Mark Cuban on the AI Bubble: Who Actually Gets Wiped Out?
Mark CubanChamath PalihapitiyaJason CalacanisDavid SacksDavid Friedberg
- Cuban distinguishes the current private-capital risk from the dot-com bubble: the likely casualties are VCs, funds, and PE firms concentrated in peak-priced private rounds, not most Americans. Unlike public companies with “no revenue, no traffic, no nothing” doubling after IPO, today’s risk sits in funds chasing Anthropic and SpaceX outcomes; Cuban says “entry price matters” when unlaunched startups jump from $5 million–$10 million angel valuations to $40 million–$60 million.
- Calacanis warns that AI infrastructure is “planning for perfection”: Google, Meta, and other cash-generating giants are consuming cash flow in CapEx and borrowing on top, including through 50-year bonds. The $100 billion OpenAI thesis must return not just revenue but profitable “margin dollars.” AI price-performance gains could turn excess data centers into “pickleball courts,” although Cuban says video could make that bearish call wrong.
- Calacanis argues that smaller AI disruptors should raise $50 million–$100 million through IPOs so stock can fund acquisitions of legacy operators, domain expertise, and data without repeatedly raising expensive cash. Cuban agrees that stock is “incredible currency.” He also favors employees with life-changing private-company wealth collaring their exposure—“How rich do I need to be?”—as he did with Yahoo stock, despite losing tens of millions on an interim short hedge.
- AI’s immediate bottleneck is implementation, not mass unemployment: two years after forecasts that 50% of white-collar workers would lose their jobs, employment is still growing and companies need AI-literate people. Cuban cites Microsoft hiring 6,000 people and Anthropic and OpenAI planning forward-deployed work as evidence that enterprise AI is hard; agents fail, drift, and demand systems thinking.
- The asymmetric opportunity is company formation and bespoke software: users are creating 770,000 applications a week with Lovable; only 30% of its business is in the United States, and only 20% of its users are engineers. Cuban generated a 24-hour-video product concept, patent, business plan, licensing requirements, bill of materials, and source companies in 12 minutes. Even if imperfect, “every single business plan ever written” is wrong, and iteration is the point.
- Text-and-image systems still lack world understanding, making video, world models, robotics, and specialized medical tools the next capability layers. A two-year-old anticipates what happens when a sippy cup falls while AI has “no clue”; Cuban cites AMI, Jan LeCun’s world-model work, Matter.com’s spectroscopy satellites, and OpenEvidence, but insists medical AI is “not going to replace doctors.”
- Cuban’s broader thesis is that LLMs may reduce political information asymmetry because their currency is trusted answers, while social media’s currency is engagement. He also criticizes wealth-tax models that ignore behavioral mobility. Separately, Calacanis sees repeat founders gaining leverage by building in Texas, Nevada, or Florida, while preserving the counterpoint that New York contributes more to the federal treasury.
1. The bubble sits in private portfolios, not taxi-cab stock tips
Cuban’s historical distinction is where the leverage resides: dot-com companies with “no revenue, no traffic, no nothing” went public and surged 50% or 100% while people discussed them in taxis. Today’s absence of that public mania means the bubble could spare most Americans yet “destroy a lot of VCs and a lot of funds and a lot of PE.”
Cuban says he has watched many investors who deployed at the wrong moment go out of business. He recalls angel entry prices that once ran $5 million–$10 million becoming $40 million–$60 million before product launch, while Calacanis says fund managers crowded into Anthropic and celebrated SpaceX outcomes because they had to outperform the fund next door.
Calacanis raises the infrastructure-financing worry: private credit already has problems, while Google, Meta, and peers spend cash flow on CapEx and then borrow more, including through 50-year bonds. Cuban says the $100 billion OpenAI thesis must return not merely revenue but profitable “margin dollars,” which nobody can confidently forecast.
Calacanis’s fiber analogy supplies the bear case. Capacity advanced from 1 to 10 to 100 gigabits, bandwidth scarcity disappeared, and dark fiber was bought on the dollar; comparable AI price-performance gains could reduce power needs and leave planned data centers converted into “pickleball courts.” Cuban notes that data-center demand could instead be rescued by video.
2. Public stock is acquisition currency—and a collar is survival capital
Calacanis’s instruction to his portfolio companies is blunt: go public. A $50 million–$100 million IPO gives an AI disruptor stock currency to acquire legacy businesses, proprietary data, or domain expertise when incumbents cannot keep pace; Cuban recalls that Broadcast.com bought roughly five companies using stock rather than repeatedly raising cash.
Calacanis’s regulatory context is four years in which corporate-development contacts told him to stand down because acquisitions risked being broken up. Cuban frames Lina Khan’s approach as a Minority Report-style attempt to stop future monopolies. His point survives without megadeals because many valuable AI targets will remain small.
For Anthropic, OpenAI, or SpaceX employees sitting on life-changing gains, Cuban favors collars: “How rich do I need to be?” Before he could collar his Yahoo stock directly, Goldman Sachs built an index of internet stocks he thought “sucked,” which he shorted as temporary protection. He lost tens of millions on that leg—“but I made up for it.”
