Mark Cuban on the AI Bubble: Who Actually Gets Wiped Out?

You and I live through a couple of bubbles. We've seen this movie before and this wave seems very different than.com wave. So let's talk about that. Are you concerned about a bubble? We're seeing bubbly like behavior, people.

0:00

It's not, it's not the traditional dot com bubble, right. Because back then there was companies going public, getting crazy valuations and people are buying them and the stock would go up, you know, 50%, 100% with companies that had no revenue, no traffic, no nothing. And, and you'd go get a cab back then and people would be talking about them and you don't see that at all today. So it's not a bubble that's going to impact most people in the room, right, or most people across the U.S. but it could just destroy a lot of VCs and a lot of funds and a lot of PE. Right, because they're going all in. I'm going all in.

0:13

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0:50

It used to be that product managers for brokerages had to outperform the numbers right for you know, the SPX or whatever. But now you got to outperform to keep the money coming in. You got to outperform the fund next door and they're all in anthropic and getting their outcomes in SpaceX and celebrating. But if shit hits the fan.

1:25

Yeah, it really is like I've only done venture for just over 10 years and it is wild to watch so many people who deployed at the wrong time just out of business. They just invested at the peak and entry price matters. And you and I have been in a bunch of deals together and we used to get to investing companies at 5 million, 10 million as angel investors and then all of a sudden the request was 40, 50, 60 and the product's not launched and you're like, how does this work?

1:45

Yeah. And you know, and what's happening now is the market leaders, Google, etc. Meta, they're borrowing hundreds of million billions of dollars.

2:13

Yeah, that's interesting.

2:21

And there's already a private credit problem right now. Right. So you just layer on private credit, like our capital getting all the refunds and then you, you know, you have these huge companies that have cash flow, but there's, you know, they're spending all their cap cap cash flow on CapEx and then they're borrowing on top of that.

2:23

That's a year bonds.

2:42

Right. That's planning for perfection.

2:44

Right.

2:45

And that's going to be hard. And we're building these data centers and you know, if there's a price performance curve on AI that minimizes the power requirements, there's going to be a lot of data centers that are going to be turned into pickleball courts.

2:46

Interesting. Because they just can't get the power turned on.

2:59

No, than just the power. Just everybody thinks that, okay, there's going to be so much more utilization and there will be. Right. It'll just scale like everybody expects. But there's going to be breakthroughs and technological breakthroughs as well. Just like we saw fiber back in the day, it was all about putting in fiber. Then it went from 1 gigabyte fiber to 10 to 100 gigabyte. And then there wasn't a fiber problem anymore.

3:01

There wasn't a bandwidth problem and quite the opposite. We had dark fiber that people bought, used.

3:22

Yeah.

3:26

For pennies on the dollar and just sitting there.

3:27

Right. And how is it not going to be the case that we don't get the same price performance improvements on the AI side and on the data center side.

3:29

Yeah.

3:37

And then with all the hate going against the data centers, I think that could be, you know, protecting them. And I mean, spending. Committing tens of billions of dollars for 10, 20 years going out.

3:37

Yeah.

3:50

I mean, nobody can predict that.

3:51

Well, I mean you're, you use the word pricing to perfection, I think earlier in the conversation. And that's really what's happening. I mean, you have to have a thesis that we're going to put 100, you know, OpenAI $100 billion to work and that's going to come back not just in revenue, but it has to come back in earnings.

3:54

A margin dollars.

4:14

Yeah, yeah. It has to be profitable.

4:15

Yes. And you just don't know. You know, and I'll tell you the other in terms the corollary for bubbles, Right. In this particular bubble, because it's so driven by private capital, there should be a lot more companies going public. Not at the SpaceX level for not OpenAI, not anthropic, but the $100 million IPO.

4:16

Yeah.

4:37

Because if AI does what AI knows, we all, we all know what it'll do in terms of disruption. Then you want to have some sort of currency that allows you to buy all those companies like you guys were talking about buying different legal companies.

4:37

Yeah.

4:55

Right. Well, if you don't have that currency. The stock is currency. Yeah. You're going to have to go out and raise money to do it. And if anything happens and that money is not cheap, that money is really, really expensive versus if you go out and you do $100 million IPO or a $50 million IPO and you can do a secondary or whatever, as many times as you need if you're performing. But the minute that company that you're competing with, that is a legacy business, can't keep up, or there's some other company that has domain expertise that you need or data that you need, like you guys were talking about.

4:55

Yeah.

5:27

You want to be in a position to buy them.

5:27

Yes. That is incredible forward thinking.

5:29

Yeah. No one is forward thinking like that at all. And I'm like, trying to tell my portfolio, companies, go public, Mother. Go public.

