Make sure you've read the service terms[1] if you plan on building apps for speakers, cars, TVs or smart watches...
12.1 The following terms apply only to current and future Google Cloud Platform Machine Learning Services specifically listed in the "Google Cloud Platform Machine Learning Services Group" category on the Google Cloud Platform Services Summary page:
Customer will not, and will not allow third parties to: (i) use these Services to create, train, or improve (directly or indirectly) a similar or competing product or service or (ii) integrate these Services with any applications for any embedded devices such as cars, TVs, appliances, or speakers without Google's prior written permission. These Services can only be integrated with applications for the following personal computing devices: smartphones, tablets, laptops, and desktops
I have a hard time imagining who this wouldn't be a dealbreaker for. These terms also mean you can't use it for open source, and you can't use it if you don't know what the ultimate application is going to be. And you probably can't resell technology you create, because no one who buys it is going to want that restriction, either.
Don't forget huge retail chains. Infinitesimal improvements in their operations can leverage, especially when compounded, sizable improvements to profit margins.
For instance, as GigaMart, if your ML system finds that you are going to need widget-x in region y two weeks ahead of time, you can plan for that including the logistics and inventory.
Hospitals? I'm sure there are lots of things in the day-to-day operations that correlate with patient outcomes that currently go unnoticed.
Etc etc. It's not about creating a huge new invention, mostly it's about creating improvements to operations of current incumbents.
That's how my company would apply the platform to our work. My boss is there now, will be interesting to see what he find out vs what we're doing with our current IBM platform.
Health care. If you're running on-prem, it does a good job of integrating Kubernetes where it's not something my data scientists have to worry about. Also fairly easy to tie in our data mart and all of our databases - MS, Oracle, DB2, MongoDB, etc.
But why would you choose this solution with those terms rather than something without those terms, even if it is an in-house application if significant investment is put towards it that is an asset that your enterprise now has and those terms are now in your enterprise poisoning it. Actually I can think of the large enterprises I've worked for and Legal would probably not have allowed those terms.
No, because using it to get the prototype going is "using these Services to create (directly or indirectly)". Frankly, those terms look poisonous - you could be liable if any part of your service has origins in Google's platform. If you infringe on the GPL, you can remove the offending code. Here, you have no way to disentangle yourself from Google's trap.
I would imagine most prototypes would be made in a Jupyter notebook. I don't see any point in tying yourself to a platform intended for training/deploying models at scale if you're planning to switch off of it.
That's fascinating. When you have that many services, platforms, company divisions, etc you end up naturally competing with yourself, or enabling your competition.
To be fair, Amazon has a way of eventually becoming a direct competitor of many of the companies they initially present themselves as a middle man for.
12.1 The following terms apply only to current and future Google Cloud Platform Machine Learning Services specifically listed in the "Google Cloud Platform Machine Learning Services Group" category on the Google Cloud Platform Services Summary page:
Customer will not, and will not allow third parties to: (i) use these Services to create, train, or improve (directly or indirectly) a similar or competing product or service or (ii) integrate these Services with any applications for any embedded devices such as cars, TVs, appliances, or speakers without Google's prior written permission. These Services can only be integrated with applications for the following personal computing devices: smartphones, tablets, laptops, and desktops
[1] https://cloud.google.com/terms/service-terms#12-google-cloud...