This is a great counterweight to the usual “China is just more open-source by design” story.
To me it doesn’t contradict the “surrender the asset, take the layer” logic — it explains why that logic works in China. If companies don’t trust the cloud, the model becomes less of the prize. The real value moves to private deployment, data, distribution, and infrastructure around it.I wrote about this from the operating-layer angle in this week’s Inside China AI — so I found this a very useful complement to that argument.https://insidechinaai.substack.com/p/chinas-ai-recap-this-month-surrender
The trust paradox you're mapping is really a *centralization* paradox, closed systems buy certainty at the cost of resilience, while distributed ones distribute the burden of trust across verification rather than authority. China's position here is instructive: the same infrastructural logic that makes sense for a centralized grid (speed, control) becomes a liability when the system itself is the point of failure. Worth asking whether the next wave of AI adoption follows power grids (still centralized) or forest networks (decentralized, antifragile) and what changes in governance when you can't unplug from a single operator.
I figured at least part of it was that export-control-driven compute constraints made the closed frontier AI model race less attractive, so Chinese firms pursued an asymmetric go-to-market strategy.
There is a trade off here between the two approaches of the U.S. and China. It will be interesting to see which model works better at facilitating innovation. It seems the U.S. has the upper hand right now.
This is a great counterweight to the usual “China is just more open-source by design” story.
To me it doesn’t contradict the “surrender the asset, take the layer” logic — it explains why that logic works in China. If companies don’t trust the cloud, the model becomes less of the prize. The real value moves to private deployment, data, distribution, and infrastructure around it.I wrote about this from the operating-layer angle in this week’s Inside China AI — so I found this a very useful complement to that argument.https://insidechinaai.substack.com/p/chinas-ai-recap-this-month-surrender
Super article! Well researched and revealing, thanks
The trust paradox you're mapping is really a *centralization* paradox, closed systems buy certainty at the cost of resilience, while distributed ones distribute the burden of trust across verification rather than authority. China's position here is instructive: the same infrastructural logic that makes sense for a centralized grid (speed, control) becomes a liability when the system itself is the point of failure. Worth asking whether the next wave of AI adoption follows power grids (still centralized) or forest networks (decentralized, antifragile) and what changes in governance when you can't unplug from a single operator.
I figured at least part of it was that export-control-driven compute constraints made the closed frontier AI model race less attractive, so Chinese firms pursued an asymmetric go-to-market strategy.
There is a trade off here between the two approaches of the U.S. and China. It will be interesting to see which model works better at facilitating innovation. It seems the U.S. has the upper hand right now.
Is another way of putting this that US AI exploited the trust in cloud based services, monopolised data and privatised AI?