5:31

Yes.

5:39

They just don't think that's the right thing to do.

5:40

Well, and M and A is, you know, not to make this political, but, you know, when you're an entrepreneur, you have to play the game on the field. M and A was off the table. Lina Khan had a certain perspective, which was, we have to be like free cogs in Minority Report. We have to predict who's going to be a monopoly in the future and stop them.

5:41

Now it's like, okay, consideration with. To compete with China and everything else that's going on globally. Yeah. Right.

6:01

Four years of no acquisitions. I mean, the people I talked to were in corporate development were like, we've been told to stand down.

6:07

Yeah.

6:13

Because it's not. But we are where we are.

6:14

But even so, right. It's, you know, with mergers and acquisitions that. That scale, fine. But if AI does what we know it will do that the companies that are disruptive don't have to be enormous companies.

6:17

No.

6:28

But you don't want to have to always raise cash to go out there.

6:28

Such a good insight like these, Right.

6:32

Because like back in the day, back with Broadcast.com, we bought like five companies just stock.

6:33

And then there was always a bigger

6:39

fish to come along, which we were happy to, you know, Yahoo.

6:40

Yeah, yeah. The famous caller. If you were a Claude employee, if you're at anthropic, you're at OpenAI. Is it time to start thinking about the collar? Try to Think about. Yeah. Pairing the position.

6:43

Collared my stock because how rich do I need to be?

6:56

Right.

6:58

You know, and if you, if you're able to change your life, if I work for any SpaceX, any of them, whatever, I'd be like, you know, somebody put together a collar for me.

6:59

Yeah.

7:10

You know, because I just need to be protected. Save part for my upside, but just cover my downside.

7:10

Yeah. When you did it, you had to like actually orchestrate that. Right. It didn't exist as a product.

7:15

No, it didn't. So I had to actually create an index of Internet stocks. I had Goldman Sachs create an index of Internet stocks that I thought sucked. And then I shorted that index because we. And we had to follow all the loss and I just had to have that short in place until I was able to do a real collar in the market on my Yahoo stock.

7:22

Yeah.

7:40

And I lost tens of millions of dollars on that short.

7:41

Yeah.

7:44

But I made up for it.

7:44

Yeah. I mean, one of the great trades of all time. What do you think this wave of capabilities in AI? I'm sure you play with it because you've always been a tinkerer. So maybe what are you tinkering with and what do you think is going to be the most world changing in the next five, 10 years for entrepreneurs, for society? Where do you look at it and go, hey, let's truly meaningful world backwards?

7:46

So AI is a lot harder to implement than anybody expected.

8:16

For sure.

8:19

Right. You know, you can do an agent pretty straightforward. Right. You can prompt away. You know, we cheated on tests, we, you know, cheated at work, you know, did projects, improved our productivity 100x. Right. All easy peasy. And we just assumed, you know, at the enterprise it'd be just as easy. It's hard.

8:20

Yeah.

8:37

And it's terrifying and not terrifying for employees because Dario. And everybody's saying 50% of white collar people are going to lose their jobs. And here we are two years later, they said within two years and, you know, employment still growing, people are hiring. We need more AI literate people. Right. So CEOs have no clue what is going on. None whatsoever. And that's not going to change. Right. And so, you know, trying to explain to them that you need to add a harness to, you know, all the. Yeah, no chance. Right. And if you think about it from an AI perspective, if AI, we're talking about AGI and we're talking about taking over the world. If you need to have forward deployed engineers, that tells you all you need to know about AI. Because by Definition, you should just be able to ask AI to do what I need you to do and ask and tell me how to implement it. Right. Yet here you have Microsoft hiring 6,000 people. You have anthropic OpenAI all saying they're going to deploy to these companies, which tells you AI is hard. And then you have Alex Karp from Palantir freaking out saying, how can you give your alpha to these companies when in my opinion, he's just saying they're doing what we're doing. Right. We're all about for deployment engineers at Palantir and they're doing the same thing.

8:37

Again, it's a great insight because if you're using it as a search engine or you're making your little agent to, you know, go do your cron job. Okay, fair enough. It's, it's going to work. You need to be have a little bit of systems thinking. But when you start putting into the enterprise and you know, this is mission

10:01

credible work about the little bit of systems thinking, because that's the second part. And I'm not trying to on AI. I love it, I invest in it. It's going to be amazing. It's the most impactful technology that we've ever seen and may ever see. Right. But try going into Cloud or ChatGPT and saying, okay, I just want you to do this search for Jason Calacanis and investments and I want you to report and I want you to email it to me every week. Yeah, you can't do it, can't do it. And then it says, okay, would you like for me to do an agent that gives you alerts? And then you say, sure. And then you have to know how to program because it either gives you a JSON file or it gives you, you know, code and it comes out slop. And yeah, then you have not. Correct. Right. You have to reiterate, you know, if you want to say, you know, hey, let me load a picture in and you tell me if I'm hot or not, or is this girl hot? What should I say to her, you know, or business versions. Great. Yeah, Right. But I is not going to, you know, take away 50% of the jobs. There's just so much it can't do that regular people need it to do.

