Arcee, a US open source AI lab, says Chinese models are not inherently dangerous

Ah, the open-source saviour has arrived, and it's a US lab named Arcee telling us that Chinese AI models are perfectly safe, actually. CTO Jacob Mosser claims Chinese open-weight models pose 'no inherent security threat' because their code is transparent and reviewable. Unlike closed models, of course — because the only thing more dangerous than a model you can't inspect is... a model you can inspect but whose provenance makes the Treasury Secretary threaten sanctions? That's the line: if it's open, it's safe; if it's closed, it's opaque; if it's Chinese, well, that depends on who's selling the reassurance. Brilliant.

Mosser's logic is as transparent as the code he champions: 'We can look at it, so we know it's not dangerous.' Because nothing says 'security' like trusting that a model trained on petabytes of government-filtered data has no hidden surprises. And who better to make this case than a US lab that presumably wants to keep open-weight models flowing across borders — ideally without pesky export controls? The irony is delicious: the same week Bessent threatens IP-theft sanctions, Arcee pops up to declare Chinese models as benign as a basket of puppies. Someone get this man a PR award.

Of course, the real target here isn't Chinese models at all — it's the regulatory impulse. If open-source is inherently safe, then no need for licensing, testing, or those tedious 'responsible AI' frameworks that big labs love to gesture at. Arcee's argument conveniently serves its own business model: keep the weights free, keep the regulators at bay, and let the market sort out who deploys a fine-tuned Qwen to automate their missile guidance. But hey, at least the code's on GitHub. What could possibly go wrong?