Ben (2:14)

And remember during this time, that's when I started talking about viewing OpenAI's activities like they were a hyperscaler. When Google launches a new product, you don't have to assume that hey, it's going to work every single time. And in fact it's the exact opposite. A lot of these experiments don't end up going anywhere. It's fine. Like again, you have this massively scaling core business, you start to say like, hey, let's experiment in a bunch of these different areas. Some of them are going to work, some aren't. It's okay. But then ultimately that creates a scenario where you're sort of like opening up maybe too many fronts right, to the competition. Right. You're competing with Meta and social with Sora, you're competing with Google in some ways, you're competing with even like the Microsoft's of the world in other ways. And ultimately this just feels like, hey, let's like narrow the fronts. And I think a lot of people expected something like this for the last few months.

Tyler (3:12)

OTP in the chat is surfacing. A very interesting old take from Ben Thompson about OpenAI should not be in the API business. And now based on the way things look originally that was like, oh wait, well maybe Microsoft will be able to handle and scale the API demand. But API demand has been so huge and it's allowed Anthropic to develop such a solid business there that it's undeniable that OpenAI should also be in the API business especially.

Ben (3:39)

Yeah, the other side of that is like they clearly need to be in the harness business too, which is why Codex is.

Tyler (3:45)

Yeah, yeah. And so the hyperscaler, like your take of think about OpenAI as the new hyperscaler. I think the takes aged extremely well, especially with recent interviews with Dylan Patel and Dorkesh. Jensen just went on Strathecary. There's a whole bunch of new data points that show how compute constrained we are, how tricky it will be, how chips will be the key bottleneck. There's that interesting story that Tyler was recounting from Dylan Patel about how the TPU was developed by the TPU team. DeepMind didn't realize how important it was going to be, how compute constrained they were going to be. So the TPU went and sold it to anthropic and then DeepMind went back to them and was like, wait, wait, wait, we want those chips. Like we need the chips. It's particularly about the ability to marshal compute at Hyperscale. I was interested to look at like the history of sidequests among MAG7 companies, among trillion dollar tech companies because it's all over the place and so it's very hard to paint with a broad brush. I think Right now the there's a huge narrative around like OpenAI was doing way too many side quests, they need to do zero side quests. And the reality is probably like, you know, we've seen this with Riley Walls joining the labs team. Like there will be small projects, there will be acquisitions, there will be a continuum of bets. There's just a level of refocusing that's going on right now and reorganization. And this has happened at many, many.

Ben (5:05)

Yeah. And I think the bet with the OpenAI Labs team is you have a really small group of people that are focused on creating or being quick to new product like approaches. But that can be again like a two pizza team. And that type of experimentation is going to make more sense if the rest of the company needs to refocus on

Tyler (5:25)

enterprise and the core business history of sidequests and tech. Can we paint with a broad brush here? You know, spoiler alert. I think the answer is no. But there are some fascinating stories. So Google has a balloon Internet play that's a serious company called Project Loon, where they inflate balloons that go into the stratosphere. I believe they go high up and then they deliver Internet sort of competitive Starlink.

Ben (5:49)

They also have the fiber play too.

Tyler (5:52)

Fiber play? Oh yeah, they just sold that. That's not even close to the weirdest thing. The weirdest Google side project that I found is they make a contact lens that will tell you how drunk you are. I'm not kidding about this. Google, they have a project, it does more than that. It's supposed to do biometrics and it can do a lot of different things. But one of the things that it can measure, it can measure glucose in your tears, it can measure any sort of like biomarker that's in your tears, which apparently is like a rich source of data. But one of them is blood alcohol level. So you can put in this contact lens from Google and it will tell you how drunk. Jarvis, am I drunk?

Ben (6:29)

Am I good?

Tyler (6:30)

Am I good? Am I good to drive?

Ben (6:32)

You're absolutely not.

