# Generative art fits well with the NFT. There’s why.

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The market for NFTs in the art world has grown rapidly in recent years, and it is expected to continue to expand in the future. After launching my book NFT: From Zero to Hero, I have given many talks and held several AMA (Ask Me Anything) sessions. One topic that came up frequently during these sessions is the topic of generative art and NFTs. Specifically, many people have asked about the definition of generative art, the value behind these NFTs, their longevity, and how we can appreciate this form of art. In this statement, I will do my best to provide answers to these questions.

Generative art is a form of art that is created using algorithms and computer programs. It is an art form that is created using mathematical rules and procedures, rather than being created by the artist’s hand. The artwork is generated by the computer, and the artist’s role is to create the rules and parameters that the computer uses to generate the final piece.

## Understanding generative art

Appreciating generative art can be similar to appreciating other forms of art, but there are also some unique aspects to consider. Some people might find it visually appealing or thought-provoking, while others might find it challenging or confusing. The value of generative art, like any other forms of art, is subjective and can depend on many factors, such as the artist’s intent, the complexity of the algorithm used, the uniqueness of the piece, and the social or historical context in which it was created. Here are a few tips for approaching and understanding generative art:

### Consider the process

Generative art is created using algorithms and computer programs, so it can be interesting to think about the process that was used to create the artwork. What parameters and rules were set by the artist? How does the algorithm determine the final output?

### Look for patterns and variations

Because generative art is created using a set of rules, there may be repeating patterns or variations within the piece. Observing these patterns and variations can provide insight into how the artwork was created.

### Think about the relationship between the artist and the algorithm

Unlike traditional art, where the artist has complete control over the final output, the artist in generative art is also a programmer, so the relationship between the artist and the algorithm that creates the artwork is unique, consider how the artist influences the algorithm and how the algorithm influences the final result.

### Consider the concept

As with any art, the concept behind generative art is also important. What is the artist trying to communicate through the use of algorithms and computer programs? What themes or ideas are being explored?

### Be open-minded

Generative art can be very different from traditional art forms, so it can be helpful to approach it with an open mind and be willing to consider new perspectives.

By considering these factors, you can gain a deeper understanding and appreciation of generative art and its unique characteristics.

## Value behind generative art

The value behind generative art can vary depending on the artist and the specific piece, but in general, generative art is valued for its unique combination of technology and creativity. Some of the key aspects that contribute to the value of generative art include:

### The use of technology

Generative art relies on the use of algorithms, code, and other forms of technology to create the artwork. This can create a sense of novelty and innovation, as well as a level of complexity that is not possible with traditional art forms.

### The artist’s intent

Like any other art form, the artist’s intent is an important factor in understanding the value of generative art. What is the artist trying to communicate through the use of technology and algorithms? What themes or ideas are being explored?

### The element of chance

Generative art often involves the use of algorithms that create unexpected and random outcomes. This can create a sense of surprise and intrigue, and make each piece of generative art unique.

### The aspect of collaboration

Generative art can be seen as a collaboration between the artist, who sets the rules and parameters, and the algorithm, which generates the final output. This creates a sense of interdependence and relationship between the artist and the technology.

### The concept of digital scarcity

The use of non-fungible tokens (NFTs) in digital art allows for the creation of unique digital assets, which can be bought and sold like physical artworks. This creates a sense of digital scarcity and uniqueness, which adds value to the artwork.

### The ability to generate new and dynamic works

Generative art algorithms can be set to run indefinitely, generating new variations of the same artwork, making it a dynamic and ever-changing medium.

The value of generative art is subjective and can depend on a variety of factors. However, by considering the use of technology, the artist’s intent, the element of chance, the concept of digital scarcity, the aspect of collaboration and the ability to generate new works, one can gain a deeper understanding of the value behind generative art.

