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dmstfctn – Fango 1000

Fango 1000 is a fully onchain multiplayer game by artist duo dmstfctn where players compete for narrative control. The game is set around a Middle Ages Italian village where a trove containing a thousand chronicles have suddenly appeared inside a Monastery. Each chronicle describes how humans from another time train a mysterious “machine intelligence” for an unknown task. Players join one of three factions with conflicting worldviews and compete to tell the best story about what the “intelligence” may be and what role it may hold in future societies by interpreting the information found in the chronicles. The best stories will be pinned to a door and last forever, the worst stories will be buried under mud.

The chronicles contain a record of actions generated by thousands of players of a separate AI training game called Godmode Epochs, developed by dmstfctn in 2023. As such each play-through of Godmode Epochs constitutes a factual dataset to be used in the universe of Fango 1000.

Fango 1000 is developed by dmstfctn together with Paul Seidler using MUD, an open-source framework for onchain development. As an onchain game, the game’s rules, state and data—in other words, the whole game, excluding the interface visible to players—are executed or stored through the blockchain rather than relying on a centralized gaming server.

The game is a toy implementation of the ideas hypothesised in the essay Large Lore Models (0xPARC, 2023) written by dmstfctn, Eva Jäger and Alasdair Milne. The essay proposes the basic configuration of a tool—a Large Lore Model, or ‘LLoreM’—able to facilitate collective and emergent narratives in fully onchain simulations. A LLoreM would link an onchain record of actions generated within a simulation or game to the stories told by its users or players. The function of this design is to maximise the affordances of a blockchain’s immutability while preserving the inherent mutability and contestability of human narratives. A LLoreM also offers alternatives to automated text generation systems like Large Language Models, emphasising instead the creative potential of collective human storytelling.

Play on: fango1000.dmstfctn.net

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