:21:03
>> To not outsource our engine.
2:21:03
Frankly, I was a little bit nervous about it.
2:21:05
How is this really going to go?
2:21:08
>> It's the best decision we ever made.
2:21:10
We're getting a fully custom cruise.
2:21:15
Could not do Boomless without our own engine. >> Sure.
2:21:18
>> It enables a totally new passenger experience.
2:21:20
I haven't revealed it yet.
2:21:20
Y >> and then I think the most important thing is we can now take that same engine core, put a power turbine on it and and get to profitability years faster than otherwise we could have.
2:21:31
This this makes uh basically superpower makes not just electricity, it makes capital and it makes the capital that finances the the capital expensive uh development of the overture passenger airliner.
2:21:41
So uh let me let me uh walk you around the shop here.
2:21:44
So this is basically the first unit of what we will copy paste into the the facility that will do 2 gawatts per year.
2:21:51
What are what are jeans made of?
2:21:54
Well, you've got big round things.
2:21:56
Um, and actually if you look inside this machine here, this is called a um a turnmill.
2:22:00
This machine weighs 65,000 lbs.
2:22:03
And spinning on it right now is a 4,000 lb doughut of cast incanel.
2:22:11
And that's that's a nickel alloy.
2:22:13
Uh, this is a relatively hard alloy.
2:22:16
This is going to be the turbine center exhaust frame.
2:22:17
This is the first very large part that we're machining in house. So big round things.
2:22:22
Uh then you've also got uh discs with blades all around them. That's called blisks.
2:22:28
Uh these are some of the hardest to make parts.
2:22:31
And so we have started what we call the blisk cre.
2:22:33
And uh this machine here is actually a more than five axis mill.
2:22:41
>> Uh so this will hold a disc of forged uh titanium or forged powder metal super alloy and then the disc will kind of rotate in and out like this while another cutter head comes down.
2:22:51
and basically sculpts each individual compressor blade uh out of uh out of metal.
2:22:58
So we uh uh ultimately we're going to have a whole bunch of these machines cranking out discs.
2:23:01
Uh over here on the uh other side, this this is part of an automated production line or compressor blades.
2:23:10
Uh so to give you an example of this, this is the uh what's called the stage one variable guide veins.
2:23:16
This goes in the front part of the compressor section of the engine.
2:23:20
Uh, these actually move as the engine changes power settings to have the optimal air flow.
2:23:26
>> And this machine here starts with that bar stock, those those kind of heavy beams I was showing you outside in the in the hanger floor.
2:23:33
>> Uh, comes in on this feeder in one side, gets held in the machine.
2:23:36
The cutter head comes over, cuts it away.
2:23:38
Uh, another um gripper comes over, grabs it, machines the back side.
2:23:43
A robotic arm comes in, grabs it, puts it on the table. We start the next door.
2:23:46
So, this thing is ultimately going to be able to run 247 building engine parts.
2:23:52
>> Quick questions about the factory. Uh, where are we?
2:23:54
What where is this factory and how big is it overall square footage roughly? >> Yeah.
2:23:59
So, this this building is about 70,000 square feet.
2:24:01
It is uh 5 minutes from our engineering HQ in South Denver.
2:24:07
>> And uh we are uh we're about to open uh early next year another factory that is three times the size of this one.
2:24:13
That's what's going to be able to do uh two gigawatts a year. >> Yeah.
2:24:18
>> So, what are the what are the key what are the key challenges now?
2:24:20
Uh this feels uh hard but maybe more straightforward than uh supersonic commercial flight like what what what are you guys doing approvals? >> Yeah. Yeah. Exactly.
2:24:33
But and and have like massive uh massive demand. Uh yeah.
2:24:39
What are kind of like the key challenges that you and the team are looking out for to to be able to deliver on on the timeline that you were talking about? >> Yeah.
2:24:45
So, after having done a boomless supersonic jet that was safety critical with a pilot on board, this feels like doing it on easy mode.
2:24:51
Literally XB1 had 68,000 parts.
2:24:56
>> 68,000 parts and they're all safety critical.
2:24:58
>> Uh the turbine has less than 2,000 >> and uh so the there's going to be a lot of challenge in in getting that to work, getting it to work reliably, getting manufacturing up to scale.
2:25:06
But after having done XB1, it feels like easy mode.
2:25:10
Uh we've got customers that are going to take as much as we can possibly make as fast as we can make it.
2:25:13
Uh we've got today we've got the capital uh to go do that. >> How much capital? >> Um 300 million. And >> congratulations. >> Thank you. Thank you.
2:25:27
after um after basically continuously fundraising for about a decade, >> I can't tell you how good it feels to have raised the round that lets us ship the revenue product that then produces the cash to fund the rest of the stuff.
2:25:41
So, we're done fundraising.
2:25:41
This is the last equity round we ever have to do. >> Let's go. >> That's incredible.
2:25:45
How was the first night's sleep after you close the round?
2:25:48
Did you [laughter] Did you I imagine I imagine that was a pretty uh pretty surreal moment even though the you know, you're still uh just getting started.
2:25:55
Uh I would say uh I uh people are going to be cons like the natural concern is like does this mean we're not getting uh we're not going to get uh the supersonic commercial aircraft?
2:26:09
You obviously I I don't I don't I haven't lost any faith.
2:26:15
>> Uh this feels like an intelligent uh move in order to enable that future basically by buy the company time to get us to that point.
2:26:22
But uh what do you what do you have to say to uh anybody that might be wavering? >> Yeah.
2:26:28
No, this if you want super passenger flight to exist, you should be very very excited about this is that the single biggest challenges we had were how do we prove that we have a reliable engine and where do we get all the money to do it and running this thing on the ground proves the engine is reliable and it literally prints the cash that we need to go develop the airplanes.
2:26:45
So I think this takes us from, you know, less than 50% chance of success to a far greater chance of success.
2:26:52
Like I think overture supersonic flight is is basically inevitable at this point.
2:26:55
And you know, some people are saying like, "Oh, I'm, you know, Blake got lost.
2:26:58
I'm going to be, you know, I'm just going to become an energy guy."
2:27:02
And it's like, guys, I didn't bust my ass for 10 years in order to like only make power turbines.
2:27:08
I'm very excited about the power turbine business. America needs it.
2:27:11
Like we're losing to China. We really need this.
2:27:13
Uh but uh this is absolutely our bridge to the the even bigger opportunity to just reinvent all of commercial aviation. >> It's awesome.
2:27:23
>> Makes uh makes a lot of sense from a from a like looking at the existing sort of like turbine uh landscape.
2:27:28
A lot of them have supply chain challenges.
2:27:31
is part of Boom's Edge that you guys are so used to making all of your own componentry and parts that you basically effectively just need the raw materials and you can make stuff happen.
2:27:44
Uh how are you kind of avoiding uh maybe some of the other delays that you know uh legacy manufacturers are experiencing. >> Yeah.
2:27:54
Well, I I think you named it.
2:27:55
Being able to build our own parts is huge.
2:27:57
And uh the you know the room I'm standing in here uh does not exist at GE does not exist at Rolls-Royce.
2:28:05
>> Uh you know the the in the sort of Jack Welch era of everyone getting focused on return on net assets like by what a random metric.
2:28:12
They all sold off their supply chains. Yeah.
2:28:15
>> And they can't make anything anymore.
2:28:16
And now we we hire like disaffected engineers out of Pratt, out of GE, and they were like, "Holy Toledo, we can resolve in an hour what used to take us three weeks or three months to do at our last companies because they didn't have access to hardware."
2:28:30
And if they ever wanted to change anything, it's really hard to change.
2:28:33
That's actually one of the biggest um biggest innovations here is what we're doing is we're trying to make the world of uh atoms more like the world of bits.
2:28:41
And you can iterate, you can evolve, you can change.
2:28:43
And part of that is about taking software engineers, putting them on a hardware engineering teams and automating uh design workflows.
2:28:51
So that means we can like change digital designs really quickly when we learn.
2:28:54
The other piece is how quickly can we turn a part?
2:28:56
Like if we take a turbine blade and we send it to a traditional supplier to be made, it's going to take six maybe nine months for us to get that part back.
2:29:03
Going from digital design to hardware.
2:29:05
What that means is if you're the engineer designing it and you get it wrong, like it's really bad.
2:29:10
you've set the whole company back six, nine months.
2:29:12
So now now, now there's a lot of hand ringing.
2:29:16
Now there's analysis paralysis.
2:29:16
Now you got to have layers of managers double-checking everything. Now you're really slow.
2:29:22
But if you build that part in house, you can actually turn a turbine blade in 24 hours with a 3D print process, heat treat, brace, get it out into the engine.
2:29:31
So what we can do is iterate really quickly.
2:29:32
So, we're liberating engineers to move really fast because if they make a mistake, if they want to do an iteration, we can turn it in days or hours in the same building that they work in.
2:29:45
>> That's super powerful because >> I see what you did there. >> Was that accidental? [laughter] I don't know. I love it. I love it.
2:29:52
Um, is there is there anything um that you've been tracking on the on the regulation side that you think needs to change?
2:30:00
We were talking about making uh making uh boomless cruise legal, removing speed limits for high-speed travel.
2:30:07
Uh if you were to wave a magic wand, is there anything that you'd change around energy production in America today to accelerate reindustrialization and everything?
2:30:21
>> It's much bigger than energy production.
2:30:24
We have we have a huge problem that I think not enough people are talking about, which was we we have a permissionbased approach to building. Sure.
2:30:31
>> Not a freedom to innovate approach to building.
2:30:32
So like if we drove to work the way we build buildings or uh permit energy plants, uh you'd have to go file a plan.
2:30:41
You have to list out exactly what turns you're going to take.
2:30:42
You're going to promise that you're going to stop at every stop sign, not run through any red lights, always drive the speed limit, and then and then some bureaucrat's going to sign off on that, and then finally you can drive to work. It's insane.
2:30:52
That's the way we build a building.
2:30:54
That's the way we build a power plant.
2:30:55
I think we need to go from um permissionbased which is a such huge delays I mean huge costs to hey we're going to have a rule book we're going to have commonplace rules um and then you can you can pledge to follow them and if you break them then um you know then you get fined or you get in trouble or you get your permits taken away but I I think we have to really get rid of the entire concept of market preapprovals if we want to move fast.
