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Does anyone know what Facebook is using the AI for?

by UXDork 12y ago

raverbashing 12y ago
Basically everything in FB has one main goal: Ads Secondary goals might be: Spam detection and extracting info from the graph/pictures, etc FB identify people from your Social Graph in Pictures, for example
- pkfrank 12y ago
  Also, identifying trends in users engaging in predatory behavior, etc.
- WillNotDownvote 12y ago
  "Basically everything in FB has one main goal: Ads" Is this actually true, or a glib answer? Ads certainly don't feel like much of the FB experience, nowhere near the level of Google, or even Twitter. They're negligible, really. Whereas shaping the feed and identifying people in pics, etc, is central to the FB experience.
  - raverbashing 12y ago
    Not necessarily Ads in the traditional sense, but FB also sells content reach (Promoted Content) and targeting Shaping the feed is certainly one part of it. But I guess that part of the success of FB is that they don't make it, as you said, not make the ads feel as much part of the experience.
  - kylestlb 12y ago
    Someone with more context can answer this better but I would guess that selling behavioral data to ad agencies is a thing?
  - samolang 12y ago
    Agreed. You can't show ads unless you have users. Optimizing advertisements is definitely second fiddle to optimizing the user experience.
  - dragonwriter 12y ago
    > Ads certainly don't feel like much of the FB experience, nowhere near the level of Google, or even Twitter. Facebook creates an artificial distinction between labeled ads (which are, of course, obvious ads) and posts with paid reach (which are also ads, but presented as normal content), exactly for the purpose of maximizing the quantity of ads while minimizing the impression of content being dominated by ads.
    - WillNotDownvote 12y ago
      Right, so ads don't feel like much of the FB experience. My point is that FB seems much, much more focused on creating an engaging user experience than it does on ads, so it seems wrong to say that their deep learning efforts have ads as their one main goal.
      - dragonwriter 12y ago
        > Right, so ads don't feel like much of the FB experience. Right, but the issue was the claim that with FB everything is about ads, not the UX feels like it is about ads. Making ads not feel like as much of the FB experience as they are is, itself, about ads -- and, particularly, is about maximizing the degree to which the FB experience is actually about ads.
        WillNotDownvote 12y ago
        "Making ads not feel like as much of the FB experience as they are is, itself, about ads..." Well, we just disagree here. I see it from exactly the other end. That the main FB goal is to engage users, and minimizing the (necessary, but grudgingly so) ads is about that.
        unclebucknasty 12y ago
        I think the answer is both-and vs. either-or. FB's bait is user engagement. So, applying machine learning to the goal of engaging users makes sense. But, to monetize that user-engagement they, of course, use ads. Applying machine learning directly there makes sense too. Beyond that, it's just semantics. Yes, one could accurately say that everything FB does is about ads because, ultimately, they are a for-profit company which derives its revenue from advertising. In that way, the ultimate goal of all of its activity is aimed at generating ad revenue. But, that doesn't mean that every single activity or bit of technology that supports that activity is directly tied to driving ad revenue. That is to say, that if FB featured no advertising but, instead, charged users, they would still likely deploy machine-learning to user-engagement and, thus, customer-retention.
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  - choppaface 12y ago
    Categorization is critical to boosting precision in information retrieval tasks. Deep networks for cropped object recognition are an important source of (inferred) content categories (especially when other context, e.g. photo captions, are not useful). While a good image categorizer would be very useful for ad targeting and auctions, the technology can also boost precision for news feed, graph search, etc., which improves user experience.
- amelius 12y ago
  The software runs on Nvidia hardware. Not sure if all their servers are fitted with one or more GPU cards... I think it is more likely that this is just research software.
  - raverbashing 12y ago
    Well, it depends, you can definitely have servers with NVidia hardware, and you don't need to have all of them with it. (Amazon offers GPGPU servers on EC2 for example)
    - bhouston 12y ago
      Amazon only offers very costly Tesla and Quadro cards on their GPGPUs. Super expensive. For scale, if you do not need the extra memory on the Tesla cards, what you want is commodity NVIDIA GeForce cards that are a fraction of the cost.
      - polskibus 12y ago
        Standard cards are handicapped for double precision operations though (1/8 speed afaik).
        p1esk 12y ago
        You don't need double precision for typical DL tasks, such as training a convnet.
        raverbashing 12y ago
        Double precision is overrated :) (at least for ML)
  - Houshalter 12y ago
    Deep neural networks are usually trained on GPUs which can provide a huge speed up, and is much cheaper. However they can easily be run on CPUs after being trained. I don't see why they wouldn't have access to GPUs in production though.
anantzoid 12y ago
To further personalise the user feed.

