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back to article Google Brain king slashes cost of AI gear

The architect behind some of Google's mammoth machine-learning systems has figured out a way to dramatically reduce the cost of the infrastructure needed for weak artificial intelligence programs, making it easier for cash-strapped companies and institutions to perform research into this crucial area of technology. In a paper …

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Portable source code

Portable source code or GTFO.

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Face

WTF! I hope this thing doesn't think all humans look like Clawhammer Jack up there in the image. If it thinks all humans look like a wet rape clown then its first decision will be that we've all got to go.

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Mushroom

Thou shalt not make a machine in the likeness of a man's mind.

It is nearly time for the Butlerian jihad.

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Coat

...in the likeness of a _man's_ mind

It isn't until it has been trained to recognise cleavage ..

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Trollface

The Butlerian Jihad has been postponed as designers fight over how to design the icon to activate said Jihad on you smartphone.

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Anonymous Coward

So... it fails to recognise slightly more than one in four cat videos. Humans are still better than AIs at wasting time on the internet.

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Terminator

Google's not the only company building deep neural networks...

I built a PaaS that does exactly this (www.ersatz1.com) There have been a lot of advances in neural nets, starting in 2006 (deep learning is now 7 years old!)

But yeah, Google seems to be focused on building bigger and bigger networks, but latest research is actually suggesting that "bigger isn't necessarily better" (see: http://arxiv.org/pdf/1301.3583v4.pdf) Our system takes the approach of training a bunch of smaller networks (although still huge compared to what people were doing just a few years ago) and stringing them together as modules, more like how our brains actually work.

Anyway, don't worry, this stuff is a looooong way from skynet... Expect to see a lot more growth in this industry, google is not the only game in town--although they do have by far the best PR team ;-)

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"Anything CPU can do GPU can do better" is BS. GPU's are better for high throughput needs, and CPU's are better for low latency needs.

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Bronze badge

A tad oversold

Machine learning is an incredibly powerful tool... Oh, it's quite credible, I assure you.

"Google researcher describes CPU-GPU architecture for large neural nets" would have been an appropriate title for this piece. There's nothing amazing or even particularly innovative here. GPUs are not a panacea (as DeWaal points out above), and bigger neural nets aren't either (as Sullivan points out). And machine learning encompasses far more strategies than just neural nets.

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