3. Enterprise AI still needs humans to install itself
Cuban’s reset is deliberately two-sided: “AI is a lot harder to implement than anybody expected,” yet it remains the most consequential technology he has seen. Personal agents, test-taking, and productivity gains can feel “easy-peasy”; mission-critical enterprise integration is difficult and frightening.
Predictions that 50% of white-collar jobs would disappear within two years have not materialized in Cuban’s telling: employment is still growing, businesses are hiring, and they need more AI-literate workers. CEOs, he says, “have no clue what is going on.”
Forward-deployed engineers are Cuban’s falsification test for current autonomy. Microsoft is hiring 6,000 people, while Anthropic and OpenAI say they will deploy into companies; users therefore cannot simply ask AI to implement itself. Alex Karp’s objection, in Cuban’s reading, is that these companies are adopting Palantir’s own forward-deployed model.
Even a simple recurring request—search for Jason Calacanis’s investments, report the results, and email them weekly—still requires code or JSON, correction, and iteration. Code and legal work benefit from narrow, mathematical structure; ordinary users still need the equivalent of yesterday’s Excel expert.
4. AI-first teams are building software that SaaS economics forbade
Inside Calacanis’s firm, AI-first employees solved five or six pressing problems while holdouts lagged as starkly as PC-and-Office users once outpaced colleagues on legal pads. His policy became “token max it”: spending a few thousand dollars monthly matters less than capturing the gains.
The path remains unstable. Teams bounced among OpenClaw, Hermes Agent, Claude Cowork, Perplexity Computer, and Lovable as agents became brittle, hallucinated, or proved too limited.
Lovable enabled staff to build a venture intranet that previously might have cost $500,000 and 12 months—and therefore would not have been commissioned. Two or three employees are now producing software Calacanis estimates would once have required $2 million–$3 million annually from an outsourcer.
Cuban’s durable opportunity is maintenance: “agents get bored” and drift as underlying LLMs change, breaking workflows written against earlier behavior. That creates room for AI-literate operators who can repair company-wide failures; Calacanis likewise says Lovable reached “$600 million in revenue” despite repeated predictions that frontier models would absorb it.
5. World models are the missing capability—and video is the capex wildcard
Cuban contrasts AMI, described as Jan LeCun’s world-model work, with systems built mainly from text and pictures. A two-year-old knows that pushing a sippy cup off a high chair brings a parent running and laughter; today’s AI does not understand that causal scene.
His sharper safety analogy: blindfolded at a street corner, would you trust a phone running AI or a seeing-eye dog? “I’m taking the dog every time.” The gap between linguistic intelligence and embodied understanding leaves substantial room for world models and robotics.
Matter.com is launching satellites using spectroscopy to record what lies below and convert it into a world model whose algorithms can be used by other world models. Video consumes vastly more tokens, so “if I’m going to be wrong on the data centers, it’s going to be because of video,” alongside world models and robotics.
OpenEvidence helped identify a timing conflict between Cuban’s iron supplement and medication, while ten years of blood tests every three to six months provide longitudinal context. Calacanis says “95% of medicine” is guessing because doctors cannot memorize every update; Cuban expects AI to augment their judgment and empathy, not replace them.
6. Truth-seeking models could weaken engagement politics
Cuban sees modern electoral advantage flowing to whoever best manipulates algorithms. Mamdani’s whole adult life has unfolded alongside Trump and social media; once a campaign provokes a search or interaction, recommendation loops deliver reinforcing Mamdani—or anti-Mamdani—content “24/7.”
LLM incentives are different: Claude and OpenAI lose trust if their answers appear dishonest, whereas social platforms profit by extending engagement. Cuban expects uncertain voters increasingly to ask, “Who should I vote for?” and receive questions about their interests before an honest answer; Calacanis says he uses “Act Rock” to vet politicians’ claims publicly.
That truth-seeking frame supports their case for legal immigration and global recruiting. Cuban’s roster analogy is zero-sum: when one team signs Dirk Nowitzki or Jalen Brunson, another cannot field that talent; losing entrepreneurs and skilled workers to other countries should therefore be alarming.
Calacanis predicts a return to normalcy after the midterms and next presidential election, while Cuban criticizes Democrats as unable to execute and Republicans as lacking empathy. When asked about running, Cuban says, “If he decides to run for a 3rd term, then I’ll run,” leaving the pronoun’s referent unstated.
7. Mobility disciplines tax policy and founder geography
Calacanis calls the wealth tax “dumb” and “crazy.” When Elizabeth Warren cited economic models, Cuban contacted a UC Berkeley economist and learned the analysis covered only one year and contained no behavioral assessment of how mobile taxpayers would respond: “showmanship more than reality.”
Cuban contrasts roughly $6,000 in Texas spending per resident with $12,000–$14,000 in New York. Calacanis’s counterpoint is that New York contributes more to the federal treasury than Texas, so the comparison carries trade-offs. Calacanis also says housing prices have fallen for three consecutive years in the Austin area and rents have fallen.
Their founder split is experiential: first-time entrepreneurs may still benefit from immersion in Silicon Valley, but repeat founders increasingly choose Texas, Nevada, or Florida, where talent can follow and building faces fewer constraints. Cuban’s cultural shorthand is “build your company and go,” rather than obsessing over Series A, B, or C status.