Does anyone know what Facebook is using the AI for?

by UXDork 12y ago

Does anyone know what Facebook is using the AI for?

Basically everything in FB has one main goal: Ads Secondary goals might be: Spam detection and extracting info from the graph/pictures, etc FB identify people from your Social Graph in Pictures, for example

pkfrank 12y ago
Also, identifying trends in users engaging in predatory behavior, etc.
WillNotDownvote 12y ago
"Basically everything in FB has one main goal: Ads" Is this actually true, or a glib answer? Ads certainly don't feel like much of the FB experience, nowhere near the level of Google, or even Twitter. They're negligible, really. Whereas shaping the feed and identifying people in pics, etc, is central to the FB experience.
- raverbashing 12y ago
  Not necessarily Ads in the traditional sense, but FB also sells content reach (Promoted Content) and targeting Shaping the feed is certainly one part of it. But I guess that part of the success of FB is that they don't make it, as you said, not make the ads feel as much part of the experience.
- kylestlb 12y ago
  Someone with more context can answer this better but I would guess that selling behavioral data to ad agencies is a thing?
- samolang 12y ago
  Agreed. You can't show ads unless you have users. Optimizing advertisements is definitely second fiddle to optimizing the user experience.
- dragonwriter 12y ago
  > Ads certainly don't feel like much of the FB experience, nowhere near the level of Google, or even Twitter. Facebook creates an artificial distinction between labeled ads (which are, of course, obvious ads) and posts with paid reach (which are also ads, but presented as normal content), exactly for the purpose of maximizing the quantity of ads while minimizing the impression of content being dominated by ads.
  - WillNotDownvote 12y ago
    Right, so ads don't feel like much of the FB experience. My point is that FB seems much, much more focused on creating an engaging user experience than it does on ads, so it seems wrong to say that their deep learning efforts have ads as their one main goal.
    - dragonwriter 12y ago
      > Right, so ads don't feel like much of the FB experience. Right, but the issue was the claim that with FB everything is about ads, not the UX feels like it is about ads. Making ads not feel like as much of the FB experience as they are is, itself, about ads -- and, particularly, is about maximizing the degree to which the FB experience is actually about ads.
      - WillNotDownvote 12y ago
        "Making ads not feel like as much of the FB experience as they are is, itself, about ads..." Well, we just disagree here. I see it from exactly the other end. That the main FB goal is to engage users, and minimizing the (necessary, but grudgingly so) ads is about that.
      - unclebucknasty 12y ago
        I think the answer is both-and vs. either-or. FB's bait is user engagement. So, applying machine learning to the goal of engaging users makes sense. But, to monetize that user-engagement they, of course, use ads. Applying machine learning directly there makes sense too. Beyond that, it's just semantics. Yes, one could accurately say that everything FB does is about ads because, ultimately, they are a for-profit company which derives its revenue from advertising. In that way, the ultimate goal of all of its activity is aimed at generating ad revenue. But, that doesn't mean that every single activity or bit of technology that supports that activity is directly tied to driving ad revenue. That is to say, that if FB featured no advertising but, instead, charged users, they would still likely deploy machine-learning to user-engagement and, thus, customer-retention.
- deleted 12y ago
  [deleted]
- deleted 12y ago
  [deleted]
- choppaface 12y ago
  Categorization is critical to boosting precision in information retrieval tasks. Deep networks for cropped object recognition are an important source of (inferred) content categories (especially when other context, e.g. photo captions, are not useful). While a good image categorizer would be very useful for ad targeting and auctions, the technology can also boost precision for news feed, graph search, etc., which improves user experience.
amelius 12y ago
The software runs on Nvidia hardware. Not sure if all their servers are fitted with one or more GPU cards... I think it is more likely that this is just research software.
- raverbashing 12y ago
  Well, it depends, you can definitely have servers with NVidia hardware, and you don't need to have all of them with it. (Amazon offers GPGPU servers on EC2 for example)
  - bhouston 12y ago
    Amazon only offers very costly Tesla and Quadro cards on their GPGPUs. Super expensive. For scale, if you do not need the extra memory on the Tesla cards, what you want is commodity NVIDIA GeForce cards that are a fraction of the cost.
    - polskibus 12y ago
      Standard cards are handicapped for double precision operations though (1/8 speed afaik).
      - p1esk 12y ago
        You don't need double precision for typical DL tasks, such as training a convnet.
      - raverbashing 12y ago
        Double precision is overrated :) (at least for ML)
- Houshalter 12y ago
  Deep neural networks are usually trained on GPUs which can provide a huge speed up, and is much cheaper. However they can easily be run on CPUs after being trained. I don't see why they wouldn't have access to GPUs in production though.

anantzoid 12y ago

To further personalise the user feed.