recently introduced a new menu item called a "chalupa".
The commercials for the chalupa say that it is
"crunchy" and "irresistible", but they
never really explain what a chalupa is. Is a chalupa
more like a taco or a burrito? After pondering this
important question, Ethan and I decided that a computer could
give us the answer.
drove to the local Taco Bell armed with a digital camera and took a
series of photographs of the contents of our value meal. We
captured images of tacos and burritos of all sorts: beef, bean, and
chicken, soft shell and hard shell. We then took a series of
photographs of the mysterious new chalupa.
the neural net on this battery
of sample images of tacos and burritos.
source images of tacos and burritos, we trained a neural net
to distinguish between tacos and burritos. The neural
net does this by establishing a weight for each pixel, summing
the weighted differences across a test image, and comparing
this sum to a threshold value. We found that after
training our neural net with ten taco images and ten burrito
images, it was able to distinguish between new pictures of
tacos and burritos with almost perfect accuracy.
the true challenge: the chalupa test. It turned out that
the chalupa images were almost invariably identified as
"tacos". After four hours of programming and
ten dollars worth of Mexican food, we had our answer: the new
chalupas at Taco Bell are more like tacos then burritos.
neural network sensitivity graph,
lighter colored areas represent pixels that
are most heavily weighted when
distinguishing between a taco and a burrito.
research didn't stop there, however. I immediately thought of
a new question: am I more like a taco or a burrito? I
took a series of ten images of myself making various facial
expressions and we passed them on to the neural net. Of these
ten images, eight were identified as "burrito" and only
two as "taco". Once again, the computer provided an
answer: my composition is roughly 80 percent burrito and twenty