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by jingpostmedia 2 hours ago
The framing that Chinese labs open-source because they're behind assumes it's purely a competitive tactic. But there's a structural dimension: DeepSeek operates under a completely different funding model than US labs. They're backed by a quantitative hedge fund that views AI as infrastructure, not as a product to monetize directly. The ROI for them comes from trading alpha, not API revenue.

Chinese AI companies also face a domestic market where open-source distribution is often the only way to reach enterprise clients who won't pay SaaS premiums. The business logic aligns with openness in a way that US labs' VC-funded models don't.
3 comments
NitpickLawyer 1 hour ago
> They're backed by a quantitative hedge fund that views AI as infrastructure, not as a product to monetize directly. The ROI for them comes from trading alpha, not API revenue.

That used to be true, but now they've raised ~7B$, so we'll see how / if that changes.

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disgruntledphd2 1 hour ago
Yeah, they were in a tough position though. All their competitors were offering equity and they didn't.
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try-working 34 minutes ago
Nope. It is purely a marketing and distribution strategy. Without open sourcing their models, their businesses would have never gotten off the ground. I've written about this here: https://try.works/writing-1#why-chinese-ai-labs-went-open-an...
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yogthos 51 minutes ago
Also, we’re seeing a classic commoditization spiral with open models rapidly closing the gap and driving prices towards the marginal cost of inference. The reality is that models themselves are general commodities and there's just not enough difference between them. A company can get ahead of others by a few months, but then the rest quickly close the gap. It's a really low margin business because there's no way to differentiate yourself.

Chinese companies understand this and they're treating models as shared infrastructure akin to Linux. The money is going to be in customization niches. Companies will charge to tune models for specific use cases and charge support for that. There's also going to be money at the bottom for hardware vendors making chips and memory. But the middle tier of generic LLMs is seeing involution where there's relentless competition driving profits towards the bottom.

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