2:31:19
It's really holding America up right now.
2:31:20
It's the biggest problem with building anything physical. >> Yeah. Yeah.
2:31:24
Uh, are you guys hiring at all right now?
2:31:29
>> Uh, we're hiring as fast as we can find great people.
2:31:31
Uh, so in fact, >> I figured, >> in fact, if I I'll plug this if you'll let me.
2:31:36
If if you go to boomchupersonic.
2:31:37
comreferral >> and you send us somebody great, we're looking for great engineers, hardware, software, mechanical, propulsion, everything.
2:31:47
Technicians, um, CNC and machinists.
2:31:49
It's hard to find enough great CNC and machinists. Send us somebody.
2:31:53
We will send you a free overture desktop model if we end up hiring that person. >> I love it. >> That's very cool. >> That's very cool.
2:32:00
>> Uh well, this has been the best uh hard tech tour we've ever gotten.
2:32:04
We've had a number of people attempt what you just did.
2:32:07
It always it always goes poorly.
2:32:09
>> Yeah, there was no high stakes.
2:32:09
It's very high stakes cuz like anything can go wrong with like your Wi-Fi or anything. I'm very impressed.
2:32:15
Uh this was amazing and uh and honestly it was just like chilling, watching, learning. This was really awesome.
2:32:21
normally have to ask way more questions to get information, but this was really informative.
2:32:26
>> I'm so excited for you and the team put together. >> What a crazy story.
2:32:30
I mean, I'm sure like, you know, the the job's not finished.
2:32:34
The book has not been written, but uh I you know, you know, I've followed your career for a long time and uh it's uh it's you're on an amazing run doing amazing things.
2:32:44
So, we appreciate you taking the time to come talk to us.
2:32:47
>> Appreciate you having me and making this so much fun. Thank you guys.
2:32:50
Have a great rest of your day and merry Christmas to the whole team. Talk to you soon. >> Merry Christmas. Over and out. >> Goodbye. >> 8. com.
2:32:56
Exceptional sleep without exception.
2:32:59
You close the $300 million round.
2:33:01
You need to sleep on an eight sleep. Fall asleep faster. Sleep deeper. Wake up energized.
2:33:06
If you're trying to build a 42 megawatt natural gas turbine while working on a supersonic jet, you definitely need a good night's sleep.
2:33:16
my eight sleep to be powered by a natural gas turbine.
2:33:20
I want to >> just give me a mini boom >> turbine for my bedroom. Yes, >> please.
2:33:26
[laughter] >> Just a small one.
2:33:28
>> It doesn't have to be full scale. >> Yeah.
2:33:30
>> But just something small that I can really rely on. >> Yeah.
2:33:33
>> Uh because >> Yeah, it is weird.
2:33:35
The the eight sleeps, you plug it into the wall, it's electric.
2:33:38
You could get a diesel >> a diesel version.
2:33:41
You just fill it up with a little bit of diesel and then and then you and then you you pull start it like a lawn mower >> and just leave the window open. >> Yeah.
2:33:51
>> So there's some air blows out. Yeah.
2:33:51
I mean the exhaust needs to like kind of flow out of the out of the house.
2:33:56
But >> or you could wear a mask and just run a like a >> Well, that could be diesel powered too.
2:34:02
>> You have a diesel [laughter] powered sleep pulling air out that's fresh. >> Exactly. Exactly.
2:34:09
>> But then you have a diesel motor running in.
2:34:11
You put your whole house on your face.
2:34:12
Your face is potentially >> kind of vibrating, but >> it' be good. >> Can see it.
2:34:18
>> Uh, well, people are starting to talk some trash about the old Meta Super Intelligence Lab. >> Who? 0.
2:34:25
005 seconds says it's now painfully obvious that Meta Super Intelligence Lab went on a massive hiring spree, promised the world, and delivered absolutely nothing.
2:34:38
There has been a mass exodus.
2:34:38
I feel like W Alex Wang was a colossal mishhire.
2:34:43
When is Zuck going to clean house and admit his mistake? >> Let him cook. >> Let him cook. >> Let him cook.
2:34:49
I was the first one I was the first one to say that Meta Vibes like should never have been uh released or uh at least advertised >> publicly.
2:34:59
I think it was uh definitively >> uh just not a good product.
2:35:03
Y >> uh and uh but let them cook. Let him cook. Uh I Yeah.
2:35:10
Again, the mistake is like people are going to judge the first thing that your new organization releases. It felt rushed.
2:35:16
It looked bad in comparison to Sora.
2:35:19
Uh but we need to see the next version of Llama.
2:35:22
I'm sure they'll call it something else.
2:35:24
they'll call it something else. Uh but uh give them give them more than >> what should they actually >> like Google has been able Gemini I feel like has been able to carve out a really unique position with Nano Banana and and
2:35:38
like it went viral and this was an at uh and at the time's like take about like the empire strikes back and I have found that like you know having the best having the best video model is a reason for people to go to your app having the best uh you know audio model the best photo model. The best deep research
2:35:56
The best deep research product is what what the rotisserie chicken is to Costco.
2:36:01
Nano Banana [laughter] analogy. Great analogy, >> right? It's a loss leader.
2:36:06
It's like come in, make a bunch of images.
2:36:08
We're going to lose a lot of money, but we're going to get you hooked on our bread and butter, >> our our language model.
2:36:16
>> And so, yeah, I mean, OpenAI has obviously developed just a great like back and forth chat experience.
2:36:19
The the the voice mode is really dominant there.
2:36:23
The deep research product.
2:36:23
possible that Zuck wanted his true believers to be able to accumulate Meta shares at around the $1 and a half trillion dollar mark >> because he wants to reward his most loyal >> potentially >> soldiers >> potentially.
2:36:37
Uh Stammy here says Limitless is acquired by Meta today.
2:36:39
End to a lovely journey with Rewind and Limitless.
2:36:43
And Ryan Jones says Zuck is going on a generational run of Max Paranoid missing mobile.
2:36:47
Really, really, really scared him because he just bought an AI wearable startup.
2:36:51
still spend it on the metaverse.
2:36:54
Um, >> I think it's obvious that Meta is just going to keep shipping hardware.
2:36:57
I think that uh this the Limitless acquisition looked like, you know, a soft landing for a team that had proven that they can ship products. Again, they did that.
2:37:06
I know they had customers because some of the customers were mad that Meta acquired them and they were talking about it.
2:37:15
>> Uh, so yeah, I shouldn't be a surprise.
2:37:19
I don't think you can I I think it's hard to hard to argue that >> Meta should just ignore any forwardinking product lines and just just do >> Yeah.
2:37:29
Well, speaking of the metaverse, we should watch this video of a robot that was clearly being teleoperated >> absolutely destroying a water bottle.
2:37:41
It's one of the craziest videos I' ever seen.
2:37:42
Uh this is like so insane.
2:37:42
So it the operator clearly takes off.
2:37:47
It feels like it should be AI or something.
2:37:50
So the >> Daniel says the hand coming down with enough the water bottle which is not easy to do if you just have a water bottle and you're you can't just rip that thing open.
2:38:00
But the the the the robot op the robot teleoperator takes the VR glasses off and then the robot just falls backwards. >> Is this real?
2:38:11
>> Imagine having one of these hanging out. >> It's comedic genius.
2:38:13
Imagine having one of these hang out in your office and it's just running bits all the time. Like it's whole goal.
2:38:18
I I have kind of class clown energy in the office, but if I could outsource that to Optimus and just be able to focus more on my work and he's Optimus is just going around running bits.
2:38:29
I mean that >> you know what we have to do?
2:38:32
We have to get one of these robots that you know how they're how so many of the robots are are claiming like we're going to do your dishes.
2:38:37
We're going to do your dishes.
2:38:38
I just I want to just have Okay, we're gonna all have a nice glass of wine.
2:38:42
We're gonna put 50 different glasses, wine glasses of all slightly different shapes on the table and just tell the robot, "Hey, clean up the clean up the wine glasses.
2:38:51
Just load them all in the dishwasher."
2:38:53
Nothing's I can barely do that.
2:38:57
I can barely do that without breaking. >> Oh, yeah.
2:38:59
All the time I'm smashing these things.
2:39:00
Um, and you imagine one of these robots just completely decimating the the the >> Sure.
2:39:07
I'll I'll unload the dishwasher just in there just >> Oh, no. No, no.
2:39:10
Please allow me allow me to unload the your your your finest crystal stemware.
2:39:16
>> This would be allow me to unload your stemware.
2:39:19
>> You discover an edge case where the robot thinks, well, to unload the dishwasher, I should break every glass and use a vacuum and just vacuum it out.
2:39:26
Way easier than just taking them all out at once. >> Oh. Oh. Oh, sorry, sir.
2:39:29
Would you like me to polish your your your fine stemware?
2:39:32
[laughter] >> I'll polish it into dust.
2:39:36
>> Polishes it into dust.
2:39:36
Anyway, uh our next guest is in the reream waiting room.
2:39:41
First, let me tell you about adquick. com.
2:39:42
Out ofome advertising made easy and measurable.
2:39:44
Plan, buy and measure out of home [music] with precision.
2:39:48
We have Naveen Ralph from Unconventional, CEO of Unconventional AI in the Reream waiting room.
2:39:53
Naveen, welcome to the show. >> Thank you. Thanks for having me.
2:39:57
Uh let's jump right into an introduction on yourself, companies you built in the past, and then we'll get into unconventional. >> Yeah.
2:40:08
So I was uh the first company I built in the AI space was called Nirvana.
2:40:11
It was actually the first AI chip company.
2:40:13
That was back in 2014 before most [clears throat] people knew what machine learning was. >> Pretty tough.
2:40:20
>> A little too little too early, >> but you're back.
2:40:22
>> Um I think it was actually decent timing to be honest with you.
2:40:24
Um but you know I I think I sold too early to be honest.
2:40:28
Um uh the second company was actually moving more toward the software and algorithmic side called Mosaic ML.
2:40:32
Uh sold out to data bricks back in 2023 and I led AI at data bicks up until uh just a couple months ago where I left to start unconventional. >> Incredible.
