How Do Neural Networks Make Art?
If you are interested in art and (more recently) NFTs, you’ve probably heard about AI neural networks like the DALL-E AI image generator. They may sound technical and confusing, but they are pretty easy to understand because they work like our brains. In this article, we will discuss what neural networks are, how they make art, and whether generated art using neural networks is "real.”
What Are Neural Networks?
In simple terms, neural networks are computer systems designed to mimic the human brain. Just like our brain, neural networks consist of interconnected neurons (or nodes). These nodes are connected via synapses, and transmit information using electrical signals. Neural networks are often used to solve problems that are difficult for traditional computers to solve, such as recognising patterns or facial expressions.
Unlike traditional computers, which take an input and use it to produce an output (a+b = c), neural networks can take in multiple pieces of information to produce an output (a+b+c+d+e = cabde). In addition, they can learn and adapt based on the outputs they produce, meaning they can improve their performance over time, just like our brains.
How Do Neural Networks Create Art?
Neural networks create art by analysing thousands of art pieces and “copying” the techniques they see in those pieces. This makes neural networks a type of “learning algorithm,” as they can improve their artwork over time.
For example, Deep Style is a neural network trained on thousands of images in order to learn how to generate new images in the style of those it had been trained on. The result is artwork that looks like a real artist could have created it, although it has really been generated by a computer. Using Deep Style, you can take a photo of your friend and turn it into a painting in the style of Van Gogh or Picasso, or you can take a landscape photo and turn it into abstract art. Keep in mind that this is just one way AI paintings are made–another popular way is to use a text prompt to generate a painting.
One of the most impressive things about neural networks is that they can create completely original art, not just a copy of what they have seen before. This is because the same rules that may limit human artists do not limit neural networks when it comes to creating art. Instead, they can experiment with different techniques and styles to create something truly unique. So, it’s clearly true that AI is a new form of art for the modern era.
One famous example of neural network art is “The Next Rembrandt,” a painting that was created by a team of AI researchers from Microsoft and the Netherlands. The painting is based on the style of Rembrandt and took over two years to create; it is considered to be one of the most realistic AI-created paintings in existence.
Neural networks are also being used to create music, and there are even some neural networks capable of creating works of poetry. As AI continues to evolve, we’ll likely see even more impressive examples of art created by neural networks in the near future.
Is Art Generated by Neural Networks Real?
This is a difficult question to answer, as it depends on your definition of “real.” If you consider something to be real only if a human has created it, then the answer is no. However, if you consider something to be real if it exists in the world and can be experienced by people, then the answer is yes–art generated by neural networks is real.
Additionally, art generated by neural networks can be legally sold as NFTs. Many online digital art marketplaces specialise in selling NFTs, such as OpenSea and Rarible, and people are making significant amounts of money by selling AI-generated art on these websites.
So, while neural networks may not create “real” art in the traditional sense, they are capable of creating works of art that are just as valid and valuable as any other piece of art. Regardless of how you define it, there is no denying that art created by neural networks is impressive, and it will be interesting to see what AI is capable of creating in the future.