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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 t

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 6mo 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 6mo ago
  This is a 5 year pledge - likely based on hitting revenue goals and not just using investor money.
libertine 6mo 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 6mo 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 6mo 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.
    - aurareturn 6mo 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. So is SOTA LLM training. There is OpenAI and Anthropic and there is everyone else. Gemini has fallen behind a bit as well. There were tens of chip manufacturers in the 80s and 90s. Most of them have been absorbed or went backrupt. Just like SOTA LLM training now. Today, TSMC is a monopoly for SOTA nodes. The only reason Intel can survive is due to geopoltics.
  - libertine 6mo ago
    I understand your argument, but I think you might be overestimating the intent of the users when they're using chatgpt. The ones killing on ads are Google, Meta, and Amazon. I just don't see how ChatGPT will gobble those market shares - ads are increasingly tied to sales attribution, and it would require a complete shift of the market for ChatGPT to take over the role of those 3 players. People will still try to look for content around the products they buy, or will shop for prices, or will look for feedback from other users of the product.
atwrk 6mo ago
How can this become a monopoly/duopoly? There is no moat, the Chinese providers will continue to hunt the market leader at 10% of the price, there is no network effect (OpenAI's Sora was a play in that direction and failed). I'm constantly amazed how this AGI/monopoly narrative can be kept up so long in the West, it just doesn't make sense (unless the state creates said monopoly by forbidding competition).
- aurareturn 6mo ago
  [flagged]
  - piker 6mo ago
    That's not what "moat" means. Claude Code has a castle. A "moat" is meant to protect the castle from invaders. It would be things like high switching costs, proprietary formats, network effects, etc. that aren't there. In other comments people mention the "flywheel" of data and money feeding training, but there's a view that at some point the baseline open-weight models are "good enough" that the money will dry up.
    - aurareturn 6mo ago
      baseline open-weight models are "good enough" that the money will dry up. I take a different view. Open-weight models aren't going to be free forever. At some point, open weight model labs will also have to make money. My guess is that the industry will consolidate. The winners will absorb the losers and focus on generating revenue. Therefore, there will be a growing gap between open and free models and the proprietary SOTA models.
      - vidarh 6mo ago
        What the open-weight labs have shown is that you can go from nothing to competing with SOTA models at a tiny fraction of the cost for the SOTA models. If there is consolidation by absorption, that derisks attempting to challenge the SOTA providers, and so they will keep facing attempts.
preommr 6mo ago
> I can see that there are only 3 companies competing for the duopoly or monopoly realistically: OpenAI, Anthropic, and Google. I could see people saying this in 2022, but now? No chance. Chinese models keep demonstrating that SOTA can be approximated for a fraction of the cost. The innovation out of these companies keep showing diminishing returns, with a greater emphasis on the tooling and application layer. Having the right workflow with the right data is more important than having the right model. We could freeze AI now, and I'd bet good money that the current state of things is good enough to - not be first - but competitive for the next few years. Even if we do end up with a oligopoly situaiton, it'll be less like Microsoft in the 90s and more like Microsoft now where they just give out windows for free, have support for WSL and the focus is on cloud services rather than their OS.
- jitler 6mo ago
  > Chinese models keep demonstrating that SOTA can be approximated for a fraction of the cost. Wow, sounds like a threat to nation security. Those Silicon Valley companies shills start donating to select donation campaigns with hope to ban Chinese LLM models. Can you imagine? Your children being exposed to the propaganda that these LLMs will be inevitably tainted to spew?
orwin 6mo ago
Yeah, no, i disagree. Frontier models were almost untouchable 6 month ago, but now i can get 90% of Opus 4.5 with any chineese model, or even with Mistral. The only thing i'm missing is the chain of thought that help me understand the "how" and "why" when AI fails at its task. For the "general purpose" AI, it's even worse, any free model i can run on my Intel Arc (yes, sorry, it was discounted an very cheap) i get like 80% of a frontier model, at virtually no cost, and i suppose Deepseek/Mistral are like 95% there.
dgellow 6mo ago
I think the performance of models is only one aspect. You have to take in account the cash flow, how much spending commitment the different actors have, debt, etc. OpenAI has taken some very risky commitments, of they don’t get the revenue to cover their expenses in the next few years their situation will be pretty bad
- aurareturn 6mo ago
  I wouldn't worry about their commitments. Their growth is insane if it's similar to Anthropic's revenue numbers. Their IPO might also raise a few hundred billion.
JumpCrisscross 6mo ago
> can see that there are only 3 companies competing for the duopoly or monopoly realistically: OpenAI, Anthropic, and Google Amazon and Microsoft have a seat at the table by virtue of their cloud businesses.

