Ai Art is a word that shakes us and builds curiosity in our minds. If you’re here you must be one of us who always look for new creations and updates. So let’s roll in to learn what AI art is.

AI art is anything that can be created digitally with the help of tools and these creations can be videos, images, voiceovers, articles, copywriting, or many other things.

As we know humans are the only species that are carrying the burden on their shoulders but with this growing World and upcoming challenges people need someone to share the burden and here comes the role of AI.


History of AI Art

In the late 1960s, the first iteration of AI art appeared. After that, Harold Cohen was the first man to build a notable system appearing in 1973 with the debut of Aaron. The Aaron system was an AI assistant that used a symbolic AI approach to help Cohen create black-and-white art drawings.

After this, there was a huge hold in AI art but in 2014 GANs was the foundation that discussed generative AI technologies. Right after that in 2015 Google released a product called DeepDream which uses a convolutional neural network to produce AI art.

2018 was the most revolutionalized year in the history of AI because this was the year in which Ganbreeder relaunched itself as a new brand called Artbreeder.

That same year an artist who was using GAN to create ART made headlines by creating and selling a painting called Edmond de Belamy, for the price of $432,500. Those GAN models are from the 14th to 19th century and are available for the public on WikiArt.

All these advancements sparked the interest and imagination of users around the world in January 2021 and immediately OpenAi launched Dall-E for the general public. Now anyone with an internet connection can produce stunning AI art with text prompts.

AI Technologies

Working Models of AI Art

The fundamental process of generating art is the same but the models and the techniques are different. The whole procedure of understanding and building AI art starts with machine learning. Modern AI art tools often use natural language processing to understand and generate images.

Different AI Models

There are different types of AI models used in different tools to generate art, images, and videos and some of them are the following.

GAN ( Generative Adversarial Network )

GAN is a network that uses multiple neural networks together for deep learning operations to help predict, or generate, the best-desired results that the user looks for based on the prompt.

CNN ( Convolutional Neural Network )

The CNN is a completely different model than GAN because it entirely focuses on deep learning to identify objects, which helps users generate useful and new images.

NST ( Neural Style Transfer )

An NST is used in conjunction with a CNN as a deep learning technique. Then it enables the transfer of the style of one image to another. You can make thousands of images in no time.

RNN ( Recurrent Neural Network )

This model is used for generating sequences of music. It uses a feedback loop to produce a sequence of outputs based on prior inputs. Then this model enables them to generate new outputs.

Use of AI by an Artist

Artists were using physical tools to design different types of outcomes but after the introduction of AI tools, it is far easier to get desired results with more perfection.

For example, if you require pictures of models with luxury white clothes let’s figure out how can we accomplish this task.

Text Prompt

Luxury Clothing Campaign, white with sea coral and seaweed background theme, tall and thin models, asian models with brown eyes, Balenciaga Demna aesthetic combined with Dior by Kim Jones aesthetic, head cover with tissus, high resolution, realistic texture, realistic skin texture, fine details, extra fine details, minimalist, 32k, shot with full frame, Canon EOS 70D, really detailed clothing, Luxury Fashion, High-end Fashion clothes, straight poses, super realistic, high production, production shoot.

Text Prompt

a pair of twins Cute Big head Big eyesPink Alien wearing mexican poncho, singing busking on a dessert, Luxury Jewelry on his head, 25mm, Wes anderson, Fashion, Colourful, Neon Lighting –ar 16:9

So with this much ease, you can create whatever you want. AI helps us to achieve things that we were assuming and imagining. Go ahead and make your collection of images, videos, and voiceovers.

Is it difficult to make AI Art?

If you have slight knowledge about AI you can easily create Art with the help of AI tools. Some artists train AI models to create art. To complete this task first of all you need to have access to a data set of art. The second thing is to train the model to learn from the assembled data. Once you have trained the data set on an appropriate GAN model, it’s time to generate art.

Now the second way of making art is to get an AI model who has already been trained on different data sets and is ready to create AI art. With these pre-trained models, artists can generate images with simple prompts of texts.

So I don’t think that generating AI art is difficult with tools that are pre-trained and you can achieve or design any specific object according to your desire.

Best Tools for AI Art

There are many tools available in the market and some of them offer new users with free credits to explore the process of AI art. Among the many AI image generator tools available to generate AI art today are the following.

  • Adobe Firefly
  • Artbreeder
  • Dall-E
  • Deep Dream Generator
  • DreamStudio
  • Midjourney
  • Platform
  • Stable Diffusion

Ethical Concerns Associated with AI Art

Once you learn to create art that is good and acceptable there are some ethical concerns that you have to consider while creating AI art. Let’s jump in to explore some of the most important factors.


Artists have enjoyed their signs after creating them but authorship works differently. The authorship of AI will go to the human who instructed the AI tool with the text prompt to create the work.


The diversity of an AI model depends on its training model, and there exists a potential for Bias when the training data lacks inclusivity and consideration for equity and discrimination-related issues.


This is one of the major concerns because most of the GAN-based AI tools have been trained on data sets that do not obtain full legal copyright access. So you have to give importance to this part to save your time and get yourself safe from law enforcement agencies.


With AI art there is an ethical question about whether generated works are genuinely original or just derivative. So always try to generate something original.


AI art is a new invention and people are making tons of money with the help of AI tools. So if you’re interested in AI creation you should learn this skill. It’s 2023 and everything is changing. So always be ahead with the latest technologies and push yourself to learn new ventures.

If you want to know about the Best Free AI Content Generators you can visit our other blog post and help yourself to know about things that matter in this digital world.