AI-generated art and digital content

TEXT_INPUT:Prompt the user to enter a topic or keyword;;CHATGPT:ChatGPT will generate a list of relevant AI-generated art and digital content based on the user's input;;HTTP_REQUEST:Fetch additional information about the selected art pieces from external APIs;;DALL_E:Generate a unique AI-generated image based on the selected art piece;;DISPLAY_OUTPUT:Display the retrieved information and generated image in a user-friendly format

Generative AI models like Language Model (LLM) and image generators offer tremendous potential in creating AI-generated art and digital content.

For instance, ChatGPT, a variant of LLM, can create original textual content such as poetry, stories or digital ad copies. It learns patterns from human-written texts and generates similar sentences, allowing for a considerable level of creativity.

Image generators utilize models like GANs (Generative Adversarial Networks) to produce visual art. OpenAI's DALL-E, for instance, synthesizes images from textual descriptions, even those that have no clear real-world analogs. This makes it possible to create concept art or unique designs based on abstract or surreal prompts.

Similarly, models like MuseNet use Transformer-based architectures to generate novel music compositions stemming from a variety of styles and epochs, further extending the artistic reach of AI models.

How to build with Clevis

This is an explanation of an exemplary application that you can build using Clevis, designed to produce and showcase AI-generated art and digital content. The application works in a series of clearly defined steps.

First, the app initiates with a Text Input step that prompts the user to enter a topic or a keyword. The app then utilizes OpenAI's ChatGPT in the ChatGPT step to generate a range of AI-created art and digital content relevant to the user's input. This helps provide users with a personalized experience tailored to their interests.

Following this, our example app performs an Http Request to fetch supplementary information about the chosen artworks from external APIs. This ensures a richer, more detailed output for every selected item.

Next, during the DALL·E step, the application uses the DALL-E model to generate a unique AI-created image based on the selected art piece, further enhancing the user interactivity with the app.

Finally, in the Display Output stage, the retrieved information and the AI-generated image are presented to the user in an intuitive and user-friendly format.

You can design similar applications within the same domain using the Clevis platform.