6 ms·

I might be naive to think this, but are Google Cloud services making money simply through the fees you pay or does Google also have an interest in the data gene

by jaflo 9y ago

I might be naive to think this, but are Google Cloud services making money simply through the fees you pay or does Google also have an interest in the data generated by and passing through its services? If the latter, what data do they collect and how do they profit?

minimaxir 9y ago
Google benefits from this (in the non-altruistic perspective) because it encourages research/model development on TensorFlow, and promotion when said research is published using the framework. Not everything has to be a data play in the big picture.
ihsw2 9y ago
They let other's use and sharpen their tools.
- halite 9y ago
  One of the goals of this project is: "Share the benefits of machine learning with the world" It doesn't say who shares what :)
  - pm90 9y ago
    Google's stated goals seem to be very altruistic and to their credit, they do genuinely contribute heavily to good causes and open science and research. I kind of find it hard to believe a for-profit corporation is purely altruistic, but their play here seems to be to basically encourage research and make it more accessible to more people so that more human minds come up with novel ideas that Google itself might some day use in the future. e.g. I can see how investing millions of $'s in funding PhD students can pay off if even a single one of them discovers an obscure algorithm that increases efficiency of some process by just 0.1%, but at Google's scale that might still save millions of $'s more.
    - moosingin3space 9y ago
      I believe Google is playing long-term here -- if they make it really easy for someone to do ML research using their frameworks, they'll collect rent from the researcher and possibly get something more innovative out of their work later. Not everything they do is about short-term data plays.
- creaghpatr 9y ago
  Would it be possible for a pass-through of 'bad' or 'faulty' data to mess up their model at a large enough scale? If the data can be used to improve the model it seems like data could be used to damage it, in theory.
  - alexbeloi 9y ago
    I think ihws2 was saying sharpening tools to mean filing bug reports and feature requests for tensorflow and the cloud service.
Ironlink 9y ago
First of all I think they are too smart to jeopardize their entire cloud service in that way; no one would buy that. Ignoring that, I would think inspecting cloud customer data is much too unreliable to be of any use to them. Before anything else, the format and schema of the customer data would have to be analyzed and converted to data structures that match Google's internal models. While I imagine a computer could do it, I certainly would want a human to verify that the analysis makes sense. Assuming this has been done, they are then at the mercy of the customer as far as whether the data is accurate, whether it is complete, how often it is updated, etc. At the end of the day, I don't see how they would build a reliable business around arbitrary data structures which they have no control over. Information you can't trust is pretty useless. Edit: They would also have to understand how the data was selected. Looking at a series of data points, you would wonder if all these are from Arizona, or all from the year 1976, or all from color blind individuals. Without understanding such limitations, making any sort of deduction from a dataset will just lead you the wrong way.
- infogulch 9y ago
  Ok, so in general I agree with your statements, but... > how they would build a reliable business around arbitrary data structures which they have no control over Google Search? The entire web could be described exactly like that.
  - sicariusnoctis 9y ago
    But at least webpages are in a standardized format. With the exception of images, some of the data might be in arbitrary formats or just not trivial.
    - infogulch 9y ago
      > standardized format† †: Parses unreliably at best, Turing-complete at worst. (aka javascript if you didn't catch that)
    - hk__2 9y ago
      Webpages are, but the information isn’t. Multiple ways to layout your page; multiple ways to express your information; multiple languages; etc.
jacquesm 9y ago
At a minimum it will tell Google exactly what people are up to which means that if something interesting pops up they have a direct line to that person. After all the proposals alone will give them all that info, no need to snoop on the machines.
dgacmu 9y ago
Just the former. Cloud is about having paying customers and keeping them happy. In general (IANAL, IANA..anything), cloud customer data is sacrosanct, and Google builds very strong walls keeping that stuff isolated. As far as I've heard, the hopes for Cloud TPUs in general are that people will think it's an amazing service worth paying for. The hopes for TFRC are more complicated, as you might imagine when a company is giving away free stuff, but one of them, I'd put in the "long-term benefit altruism" category: It's quite hard to do some kinds of machine learning research in academia, because it can be fantastically expensive. We just blew $5k of google cloud credits in a week, and managed only 4 complete training runs of Inception / Imagenet. This was for one conference paper submission. Having a situation where academia can't do research that is relevant to Google (or Facebook, or Microsoft) is really bad from a long-term perspective, and one thing TFRC might do is help make sure that advances in deep learning continue at a rapid pace. From watching the rate at which my deep learning colleagues get swallowed up by industry, I think it's a very valid concern, and I'm very supportive of all of the industry efforts we're seeing to try to address this. It's good for the entire research ecosystem. (There are undoubtedly many other reasons, such as those noted below by minimaxir, but this is the one I personally feel the pain of.) Disclaimer: I get paid by Google part-time to do work related to this, but this is not any kind of official statement. The pain-of-ML-in-academia bit is purely from my hat as a CS professor.

