DALL-E 3, one of the most advanced AI image generators, is trained to produce graphics based on the descriptions provided by text inputs. That is important because it is a very different concept from an AI model that interprets individual words.
So, what is a neural network, and how are the next-generation AI models trained to provide this level of understanding? Generative AI technology offers access to creative outputs regardless of your proficiency or technical knowledge, using deep learning to study huge datasets.
What is the controversy with AI image generators and the way they are trained? Critics feel that because a neural network effectively digests and categorises billions of existing pieces of artwork and real-world images, it could potentially be used to replicate or mimic the unique style and flair of an artist, past or present.
How Does a Neural Network Create Artwork?
AI artwork generators do not copy or simply reproduce images. Instead, they are trained intensively through deep-learning neural networks and use that training to produce new, original graphics. The process involves an algorithmic estimate of the pixel values that should populate every part of the image based on knowledge extracted from training data.
When a user provides a text prompt, the AI takes that as a set of parameters and then develops a new image around those instructions–it can take from a couple of seconds to several minutes, depending on the image generator and the complexity of the prompt and the finished graphic. In many cases, you’ll tweak the image by adjusting the parameters if the AI hasn’t understood exactly what you want your completed illustration to look like.
Can you copyright AI-generated images if they have been created using knowledge based on pre-existing artwork? Currently, this is a matter of intense debate, but the general stance depending on the legislation in your area, is that you cannot copyright your artwork unless you can provide evidence of a threshold of human involvement, such as post-production editing.
What Is the Difference Between AI and Neural Networks?
While the most advanced AI artwork generators work on a neural network learning model, they are two different elements of the same technology. ‘Artificial intelligence’ is a term that means a machine that can replicate the cognitive understanding present in the human brain.
Neural networks are systems created from nodes, or artificial neurons, modelled on similar networks that occur naturally in biology–also present in our brains. The neural network is built on an algorithm and can receive information and process or interpret it, such as translating data and identifying which category it belongs to based on the datasets it has been trained on.
How Does Deep Learning Tie Into Neural Networks?
Deep learning is another machine learning subset that allows AI graphic generators to digest those enormous datasets and create structures and logic to help with decision-making, such as knowing what objects a user wants to feature in their artwork, as well as the size and shape of those objects in relation to the next.
Put together, these elements create an artificial neural network, combining deep learning, neural networks, and AI functionality, surpassing the capabilities of conventional machine learning models and making artwork generators far more intelligent and able to interpret complex text descriptions.
Fortunately, you don’t need to understand the technical features behind an AI artwork generator because all of this happens behind the scenes while you wait for the platform to produce your very own artwork!