The Python code etched into the plexiglass above this image is excerpted from openpilot, an open source driving agent. The software communicates with a vehicle’s on-board diagnostics adapter to control the accelerating, braking, and steering actuators in most new car models. openpilot is claimed to be equivalent in performance to Tesla’s Autopilot.

The tin friction toy in the photograph, circa 1950, was manufactured by ALPS of Japan. A previous owner replaced the toy’s original human driver with a robot.

The Python code etched into the plexiglass above this image is excerpted from Xvision, a chest X-ray analysis application for TensorFlow that relies on deep learning and a convolutional neural network.

The 1940s tin friction toy in the photograph was manufactured by Lupor Metal Products of New York City.

The Python code etched into the plexiglass above this image is excerpted from TensorRec, a framework to create custom recommendation algorithms for TensorFlow using deep neural networks. TensorRec was developed by a former senior engineer from Spotify.

The Zoltan toy in the photograph was produced by FAO Schwarz and popularized in the movie Big.

The Python code etched into the plexiglass above this image is excerpted from Anki’s Desktop Security Guard application for its Cozmo robot. The application learns the faces of your friends and trusted colleagues. Cozmo then scans its environment. When it detects a face it doesn’t recognize, it sets off an alarm.

The wind-up toy in the photograph was manufactured in 1956 under the name Ratchet Robot by the TN Nomura Corporation of Tokyo, Japan.

The Python code etched into the plexiglass above this image is excerpted from Deep Learning Neural Network for Chaotic Systems, an application designed to predict the pocket a ball will land in during a game of roulette.

The tin toy in the photograph is Roulette Man, manufactured by the Plaything toy company of Japan in the 1960s.

The Python code etched into the plexiglass above this image was excerpted from Google’s Exoplanet ML software, a neural network built to discover exoplanets (i.e., planets beyond our solar system) in light curves. The Exoplanet project is a collaboration by NASA and Google’s AI research team, and relies on data from the Kepler Space Telescope. This software successfully uncovered Kepler-90i, a rocky planet 2,545 light years from Earth.

The wind-up toy in the photograph was manufactured by Chucklesnort Robots and is a tribute to the tin space toys of the 1950s and 60s.

The code excerpt etched into the plexiglass above this image was submitted by a Moscow-based contestant in response to a 2017 challenge from the United Kingdom’s Defence Science and Technology Laboratory. The challenge was to create software to label objects in satellite images, quickly and accurately. Each contestant was given satellite images covering a one-square-kilometer region and was challenged to identify and label ten structures in the shortest time. An application like this can help one country track the location of other countries’ mobile missile launchers. This code relies on a convolutional neural network.

The cast iron toy in the photograph is of unknown provenance.