jqpabc123 6mo 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 6mo ago
This is a 5 year pledge - likely based on hitting revenue goals and not just using investor money.

libertine 6mo 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 6mo 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 6mo 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.
  - aurareturn 6mo 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. So is SOTA LLM training. There is OpenAI and Anthropic and there is everyone else. Gemini has fallen behind a bit as well. There were tens of chip manufacturers in the 80s and 90s. Most of them have been absorbed or went backrupt. Just like SOTA LLM training now. Today, TSMC is a monopoly for SOTA nodes. The only reason Intel can survive is due to geopoltics.
- libertine 6mo ago
  I understand your argument, but I think you might be overestimating the intent of the users when they're using chatgpt. The ones killing on ads are Google, Meta, and Amazon. I just don't see how ChatGPT will gobble those market shares - ads are increasingly tied to sales attribution, and it would require a complete shift of the market for ChatGPT to take over the role of those 3 players. People will still try to look for content around the products they buy, or will shop for prices, or will look for feedback from other users of the product.

atwrk 6mo ago

How can this become a monopoly/duopoly? There is no moat, the Chinese providers will continue to hunt the market leader at 10% of the price, there is no network effect (OpenAI's Sora was a play in that direction and failed). I'm constantly amazed how this AGI/monopoly narrative can be kept up so long in the West, it just doesn't make sense (unless the state creates said monopoly by forbidding competition).

aurareturn 6mo ago
[flagged]
- piker 6mo ago
  That's not what "moat" means. Claude Code has a castle. A "moat" is meant to protect the castle from invaders. It would be things like high switching costs, proprietary formats, network effects, etc. that aren't there. In other comments people mention the "flywheel" of data and money feeding training, but there's a view that at some point the baseline open-weight models are "good enough" that the money will dry up.
  - aurareturn 6mo ago
    baseline open-weight models are "good enough" that the money will dry up. I take a different view. Open-weight models aren't going to be free forever. At some point, open weight model labs will also have to make money. My guess is that the industry will consolidate. The winners will absorb the losers and focus on generating revenue. Therefore, there will be a growing gap between open and free models and the proprietary SOTA models.
    - vidarh 6mo ago
      What the open-weight labs have shown is that you can go from nothing to competing with SOTA models at a tiny fraction of the cost for the SOTA models. If there is consolidation by absorption, that derisks attempting to challenge the SOTA providers, and so they will keep facing attempts.

preommr 6mo ago

> I can see that there are only 3 companies competing for the duopoly or monopoly realistically: OpenAI, Anthropic, and Google. I could see people saying this in 2022, but now? No chance. Chinese models keep demonstrating that SOTA can be approximated for a fraction of the cost. The innovation out of these companies keep showing diminishing returns, with a greater emphasis on the tooling and application layer. Having the right workflow with the right data is more important than having the right model. We could freeze AI now, and I'd bet good money that the current state of things is good enough to - not be first - but competitive for the next few years. Even if we do end up with a oligopoly situaiton, it'll be less like Microsoft in the 90s and more like Microsoft now where they just give out windows for free, have support for WSL and the focus is on cloud services rather than their OS.

jitler 6mo ago
> Chinese models keep demonstrating that SOTA can be approximated for a fraction of the cost. Wow, sounds like a threat to nation security. Those Silicon Valley companies shills start donating to select donation campaigns with hope to ban Chinese LLM models. Can you imagine? Your children being exposed to the propaganda that these LLMs will be inevitably tainted to spew?

orwin 6mo ago

Yeah, no, i disagree. Frontier models were almost untouchable 6 month ago, but now i can get 90% of Opus 4.5 with any chineese model, or even with Mistral. The only thing i'm missing is the chain of thought that help me understand the "how" and "why" when AI fails at its task. For the "general purpose" AI, it's even worse, any free model i can run on my Intel Arc (yes, sorry, it was discounted an very cheap) i get like 80% of a frontier model, at virtually no cost, and i suppose Deepseek/Mistral are like 95% there.

dgellow 6mo ago

I think the performance of models is only one aspect. You have to take in account the cash flow, how much spending commitment the different actors have, debt, etc. OpenAI has taken some very risky commitments, of they don’t get the revenue to cover their expenses in the next few years their situation will be pretty bad

aurareturn 6mo ago
I wouldn't worry about their commitments. Their growth is insane if it's similar to Anthropic's revenue numbers. Their IPO might also raise a few hundred billion.

JumpCrisscross 6mo ago

> can see that there are only 3 companies competing for the duopoly or monopoly realistically: OpenAI, Anthropic, and Google Amazon and Microsoft have a seat at the table by virtue of their cloud businesses.