6 ms·

Distributed Neural Networks with GPUs in the AWS Cloud

57 points by srajbr 13y ago

nctalaviya 13y ago
Really a good news. Looking something like this
frosted_moose 13y ago
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.
dhfjgkrgjg 13y ago
What is it's first recommendation? Add more DRM into the web standards? Subvert the open web further?
waterlesscloud 13y ago
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-networks-with-gpus.html http://techblog.netflix.com/2014/02/distributed-neural-netwo...
luser 13y ago
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 13y ago
  It has that at the top of the page
  - gdubs 13y ago
    Yea, but it's harder to get the specific ones like 'gritty crime dramas from the 80's with strong female leads'.
- arh68 13y ago
  I have made more than one good decision choosing from the Random Picks list. For all I know they're not random and very calculated, but they seem to 'stretch' my taste.
danso 13y ago
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 13y ago
  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.
Houshalter 13y ago
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???
- deleted 13y ago
  [deleted]
- IanCal 13y ago
  > Many of the advancements in Deep Learning were learning to extract features from unlabeled data. I assume all of Netflix's data is labelled. Probably not. They'll have a vast amount of information about what people watched, for how long, etc. but they won't have labelled scores for everything. In this case, you'd maybe run an unsupervised algorithm to extract features first (the deep learning bit) then another algorithm to map those features to labels (here you'd use the labelled data). They may also want to do similarity measurements between different films, in which case again they don't have labelled data (you want to discover the clusters). While I'm sure they have problems where they do have nice labelled data, I'm sure they have a vast amount of problems where they don't have some or any labels.
- waterlesscloud 13y ago
  A mod changed the link and title to the netflix tech blog entry, which is far more appropriate for this audience anyway. The wired thing was sort of blogspam.
- jjh42 13y ago
  Deep learning just refers to the idea of a many layered neural network. These can be used for unsupervised (unlabeled) learning and supervised learning (labelled). Many of the recent headline results for deep learning have been supervised such as the image net classification challenge (http://www.image-net.org/challenges/LSVRC/2013/ http://www.image-net.org/challenges/LSVRC/2013/)
doh 13y ago
Isn't this infringing the recent patent of Neurala? 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 http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=H...
- chroem 13y ago
  Holy crap. Am I reading this correctly? Is this really a patent for running learning algorithms on the GPU?
  - mdda 13y ago
    I don't see how the patent office didn't just google for 30 seconds... http://www.sciencedirect.com/science/article/pii/S0031320304000524 http://www.sciencedirect.com/science/article/pii/S0031320304... 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.
dasmithii 13y ago
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.

57 points by srajbr 13y ago

Really a good news. Looking something like this

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.

dhfjgkrgjg 13y ago

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

waterlesscloud 13y ago

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

luser 13y ago

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 13y ago
It has that at the top of the page
- gdubs 13y ago
  Yea, but it's harder to get the specific ones like 'gritty crime dramas from the 80's with strong female leads'.
arh68 13y ago
I have made more than one good decision choosing from the Random Picks list. For all I know they're not random and very calculated, but they seem to 'stretch' my taste.

danso 13y ago

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 13y ago
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.

Houshalter 13y ago

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???

deleted 13y ago
[deleted]
IanCal 13y ago
> Many of the advancements in Deep Learning were learning to extract features from unlabeled data. I assume all of Netflix's data is labelled. Probably not. They'll have a vast amount of information about what people watched, for how long, etc. but they won't have labelled scores for everything. In this case, you'd maybe run an unsupervised algorithm to extract features first (the deep learning bit) then another algorithm to map those features to labels (here you'd use the labelled data). They may also want to do similarity measurements between different films, in which case again they don't have labelled data (you want to discover the clusters). While I'm sure they have problems where they do have nice labelled data, I'm sure they have a vast amount of problems where they don't have some or any labels.
waterlesscloud 13y ago
A mod changed the link and title to the netflix tech blog entry, which is far more appropriate for this audience anyway. The wired thing was sort of blogspam.
jjh42 13y ago
Deep learning just refers to the idea of a many layered neural network. These can be used for unsupervised (unlabeled) learning and supervised learning (labelled). Many of the recent headline results for deep learning have been supervised such as the image net classification challenge (http://www.image-net.org/challenges/LSVRC/2013/ http://www.image-net.org/challenges/LSVRC/2013/)

doh 13y ago

Isn't this infringing the recent patent of Neurala? 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 http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=H...

chroem 13y ago
Holy crap. Am I reading this correctly? Is this really a patent for running learning algorithms on the GPU?
- mdda 13y ago
  I don't see how the patent office didn't just google for 30 seconds... http://www.sciencedirect.com/science/article/pii/S0031320304000524 http://www.sciencedirect.com/science/article/pii/S0031320304... 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.

dasmithii 13y ago

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.