Artificial imagination

Not to be confused with Hallucination (artificial intelligence).

Artificial imagination is a narrow subcomponent of artificial general intelligence which generates, simulates, and facilitates[1] real or possible fiction models to create predictions, inventions,[2] or conscious experiences.

The term artificial imagination is also used to describe a property of machines or programs. Some of the traits that researchers hope to simulate include creativity, vision, digital art, humor, and satire.[3]

Practitioners in the field are researching various aspects of Artificial imagination, such as Artificial (visual) imagination,[4] Artificial (aural) Imagination,[5] modeling/filtering content based on human emotions and Interactive Search. Some articles on the topic speculate on how artificial imagination may evolve to create an artificial world "people may be comfortable enough to escape from the real world".[6]

Some researchers such as G. Schleis and M. Rizki have focused on using artificial neural networks to simulate artificial imagination.[7]

Another important project is being led by Hiroharu Kato and Tatsuya Harada at the University of Tokyo in Japan. They have developed a computer capable of translating a description of an object into an image, which could be the easiest way to define what imagination is. Their idea is based on the concept of an image as a series of pixels divided into short sequences that correspond to a specific part of an image. The scientists call this sequences “visual words” and those can be interpreted by the machine using statistical distribution to read an create an image of an object the machine has not encountered.

The topic of artificial imagination has garnered interest from scholars outside the computer science domain, such as noted communications scholar Ernest Bormann, who came up with the Symbolic Convergence Theory and worked on a project to develop artificial imagination in computer systems.[8] An interdisciplinary research seminar organized by the artist Grégory Chatonsky on artificial imagination and postdigital art has taken place since 2017 at the Ecole Normale Supérieure in Paris.[9]

  1. ^ Abramson, J.; Ahuja, A; Carnevale, F. (21 November 2022). "Improving Multimodal Interactive Agents with Reinforcement Learning from Human Feedback". p. 26. arXiv:2211.11602 [cs.LG].
  2. ^ Allen, K.R.; Lopez-Guevara, T.; Stachenfeld, K.; Sanchez-Gonzalez, A.; Battaglia, P.; Hamrick, J.; Pfaff, T. (1 February 2022). "Physical Design using Differentiable Learned Simulators". arXiv:2202.00728 [cs.LG].
  3. ^ "How Generative AI Can Augment Human Creativity". Harvard Business Review. 2023-06-16. ISSN 0017-8012. Retrieved 2023-06-20.
  4. ^ Thomee, B.; Huiskes, M.J.; Bakker, E.; Lew, M.S. (July 2007). "Visual information retrieval using synthesized imagery". Proceedings of the 6th ACM international conference on Image and video retrieval. ACM. pp. 127–130. doi:10.1145/1282280.1282303. ISBN 9781595937339. S2CID 11199318. Retrieved 19 December 2023.
  5. ^ Audio Content Transmission by Xavier Amatriain & Perfecto Herrera, "Publications" (PDF). Archived from the original (PDF) on 2007-01-06. Retrieved 2007-12-22.
  6. ^ Hypertext and “the Hyperreal” by Stuart Moulthrop, Yale University http://portal.acm.org/citation.cfm?doid=74224.74246
  7. ^ Learning from a random player using the reference neuron model in the Proceedings of the 2002 Congress on Evolutionary Computation, 2002. https://ieeexplore.ieee.org/document/1007019/;jsessionid=BBE5A0E379BB9B061933356B7461B639?arnumber=1007019
  8. ^ Twentieth-Century Roots of Rhetorical Studies, by Jim A. Kuypers and Andrew King, 2001. published by Praeger/Greenwood, page 225.
  9. ^ Postdigital Artificial Imaginationhttp://postdigital.ens.fr