Art has been a very selective world. Without the proper education, you weren’t considered an artist. Many amateur artists struggle to show their work to the world, and therefore, cannot sell any of their artworks. That’s very frustrating for many because you want to show your art to the world.
The digital art revolution made possible through blockchain technology, also referred to as non-fungible tokens (NFTs), has democratized art creation-especially digital art creation.
NFTs make it possible to create digital scarcity and prove ownership over an artwork. This ownership was hard to establish before the invention of blockchain technology. As a result, an entire industry of new artists has risen who can now create digital art and easily expose it to the rest of the world. Not only that, non-fungible tokens make it possible to quickly trade artwork ownership, or even make it possible for multiple people to own a piece of digital artwork.
As a side effect of this art revolution, a new industry has sprung up called generative art. Generative art is created by code or algorithms that set the boundaries for the creation process. However, some projects have taken this to the next level by including machine learning in the mix.
Can generative art be considered true “art”?
There’s a lot of skepticism among the art world about generative art, whether it’s true art. An artist can now generate 10,000 art pieces in a matter of time and put them up for sale. For that reason, it’s obvious some artists trash-talk generative art because it seems wrong to them that an artist can mass-produce art while a computer does all the work.
So, is generative art real art? In my opinion, the answer is a resounding yes!
It takes a considerable amount of time to craft a good algorithm that produces art that people like, and more importantly, want to attach value to. Moreover, the creation process with generative art is the “coder/developer” tweaking the boundaries of the code or even changing some of the algorithm’s rules to create compelling pieces of art. In other words, the creative process happens on a digital canvas, and it allows an artist to iterate much quicker over ideas they might have.
There are different types of generative art projects. For instance, you have generative art projects that create computer-generated cats, aliens, or burritos. The central focus here is that each generative NFT has a set of traits. It’s too time-consuming to generate each piece of art themselves.
On the other hand, you have projects that use an algorithm for drawing stuff on a canvas. These algorithms use random data as input for generating a new piece of work. Most often, the generated piece of work is ugly, however, in rare cases, the artist generates a work that they like and want to sell.
Again, it’s not only the computer that generates art. A computer is a tool for generating art. The artist always has a concept in mind and tweaks the algorithm to find works that fit their mindset. Below you see an art piece generated under the Avid Lines project. It takes time to tweak the algorithm to get the correct spacing, variety in circles, and color profile.
(Source: Avid Lines owned by propervault)
In other words, the artist has to review each piece they create based on random data input. It’s a manual and slow process to find a gem the artist thinks people like and want to pay money for. Therefore, this manual process is also part of the creation process, making it “art”.
Which generative art projects should you look out for?
There are many interesting generative art projects, too many to name. Here’s a personal selection I like based on how they approach the art creation process.
Botto - Decentralized artists using AI and community feedback
Botto is a decentralized artist that generates art based on community feedback. The project presents 350 art pieces to the community every week, who then vote on their favorite artwork. Next, it uses these votes to train its algorithm, changing the art it creates over time. Each week, one final artwork is minted as an NFT and put to auction on SuperRare.
You can only participate in the voting process with BOTTO tokens. Furthermore, you have to stake those BOTTO tokens to get Voting Points (VP) in return. You can then spend those VPs on one or multiple art pieces you like.
(Scene Precede sold for $430,200 (100ETH) in its second Botto auction. Source: SuperRare)
When the weekly art piece, selected by community voting, has been sold, the proceeds are redistributed among the community voters. In other words, they act in their best interest to select the artwork they like the most and will offer the best return on the free NFT market.
More recently, robotic artists like Botto have become the toast of the tech and art world. For instance, the piece above titled ‘Scene Precede’, commanded both media attention and a price tag in the mid 6 figures. And the rise of AI-based art seems to be a growing and exciting market for NFT collectors.
What Botto did is truly remarkable. Not only does it leverage AI to generate art, it also allows a community to decide on which art should be generated and earn a return by doing so. It gives everyone a stake in the decentralized art process.
The project is also an example of a broadening range within algorithms: Botto’s creations differ greatly in style and represent a gradual, collective shift of community preference. This has become more apparent as Botto matures, with its art pieces varying from the whimsical to a more traditional interpretation of what’s aesthetically pleasing.
(Cross Adieu sold for $81,000 (18.9ETH) in its second Botto auction. Source: SuperRare)
If you like Botto, you can read more about the art engine and generation process or even try to participate in the voting process (I recommend joining their Discord community if you’d like a warmer introduction). Botto has sold over $1.3 million over 7 different art pieces in its first eight weeks - validating both the concept and the idea behind decentralized autonomous artistry, with famous art collectors in the NFT realm, including CozomoMedici (some may know him as Snoop Dogg), HashesDAO, and FlamingoDAO.
Algorhythms by Han and Nicolas Daniel
The AlgoRhythms project uses a script that accepts a hash as an input. This hash determines different parameters for generating a melody and a visualization of this melody. The result looks like this:
(Source: @AlgoRhytms_io)
From an interview with Nicolas Daniel, he says the project is a collaboration with Han, whom he met via Twitter at the end of 2020. They quickly discovered that both of them are currently learning to play the piano and love lovely melodies. That’s why they wanted to create some generated tunes!
A similar project that sells AI-generated music is Euler Beats.
Solvency by Ezra Miller
(Source: Solvency.art)
Solvency has emerged as one of the most exciting new generative art projects to watch in the NFT space. Created by New York artist Ezra Miller and launched in April, the project employs dynamic WebGL simulations to generate textured feedback loops drawn from a GAN trained on 35 mm photographs and layered colors based on information from its minting transaction.
The project uses a rising floor price and has achieved support from top collectors like 888, Seedphrase, and Pranksy.
Conclusion
The generative art world is moving quickly! Creating generative art has become very accessible with JavaScript libraries like p5.js. To stand out among all generative art projects, you have to step up the game and combine different fields like music, maths, or photography.
