American AI is locked down and proprietary. It's losing
The article argues that the US strategy of closed, proprietary AI models is failing compared to China's open-weights approach. It suggests that the real value in AI lies in enterprise integration rather than the models themselves, which are easily interchangeable.
Why it matters
This perspective challenges the prevailing US tech policy of export controls and proprietary development, suggesting it may hinder long-term innovation and economic competitiveness.
China's open-weights AI strategy is winning: its companies are taking the lead. America's closed-first, locked-down strategy is doomed to failure - and it could take the US economy down with it.
Link: China delivers a one-two punch to America’s AI dominance, by Robert Hart in The Verge
AI models, as a product in themselves, have very little moat beyond what amounts to brand loyalty and superficial switching costs. Instead, the moat is in the enterprise services that sit around them: the deals and contracts, connectivity with enterprise systems, and quality of life features in an enterprise context.
If we consider the models themselves, it’s easy to switch between them: someone could be using ChatGPT today and Claude tomorrow, with very little impact on their workflows. This is particularly true in the engineering world, where models are accessed via API: you can swap out the API and use the same prompt.
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in