
Machine Learning: The High-Interest Credit Card of Technical Debt [pdf] - teej
https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43146.pdf
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Pica_soO
Is there a paper comparing the cost of technical debt, as created by using a
machine learning solution- versus the permanent rising cost of having a over-
engineered, abstraction heavy enterprise solution - that automatically reduces
the people who can work effective on it?

Maybe it is just me, but this paper reads from the paragraph "System-level
Spaghetti" on-wards like written by one of those java-consultants for 1000 $ a
hour.

Someone - who is desperately trying to sell this software-engineering toy-
toolbox, which has been replaced with a database, lots of graphic-cards
server-racks, some admittelty tangled clot statistics plus library glue-code.

There is some merits to the point, that a NN should be trained on a well
defined problem, and that there is a need for a higher system logic bundling
the specialist-abilitys of the NNs, also having a eye on some key-output-
parameters drift within boundaries.

But that sounds a lot like - you need good "craftsmanship" to train a NN.
Which is true- true for nearly all things.

