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Meh. As far as I'm concerned, it does _exactly_ what it says on the tin -- democratizes access to custom ML. Will you get a state of the art model out of it? Pr

Meh. As far as I'm concerned, it does _exactly_ what it says on the tin -- democratizes access to custom ML. Will you get a state of the art model out of it? Probably not. Will you be able to train a decent model and deploy it at scale fairly easily? Probably yes. That's the problem they're solving: getting people to use ML/AI without hiring a $400K/yr research scientist.

YeGoblynQueenne 8y ago
I'm not a businessperson and I try to avoid talking as if I were one, but I don't see what is the, well, business incentive for Google to "democratize access to custom ML". Accordingly, I don't see them even trying to do that. Rather, it seems to me that their policy so far amounts to an attempt at platform lock-in. If you want to do Deep Learning like Google does, you basically have to use their tools (yes, that's tensorflow I'm talking about) and their data (in the form of pre-trained models) and eventually pay them for CPU or GPU time (you can also pay their competitors, of course). In fact, I'd take this a step further and say that the whole Deep Learning hype is starting to sound like a total marketing trick, just to get more people to use Google's stuff, in the vain hopes of achieving their performance. However, to beat Google at their own game, with their own tools and their own data, running their models on their own computers... that does not sound like a winning proposition.
- h4b4n3r0 8y ago
  Well, the tools are free and open source, and other pretrained models are available for download. All that’s missing is an expensive PhD or two to make sense of it all, so that option is also available. You can do ML/DL on Google Cloud too in a completely portable way, using, for instance, Facebook’s PyTorch and pretrained models for it. You will discover, however, that it’s much harder and much more expensive to get anything usable that way, without Google doing most of the yak shaving for you, even though PyTorch is much easier to use than TF.

YeGoblynQueenne 8y ago

I'm not a businessperson and I try to avoid talking as if I were one, but I don't see what is the, well, business incentive for Google to "democratize access to custom ML". Accordingly, I don't see them even trying to do that. Rather, it seems to me that their policy so far amounts to an attempt at platform lock-in. If you want to do Deep Learning like Google does, you basically have to use their tools (yes, that's tensorflow I'm talking about) and their data (in the form of pre-trained models) and eventually pay them for CPU or GPU time (you can also pay their competitors, of course). In fact, I'd take this a step further and say that the whole Deep Learning hype is starting to sound like a total marketing trick, just to get more people to use Google's stuff, in the vain hopes of achieving their performance. However, to beat Google at their own game, with their own tools and their own data, running their models on their own computers... that does not sound like a winning proposition.

h4b4n3r0 8y ago
Well, the tools are free and open source, and other pretrained models are available for download. All that’s missing is an expensive PhD or two to make sense of it all, so that option is also available. You can do ML/DL on Google Cloud too in a completely portable way, using, for instance, Facebook’s PyTorch and pretrained models for it. You will discover, however, that it’s much harder and much more expensive to get anything usable that way, without Google doing most of the yak shaving for you, even though PyTorch is much easier to use than TF.