Generominos (Kate Compton)

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Generominos is a deck of cards designed to help the user think of possible generative art and visualization projects. Some of the cards describe input types (words, images, geographical locations, etc); others describe output formats (3D printed shapes, light changing glass, and so on); and then there are a number of cards that describe ways of transforming one type of data into another. The ideas generated would be suitable for lots of applications, from alternative game controllers to computational-creativity crafts to data visualizations to museum installations.

There are additional project modifiers that suggest purposes for the project (making a creative activity for a senior center, for instance, or put it someplace where no humans can see it).

The cards make a cool teaching (or self-teaching) tool, both around process — how might you change one kind of data into another? — and about specific techniques. Kate has a wide experience with generative art forms in both physical and digital space, which means she includes ideas like “express your output in colored fire” or “attach a webcam to a microscope to observe microbes moving” or “get ocean condition data from NOAA’s API”. Even with a fair amount of experience in related spaces, I found a shuffle through the cards suggested a lot of possibilities I hadn’t considered. So it’s an interesting place for beginning-to-intermediate users to start thinking about generative art design. It also provides a bit of framework for more advanced users: you can add your own cards as you think of new methods and inputs, and then play with how those might generate interesting new combinations.

The flip side of this: the cards may suggest a cool project that would be prohibitively difficult or expensive to build at home, or that would require a dive into new code or algorithms to realize. And in some cases, a little more context might be useful. For instance, the card on word2vec accurately explains that you put a word in and get a vector out, but there’s not enough room on the card to talk about the ways word2vec is often used to get from one input word to another, or to calculate analogies.

So actually building a project based on these ideations is possibly not a beginner-level task; or, to be more precise, the cards may not give enough information for a beginner-level user to tell which concepts would be accessible enough for them to implement from scratch. One might need to do some additional research into particular techniques, or be encountering the cards in a classroom or workshop context.

Bonus recommendation: Rich Vreeland gave some great talks at the AI Summit this year about the procedural music for Mini Metro and about sonification in general as a way of understanding data (instead of or alongside visualization). If you happen to have GDC Vault access for 2018, that material is definitely worth checking out.

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