08_runwayml

Introduction to RunwayML

Objectives

• Become familiar with RunwayML and understand how to run new models in the browser.

Background on RunwayML

• Machine Learning En Plein Air: Building accessible tools for artists by Cristóbal Valenzuela
• Runway: Adding artificial intelligence capabilities to design and creative platforms by Cristóbal Valenzuela, Alejandro Matamala, and Anastasis Germanidis

Resources

• RunwayML.com
• Introductory Guide to ML Lab
• Model Directory
• Model Chaining
• RunwayML YouTube Channel

Related Projects

• Projects Made with RunwayML
• No Machine is an Island by Yuxi Liu and Larissa Pschetz
• Introspectons by Philipp Schmitt

Assignment (Due Monday, Nov 1):

Reading

• Machine Learning En Plein Air: Building accessible tools for artists by Cristóbal Valenzuela
• Runway: Adding artificial intelligence capabilities to design and creative platforms by Cristóbal Valenzuela, Alejandro Matamala, and Anastasis Germanidis

Instructions

1. Pick a model available in RunwayML. Run the model both as a preview and experiment with the "export" option. You can choose a model you worked with in class or a different one. Feel free to try more than one if you like. Consider the following questions:
   • What is this model developed to do?
   • Can you write a Model and Data "biography" that covers where it came from and what data was used to train it?
   • Describe the results of working with the model, do they match your expectations?
   • Can you "break" the model? In other words, use it in a way that it was intended for and what kinds of results do you get?
2. Document your thoughts on the above questions and your experience working with RunwayML in a blog post. Include screenshots and screen captures of your workflow. Compare and constrast working with RunwayML as a tool for machine learning as related to ml5.js, python, and any other tools explored this semester. Link from the homework wiki.