Comment by gruez
2 days ago
You could ask the same about how z.ai, moonshot ai, minimax, and alibaba are going to continue training and releasing models for free.
2 days ago
You could ask the same about how z.ai, moonshot ai, minimax, and alibaba are going to continue training and releasing models for free.
1. they still have revenue though. it might not enough to cover all the r&d but it is surely enough to cover the hardware cost.
2. people tend to ignore this, but the salary budget of a US frontier lab and chinese frontier lab is nowhere comparable, the first can easily outdone the later by 100x.
3. us labs, like other US style startups, always throw ton of money to capture the market. I don't see the chinese company doing the same scheme at all.
so, surely chinese AI providers also lost money making new models, but they are not spending nearly as much as US ones.
>1. they still have revenue though. it might not enough to cover all the r&d but it is surely enough to cover the hardware cost.
>2. people tend to ignore this, but the salary budget of a US frontier lab and chinese frontier lab is nowhere comparable, the first can easily outdone the later by 100x.
Both arguments make it seem like there's a double standard for american vs chinese AI companies, where american labs are held up to strict standards for profitability, but chinese labs get a pass because [insert handwaving about how some aspect of chinese labs is different]. Let's do apples to apples comparisons here, what are both sides' run rates and revenue growth prospects?
>3. us labs, like other US style startups, always throw ton of money to capture the market. I don't see the chinese company doing the same scheme at all.
Right, instead they're releasing their models for free so competitors can undercut them on inference. American labs' prospect of "there are open models 90% as good but cost less" might seem bad, but chinese labs' prospect of "there are companies offering the exact same models but aren't on the hook for r&d spend" seems even worse.
> there's a double standard for american vs chinese AI companies
Not really, in a way. Things just cost far more in the US than in China; has pretty much always been the case, far back as I can recall. The Chinese state heavily invests in anything it wants to succeed at, and it has the resources to throw. Cost of living is generally wildly lower in China, along with salaries (although it's also pretty location- and role-dependent).
Overall I'd say labs are far cheaper to run in China than in the US, in more than just from the finances angle.
Literally nothing is known about how these companies are financed. The usual story is that Moonshot was chosen when 'Mythos' occasioned a huge state crisis. China is the ascended masters of insane amounts of capital poured into whatever the state takes into its head next.
By charging $$$ like they do now and having a non terminal business model.
PRC AI have lower opex and capex, i.e. export controls means they couldn't be trillions in the hole on inflated hardware in the first place. They only need to extract a few 10s of billions from domestic market have a healthy runway. If investors/gov wants to throw in a few billion to treat as utility, whatever, it's still rounding error.
Dirt cheap Chinese solar is a competitive advantage just sitting there waiting, but instead the US is trying to revive coal, restart a grossly ineffective small scale nuclear system with immensely bad fuel utilization, and spending billions to cancel renewable projects that were already approved. I'm so tired of these insurrectionist dog traitors to this country I love.
>Dirt cheap Chinese solar is a competitive advantage just sitting there waiting, but instead the US is trying to revive coal,
This seems like a double standard given that china is still building coal.
just like there were mistrals, coheres, llamas, etc, there will be new deepseeks and moonshots if those ever flame out (worst case, given out at cost by google, meta, alibaba or etc)
OpenAI and Anthropic are already in a ~200bil hole from previous model iterations and are committing to trillions of additional spending
OpenAI spent more TBPN than kimi spent on training K3
They are owned by the state, so the economics are a bit different.
>They are owned by the state
They are by all accounts, not. Z.ai for instance is a public company according to wikipedia. Moonshot AI is private but all their investors are private companies. Alibaba, as we all know, is a massive publicly traded tech conglomerate.
Moreover even if we take the more charitable view that they're controlled by the CCP, and therefore will continue releasing models for free, that seems as questionable as the prospect that private investors will continue shoveling money into anthropic/openai.
China has "classroom game capitalism", where companies can play the game, but the teacher still has uncontested, absolute, unilateral control in everything and anything. All the parameters of the game are managed by the teacher, and the teacher is the one who creates the foundations for the direction they want the game to move in.
Don't forget, Jack Ma of "publicly owned" Alibaba, had to go into classroom time out after seemingly forgetting that its classroom capitalism and not real world capitalism.
3 replies →
The core employees of z.ai are billionaires, because of the equity given to them in the past, which in their system is not antecedently evaluated. Much of the past annual expenditure of OpenAI has been the same, handing out equity - but because of the different legal system it is given an evaluation and listed as expenditure. Meanwhile the expenditure on compute for training and inference are apples and oranges again as the state is all over this with moonshot and z.ai and so on .
By charging $$$ like they do now and having a non terminal business model. PRC AI have lower opex and capex, i.e. export controls means they couldn't be trillions in the hole on inflated hardware in the first place. They only need to extract a few 10s of billions from domestic market have a healthy runway. If investors/gov wants to throw in a few billion to treat as utility, whatever, it's still rounding error.
At a fraction of the cost.
Shoveling 70% less money into a money pit is still shoveling money into a money pit. Not to mention that at least openai/anthropic has better prospects of making back the money because their models are proprietary, and won't be cannibalized by other companies serving the exact same models.
Neither of the two is designed or cares to ever be profitable or make any money back.
Those are Musk-like businesses, on steroids.
Not even Tesla has been profitable compared to the capital raised and the debt issued.