Generative Content Creation - Post 3

For the third assignment in Generative Content Creation, we looked at numerous examples of generative art. It was really amazing to see, what these artists have come up with. Generally simple ideas have been merged with other ideas in unpredictable ways and then could be manipulated again by the viewer.

The assignment involved applying the concepts and theories learned in previous posts on real generative art examples.

With the first assignment we looked into the field of multimedia and new media. Manovich (2001) brought out some good statements and observations in his article. The most intriguing for me was the part where he described how everything is being transformed into computer-mediated form. Every piece of information found on the Internet, be it images, videos, podcasts, music, text or animation, everything consists of ones and zeros. Therefore it could be easily manipulated and as a result made to something different.

The second assignment had us reading articles about generative art, to understand this term better and to get an overview of the background and theories of this type of art. According to Galanter (2003) generative art refers to any art practice where the artist uses a system, such as a set of natural language rules, a computer program, a machine, or other procedural invention, which is set into motion with some degree of autonomy contributing to or resulting in a completed work of art.

Although the system, which is used in the creation of generative art could be anything from natural language rules, a machine or other procedural invention, I guess the main emphasis at least in the light of this course is the computers involvement. As I described previously, all the information in the computers really consists of small particles and these of smaller particles etc, which could be manipulated, changed and altered in many different ways. If the systems and programs are created which use this data to create something new, attractive and interesting, then generative art is created.

Some interesting examples of generative art practices:

Jörg Pininger is a musician, poet and media artist. The application he created for iPhone is a mix of all of his talents. As described on his website the app "abcdefghijklmnopqrstuvwxyz" is a sound toy, a performance tool and an art work in its own right. "You can play with the letter-creatures and watch and listen how they interact with each other or use them to produce soundscapes like you would with an electronic musical instrument. "abcdefghijklmnopqrstuvwxyz" blends art, biology, fun and physics to create a unique, dynamic and interactive sound ecology" (joerg.piniger.net).

Pininger's application is a good example of generative art, as it has all the characteristics of generative art, complex systems and allows manipulation by the user. The user can choose how to interact with the application. Each order gives a feedback and results in new sound or visual pattern on the display. The sounds can be formed into generative music and the lines, created by the flying letter, could form a digital painting.

This is an iPhone application made to imitate the creation of Jackson Pollocks paintings. Jackson Pollock was mentioned in several articles which discussed the meaning of generative art. Galanter argued, whether Pollock could be called a generative artist or not, as his techniques of painting were rather random that systematized.

http://www.bestiario.org/research/flow/

This application represents the chronology of tagging process on wikipedia articles Santiago Ortiz and his team have been selecting for their research. This application uses the data available in the Internet and combines it into a visually attractive and informative systematic form. By moving the arrow over the graph, each sector lights up and the information about this research topic could be seen.

The second example from Ortiz also uses the data from the Internet. It is a tridimensional scheme, which represents the strength of relations between cities from searches on google. The user can turn the globe and look at the different cities, their coordinates and the results from Google. The methodology of the generation process is described as well.

http://bestiario.org/research/citydistances/

To conclude, the topic of generative media was new for me. It was interesting to see how the art, technology and information connect to each other and create amazing artwork. Some of the artworks and their intentions still remained a little vague for me but probably it takes time and practice to understand this topic a little better.

Galanter, Philip. 2003. What is generative art? Complexity theory as a context for art theory. In In GA2003–6th Generative Art Conference http://www.generativeart.com/on/cic/papersGA2003/a22.pdf.

Manovich, Lev. 2001. The Language of New Media. Massassuchets: MIT Press. http://www.manovich.net/LNM/Manovich.pdf

Generative Content Creation - Post 2

This post concentrates on the topic of generative art. The term generative art was confusing to me at first, but after reading Galanter's (2003) article I got a more clear idea of generative art

Galanter gives a definition to the term of generative art:

"Generative art refers to any art practice where the artist uses a system, such as a set of natural language rules, a computer program, a machine, or other procedural invention, which is set into motion with some degree of autonomy contributing to or resulting in a completed work of art." (Galanter, 2003).

Five years later Galanter improved his definition a little but basically the core meaning remains:

"Generative art refers to any art practice where the artist cedes control to a system that operates with a degree of relative autonomy, and contributes to or results in a completed work of art. Systems may include natural language instructions, biological or chemical processes, computer programs, machines, self-organizing materials, mathematical operations, and other procedural inventions." (Galanter, 2008).

In Galanter's article "What is generative art" he describes the activities, which are a part of todays contemporary generative art. These are for example electronic music, computer graphics and animation, industrial design and architecture. All of these activities use computer systems to create a complete work of art. Galanter believes the systems to be the most important part of generative art. "The key element in generative art is then the system to which the artist cedes partial or total subsequent control," he says (2003).

The systems which can not be easily or not at all comprehended by the scientists, but which seem to have an order are called complex systems. Galanter describes complex systems like this:

"Complex systems typically have a large number of small parts or components that interact with similar nearby parts and components. These local interactions often lead to the system organizing itself without any master control or external agent being "in charge". Such systems are often referred to as being self-organizing."(Galanter, 2003).

Another systems Galanter analyzes are chaotic and random systems. He believes chaotic systems to be a part of complex systems. Galanter brings out examples such as weather, which is a complex system that is not very easily comprehendible, yet it is a system where each small particle is dependent on others and vice versa. Galanter strictly says that chaotic systems are not the same as random systems. The weather example proves it well.

