ALEJANDRA VASQUEZ: Hello, my name is Alejandra.
ERICSON HERNANDEZ: And I'm Ericson.
ALEJANDRA VASQUEZ: And we're using
machine learning to find potholes
on the streets of Los Angeles.
ERICSON HERNANDEZ: LA has over 7,400 miles
of roads and freeways.
ALEJANDRA VASQUEZ: That's a lot of roads
and a lot of potholes to fix.
ERICSON HERNANDEZ: Right now, construction workers
have to manually inspect roads for dangerous potholes
and cracks or rely on people calling in tips,
which takes a lot of time.
ALEJANDRA VASQUEZ: While studying at LMU,
we started to see if we could figure out
a faster way to identify potholes throughout the city.
ERICSON HERNANDEZ: First, we needed data.
So we rigged a camera to a car, and we drove around
to capture footage of different roads and freeways.
ALEJANDRA VASQUEZ: Then we used TensorFlow,
Google's open-source machine learning tool,
to develop a model that could quickly identify potholes, road
cracks, and other weird stuff with a high rate of accuracy,
which means workers can spend less time finding potholes
and more time fixing them.