00-introduction

Introduction

[ Slides | Sketches ]

Objectives

• Define Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL).
• Learn about the history of machine learning.
• Overview of applications of machine learning, especially for art and design.
• Learn about the tools for machine learning.
• Understand the difference between classification and regression.

Lecture Notes

Tools

• p5.js Website
  • p5.js Reference
  • p5.js Web Editor
• ml5.js Website
  • ml5.js Reference
• TensorFlow Website
  • TensorFlow.js Website

Applications of Machine Learning

Drawing

• Scrying Pen by Andy Matuschak.
• Handwriting with a Neural Net by Shan Carter, David Ha, Ian Johnson, Chris Olah.
• Quick, Draw! by Jonas Jongejan, Henry Rowley, Takashi Kawashima, Jongmin Kim, Nick Fox-Gieg, with friends at Google Creative Lab and Data Arts Team.

Images

• Pix2Pix by Isola, Phillip and Zhu, Jun-Yan and Zhou, Tinghui and Efros, Alexei A.
• Fast Style Transfer in TensorFlow by Logan Engstrom.
• This Repository Does Not Exist on GitHub.
• Stable Diffusion by Stability AI.
  • Stable Diffusion Demo on HuggingFace.
  • Diffuse the Rest Demo on HuggingFace.
• DALL·E by OpenAI.
• DALL·E mini Demo on HuggingFace.

Videos

• Motion Representations for Articulated Animation by Siarohin, Aliaksandr and Woodford, Oliver and Ren, Jian and Chai, Menglei and Tulyakov, Sergey.
• Gen-3 Alpha by Runway.
• Sora by OpenAI.

Arts & Culture

• X Degrees of Separation by Mario Klingemann & Simon Doury.
• Art Palette by Simon Doury & Etienne Ferrier.
• Runway Palette by Artist in Residence at Google Arts & Culture Lab: Cyril Diagne, in collaboration with The Business of Fashion.

Physical Computing

• Objectifier Spatial Programming by Bjørn Karmann.
• Intel Curie Pattern Matching Dress by Kitty Yeung.
• Rock-Paper-Scissors Machine by Kaz Sato.

Texts

• GPT-4 by OpenAI.
  • GPT-2 Demo on HuggingFace.
• Copilot by GitHub.

Playful

• Emoji Scavenger Hunt by Google Brand Studio.
• Giorgio Cam by Eric Rosenbaum & Yotam Mann.
• Thing Translator by Dan Motzenbecker.
• ml5.js Playful Examples by Andreas Refsgaard.

Accessbility

• Creatability from Experiments with Google.
• Be My AI from Be My Eyes.

Supplemental Materials

• What is machine learning? by Karen Hao.
• Algorithmic Accountability: A Primer from Data & Society.
• Seeing Machines Think by Martin Wattenberg and Fernanda Viégas.
• Weird Intelligence by Kyle McDonald.

Video Tutorials

• Learning While Making p5.js with Lauren McCarthy.
• p5.js Web Editor Overview with Cassie Tarakajian.
• Code! Programming with p5.js by Daniel Shiffman.
• Creative Coding for Absolute Beginners by Jack B. Du.

Assignment 1a

1. Create a blog (or a category on a blog) for the course. (You may use any means for publishing your assignments including, but not limited to, a GitHub markdown file, medium post, etc.) This wiki page has resources and information on creating your own blog. Additionally, here is some helpful information on privacy options for your blog.
2. Read A People’s Guide to AI by Mimi Onuoha and Mother Cyborg (Diana Nucera).
3. Creating a blog post documenting and reflecting on the following exercises from A People’s Guide to AI.
   • When you hear the words "Artificial Intelligence", what are the first four things that come to your mind? (p.11)
   • Answer the questions from the "Everyday AI Activity" on pages 23–28 of the A People’s Guide to AI.
4. Add a link to your post on the Assignment 1a Wiki page. You are welcome to post under a pseudonym or alias.