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Yesterday I encountered a "wrong-on-the-internet" rando professing his excitement for "using machine learning" in #3dprinting to throttle speeds in the right places to avoid quality loss.
While completely not worth engaging with, I feel like this is a useful example to understand why this idiocy is so infuriating...
@dalias Can you tell us more about why machine learning isn’t a good fit for this? Though I didn’t even know throttling speeds could possibly improve quality. Knowing little it sounds possible? But what tipped you off that it would not work?
@futurebird It's not that it couldn't work, but that we understand the physical reasons when/why going too fast can give poor results, and can just apply that rather than trying to coax a model into figuring out the same things without underlying models of thermal transfer, etc. It's really low hanging fruit.
@dalias @futurebird so many people chase “machine learning” when what they have is a basic control systems problem
@dalias @futurebird and the reason “machine learning” seems appealing is that it offers the appearance of being able to solve the problem without figuring out what control systems problem they have or even that they have a control systems problem, I suppose
@kevinriggle @dalias @futurebird interpolation functions are for when you can't solve the problem analytically.
LLMs are very big interpolation functions.