This is the TOS specifically for two of the managed services - it says so right in the link "Google Cloud Machine Learning Group and Google Cloud Machine Learning Engine"

These specific ML-as-a-service products are pretty easy to plug into and resell to third parties, which is why the wording is so restrictive in the TOS.

Many of Google Clouds other ML products, which typically are more customizeable and powerful, do not have these restrictions. The way your comment is worded makes it seem like this restriction is on all of Google Clouds ML products, but it's not.

I don’t understand these restrictions. Why is reselling bad? I would think people would still prefer first party services and even if they don’t you still get utilization in any case. Sure, there can be some outlier bad cases but these kind of restrictions can be a complete turnoff for enterprise users who just don’t want to take any legal risk of breaking TOS.

It might have not been clear from my comment, but I was specifically referring to those ML as a service. The TPUs seem to fall under GCP which has a less restrictive ToS.

I do understand they don’t want to make it too easy to resell their research. But having access to all your source code, training data and documentation is a bit extreme. Why can’t they just tell you to stop selling your product?

From the link:

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

Those services are (from https://cloud.google.com/terms/services):

  - Cloud AutoML
  - Cloud Text-to-Speech
  - Dialogflow Enterprise Edition
  - Google Cloud Data Labeling
  - Google Cloud Natural Language
  - Google Cloud Speech-to-Text
  - Google Cloud Video Intelligence
  - Google Cloud Vision

Right - that is the Google Cloud Machine Learning Group, which are managed ML-as-a-service products.

If you read the list, you will see they're highly specialized, out of the box ML products and super easy to resell, hence the TOS restrictions.

Sincerely thank you for the public service of posting that. You’ve probably saved a lot of folks on here from a big mistake.

I had no idea GCP had such terms. I had been considering alternative cloud hosting for a ML SaaS but will definitely not consider GCP.

You'll probably find that all ML SaaS EULAs look about the same.

That is only in the terms for the managed offerings though, which I'd assume, is not what you'd be looking into.

It's not for GCP but the ML products.

.. We will force you to admit that we OWN machine learning for all consumer use cases and will happily sue you just for renting our servers, or force you to turn over your Intellectual Property Rights to us. Thanks.

> These terms will survive termination or expiration of the Agreement.

Is this legal? Forgive me because I actually don't know if it could be?

It's standard, even though it's a bit of a weird concept when you think about it: https://www.adamsdrafting.com/survival/

A common case is an employment contract that has an NDA or non-compete or non-poaching section survive the employment itself. I can't say, "I quit, therefore my employment contract doesn't apply any more, therefore I'm going to push all the company secrets to GitHub and you can't stop me."

I guess that if someone doesn't think the terms are legal, they are fully entitled to take it to court against an army of Google lawyers...

Does someone knows of some instance of ToS from a big company being challenged in court?

IANAL, but I seen many agreements with the language like this.

To be fair, "Warranty Void if Removed" stickers are common but in many cases have no legal standing both in the US, EU, etc. They're just a common "boilerplate" kinda item.

>(ii) integrate these Services with any applications for any embedded devices such as cars, TVs, appliances, or speakers without Google's prior written permission.

Genuinely curious about the restriction regarding embedded devices.

If there's a mishap, it is the responsibility of the owning company, certainly not Google.

So what gives? Why would they do this?

If they have patents for technology applied to those items, they would lose the patents if the didn’t enforce them. I’m sure they could arrange a license if you had a use case, and that may be free. Again, if they demonstrate they don’t enforce their IP (which is possibly incredibly valuable) at least in writing they could lose all rights to enforce their patent. I’m no IP lawyer but I paid one a bunch of money once.

This isn’t true. Are you thinking of trademarks?

Eh, you’re right, I was confusing it with trademarks. I’ll dust off that pitchfork, there isn’t any good excuse for them naming the industries they would like to own and barring their customers from competing with them.

This doesn't seem plausible. They have tens of thousands of patents on all sorts of stuff, and people "infringe" on them all day long with no repercussions. Some of those patents will probably be violated when I click the "reply" button under this message.

> violation of these terms is deemed violation of Google's Intellectual Property Rights

Oh, it's deemed? I guess that's settled then.

The word "deemed" is almost always used by somebody who doesn't actually have the authority to decide something, but wants you to think they do.

Regardless of the ToS, my clients don't allow sending data to third parties so this service is completely useless to me.

Wow! That is even more aggressive than I would have guessed, and I’m cynical.

Do they have actual business customers that agree to those terms?

I think this only applies with ML products.

ML is about the only GCP service that’s interesting to large business customers.

It's definitely not, but the terms are indeed aggressive for using it.

Ok one large business customer then. :). I kind of want to see the lawyers go at it over this.

Does GM's Cruise use GCP? They might just be using the GPUs/CPUs parts though.

Customers of GM size have a chance to renegotiate the terms.

I was taken aback by this one as well. Basically this is an ineffectual attempt at preventing giving away their AI advantage by letting others use their proprietary models (and thus, indirectly, the gigantic dataset that make those models so good) as a "teacher" for their own models, using the fairly standard model refinement techniques popularized by their own Geoff Hinton. Keeping the cards close to their vest, as it were.

See e.g. https://www.quora.com/What-is-hiybbprqag for an example where Microsoft trained their ranker on Google's long tail and substantially reduced the relevance gap on the cheap, and in a way that makes it impossible for Google to trivially regain the advantage. People misinterpreted this as "Microsoft is copying the results", but that's not what it was. Google was unwillingly teaching Bing how to rank. Google responded with personalized search.

I don't think they can realistically prevent this, though. And it's not going to be anywhere near as traceable as "hiybbprqag" was.

Google has been using different trick for the same reason with their own employees: that famous 20% of working time that can be dedicated to personal projects. You might think they did that to increase employee satisfaction, but the real reason is that this way they own copyright to whatever their employees create in their spare time, and avoid Facebook-WhatsApp scenario (i.e. having to spent $14B on something you could have aquired for free).

Now I guess they apply the same principle to their GCP customers.

>but the real reason is that this way they own copyright to whatever their employees create in their spare time

Yeah it's not their spare time; it's work time. I would enjoy being able to spend one day a week working on whatever I like _for the company that employs me_. It's not a vacation day you spend in the office.

It was never for personal projects. The actual IPO quote is "We encourage our employees, in addition to their regular projects, to spend 20% of their time working on what they think will most benefit Google".

It's often done in other companies to a lesser degree with hackdays/weeks and is a good way to clean up tech debt or kickstart new product ideas.

> create, train, or improve (directly or indirectly) a similar or competing product or service

Talking about Google/Alphabet? Good luck with finding something not similar or competing.