8 ms·
If I collect a bunch of data and train a model is the data/model mine or theirs? what if in the future they change their minds and decide to change the TOS? di
by sharemywin 9y ago
If I collect a bunch of data and train a model is the data/model mine or theirs?
what if in the future they change their minds and decide to change the TOS? did I just build on top of quicksand?
- TheIronYuppie 9y agoDisclosure: I work at Google on Kubeflow The data remains yours and the model is yours - eg if you delete your account, the data and model goes away (think of it like the data or model you stored on a VM). However, what I think you're looking for is to be able to actually download the model, and I'm afraid that's not possible. Are you looking to avoid lock-in? Or something else?
- sharemywin 9y agooutside audits of data handling practices.
- TheIronYuppie 9y agoDisclosure: I work at Google on Kubeflow I'll make sure we have clear statements/auditing on this! We're already committed to GDPR[1] - is there a specific additional service/certification you'd like to see? [1] https://www.google.com/cloud/security/gdpr/ https://www.google.com/cloud/security/gdpr/
- sharemywin 9y agocurious is that Europe only?
- bistro17 9y agoand addressing model interpretibility?
- chimtim 9y agoThen what is "Auto ML"? It sounds like just another cloud service.
- rasmi 9y agoCompared to ML Engine, where you provide the labeled data and model code, with AutoML, you just provide the labeled data (with your custom labels for whichever domain you may be working in) and AutoML builds the model for you.
- jmngomes 9y agoSimilar to Amazon's ML: https://aws.amazon.com/aml/details/ https://aws.amazon.com/aml/details/ Eventually useful for building a very basic model to serve as a benchmark for a real model.
- chimtim 9y agoThis does not sound very useful. The entire market and AI consulting is for that last 5% of accuracy. Is there a reason why Google is investing so heavily in this space? Perhaps a simple model/UI is a good starting point for many customers, and many of them end up renting the classic cloud after they gain some expertise. And the rationale for all this PR is that Google does not want to miss these customers to Amazon
- TheIronYuppie 9y agoDisclosure: I work at Google at Kubeflow There are a few different reasons: 1) Most companies have very limited skill in building advanced models. While many folks are trying to achieve 5% or better accuracy, MOST folks are trying to achieve ANY accuracy (since they have nothing) 2) Many problems are not very complicated and do not require a custom model. From the blog post, the "cloud" example only requires a small amount of changes to classify for a specific domain - to have to build an entirely new model for that, or train on MM of images seems like overkill 3) AutoML (often) is better than humans already[1]. So if you want to achieve that 5%, you MIGHT need to use a machine anyway. [1] https://arxiv.org/abs/1712.00559 https://arxiv.org/abs/1712.00559
- RubenSandwich 9y agoI can't speak for OP, but I'd expect to download the generated model otherwise my business is locked into this service. If Google is worried about people just generating models and running, then charge for training time/resources.
- TheIronYuppie 9y agoDisclosure: I work at Google on Kubeflow That's fair - the reality is that it's less about the worry of people "taking of models and running it themselves", it's more about the amount of custom stuff that has to go on behind the scenes in order to enable this kind of model exploration and training. We're exploring all options but, yes, you'd be committing to the platform (for now). If you're interested in a portable solution, may I recommend (extremely selfishly) Kubeflow[1]? We don't provide AutoML, but we do provide a very portable solution for running an ML stack. [1] https://github.com/google/kubeflow https://github.com/google/kubeflow