AI Can Generate Creative and Better Images

As we get used to an AI-driven world, it is…

As we get used to an AI-driven world, it is becoming harder to differentiate human skills from AI skills. Already, OpenAI’s GPT-3 language model can create smooth and meaningful text that reads like human-written text.

Many questions abound about the long-term capability of AI. Questions like “can AI generate photo?” are already getting answers. And the answers are quite positive.

In this article, we look closely at image creation and artificial intelligence.

person holding black dslr camera
Photo by Inkredo Designer on Unsplash

Can AI Generate Photo?

The simple answer to this question is a resounding YES! AI can generate photos. AI and machine learning (ML) have gotten so advanced that Picasso and Von Gogh will be envious of the output. Models have been built to generate photos and images in any form. From random face generators to text-to-image tools, there are quite a lot of tools available to generate images.

How Can AI Generate Photo?

Now that we’ve established the fact that AI can generate photos, it’s time to understand how it does it. To start with, AI can use different systems or models to create images. We’ll explore two of the most common types – GANs and Diffusion models.

GANs

GANS (Generative Adversarial Networks) is an ML system that pitches two neural networks against each other. New York Times once described GANs as a game of cat and mouse.

As indicated earlier, there are two competing (adversarial) networks in a GAN setup – the generative network and the discriminative network. The generative network attempts to create fake images.

On the other hand, the discriminative network assesses the generated photo to determine its authenticity. In the process, the generative network learns how to generate believable yet fake images. Once the generative network has a handle on how to create fake images, the discriminative network eventually accepts the fake image as authentic. 

A prominent example of art generated with GANs is the Portrait of Edmond Bellamy. The art piece is a print on canvas measuring 700 mm x 700 mm. The algorithm that painted the portrait was trained with a data set of over 14,000 portraits. These portraits were painted between the 14th century and the 20th century.

Diffusion Model

Diffusion models are transformer-based generative models. In simple terms, this model destroys to create. It takes a piece of data and adds noise to it until it is no longer recognizable. Subsequently, the model tries to recreate the data to its original form. This process allows the model to learn to perform various tasks, including image generation.

OpenAI’s Dall-E 2 and Google’s Imagen are two of the most popular AI image generators that use the diffusion model. They create highly realistic images with great attention to detail.

These tools have a high level of language understanding that makes the text-to-image process a joy to behold. You get the best of both worlds – quality image results and a deep level of language understanding.

The Future of AI and Image Generation

AI might seem so advanced that one might be tempted to think we’ve reached the pinnacle. As true as this assertion sounds, there are still some improvements to be made.

We have AI writing software like INK that has made many forms of writing easier for people. We can envisage this sort of liberalization in the area of AI image generation as well. 

Conclusion

AI will change the way we work. For some, it’s already changing it. People can now give form to their imagination with AI image generators.

These AI machines can simulate the creative process by using randomness. They can also grow and improve with more input. With this, they can visualize things that are not currently within their capability.

Frequently asked questions

Can robots become creative?

Yes they can. Creativity is about bringing ideas together in inventive ways. We associate genes from different parents with remarkable creativity in nature, where they are merged into one.

Are AI generated images copyrighted?

Currently, the US copyright prohibits these images from copyright protection. An authorship-only work is considered. A US Copyright Office report states that, to qualify as a work of ‘authorship, a human being must create the work.

Does AI have creativity?

Using AI techniques, one can create new ideas in three ways: by creating new combinations of familiar concepts; exploring the potential of conceptual spaces; and making transformations that enable the generation of previously impossible ideas.

What is the AI image generator?

TikTok has launched an in-app text-to-image AI generator that allows users to type a prompt and receive an image that can be used as the background for their videos. The effect is called “AI greenscreen” and can be accessed via the camera screen of the short-form video app. The Verge first reported of this new effect.

Can AI generate ideas?

Three major ways in which AI can be used to create new ideas exist: Creating novel combinations. Exploring ideas of conceptual spaces. Making transformations.

Is AI more creative than humans?

Klingemann suggests computers may even become more creative than us. When they trawl the web, they may have access to all knowledge. Human brains are too limited to comprehend how powerful machine creativity can become. An AI art installation raises many questions.

What are creative AI tools?

The best AI tools are those that complement the creative process by utilizing artificial intelligence. You can either use them to create workflow efficiencies or to help inspire others.

What is the AI art Generator from TikTok?

The “AI greenscreen” filter has been launched by TikTok, which is an in-app text-to-image generator. Initially reported by The Verge, users can type a provocative word like “exploding galaxy flowers,” and TikTok will create an abstract interpretation that can be used as a video background.

Why can AI not be creative?

As artificial intelligence mimics creativity, it creates art from previous work. Data is derived from people’s data. However, it is not capable of reading human emotions and creating demand art based on social norms. AI will never match human creativity due to consciousness, emotion, and perception.

Can creativity be taught to an AI?

Some AI can come up with something novel just randomly,” he says. However, it’s very difficult to come up with something that is novel and unexpected and useful.” Artists have gone as far as using AI to design sculptures and create paintings that replicate great works of art.

Can I sell AI generated art?

It is even more important to ask questions about artificial intelligence. OpenAI has promised to give one million subscribers to the DALL-E 2 waitinglist access to the astonishing AI art generator, and now they can sell the images their prompts create.

Can robots have imagination?

The deep neural networks, despite advances, still struggle with the very human skill of ‘imagining’. Now, researchers have developed an AI that uses human-like capabilities to imagine a new object with different attributes. Let’s imagine an orange cat.

Can AI generate images?

AI can create realistic images and videos of cats and hamburgers, representations of your words, faces that aren’t of real people, and even original works of art today.

How does AI create art?

In order to create AI art, artists write algorithms not to follow a set set of rules, but to “learn” an aesthetic through analyzing thousands of images. In accordance with the aesthetics it has learned, the algorithm attempts to generate new images.

Can AI replace artists?

AI models learn and recreate images merely by learning. An image cannot be considered context or purpose without them. AI machines won’t replace artists at least in the near future. Often times, people believe that AI is not capable of creating art because it cannot feel or understand the emotion that we are creating.

AI Can Generate Creative and Better Images

Abir is a data analyst and researcher. Among her interests are artificial intelligence, machine learning, and natural language processing. As a humanitarian and educator, she actively supports women in tech and promotes diversity.

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