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Mark Cuban: OpenAI Will Never Return the $1T It's Investing [video]

jqpabc123 5mo ago
In my experience, Cuban is generally pretty good at stripping away the stupidity and BS.
- aurareturn 5mo ago
  Sometimes he is the stupidity and BS.
  - orwin 5mo ago
    Yeah, he falls in the categories "is able to underline the issues" + "Explain why you are beeing bullshitted", but also in the "Snakeoil salesman", and that made him hard to trust. Basically i listen to him to talk basketball and that's basically it.
  - consumer451 5mo ago
    Genuine question: could you please share some notable examples?
- rwmj 5mo ago
  He's stating the obvious, but perhaps it needed to be said.
aurareturn 5mo ago
He's right, there is a race. It's going to be a natural monopoly or duopoly because the cost to train the next SOTA model is always increasing. I can see that there are only 3 companies competing for the duopoly or monopoly realistically: OpenAI, Anthropic, and Google. Everyone else has fallen behind. The flywheel of generate more revenue, get more data, get more compute train a better model might already be too great to overcome for anyone else. I don't understand why he thinks OpenAI can't be one of the duopolies or become the monopoly. OpenAI's models are always the first or second best overall - usually the first. They are also leading in the consumer market by a wide margin. They also made a strategic decision that is paying off which was committing to more compute early on while Anthropic is hammered by the lack of compute. PS. They've raised ~$200b total, not $1 trillion.
- jqpabc123 5mo ago
  https://www.reuters.com/business/openai-makes-five-year-plan-meet-1-trillion-spending-pledges-ft-reports-2025-10-15/ https://www.reuters.com/business/openai-makes-five-year-plan...
  - aurareturn 5mo ago
    This is a 5 year pledge - likely based on hitting revenue goals and not just using investor money.
- libertine 5mo ago
  Out of those 3, only Google seems to be in the position to reach that kind of profit levels due to distribution and advertising. Claude is kicking ass in the niche of coding and processes. 1 trillion is a lot of money for something that's not differentiated and protected in a massive market. Does it look like OpenAI has that in place? Cuban thinks they don't, and won't.
  - aurareturn 5mo ago
    I wrote about how I think OpenAI is going to kill it in advertisements here: https://news.ycombinator.com/item?id=46087109 https://news.ycombinator.com/item?id=46087109 Claude is kicking ass in coding but it seems like Codex is catching up fast. Claude Code's PR has taken a hit recently due to the lack of compute forcing Anthropic to dumb down the models. Codex has been gaining momentum. Chip manufacturing aren't really differentiated either - it didn't stop TSMC from becoming the monopoly for high end chip nodes, capturing 90%+ of the advanced chip market. The reason they have is because Rock's Law makes it too expensive to build the next node unless you've generated enough revenue from the current node. I don't see why it isn't the same for SOTA models.
    - rwmj 5mo ago
      Chip manufacturing is insanely hard, it requires know-how, that's the moat. It's not money, otherwise the EU and China would have leading edge fabs. Machine learning has no real moat. There's no network effect, it's not hard (you can just throw money at the problem). It's not data, because we have an existence proof that general intelligence can be trained by a few humans and a shelf full of books. The compute to do it is generally available. As soon as one organization releases open weights, everyone can use it immediately, even on modest local hardware.
Jare 5mo ago
> Fewer people applying for patents, because the minute you apply for the patent, it's available to everybody, which means every model can train on it We know LLM companies have, for lack of a better word, "sidestepped" the copyright on millions of works with their "transformative fair use" arguments. Are LLMs also a way to sidestep patents?
- pjc50 5mo ago
  LLMs are accelerants. They enable people to do patent and copyright infringement at a much larger scale. As we know from previous examples, if you break the law enough as a company eventually they have to let you keep doing it.
  - newsy-combi 5mo ago
    Not just as a company...
- dgellow 5mo ago
  I don’t see how? You can train on something pending patent, but what are the benefits? If it gets patented you open yourself to get sued, I don’t see how AI works around that, the idea itself is still patented? I think I’m missing something for the argument to make sense. Or is the idea that if too many people use your patented idea you won’t be able to enforce it? That sounds risky to me
  - ozlikethewizard 5mo ago
    Because no AI company has been sued yet. Without more specific legislation there is no reason for AI trainers to not pilfer everything.
    - JumpCrisscross 5mo ago
      Patents are public. Ingesting and innovating on them is the intended use. If you use an LLM to then make and market something that infringes on a patent, that isn’t the LLM doing any infringing, it’s you.
feverzsj 5mo ago
Why should they return your money if it's a Ponzi scheme?
grunder_advice 5mo ago
IMHO, Google, Meta and Microsoft are best positioned to be the last ones standing because they have alternative cashflows. The danger with OpenAI and Anthropic is that they might end up being the Sun Microsystems of the AI era. It will only takes them a couple of misteps along the wrong technology path for them to be out of the game.
SilverBirch 5mo ago
I think it's unquestionably right that these companies can't all win, and those that don't win are going to burn a lot of money for nothing. However there's kind of two directions this can go: Compute gets cheaper, in which case there's no monopoly it'll be easy for many companies to make good models and there won't be pricing power on serving a good model. The other case is compute gets cheaper but we keep using more and more of it, so it does likely become winner take all. The first scenario is good for the economy but likely bad for the returns on these AI stocks. The second is maybe bad for the economy and maybe not even good for the winner. Take Google or Meta: Today Google makes a shit-tonne of money and to make that money they need to run some servers. The servers are extremely cheap relatively to the revenue they make running the business. This makes them a very attractive stock - the core of why SAAS looks great. Now let's assume the monopoly path. Google can win. I think they likely will win. But now they're going to spending... how many hundreds of billions constantly training new models? The cost of providing the service suddenly isn't small relative revenue they're getting. So even for them it looks awful for their valuation.
- JumpCrisscross 5mo ago
  > these companies I think the conclusion the market is rapidly and correctly reaching is we aren’t in an AI bubble, we’re in an OpenAI bubble. Google, Amazon and Anthropic look likely to see ROI on their capital investments because they’ve made them halfway reluctantly. Microsoft is up in the air. Not sure what Meta is doing. And with the benefit of hindsight, OpenAI used capex as a marketing strategy with investors (while Sam Altman materially lied about his compensation and somehow looped Paul Graham and Jessica Livingston, founder of The Information, into his racket).
  - aurareturn 5mo ago
    Why would you say we're in an OpenAI bubble if Anthropic is valued more than OpenAI now?
    - JumpCrisscross 5mo ago
      > Why would you say we're in an OpenAI bubble if Anthropic is valued more than OpenAI now? One, it’s not. They’re roughly even. The folks quoting crypto tokens don’t know what they’re talking about. Two, Anthropic has more revenue and higher-quality growth. Three, OpenAI is levered in a way Anthropic and the tech giants are not. Nobody is immune from being overvalued. But what separates a bubble from normal overvaluation is leverage—the consequence of the valuation deflating isn’t just losses, it’s total loss because of debt or debt-like obligations. OpenAI has racked those up in its datacenter drive. Anthropic and the tech giants have been more disciplined. If OpenAI’s revenues dip, its valuation not only crashes, its commitments to various datacenter projects start strangling it.
Yizahi 5mo ago
OpenAI maybe won't, but someone else will. Maybe US government, maybe some fund etc. Too big to fail.

