Yes, same feeling about ML really. Whether you are working with classic ML or LLMs, it's all about trial and error without predictable results, which just feels like sloppy (pun unintended) engineering by programmers' standards.
Yes, same feeling about ML really. Whether you are working with classic ML or LLMs, it's all about trial and error without predictable results, which just feels like sloppy (pun unintended) engineering by programmers' standards.
But this just doesn't correspond to reality. Most interesting algorithms in optimization etc. are metaheuristics as precise solutions are either proven to be impossible to get or we haven't found a solution yet. In the meantime, we get excellent results with "close-enough" solutions. Yes, the pedantic aspect of my soul may suffer, and we will always strive towards better and better solutions, but I guess we accepted already over a century ago that approximate solutions are extremely valuable.