8. NBA value now rests on rookie contracts and streaming retention
Cuban says the second apron has fundamentally increased parity: teams cannot sustainably carry three maximum-salary players, one injury can trap the roster, and contenders such as OKC accumulate draft assets knowing they must eventually break up talent. Rookie contracts—Wemby’s included—create temporary strategic windows.
His forecast allows back-to-back champions but rejects another three-peat because roster economics force turnover and reward luck alongside construction skill. The same parity that frustrates dynasties makes outcomes less predictable.
Franchise valuations are no longer driven principally by attendance, wins, or television ratings. Ratings still sell ads, but Peacock and ESPN subscriber additions now matter more; “if there’s churn, who knows what happens with valuations. If there’s not, valuations keep on going.”
Full transcript
You and I lived through a couple of bubbles. We've seen this movie before, and this wave seems very different from the dot-com wave. Let's talk about that. Are you concerned about a bubble? We're seeing bubbly-like behavior.
It's not the traditional dot-com bubble, right? Back then, companies were going public, getting crazy valuations, and people were buying them. The stock would go up 50% or 100% for companies that had no revenue, no traffic, no nothing. If you got a cab back then, people would be talking about them.
Yeah.
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, or most people across the US. But it could destroy a lot of VCs, a lot of funds, and a lot of private equity, because they're going all in.
It used to be that product managers for brokerages had to outperform their numbers, right? For, you know, the SPX or whatever. But now you have to outperform to keep the money coming in. You have to outperform the fund next door. They're all in Anthropic, getting their outcomes in SpaceX, and celebrating. But if it hits the fan—
Yeah.
Oof.
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 go out of business. They invested at the peak, and entry price matters. You and I have been in a bunch of deals together, and we used to get to invest in companies at $5 million or $10 million as angel investors. Then, all of a sudden, the request was $40 million, $50 million, or $60 million, and the product wasn't launched. You're like, “How does this work?”
Yeah, and what's happening now is that the market leaders—Google, Meta, et cetera—are borrowing hundreds of millions, even billions, of dollars.
Yeah, that's interesting.
And there's already a private credit problem right now, right? So you just layer on private credit, like Al Capital getting all the refunds, and then you have these huge companies that have cash flow, but they're spending all their cash flow on CapEx and borrowing on top of that.
50-year bonds.
Right. That's planning for perfection, and that's going to be hard. We're building these data centers, and if there's a price-performance curve on AI that minimizes the power requirements, there are going to be a lot of data centers that get turned into pickleball courts.
Interesting, because they just can't get the power turned on.
No, and then there's the power. Everybody thinks that there's going to be so much more utilization—and there will be, right? It will scale like everybody expects. But there are going to be technological breakthroughs as well. It's just like what we saw with fiber back in the day. It was all about putting in fiber, then it went from 1 gigabit fiber to 10 to 100 gigabits, and then there wasn't a fiber problem anymore. There wasn't a bandwidth problem anymore.
Quite the opposite. We had dark fiber that people bought.
Yeah, and that's what people are doing—buying it on the dollar and just sitting there, right?
Yeah.
How is it not going to be the case that we get the same price-performance improvements on the AI side and on the data-center side?
Yeah.
And with all the hate going against the data centers, I think that could be protecting them. Spending and committing tens of billions of dollars for 10 or 20 years going out—nobody can predict that well.
I mean, you used the words “pricing to perfection” earlier in the conversation, and that's really what's happening. You have to have a thesis that we're going to put $100 billion to work in OpenAI, and that's going to come back not just in revenue, but in earnings.
In margin dollars, yeah.
Yeah, it has to be profitable.
Yes, and you just don't know.
You don't.
Now, I'll tell you the other corollary for bubbles. 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, not OpenAI, not Anthropic, but the $100 million IPO.
Yeah.
Because if AI does what we all know it will do in terms of disruption—
Yeah.
—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, right?
Yeah.
Well, if you don't have that currency—the stock is currency—
Yeah.
—you have to go out and raise money to do it, and if anything happens, that money is not cheap. That money is really, really expensive. Versus if you go out and do a $100 million IPO or a $50 million IPO, you can do a secondary, or whatever, as many times as you need if you're performing. But the minute that company you're competing with, which is a legacy business, can't keep up, or there's some other company that has domain expertise or data that you need, like you guys were talking about, you want to be in a position to buy them.
Yes. That is incredible currency.
Thinking. Yeah, nobody is forward-thinking like that at all. I'm trying to tell my portfolio companies, “Go public, motherfucker. Go public.” They just don't think that's the right thing to do.
Well, M&A is—not to make this political—but when you're an entrepreneur, you have to play the game on the field. M&A was off the table. Lina Khan had a certain perspective, which was, “We have to be like precogs in Minority Report. We have to predict who's going to be a monopoly in the future and stop them now.” It's like, okay, how are we supposed to compete with China and everything else that's going on globally?
Yeah. Four years of no acquisitions. The people I talked to who were in corporate development were like, “We've been told to stand down—”
Yeah.
—because it's not worth the breakup.
Where we are right now, even so, with mergers and acquisitions at that scale, fine. But if AI does what we know it will do, the companies that are disruptive don't have to be enormous companies.
