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> Case in point is Uber with models per city/ time of day (with 1000's of models in production).

That is a good case-in-point, because one of the arguments in the article is that AI is expensive.

At what point does 40,000 compute-hours and a few million dollars spent on hundreds of city models become a better use of time and money than an afternoon noodling with ARIMA or some Fourier analysis on a $5,000 workstation?

Perhaps -- perhaps -- at Uber's scale, squeaking out a tenth of a percent is worth the time and money. But the rest of us schmoes can do pretty well with an SQL query, some R or Python or Julia and a generous dollop of good old-fashioned all-American hubris.



I absolutely agree. I did not say 1000's of deep learning models.

There should always be a tradeoff between performance and cost.

But it is much better to give customer the option, instead of forcing her to the said SASS architecture.




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