2:40:43
Uh so yeah, jump jump right into it.
2:40:45
Uh talk about you know the vision.
2:40:47
Uh, I feel like you guys, um, the perfect amount of controversy yesterday because people were latching on to a [laughter] not not a seed round at a $500 million valuation, but a a 500 million of of capital invested at the seed round.
2:41:02
Uh, it was honestly perfect.
2:41:04
You want you want a little bit of spice on the timeline to get attention, and I'm sure there's been, you know, a ton of inbound interest both from the candidate side and and future customers.
2:41:14
>> Yeah, I mean, you know, obviously that was somewhat intentional.
2:41:15
uh we wanted to have a big shocking moment.
2:41:17
Um you know, but I think it's actually pretty rational when you think about the opportunity ahead of us.
2:41:23
So what we're doing at Unconventional is rethinking how a computer works.
2:41:28
You know, the computers that we use today, uh the the fundamental abstractions have been around for nearly 80 years.
2:41:33
And you know, it's kind of weird to think about in the tech industry something being around for 80 years, but it really is true.
2:41:40
And uh uh now we're we've come to the point where we've pushed that paradigm as far as we can push it.
2:41:45
You know, fundamental constraints around energy are now hitting us at the global level.
2:41:50
Like if we keep scaling AI like we're doing, I mean, I think AI is amazing.
2:41:55
I I use it all the time and I think the rest of the world is going to do that too. We can't get there.
2:41:58
We're going to run out of energy to scale these things up because it requires very power- hungry chips.
2:42:04
power- hungry chips. So really we we saying can we rethink the paradigm actually from the circuit level up and build something that's vastly more efficient like a thousand times [clears throat] more efficient uh than what we've been building and focus prime only on AI we don't need to do accounting software and you know
2:42:21
artillery calculations and all the things that traditional computers do we'll let that be in the realm of digital machines but can we build something that's much more efficient for the substrate of AI and uh so the opportunity ahead of us I think is nearly infinite and That's why valuation actually can make some rational sense. >> So what does your supply chain look like
2:42:38
>> So what does your supply chain look like or or what do you think it will look like in the in the near future?
2:42:46
>> Yeah, I mean when we started this project there were two fundamental constraints I put on it.
2:42:48
One is that we have to be able to solve the problem within 5 years >> because this problem is going to hit us in three or four years and we need to have a solution ready.
2:42:57
>> Then at that point when we have a solution you can't have something that's like I've solved the science problem now what we have to be able to manufacture it.
2:43:03
So we have to have scalable manufacturing.
2:43:05
So we believe we can solve this problem in a in a big way within 5 years that actually leverages the silicon ecosystem.
2:43:12
>> So we do want to manufacture it on standard lithography techniques.
2:43:14
Now >> interesting like ASML could potentially be a partner in the next 5 years like they're not off the table. >> Yeah.
2:43:23
TSMC we we talking with already.
2:43:25
You know I was out in Taiwan just a few weeks ago for this purpose.
2:43:27
And um you know it doesn't mean that's the end the beall end all.
2:43:31
What we're doing is really building a new set of abstractions like a computer is built on a digital abstraction.
2:43:36
Can we move away from that and actually move to something that is more amendable to using fundamental dynamics of uh the substrates and if we can do that we can actually open up the world to a whole new set of you know [snorts] potential um substrates.
2:43:50
It silicon is one of them and maybe there'll be more exotic things.
2:43:54
I've talked to folks who are building 3D printed circuits and all kinds of crazy stuff.
2:43:58
And so I think the world is going to be very rich in the next 20 years in terms of new capabilities.
2:44:03
Right now we got to leverage what we have. >> Yeah.
2:44:06
I I mean in terms of of leveraging what we have, I feel like there's been uh you know movement from okay GP Nvidia GPUs are bust.
2:44:14
Everyone's just doing that.
2:44:16
Then we got some serious movement this year from AMD stepping it up. We got TPU.
2:44:21
Tranium's looking pretty good.
2:44:23
There's like these AS6 are doing well.
2:44:25
There's a whole crop of of AS6 startups that are saying, "Hey, we're going to bake the transformer right onto the silicon." They're going with TSMC.
2:44:31
Can you help me understand how you were thinking about um like creating something that's higher performance but still leaving enough like flexibility to be able to actually work with um whatever the next algorithmic paradigm looks like. >> Yeah.
2:44:54
I mean one part of what we're doing is a very deep code design.
2:44:56
So we're not saying here's a transformer and it's immutable.
2:45:01
We're not looking at it like that.
2:45:02
the the the way you define the neural network itself is something we're going to change and actually link to the hardware.
2:45:08
And if you look at biology, there is no difference between the definition of the neural network and the phys physical substrate.
2:45:13
They're one and the same.
2:45:16
>> So the the the dynamics, the physics of those neurons actually gives you the algorithmic richness that you have.
2:45:22
>> So we want to move more that direction.
2:45:24
It's not this abstraction on a digital machine which is built out of numeric.
2:45:28
All the machines that you highlighted just then which all have a wonderful purpose by the way um all work on the same fundamental abstraction.
2:45:34
They all use bits to represent numbers and those numbers represent weights that then are manipulated in some way to build a neural network.
2:45:44
We're actually talking about building those sort of effective numeric on the physics. >> Yeah.
2:45:51
>> On on the fundamental properties.
2:45:51
Do do you have a view on uh you know we were reflecting on this Mark Beni off post earlier in the show.
2:45:57
Uh he was kind of making the argument that LLMs are going to commoditize that you know it's like hard discs and you're going to be able to move them around.
2:46:04
There's not a lot of value or not a lot of lock in at the okay I got this bag of weights layer and I'm wondering if you have a view on how the the you know foundation model landscape will evolve over the next five years because I want to know what your customer mix looks like.
2:46:20
Uh but you can kind of tie that together however you like. >> Yeah.
2:46:25
I mean transformers are something that works really well today.
2:46:28
We were able to scale it up.
2:46:30
We're able to prove out that we can build synthetic systems that learn.
2:46:34
I think that was enormous in the last several years, right?
2:46:36
And actually not just that learn that can learn but can be useful.
2:46:40
>> So now it's about okay well we can define what useful is.
2:46:43
Now we have these quality metrics for what a token is.
2:46:47
That actually has opened up a whole new world to me in a sense where I can say, well, as long as I can supply that quality, I don't really care if it's a transformer.
2:46:55
I don't really care what it looks like.
2:46:56
And if I can do so very cheaply and very fast, that's all I care about.
2:47:01
So now we're really getting to this almost pure play supply of intelligence. That's what we want.
2:47:04
So now, if that's the abstraction, it's not about a transformer, it's about intelligence, and I can define that with some metrics.
2:47:11
Okay, now I can supply that in new ways.
2:47:14
And so that's the way we're looking at it.
2:47:16
Like I'm not looking at the world today.
2:47:17
I'm looking at the world in four or five years in terms of a product. >> Yeah.
2:47:23
Can what like what do you what do you uh can you break down more specifically what what you expect your like kind of first initial customer cohorts to to look like? >> Yeah.
2:47:36
Yeah, I mean the way we're going to see all of this stuff expressed is really much cheaper per token cost like 1500 the cost per token or something like that.
2:47:44
And um and I think our our cohort is really at first we're going to go out for data center as the as the fundamental rollout but anyone who's using intelligence for an application at that point they're going to actually have probably strict requirements on what the capabilities of the models are what their uh what the token quality is defined as.
2:48:04
So when we have that metric, we can build toward it.
2:48:06
We can say okay well GPT8 or whatever it is at that point gives me this and is there a way I can recapitulate that in a in the kind of neural network we're defining and the answer should be yes.
2:48:18
And so we we will have kind of strict specs in in a way to build toward in terms of what that intelligence token really means.
2:48:27
>> And so it's it's really our our customer cohort will be anyone who's using AI as part of their application.
2:48:31
And uh we want to supply that faster, cheaper and eventually in a more ubiquitous way.
2:48:36
I mean personally if I really want to look out there like 10 years, I think robotics are going to be huge.
2:48:41
And I think robotics require us to solve this problem of bringing energy down drastically to actually have more processing on on the bot itself.
2:48:48
That's how we're really going to open up this world of autonomy.
2:48:53
>> And so uh personally, I think that's where I'm really excited.
2:48:55
Maybe that's just the kid in me uh excited about seeing that future, but I think that's where we're going to go. What? Uh, yeah.
2:49:02
I I mean, you I know you talked a little bit about the the size of the seed round, but um can you help me understand a little bit more?
2:49:07
$475 million is a ton of money.
2:49:10
Uh is is there [clears throat] is there like a you know a bill that you see yourself paying where you're like, "Yeah, I'm going to I'm going to spend $200 million on this."
2:49:18
Or is it more like you're just going to be operating at the level of like, okay, we're burning a hundred million dollars a year on a lot of top engineers and AI scientists and like it's just a big organization early and you're just kind of jumping to growth stage company scale as fast as possible.
2:49:39
>> Uh not not really that.
2:49:39
So I don't anticipate the company becoming huge in terms of people.
2:49:42
Um call it 80 to 100 people steady state for a while. >> Yeah.
2:49:47
Uh but much like a frontier lab, like a frontier lab spends a bunch of money on GPUs to iterate. >> Yep.
2:49:53
>> Like training GPT5 maybe 30 million bucks, but you got to follow a bunch of dead ends, right?
2:49:58
>> And you do that with GPU compute.
2:49:58
Our version of that is actually building hardware.
2:50:01
So we're going to be fabricating chips.
2:50:03
We're going to be trying different things.
2:50:04
It's very hard to model some of this stuff actually numerically.
2:50:07
And you [clears throat] know, we're going to do our best to model it, scale up that modeling actually on GPUs.
2:50:11
Uh but at the end of the day, you got to build it, you got to test it, and you got to see if the whole thing works end to end.
2:50:17
And we're gonna do that a whole bunch of times. >> Yeah. Yeah.
2:50:21
>> How are you uh how are you planning to actually use existing Gen AI kind of the existing Gen AI stack to accelerate your own development of of uh of an alternative to traditional, you know, GPUs?