No.
So you don't want to have to always raise cash to go out there and do that.
Because, like, back in the day with Broadcast.com, we bought 5 companies just for stock.
Yes, and then there was always a bigger fish to come along.
They were happy to be acquired by Yahoo.
Yeah.
Yeah, the famous scholar.
If you were a Claude employee—if you're at Anthropic or at OpenAI—is it time to start thinking about the collar? Trying to think about—
Yeah, I collared my stock, because how rich do I need to be? If you're able to change your life, if I worked for SpaceX, Anthropic, OpenAI, any of them, I'd be like, “Somebody put together a collar for me.” I just need to be protected. Save part of my upside, but cover my downside.
Right. And when you did it, you had to actually orchestrate that, right? It didn't exist as a product.
It didn't. So I had Goldman Sachs create an index of internet stocks that I thought sucked. Then I shorted that index, because we had to follow all the laws, and I had to have that short in place until I was able to do a real collar in the market on my Yahoo stock. I lost tens of millions of dollars on that short.
Yeah.
But I made up for it.
Yeah, I mean, one of the great trades of all time. What do you think this wave of capabilities in AI is going to do? I'm sure you play with it, because you've always been a tinkerer. What are you tinkering with, and what do you think is going to be the most world-changing in the next 5 or 10 years—for entrepreneurs, for society? Where do you look at it and go—
This is totally going to work backwards.
Yeah.
Okay. AI is a lot harder to implement than anybody expected.
For sure.
Right? You can do an agent pretty straightforwardly. You can prompt away, cheat on tests, cheat at work, do projects, and improve your productivity 100 times—all easy-peasy. We just assumed that, at the enterprise level, it would be just as easy. It's hard.
Yeah.
And it's terrifying—and not terrifying for employees, because everybody's saying 50% of white-collar people are going to lose their jobs. Here we are, 2 years later. They said it would happen within 2 years, and employment is still growing. People are hiring. We need more AI-literate people, right? CEOs have no clue what's going on. None whatsoever, and that's not going to change.
Trying to explain to them that you need to add a harness to the AI—no chance. If you think about it from an AI perspective, we're talking about AGI and 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 be able to ask AI to do what you need it to do and tell you how to implement it. Yet here you have Microsoft hiring 6,000 people, and Anthropic and OpenAI all saying they're going to deploy into 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?” In my opinion, he’s just saying they’re doing what we’re doing, right? We’re all about forward-deployed engineers at Palantir, and they’re doing the same thing.
It’s a great insight because if you’re using it as a search engine, or if you’re making your little agent to go to your cron job, okay, fair enough—it’s going to work. You need to have a little bit of systems thinking. But when you start putting it into the enterprise, and this is mission-critical work…
The little bit of systems thinking—that’s the second part. I’m not trying to shit 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 Claude or ChatGPT and saying, “Okay, I just want you to search for Jason Calacanis’s investments, report on them, and email it to me every week.”
Yeah.
It can’t do it.
Can’t do it.
And then it says, “Okay, would you like me to create an agent that gives you alerts?” And then you say, “Sure,” and you have to know how to program because it either gives you a JSON file or it gives you code.
And it comes out slop, and then—
Yeah, then you have to correct it. You have to reiterate. If you want to say, “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?”—or business versions of that—great.
Yeah.
Right? But AI is not going to take away 50% of the jobs. There’s just so much it can’t do that regular people need it to do.
Yeah.
Now, does that create opportunity? Enormous opportunity, right? I’m an investor in Lovable, and we were here this morning talking. Anton was saying that people are using Lovable to create 770,000 applications a week. A week.
Yeah.
Right? Only 30% of their business is in the United States, and only 20% of their users are engineers. What’s happening is that entrepreneurs, to answer your question about where it’s going—like he was saying before, there’s no better time to be an entrepreneur. He nailed it, right? That’s where AI is the most impactful.
No matter where you are in the world, they have significant utilization in Brazil and India. If you’re in France, the United States, wherever. I gave it a prompt because I wanted to see what it would take. I said, “Okay, we’re going to create an imaginary company that has a button that can record 24-hour video. I want it to be able to send it to me every 24 hours, and I want you to create a patent and a business plan and tell me what licensing or whatever I need.” Twelve minutes.
Yeah. Wow.
Dude, just know we’ve started a ton of businesses.
Yeah. Six months to get a prototype, 12 months to launch it.
Yes.
And then you have to—
And then I asked for a bill of materials and the source companies—the basic stuff, the blocking-and-tackling stuff that every company has to do when you’re setting it up and early in its life cycle.
Done.
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, is that every single business plan ever written in the history of business plans—
Yeah.
—is wrong.
Of course. Yeah, it’s a thought exercise that at least gives you some sort of direction you’re going in.
Yeah, and it’s some sort of guideline and a template for you, right? But it’s wrong.
Yeah, we’re going to iterate.
So what if the AI is wrong? If the model is wrong, 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—
Yeah.
—right? And you have to have, like you said, a programming mindset in order to be able to iterate and figure it out.