10:17

Yeah.

11:17

Right. Now does that create opportunity? Enormous opportunity, yes. Right. So like I'm an investor in Lovable and we were here this morning talking and so I was saying that Anton was saying that people are using lovable to create 770,000 applications a week, a week and that only 30% of their business is in the US and only 20% is engineers. And what's happening is entrepreneurs. To answer your question about where it's going. Right. If you're an entrepreneur, like he was saying before, there's no better time to be an entrepreneur. He nailed it. Right. Because that's where AI is the most impactful. No matter where you are in the world. They have big utilization in Brazil, India. Right. If you're in France, us, Wherever. I gave it a prompt, like I said, because I wanted to see what it would take. I was like, okay, we're going to create an imaginary company that has a button that can record 24 hour video and then I want it to be able to send it to me every 24 hours.

11:18

And.

12:26

And I want you to create a patent and a business plan and tell me what licensing or whatever. I need 12 minutes.

12:26

Yeah.

12:33

Why did. Just know we've started tons of businesses.

12:34

Yeah. Six months to get a prototype, 12 months to launch it.

12:37

Yes.

12:41

And then you have to.

12:42

Then I asked for a bill of materials and the source companies like the basic stuff to be that, the blocking and tackling stuff that every company has to do at, you know, when you're setting it up and early in its life cycle.

12:43

Done.

12:58

Done. And even if it's wrong, so what? Because the one thing you and I both know and everybody in the room should know, every single mother business plan ever written in the history of business plans.

12:59

Yeah.

13:10

Is wrong.

13:10

Of course.

13:11

Yeah. It's, it's a thought exercise that at least gives you some sort of direction. You're going.

13:11

Yeah. Some guideline and a template for you. Right. But it's wrong.

13:16

Yeah. I'm going to iterate.

13:20

So what if the AI is wrong? If the model is wrong, you know, because you're going to learn and you're going to iterate. But it's still. Again, all this talk about taking white collar jobs is ridiculous when it can't even do the basic. Right. And you have to have, like you said, a programming mindset in order to be able to iterate and figure it out. And like even you would think, if AI is as advanced as we want to believe AI is right now, all the errors that we get when we ask it to do a project, it would learn from all those errors and even have. Hey, I'm Claude. I see you have a problem with this. Right. And it failed on these three attempts. Let me just tell you what 97.6% of the other people who ran into this did. Right. And then it would fix it for you, would tell you it doesn't even do that. It just says failed. Right. Or it says whatever. Again. AI is amazing. And particularly for programmers, it's game changing.

13:21

When you have a narrow data set like code or legal, it's just tax, it's magic.

14:19

And it's just math. Right. Basic data. Right. But when you want it to do, when normal people anywhere in the world want to use it for normal stuff, great. You start a business, great. But if you want to start getting advanced, it's like figuring out PowerPoint used to be what. Or Excel. Right. You always have to have your Excel expert, you know, your power in your company.

14:25

Yeah.

14:49

Or whoever that you knew. Right. Or there would be companies built. I've invested in like a company that slideshare that all they did was have PowerPoint templates that you could download and redo. AI is not even that advanced for, you know, once you get to the second level. And so that creates so much opportunity for anybody to walk into a small, medium sized, even large business and say, hey, I understand AI. I have a basic computer background or better. And so all these fails that you're running into across your, your, your company, big or small, I can help you fix them. Because what AI can do once those issues are fixed is phenomenal.

14:50

Yeah.

15:33

But even better, if you're thinking as an entrepreneur to start a business, those things will eventually break. Agents get bored. Right. And they drift. Because as the underlying large language model starts to change, the way it was originally programmed doesn't match what the large language model turned into. Right. You see what I'm saying? And you even wrote something about this, right. Where it's taking more people to manage all this stuff. I'm going all in.

15:33

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16:05

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16:11

Today I'm trying to get the whole firm to be AI first. And even with young people, it's like one group embraces it and, you know, they, they solve. You know, I don't know, let's call it five or six really pressing issues. The other group is, you know, not embracing it. And the difference between those AI first employees and the non AI first employees. The gap is like, whoa. It's almost like when we got into the industry and somebody knew how to use the office suite in a PC.

