> Otherwise what innovation are you talking about?

Quantity: Google has the highest number of deep learning papers accepted into top conferences among all institutions, even when papers from DeepMind are not counted in Google's.

Quality: Transformer and the recent BERT have, pun intended, transformed the entire NLP field. Batch normalization is now a staple of all neural networks, as are its descendants instance normalization, group normalization, etc.

These are just on top of my head. Google may have done many things wrong these days, but it definitely has not lost any edge in machine learning.

While I don't know real numbers, back of the enveloper estimations for hardware costs alone (based on GCP TPU/GPU pricing) give order of hundreds thousands for BERT, and tens of millions for AlphaGo and friends. Notice how very few organizations in the world are in position to commit these kind of resources to AI problems, and that only Google and China are choosing to do so.

And? Most scientific breakthroughs after the World War II require expensive equipments and materials. That fact doesn't make the achievements from Google, from Bell Labs, from CERN, from Fermilab less innovative.

Brain existed prior to deep mind, and is a leader in it's own right.

Hardware innovation in the Pixel Camera also uses ML. "Night Sight" is the result of work across teams

Would love to know more if you have some references for this.

Here you go - https://www.blog.google/products/pixel/see-light-night-sight...

deep learning at google was due to distbelief, not deepmind. deepmind brought reinforcement learning.