2:50:35
>> Yeah, actually that's a great question.
2:50:37
There's it's it's really interesting as we start clicking into like the the tools for designing hardware.
2:50:40
they're still pretty far behind.
2:50:42
Um, you know, automation of digital logic is has been done to some degree as almost like coding tools.
2:50:49
Uh, but on the analog side, this is still relatively new.
2:50:52
And we are seeing now companies that are saying, hey, I can explore the design space of different circuit architectures for you using AI.
2:51:00
And you know, we said great, we want to either work with them or buy them, I don't know, whatever it is, whatever makes sense for us.
2:51:06
But yeah, we are trying everything to use the latest techniques to accelerate our exploration of the space.
2:51:12
That's the way we're looking at this is how fast can I iterate?
2:51:16
How fast can I find working solutions?
2:51:18
That's our main goal right now. >> Makes sense.
2:51:21
What have you learned from racing that you've applied to company building?
2:51:25
And what have you learned from company building that you apply to racing? >> Oh boy.
2:51:30
Uh, I think racing when you start getting into like truly competitive events, you you start to see that every like tenth of a second matters.
2:51:40
Like when you're coming into the pit lane, for instance, you have a pit lane speed limiter, right?
2:51:45
So, I don't think people even know this, but when you when you come in, you you hit this pit lane speed limiter, and when you drop below the pit lane speed limit, you hit the throttle, it's it pegs it at the speed speed limit.
2:51:55
You basically want to optimize that so you don't even lose a tenth when you come into the pit lane.
2:51:59
You basically hit the brakes at a certain point, slow down and and are at this pit lane speed.
2:52:03
You don't want to slow down ahead of time and kind of ease your way in.
2:52:06
>> Y >> every tenth of a second matters, and that may be in even a 24-hour race.
2:52:09
And I think that's true with a company. Like, don't waste time.
2:52:12
[clears throat] Every moment matters.
2:52:14
You may make bad decisions. That's okay.
2:52:16
Figure out how to back them out. Move as fast as you can.
2:52:20
If you may, if you hired the wrong person, fix it.
2:52:21
Um, and so I think the main thing I learned is that time is your biggest enemy always. >> Love it.
2:52:28
Love Uh, well, we normally ring the gong for $475 million, but we should also ring the gong for $265 points in the Ferrari challenge.
2:52:37
>> There you [laughter] go. >> Yes, I'll take it.
2:52:41
>> Uh, >> they're both massive accomplishments.
2:52:44
>> Well, we're big fans of the Ferrari challenge around here, so it's a big deal for us. >> Imp is where it's at. Really? That's the big stuff. >> Oh, cool. Cool. Yeah. >> Yeah.
2:52:51
We >> we were out in thermal uh a couple weeks ago and it was a first time for both of us on the track and it was it was life-changing.
2:52:58
It was like a new like I'm sure somebody that you probably shared the hobby uh here and there.
2:53:01
So uh anyways, congrats uh on on the announcement and everything and the whole team.
2:53:08
Uh sounds like an incredible place uh to go work right now and uh >> uh I'm sure uh uh I I can't wait to have you back on >> and and what a murderer's row.
2:53:18
We got Andrees, Lightseed, Sequoia, Lux, DC, VC, Future Ventures, Jeff Bezos, Data Bricks, and many others.
2:53:24
Uh, what a fantastic way to kick off a new business. Congratulations. >> Awesome. Thanks.
2:53:31
>> Have a great rest of your day. We'll talk to you soon. >> Goodbye.
2:53:33
[applause] >> Uh, let me tell you about wander. com.
2:53:38
Book a wander with inspiring views, hotel graded minis, dreamy beds, top tier cleaning, and 247 concier service.
2:53:43
It's a vacation home, but better, folks. That's right.
2:53:45
Um, our next guest is already in the reream waiting room.
2:53:47
We have the founder of >> Welcome to the stream. How are you doing? >> I'm I'm doing great.
2:53:56
Thank you very much for having me.
2:53:58
I'm very excited to be here.
2:54:00
>> Thanks for very excited as well.
2:54:00
We wanted to get you on uh last week, but we were on the road.
2:54:04
Uh, and yeah, very excited to chat. >> Thank you very much.
2:54:10
>> Introduce yourself, introduce the company.
2:54:12
We'd love to get uh you know how you're positioning it and then I want to go into the funding round and some of the implications of this but uh kick it off with a little bit of an introduction for us. >> So sounds great.
2:54:21
As always I always start by saying my name is Ofair.
2:54:23
I'm married to wonderful Julian father to Rome.
2:54:26
Objectively cutest baby ever born. >> Wow. That's a great intro. I love it.
2:54:31
[laughter] >> These are the important stuff. Less important stuff.
2:54:34
I I started a few companies before.
2:54:35
Actually four companies to be exact. Wow.
2:54:37
Most recent one was a company called Cloud and Do which we sold to Amazon on January of 2019.
2:54:43
Grew the business to a billion dollar business uh doing migration and disaster recovery to the cloud.
2:54:50
>> Let's give it up for migration and disaster recovery in the cloud doesn't get enough doesn't get enough credit.
2:54:54
It does not get enough credit. That's right. >> I agree.
2:54:59
I'm actually this I was this crazy guy who really love data data data regression data protection.
2:55:04
We we lived this all so long and both me and my co-founders and while we were there we saw an opportunity that we just couldn't resist all those companies really moving to the cloud especially around co >> and and later on and all the incumbents in our space uh were born on premises.
2:55:23
So we decided to start a company in cloud backup.
2:55:27
>> You could say cloud backup isn't it solar like in 1981. >> Yeah.
2:55:31
Well, we figure out that as companies move to the cloud become very significant, they have a very big big problem actually managing their data.
2:55:38
Imagine the secondary storage backups are like tapes.
2:55:42
These are companies storing their most precious data for a very long time and they can't access that.
2:55:50
>> So, we started as a backup company.
2:55:50
I said, I'm this crazy person starting a non-AI company in an AI world. >> Yeah.
2:55:57
>> But then you know what? It hit me.
2:55:57
AI is such a strong compelling event with just strong tailwinds that we just had.
2:56:05
>> I mean, look at the Seagate and Western Digital stocks.
2:56:07
They're through the roof this year. It's crazy.
2:56:10
>> And it makes sense because everyone's going to need to store a lot more data.
2:56:13
Everyone's creating so much more data.
2:56:16
>> So much data created all the time. And you always data.
2:56:18
And I don't know who's going to win the comput wars. >> Yeah. Yeah.
2:56:22
>> Open AI, anthropic, a data brick, snowflake in any area.
2:56:24
What I do know, no matter what's going to happen, >> yeah, >> data is going to be the enterprise mode. Yeah.
2:56:33
>> And we are here to help them allocate this data.
2:56:36
We're automating cloud backups. Sounds boring, right?
2:56:39
>> Making it into useful, accessible assets, data links.
2:56:44
>> So you can back up all your data in a very seamless, easy way, but then use it >> for example to train models.
2:56:49
That's all the hype, right? >> And analytics, NBI.
2:56:52
Wait, so no, so no tapes. It's on drives.
2:56:58
>> No tapes on tapes as it seems.
2:56:58
We're software only solution. Okay.
2:57:02
>> Only in the cloud, cloud born.
2:57:02
This is what we've been doing. >> Yeah.
2:57:07
>> On on a public cloud or on your own cloud because I imagine that one of the benefits of backups and one of the one of the key things that people want to buy when they're backing up data is, hey, I'm I'm already tied to AWS.
2:57:17
I don't want everything on AWS.
2:57:19
I want I want security in case AWS goes down.
2:57:22
I want to back up somewhere else.
2:57:24
How are you thinking about that? >> Perfect.
2:57:27
>> So, and we've seen quite a few outages in last few weeks, right?
2:57:29
And what we're saying with democratizing your data, it's your data, >> whether it's AWS, Azure, and GCP, great clouds or other clouds.
2:57:38
>> We're making sure you can extract the data, >> make it portable between clouds, making accessible, performant, >> browsable, and searchable.
2:57:45
You can search and browse all of your data and all of your history immediately.
2:57:49
And because we're building our own software stack, software only, it's not going to cost you a dime.
2:57:56
It's actually cheaper than building it on your own or using existing cloud technologies to do that.
2:58:03
So we're trying to make sure that we make it a we we give you an easy button as a customer to just enable the use of all of your data, make it accessible to if you want to run snowflake or data bricks or red shift or bigquery or anything that you want on your data, that's great.
2:58:18
We are here to make sure that you enable to do it on all of the data that you have and all of the data that you had in the past.
2:58:26
>> But how could you possibly be cheaper than the big hyperscalers, the the the big public clouds?
2:58:31
I imagine that you know Microsoft, GCP, Azure, AWS, like they're buying so many Cay drives, so many Western Digital drives.
2:58:40
Uh how can you possibly compete on price?
2:58:45
>> That's an unbelievable question.
2:58:46
Actually, I don't want to just win on price.
2:58:48
I just want to make it easy for you.
2:58:50
So what we're doing even though we're still in the cloud using cloud building blocks, object storage, GCS, S3, Azure blobs, etc. Got it.
2:58:59
>> We're building in a very different way. Sure.
2:59:01
>> And actually building a more more efficient, it's called version of cloud snapshots. Got it.
2:59:06
>> That purposely built for backup and data retrieval. >> Okay.
2:59:10
Yeah, that makes a lot of sense.
2:59:11
Uh take us through the news. What's the funding news?
2:59:14
I want to ring the gong for a data storage company. Thank you very much.
2:59:19
And I'm also very excited.
2:59:20
So we raised $500 million in total.
2:59:23
$300 million just in this round. Really excited.
2:59:26
Led by Elad Gil with not only an amazing investor, he's also an amazing human being. >> Yeah.
2:59:33
>> And we we got >> What's it like?
2:59:35
What's it like being what's it like being a fly on the wall when you and Allah get together and talk about uh data?
2:59:43
>> Well, Elad is simply unbelievable.
2:59:43
you know, he's one of the most humble people I've met and at the same time brilliant, brilliant and so wellconnected.
2:59:51
I don't think I've ever seen an investor that everyone likes so much.
