Not that it makes it any better, but they only took down the episode in Saudi Arabia, not globally. The headline makes it sound like they took down the episode altogether.
This is why Google struggles to compete with Amazon and Microsoft in the enterprise cloud space - the trust that these services will be maintained and legacy support provided just isn't there for large enterprise clients.
Likely it'll be a transition technology for businesses still using phone appointments as their primary API, and eventually it'll ease the path for more direct integration.
1. No oil changes.
2. Fewer moving parts, fewer repairs, longer life.
3. Instant acceleration.
4. Zero emissions.
5. Ability to be fully powered by renewable energy.
Takes little time to set run Tensorflow from a docker image, or learn from Jupyter notebooks, etc... with fully open source projects where you can consult the source code and see how an algorithm is implemented.
This is exactly the problem -- what you're describing is not easy for anyone outside of tech to do. If you want to, say, run a simple text classification task and have thousands of labels, this is way overkill. Machine learning has the opportunity to become a common place utility for automating repetitive tasks, and the barrier to entry does not need to be learning Tensorflow, Docker, and Jupyter.
This is awesome! I've been waiting for someone to release an Excel-type ML product to make machine learning more accessible. This looks right up that alley, and will probably "democratize" access to ML in a number of fields that tend to be less coding-savvy.