Even you would think that if AI is as advanced as we want to believe it is right now, all the errors we get when we ask it to do a project—it would learn from all those errors and even say, “Hey, I’m Claude. I see you have a problem with this, right? It failed on these 3 attempts. Let me just tell you what 97.6% of the other people who ran into this did.” Then it would fix it for you. It 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.
Yeah, when you have a narrow data set, like code or legal—
It’s just math. It’s math.
Yeah, and it’s just math, right? Basic data.
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 or Excel used to be, right? You always had to have your Excel expert, or your PowerPoint—
Company.
Yeah, or whoever it was that you knew, right? There would be companies built around it. I invested in a company called SlideShare, where all they did was have PowerPoint templates that you could download and redo. AI’s not even that advanced once you get to the second level.
So it creates so much opportunity for anybody to walk into a small, medium-sized, or even large business and say, “Hey, I understand AI. I have a basic computer background or better. All these failures you’re running into across your company, big or small, I can help you fix them.”
Mhm.
Because what AI can do once those issues are fixed is phenomenal.
Yeah.
But it’s even better if you’re thinking as an entrepreneur and want to start a business. Those things will eventually break. Agents get bored, right? And they drift. As the underlying large language model starts to change, the way it was originally programmed no longer matches what the large language model has turned into. You see what I’m saying?
Yeah.
And you even wrote something about this, right? Where it’s taking more people to manage all this stuff.
I’m trying to get the whole firm to be AI-first. Even with young people, one group embraces it and solves, let’s call it, 5 or 6 really pressing issues. The other group isn’t embracing it, and the difference between those AI-first employees and the non-AI-first employees is like—whoa. It’s almost like when we got into the industry and somebody knew how to use the office suite and a PC—
Right, right.
—and somebody else was on legal pads. It’s that much of a difference. It’s so stark.
People who are AI-literate—when do they run into a ceiling?
Well, what I’m seeing is a lot of tool-hopping. They started with OpenClaw and started building it; it got brittle, and then it just got—
Who uses OpenClaw?
Who’s using Hermes Agent? Okay, there you go. Who’s on Claude Cowork? And Perplexity Computer, anyone? Okay, interesting. Those are the 4 tools people have been bouncing around on.
What I decided to do was just say, “Hey, token-max it. You can use it for a couple thousand dollars a month. I don’t care about that. I just care about the gains.” They all wound up going from OpenClaw. All the agents started breaking and hallucinating, and it was too frustrating. They started using Claude Cowork. Okay, great, but it was kind of limited.
Then they started using Lovable. They built intranets for the venture business that no venture business would spend $500,000 and 12 months building. You’d just put it in Notion, Google Sheets, or whatever. Then they started building more and more software.
I have 2 or 3 people building software that, 5 years ago, we would have spent maybe $2 million or $3 million a year building with an outsourced company.
We would not have done it.
Which means we wouldn’t have done it.
Right. You would’ve just bought the SaaS application that did it.
And then we would have tried to shoehorn it into a SaaS app and customize it. It wouldn’t have worked. We would have given up.
But how are you going to manage it now once they get there?
Well, again, to your company, Lovable—man, congrats on that investment, because that company was going to go out of business 4 times. I told Anton, “Every time they say you’re going out of business, you add 100 million in revenue.”
Six hundred million in revenue. And 4 times—200 million, 300 million. Oh, yeah, it’s going to be absorbed into the frontier model, right?
Right? I mean, I’ve got Lovable. I’ve got Synthesia, which I was the first investor in, like, 10 years ago, maybe, and that’s just killing it, right? I’ve got AMI, which is Jan LeCun's world model.
We haven't even talked about world models versus LLMs and transformers, right? Because everything we do is built on text and pictures.
Yeah.
Nothing's going to beat text and pictures in 10 years, right? But what's going to drive it? People say, “AI is so smart, it's going to change everything.” I'm like, “Okay, if you show AI a video of a 2-year-old in a high chair with a sippy cup, the AI knows that if you push the sippy cup over the edge, Mom's going to come running.”
Yeah.
And the kid's going to start laughing.
Yeah.
AI has no clue what's going to happen.
Yeah.
None, right? If you're at a corner blindfolded and you have to cross the street, would you rather have a video, or would you rather have your phone with AI? Or would you rather have a seeing-eye dog?
Yeah. A dog.
I'm taking the dog every time.
Yeah. It's not ready.
Right?
Yeah.
It's not ready. Just think about how far we have to go.
Yeah. Huge opportunity, though. The world models are crazy because you have videos available on YouTube; we have the world there. World models are not enough. It’s not enough. They have to wear gloves, and now they’ve got people in Manila doing recipes.
So, I invested in this company matter.com and they're launching satellites just to take— they do spectroscopy, where they use the satellites to take videos of everything underneath them and use a spectrum. I don't even understand all of it, but it's in order to convert it into a world model that will provide algorithms that other world models can use, right? There's just no way that the future of AI doesn't include video.
Well, it's a huge part of it. As we think about inference and the build-out of these data centers, and wonder what's going to happen with people wanting to use more tokens, world modeling and video take a magnitude more tokens.
If I'm going to be wrong on the data centers, it's going to be because of video.
Yeah.
Right?
And world models and robotics, which is all related.
Yeah. And in robotics, it's related, but we still have a long way to go.