In my experience, Cuban is generally pretty good at stripping away the stupidity and BS.

aurareturn 5mo ago
Sometimes he is the stupidity and BS.
- orwin 5mo ago
  Yeah, he falls in the categories "is able to underline the issues" + "Explain why you are beeing bullshitted", but also in the "Snakeoil salesman", and that made him hard to trust. Basically i listen to him to talk basketball and that's basically it.
- consumer451 5mo ago
  Genuine question: could you please share some notable examples?
rwmj 5mo ago
He's stating the obvious, but perhaps it needed to be said.

He's right, there is a race. It's going to be a natural monopoly or duopoly because the cost to train the next SOTA model is always increasing. I can see that there are only 3 companies competing for the duopoly or monopoly realistically: OpenAI, Anthropic, and Google. Everyone else has fallen behind. The flywheel of generate more revenue, get more data, get more compute train a better model might already be too great to overcome for anyone else. I don't understand why he thinks OpenAI can't be one of the duopolies or become the monopoly. OpenAI's models are always the first or second best overall - usually the first. They are also leading in the consumer market by a wide margin. They also made a strategic decision that is paying off which was committing to more compute early on while Anthropic is hammered by the lack of compute. PS. They've raised ~$200b total, not $1 trillion.

jqpabc123 5mo ago
https://www.reuters.com/business/openai-makes-five-year-plan-meet-1-trillion-spending-pledges-ft-reports-2025-10-15/ https://www.reuters.com/business/openai-makes-five-year-plan...
- aurareturn 5mo ago
  This is a 5 year pledge - likely based on hitting revenue goals and not just using investor money.
libertine 5mo ago
Out of those 3, only Google seems to be in the position to reach that kind of profit levels due to distribution and advertising. Claude is kicking ass in the niche of coding and processes. 1 trillion is a lot of money for something that's not differentiated and protected in a massive market. Does it look like OpenAI has that in place? Cuban thinks they don't, and won't.
- aurareturn 5mo ago
  I wrote about how I think OpenAI is going to kill it in advertisements here: https://news.ycombinator.com/item?id=46087109 https://news.ycombinator.com/item?id=46087109 Claude is kicking ass in coding but it seems like Codex is catching up fast. Claude Code's PR has taken a hit recently due to the lack of compute forcing Anthropic to dumb down the models. Codex has been gaining momentum. Chip manufacturing aren't really differentiated either - it didn't stop TSMC from becoming the monopoly for high end chip nodes, capturing 90%+ of the advanced chip market. The reason they have is because Rock's Law makes it too expensive to build the next node unless you've generated enough revenue from the current node. I don't see why it isn't the same for SOTA models.
  - rwmj 5mo ago
    Chip manufacturing is insanely hard, it requires know-how, that's the moat. It's not money, otherwise the EU and China would have leading edge fabs. Machine learning has no real moat. There's no network effect, it's not hard (you can just throw money at the problem). It's not data, because we have an existence proof that general intelligence can be trained by a few humans and a shelf full of books. The compute to do it is generally available. As soon as one organization releases open weights, everyone can use it immediately, even on modest local hardware.