Tyler (6:33)

He's like, sir, you should take a Waymo tonight. Would you like me to connect? You see, this is all part of the plan. They also briefly owned Boston Dynamics, but most Importantly, they bought DeepMind, which was completely seen as like this wild card side project. How does that fit in? You know, it's a bunch of researchers and then it became like the most

Ben (6:49)

critical thing in Amazon has taken tons of shots during delivery and home security stuff. They also own Twitch, but they never really linked the site to live shopping and close that loop.

Tyler (7:00)

Have you thought that that's weird.

Ben (7:01)

Jassy doesn't do earnings calls.

Tyler (7:03)

He doesn't do earnings calls on Twitch.

Ben (7:05)

Of course Apple tried to build a

Tyler (7:06)

car, then pulled out. Who knows where the Apple Vision Pro goes? Although of course I hope it continues. I'm hoping for another. Another Apple Vision Pro. Apple Vision Air. Just make it lighter, same screen. That's the trick. Make it like a thousand bucks. I think it'll sell. And they have a bunch of health moonshots. They've been working on non invasive glucose monitoring, which is. There's some book about it called like the. The White whale of Biotech or something. It's something that people have been working on for so long and they've never been able to crack it. The best thing I think they have is that you can get a continuous glucose monitor. Thank you for the W's in the chat, by the way. There's a lot of W's in the. You can get a continuous glucose monitor that is invasive, meaning it is pricking you. It is measuring your blood and then calculating the amount of glucose in that. And you can wirelessly connect that now to your Apple Watch. But they can't do it in the Apple Watch. There's always been the question about could you just shine a light through your skin and detect the blood, the glucose in the blood. Very, very difficult to do. Lots of money spent with little to show for it. At least so far. Meta is probably the most, you know, egregious side quests.

Ben (8:09)

They don't do side quests. They do full quests.

Tyler (8:10)

They create side quests in VR. There's actually one of the popular games is all about doing side quests. And yeah, I mean they bought Oculus, they bought a bunch of VR studios, they rolled everything up, they renamed the company, spent tens of billions of dollars on what is starting to feel like less of a side quest, but still is so early. You know, the Meta Ray Bans are like a success but to the tune of millions of units. Not, you know, billions of units or anything like that or hundreds of millions of units. I think the iPhone has an install base over a billion now and the ramp from here to there on Meta Ray Bans is going to be long. Tesla launched a premium tequila in a lightning bolt shaped bottle. So you know, it comes for all different max 7 companies. But truly like sidequests come in all shapes and sizes. Some are just good for morale. Like it's just fun. We did, we do side quests here all day long. TVPN simulator. That's a side quest. What was the other simulator? Jeremy Gifon simulator that was a side quest. They're just fun. Some of them are good for marketing, good for attention, good for fun. Some are complete dumpster fires where you just pour money in and it just sucks all resources and you get nothing out. And then some reshape businesses entirely. DeepMind's a great example and there's certainly others in the Mag 7 that have really, really changed the business.

Ben (9:24)

It seems like the entire boring company is a side quest.

Tyler (9:27)

Yeah, it's technically a separate company, but Elon's. Yeah. King of. King of sidequest. Although I think.

Ben (9:32)

Yeah, I mean it just, it feels like. It feels like the company that gets the least amount of attention. That's not like on the critical path for many of the other projects.

Tyler (9:41)

Totally. Some of OpenAI's teams come from very small teams with relatively tiny compute budgets, but they get a lot of attention sometimes because of the particular product category. So Soar is a great example where small team, not huge resource investment, probably a lot of inference and training cost. But relative to Codex 5.4 spar, I don't know. I don't actually know like how we're looking on the order of magnitude there.

Ben (10:06)

Yeah, I think a big. Yeah, big part of super viral.

Alex (10:09)

Right.

Ben (10:09)

And what, what percentage of the team, the overall team's energy is going towards a specific product.

