[tree_of_item]

Huh? They're attempting to dominate the machine learning ecosystem by writing a bunch of free and high quality machine learning libraries? What exactly are they doing wrong?

I wouldn't compare a permissively licensed library to Android services at all.

[congerous]

I'm surprised I have to write this, but Google is not a charity. They are pouring commercial resources into Tensorflow for a reason. That reason is Google Cloud. Tensorflow is a Trojan horse to get people to use Google Cloud and other paid Google products. How do I know this? Because Tensorflow works better on Google Cloud than anywhere else, and Google is making a concerted effort to catch up with AWS in cloud, mostly through machine learning.

I didn't compare Tensorflow to Android services. I said that Tensorflow would serve as the basis of a service bundle, much like Android did. Let's come back in a couple years and I'll tell you I told you so.

[matt4077]

> I'm surprised I have to write this,

Insulting the reader

> but Google is not a charity

truism

> They are pouring commercial resources...

As opposed to "non-commercial resources"?

> ... for a reason.

Everything happens for a reason.

> That reason is Google Cloud.

> How do I know this?

Pray tell!

> Because Tensorflow works better on Google Cloud than anywhere else.

This is the only real argument in this conspiracy. And if "anywhere" includes the users' hardware, it's wrong: tensorflow runs flawlessly on any Linux/NVIDIA hardware. Maybe it works better with GCE than AWS, but that would once again fall into that "rather unsurprising" category of factoids.

> Google is making a concerted effort to catch up with AWS in cloud, mostly through machine learning.

This can be re-written as "Google has a cloud offering, which it tries to sell. And right now, machine learning is pretty hot". Throwing a "concerted effort" in there is just trying to jazz it up to something ominous. Which it isn't.

> I didn't compare Tensorflow to Android services. I said that Tensorflow would serve as the basis of a service bundle, much like Android did.

"The basis of a service bundle" actually doesn't sound that scary. Nobody is disputing that Google offers services build on tensorflow. It just isn't any sort of "Trojan horse" conspiracy, and it is somewhat limited by the fact the tensorflow is OSS licensed and could be forked by anybody people suddenly find out it's full of geek soldiers.

[congerous]

> truism

Maybe, be people in this thread treat Tensorflow's creation as an act of simple altruism.

> And if "anywhere" includes the users' hardware, it's wrong: tensorflow runs flawlessly on any Linux/NVIDIA hardware. Maybe it works better with GCE than AWS, but that would once again fall into that "rather unsurprising" category of factoids.

Sorry, Tensorflow is slow on GPUs compared to other frameworks. This is not just an early blip, its a consistent pattern that has been repeatedly demonstrated. Why is Tensorflow slow on commodity hardware? Why isn't Google with it's infinite resources making Tensorflow run as fast as other frameworks on GPUs? Because it needs to demonstrate an advantage on the Google Cloud with TPUs.

On that cloud, it surrounds Tensorflow with other functionality that makes it easy to build AI, which aren't part of the Tensorflow project. Tensorflow is hard and inefficient to serve for inference, for example.

Machine learning is Google cloud's only hope to salvage Diane Greene's efforts and extend their dominance to a new sector. They're running a distant fourth.

> actually doesn't sound that scary.

It sounds scary to a lot of companies that don't want to be controlled or destroyed by Google. But by all means, lend them a hand, geek soldier.

[yorwba]

In what way is Tensorflow working better on Google Cloud? Are they tuning the ML code for specifics of their infrastructure or does Google Cloud just have more tooling for Tensorflow?

[agibsonccc]

Disclaimer: I am notoriously anti google and have tons of reasons to post these links. We push on hybrid cloud/on prem deep learning with our own deep learning framework that competes with the commerical sides of tensorflow, mxnet,..

Sample of search results: https://cloud.google.com/ml-engine/ https://cloud.google.com/tpu/

Even their docs: https://cloud.google.com/tpu/

Marketing content/training: https://www.coursera.org/learn/serverless-machine-learning-g...

vs (1 link I found with googling) for AWS: https://aws.amazon.com/tensorflow/

If we push the amazon equivalent though, run this: site:amazon.com aws mxnet

Every cloud vendor has their own framework. Microsoft has CNTK on azure as well.

Google doesn't want a repeat of what happened with map reduce and hadoop: https://www.quora.com/What-is-the-relationship-between-MapRe...

That being said, as a user: Just take it. You benefit from vendors competing. Google would love to pay you to use their tools.