Yeah. Health—you look great, by the way. I don't know what's going on. What do you have, the red tie? What's on the menu here? What's off the menu?
I'm eating better.
I mean, you look better now than you did 20 years ago.
I appreciate that. Thank you.
Yeah, you look thin and fit. Listen, we're getting up there now. We're not kids anymore.
The tan helps, too, right?
The tan, but you look thin and fit.
I use it, too. I invested in a company called OpenEvidence.
Yes.
It's just for medical care, right? I used it, and I have one supplement I have to take because my iron levels are low, and I have to take one medication. I was taking them at the same time and couldn't understand why I was having problems. I ran it through OpenEvidence and said, “Here's everything I'm taking. Here's everything I'm eating.” They said, “No, you have to do this. When you get up to pee at 3:00 in the morning, take this medication. When you get—”
Getting old sucks.
Yeah, right.
I was right there with you last night. What's going on?
What's going on, right? For health, it's going to make a huge difference, but it's not going to replace doctors.
No. But it is pretty amazing. Are you on Whoop or your Apple Watch?
Yeah.
The Whoop, plus getting your blood tests, is self-directed health care with AI. You're going to get some early wins, and then when you do go talk to your doctor—
No, you have it right there, right? I have my blood tested every 3 to 6 months.
Yeah.
I've been doing it for 10 years, so I know all my trends.
Wow.
And so—
You were doing it before Function and Superpower and all of those.
You could go look up “Mark Cuban blood tests” on Twitter—X. I would get into it with doctors 8 or 10 years ago, just saying, “You're going to need this for your benchmarks.” It's only going to get better.
Yeah. What's going to be really interesting is that we had this big-data moment. It was like, “Okay, we're storing all this data, but we didn't have any intelligence against it.” Now Apple is putting that data to work and doing studies. I don't know if you've been invited to studies on your Apple Watch, but I'm like, “This is going to get very interesting.” Whoop just added blood panels. Now you have your sleep data, your steps, your heart rate, your respiratory rate, your EKG, plus your blood work—
That's pretty amazing.
Then if you can get your diet into it as well—
Yeah, that's what my watch has in it—health, right?
Yeah. You're just going to get smarter.
Yeah.
That'll make your doctors smarter because 95% of medicine is guessing. There's no way a doctor can memorize all the new information that comes out every single day. You just can't. But a doctor using these tools, having the empathy and the ability to communicate, and the ability to see—
Yeah.
Right? Because, again, there's— you can't see.
Yeah.
You could have a doctor ask, “Why am I bleeding?” Well, you've got blood that looks like a gunshot wound, right? They're not going to tell you that today.
When we look at the opportunity here, there's going to be a lot of change and 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. Thanks for welcoming me; I'm enjoying my time in Texas.
Yeah, I love Texas, man.
Texas is fun. The heat's kind of like this, though.
Yeah.
But we have air conditioning.
We do have air conditioning. There's a record number of air conditioners coming from China to Europe this summer.
You know, I looked at what companies installed them and everything.
Oh, you always have to trade. You always have to trade.
But there's no real—
Sold out. They're all being shipped here from China at the moment.
But, really interestingly, it feels like entrepreneurship—which has been our shared passion for many decades—and investing are two other shared passions. Giving people access to public markets through Invest America is interesting. We have this dueling narrative: socialism in America versus capitalism. You and I are close in age, and this is the most fevered we've ever seen it in our lifetimes.
Maybe not since the '60s or '70s.
I missed that. I was born in 1970. You were born, I guess, in 1958.
58.
58. I always joke that he's my older brother.
Don't I?
You look good for 1923. This is pretty polarized. What's your take on the socialist movement?
There are 2 things here. One, all the DSA stuff is local. It's really easy to be Mandami in New York when you have a budget you get to control, and it's local, right? You got elected, you just do it, and you have to balance the budget. 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 that the people doing this are the people who are best at social media.
Right.
The algorithms drive how people vote in the United States. I can't speak to the rest of the world. More than anything else, whoever controls the algorithm controls the election in many cases. Trump knows how to use it. What's unique about Mamdani relative to Trump? He's 31 or 32 years old. His whole adult life has been Trump—
Mhm.
—and social media.
He studied it.
And the 2 together. The same thing applies. If you're good at driving algorithms, whether it's flooding the zone or Trump's saying, “They're eating cats and dogs”—
Yeah, it's just attention.
Yeah, and it's just defining the algorithms, because whatever you search for, you get more of. If they can get you to search for what they're saying and show your interest, then you're going to get Mandami 24/7.
Yep.
You'll get the positive sides of Mandami, or if you happen to be on the other side of the aisle and are looking at things that are counter to that, you'll get more of that. But one other piece I think is starting to change that, and that's large language models.
Mhm.
The thing that I think will save us as a world more than anything else—in terms of information availability and reducing information asymmetry as it applies to politics—is large language models. Large language models have to be as literate, literal, and honest as they possibly can.
Truth-seeking.
Yeah, truth-seeking. That's a better way to put it. They have to seek truth; otherwise, you'll lose trust in them.
The last thing Claude or OpenAI needs is to lie about this.
Yeah, their currency is getting you the correct answer and the correct knowledge. Social media’s currency is keeping you engaged. It’s 2 different missions.