Tyler (10:16)

Yeah, yeah. So the idea of experimenting quickly and then consolidating efforts even faster makes a ton of sense. Nano Banana was a big deal for Gemini. Bringing image, video and audio generation together In a single ChatGPT flow is clearly the next step. And so some of this is not. It's probably not going to take the form of like, stop doing the side quest. It's like, let's fold that into the main quest because clearly the interaction pattern of ChatGPT is where people want to go. And so once we've done the experiment, it works. Put it all together. Dylan Patel and Doorkash said the Tam for GPT 5.4 was north of $100 billion, which is crazy for a bunch of reasons. I mean, it's just a huge, huge market that was created in just a few years. The enterprise opportunity in general is crystal clear for anyone involved. At the same time, you still do need to experiment to make sure you are early to create the next breakout product experience. And so with that backdrop, OpenAI Labs and being more efficient with the shots on goal makes a lot of sense. I still think that the overall narrative around AI, just in AI broadly this year will be about the main quest, which I see as like, compute scaling, raise the money, do the deals, grow the capacity. I was thinking back to Travis on the show saying, if you're doing something and it's easy, it's not valuable. The key is if money matters, which I think we say, we would say it does, especially in certain categories. He was probably thinking of ride sharing, where there was a capital war and AI compute, but there's also a capital war. You need to be the best in

Ben (11:38)

the world at it. Yeah, yeah. And I think, I think overall there's real competition now. It's intense. Right. You have, you have OpenAI, Anthropic at the frontier, pushing very, very hard. But the other side of this for OpenAI is like, yes, there was a ton of stuff that was announced last year. There was, there was hardware, sora, et cetera. But Sam was running around doing all these different mega deals for the compute side that now serve the main quest. And so the positioning is actually great.

Tyler (12:04)

Google Capital bloke, the longtime Google bull, says, so Anthropic and OpenAI are going to just give the consumer market to Google. And I don't know how.

Ben (12:14)

How.

Tyler (12:15)

I mean, yes, they're like, like OpenAI reportedly planning to shift the strategy to refocus around business users and vibe coders. There's a lot of stuff going on there. Listening to some of the data around the retention curve of the various products, like, I don't think that they're giving up on consumer at all. That seems like sort of an odd read.

Ben (12:32)

Yeah. And we can pull up this chart that Sam showed of Codex usage. This is like the. Again, this is like what I think is informing the battle with Anthropic as well as, like, this chart is going to inform the strategy shift, which is like, hey, we can run. We can take revenue into the hundreds of billions of dollars with the current products that we have. Let's focus on them and make the best possible products. In other news, OpenAI is forming a joint venture with TPG, Advent International, Bain Capital and Brookfield Asset Management.

Tyler (13:04)

This is great news to form a joint venture.

Ben (13:06)

AI is coming to distribute enterprise products across the firm's portfolio companies and. And beyond the proposed deal as coming

Tyler (13:13)

to Fogo de Chao. Bain Capital owns Fogo de Chao, the Brazilian steakhouse.

Ben (13:17)

Maybe now they can take Apple Pay.

Tyler (13:19)

Oh, yeah, we got cooked on that. Maybe they deliberately don't. I wonder if Apple Pay is expensive for them. And this is actually a cost consideration, Fiji Semo said. This news came out a little bit earlier than we planned. We're excited to be building a deployment arm and we'll share more details soon. Companies have a ton of urgency to deploy AI in their organizations and we're sprinting to meet that demand. We more than 1 million businesses run on OpenAI products. Codex is now at 2 million weekly active users, up nearly 4x since the start of the year. API usage jumped 20% in the week after GPT 5.4 Watch launched in Frontier, which launched last month to help enterprises build, deploy and manage AI. Coworkers that can do real work has way more demand than we can handle. That's why we launched Frontier Alliances. So we leverage our ecosystem of partners and scale and to scale. And that is also why we're launching a dedicated deployment arm tasked with embedding forward deployed engineers deeply inside enterprises. This project has been in the works with our investors and alliance partners since last December and we are grateful for them and their partnership. We're still early, but the speed of adoption is a clear signal of where this is headed. We're excited to not just be building these technologies, but also building many ways for companies to deploy them and get impact. There was a big, there was a big talk for a long time about like the the next gen private equity firm will buy businesses and like deploy AI inside them. And this feels like well maybe that works at the mid market private equity level, but you don't necessarily need a new AI native private equity firm because