16:35

Right, right.

17:06

And then somebody else was like on legal pads. It's like that much of a difference. It's so stark.

17:07

People who are AI literate, when do they run into a ceiling?

17:12

Well, you know, it's. What I'm seeing is a lot of tool hopping, which. It's a good question because they started with openclaw, they started building it, it got brittle.

17:16

Wait, does anybody still use openclaw?

17:25

Who's openclaw? Anybody using Hermes Agent. Okay, there you go. Who's on Claude Cowork? And then. Oh, whoa. And Perplexity Computer. Anyone? Okay, interesting. Those are the four that people have been bouncing around on. And what I decided to do is I was just like, hey, Token Max, you can each spend a couple thousand dollars a month. I don't care about that. I just care about the gains. And they all wound up going from open claw. All the agents started breaking. It's hallucinating. It's like too frustrating. They started using Claude Cowork. Okay, great, but kind of limited. And then they started using Lovable. And they built intranets for the venture business that no venture business would spend a half million dollars and 12 months building an intranet. Like, you'd just be like, I'm going to put it in notion Google sheets, whatever. And then they just started building more and more software. So I have two or three people who are building software that I would say five years ago, we would have spent maybe two or three million dollars a year building this with that outsourced company.

17:27

You just would not have done it.

18:30

Which means we wouldn't have done it.

18:31

Right. You were just about the SaaS application that did it.

18:32

And then we would have tried to like shoehorn it into a SaaS app and customize it. It wouldn't have worked and we would have given up.

18:34

But how are you going to manage it now once they get there?

18:39

Well, you know, again, to your company, Lovable. Which man, Congrats on that investment. Because that company was going to go out of business four times. And I told Anton, every time they say you're going out of business, you add 100 million in revenue, 600 million in revenue, and four times 200 million, 300 million. Oh, yeah. It's going to be absorbed into the frontier models of the world.

18:42

Right? Yeah. I mean, I've got Lovable, I've got Synthesia IO.

19:00

Oh yeah.

19:04

That was the first investor in Nice 10 years ago. Maybe that, that are just killing it. Right. I've got ami, which is Yann Lecun's world model.

19:05

Yeah.

19:13

We haven't even talked about world models versus LLM and Transformers. Right. Because everything we do is built on text and pictures.

19:14

Yeah.

19:21

Nothing's going to be texting pictures in 10 years. Right. And but what's going to drive it? And like people say, well I so smart it's going to change everything. I'm like, okay, if you tell AI, if you show a video of a two year old on a highchair with a sippy cup, the the two year old knows if you push the sippy cup over the edge.

19:22

Yeah.

19:43

Mom's going to come running and the kid's going to start laughing.

19:43

Yeah.

19:46

AI's got no clue what's going to happen.

19:47

Yeah.

19:49

None. Right. Would you rather if you're at a corner blindfolded and you have to cross the street, would you rather have a video? Would you rather have your phone with AI or would you rather have a seeing eye dog?

19:50

Yeah, dog.

20:01

I'm taking the dog every time.

20:03

Of course.

20:04

Yeah.

20:04

It's not ready, right?

20:05

Yeah, it's not ready. So just think about how far we have to go, you know, and all

20:05

this huge opportunity though. I mean the world models are crazy because you have videos available on YouTube and just we have the world there. So not enough. It's not enough. They have to wear gloves and you're. Now they've got people in Manila like doing recipes.

20:11

So I invested in the company matter.com and they're launching satellites just to take. And they do spectrography where they take. Use the satellites to take videos of everything underneath them and use a spectrum. I don't even understand all the shit. In order to be able to convert it into a world model that will provide algorithms that other world models can use. There's just no way that the future of AI doesn't include video.

20:27

I mean it's a huge part of it. And as the inference and back to the build out of these data centers as we wonder what's going to happen, people wanting to use more tokens and then these world building and video, man, that takes a magnitude Video.

20:56

Like if I'm going to be wrong on the data centers, it's going to be because of video. Yeah, right.

21:14

And world models and robotics, which is all related.

21:18

Yeah. And robotics. You know, it's related but we still got a long way to go.

21:20

Yeah. Health you look great, by the way. I don't know what's going on. You got the Reddit. What do you got? Red. A true tie. What's on the menu here? What's off the menu?

21:26

Follow me on Instagram. M. Cuban. I just, I'm eating. Better not.

21:35

I mean, you look better now than 20 years ago.

21:38

Oh, I appreciate that. Thank you. I mean, helps too, right?

21:40

The tam. But I mean you look thin and fit and listen, we're getting up there now. We're not kids anymore. This is definitely going to help AI.