2:59:56
And I have the privilege to choose amazing investor.
3:00:00
I have Seoia and Lightseed and Greenox and Bond Capital and and likes of Omry Kaspi who are just amazing amazing investors.
3:00:09
And Eladgil is is very unique.
3:00:09
And Eladgil is is very unique. Actually, I so we got preempted by 16 VCs and I so wanted it to be a lad really and when a lad when a lad wanted said I'm going to lead my year round I was in New York he flew from San Francisco he came to my office
3:00:29
he basically wouldn't leave until I signed and to be honest I really really want to do that because I got to know the the person not just the investor in the last few months and and year he he put a small check in a previous found and honestly we just fell in love. Not
3:00:42
Not just myself, my other co-ounders as well.
3:00:48
>> So >> that's incredible.
3:00:49
>> When we had the chance, we had to do it.
3:00:51
>> That's and really really happy, excited about it.
3:00:54
>> You wrote the book on high growth. >> You did. >> I know. I know. And >> absolutely. Absolutely.
3:01:02
And I'm I'm really thrilled.
3:01:03
We have now a lot of capital in a time when we can we can now plan ahead.
3:01:10
We don't think need to think about the macro.
3:01:12
We don't need to think whether everything's going to continue to be rainbows and unicorns.
3:01:15
Do we going to have a a a downturn soon? >> Who knows?
3:01:20
But we know we can build a strong fundamental business >> that's going to be for a very long time. >> This is hilarious.
3:01:28
But it's a great take and it's a great way to build your company and your business so that you can take advantage of these tailwinds but also survive the headwinds and uh congratulations to you. Great.
3:01:38
This is this is what we need. >> This is a >> Exactly.
3:01:42
We're here for a long time. >> Yeah. >> Yes. >> Forever. Forever.
3:01:44
Is this your Do you want this to be You've done four companies prior to this.
3:01:48
Do you want this to be the last one?
3:01:49
You You just want to >> just >> Last one. >> Last one.
3:01:53
>> All the way to the IPO and beyond. >> Yes. Yes. >> That's my goal. >> Fantastic. >> Incredible.
3:01:57
You have incredible energy.
3:01:58
I'm excited to uh follow uh follow your journey and you're welcome on the show anytime.
3:02:05
>> Thank you so much for coming. >> Thank you very much. I'm really excited. I love your showing. Thank you very much.
3:02:09
I'm going to get back and tune to that. Thank you. [laughter] >> Thank you. We'll talk to you soon.
3:02:12
Have a great rest of your day. Cheers. >> Goodbye.
3:02:15
Uh that that is worthy and valuable.
3:02:18
We were debating uh what is worthy and valuable.
3:02:20
That feels like a company.
3:02:22
That's the worthy and valuable company of San Francisco.
3:02:26
>> He's keeping What do you need to do?
3:02:26
I don't even >> I'm glad he's keeping our all of our data >> like Yeah. Yeah.
3:02:30
It seems it seems it seems extremely valuable. >> He's he's that guy.
3:02:36
>> Well, we have Gork from Fall in the Ready Room >> uh with some massive news. He's back on the show. You know him. You love him.
3:02:44
He makes all the things possible.
3:02:48
>> Every time you're on, I'm like I He's going to be back on.
3:02:51
>> He's going to be back on soon.
3:02:52
>> You guys Merry Christmas. Merry Christmas. >> Thank you so much.
3:02:56
Good to be back in in the temple of technology. Capital of capital. There was one more. The fortress of finance. >> Fortress of finance.
3:03:04
[clears throat] There you go.
3:03:05
[laughter] >> Thank you so much for coming on the show. Uh give us the news. What happened?
3:03:12
>> Yeah, today we announced our $140 million [music] series D.
3:03:18
Seoat and meaningful participation from Kleiner Perkins and Nvidia.
3:03:22
It's the SEO capital firms.
3:03:26
[laughter] >> We had an incredible year this year.
3:03:28
We have some of the biggest advertisers, retail platforms, design and productivity apps and movie studios generating images and videos on the platform and we we >> 8xed our revenue in the whole year.
3:03:43
So it was >> this is our third fund raise of the year.
3:03:48
We we announced 5B earlier this year in the beginning and then >> you got one more.
3:03:53
You're going for the four Pete won a quarter. Come on. Come on. We got We got two weeks.
3:03:57
[laughter] >> You got two weeks.
3:04:01
>> Couple remarkable couple weeks.
3:04:01
What's been uh what's been the biggest driver of of revenue growth?
3:04:05
Has it been uptime uh you know being a one-stop shop like like what what messaging has really resonated the the most and driven the most growth for you this year? >> Yeah.
3:04:17
So beginning of this year, we thought we were going to ride the AI video wave for the whole year.
3:04:25
>> That that was that was accurate.
3:04:25
It was it was an incredible year for AI video.
3:04:30
But what was surprising to us is actually rise of image editing.
3:04:32
Um like image models existed a couple years ago like that's how we started our business.
3:04:41
But image editing, one of the first good models, uh, came out around May and now it's a bigger part of our business than than AI video.
3:04:49
That was surprising to us.
3:04:52
So we thought we were going to ride a big wave but another even bigger wave you know collided with it and are used >> is that is that surprising because >> I mean when you think if if it's very it's very common place now to like one-shot a great image output >> and it's so much harder to oneot or even get a great video output.
3:05:13
You can get a decent video output.
3:05:15
So I feel like it makes sense.
3:05:17
Everybody's making images all the time.
3:05:19
It's like uh it has it's it's like when you think about uh in the workplace there's just so many different use cases even even you know for consumers.
3:05:29
So I think it makes sense and it really is just exciting because that's uh the image models feel like they're so good now.
3:05:34
Everybody's so used to seeing it and getting kind of like faked out by an image now because you can't tell the difference.
3:05:41
video, you can still usually tell, but it feels like maybe in a year from now, it'll be the same >> situation where it's like, I just don't know what's real.
3:05:49
I don't know what's what's fake. It's it's all confusing. >> 100%.
3:05:53
Video video models are still very hard to work with still.
3:05:56
Uh some really talented AI creative people create great content with it, but it hasn't really reached mainstream.
3:06:04
I would say it it takes even more effort to create an ad with a video if it's like high quality than actually shooting it yourself.
3:06:12
But what happened with image models is going to happen with video and the user experience of video models are going to going to get much much better and you'll have even even more mainstream adoption of of these models. I'm pretty sure of this.
3:06:28
And that's what makes me really excited because we we went so far.
3:06:30
It's it's a lot of image models, a lot of image editing, just just a glimpse of video models and this this is all going to get better and better and it's going to reach complete mainstream.
3:06:41
All the studios, all the retailers are going to make use of this technology. >> How Oh, sorry. >> Yeah.
3:06:49
Just uh what what are you seeing like how are you thinking about 2026 uh from a model model progress standpoint?
3:06:58
uh you know, Nano Banana was obviously, you know, massive uh leap.
3:07:01
I'm expecting we'll see uh even more activity in 2026, but I'm sure you have uh somewhat of a preview just given given uh your guys' position in the market. >> Yeah, exactly.
3:07:14
So, usually one of the Frontier Labs pushes the boundaries.
3:07:17
In this case, it was Nana Banana twice this year.
3:07:23
It was like their first release and now this very recent Nanovana Pro release but very quickly e either the open source community or or labs from China people catch up.
3:07:34
Uh there are a couple reasons for it to be honest.
3:07:38
Once once they see there's demand for it once people know exactly what to build for it's usually easier for them to get motiv motivated and catch up.
3:07:47
but also some of the tricks, some of the the research tricks leak and people use them and and train these models.
3:07:55
The the model market for generative media is a lot more fragmented than LLMs. There's so much choice.
3:08:02
There's so many models that are different than that are better at different things that the the best model keeps changing.
3:08:09
Even Nana Banana was dethroned couple times throughout the year.
3:08:13
Right now it's considered the best image image editing model, but I don't know how long that's going to last.
3:08:21
>> What are you uh excited for um in terms of capabilities for next year?
3:08:27
Do you have do you have specific like benchmarks that you're tracking or even like functionality like um I've noticed I have one that's the where's Waldo test where I will ask you to generate a full where's Waldo and even Nano Banana Pro still can't quite do it.
3:08:47
It'll either put Waldo right at the center or it'll make two Waldos.
3:08:49
And th those images in the ch children's book are really complicated.
3:08:54
It's not just a portrait and there's maybe not enough training data on the internet.
3:09:00
But that's one test that I've been tracking.
3:09:01
Do you have your own internal benchmark or you know that whatever you think is like next the thing it can't do right now?
3:09:08
>> Yeah, I have some of my favorite prompts that I try with every single model. But I rely on our team.
3:09:13
We have great creative people in the team.
3:09:16
They spend all their living hours working on these models.
3:09:23
They are the usually ones coming up with very creative ways to utilize.
3:09:28
One thing that changed with nonabanana is you can actually feel the model has more world knowledge than than other models and that opens up other door.
3:09:35
I don't know have you seen people are now adding some web search and creating like newspaper articles on the fly things like that that is that are very creative uses of these models.
3:09:47
Uh, and on the on the video side, people really want more controllability.
3:09:53
They want character consistency.
3:09:55
They want scene to scene consistency.
3:09:57
And some of the releases that happened recently, [clears throat] Cling, for example, is is one of the better video models out there.
3:10:04
They've uh announced some editing capabilities which are pretty remarkable.
3:10:12
And all of that is going to get easier to use.
3:10:14
And once people have more consistency with the scenes they're creating with with video models, I think that's going to make a big difference.
3:10:22
>> Yeah, I always see those videos of uh it's a little yachty walk out.
3:10:24
Uh that is character swapping and it's always really obvious what's going on.
3:10:30
It's rough around the edges, but it's still hilarious because it's a great meme.
3:10:33
And I definitely would predict 2026 is the year that that that little yachty walkout just looks 100% real.
3:10:45
next fund raise announcement. >> I can't wait. I can't wait. Yeah. Yeah. Yeah. Yeah.
3:10:48
We need to do that for you.
3:10:49
We need to get get your body scanned a little bit.
3:10:52
>> Uh uh you've never asked this question, but you might know the answer.