Ben (14:45)

Bain Capital is what I've always said like traditional private equity is not, not going to just be like oh well we'll figure out AI in like 2030. It's not really on a roadmap right now. They're working as hard as they can to implement it. Question is like will will traditional private equity be able to basically roll out and unlock the value of AI better than some of these AI native more venture oriented rollups.

Tyler (15:09)

What is the pitch for a Mini or a nano model?

Alex (15:11)

Someone ran some evals and the Mini models are equivalent to GPT5 when that first came out. But it's just way cheaper right? So if you're like cost sensitive, if you're running a ton, a ton of queries, but they don't need to be like the max intelligence then you just

Tyler (15:23)

use the so cheaper but also faster.

Alex (15:26)

Yes, probably, yes.

Tyler (15:27)

And potentially runs on older hardware.

Alex (15:30)

I think that's unclear.

Tyler (15:31)

This is bullish for our vintage Neo cloud, the oldest GPUs.

Ben (15:35)

Yeah, this was crazy idea yesterday.

Tyler (15:36)

Yeah. We're going to run this on.

Alex (15:40)

Yeah. I mean it's like, doesn't like how small the model is. Doesn't actually like matter on.

Tyler (15:44)

Imagine.

Ben (15:44)

Imagine running your vintage Neo cloud with. With that wood fired hearth.

Tyler (15:50)

Yeah.

Ben (15:50)

Powering it all.

Tyler (15:51)

Yeah. I mean you have to imagine that. What's after Blackwell? What's the one that announced today? Fair.

Alex (15:57)

Rubin.

Tyler (15:57)

Rubin. Rubin. Like you have to imagine that there will be models that only run on Ruben and need to be sort of re architected to run on Hopper, I would imagine.

Alex (16:06)

Sure. I mean I think there's like small performance boosts that you can get.

Tyler (16:09)

Or it might just be slower but.

Alex (16:11)

But you can always. You can run any model on like any hardware. It's just like it could be like way, way slower.

Tyler (16:16)

Because you have way, way slower.

Alex (16:17)

The memory is not enough.

Tyler (16:18)

Fleet of A1 hundreds where you could just be beyond like a smaller rack of reubens. Interesting. What did Kalshee launch?

Ben (16:26)

Kalshee launched the $1 billion Perfect Bracket Challenge. $1 billion for a perfect March Madness bracket.

Tyler (16:33)

So you can win $1 billion for entering this competition.

Ben (16:37)

I haven't read the fine print, but it is positioned that way. Vinnie says it would be hilarious if Citadel built out a team to attempt to financially impair their competitors. So Sig Parametrics from Susquehanna Ye is basically like the financial backer for this promotion. So if Citadel can figure this out, they could leave their competitor with a $1 billion bill.

Tyler (17:02)

Yes.

Ben (17:02)

Obviously trying to nail the perfect bracket is functionally impossible, but so there are

Tyler (17:10)

nine quintillion possible brackets. So the odds of a perfect bracket are 1 in 9 quintillion. And I believe that they are capping.

Ben (17:20)

I like my odds.

Tyler (17:20)

I like my odds and I believe that they are capping out entries at 10 million entries. So if you math that out and then you take some insurance out, you should be able to hedge out any of the risk. If you are good and you don't suffer from any skill issues, you can basically with strong basketball knowledge, if you have ball knowledge, apparently you can get the odds down to like 1 in 10 billion. And at that, you know, not from 9 quintillion to 10 billion.

