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week8-diynn/README.md

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 1. Watch [Machine Learning for Human Creative Practice](https://vimeo.com/287094397), Dr. Rebecca Fiebrink at Eyeo 2018. Write a response to the following question posed by Dr. Fiebrink:
    - How can machine learning support people's existing creative practices? Expand people's creative capabilities?
 2. Dream up and design the inputs and outputs of a real-time machine learning system for interaction and audio/visual performance. This could be an idea well beyond the scope of what you can do in a weekly exercise.
-3. Open api chat p5 sketch: https://editor.p5js.org/yining/sketches/cnlmIOoL9
+3. Open api chat p5 sketch, text generation: https://editor.p5js.org/yining/sketches/cnlmIOoL9, text to image: https://editor.p5js.org/yining/sketches/ubpprBEg3
 4. Create your own p5+ml5 sketch that trains a model with real-time interactive data. This can be a prototype of the aforementioned idea or a simple exercise where you run this week's code examples with your own data. Here are some exercise suggestions:
    - Try to invent more elegant and intuitive interaction for collecting real-time data beyond clicking buttons?
    - What other real-time inputs might you consider beyond mouse position, image pixels, or face/pose/hand tracking? Could you use real-time sensor data?