21:42

All the work being done and I use it too. Like I invested in a company called Open Evidence.

21:52

Yes.

21:56

Yeah. Which is for medical. Right. And I used it and like I have two, I have one supplement I have to take because my iron levels are low and I have to take this one medication and I was taking them at the same time and couldn't understand why I was having problems. I run it through Open Evidence and I said, here's everything I'm taking, here's everything I'm eating. And they're like, no, you got to do this. You know when you get up to pee at 3 in the morning, take this medication, man. When you get it.

21:57

Yeah, no, it sucks.

22:20

Yeah. Right.

22:21

I was, I was right there with you last night. What's going on?

22:22

What's going on?

22:25

Right.

22:26

And so you know, but it's for health. It's going to make a huge difference. But it's not going to replace doctors.

22:27

No, but I mean it is pretty amazing. Are you on WHOOP or your Apple watch?

22:35

I watch, yeah.

22:40

Yeah. I mean the Apple, the Whoop plus getting your blood test. Just self directed health care with AI man, you're going to get some early wins. And then when you do go talk to your doctor.

22:40

Oh, you have it right there. Right there. You know. Now six months are still three to six months. Yeah, right. And I've been doing it for 10 years, so I know all my trends. Wow.

22:51

And so you were doing it before function and superpower.

23:00

Like you could go look up Mark Cuban blood test on Twitter. Right. And I would get into it with doctors like 8, 10 years ago saying you're going to need this for your benchmarks and. But it's only going to get better.

23:03

Yeah, it's going to be really interesting. We had this big data moment and it was like, okay, yeah, we're storing all this data but we didn't have any intelligence against it. Now that's incredible. When Apple is now putting that data, they're doing studies I don't know if you've been invited to studies on your Apple watch. I'm like, well, this is going to get very interesting. Just added blood panels.

23:15

Yeah.

23:36

So now your sleep data, your steps, your heart rate, your respiratory ekg, plus your blood work.

23:36

That's pretty.

23:43

Then if you can get your diet into it as well.

23:44

Yeah, that's what I watch has in eye health. Right.

23:46

Yeah.

23:48

So, yeah, you're just gonna get smarter, you know, and that'll make your doctors able to be smarter because 95% of medicine is guessing, you know, because you can't. There's no way a doctor can memorize all the new that happens every single day. You just can't. But a doctor using these tools, having, you know, the empathy and the ability to communicate and the ability to see. Yeah, right. Because again, there's. You can't see.

23:49

Yeah.

24:14

You know, you could have. Doctor, you know, why am I bleeding? You got a blood. Looks like you got a gunshot wound. Right. It's not going to tell you that the way.

24:14

Yeah. When we look at the opportunity here, it's going to be a lot of change. A lot of talk about wealth disparity in the U.S. invest America. Our friend Brad Gerstner and our friend Michael Dell, another great Texan. And thanks for welcoming me. I'm enjoying my time in Texas. Yeah, I mean, it's great. I love Texas, man.

24:24

It's kind of like the heat. Kind of like this, though. Yeah, we have air conditioning.

24:48

We do have air conditioning. There's a record number of air conditioners coming from China to Europe this summer.

24:52

You know, I looked at what companies installed them and everything.

24:58

Oh, you always got to trade. You always got a trade.

25:01

Curious, but there's no real sold out.

25:04

They're all being shipped here from China at the moment. But really, interestingly, you know, feels like entrepreneurship, which has been our shared passion for many decades. Hey, investing another shared one. Giving people access to public markets. Invest America. We have this dueling narrative socialism in America, capitalism. And it feels like this is the. In our lifetimes, you and I are close in age. This is the most fevered we've ever seen it. I mean, we have states maybe not since the 60s or 70s. I missed that. I was born 1970. You were born, I guess 1943. 23. 23. I always joke, he's a brother. You look good for 1923. But, you know, it's. This is pretty polarized. And what's your take on the. The social.

25:06

There's two things here.

25:58

Yeah.

25:59

One all the DSA stuff is local.

25:59

Right.

26:02

It's really easy to be Mandami. And in New York, when you have a budget, you get to control it and it's local. Right. You got elected, you just do. And you have to balance the budget and you'll see it in Michigan and wherever else. I don't think it's going to be game changing. But the more important thing is the people who are doing this are the people who are best at social media.

26:02

Right.

26:22

You know, because the algorithms drive how people vote in the United States. I can't speak for the rest of the world. More than anything else, whoever controls the algorithm controls, you know, the election in many cases. Trump knows how to use it. And what, what do Mandami. You know what, what is unique about Mandami relative to Trump? He's what, 31, 32 years old?

26:23

Yep.