Corcuff (2008) describes generative art a little differently and also brings the subjects of chance and unpredictability into the picture. So if to compare Galanter's and Corcuff's articles it gets kind of mixed up. If Galanter strictly demands the usage of systems in the generative art and Corcuff describes chance then they do not match completely. Galanter does not think that Jackson Pollock's works should be considered as generative, at the same time Corcuff mentions Pollock in her article. Therefore it can be assumed that she takes Pollock as a generative artist.

But if to look at Corcuff's article, what is chance in the concept of generative art. Is it actually a system or is it not? In one hand for example if the dice are used, it is still a system, the predictability can be calculated and possible results even if there are millions can be predicted. Or is the chance just so unpredictable and complex that it could be called chaotic?

In his article "What is Complexism?" Galanter (2008) describes the complexity theory which he believes to be the core component of generative art. Complexism in his words is a highly disordered system which seems chaotic. He suggests that complexism is the next step from modernism and postmodernism. He compared the three, explained their characteristics and differences.

It could be seen that complexism is a part of art evolution, which follows modernism and postmodernism. When the modernism involved a concrete system, the fixed way of doing things, authority and hierarchy, then postmodernism resented modernism and did completely the opposite. Complexism in the other hand is again another wave of difference. But it seems to have grown up a bit. Instead of total collapse, no truth and randomness, complexism in taking more into account the feedback, generative networks and co-evolution. Although the generation of art is seemingly chaotic, it still leaves an impression of higher meaning and goals.

As always, art represents the thoughts, dreams, desires and resistance of the creative elite of the particular era. In general, generative art could be considered as obscure or chaotic, meaningless even. But as I could understand, in this case, it is not only about the art piece itself but also the system, which was developed for making the art piece.

Corcuff, Marie-Pascale. 2008. Chance and generativity. In GA2008, 11th Generative Art Conference, 189-199. http://www.generativeart.com/on/cic/papersGA2008/16.pdf.

Galanter, Philip. 2003. What is generative art? Complexity theory as a context for art theory. In In GA2003–6th Generative Art Conference http://www.generativeart.com/on/cic/papersGA2003/a22.pdf.

Galanter, Philip. 2008. What is Complexism? Generative Art and the Cultures of Science and the Humanities. In GA2008, 11th Generative Art Conference, 151-167 http://www.generativeart.com/on/cic/papersGA2008/13.pdf.

Generative Content Creation - Post 1

POST_1 - Students must read the articles (Weeks 44 and 45), posting a critical review (750 words) of one or several of these essays in this online forum. This post will be later used in the first part of the final essay.

Critical review of "The Language of New Media" Chapter I - "What is New Media?" by Lev Manovich

Manovich says that the popular definition of new media identifies it with the use of a computer for distribution and exhibition, rather than with production. He thinks that it is too limiting to consider texts and photographs distributed with the use of computer as new media, and the same texts and pictures distributed in books as not. He thinks that computer either used for distribution or production, influences (or does not influence) the culture the same way.

The computer revolution we are experiencing today is nothing ever seen before. If the emergence of printing machines influenced the distribution of texts and the invention of photography influenced the production of still images, then computers affects all types of media - texts, still images, moving images, sounds, etc.

Manovich brings out an interesting idea that today, all of our culture is being shifted into computer mediated form. Everything from books, movies, photos can be produced, distributed and communicated through computers. He looks at the two parallel paths which both lead to the development of a computer as we know it today. The first path is the convergence of computing and development of calculators, the other is the convergence of media technologies. It is interesting to realize, that everything we experience while using computers are actually numbers and mathematics. Every piece of information has its numerical representation which could be understood by the computers in order for them to create content.

In the chapter of "How Media Became New" he goes through the historical inventions and developments which are all a prerequisites to developing computers. Here he describes the trajectories of computing and media technologies. He said that For a long time the two trajectories ran in parallel without ever crossing paths. When finally in just less than 70 years ago the two paths meet, Manovich says that the media becomes new media. Basically it can be said that new media was born by merging computing technologies with media technologies. Calculators with cameras or printing machines.

Manovich describes the principles of new media, which can not be used for characterizing old media. These are:

1. Numerical representation
2. Modularity
3. Automation
4. Variability
5. Transcoding

Numerical representation means that all new media objects, whether they are created from scratch on computers or converted from analog media sources, are composed of digital code; they are numerical representations.

Modularity suggests that every media element consists of smaller parts like pixels, polygons, voxels, characters or scripts. The small particles form together a media element such as a still image, music, text etc. These media elements could be used together to make a film clip for example, which is again another media form. While modulating all these media elements and changing their purposes, the all the elements still stay the same and their identity remains.

The principles of numerical representation and modularity together allow another principle to emerge - automation. Many operations of media creation, manipulation and access could be done without human help. The texts and pictures could be automatically corrected by the software. Automation is used in creating 3D effects in movies and computer games, also in creating new virtual objects from scratch. All this knowledge is programmed into computers by numerical representation and modularity. Computers logically assume how every element fits into the larger picture.

Variability of new media is also derived from principles 1 and 2, but is also closely connected to principle 3 - Automation. While old media involved the industrial development of identical copies of books for example, then new media can be characterized by variability and have many different versions.

Manovich says that new media can be seen as consisting of two layers - cultural layer and computer layer. It means that in one way the content of new media can be seen by humans as a collection of images, which could be interpreted as some kind of a narrative or comprehensive content, in the other hand the computer "sees" the same content as numbers. It is again interesting to see how computers and numerical representation can form the media into something which could be easily understandable for humans.

Manovich's views on new media and its principles give a logical and intriguing overview of the essence of computerization and new media. His theories although from almost ten years ago still illustrate the ways media and computer technologies are developing to this day. As he stated, the principles 1 and 2 are the prerequisites for principles 3-5. Therefore it could be that ten years from now, some more principles will emerge to characterize new media or even produce a newer media.