A recent competition aims to uncover tasks where larger models perform worse, challenging the prevailing notion that scaling always leads to better outcomes. As models grow, they may increasingly rely on their training data, potentially leading to deeper levels of misinformation. The results from this initiative could provide valuable insights into the limitations of scaling in AI.