Alex (17:54)

If you have 9 quintillion, you can sort them by how likely they are. Take the top 10 million. That's, you know, maybe there's some kind of power law thing here where we actually. Yes, you're getting your odds.

Tyler (18:03)

But I think, I think if there's 10 million. If there's 10 million, assume that there's 10 billion reasonable brackets and out of the 9 quintillion. So you're, you're discarding like all the craziest upsets to get to that 10 billion. You already ranked it and narrowed it down by like what, six orders of magnitude or something. And then you're submitting the top 10 million of those 10 billion. Like your odds of winning are still one in a thousand.

Alex (18:30)

You can make it a thousand accounts.

Tyler (18:31)

And that's. No, no, no, no. I think that they are capping the Entire campaign to 10, the first 10 million entries. So you have to be on Kalshi

Ben (18:39)

and you have myopen Claw already submitted. The SEC prepares proposal to eliminate quarterly reporting. If you liked earning.

Tyler (18:47)

I was thinking like this bad for us. We like earnings days, but it's not like our whole shtick. So I think we'll be okay. We will continue soldiering on.

Ben (18:55)

Good. Alexander says finally, less transparency around financial results. Yeah, I don't, I don't know. I don't know if this is going to be enough to, to make it easier to be a public company. It's certainly a burden, but the kind of shareholder lawsuit risk and all that other stuff feels like a much bigger burden. What this is just going to do is create more volatility. Right. If you're only getting updates twice a year, you can just see these massive swings because it's like, hey, we haven't heard from this management team in a formal capacity for six months. The business could have changed wildly, growth rates fluctuating, et cetera. And so again, if you love volatility, you're probably going to love this.

Tyler (19:43)

So it's good for the vix. That's bullish for VIX investors out there. There is a world where, I mean the typical like public versus private debate is that when you're private, you can think in multiple years, depending on who your investors are, maybe think in decades even. Whereas when you're in the public markets, you need to think in quarters. And so advancing that from quarterly to six months and you start putting management teams in. Okay, what can we deliver that will show up in six months as opposed to what can we deliver that shows up in three months? That's twice as long. It feels like you could wind up with better run companies doing more ambitious things. I don't know. There is a bull case. Yeah.

Ben (20:24)

I mean the other side of it is you just get more complacency. There's less of that. There's less of that. You're not like on the daily, the daily March, you know, you finish earnings and you're like, okay, 90 days. We got to do this again. Like, there's no days off, kind of.

Tyler (20:39)

So are you. Are you an advocate for monthly reporting?

Ben (20:41)

Daily, Daily earnings calls, potentially hourly.

Tyler (20:44)

Just. I mean, this is the. This is the crypto folks. They're like, put on the blockchain. I want to be able to see in real time the revenues of this asset stream, how things are moving around. I want full transparency at all times as an investor. I don't know.

Ben (20:56)

Nvidia and video. Nvidia DLSS5 and AI powered breakthrough and Visual Fidelity for games coming this fall.

Tyler (21:04)

Video games are going to get more realistic. Prepare over the next couple decades. This is going to be. This is. It's entirely possible this happens. Continue.

Ben (21:14)

Let's pull up the video. It's funny because when I see the

Tyler (21:16)

video, I want to see it big.

Ben (21:17)

When I see the video. My thought was, weren't video games already this realistic? But I haven't played video games besides Tetris on the matic.

Tyler (21:28)

Oh yeah, long time. So let's play GeForce RTX DLSS 5. DLSS of course stands for Deep Learning, super shading. Something like that. Dlss, it uses deep learning. It's used AI for a long time. The whole pitch for DLSS super sampling has always been go from a 720p render to 4k up res. Just interpolate the pixels. This is different. You can see that it's not just becoming higher resolution, it is becoming gen AI. Like there is a world where you render that at higher res. The lighting is changing, the shading is changing, the makeup, the structure of that person's face is changing, but it's still driven by the underlying. Why are you posting the bubbles? Because I'm ranting.

