The DeepDream software, originated in a deep convolutional network codenamed "Inception" after the film of the same name,[1][2][3] was developed for the ImageNet Large-Scale Visual Recognition Challenge (ILSVRC) in 2014[3] and released in July 2015.

[6][7] After Google published their techniques and made their code open-source,[8] a number of tools in the form of web services, mobile applications, and desktop software appeared on the market to enable users to transform their own photos.

[10] However, once trained, the network can also be run in reverse, being asked to adjust the original image slightly so that a given output neuron (e.g. the one for faces or certain animals) yields a higher confidence score.

[11] However, after enough reiterations, even imagery initially devoid of the sought features will be adjusted enough that a form of pareidolia results, by which psychedelic and surreal images are generated algorithmically.

[20] In 2017, a research group out of the University of Sussex created a Hallucination Machine, applying the DeepDream algorithm to a pre-recorded panoramic video, allowing users to explore virtual reality environments to mimic the experience of psychoactive substances and/or psychopathological conditions.

[21] They were able to demonstrate that the subjective experiences induced by the Hallucination Machine differed significantly from control (non-‘hallucinogenic’) videos, while bearing phenomenological similarities to the psychedelic state (following administration of psilocybin).

[23] In 2022, a research group coordinated by the University of Trento "measure[d] participants’ cognitive flexibility and creativity after the exposure to virtual reality panoramic videos and their hallucinatory-like counterparts generated by the DeepDream algorithm ... following the simulated psychedelic exposure, individuals exhibited ... an attenuated contribution of the automatic process and chaotic dynamics underlying their decision processes, presumably due to a reorganization in the cognitive dynamics that facilitates the exploration of uncommon decision strategies and inhibits automated choices.