We are at the cusp of a Cambrian explosion in user-generated content. It’s unlike anything we’ve seen before. Chances are, you’re already starting to see it all over social media; the ultra-realistic art, the deep fakes, the videos that look like moving paintings. Generative image content has steadily evolved from simple static images to more complex interactive visuals. New applications powered by AI are the force behind this trend, allowing users to create unique and dynamic visual experiences that can be used in a variety of contexts, such as advertising, entertainment, education, and more. AI-powered user generative image content (UGIC) has a wide array of applications. From more effective data visualization to creating virtual worlds, the exponential adoption of AI has removed all the technical barriers to entry for everyone. What was once reserved for technical specialists is now wholly accessible to anyone with a smartphone. How did all of this start? Where is it going? And what kind of role will artificial intelligence play in the evolution of generative image content? Introduction to Generative Image Content Generative image content is a subset of the broader machine learning field. The goal has been to program computers to emulate human thought processes and problem-solving. At the end of the day, this means computers can . learn without being programmed In 2014, image generation took a giant leap when were developed. This led to much more realistic images generated by AI. Now, generative image content can be used to create highly personalized and interactive visual experiences. generative adversarial networks (GANs) Generative images are created using algorithms, which are sets of instructions that allow computers to generate visuals from a given set of parameters. This is known as machine learning. The idea behind the current system of generative image AI has its roots in two different technological advances, one that came about in the 1950 and the other in the 1960s. Joseph Weisenbaum was the brilliant mind behind the , which was, in essence, the first chatbot. ELIZA program It was a simulation where the program learned from the response of the patient, with the program pretending to be a legitimate human psychologist. It was so good that many patients had no idea ELIZA wasn’t a real person. About a decade later, a process was being studied. It’s a complex system, even today, but it is the foundation for what is a much more common term today: Machine learning. Here’s the : known as deep learning official definition “Deep learning is a subset of AI and machine learning that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, language translation, and others.” Without the above tech from decades ago, modern AI would not exist as we know it. Adding Artificial Intelligence Into the Mix The rise of artificial intelligence (AI) has had a major impact on the development of generative image content. AI algorithms can build more complex visuals and interact with user input in real time. This has allowed for some impressive applications, such as interactive virtual worlds enabling users to control their environment. The tech can also be used to create personalized visuals based on a user’s preferences or behavior. This allows for more immersive experiences in gaming, advertising, and even education. Now, platforms are leveraging this ability to offer users exciting new capabilities, and both users and investors are all for it. Lensa was one of the first to hit the mass market, and it was well rewarded. The app hit several astounding milestones almost immediately, including making , just after its initial launch. several million dollars within a single month Lensa: Starting It All While Lensa wasn’t the first of its kind, it demonstrated the demand for these types of AI tools. Lensa renders photos into artwork based on text prompts. Leveraging AI models, the app allows users to create virtually any kind of artwork imaginable, from cosmic fantasy to 80s-themed pop. And if that wasn’t impressive enough, the app also allows users to transform their selfies into highly customizable portraits. To achieve this, Lensa uses a copy of open-source code called Stable Diffusion to run its program. This provides access to billions of images from around the web and then compiles them into a dataset. Then, the AI uses these images to “learn” techniques that it applies to generate new works. So far, it’s been on social media, with tens of millions of downloads since it went live. But the app has drawn criticism from artists, claiming the art it generates is based on stolen work. a big hit So while Lensa’s future is uncertain, it has demonstrated a sliver of what is possible when combining images and AI. And with consumers demanding more, the race is on to see what all can be done with generative imagery.. The Future of AI Art With the help of algorithms and deep learning techniques, computers can now create original works of art that rival those of human artists. This disruption has the potential to shake up various industries that incorporate art, such as advertising, fashion, and entertainment. Interior decoration Some have a natural aptitude for interior design. They can visualize how a room can look with different colors, furniture, and art. For many, this can be quite challenging, but not for long. Generative AI has given way to platforms such as , which can act as your own virtual interior designer. Interior AI Create an image from (almost) nothing. While Lensa was able to edit and change existing photos, apps such as allows users to create ultra-realistic selfies using reference images or even just text. Users are able to create a completely new and unique photo from something as simple of a prompt as “a woman petting a dragon.” This begs the question, will photographers soon be out of a job? Artisse AI Virtual photoshoots Platforms such as could potentially make photoshoots obsolete as well. This website allows users to upload an image of themselves and then generate images in a variety of settings, poses, and more. What’s more, the images come out incredibly realistic, so convincing your friends you went to Paris for the weekend is a cinch. Photo AI Are generative images the future? The applications for AI-generated imagery are endless. It’s only a matter of time before these tools are adopted worldwide, both professionally and for everyday use. The platforms we see today are just the very beginning. Every day that goes by is more time for these AI models to learn and continue to perfect their algorithms. So whether you’re looking for an interior designer or custom images, AI holds the key to the future of generative images.

This story contains new, firsthand information uncovered by the writer.

The Evolution of Generative Image Content

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

A Necessary Evolution of Privacy and Data Protection on Blockchain Networks

The Noonification: How Often Do NFTs Pass The Howey Test? (1/13/2023)

Darwin's Hybrid Intelligence to Align AI & Human Goals for Startups & VCs

The Noonification: White Man (11/26/2022)

The Noonification: The Metaverse is a Sh*tshow (11/2/2022)

100 Days of AI Day 1: From Newsletter to Podcast, Leveraging AI for Audio Transformation

A Necessary Evolution of Privacy and Data Protection on Blockchain Networks

The Noonification: How Often Do NFTs Pass The Howey Test? (1/13/2023)

Darwin's Hybrid Intelligence to Align AI & Human Goals for Startups & VCs

The Noonification: White Man (11/26/2022)

The Noonification: The Metaverse is a Sh*tshow (11/2/2022)

100 Days of AI Day 1: From Newsletter to Podcast, Leveraging AI for Audio Transformation

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps