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.

▲ preommr 7 hours ago | parent | next [-]

> 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 2 hours ago \| parent [-]
		> 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?

▲ atwrk 7 hours ago | parent | prev | next [-]

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 7 hours ago | parent [-]

There is clearly a moat - or Claude Code wouldn't be generating over $10b in ARR every single month.

▲ piker 7 hours ago | parent | next [-]

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 7 hours ago | parent [-]

  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 7 hours ago | parent | next [-]

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.

▲

atwrk 3 hours ago | parent | prev | next [-]

But all the open-weight players make money right now. Google (Gemma), Alibaba (Qwen), z.ai (GLM), minimax.io (Minimax) - they all have hosted offers and sometimes closed-weight max versions.

And the fact that the open-weight as well as cheaper tier 2 offers exist both place a ceiling on the prices the SOTA companies can demand - and as far as we know current prices don't even fully pay for inference alone already, at least not for OpenAI.

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aurareturn 2 hours ago | parent [-]

Are they profitable on their LLM training?

It's not clear. Z.ai is definitely not profitable.

	▲	atwrk an hour ago \| parent [-]
		To my knowledge none of the players is even profitable on inference, though Google probably is, considering the continuous release of papers around kv cache optimizations, mtp etc.

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thepasch 6 hours ago | parent | prev [-]

> Open-weight models aren't going to be free forever.

The ones that are already released are, and they're already very good for most purposes and can be fine-tuned indefinitely, includin months or years down the line when processes have been optimized and things aren't as compute-heavy as they are now.

▲ aswegs8 7 hours ago | parent | prev [-]

That's definitely a moat. Being able to generate ARR every month.

	▲	atwrk 3 hours ago \| parent \| next [-]
		No, a moat would be a feature preventing the competition from competing successfully. Classically things like patents, for example, or process knowledge like ASML currently has for EUV lithography, or the network effects of a social media platform, or access to data no one else has access to. ARR is not a moat at all, because the revenue of OpenAI is not preventing Alibaba, z.ai and so on from generating revenue as well. The opposite is true, actually, because the first mover prepared the market (e.g. user education about application possibilities, creating the willingness to pay for the service in the first place) for the second movers. People here write about switching from Claude to Codex mid-workday - that is the absolute opposite of a moat. The only companies that have a chance of not losing everything in this market are those with established non-AI revenue streams, like Google or Alibaba, or those focusing on profitability in niche markets instead of participating in the SOTA death race.
	▲	rowanG077 5 hours ago \| parent \| prev [-]
		No it's not. There is a even a wikipedia page for it: https://en.wikipedia.org/wiki/Economic_moat A moat is protection so you can keep your ARR up or increase it over years. Arguably only google have a moat with their TPUs. NVidia has a moat. But the others who just train some models on NVidia hardware have no moat.

▲ JumpCrisscross 4 hours ago | parent | prev | next [-]

> 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.

▲ dgellow 7 hours ago | parent | prev | next [-]

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 2 hours ago \| parent [-]
		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.

▲ orwin 7 hours ago | parent | prev | next [-]

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.

▲ libertine 7 hours ago | parent | prev | next [-]

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 7 hours ago | parent [-]

I wrote about how I think OpenAI is going to kill it in advertisements here: 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 7 hours ago | parent | next [-]

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 6 hours ago \| parent [-]
		`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.

▲ machiaweliczny 4 hours ago | parent | prev | next [-]

They would compete with Meta then which already does something like this but has mature AD tech

▲ libertine 7 hours ago | parent | prev [-]

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.

▲ jqpabc123 7 hours ago | parent | prev [-]

https://www.reuters.com/business/openai-makes-five-year-plan...

	▲	aurareturn 7 hours ago \| parent [-]
		This is a 5 year pledge - likely based on hitting revenue goals and not just using investor money.