Artificial imagination , also called synthetic imagination or machine imagination, is defined as an artificial simulation of human imagination by a general purpose computer or a special or artificial neural network.
The term artificial imagination is also used to describe the properties of machines or programs. Some traits that researchers expect to simulate include creativity, vision, digital art, humor, and satire.
Artificial imagination research uses tools and insights from various fields, including computer science, rhetoric, psychology, creative arts, philosophy, neuroscience, affective computing, Artificial Intelligence, cognitive science, linguistics, operations research, creative writing, probability and logic.
Practitioners in the field are examining various aspects of Artificial imagination, such as Artificial (visual) imagery, Artificial (aural) Imagination, modeling/content filtering based on human emotions and Interactive Search. Several articles on the topic speculate on how artificial imagination can evolve to create an artificial world. "People may be comfortable enough to escape the real world".
Some researchers like G. Schleis and M. Rizki have focused on using artificial neural networks to simulate artificial imagination.
Another important project is headed by Hiroharu Kato and Tatsuya Harada at the University of Tokyo in Japan. They have developed computers that are able to translate the description of objects into images, which can be the easiest way to define what an imagination is. Their idea is based on the concept of the drawing as a series of pixels divided into a short sequence that corresponds to a particular part of an image. Scientists call this sequence "visual words" and they can be interpreted by machines using statistical distributions to read creating images of machine objects yet to be encountered.
The topic of artificial imagination has attracted the interest of scholars outside the domain of computer science, such as renowned communication expert Ernest Bormann, who came up with the Symbolic Convergence Theory and worked on a project to develop artificial imagination in computer systems. An interdisciplinary research seminar on artificial imagery and postdigital art has been going on since 2017 at the Ecole Normale Supérieure in Paris.
How to Build a Mind: Toward a Machine with Imagination by Igor Alexander is an academic book on this topic; Artificial Imagination , roman ÃÆ' clef, is a non-academic book that should be written by an artificial imagination system.
Video Artificial imagination
Custom Made Imagination
Typical applications of artificial imagination are for interactive search. Interactive search has been developed since the mid-1990s, accompanied by the development of the World Wide Web and search engine optimization. Based on the first request and feedback from the user, the searchable database is reorganized to improve the search results.
How artificial imagination can contribute to interactive search
Artificial imagination allows us to synthesize images and develop new images, whether in the database, regardless of its existence in the real world. For example, the computer shows results based on answers from the original request. The user selects some relevant images, and then the technology analyzes these options and rearranges the image to fit the request. In this process, artificial imagination is used to synthesize selected images and to improve search results with additional relevant synthesis drawings. The technique is based on several algorithms, including the Rocchio algorithm and the evolutionary algorithm. The Rocchio algorithm, locating the point of interest near the relevant instance and away from the irrelevant example, is simple and works well in small systems where databases are arranged in a particular rank. evolutionary synthesis consists of two steps: standard algorithm and standard algorithm improvement. Through user feedback, there will be additional images synthesized so that it matches what the user is looking for.
Maps Artificial imagination
General Artificial Imagination
Artificial imagination has a more general definition and wide application. The traditional fields of artificial imagination include the visual imagination and aural imagination. In general, all actions to form ideas, images, and concepts can be attributed to the imagination. So, artificial imagination means more than just producing a graph. For example, moral imagination is an important research subset of artificial imagination, although the classification of artificial imagination is difficult
Moral is an important part of human logic, while artificial morale is important in artificial imagination and artificial intelligence. The general criticism of artificial intelligence is whether humans should be responsible for errors or machine decisions and how to develop a well-behaved machine. Since no one can provide a clear description of the best moral rules, it is impossible to create machines with generally accepted moral rules. However, recent research on artificial morals avoids a moral definition. Instead, machine learning methods are applied to train machines to mimic human morals. Because data on moral decisions of thousands of different people are considered, trained moral models can reflect widely accepted rules
Memory is another area of ​​artificial imagination. Researchers like Dr. Aude Oliva has done extensive work on artificial memory, especially visual memory. Compared to the visual imagination, visual memory focuses more on how machines understand, analyze, and store images in a human way. In addition, characters such as spatial features are also considered. Because this field is based on the brain's biological structure, extensive research on neuroscience has also been conducted, which makes it a major intersection between biology and computer science.
References
Source of the article : Wikipedia
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