26:43

His whole adult life has been Trump and social media. He studied it and the two together.

26:43

Yeah.

26:49

And the kid, the guy in Michigan, same thing. So if, if you're good at AI, I mean, algorithm, you know, driving algorithms, whether it's flooding the zone or, you know, like Trump saying they're eating cats and dogs.

26:50

Yeah. It's just attention.

27:03

Yeah. And it's just, you know, defining the algorithms because whatever you search for, you get more of. And if they can get you to search for what they're saying and show your interest, then you're going to just get Mandami 247 and you'll get the positive size of Mandami. Or if you happen to be on the other side of the aisle and you are, you know, looking at stuff that's counter to that, you'll get more of that we don't like. But one other piece I think is starting to change that, and that's the large language models. The thing that I think will save us as a world more than anything else in terms of information availability and reducing the information asymmetry as it applies to politics, are large language models. Because large language models have to be as literate or in literal and honest as they possibly can.

27:04

Truth seeking.

27:58

Yeah, truth seeking. Better way to put it. Yeah. So they, they have to seek truth, otherwise you'll lose trust in them. And the last thing, you know, Cloud OpenAI needs is, well, you know, they're lying their off about this for.

27:59

Yeah. Their currency is getting you the correct answer and the correct knowledge. Social media's currency is keeping you engaged.

28:11

Right.

28:17

It's two different missions.

28:18

Totally different missions. Right. And so you're not going to get rid of social media. But I think people, as they become more uncertain with their politics, are going to go more and more and more to large language models and say, who should I vote for? And the large language models will come back and say, well, what do you think about this? What are your interest in this? And that it up? And they'll give you honest answers.

28:19

Yeah. And if you ask it, hey, what's a reasonable immigration policy? It'll give you a reasonable immigration policy which is like, yeah, maybe. And do a point based system like Canada, New Zealand, whatever it may be.

28:40

Right. Yeah, I've done the same thing. And it's impressive.

28:53

Very impressive.

28:56

You know, my favorite troll now is like JD or you know, AOC will, you know, they'll come out with whatever their craziness is on either side of the aisle. And then I'm like, akrock, please vet these claims, be as objective and factual as possible.

28:56

Check your work and show your stories.

29:10

And then it just replies to them. So I've been just totally trolling Stephen Miller.

29:12

Oh, my God.

29:15

Who? You know, he's like anti immigration. I'm very passionate about like legal immigration and recruiting great people because we need them every. Because you're running a basketball team. Every time you get Dirk Nowitzki, somebody else doesn't have him on the team. You get Jalen Brunson. He's not on the Mavericks anymore. Now he's on the Knicks. You know, like.

29:16

Well, that's why we come to these things in Europe, right?

29:36

Yes.

29:38

Because great talent. Right. Smart people. Obviously you guys are geniuses for being here, you know, but. But at the same time, there's a different vibe in every European country and India and the whole rest of the world. Right. And I think you're starting to see some entrepreneurs leave us.

29:38

Yep.

29:57

To come here. And that's scary. And hopefully, you know, large language models seeking the truth will help educate people away from what the algorithms tell them.

29:58

Yeah. I think it's like important you optimistic now. It's been pretty chaotic, but we're seeing such great progress. You're optimistic about, let's start with America and then we'll go to humanity.

30:09

Yeah, no, I mean, you know, like every country we have our issues. Ours just happened to be kind of insane.

30:25

It is pretty wild.

30:33

Yeah. But the good news is, you know, we have term limits for our presidents.

30:35

Yeah. Yeah. And it seems like 12, three terms is going to be the one for president. I mean, you're gonna run. I mean, I hope you do.

30:41

Man.

30:51

I would love to Be your press secretary. That would be a bet. We'd have so much fun, though. We'd have fun.

30:51

We would have fun. Well, if he decides to run for a third term, then I'll run.

30:56

But he's. Yeah, okay, that's good. That's breaking news. I mean, I honestly, like, if you think about what we need, I think in leadership, executives who can, I think, you know, who are like post money, post. Needing to make a living.

30:59

No, I'm not gonna even go there.

31:16

Well, and then maybe who are doing it for love of country and maybe some amount of civic pride or.

31:18

No, I get what you're saying.

31:24

Right.

31:25

It's just like, you know, in the us what the Democrats don't know how to actually do anything. Right. You know, they know how to take whatever happens and extrapolate that to the end of the world and the end of democracy. Right. Yeah, but. And the Republicans, on the other hand, you know, do crazy shit, right? Like they don't care about the people in the country. They don't, you know, there's no connection to people. There's no empathy. And so, you know, we're. But in the short term. But I think as we get past this next, the midterms and the next

31:25

presidential election, I think we'll get back to normalcy.