Jare 5mo ago

> Fewer people applying for patents, because the minute you apply for the patent, it's available to everybody, which means every model can train on it We know LLM companies have, for lack of a better word, "sidestepped" the copyright on millions of works with their "transformative fair use" arguments. Are LLMs also a way to sidestep patents?

pjc50 5mo ago
LLMs are accelerants. They enable people to do patent and copyright infringement at a much larger scale. As we know from previous examples, if you break the law enough as a company eventually they have to let you keep doing it.
- newsy-combi 5mo ago
  Not just as a company...
dgellow 5mo ago
I don’t see how? You can train on something pending patent, but what are the benefits? If it gets patented you open yourself to get sued, I don’t see how AI works around that, the idea itself is still patented? I think I’m missing something for the argument to make sense. Or is the idea that if too many people use your patented idea you won’t be able to enforce it? That sounds risky to me
- ozlikethewizard 5mo ago
  Because no AI company has been sued yet. Without more specific legislation there is no reason for AI trainers to not pilfer everything.
  - JumpCrisscross 5mo ago
    Patents are public. Ingesting and innovating on them is the intended use. If you use an LLM to then make and market something that infringes on a patent, that isn’t the LLM doing any infringing, it’s you.

feverzsj 5mo ago

Why should they return your money if it's a Ponzi scheme?

grunder_advice 5mo ago

IMHO, Google, Meta and Microsoft are best positioned to be the last ones standing because they have alternative cashflows. The danger with OpenAI and Anthropic is that they might end up being the Sun Microsystems of the AI era. It will only takes them a couple of misteps along the wrong technology path for them to be out of the game.

SilverBirch 5mo ago

I think it's unquestionably right that these companies can't all win, and those that don't win are going to burn a lot of money for nothing. However there's kind of two directions this can go: Compute gets cheaper, in which case there's no monopoly it'll be easy for many companies to make good models and there won't be pricing power on serving a good model. The other case is compute gets cheaper but we keep using more and more of it, so it does likely become winner take all. The first scenario is good for the economy but likely bad for the returns on these AI stocks. The second is maybe bad for the economy and maybe not even good for the winner. Take Google or Meta: Today Google makes a shit-tonne of money and to make that money they need to run some servers. The servers are extremely cheap relatively to the revenue they make running the business. This makes them a very attractive stock - the core of why SAAS looks great. Now let's assume the monopoly path. Google can win. I think they likely will win. But now they're going to spending... how many hundreds of billions constantly training new models? The cost of providing the service suddenly isn't small relative revenue they're getting. So even for them it looks awful for their valuation.

JumpCrisscross 5mo ago
> these companies I think the conclusion the market is rapidly and correctly reaching is we aren’t in an AI bubble, we’re in an OpenAI bubble. Google, Amazon and Anthropic look likely to see ROI on their capital investments because they’ve made them halfway reluctantly. Microsoft is up in the air. Not sure what Meta is doing. And with the benefit of hindsight, OpenAI used capex as a marketing strategy with investors (while Sam Altman materially lied about his compensation and somehow looped Paul Graham and Jessica Livingston, founder of The Information, into his racket).
- aurareturn 5mo ago
  Why would you say we're in an OpenAI bubble if Anthropic is valued more than OpenAI now?
  - JumpCrisscross 5mo ago
    > Why would you say we're in an OpenAI bubble if Anthropic is valued more than OpenAI now? One, it’s not. They’re roughly even. The folks quoting crypto tokens don’t know what they’re talking about. Two, Anthropic has more revenue and higher-quality growth. Three, OpenAI is levered in a way Anthropic and the tech giants are not. Nobody is immune from being overvalued. But what separates a bubble from normal overvaluation is leverage—the consequence of the valuation deflating isn’t just losses, it’s total loss because of debt or debt-like obligations. OpenAI has racked those up in its datacenter drive. Anthropic and the tech giants have been more disciplined. If OpenAI’s revenues dip, its valuation not only crashes, its commitments to various datacenter projects start strangling it.

Yizahi 5mo ago

OpenAI maybe won't, but someone else will. Maybe US government, maybe some fund etc. Too big to fail.