• Feathercrown@lemmy.world
    link
    fedilink
    English
    arrow-up
    2
    ·
    4 months ago

    this is a completely different problem

    Yes, that’s what I’ve been trying to explain. And no, JWO was not built to be accurate, it was built to be convenient. That’s a very different incentive that will lead to skipping alternatives that are less convenient but more accurate-- like the checkout kiosks I’ve been talking about. I’m not defending JWO and it’s obviously both a harder problem and one that’s not managed well, focusing on optics over accuracy.

    nobody’s placing the berry or berries they decide to eat or not eat in a separate area before placing them in their mouth

    That’s not necessary, they’re already placed in a nearly ideal environment by the person setting up the berry bowl. Notice how the “bowl” is a white square with each fruit placed in a way where they’re separated by the whitespace. You wouldn’t even need to train a model on the whole bowl, you could just do an image region detection --> object recognition pipeline. The hardest part about the berry bowl would by far be determining the person taking the fruit! (In fact, I wouldn’t be surprised if that was manually reviewed, with that few instances to look at.)

    • whenyellowstonehasitsday@fedia.io
      link
      fedilink
      arrow-up
      1
      ·
      4 months ago

      Yes, that’s what I’ve been trying to explain

      jwo is a different problem than the separate checkout kiosk you’re describing

      jwo is the same problem as is in the image

      JWO was not built to be accurate, it was built to be convenient

      it was built to be accurate within the boundary of “no checkout step”

      at this point it feels like you’re deliberately misinterpreting me

      Notice how the “bowl” is a white square with each fruit placed in a way where they’re separated by the whitespace

      unless somebody moves or jostles them while taking some fruit

      you’re essentially making the exact same naive assumptions about the operating environment that led to jwo’s failures

      if “just track which one disappeared” was a valid solution to the problem, jwo wouldn’t have failed

      The hardest part about the berry bowl would by far be determining the person taking the fruit

      facial recognition is a thoroughly solved problem, at least in terms of the accuracy that we’re aiming for here

      • Feathercrown@lemmy.world
        link
        fedilink
        English
        arrow-up
        1
        ·
        4 months ago

        I’m not deliberately misinterpreting you, but I think I found where the disconnect is:

        jwo is a different problem than the separate checkout kiosk you’re describing

        jwo is the same problem as is in the image

        I don’t think this is the case. The berry box is somewhere between JWO and checkout kiosks, in that the density of items is small, and the background is clear, but there are multiple items at the same time. I’m seeing the items as discrete enough that it’s more similar to checkout kiosks, but you’re seeing it as more similar to JWO (now I understand why you keep bringing JWO up).

        it was built to be accurate within the boundary of “no checkout step”

        Was it? I mean in some sense yes, but I feel like it was primarily built for Amazon’s image, to give the appearance of it working well. That’s why they’re secretly hiring people and claiming it’s AI, after all. If they weren’t doing it for their image they wouldn’t even need to pretend that it was AI.

        unless somebody moves or jostles them while taking some fruit

        you’re essentially making the exact same naive assumptions about the operating environment that led to jwo’s failures

        I suppose I am, but it appears that the person in the image is also making that same assumption (to the extent that the image is real-- it is satire after all). Having multiple items in the box would decrease the accuracy not only because of items touching, but also because the person could cover the box while jostling all the items’ positions. You’d have to count every item before and after their interaction, and they could take 0, 1, or more items. It’s definitely not as simple as I was thinking, you’re right. Still easier than JWO imo but not as easy as the kiosks.

        facial recognition is a thoroughly solved problem, at least in terms of the accuracy that we’re aiming for here

        It’s not clear to me whether it’s easy to take fruit from the bowl without showing your face. It’s certainly possible, but it depends on where the people are approaching from whether it’s likely.