31:58

I think we'll get.

32:00

I think people want it. And you know, thing that has been really eye opening for me, having lived in New York, California, now Texas. In Texas, we spent half as much money per, sometimes less. I think it's 2.2 times as much is spent on each citizen in New York. And we spend half as much, six, $7,000 per person. They spend like 14 or something. 12 to 14. And the quality of life's better.

32:01

But on the flip side, New York contributes more to the federal treasury than Texas does. And you would think it should be the opposite, right, Just because of the business and how things are run. So there are trade offs.

32:28

Yeah. But it's, it's changing. Like, what do you think about all of us moving to Austin and like

32:40

Texas, you got smart, obviously, for obvious reason, particularly, you know, like the wealth tax shit is just dumb, dumb crazy.

32:44

They tried it here.

32:51

Everybody left. Yeah.

32:53

And they did it for about two years in France.

32:54

Did they? Yeah, I don't know. But you know, when Elizabeth Warren first proposed the wealth tax, so I found, and she said, well, we have these models and everything. So I found the economist at UC Berkeley and I said, would you share your model with me or at least tell me about it, he goes, I'm like, was it more than one year? And he goes, no, it's just one year. I'm like, did you do any behavioral analysis to see how people would respond to the changes? Yeah. No. And so, you know, whether it's Madame Elizabeth Warren, whether it's California, it's showmanship more than reality.

32:55

Yeah. And I think people are forgetting that people are mobile. You know, like in the US it's pretty extraordinary. You got Travis Sachs, myself, Elon. Just a bunch of folks have all of a sudden just shown up.

33:27

I was there first.

33:42

You were. I remember talking to you about it. And the thing that's amazing to me is, you know, in California they won't let you build anything. And then we go to, I come to Texas, I buy a ranch and I asked the guy like, hey, can I like put a solar farm in here? He's like, on your ranch? I'm like, yeah, here. He's like, oh, son, it's your ranch. You can do that. It's like, can I, can I like build?

33:42

Like, trust me, in the cities themselves by doing that. In the city of Austin, I mean,

34:04

but just outside of it, you build and housing prices have gone three, three years in a row, housing prices and rents have gone down. When you build a company in Austin now, I'm sure it's like that in Dallas and Houston and San Antonio. When I have founders move there, the entire pressure is released. People can own a home. And I was like, wow, is that.

34:08

But why do people still go to Silicon Valley? That like drives me.

34:27

I think if you're a first time founder, nothing better in terms of soaking in it. But when you're a second time founder,

34:32

they're soaking in it. But what they don't tell you, the it is. Right? Yeah.

34:37

It's tough. I think second time founders have now realized if I build it in Texas or Nevada or Florida, I'm going to just. All the talent's going to come in

34:40

the Silicon Valley just sets people's heads so wrong. Yeah, right. So whether it's Travis, Mike, by the way, I've known Michael Dell since we were 22.

34:49

Yeah.

34:56

And I used to do business with him way back when. But just the. In Texas it's just like build your company and go, yes. In the Valley, it's like, so are you Series A? Are you serious? Yeah. Are you serious?

34:57

A lot of distractions.

35:10

Yeah.

35:11

25 years I've been waiting for my Knicks to win a championship. And you played a significant role.

35:12

No, the spurs, forget roll they should have kicked your.

35:20

And why didn't they? Why didn't they?

35:23

I think it was coaching lack of experience.

35:25

Yeah.

35:28

Because you're up. Put aside the 29. Right. You're up in the fourth quarter of every game. Wemby throws it into the back of some guy, misses two free throws. Dear. And Fox goes the wrong way.

35:28

A lot of mistakes.

35:39

Yeah. And you'd be talking about firing Mike Brown.

35:40

I mean, it was a. We were concerned when he got hired and getting rid of Tibs. Oh, my God.

35:42

But JB was the real deal, right? My Indiana boy, og, Right.

35:48

Yeah.

35:52

He, you know, he saved you guys, so.

35:52

Yeah. And you had Jalen Brunson.

35:54

Yep.

35:57

He left, and that was kind of destiny. His family wanted to come.

35:59

That's what he wanted. I mean, I could show you a text where his agent, you know, texted me, says he wants his own team.

36:03

He wants his own team, right?

36:08

Yeah. He was ready to go.

36:09

And I texted or emailed you, and I said, what's the story? This is what we're going to base the franchise on. You said, he's really good. He's the real deal.

36:10

I love. He's a great guy. That's the best part about jb. He's just really a good human.

36:18

I was there for the fifth game, six rows behind the bench.

36:23

That's cool.