Ben (22:13)

I want to see.

Tyler (22:15)

You're not.

Ben (22:15)

LS S5 do this.

Tyler (22:18)

Oh yeah. But. But this is what we were talking about yesterday. We were like, what will it take to get TVPN simulator photo real? I think we should try and pipe it through DLSS5. Although who knows what this is going to run on. Because Nvidia is not shipping new graphics cards to gamers or something like that. They're delaying the next. The next gaming graphics card. People are upset. There's a community note that has yet to be accepted, but the community notes are not happy. Like, one of the community notes is just a slop and it's like, yeah, like that's in the name. It's Deep Learning. Like, what do you think the DL stands for? And also why are we on DLSS 5? Oh, because this is like a decade old technology. I don't know. People are very upset. One of the community has AI technology has fastest effects on the environment. The majority of gamers did not ask for this.

Ben (23:07)

Are those the most photorealistic video games that we have today? And then they're showing how they're even getting more realistic.

Tyler (23:13)

No, no, no.

Ben (23:14)

Yeah, because they don't look, they don't look. They look like games that are kind of like animated characters that aren't trying to be photoreal.

Tyler (23:21)

So there's a range of games there that some of them have pretty outdated engines, pretty outdated rendering pipelines. Some of them are on the latest and greatest and look very high fidelity. There's also a whole bunch of trade offs in game development around the scale of what you're building and how many poker chips you want to put into great graphics. If you're making some moody first person shooter that's going to be dark and there's going to be lots of blood splattering and aliens and stuff, you could potentially make it ultra photo real. But if you're trying to build something like Minecraft, it's this massive world that's interacted with a ton of different people by narrowing down the scope. The beauty of Minecraft was that the whole thing's voxel based, which is these little blocks and so, so the computer can store an entire world very efficiently because all it needs to say is just there's a cube there and it's green. There's a cube there and it's black. There's a cube there and it's gray. What do you think?

Alex (24:26)

I was going to say Minecraft is a good example of what this can improve. Right. Go to the next post.

Tyler (24:30)

Oh, yes, yes.

Alex (24:31)

This is what Minecraft could look like.

Tyler (24:33)

This is what Minecraft could look like. There are drawbacks, obviously, because you're driving the style transfer from the particular images from the shape. You're not reconstructing the entire image. You're just applying this re rendering on top of the underlying structure. And so you can get really weird outcomes like this.

Ben (24:57)

Take us to space, Jensen.

Tyler (24:58)

Let's listen to Jensen talking about data

Ben (25:01)

centers in space, courtesy of Nick.

Jensen (25:03)

I'll spend very little time on this at this time. However, we're going to space. We've already been out in space. Thor is radiation approved and we're in satellites. You do imaging from the, from satellites. In the future, we'll also build data centers in the, in the, in, in Space, obviously very complicated to do. So we have, we're working with our partners on a new computer called Vera Rubin Space One. And it's going to go out to space and start data centers out. Out in space. Now, of course, in space there's no conduction, there's no convection, there's just radiation. And so we have to figure out how to cool these systems out in space. But we've got lots of great. I'll spend very little time on it.

Tyler (25:45)

Lots of great engineers working on it. It was very funny listening to Dylan Patel talk about space data centers and saying that, like, yeah, even if you solve everything, like, it's still hard to make chips. It's just like it still comes back down to the chip bottleneck above all else. Yeah.

Alex (25:59)

I mean, this is why you see Elon doing the terafab thing, right?

Tyler (26:02)

Yeah, yeah. I really want to know what his plan is for that, because has he put in an order for a tool or is he going to do Terra ASML? Like, because there's like the supply chain is what, 10,000 companies.

Alex (26:16)

I mean, historically they've done, they've gone super, super early in the supply chain.

