Faces of AI: Visual AlgoRithms

Once upon a time, in ancient times, Creativity was an attribute of the Divinity, and humans often made Arts to celebrate the Divinity.
Then, when human’s reasoning and Skills were Acknowledged, during the Age of Enlightenment, Creativity became an attribute of Individuals. And once with Romanticism, the idea of Genius was born, associated with the notions of Fantasy, Personal struggles, and Disorders.
But, afterward, Creativity has become Democratised, and it is considered a common attribute of every person, being used not only by Artists, but in different problem-solving activities.

Once with scientific and technological developments, the boundaries are pushed even more, and creativity is associated with artifacts, machines.
People describe machines as creative when they have the same creative behaviors of humans, and can generate artworks such as painting, music, poetry, so on.
This has a huge implication not only to the creative industries like media, arts, culture, entertainment, but also to wider society and humanity as well. forced to reflect on our own creativity and uniqueness.
Autonomous non-human beings have intrigued humans for as long as we could imagine that. And the very first ideas can be traced back to 1842 to Ada Countess of Lovelace, celebrated by many as the world’s first computer programmer.

Ada Lovelace not only materialized the concept of an autonomous being that is able to solve challenging problems in the world, she also came up with a language to communicate with the machine. But, she firmly believed that the analytical engine could not think. In her view, only when the machine can originate something, it can be considered as having a mind of itself.

Time has proved that machines can think, and be creative. (Read more about the history of algorithms in our previous article, HERE)

All of this is possible because somehow in old or modern times, an Algorithm was invented. Some sort of set of rules that help us easily navigate an environment full of too much information. And this never endless evolutive process creates, recreates our tempo and perception of human life.

So, let’s start exploring how machine creativity has developed where it is now, and where the future lies.
As we said in previous chapters, we intend to analyse the essential senses of human expression of creativity through Sound, World, Sight but also View and their evolution.
Let’s start with Sight and Vision.

Pioneers of Generative Arts

Throughout history, both practitioners and beauticians in the field of arts have always questioned the genesis of artistic-creative thinking. Hypotheses, theories, studies and millions of opinions and contradictions
But, Harold Cohen gives us something different and unexpectable response to question such as:
How do artists process their information in the creation of artworks?
What are the minimum conditions under which a set of marks functions as an image?
What makes an image evocative?
Harold Cohen was a pioneer in computer art, in algorithmic art, and in generative art and creator of AARON, a computer software program designed to generate art autonomously.
When Cohen started to work with the computer, the interaction was the same with the thought he applied to create his paintings.
The fact that Coding and At follow the same principles via Some standards norms or technique, generate new pictorial composition. It’s amazing how some of the instructions generated unimaginable forms.
The possibility of setting up commands that would enable the machine to make artistic decisions, similar to the creative process of human beings.
Cohen’s work with AARON represented a unique man-machine collaboration, which became popular with science centers as an area of exploration. Over the years Cohen has changed and applied different tactics.
The Relationship between “creator and creature” grew to the next level. Cooperation.
In the 80s, AARON learned to visualize objects in 3D, and in the 90s-to use different colors and shades. His works began to be bought by collectors. The robot’s skill grew every year, and according to Cohen, AARON even surpassed the creator in working with color.

Our recommendation : Article made by  Chris Garcia publish in Computer History Museum: HAROLD COHEN AND AARON—A 40-YEAR COLLABORATION
Like many of the creators, he thought of his opera immortality and the possibilities of the continuity process of generated art after death.
“It would be nice if Aaron could tell me which of them it thinks I should print, but it can’t. It would be nice if it could figure out the implications of what it does so well and so reliably, and move on to new definitions, new art. But it can’t. Do those things indicate that Aaron has reached an absolute limit on what computers can do? I doubt it. They are things on my can’t-do-that list, and I’m aware I may never find a way of getting them off. But how can I know what insights tomorrow may bring?”

His tomorrow is our todays, well let’s take a quick tour of the developments 

Dr. Simon Colton wanted to push further the boundaries to create a machine that can be regarded as a creative artist on its own.
The project is called the Painting Fool.
The Painting Fool processes the information just as an artist may do, by picking up a dominant color palette of his painting subject or reading the day’s headlines that will influence his mood.
You can Try it here http://www.thepaintingfool.com/

Tech companies started to become fascinated about creativity and art and invested in research.  Google engineer Alexander Mordvintsev created the DeepDream program. Initially it was invented to help scientists and engineers to see what a deep neural network is seeing when it is looking in a given image.

More info in GoogleBlog :Inceptionism: Going Deeper into Neural Networks article made by Alexander Mordvintsev, Software Engineer, Christopher Olah, Software Engineering Intern and Mike Tyka

The algorithm has become a new form of psychedelic and abstract art. 

New tendency in Art- inceptionism

In 2015, Deep Dream created a New tendency in art- inceptionism , probably of the film ” Inception ” 
Program has learned how to complement ready-made images and generate new ones from scratch. 
You can Try it here https://deepdreamgenerator.com/

The effect of using such technologies forces us to take a fresh look at the creative potential of AI. Google engineers have been using neural networks for several years to pick up similar images, recognize the area or individual objects in the photo. Later, Deep Style was developed capable of using its own knowledge to interpret a painting style and transfer it to an image.

