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Generative AI tool based to convert news/topics to comedy routines based on current political comedy routines present.
ai-technologyeducation
github.com/unna97/audio-annonation ↗ github.com/unna97/reclist ↗
I am making an AI tool that produces comedy routines for a given topics with news articles given. The first step would to produce analysis of the present political routines i.e topics they cover, demographic they appeal to, "funniness" of the jokes.
I hope to learn how to communicate interestingly as well as effectively especially with respect to politics.
I have created the annotation app and have some labelled data(although not public): https://github.com/unna97/audio-annonation
I have been an ML engineer and data scientist for a few years now. I have also dabbled with generative AI technologies and have worked on open source ML libraries such as reclist (https://github.com/unna97/reclist).
No displayed figures preserved for this project.
Season totals as displayed on the platform's public accounting — not a statement of amounts paid out. V2 = Venus sales + Venus extras. The original page also broke each season down by fund drive and showed an Available (unclaimed) balance; that level of detail survives only on the preserved snapshots.
Leaderboard page (offline): https://artizen.fyi/projects/political-comedy-routine-generation
Wayback: leaderboard page ↗ · Wayback: platform page ↗
Not recovered: creator, tags, funding, drives, submissions, snapshot. Sources: "snapshot" = verbatim Internet Archive page · "platform metadata" = archived artizen.fund page metadata · "leaderboard" = the artizen.fyi public accounting tables · "match catalog" = the platform's public fund-matching catalog (captured 2026-10-15, generated 2026-09-07) · "community catalog" = a June 2026 platform scrape preserved in a community repo.