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I'm late to the comment party, but: this is classic "commoditize your complement". This guy would have you believe that Pytorch has Solved the entire, vast fie

I'm late to the comment party, but: this is classic "commoditize your complement". This guy would have you believe that Pytorch has Solved the entire, vast field of data analysis as inherited from Newton, de Moivre, Laplace, Bayes, Fisher, Neyman, Pearson, Wald, Savage, Jaynes, Breiman, Pearl. This is a lot like saying that photography has Solved art, and now we need people who can climb ladders and glue the posters on them big billboards. It would be delusional if it didn't have a self-interested angle. What, we with math degrees are fully confident that the plumbing problem is easier to commoditize than the problem of making sense of data.

nelsondev 6y ago
It’s about diminishing returns. E.g. getting a model from 0% accuracy to 70% accuracy might be a couple Pytorch library calls that any dummy who watched Andrew Ng’s course can do. But getting that same model from 70% to 75% accuracy might be deeply mathematical and require the latest and greatest mathmeticians, statisticians. But in this hypothetical example, an engineer who stands up the 70% model and keeps it running 99.9% of the time, with high uptime; is more valuable to the bottom line of the business than the 75% accuracy model hacked together with scripts with 50% uptime.