[trimbo]

How do you know there aren't humans on the other side of the cameras doing the item-customer matching?

Go has relatively few stores. Seems like the sort of thing you can still do manually, especially if the model expresses doubt.

[tracer4201]

I went to one of these stores in Seattle on a weekday afternoon with a couple friends. It was literally packed with people. We tried breaking the system by leaving items in random places and exchanging them between us. It still charged me accurately for a couple bottled waters, a sandwich, and some other snacks.

[m463]

Customer "4201, tracer". Troublemaker. Enable customer-specific pricing increases until resolution.

[trimbo]

Again, how do you know there aren't humans on the other side of the cameras/sensors facilitating this?

At the scale they're operating at and the accuracy you point out, to me it's more plausible they're having humans assist.

[nicoburns]

I think they're saying that humans behind cameras likely wouldn't be able to do this accurately.

[trimbo]

Except that cameras in stores have been used for anti-shoplifting for decades. They've been used for more subtle things like monitoring tables at casinos.

I mean, I'm just asking the question how people know for sure Go isn't (at least partly) a Turk. It seems like an obvious thing to ask? But I first came to wonder if there's manual component involved after shopping a few times at Go. When it was busy, it took sometimes well over an hour to get a receipt. When it was empty, it was immediate. How come?

Also, the accuracy is completely anecdotal both ways... at least one person I visited the store with never got billed.

[klyrs]

This is the fun kind of Turing test: tasks where only a computer/mechanized system can succeed.