An In-N-Out employee taking your order and a traffic cone, your Tesla thinks they’re the same.
Reddit user BinaryShrub was in line at his local Anaheim In-N-Out, ready to tell his order to the In-N-Out employee making the trek through the long line of waiting cars, when he noticed how his Tesla saw the In-N-Out employee. His Tesla Model 3 didn’t “see” this stationary, white and red object as a person but a regular traffic cone, instead.
Here’s his hilarious photo making the rounds on /r/funny below.
It’s the regular practice from a bygone car hopping era for In-N-Out employees to take orders directly from customers when drive-thru lines get too long. It not only adds a personal touch to your order, but it speeds up the line just a tad.
While Tesla’s suite of eight cameras, a dozen sensors, and one forward facing radar is a champ when recognizing moving objects, the network has a long way to go classifying literally everything it sees. A stationary fast food worker, this red object with a white top, a traffic cone is the best that this Tesla could come up with.
Teslas have a history of classifying people as cones. According to Inside EVs, this Tesla saw a kid standing on the side of the road as a traffic cone, too.
How Tesla sees stationary objects it does or doesn’t know is quite fascinating. According to Tesla engineer Andrej Karpathy, Tesla relies on the millions of Teslas already on the road to learn and label uncommon objects it encounters.
This Tesla asked its neural network on this particular In-N-Out employee and, according to similar images other Teslas saw, classified her as a cone. With millions of Teslas already on the road you’d think Tesla would know what a person is, but the system is not perfect. For one, since In-N-Out is mostly a California thing, a small percentage of Teslas on the neural network ever come across this specific image, a person in an In-N-Out uniform standing perfectly still.
In all likelihood a Tesla employee already caught wind of this anomaly and manually classified this object as a person in the aforementioned neural network.
Able to get you from work to home with no input from you? Sure. But accurately identifying a fast food employee as a sentient being? As of now, not 100 percent.