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subahini authored Dec 23, 2024
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# Art of Knowing When to Stop (Optimization)

Think of optimization like perfecting a recipe: A baker named Sam kept adjusting his bread recipe to make it better. At first, small changes improved the bread, but when he added more changes the quality and taste stayed the same but the recipe got more complicated. He realized that the best version wasn’t necessarily the most complex one—it was the one that balanced simplicity and quality.

The same idea applies to optimizing data and models. There’s a “sweet spot” between keeping things too basic and making them overly complex. True optimization means improving pipelines or models in ways that genuinely add value or maintain performance while avoiding unnecessary complications. The goal is to strike the right balance, just like Sam did with his bread
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