Every psychonaut knows that the things you see when you take psychedelics, widely known as “visuals,” are a crucial part of the experience. The intensity of one’s visuals might even be used to gauge the potency of a trip (“I was tripping so hard, the visuals were insane!”). Whether on acid, shrooms, DMT, ketamine, or MDMA, you may see visuals in the world around you, behind closed eyes, or just in your imagination. No matter the specifics, visuals are likely to leave a lasting impression—yet they are stubbornly difficult to discuss or represent after the fact.
For decades, artists like the married couple Alex and Allyson Grey have created stunning “visionary art” that mirrors and builds upon spiritual visions reached through psychedelic states. In recent years, a Reddit community called /r/Replications has coalesced around the goal of “replicating” such visuals and sensory experiences with the aid of modern technology. These efforts reached new heights with a video uploaded this year by Josie Kins, a psychedelic researcher who is an administrator of /r/Replications, and founded a related project called the Subjective Effect Index.
The mesmerizing video features a reel of computer-generated images of faces and “entities” that strongly resemble the beings many people report encountering after taking DMT. These images were produced by an AI model that Kins and a team of collaborators created using the StyleGAN v2 network. Yet their intent was never to create DMT faces—the AI began to do that on its own after analyzing a wide array of visuals.
The team “trained” this model by feeding it a data set of more than 4,000 works of psychedelic and visionary art sourced from all over the Internet. After processing this art and identifying its common features and patterns, the AI—which initially only seemed to output geometric and patterned visuals—began creating artwork with facial features resembling DMT entities (supposed beings that Terrence McKenna referred to as “machine elves”). Roughly one in every thirty of the AI’s output contains these psychedelic faces.
This result surprised Kins and her team, who didn’t expect their algorithm to replicate a specific, recognizable form of visuals with such accuracy. “Essentially, the system worked much better than we initially anticipated,” Kins tells DoubleBlind. The AI had this surprising creative “breakthrough” about one year into its training after the team expanded the data set of art it could learn from. This was thus an adventure in machine learning, a promising field in which computers leverage data to continually improve at tasks they are given, such as mimicking human art or speech.
StyleGan v2, the machine learning network Kins’ team used to create this DMT art, was superseded by StyleGan v3 in November 2021. The team is already hard at work on building a new model with this updated framework, which Kins expects to be an “exponentially” more powerful tool for generating replications.
Whether made by humans or machines, replications are considered important because they translate subjective psychedelic experiences into a sharable visual medium. Through replications, trips—which are typically quite personal and specific—can be more openly discussed and analyzed.
“The psychedelic experience is extremely valuable and should be recognized as an important aspect of the human experience,” says Kins. “Yet words can only take us so far… Therefore it is crucial that we develop universally understandable methods of conveying and communicating these profound experiences.”
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