3:10:55
Do you know why it's called Nano Banana Pro?
3:11:00
>> Where do you have any idea what the origin is of the name?
3:11:03
>> So, they had a code name Nano Banana.
3:11:06
Usually when they put these models into the uh benchmarking websites, they usually add a code name like they were Blueberry was one one code name, Red Panda was another and this was Nana Banana and people recognize the model like that and they kept it. That's the story I know.
3:11:24
I don't know if there's another there's another version of the story.
3:11:28
>> But I I guess the other question is uh is obviously it is a code name but where' the code name come from?
3:11:32
Uh Google has a long history of using fruit, although so does uh OpenAI with strawberry, but uh all the Android iterations were like ice creams and desserts for a long time.
3:11:44
Um but the question is is Yeah.
3:11:46
Is is is what's the nano doing there because I want the full banana.
3:11:52
[laughter] >> Give me the Don't give me the nano banana.
3:11:55
Give me the give me the gigab banana.
3:11:57
I want the gigab [laughter] banana. The biggest exa banana. The mega banana.
3:12:02
I want the biggest banana model.
3:12:04
Don't give me the shrunken down nano one.
3:12:06
I want the I want the gigab banana version.
3:12:08
>> Yeah, I think it's using the smaller Gemini model as the as the reasoning as the reason.
3:12:14
That's why it's nano, but no [laughter] mass but it's funny.
3:12:17
It's funny to have fun with.
3:12:19
Anyway, thank you so much for coming on the show.
3:12:22
Congratulations on the massive news and thank you for supporting us all year long.
3:12:26
>> And you got to if you 8x again next year, you got to 8x the number of fundraises, too.
3:12:30
that put you at like two fundraisers two fundraisers a month. Two fundraisers a month. 24 for 2026. We'll see. >> That'd be great.
3:12:39
>> Uh but uh congratulations to the to the whole team and uh we're very excited for you guys. >> Have a good one. >> Great to see you. Cheers. >> Goodbye.
3:12:46
>> Well, we have our next guest already in the reream waiting room.
3:12:49
We have P Pedro from Bra, the founder and CEO of B um announcing a massive partnership.
3:12:56
We're very excited to welcome him to the TVPN Ultraome. >> Welcome to the show.
3:13:01
>> Good to see you, Pedro. How are you doing? How's your day? Merry Christmas. >> I'm great. How are you guys? Thanks for having us. >> We're great.
3:13:08
We're in the We're in the Christmas spirit. We are in the Christmas. We got bells.
3:13:10
Very very holiday themed [laughter] holiday themed shows for the rest of the year. >> Yes.
3:13:17
>> But uh but it's great to it's great to meet you on the show. Yeah.
3:13:18
Please take us through the news today.
3:13:21
Uh, oddly I'm actually a fifth third customer, so I I want I want to know how this this uh this applies to me.
3:13:30
>> Yeah, you get a Brex cartoon.
3:13:30
No, so in all seriousness, um, thanks for having me.
3:13:34
So, uh, today we're announcing a pretty big partnership between Brex and Fifth Third Bank. Uh, it's a $5.
3:13:38
6 billion commercial card partnerships where uh, effectively >> Wow, >> massive. >> So good. >> I heard a big number.
3:13:48
I had to say >> I I want I want that in my office. Fantastic.
3:13:51
Fantastic. And uh and we're really excited just because you know when we look into across all the US and we just see you know tens of thousands of businesses out there that are still 98% of business are still using legacy corporate cards and you know there's so many uh there's so much opportunity in
3:14:07
just automating how these teams run their finances and vifer just has this massive distribution and trust and of course has the the financial services and the the software and the AI that just helps these businesses automate so much of their manual work and better allocate capital. Um, and party. Um, and party. >> Yes. Sorry to interrupt.
3:14:24
I'm curious when when you guys started working on embedded products.
3:14:27
Because if you go back to 2021 and 2022, I'm sure there was a bunch of companies that or at least a few that got created to go and pitch some of these same banks and say, "Hey, your corporate I don't know if people remember anybody that remembers SVB like corporate cards back in the day." I had a few of those.
3:14:44
>> Their UI was truly insane.
3:14:44
It was It was like, "How is this how is this?"
3:14:48
>> And you had like a different You had like a different login, too. It was crazy.
3:14:51
>> It was truly the most product experience of all time.
3:14:54
>> And it was like this is Silicon Valley Bank.
3:14:56
We're supposed to be the tech of not to talk but beat a dead horse there.
3:15:00
Kind of >> at some point you said like hey like like we'll go compete here as well. >> Yeah. >> Yeah.
3:15:07
So so for us it's really been driven by by a lot of just customer demand.
3:15:11
So we saw we started this with with Navon and Zip uh where they really saw a lot of the value in bringing financial services and card workflows into their software. Sure.
3:15:21
>> Uh and we're really excited about it because it's just a oneplus 1 equals 5 situation.
3:15:24
Both products becoming better together. Yeah.
3:15:26
together. Yeah. And then as we thought about the rest of the US and you know there's you know 8% of businesses are now you know accessible through this partnership for example in the US which is a really exciting thing in the commercial space and and the really big thing is how do we make the banks
3:15:39
product materially better and when you bring the technology and uh you know what we've done on the card side and especially the financial infrastructure that we've built from scratch like we don't run on stripe issuing or marquetta we just build our own rails from the ground up that enables that partnership to actually take place. So, uh,
3:15:52
So, uh, >> how does it how does it actually work?
3:15:56
Is it is it fully white labeled or does somebody in in First Third get kicked out? >> No, no, no.
3:16:02
It's actually it's actually a fully uh a fully Brex uh uh branded card and and the reason is because Fifth Third wants to have uh someone that's actually responsible for delivering this great customer experience on the card and implementing the software and rolling that out to their customers.
3:16:16
And what they do really well is uh the banking side, right?
3:16:20
is a lending side, is the banking, is the relationships and you know the thousands of branches and just the thousands of uh uh distribution partners that they have on their side uh and the tens of thousands of customers they serve are all effectively relying on that and already have that relationship and now they get a Brex card which are really excited. >> Yeah.
3:16:39
>> Sorry you mentioned you're not you're not using Stripe for what was it issuing issuing.
3:16:44
Um, does does Stripe or do do are there other FinTechs that do play a role in like your supply chain or are you like down at like an a layer like just like what what's kind of going on under the hood? >> Yeah.
3:16:59
So, what we've done since uh 2018 on Brex is we actually built our own financial infrastructure from scratch. Okay.
3:17:06
>> So, we actually went straight to the metal on Mastercard and built everything from the ground up.
3:17:09
And because we vertically integrated the whole thing, this created this pretty big advantage uh on everything that requires like bare metal capabilities on financial services.
3:17:19
So for example, global, right, we operate in over 200 countries today with local cards, local issuance because for us it's just a matter of saying, "Hey, Mastercard, we're going to issue in Europe or Brazil or India or Mexico."
3:17:31
And just flipping a switch for them because we are our own issuer, right? We we run our own stack. Yeah.
3:17:36
>> And then Fifth Third was another example where we said Fifth Third wanted to issue a Fifth Third issued card.
3:17:39
They wanted it to be their name on the card.
3:17:43
It has to be under their license on Mastercard and all of that.
3:17:45
And for us is just effectively, you know, bringing in a new bank live which you know we have a few banks on the back end and including Fifth Third of course.
3:17:52
So for us it was uh it was sort of piggy back on this advantage that we've had over over many years by building our own rails from the ground up which is really >> How are you um how are you thinking about uh we've had bunch of different teams and companies on the show building like new layer 1 blockchains for payments.
3:18:10
They're touting like speed default global all these things.
3:18:12
We've had a bunch of stable coin issuers and and business.
3:18:17
I'm sure in conversations that you have, you know, you're you're being pitched these companies from to be an infrastructure >> provider.
3:18:25
I'm sure your your investors are like maybe asking you sometimes, should we should should should there be a Brex stable, you know, who knows, right?
3:18:32
I'm sure these questions are coming up.
3:18:33
How do you think about kind of the layer one landscape?
3:18:34
And you're you're operating a a global business today.
3:18:39
Uh and so I would I would you know your opinion on some of this stuff in terms of the the real value of it I feel like would carry a lot of weight. >> Yeah.
3:18:48
So the way we think about it is maybe a little bit different which is we we think that first like stable coins and and and blockchain in general have you know tremendous application and we're really excited about a lot of the work there.
3:18:59
We you know we announced support for stable coins this year.
3:19:01
Uh when it comes to our banking product and you can pay the card to stable coins.
3:19:05
We've done a lot of that.
3:19:05
We've done a lot of that. But when we come when it comes to global right and and just s supporting customers in a wide variety of countries uh really the the challenge there is the on-ramp and off-ramp right and specifically you know the the fiat last layer for uh you know
3:19:21
an employee to reimburse you in you know u Indian rupees or Brazilian riis and then to for you to settle the card in that currency and do all that locally and unfortunately stables don't help you that much on that last layer and the whole actually a misconception about the
3:19:36
way our global product works is a lot of the value comes from remaining in local currency because what they're trying to do is minimize FX right even on stables like FX has a cost just intrinsic to it >> sure >> and a lot of what we're trying to do is keep you entirely in rei so your revenue
3:19:51
in real ice in Brazil are settling your expenses in realis or in euros or in GBP or whatever currency you're in so a lot of the infrastructure build is to enable this multicurrency and multi-entity operations versus having to do the FX X and a lot of the benefits that stables typically bring to the table. So, our
3:20:07
So, our use case is a little bit different.
3:20:11
>> I'm sure that's disappointing to people building global [laughter] payments L1's.
3:20:14
They're like, "Wait, you're supposed to need this?"
3:20:18
>> I mean, we do use it internally for some stuff, but but you know, I would say the value prop for our customers is we stay in local currency as much as possible because just minimize so much savings and effects. Yeah.
3:20:28
>> What what what are the other uh like keys to success?
3:20:30
Uh obviously you you you know you have experience internationally but you're like a YC company.
3:20:38
I think I think of Brex very much as like an American company.
3:20:40
Um but then in terms of winning internationally, what does it take?
