I find this article a bit funny, and see it mostly as hype. I worked very revently on a large internal face detection service for a legal and compliance application at a large US company. Being pragmatic engineers, the first thing we did was to pilot test Rekognition against an in-house prototype built by modifying some open source deep learning approaches. Rekognition performed so poorly compared to our prototype (w…
As it get customers, it will likely get more and more resources thrown at it and get better and better. Even if the tech may not be useful right now, it probably will be in 5 years, and unless something is done now, another large slice of the little bit of privacy that remains will be gone.
Companies would end up paying huge premia to Amazon essentially to have Amazon build in-house teams that would be equivalent, only much more expensive, than the companies own in-house team just building an in-house solution.
With some forms of consulting this can make sense, because the consulting services are temporary and should set the company in a position such that for the long run, the company can maintain the solution cost-effectively.
But for something like face detection, assuming it's a pivotal service you'll need on an on-going basis, this would become the worst sort of vendor lock-in imaginable, combined with the fact that if you don't appear to be creating growth for Amazon, you're liable to be deprioritized at any point, and at the mercy of Amazon's choices regarding when and how to address your bespoke need.
For these specialized machine learning services it doesn't fit the same kind of commodity model that AWS infrastructure uses, though that's currently how Amazon is pursuing it.
Don't get me wrong, Amazon is very good at making money and convincing nervous management to buy their brand. I suspect they will find ways to sell these services despite the services not being cost-effective or customizeable for bespoke customer situations.
But when I point out that Amazon's machine learning services don't offer cost-effective performance, it's very different from a "just throw more devs at it" kind of problem, fundamentally.