- 📕 Understanding word vectors
- 🍿 What is word2vec, Color Vectors
- 📚 2018 Universal Sentence Encoder paper
- 💻 Universal Sentence Encoder - tensorflow.js
- 💻 Universal Sentence Encoder ml5: comparison grid
- 💻 Universal Sentence Encoder ml5: match intent
- 📚 The Unreasonable Effectiveness of RNNs and Visualizing and Understanding Recurrent Networks by by Andrei Karpathy
- 📚 Rohan & Lenny #3: Recurrent Neural Networks & LSTMs
- 📚 Understanding LSTM Networks by Christopher Olah
- 🍿 Sunspring
- 🎨 Double Agent by Simon Biggs (Drawing)
- 🎨 Four Experiments in Handwriting with a Neural Network (Drawing)
- 📖 10 things artificial intelligence did in 2018 by Janelle Shane (Text)
- 📖 Writing with the Machine
- 📋 ml5 charRNN reference, 💻 ml5 charRNN examples, 💻 ml5 charRNN training in colab, training-charRNN repo
- 🍿 Interactive Drawing with SketchRNN
among the reasons I use large pre-trained language models sparingly in my computer-generated poetry practice is that being able to know whose voices I'm speaking with is... actually important, as is being understanding how the output came to have its shape - @aparrish
- 📚 Attention is All You Need - Original "Transformer" paper from 2017
- Also Neural Machine Translation by Jointly Learning to Align and Translate -- Attention paper from 2014
- 📕 Allison Parrish Large Language Model Tweet Thread
- 🍿 On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜
- 🍿 Generative Text Training with GPT-2 from RunwayML
- 🍿 AI Language Models & Transformers - Computerphile
- 📚 The Next Word: Where will predictive text take us?
- 📚 The Supply of Disinformation Will Soon Be Infinite
- 💻 GPT-2 RunwayML + p5.js template on Glitch
- 💻 Hugging Face
Reading list thanks to @advadnoun!
- 📕 A brief history of the CLIP art scene
- 📚 Feature Visualization
- 📚 Illustrated Transformer
- 📚 OpenAI CLIP blog post
- 📚 Taming Transformers VQGAN blog post
- 💻 The Big Sleep BigGANxCLIP
- 💻 Aleph-Image: CLIPxDAll-E
- 🚨 Watch this video tutorial! (this is technical info needed for the examples). Of course if you already know this material, you can skip.
- 🔢 This is found in a group, maybe pick just one to check out!
- 🍿 Additional video if you have a particular interest and want to do a deeper dive.
- 📕 Required reading! Let's make sure we all have read this.
- 📚 Optional additional reading for a deeper dive.
- 💻 Code examples here!
- 📈 Class presentation slides
- 🔗 Extra reference material / link