3:20:43
What what have the lessons been?
3:20:46
What are the uh what are the interesting insights or what were some surprises that that uh cropped up on the journey? >> Yeah.
3:20:55
So I would say the biggest one is that when you go into like true global like true enterprise the amount of requirements and specifically on both the card and expense management side is unbelievable.
3:21:08
So you have these rules for example local PDMs.
3:21:10
So when you are in Europe there's these rules that if you have a German employee traveling to London is one set of rules.
3:21:16
If you have a London employee traveling to Germany completely different set of rules. Whoa.
3:21:22
>> And then if they rent a car there's different mileage requirements.
3:21:23
different mileage requirements. And then all this information is something you have to be aware of and >> you know of course we use a lot of the car data to make that easier uh and recon it automatically but probably the the the biggest challenge overall is just building the core financial infrastructure because this is something that you know we're literally the only issuer in the US that actually had done
3:21:41
this from scratch uh and just the amount of time and energy that we dedicated into building these you know core financial services infrastructure uh is pretty tremendous but you know it gave us a pretty big advantage when it comes to these enterprise customers and you know Today we have maybe three or four years ago I think we had five or maybe 10 public companies on Rex and now we have 250 and growing. So that's exciting
3:21:59
So that's exciting things. >> That's amazing. >> Awesome.
3:22:05
>> Well, congrats to the whole team on the deal. Congrats to Art. Yes.
3:22:07
Uh and uh chief business officer, correct? >> CBO CBO.
3:22:12
He was coming in to defend uh Keith Ra Boy last week was was talking some smack about the the BD uh BD people of the world.
3:22:21
Does open have a have a chief business officer because they just got a CRO.
3:22:24
They have a they have a CFO and a they have two CEOs.
3:22:27
I think they're missing a >> underrated title.
3:22:30
You got to lock down art.
3:22:32
He's going to get poached. >> Artist. Don't listen to them. [laughter] >> Awesome.
3:22:38
Uh well, yeah, congrats to the whole >> Congratulations. Congratulations.
3:22:39
Great to have you on the show. >> Yeah. >> Thanks for having me. I appreciate it. >> We'll see you soon. Have a good one. Merry Christmas. Goodbye. >> Thank you. Merry Christmas.
3:22:46
Uh, [laughter] >> the ho ho ho really gets me every time.
3:22:52
I've I've been thoroughly enjoying it. I I love that.
3:22:54
I love the idea of uh of countrysp specific uh pdiums because if I had a German employee, I would want them to know that they are not an American employee and they are secondass citizen in the in this organization and they will be not they will not be dining out on the company dime and a nice they will be eating sauerkraut in the gutter for $5.
3:23:17
[laughter] >> That's brutal.
3:23:20
The most American the most American American John Kugan everyone. >> Yes.
3:23:24
[laughter] Uh well uh speaking of travel to international countries, if you go to Saudi Arabia, you can now booze it up.
3:23:30
I guess you can drink alcohol.
3:23:33
Uh Saudi Arabia is loosening alcohol rules letting non-Muslim foreign residents earning over $13,000. Uh you can buy alcohol.
3:23:42
So you have to check you have to do a whole >> check. Daniel's line is great.
3:23:45
He says, "This is such a galaxy idea.
3:23:47
It could only come from a mind totally disconnected from normal material reality. It's hilarious. >> It is. It is interesting.
3:23:55
Imagine, hey, if you want to do, you know, drugs, if you want to consume alcohol, you got numbers, but you have to be putting up numbers. >> Yes. Yes. Exactly.
3:24:06
>> Be putting up numbers. Exactly.
3:24:06
And so, you know, if you're underage, >> actually, cannabis should be like $10 million a year on your W2.
3:24:13
>> I was about to say, but you know what happens then?
3:24:15
So, you have everyone in America, you know, you turn 17, 18, 19, you're not 21 yet.
3:24:21
You get a fake ID to try and buy some booze.
3:24:23
You're going to need a fake W2 as well.
3:24:26
>> You're going to [laughter] fake your income statement.
3:24:28
And you're going to need to do all these crazy things where where you have all these like circular deals.
3:24:33
>> You're bringing your your fake W2 to the corner liquor store just being and they're just like looking through every line >> in in Saudi Arabia.
3:24:39
So you you're in Saudi Arabia and let's say you're making $1,000 a year USD or you know you're making 10,000 real.
3:24:47
You need to go and set up a circular contract where where you're a 17-year-old, somebody else is 17.
3:24:52
I pay you 10,000, you pay me 10,000 and then we get >> a couple times. Exactly. Do it a couple times.
3:24:58
Then we're earning enough to go buy alcohol.
3:25:00
We can go get drunk together. >> That is crazy. >> That is truly galaxy.
3:25:04
We're we're we're out galaxy braining them.
3:25:07
We're gonna we're going to galaxy brain all the way to the top.
3:25:10
Uh we do have to hop on with Riad soon.
3:25:14
Um let's close out with anything else that's on the timeline.
3:25:17
Uh Jordy, why don't you take a pass?
3:25:19
Let me know if there's anything that we m that we uh >> fluid stack raising uh apparently 700 million out of 7 billion valuation. >> Okay.
3:25:30
>> Built on Google back leases for new AI data centers according to Rohan uh Paul.
3:25:37
uh fluid stack a real player on the semi analysis uh uh uh what's what's it called the >> cluster max >> cluster max um and uh so not not surprising here interesting that uh potentially you've got Leopold looking to lead the financing so dipping his toes into privates >> well the uh yeah I mean they have cluster max over at semi analysis they have inference max are they going to do looks max >> potent potentially they could.
3:26:06
We It looks like according, you know, looking at some of our officials, it looks like we might be developing a strategic looks maxing reserve.
3:26:15
>> I I mean there are lots of people that would comment on looks maxing and try and rank like the hottest men in tech.
3:26:18
I personally would only I would only regard semi analysis's opinion as credible on that on that issue specifically.
3:26:29
>> It must come from them. >> Post here from Buco.
3:26:30
He says, "Hectan acquired VMware, had coffee chats with the employees where he made fun of them, fired half the business."
3:26:37
So, a little excerpt here.
3:26:39
Earlier last year, Broadcom CEO Hawkan decided to host what he likes to call a coffee chat with employees of VMware, the software giant that Broadcom CEO had recently purchased for $84 billion.
3:26:49
The companywide meeting was Tan's effort to introduce himself and answer questions from those employees about life at the semiconductor firm. Crazy.
3:26:56
At the time, VMware's PaloAlto uh campus sprawled over 18 buildings and 100 acres of delicately pruned gardens, an outdoor amphitheater, and a turtle pond.
3:27:06
Employees enjoyed nice HR perks, including child care, marital counseling, and an annual $1,000 well-being allowance for anything from dumbbells to Xboxes. >> $1,000 on Xboxes.
3:27:16
That's like one Xbox every month. That's so many Xboxes.
3:27:23
>> You can actually only spend this on Xbox.
3:27:24
Uh, when Tan opened the discussion up to questions, a VMware employee asked if Broadcom provided such benefits.
3:27:29
Tam Tan seemed surprised.
3:27:32
Why would I do any of this?
3:27:35
>> I'm not your dad, he replied.
3:27:35
According to three people in attendance, >> we need a trading card. I'm not your dad.
3:27:42
>> Over the next few months, Tan fired about half of VMware's 38,000 employees. That is wild.
3:27:46
He also said Florida private equity, selling all but five of the buildings.
3:27:51
at the remaining offices.
3:27:52
Tan had the espresso machines removed. >> Okay.
3:27:55
Well, that is a question.
3:27:55
They need to stay caffeinated.
3:27:58
>> I got to hold the line here. >> What are they doing?
3:27:59
I mean, I'm okay with I'm okay removing >> doing white monsters.
3:28:04
>> If they're doing white monsters, then I approve of it, but if you're going to have a decaffeinated workforce, that just makes no sense.
3:28:10
That's just not elite performance.
3:28:13
>> He says the article says somewhat against the odds the turtles were allowed to stay.
3:28:16
So, >> you think do you think he he's putting espresso in the turtle pond?
3:28:22
>> No, I imagine I imagine he had a he had a like a massive broadsword and was above the turtle ready to let it all go and he's like, >> "I can't do it."
3:28:33
And he drops the it drops the blade and it falls to the ground, clanks him and he says, >> "You live to fight another day, turtle.
3:28:41
You're too important here."
3:28:42
>> He's got him making TPUs.
3:28:42
Completely different vibe from when Pat Gellzinger was getting a VMware tattoo on his arm or temporary tattoo at least showing his love for the company that he just bought while he was at Intel.
3:28:52
Uh Hawkan clearly cut from a different cloth but clearly also putting up big numbers.
3:28:58
Broadcom's been on an absolute run.
3:29:02
>> Alexis O'hane says been warning y'all.
3:29:05
AI everywhere dead internet real is increasingly scarce online and thus increasingly avaluable.
3:29:09
There's a wired article called AI slop is ruining Reddit for everyone.
3:29:14
This is my this has always been >> there's such an incentive for companies and people to just like create narratives on Reddit because AI is training on Reddit >> and uh the natural end state is you know it's 99.
3:29:26
9% bots and just a handful >> of humans.
3:29:29
So >> stick to the group chats I guess. >> Yeah.
3:29:34
In other news, Netflix has launched Best Guess Live, a new Netflix mobile game show where guessing the right answer based on five clues could win win you thousands.
3:29:45
Dylan Abbercato in this economy. >> Come on. Let's get those.
3:29:50
Oh, they're Oh, they're willing to spend $80 billion to get Warner Brothers 40 billion per war.
3:29:57
>> They should give you They should give you some IP.
3:29:58
You should be able to win Porky Pig.
3:30:00
I get Fogghorn Legghorn >> or some of the masculine films.
3:30:05
>> I want the Steven Seagal rights.
3:30:05
I want the rights to Hard to Kill for sure.
3:30:10
Dylan Elder Scott on our team team says, "Can I copy your homework?"
3:30:11
Yeah, just change it up a bit so it doesn't look obvious. You copied.
3:30:15
Of course, he worked at uh you know a competitor to this or or the precursor to this.
3:30:22
>> He created game shows.
