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Fathom Information Design
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Generative Science Fiction
In early 2022, the team was talking about generating imaginary science-fiction book covers. Paul started some sketches of this generator, and after a few iterations of the titles and cover art for these books, he had a catalog. As the team reviewed the catalog, with books such as ‘Situation Under A Mausoleum’, ‘Courtyard 15’, and ‘New York Heliosphere’, we mused that we should generate the text of the books themselves.
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Generative book covers
This side project is an exploration of lo-fi generative art. My initial idea was to spin up titles for speculative novels  —  a serendipity engine for an imaginary bookshelf. Often, machine learning is used to mimic style and syntax when working generatively with text, but I was curious to see where a looser and less sophisticated process might lead.
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Kicking off 2022
This was originally intended to be a spring 2021 e-mail, which became a summer update, then it was gonna be “goodbye to our intern” in August, then part of it was spun out as its own post in October. Finally it was gonna wrap up the year and now… here we are to kick off 2022! (On the 25th day of January.)
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Building Tools for the Next—and the Current—Pandemic
For years, Pardis Sabeti has tried to get funding to build the necessary tools to mitigate the “next pandemic.” On the front lines of the Ebola outbreak in 2014, she saw firsthand all the ways in which institutions and infrastructure broke down. Most simply, the time to act is not during a crisis — when people are frightened, institutions are stressed, and the day-to-day is itself exhausting. The results are predictable: a haphazard response, money suddenly flowing to all the wrong places, and substantial inequities where the vulnerable become only more so.
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Twenty Twenty…
To navigate the strange territory of the past year, which included learning to collaborate with team members 5,000 miles away, keeping 10,000 students safe from COVID-19, and balancing time with our families, pets, and plants, we did what we do best: we iterated.
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