36:28

And, man, I just cried. I just cried. It's been so many years. And you got your chip, too, with Dirk.

36:29

Yep.

36:37

It's so amazing how sports plays such a role in so many people's lives. Yeah.

36:38

Especially now. Look at the World Cup. I mean, it's just like sports has just changed everything. And, you know, like, I've been to four World cup games in Dallas, and I hate soccer, football. Right, right. I hate it. But just the whole scene, the vibe, the energy. You can't beat it. It's like going to a Knicks game, going to a Mavs game. Same thing.

36:44

Yeah. And the NBA is. It peaked, it sounds like.

37:02

It's hard to say. I mean, you know, for fans. No, because, I mean, it just grows on social media. You know, I went. I was walking in Paris, and there was a basketball store, you know, and had Wemby jerseys and Gobert jerseys and everything. And so, I mean, it's just growing globally. Yeah.

37:08

Is Wemby the real deal?

37:24

Yeah, he's got. He got humbled, though.

37:26

Yeah.

37:28

Which is good for him. It's like Dirk in 2006 got humbled and came back better. Wemby will come back bigger, stronger, better.

37:28

Yeah. It's amazing how he went from this like incredibly. I don't know, there was a, there was a magic about him to. No, he's a villain and he turned into a villain.

37:34

This was New York and 50 some years, right? And just the circumstances and you know, San Antonio thought they had in the bag. Everybody. It's like I went to Indiana University, right? And if anybody here follows college football in the states, like we were the ultimate underdog. We had not had, you know, we had not won 10 games. We had. We beat more top 10 teams last year than we did in 100 plus years of the program. And so that, that just changes people's attitude.

37:45

You were very much involved in rule changes and we're going to get on AI next. But it's just great to talk to you about this since we're both such super fans of the NBA. Seems like the rule changes, the apron and you know how punitive it is has created a lot more parody in the league and nobody knows who's going to win.

38:11

Well, because you have to break up your team, right? Because at some point OKC will have to break up their team. That's why they collect all the draft assets. Because you can't have three max players and if one of them turns out to be hurt or not what you expected, then you're in deep, right? And so the second apron is just a complete game changer. And you have to be so much better at putting together a team than you were before. And you have to get lucky like the spurs have wen be on a rookie contract. You know, the OKC has got no hatchet on a rookie contract. He's not on a rookie contract any longer. So they have to be even more careful. And so it really changes the strategy behind building a roster.

38:33

So we're going to see back to backs or any more chance.

39:15

No chance.

39:18

No, I maybe back to backs, but not. What do they call when you have three? The three P3.

39:18

Yeah, there can be back to backs. Like, you know, if Jalen Jay Williams, J Dub hadn't gotten hurt for okc, I think they would have beat San Antonio and I think they would have beat the Nets.

39:23

I was worried about them versus the Knicks. I knew we could beat the spurs, but I was concerned about not know you could. I knew.

39:34

Come on, we beat them two out

39:41

of three of the games of the year. We split spanked him. I knew it would be like I said, Nixon 6. It was Nixon.

39:42

You guys barely beat the Hawks. And then.

39:48

Oh, come on now we, we were tweaking the offense and we just had to get cat to buy in us.

39:50

Anyways, let's talk. AI, let's talk.

39:55

But it is so great to be a champion. God, it was. Where's your ring?

40:00

They didn't give you?

40:04

They didn't yet. No, I'm gonna get it at the ring, sir. I, you know, I always was like, man, I got to follow Cubes and get, you know, a piece of it.

40:04

You'd always tell me you wanted to buy a team.

40:13

I always wanted to get like a, you know, a piece of the Knicks. And now it's like my net worth doing great. The value of the team disconnected from reality. I mean, my only chance is to call like Elon and be like.

40:15

Part about the valuations is it's not driven by attendance. It's not driven by wins or losses. It's driven by subscriptions to streaming services. And it's going to be interesting to see because it used to be we looked at ratings, TV ratings.

40:27

Yeah.

40:42

And people said the NBA was underperforming versus everybody else. Now the Knicks play. Obviously there's some pent up demand there, but what really matters is the number of subscribers Peacock gets, ESPN gets. It's the ratings for ad sales, but it's more subscribers.

40:42

I mean, I literally had to subscribe to like, I think one or two more services.

40:58

Well, that's the whole point. Right. And did you keep them? Is the question. Question.

41:01

Yeah, I'll keep them, Sure. I mean, there.

41:04

Will there be churn if there's churn. Who knows what happens with valuations if there's not Valuations keep on going.

41:06

Wow, it's so crazy. All right, Listen, there's your 45 minutes with Mark Cuban, the one and only.

41:12

I'm doing all it.

41:34