by jaflo 9y ago

minimaxir 9y ago

Google benefits from this (in the non-altruistic perspective) because it encourages research/model development on TensorFlow, and promotion when said research is published using the framework. Not everything has to be a data play in the big picture.

ihsw2 9y ago

They let other's use and sharpen their tools.

halite 9y ago
One of the goals of this project is: "Share the benefits of machine learning with the world" It doesn't say who shares what :)
- pm90 9y ago
  Google's stated goals seem to be very altruistic and to their credit, they do genuinely contribute heavily to good causes and open science and research. I kind of find it hard to believe a for-profit corporation is purely altruistic, but their play here seems to be to basically encourage research and make it more accessible to more people so that more human minds come up with novel ideas that Google itself might some day use in the future. e.g. I can see how investing millions of $'s in funding PhD students can pay off if even a single one of them discovers an obscure algorithm that increases efficiency of some process by just 0.1%, but at Google's scale that might still save millions of $'s more.
  - moosingin3space 9y ago
    I believe Google is playing long-term here -- if they make it really easy for someone to do ML research using their frameworks, they'll collect rent from the researcher and possibly get something more innovative out of their work later. Not everything they do is about short-term data plays.
creaghpatr 9y ago
Would it be possible for a pass-through of 'bad' or 'faulty' data to mess up their model at a large enough scale? If the data can be used to improve the model it seems like data could be used to damage it, in theory.
- alexbeloi 9y ago
  I think ihws2 was saying sharpening tools to mean filing bug reports and feature requests for tensorflow and the cloud service.

Ironlink 9y ago

First of all I think they are too smart to jeopardize their entire cloud service in that way; no one would buy that. Ignoring that, I would think inspecting cloud customer data is much too unreliable to be of any use to them. Before anything else, the format and schema of the customer data would have to be analyzed and converted to data structures that match Google's internal models. While I imagine a computer could do it, I certainly would want a human to verify that the analysis makes sense. Assuming this has been done, they are then at the mercy of the customer as far as whether the data is accurate, whether it is complete, how often it is updated, etc. At the end of the day, I don't see how they would build a reliable business around arbitrary data structures which they have no control over. Information you can't trust is pretty useless. Edit: They would also have to understand how the data was selected. Looking at a series of data points, you would wonder if all these are from Arizona, or all from the year 1976, or all from color blind individuals. Without understanding such limitations, making any sort of deduction from a dataset will just lead you the wrong way.

infogulch 9y ago
Ok, so in general I agree with your statements, but... > how they would build a reliable business around arbitrary data structures which they have no control over Google Search? The entire web could be described exactly like that.
- sicariusnoctis 9y ago
  But at least webpages are in a standardized format. With the exception of images, some of the data might be in arbitrary formats or just not trivial.
  - infogulch 9y ago
    > standardized format† †: Parses unreliably at best, Turing-complete at worst. (aka javascript if you didn't catch that)
  - hk__2 9y ago
    Webpages are, but the information isn’t. Multiple ways to layout your page; multiple ways to express your information; multiple languages; etc.

jacquesm 9y ago

At a minimum it will tell Google exactly what people are up to which means that if something interesting pops up they have a direct line to that person. After all the proposals alone will give them all that info, no need to snoop on the machines.

dgacmu 9y ago

Just the former. Cloud is about having paying customers and keeping them happy. In general (IANAL, IANA..anything), cloud customer data is sacrosanct, and Google builds very strong walls keeping that stuff isolated. As far as I've heard, the hopes for Cloud TPUs in general are that people will think it's an amazing service worth paying for. The hopes for TFRC are more complicated, as you might imagine when a company is giving away free stuff, but one of them, I'd put in the "long-term benefit altruism" category: It's quite hard to do some kinds of machine learning research in academia, because it can be fantastically expensive. We just blew $5k of google cloud credits in a week, and managed only 4 complete training runs of Inception / Imagenet. This was for one conference paper submission. Having a situation where academia can't do research that is relevant to Google (or Facebook, or Microsoft) is really bad from a long-term perspective, and one thing TFRC might do is help make sure that advances in deep learning continue at a rapid pace. From watching the rate at which my deep learning colleagues get swallowed up by industry, I think it's a very valid concern, and I'm very supportive of all of the industry efforts we're seeing to try to address this. It's good for the entire research ecosystem. (There are undoubtedly many other reasons, such as those noted below by minimaxir, but this is the one I personally feel the pain of.) Disclaimer: I get paid by Google part-time to do work related to this, but this is not any kind of official statement. The pain-of-ML-in-academia bit is purely from my hat as a CS professor.