Tyler (26:19)

Right?

Alex (26:20)

They've done like mining stuff.

Tyler (26:21)

Yeah, yeah, yeah. Speaking of Dylan Patel Semianalysis was featured at Nvidia gtc. The Inference King has been crowned. Nvidia won a massive belt and it looks like Jensen's holding it up. He is in fact standing in front of a LED wall or projector. But a beautiful thing to see. The Semianalysis logo.

Ben (26:42)

It's all WWE. The entire world is WWE.

Tyler (26:48)

Nvidia extreme co design revolutionized token cost. The GB NVL72 is the inference king with 50x higher performance per watt on inference x by semianalysis. 35x lower cost. Very, very exciting. And congrats to Jensen for becoming the Inference King and winning the Inference Max Award, or Inference X as it's now known. Jensen is also confirming what we see in our GPU availability data. There is now an epic scramble for compute B200. Basically unavailable availability for GH Grace Hopper 200 H200 and A100 also collapsing. Low availability means high demand. And people, people were kind of going back, joking about like he said, like 1 trillion of demand or something over some period of time. And people were like, oh, so he's guiding down. It's like, I guess that's where we're at.

Ben (27:45)

Yeah, it's hard when you're doing, when you're doing cumulative revenue.

Tyler (27:49)

Let's move over to a much smaller deal for Netflix and Warner Brothers and the final deal which went to Paramount, of course. And David Zaslav is in the Wall Street Journal. David Zaslav deal could deal Pay could top $800 million after last minute tax benefit so Warner Brothers chief executive David Zaslav could collect more than $800 million in severance and other payments after rival Paramount acquires the company. The sum of cash includes some includes cash and payments for options and restricted stock holdings, as well as a newly adopted tax reimbursement for Zaslav in a securities disclosure filed late Monday. The total doesn't include the more than 20 million he's likely to get for shares he owns outright. So he's been, he's been investing as well. About 504 million is due to Zaslav if the deal closes, the company said while 47 million would be triggered if he is fired or leaves under certain circumstances. Within a year of the close 116 million in equity has already vested. Some 335 million would only kick in if other payments trigger a 20% federal excise tax on golden parachute severance payments he receives. The ultimate value of the payout is based on tax code rules that are expected to cause it to to significantly decline with the passage of time, the company said in a filing. Without the tax payment, the total would be about 667 million. Companies typically try to keep severance at or below three times salary and target annual bonus to avoid or minimize the tax. And investors often criticize companies for reimbursing or grossing up executives for the tax. The company said Zaslav wouldn't have to pay the excise tax if the deal closes in 2027, which would save the company costs of the tax gross up. Yeah.

Ben (29:31)

A lot of people are did he earn that? Yeah. And the reason that I think it is warranted from a business standpoint is when we were sitting here last year talking with someone who won't be named in the, in the, in the media space who has done, he was sitting here telling us at this very table that he didn't think there would be any bidding process at all.

Tyler (29:56)

Yeah.

Ben (29:56)

And it was just going to land with the Ellison for a pretty predictable price. And Zaslav did his job as CEO to get the best possible price for shareholders.

Tyler (30:08)

And it's remarkable.

Ben (30:09)

And that is why, you know, he was able to have outsized impact. He's getting, he's getting outsized compensation. He increased the enterprise value through his deal making by tens of billions of dollars and he's getting a significant, but I think warranted payment. And if you, if you don't like this, then you probably don't like the game of business very much either.

Tyler (30:33)

Well, thank you for tuning in to TVPN today. We will see you tomorrow.

Ben (30:37)

Go have the best day.

Tyler (30:40)

Give us five stars on Apple, podcasts and Spotify.

Ben (30:42)

It's been an honor.

Tyler (30:42)

Why don't you throw that flashbang? Throwing flashbang. We'll see you tomorrow.

Ben (30:46)

See you tomorrow.

Tyler (30:47)

Goodbye.