

Distributed Neural Networks with GPUs in the AWS Cloud - srajbr
http://techblog.netflix.com/2014/02/distributed-neural-networks-with-gpus.html

======
doh
Isn't this infringing the recent patent of Neurala?
[http://patft.uspto.gov/netacgi/nph-
Parser?Sect1=PTO1&Sect2=H...](http://patft.uspto.gov/netacgi/nph-
Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=8,648,867.PN.&OS=PN/8,648,867&RS=PN/8,648,867)

~~~
chroem
Holy crap. Am I reading this correctly? Is this really a patent for running
learning algorithms on the GPU?

~~~
mdda
I don't see how the patent office didn't just google for 30 seconds...

[http://www.sciencedirect.com/science/article/pii/S0031320304...](http://www.sciencedirect.com/science/article/pii/S0031320304000524)

Maybe the patent has interesting twists and turns, but applying known
algorithms on previously known architectures doesn't seem like the innovation
that they should hand out protection for 17 years.

------
waterlesscloud
The Netflix tech blog goes into more detail about running deep learning on
Amazon's cloud servers.

[http://techblog.netflix.com/2014/02/distributed-neural-
netwo...](http://techblog.netflix.com/2014/02/distributed-neural-networks-
with-gpus.html)

------
Houshalter
Is this really a good idea? I thought neural networks didn't do as well as
other methods outside of image classification and problems like it. Many of
the advancements in Deep Learning were learning to extract features from
unlabeled data. I assume all of Netflix's data is labelled.

EDIT: The deaded comment below me makes a good point, but they still have
labels in the sense of what everyone watched and for how long.

Also the new title is terrible. Oh I guess it's a different article now???

~~~
Homunculiheaded
Feature extraction can be aided by unsupervised data but will certainly work
with labeled data. One of the advancements bundled under 'deep learning' is
how we can leverage unlabeled data (which is much easier to come by) to
improve performance. And of course you can always do unsupervised learning
with labeled data, just toss out the labels ;)

It's actually the multiple layers hidden units that perform non-linear feature
extraction and the unsupervised pre-training is simply a means to do this
better (theoretically, although we don't really know what's happening as much
as it would seem).

Most of the current research shows deep neural nets to be state of the art in
image classification and nlp. I don't know that it is the case that deep
learning techniques do not work out side this area, it's just there hasn't
been much published on it either way. Although I do believe the Kaggle Merck
contest was neither of these, and deep learning out performed all other
techniques [http://blog.kaggle.com/2012/11/01/deep-learning-how-i-did-
it...](http://blog.kaggle.com/2012/11/01/deep-learning-how-i-did-it-merck-1st-
place-interview/)

------
dasmithii
Has any large-scale genetic algorithm infrastructure been developed? I've
often wondered if EaaS (Evolution as a Service) could ever function
successfully. Surely it has potential.

------
luser
I wish Netflix would just give me a list of genres I could browse through and
stop with the oh-my-so-clever recommendation engine. Maybe I want to stretch
my viewing habits... how am I going to see what is on offer if it is always
filtered through what I chosen before?

~~~
Irishsteve
It has that at the top of the page

~~~
gdubs
Yea, but it's harder to get the specific ones like 'gritty crime dramas from
the 80's with strong female leads'.

------
frosted_moose
The best possible side-effect from this? That we finally figure out a
universal theory of film production and consumption. The social
scientific/cultural sociological significance of this is quite lovely.

------
danso
Sadly, the Recommendation Engine is only of limited use...and I hate to be one
of those naysayers as I understand the economics and contractual issues
here...the movies that Netflix thinks I would really enjoy _and_ are available
for streaming _and_ I haven't seen (I watch a lot of movies but am by no means
prolific) goes downhill after a couple dozen.

It used to be that on the iPad, at least two bottom rows were dedicated to
"New Releases" and "Recently Added"...sometimes neither of those rows seem to
show up, and so I find myself logging into the web client just to see those
listings, and -- I assume this is why they aren't as spotlighted in the iPad
app anymore -- there's generally not much new to see. While I like House of
Cards, I think Netflix would appeal to me much better if it spent that money
on 200 - 300 _good_ recent releases, or holding steady on to some of the great
classics (there used to be more Akira Kurosawa and Woody Allen movies on
Instant).

~~~
brucehart
I don't find the recommendations very useful either. Maybe the secret value of
the recommendation engine for Netflix is evaluating movies outside of their
catalog. When considering how much to pay for the streaming rights to a movie,
they can use the recommendation engine to determine how well received it would
be by their membership and bid accordingly.

------
nctalaviya
Really a good news. Looking something like this

------
dhfjgkrgjg
What is it's first recommendation? Add more DRM into the web standards?
Subvert the open web further?

