One thing I’ve been wondering about lately is whether the AI community overestimates the importance of having the “best” model. If an AI product offered a genuinely new capability or workflow that saved you significant time, would you use it even if its underlying model wasn’t as strong as the current leaders? For example, imagine Product A uses the best available model and consistently produces better outputs. Product B uses a weaker model but introduces a completely new way of getting work done that no other AI product offers. Which would you choose? My intuition is that users ultimately care more about outcomes than benchmark performance, but I’m curious whether others agree or disagree. submitted by /u/No_Anxiety_1613
Originally posted by u/No_Anxiety_1613 on r/ArtificialInteligence
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