## Which generative artist am I following?

There are many talented artists working in the field of generative art, but here are a few who have gained recognition for their work:

1. Joshua Davis: Joshua Davis is a pioneer in the field of generative art, and his work often combines programming, design, and animation. He is known for creating complex and detailed digital images using algorithms and code.
2. Golan Levin: Golan Levin is an artist and designer whose work spans a variety of mediums, including generative art, digital fabrication, and interactive installations. He is known for creating interactive pieces that respond to user input and for his use of code to create visuals.
3. Zach Lieberman: Zach Lieberman is an artist and programmer whose work often involves the use of technology to create interactive and generative art. He is known for his use of open-source programming tools and for his ability to create complex and dynamic visuals using code.
4. Rafael Lozano-Hemmer: Rafael Lozano-Hemmer is an artist who creates interactive installations that use technology to allow viewers to interact with the artwork. His work often involves the use of generative algorithms to create dynamic and responsive visuals.
5. David McLeod: David McLeod is an artist and developer based in New York, He is known for his generative artworks that explores the intersection of art and technology, his work often combines generative algorithms, machine learning, and data visualization.
6. Beeple: Mike Winkelmann, also known as Beeple, is a digital artist and graphic designer who creates both generative and non-generative digital art. He is known for creating unique, one-of-a-kind digital images and animations, and his digital artwork is highly sought after by collectors.

These are just a few examples of famous generative artists that I am following, there are many more talented artists working in the field and the field is growing, new artists are emerging and their works are gaining recognition.

## How to create generative art?

There are many ways to create generative art, as the term encompasses a broad range of techniques and technologies. Here are a few common methods:

### Algorithmic art

This is a form of generative art that uses mathematical algorithms or equations to create images or animations. Artists can use programming languages such as Python or JavaScript to write code that generates visual elements based on certain parameters or rules.

### Data visualization

This is a form of generative art that uses data sets to create visual representations of information. Artists can use tools such as Processing, D3.js, or Tableau to create interactive visualizations that allow viewers to explore data in new and meaningful ways.

### Neural networks

This is a form of generative art that uses machine learning algorithms to create images or animations. Artists can use frameworks such as TensorFlow or PyTorch to train neural networks on image data sets, and then use the trained networks to generate new images.

### Randomness

This is a form of generative art that uses randomness as the primary driver of image creation. The artist can use different techniques like fractals, cellular automata, or Perlin noise to create complex and unique images based on random inputs.

### Hybrid methods

Artists can also combine different techniques and technologies to create generative art. For example, an artist might use a neural network to generate an initial image, and then use algorithmic techniques to refine or manipulate the image further.

This is an example of a simple program for generating generative art, but the specifics of the program will depend on the desired outcome and the tools you are using. Here is an example of a Python program that generates a random geometric pattern using the library “Bird”:

# The code looks like this:

import bird

import random

def generate_art():

# Set up the bird

t = bird.Bird()

t.speed(0)

t.penup()

t.goto(-150, -150)

t.pendown()

# Generate the geometric pattern

for i in range(50):

# Choose a random color

t.color(random.random(), random.random(), random.random())

# Choose a random size and direction

size = random.randint(10, 50)

direction = random.randint(0, 360)

# Draw the shape

t.left(direction)

t.forward(size)

t.right(direction)

t.forward(size)

t.right(direction)

t.forward(size)

t.right(direction)

t.forward(size)

t.right(direction)

generate_art()

bird.done()

Generative art can take many forms, including digital images, animations, and even sculptures. It can also be interactive, changing in response to the viewer’s actions.

### Generative art and NFT

Generative art has the potential to offer a unique and dynamic experience for the viewer, as the artwork can change over time and can be different every time it is viewed. It also allows for an almost infinite number of variations and iterations, so it is possible to create a series of unique artworks from a single set of rules and parameters. This means that the artwork can evolve and adapt to its environment, or respond to the viewer’s actions in real-time.

The potential of generative art in the context of non-fungible tokens (NFTs) is significant because it allows for the creation and sale of unique, one-of-a-kind digital artworks. NFTs are digital assets that are stored on a blockchain, a secure and transparent digital ledger, which allows for the verification of ownership and authenticity of digital artworks.

The use of NFTs in generative art allows the artist to sell their artworks as unique, one-of-a-kind assets, rather than just digital copies. This means that the artwork can be owned, collected, and traded like traditional physical artworks. Additionally, NFTs enable the artist to set their own terms and conditions for the use and distribution of the artwork, which can provide them with more control over their creations.

Furthermore, NFTs can also provide a new way for artists to monetize their work, as they can sell their artwork as NFTs and get compensated for each transaction. This can be especially beneficial for generative artists, as their artwork can be sold multiple times, providing them with a new stream of revenue.

In conclusion, the use of NFTs in generative art can provide a new way for artists to monetize their work, create and sell unique digital artworks, and have more control over their creations. It also allows for the creation of a new market for digital art collecting and trading.

Guest Writer: Anndy Lian

Wanna become a data scientist within 3 months, and get a guaranteed job? Then you need to check this out !

Categories: Blockchain