Totally different missions, right? 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?”
Mhm.
And the large language model’s going to come back and say, “Well, what do you think about this? What are your interests in this and that and that?” And they’ll give you honest answers.
Yeah, and if you ask it, “Hey, what’s a reasonable immigration policy?” it’ll give you a reasonable immigration policy, which is, yeah, maybe shut the border and do a point-based system like Canada or New Zealand.
Whatever it may be, right? Yeah, I’ve done the same thing, and it’s impressive.
Very impressive. You know, my favorite troll now is, like, JD or AOC. They’ll come out with whatever their craziness is on either side of the aisle, and then I’m like, “Act Rock, please vet these claims. Be as objective and factual as possible. Check your work.” And then it just replies to them. So I’ve been totally trolling Stephen Miller.
[Laughter] Oh my gosh.
He’s anti-immigration. I’m very passionate about legal immigration and recruiting great people because—
You need them. We need them.
We need them. If every coach is 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.
Well, that’s why we come to these things in Europe, right? Because of great talent, smart people. Obviously, you guys are geniuses for being here. But at the same time, there’s a different vibe in every European country, and India and the whole rest of the world, right? I think you’re starting to see some entrepreneurs leave us—
Yep.
—to come here, and that’s scary. Hopefully, large language models seeking the truth will help educate people away from what the algorithms tell them.
Do you feel optimistic now? It’s been pretty chaotic, but we’re seeing such great progress. Are you optimistic? Let’s start with America, and then we’ll go to humanity.
Yeah, no, I mean, like every country, we have our issues. Ours just happen to be insane.
It is pretty wild.
Yeah. But the good news is, we have term limits for our president.
Yeah. And it seems like 12 years, 3 terms, is going to be the one for president. I mean, are you going to run? I hope you do, man. I’d love to be your press secretary. That would be fun, though. We’d have so much fun.
We’d have fun. If he decides to run for a 3rd term, then I’ll run.
Yeah, okay, that’s good. That’s breaking news. Honestly, if you think about what we need in leadership, executives who are post-money, post-needing to make a living, who are doing it for the love of country and maybe some amount of civic pride—
You mean that? No, I’m not going to even go there.
[Laughter]
No, I get what you’re saying, right? It’s just like, in the US, the Democrats don’t know how to actually do anything. They know how to take whatever happens and extrapolate that to the end of the world and the end of democracy, right?
Right.
But the Republicans, on the other hand, do crazy things. They don’t care about the people in the country. There’s no connection to people, and there’s no empathy. But in the short term, as we get past the midterms and the next presidential election—
I think we go back to normalcy. I think we’ll get back to normal.
I think people want it, and the thing that’s been really eye-opening for me, having lived in New York, California, and now Texas, is that in Texas we’re spending half as much money per person, sometimes less. I think 2 to 2.2 times as much is spent on each citizen in New York, and we spend half as much. It’s $6,000 per person; they spend something like $12,000 to $14,000. And the quality of life is better.
But on the flip side, New York contributes more to the federal treasury than Texas does, right? You would think it should be the opposite, just because of the business and how things are run. So there are trade-offs.
Yeah, but it’s changing. What do you think about all of us moving to Austin and Texas?
Smart, obviously, for obvious reasons, particularly because the wealth tax is just dumb, crazy.
They tried it here.
Yeah, it didn’t work. And they did it for about 2 years in France.
Did they? I don’t know. But when Elizabeth Warren first proposed the wealth tax, 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 said, “No.” I asked, “Was it more than 1 year?” He said, “No, it was just 1 year.” I asked, “Did you do any behavioral analysis to see how people would respond to the changes?” No. So whether it's Madami, Elizabeth Warren, or California, it’s showmanship more than reality.
Yeah, and I think people are forgetting that people are mobile.
In the US—
Yeah, in the US, it’s pretty extraordinary. You’ve got Travis, Sachs, myself, Elon—just a bunch of folks have all of a sudden shown up.
I was there first.
You were. I remember talking to you about it. And the thing that’s amazing to me is, in California, they won’t let you build anything. Then I come to Texas, I buy a ranch, and I ask the guy, “Hey, can I put a solar farm in here?” He says, “On your ranch?” I say, “Yeah, here.” He says, “Oh, son, at your ranch, you can do that.” And I’m like, “Can I build, like—”
Trust me, they do it in the cities themselves. Try doing that in the city of Austin.
But just outside of it, you can build. Housing prices have gone down 3 years in a row, and housing prices and rents have gone down. When you build a company in Austin now—and I’m sure it’s like that in Dallas, 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 a world—”
They still go to Silicon Valley? That pisses me off.
I think if you’re a first-time founder, there’s nothing better in terms of soaking in it. But when you’re a second-time founder, you’ve already soaked in it. What they don’t tell you is that it’s tough. I think second-time founders have now realized, “If I build it in Texas or Nevada or Florida, all the talent’s going to come.” That’s where people’s heads are so wrong. So whether it’s Travis or Mike—by the way, I’ve known Michael Dell since we were 22, and I used to do business with him way back when. But in Texas, it’s just like, build your company and go.
Yes.
In the Valley, it’s like, “Are you Series A? Are you Series B? Are you Series C?”
