Are better models better?

Benedict Evans raises a crucial question about the relentless pursuit of "better" AI models. He astutely points out that many questions don't require nuanced or improved answers, but rather simply correct ones. Current AI models, while excelling at generating human-like text, often struggle with factual accuracy and definitive answers. This challenges the very definition of "better" in the context of AI. The article prompts us to reconsider our expectations of computers and how we evaluate the progress of AI, particularly in areas where correctness is paramount over creativity or approximation. It forces a discussion on whether the focus should shift from simply improving models to ensuring reliability and accuracy.

• •'Better' AI doesn't always mean more accurate AI.
• •We need to redefine what we expect from AI in different contexts.
• •Accuracy and reliability should be prioritized in certain applications.