In 2017,  The research organization Bethge Lab has taught AI to copy the visual style of famous artists’ true algorithms. Neural networks Algorithms were able to separate the design from the content in some images and overlay it on other image files. Bethge Lab focuses on uncovering the algorithms and neuro-computational design principles of perceiving neural networks.  You can Try it here http://bethgelab.org/

App deepart.io – become a digital artist 2018-2019 Philip Wang from UBER developed an Algorithm that based on the generative StyleGAN2 neural network from Nvidia. The neural network creates a realistic image of a human face. The neural network has infinite applicability for everything from gaming to creating false documents

This Person Does Not Exist: You can Try it here https://thispersondoesnotexist.com/

Our recommendation : Article made by Jessica Miley ”This Person Does Not Exist Website is a Creepy Look Into The Future” and publish in Interesting Engineering

Creative AI as Art critic.

An interesting experiment was done by Ahmed Elgammal and Babak Saleh
The two researchers focused on computers ability to asses creative products, namely art (paintings and sculptures). The definition used by the machine for creativity took into consideration the originality of the product and its historical influential value.
The machine exposed to paintings and sculptures from different historical periods could accurately assess the original artworks (not just artists). Most interestingly, if an intentional error was introduced, such as painting from a different period, the machine could correct it.

So, the most important conclusion of this work is that, when introduced with a large collection of paintings (and sculptures), the algorithm can successfully highlight paintings that are considered creative. In the near future, such AI could work side-by-side with art historians and critics.

OUR RECOMMENDATIONS: Research made by Ahmed Elgammal and Babak Saleh ”Quantifying Creativity in Art Networks” published in ResearchGate

AI as curators.

Curators seem to be working soon with AIs, as well. MIT developed an algorithm, MosAIc, that can spot similarities between artworks.
MosAIc can even notice similarities in different media and from different cultural origins, or to identify the generative adversarial networks (or GANs) used to generate deep fakes.

OUR RECOMMENDATIONS: article made by Sarah Cascone, An AI Algorithm Developed at MIT Can Spot Similarities Between Artworks Made in Vastly Different Periods of Art History published in ARTNET

AI as an impersonator

AI can copy the style of an artist and reproduce it, and find new works or relations. These are achieved through Generative Adversarial Networks MAybe the most famous is the “Portrait of Edmond Belamy” 2018, created by GAN, sold for $432,500 at Christie’s in New York.
The GAN is created by team of French entrepreneurs called Obvious.
‘The algorithm is composed of two parts,’ says Caselles-Dupré. ‘On one side is the Generator, on the other the Discriminator. We fed the system with a data set of 15,000 portraits painted between the 14th century to the 20th. The Generator makes a new image based on the set, then the Discriminator tries to spot the difference between a human-made image and one created by the Generator.
The aim is to fool the Discriminator into thinking that the new images are real-life portraits. Then we have a result.’, explains the group.

Other example is the street AI-artist, GANksy, created by https://vole.wtf/ that was trained to mimic street artist BANksy

OUR RECOMMENDATIONS: Is artificial intelligence set to become art’s next medium?
OUR RECOMMENDATIONS: AI software GANksy was shown street art, and learned to draw like banksy

AI as a collaborator and co-creator

AI can work alongside artists and create together and even influence each other.
One such collaboration has been established by Soungwen Chung , an artist that works with machines. She built the first co-bot with the idea that she will teach her style and the machine can help her. But She discovered there is more than that and humans and machines can create together.. She considered that exploring art can shape the machines that are shaping us, and the future of human creativity lies in how this collaboration is set up.

AI AS A CREATOR ITSELF

The question might remain open for the future, most probably one day, AI will evolve in that direction, as well.
Ai-DA, the robot artists, had an exhibition already in London, at the design museum. https://www.sciencefocus.com/news/ai-da-robot-artists-self-portraits-on-display-at-the-design-museum/ It was created in 2019 by Aidan Meller https://aidanmeller.com , and named after scientist and mathematician Ada Lovelace.

The AI made a series of self-portraits using AI algorithms. https://www.ai-darobot.com/
Similarly, Sophia, made in Hong-Kong based Hanson Robotics, has artistic algorithms and has already auctioned it as an NFT for nearly $700,000.

ART AI established an Art gallery, artaigallery.com, whose Art was created by Artificial Intelligence.
The group says that their main aim is to democratize Art by allowing more people to become owners of original, one of a kind artworks.
You can find there many exclusive AI artworks at prices accessible to every Pocket.

What is next?
New forms have already started to appear at the intersection of blockchain and NFT.
But of these evolution in a different chapter!

Stay with us as we will analyse all these creative processes that blurs the line between machines and humans, possible machine-human creations, code-art, generative art, art made by robots, but also new trends of generative NFTs or iNFTs that all challenge the limits and limitless of creativity and make us reflect on our creative future as human beings creating alongside more and more developed AIs. 

TO BE CONTINUED