I hope that we will soon see open-source versions of these functionalities, because I don't like the idea of using an external service for reasons including privacy, reliability and latency.
The problem in most cases is a lack of openly available training data. No open source library helps you with that. It's the data itself that needs to be open-sourced. Companies like Google and Amazon naturally have a huge amount of relevant data but they aren't exactly eager to share that data with the world (which by the way would have huge privacy implications as well).
AWS wins not because they have created an impenetrable black box, but because the economics of reverse engineering (and maintaining) are not cost effective for the majority of users.
(For applications where the problem you're trying to solve is relatively similar to the ones Apple/Google/Amazon are trying to solve - conversational AI)
At best you can partly do this, and even that is debatable.
Here's a simple example: say Google builds a linear regression for the incremental likelihood to click a social post based on the distance of poster from you in a social network. By merely revealing the (single) coefficient in this model, they've revealed something about the underlying data set that they may not have intended.
It gets exponentially (I use this term deliberately) more difficult with multivariate nonlinear models. I have no doubt that substantial information about a data set could be reverse engineered from complex ML models, even if we don't yet know how. But even in the case of basic multivariate regression, the model directly encodes both the mean values and the covariances of all the variables. So that's a fair amount of disclosure already.
In some sense all models are (usually lossy) data compression, and it's just a matter of understanding the compression logic to go backwards from facts about the model to facts about the source data.
Would it be possible to run a service like this in a truly distributed fashion, SETI@Home and Folding@Home style?
How is permission provided? I mean I don't foresee people calling up Amazon and saying hey dataset 2001-G yeah you have permission to use that to train on!
So I guess I would expect Amazon to ask you when you submit your training data, and how do they ask you. Is it opt-in or opt-out and so forth. I would expect them to make it easy to share the data with them, and difficult to opt out.