ARTIFICIAL INTELLIGENCE

The toys we played with as children promised us a future of robots, flying saucers, and fortune-telling automatons. Now, as adults, we discover our future is actually being shaped by a special kind of computer code that can produce artificial intelligence.

This portfolio explores the connection between retro, futuristic toys and cutting-edge computer science. Each photograph of a vintage toy represents an application of artificial intelligence. The lucite pane protecting the photograph is laser-etched with an excerpt of actual machine learning computer code that relates to the toy. The etched letters cast a shadow on the photograph behind them. Each photograph is offered in a limited edition of five prints.

I exhibited this portfolio at the United Nations’ 2019 AI for Good Global Summit in Geneva, Switzerland, and at the 2019 Laguna Beach Festival of Arts.

Self-Driving Vehicles . Framed dimensions: 29 x 50 in, 72 x 126 cm. The Python code accompanying 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.

Self-Driving Vehicles. Framed dimensions: 29 x 50 in, 72 x 126 cm. The Python code accompanying 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.

Cognitive Medicine . Framed dimensions: 29 x 50 in, 72 x 126 cm. The Python code accompanying this image is excerpted from Xvision, a chest X-ray analysis application for TensorFlow that relies on deep learning and a convolutional neural network.

Cognitive Medicine. Framed dimensions: 29 x 50 in, 72 x 126 cm. The Python code accompanying this image is excerpted from Xvision, a chest X-ray analysis application for TensorFlow that relies on deep learning and a convolutional neural network.

Robotics . Framed dimensions: 42 x 50 in, |05 x 126 cm. The Python code accompanying 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.

Robotics. Framed dimensions: 42 x 50 in, |05 x 126 cm. The Python code accompanying 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.

Prediction . Framed dimensions: 42 x 50 in, |05 x 126 cm. The Python code accompanying this image is excerpted from TensorRec, a framework to create custom recommendation algorithms for TensorFlow that incorporates deep neural networks. TensorRec was developed by a former senior engineer from Spotify.

Prediction. Framed dimensions: 42 x 50 in, |05 x 126 cm. The Python code accompanying this image is excerpted from TensorRec, a framework to create custom recommendation algorithms for TensorFlow that incorporates deep neural networks. TensorRec was developed by a former senior engineer from Spotify.

Space Exploration . Framed dimensions: 42 x 50 in, |05 x 126 cm. The Python code accompanying 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.

Space Exploration. Framed dimensions: 42 x 50 in, |05 x 126 cm. The Python code accompanying 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.

Missile Defense . Framed dimensions: 42 x 50 in, |05 x 126 cm. The code excerpt accompanying this image was submitted by a Moscow-based contestant in response to a 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. 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.

Missile Defense. Framed dimensions: 42 x 50 in, |05 x 126 cm. The code excerpt accompanying this image was submitted by a Moscow-based contestant in response to a 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. 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.