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Why did Google Brain exist?

moderndescartes.com

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Re: Why did Google Brain exist?

#2
because once Jeff Dean had solved Google's maslow problems (scaling web search, making ads profitable, developing high performance machine learning systems) he wanted to return to doing academic-style research, but with the benefit of Google's technical and monetary resources, and not part of X, which never produces anything of long-term value. I know for sure he wanted to make an impact in medical AI and felt that being part of a research org would make that easier/more possible than if he was on a product team.

Re: Why did Google Brain exist?

#3
> The next obvious reason for Google to invest in pure research is for the breakthrough discoveries it has yielded and can continue to yield. As a rudimentary brag sheet, Brain gave Google TensorFlow, TPUs, significantly improved Translate, JAX, and Transformers.

Except that these advances have made other companies an existential threat for Google. 2 years ago it was hard to imagine what could topple Google. Now a lot of people can see a clear path: large language models.

From a business perspective it's astounding what a massive failure Google Brain has been. Basically nothing has spun out of it to benefit Google. And yet at the same time, so much has leaked out, and so many people have left with that knowledge Google paid for, that Google might go the way of Yahoo in 10 years.

This is the simpler explanation of the Brain-Deep Mind merger: both Brain and Deep Mind have fundamentally failed as businesses.

Re: Why did Google Brain exist?

#4
>PyTorch/Nvidia GPUs easily overtaking TensorFlow/Google TPUs.

TF lost to PyTorch, and this is Google’s fault - TF APIs are both insane and badly documented.

But nothing comes close to performance of Google’s TPU exaflop mega-clusters. Nvidia is not even in the same ballpark.

Re: Why did Google Brain exist?

#5

> The next obvious reason for Google to invest in pure research is for the breakthrough discoveries it has yielded and can continue to yield. As a rudimentary brag sheet, Brain gave Google TensorFlow, TPUs, significantly improved Translate, JAX, and Transformers. Except that these advances have made other companies an existential threat for Google. 2 years ago it was hard to imagine what could topple Google. Now a lo…

[deleted]

Re: Why did Google Brain exist?

#6
post #4

>PyTorch/Nvidia GPUs easily overtaking TensorFlow/Google TPUs. TF lost to PyTorch, and this is Google’s fault - TF APIs are both insane and badly documented. But nothing comes close to performance of Google’s TPU exaflop mega-clusters. Nvidia is not even in the same ballpark.

I can speak from experience on this. Getting started with TensorFlow was very complicated with sparse documentation, so we dropped the idea of using it.

Re: Why did Google Brain exist?

#7
Lots of great insight. Here’s one:

“Given the long timelines of a PhD program, the vast majority of early ML researchers were self-taught crossovers from other fields. This created the conditions for excellent interdisciplinary work to happen. This transitional anomaly is unfortunately mistaken by most people to be an inherent property of machine learning to upturn existing fields. It is not.

Today, the vast majority of new ML researcher hires are freshly minted PhDs, who have only ever studied problems from the ML point of view. I’ve seen repeatedly that it’s much harder for a ML PhD to learn chemistry than for a chemist to learn ML.”

Re: Why did Google Brain exist?

#9
post #6
post #4

>PyTorch/Nvidia GPUs easily overtaking TensorFlow/Google TPUs. TF lost to PyTorch, and this is Google’s fault - TF APIs are both insane and badly documented. But nothing comes close to performance of Google’s TPU exaflop mega-clusters. Nvidia is not even in the same ballpark.

I can speak from experience on this. Getting started with TensorFlow was very complicated with sparse documentation, so we dropped the idea of using it.

I had to use TF when I worked at G, when I left I immediately started to use PyTorch and never looked back.

Re: Why did Google Brain exist?

#10
post #7

Lots of great insight. Here’s one: “Given the long timelines of a PhD program, the vast majority of early ML researchers were self-taught crossovers from other fields. This created the conditions for excellent interdisciplinary work to happen. This transitional anomaly is unfortunately mistaken by most people to be an inherent property of machine learning to upturn existing fields. It is not. Today, the vast majority…

obligatory XKCD: https://xkcd.com/793/
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