ruinar50

Putting aside the detailed discussions on what exactly is "overfitting" for the moment, interested to hear more about the utility of micro-models in actual value delivery pipelines.

Does it matter if it's technically overfitting or not if everyone understands what their "one specific thing" is and how to "stitch" them together to get accurate results over a some real-world problem space? (conversely, people have to recognize the limitations.) Also, for "micro-model" as a word, appreciate having neutral vocabulary to talk about a model that doesn't solve the whole problem space, but does work for some of it. As opposed to "overfit model" or "incomplete model", which seem to cast negative connotations on a concept which is potentially useful when properly applied. (Though an eventual consensus on vocabulary likely necessary as the space matures...)

Later parts of the article introduced kick-off, iteration, and prototyping time as concrete benefits. Interested to see a follow-up addressing how micro-models fit into general problem-solving pipeline. What's next in terms of speeding up the assembly-line process? Where do they fit into data-oriented programming on the whole?