3:30:23
>> He created game shows with HQ trivia, which you should know.
3:30:26
Run says, "A lot of people think CEOs are on coke or stimulants because of how hyper they look in interviews, but I think the unfortunate truth is that natural amount of energy is extremely unequally distributed."
3:30:37
>> I was going back Yeah, I was going back and forth on this one.
3:30:39
Obviously, it's a subweet of cart, but um I I I think he's I think he's just like that.
3:30:44
I think he's just I think he's just high energy and I think that so the the carp clip looks crazy as a single clip, but I actually watched the full interview and there is a flip on it which is maybe more negative which is like that was a question he was squirming on.
3:31:06
Like that was an uncomfortable question.
3:31:08
And I notice it on this show all the time.
3:31:10
If we ask someone a question and they're like not that happy that we asked that question, you'll see on their body language they'll cross their arms and and crossed arms is a is a is like a wellestablished body language for like I'm closing myself off versus like if I'm hanging out here with you, I'm just having a good time >> if I'm sitting up and >> Yeah. Yeah.
3:31:29
And so and so there's a world where where where you're literally they call it being in the hot seat.
3:31:34
>> The camera they just needed a better camera tracking.
3:31:36
So [laughter] >> yeah, they call it being in the hot seat.
3:31:39
And when you're in the hot seat, you're kind of bouncing around.
3:31:41
And yes, it can look like you're on a lot of stimulants.
3:31:44
Maybe you're on some caffeine.
3:31:46
Maybe you're a little wired, but also maybe you're dealing with a serious interviewer sorcin across from you on a stage.
3:31:54
There's nothing to help you on at Dealbook.
3:31:57
Like the the the crazy thing is you keep seeing people's legs all funny and it's like because you're just in a chair. There's no desk there.
3:32:04
So there's nothing covering you up.
3:32:06
So it's like you're very vulnerable. There's this big wall.
3:32:08
There's this big wall. has done everyone's looking at you and and also it's not just a private conversation where it's like you and Sorcin are just hanging out here having a normal conversation like there's a couple people all of our friends are here right imagine it's like all of your rivals are in the all of your rivals are watching
3:32:23
>> all your haters are watching online and all your rivals are in the building in the seats right there looking at you answer tough questions I don't know it it just feels like this is not that crazy of a reaction for a high energy guy who's kind of quirky who's in that position and is asking is is answering some tough questions. I don't know. I don't know.
3:32:44
>> But >> well, Tyler, figure out how to use AI to run an analysis on every guest we've ever had to see who and just rank their body language from most trustworthy to least trustworthy.
3:32:55
>> Yeah, I did like Gabriel here.
3:32:55
He says uh he's quote tweeting someone who's like there is zero chance that these hyperanimated CEOs are just naturally that way.
3:33:03
Kind of the counter to what I was just laying out as an argument.
3:33:05
And Gabe says, "Uh, cocaine expert here.
3:33:09
These CEOs do a lot of cocaine.
3:33:09
Feels like a very 2025 moment somehow." And I agree with that. I agree with that.
3:33:14
Uh, it it is a very weird weird thing.
3:33:16
Well, in less weird headlines, uh, we have some fantastic news from Lulu, who has raised a $40 million. >> Give me the mallet. Give me the mallet. I don't know. You go for it. Too late. Too late.
3:33:31
>> Congratulations to >> This photo goes hard.
3:33:35
>> It's a good It's a good photo.
3:33:35
She >> It's proper paparazzi.
3:33:36
She got caught by the paps. The paps got her.
3:33:39
Uh this is a throwback photo from when she was uh working on the Microsoft Blizzard deal.
3:33:48
I mean, the fact that she's a board member at Activision is just crazy at the time. A$80 billion company.
3:33:51
You know, people talk about Lulu like she's some like uh you know, smalltime PR advisor for startups, but it's like she is on the board 80 billion company, right?
3:34:07
>> Flies under the radar. >> Yeah.
3:34:08
Well, we're blown up or we're blown up here now. Sorry. Sorry about it.
3:34:11
Anyway, at least it's at the end of the show.
3:34:13
>> Um Lean Alib says the normies are waking up on TikTok.
3:34:18
They're saying Chach is washed.
3:34:21
John says perplexity is goatated.
3:34:24
>> Uh hard claw is they're ranking them.
3:34:28
>> They're all over the place.
3:34:28
Clawed greater than Gemini. >> Never be washed.
3:34:31
You don't want to be cooked either. >> Yes.
3:34:35
Be washed, cooked, or chopped >> from our >> If you're a language model that wants Gen Z adoption >> from our Gen Z employee who is currently both chopped and cooked, he's not here.
3:34:46
We hope he gets not you, the one who's sick, who we hope gets better soon.
3:34:49
But we didn't learn any lingo from you, Tyler.
3:34:54
>> Buco says, "What people get wrong, OpenAI's code red is bullish, not bearish.
3:34:57
It's an admission they were overeating, getting beat, and needed to focus.
3:35:00
That's what great teams do."
3:35:00
Now, here's the challenge.
3:35:02
Code Reds are really hard. It's easy to say yes.
3:35:04
Hard to say not right now.
3:35:05
All eyes on how they execute Code Red. >> I'm skeptical.
3:35:10
Overeating seems to be embedded in the culture.
3:35:12
Sam obviously likes to dabble in a lot of things.
3:35:17
>> Every code red is followed by a Baja blast. >> That's right. >> Let's get ready.
3:35:21
>> I think the next the next model should be >> Baja Blast.
3:35:24
Go back to the crazy names that make no sense. >> Stop it with the 5. 2 tomorrow. Wait, wasn't 5.
3:35:30
2 just supposed to come out today?
3:35:32
>> Uh that was if you looked at Poly Market, that's what it looked like.
3:35:34
It's now moved to I think by December 13th. Okay. 90%. So >> yeah. Yeah. Yeah.
3:35:39
Anyway, >> but also you got >> this is a separate topic, but I need to put you in the truth zone.
3:35:43
There actually are spots on the moon that are perpetually in sunlight. >> Oh, really? >> You figured it out.
3:35:48
>> The rims of certain craters.
3:35:49
>> Oh, >> the inside of them are always in darkness.
3:35:51
The the rims are >> the rim on the crater is always in the sun. >> Yeah.
3:35:55
So, that's where we need the data center. >> Okay.
3:35:58
Well, how much how much crater rim is there?
3:36:01
Is there enough crater rim to actually build a lot of data?
3:36:05
>> If there's not, you could probably nuke the moon.
3:36:07
[laughter] make more craters. >> Yeah. >> Yeah. I don't know.
3:36:10
I I still have trouble visualizing this.
3:36:12
Doing like the celestial body physics math in your head is very very difficult.
3:36:19
>> Other news, this person on X Kenu >> Nazari says they got their hands on some North Korean cigarettes. >> They did.
3:36:28
>> They got them in a DPRK stateowned restaurant from a waitress who is from Pyongyang.
3:36:34
>> Basically impossible to find any background info on them online.
3:36:35
They taste and look 100% What is that? >> I have no idea.
3:36:44
>> Uh, but I like the packaging.
3:36:44
The packaging goes pretty hard.
3:36:46
It feels uh >> does very >> but I can't support it because I don't support North Korea.
3:36:54
>> Uh, and this is a good place to end the show.
3:36:55
Sag Harbor Capital says, "If this niche Scandinavian brand doesn't ship my overcoat in the next 24 hours, I'm going to blow up the Nord Stream 2 pipeline.
3:37:06
>> [laughter] >> That's really funny.
3:37:09
>> He tags the brand, too. >> He does wear Oh. Oh, wait. Bergen B. >> I need an overcoat.
3:37:13
I I was trying to just go around New York last week with just my suit and I and I was kind of cocky going into it.
3:37:19
I was like, "Oh, John, nice coat.
3:37:21
You're you're [laughter] we're going to be outside for 20 seconds." >> Yeah. You're like succession.
3:37:27
Kendall Roy doesn't need a coat cuz he's so rich. I didn't say that.
3:37:33
>> I think Dylan said that. >> Dylan said that.
3:37:34
But I was like, yeah, like we're not we're [laughter] not that rich yet.
3:37:38
Whatever's going on in success.
3:37:40
>> We went we went for a half mile walk and I was devastated. >> We did.
3:37:44
But it's nice when you're in a coat.
3:37:46
It's fun to walk around New York City.
3:37:47
Also, it wasn't that cold, but you you were getting destroyed.
3:37:51
>> We got to pull up last post of the day.
3:37:53
Uh Skooks says, "The concept of getting sent to rehab by the Taliban because you and your cousins wanted to LAR as the Peaky Blinders in Afghanistan."
3:37:59
and uh found here that says reportedly four people in the Harat province were detained and sent to rehab by the Taliban's Virtue Ministry for imitating characters from British crime series Pey Blinders and parading around the city resembling the vintage gangsters an act seen as violating local values.
3:38:21
>> This is I have no idea how to process if this is real at all. >> Hope says Taliban L. >> This is crazy.
3:38:28
I mean, they look they look fantastic.
3:38:31
>> They do look fantastic.
3:38:32
>> I feel like this would encourage >> t potentially they could open up a tourism market for people uh kind of like the Disneyland for Pey Blinders enthusiasts.
3:38:42
[laughter] >> It's such a weird phenomenon to happen here.
3:38:45
Also, like what does being sent to rehab look like in Afghanistan?
3:38:48
They're just like >> no more no more peaky.
3:38:52
>> Is it like Alcoholics Anonymous?
3:38:52
You're like first step I am powerless to peaky blinders.
3:38:57
I I I am a Peiquey Blinders impersonator.
3:39:00
You have to come, you know, you have to say, "I'm an alcoholic."
3:39:04
Uh, you know, I I'm a Peiquey Blinders impersonator and I am powerless.
3:39:08
Uh, and the [laughter] >> and I, uh, you need to say the what is it? The Lord's Prayer. Something like that.
3:39:15
Anyway, >> anyways, uh, thank you for being with us today, folks.
3:39:17
Uh, we we love you dearly and we will see you tomorrow.
3:39:21
We hope a fantastic evening. >> Goodbye. >> Cheers.