A lot of distractions, yeah.
25 years I've been waiting for my Knicks to win a championship.
And you played a significant role.
No, the Spurs played a significant role. They should have kicked your ass.
And why didn’t they? Why didn’t they?
I think it was coaching and lack of experience. Put aside the 29-point lead, right? You’re up in the 4th quarter of every game. Wemby throws it into the back of some guy, misses 2 free throws, and De’Aaron Fox goes the wrong way.
A lot of mistakes.
Yeah, and you’d be talking about firing Mike Brown.
[Laughter] I mean, it was—we were concerned when he got hired and getting rid of Tibbs. And oh my God, Tibbs.
But J.B. was the real deal, right? He’s my Indiana boy, OG. He saved you guys.
Yeah. And you had Jalen Brunson.
Yep.
He left, and that was kind of destiny. His family wanted to come to New York—
That’s what he wanted. I mean, I could show you a text where his agent texted me and said he wants his own team.
He wants his own team.
Right. Yeah, he was ready to go before—
And I texted or emailed you, and I said, “What’s the story?” Like, this is what we’re going to base the franchise on. You said, “He’s really good.”
You know what I love? He’s a great guy. That’s the best part about J.B. He’s just a really good human.
I was there for the 5th game, 6 rows behind the bench.
That’s cool.
And, man, I just cried. I just cried.
It’s been so many years. And you got your chip, too, with Dirk.
Yep. It’s so amazing how sports plays such a role in so many people’s lives.
Especially now, look at the World Cup.
I mean, it’s incredible.
Sports has just changed everything. I’ve been to 4 World Cup games in Dallas, and I hate soccer—football.
Right.
Right?
Yeah. 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. Yeah, and the NBA—is it—has it peaked? It sounds like—
It’s hard to say. For fans, no, because it just grows on social media. I was walking in Paris, and there was a basketball store, and it had Wemby jerseys and Gobert jerseys and everything. So it’s just growing globally.
Yeah, is Wemby the real deal?
Yeah, he got humbled, though.
Yeah.
Which is good for him. It’s like Dirk in 2006 got humbled and came back better. Wemby will come back bigger, stronger, better.
Yeah, it’s amazing how he went from this—I don’t know, there was a magic about him—to, “No, he’s a villain.” And he turned into a villain.
Because it was New York and 50-some years, right? And just the circumstances. San Antonio thought they had it in the bag. It’s like, I went to Indiana University, right? If anybody here follows football in the States, we were the ultimate underdog. We had not won 10 games. We beat more top-10 teams last year than we did in 100-plus years of the program. And so, that just changes people’s attitude.
You were very much involved in rule changes. 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. It seems like the rule changes, the apron, and how punitive it is have created a lot more parity in the league, and nobody knows who’s going to win. Like—
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 3 max players.
No.
And if one of them turns out to be hurt or not what you expected—
Mm-hmm.
Then you’re in deep, right? And so the second apron is just a complete game changer. You have to be so much better at putting together a team than you were before, and you have to get lucky. The Spurs have Wemby on a rookie contract. OKC has got hatchet on a rookie contract. He’s not on a rookie contract any longer.
Right.
So they have to be even more careful. And so it really changes the strategy behind building a roster.
So we’re going to see back-to-backs or any more—
No chance.
No, I—
Maybe back-to-backs, but not a—what do they call when you have 3? The three-peat.
Three-peat, yeah.
No more three-peats. There can be back-to-backs. Like, if Jaylen Jay Williams Jay Dubbhadn’t gotten hurt for OKC, I think they would have beaten San Antonio, and I think they would have beaten the Knicks.
I was worried about them versus the Knicks. I knew we could beat the Spurs, but I was concerned about them.
You knew you could beat the Spurs?
Them? Come on. We beat them 2 out of 3 games this year. We spanked them. I knew it would be like—I said Knicks in 6. It was Knicks in 5.
You barely beat the Hawks, and then—
Oh, come on now. We were tweaking the offense, and we just had to get KAT to buy in as a 5.
And he was just talking AI.
Yeah, let’s talk AI. But it is so great to be a champion. God, it was—
Where’s your ring? They didn’t give you a ring.
They didn’t yet. No, I’m going to get it at the ring ceremony.
Yet? You got one?
I always was like, man, I’ve got to follow Cubes and get a piece of a team.
Like me, you want to buy a team.
I wanted to get, like, a piece of the Knicks, and now my net worth is doing great. The value of the team is disconnected from reality. I mean, my only chance is to call, like, Elon, and be like—
Yeah, the valuation isn’t driven by attendance, it’s not driven by wins or losses; it’s driven by subscriptions to streaming services.
Wow.
And it’s going to be interesting to see, because it used to be we looked at ratings, TV ratings, 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. The ratings sell for ad sales, but it’s more subscribers.
I mean, I literally had to subscribe to, I think, 1 or 2 more services just—
Well, that’s the whole point, right? And did you keep them is the question.
Yeah, I’ll keep them, sure. I mean—
But will there be churn? If there’s churn, who knows what happens with valuations. If there’s not, valuations keep on going.
Wow. It’s so crazy. All right, listen. There’s your 45 minutes with Mark Cuban, the one and only.