3 ms·
interesting that one of the uses of NN here is to shrink the amount of storage required per product in the product recognition DB -- compression is a neat appli
by awinter-py 6y ago
interesting that one of the uses of NN here is to shrink the amount of storage required per product in the product recognition DB -- compression is a neat application of NN that generally follows from recognition / synthesis tricks, and will matter a lot on mobile.
I'm wondering if 'on device' is an exaggeration. The post is saying 64 bytes per product, and a DB of millions of products, but the video is showing product details, prices, and a box image. I wonder if once it identifies the product it then loads metadata from ze cloud?
- anoncareer0212 6y ago'it had to load an image from the cloud' sounds much more like a nitpick than 'it recognized the product locally' sounds like an exaggeration
- awinter-py 6y agoit's a spectrum, right? 'on-device' is a big claim with different implications if you're thinking about this as an NN problem or a privacy problem. Loading an image from the cloud = sending telemetry on your supermarket shopping to a giant ads company.