Standard Cognition uses its cameras to track individual people in real time as they move around the store (Suswal says the company is not doing any facial recognition), and spot the items they take off the shelves. The company trains its deep neural networks to recognize items in the store, too, in a process that takes about two minutes per item and consists of an employee grabbing the item and doing things like turning it over, putting it behind their back, and placing it in a basket in view of the cameras.

You can see a visual representation of this right when you walk into Standard Cognition’s faux store. Against one wall is a big flat-screen monitor, showing a live video feed of the space with a different colored marker denoting each person; whenever you pick something up, it gets a circle and a label on the screen. A video the company released shows the technology in action, as two people stand in the demo store grabbing items and generally trying to perplex the system.

I grabbed a shopping basket to try it out myself. The results, while a little rough, were still impressive. I wandered down the aisle, placing Nilla Wafers, bottles of Coke, and other items in my basket, then taking some out and leaving them behind. I quickly shoved a can of Red Bull up my shirt in hopes that the cameras would miss it, and loaded up on similar-looking items (a bag of Doritos and a bag of Cheetos, as well as two different kinds of Mrs. Meyer’s liquid hand soap).

When I was done, I walked over to a tablet that showed me a list of all the items Standard Cognition thought I had in my basket. It missed one of my two bottles of Coke and added an additional bottle of soap—things we could edit in the checkout app on the tablet. But the list was mostly correct, and, to my chagrin, it caught that Red Bull, too.

Brandon Ogle, another cofounder and an engineer for the company, says item classification in the demo store is currently correct 98 percent of the time. Standard Cognition is working on it, in part by teaching its computers to identify more products—Ogle says the more items the company has added, the more accurate it has gotten.

It may take a while for autonomous checkout to become the norm in most stores, though. Tom Davenport, a professor at Babson College and coauthor of Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, thinks that we’ll increasingly see such experiences, but he’s skeptical about how quickly this will happen. After all, he says, self-checkout has been around for about two decades in the U.S. and still hasn’t revolutionized the checkout process here.

“I think nobody these days would suggest that becoming a supermarket point-of-sale clerk is a growth industry,” he says. “But they’ve proven remarkably resistant to going away.”