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?
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.