[ChuckMcM]

I tend to disagree. Assuming they are correct on a larger corpus you can start doing things like "only do face matching on pictures with people in them" and weed out photos in a batch that don't have those three properties.

Watson is a training API rather than say the more fanciful emergent AI type API. More data, the better it gets. It is like Google's voice recognition isn't good because someone coded the magic constants for various accents, rather it is good because Google fed it millions of samples of spoken words and corrects it when they get it wrong.

[qeorge]

Thanks for your comment. This makes sense - I would use Watson to determine which photos have humans at all, and then run those through, e.g., my facial recognition software. But Watson would keep me from having to waste resources looking for faces in photos of trees, for example.

I'm not in this field, so I'm having trouble understanding what use cases / consumer facing features this API unlocks. Your comment is very helpful in that regard.