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Use Case

Virtual wildlife and nature tours

Generative AI models like LLMs (Language Model by OpenAI) and image generators can be utilized to curate virtual wildlife and nature tours. A Language model like ChatGPT can be utilized to generate engaging interactive narratives and descriptions of various wildlife species and natural habitats, enhancing user engagement and providing a rich immersive experience.

Image generators can create high-definition, realistic images to aid in visual storytelling. They can help in fabricating detailed and dynamic landscapes, wild animal portrayals or sketching rare plant species, extending the reach of tours beyond existing footage or photographs. This can be particularly beneficial for visualizing threatened habitats or species that may be challenging to capture with traditional photography or videography.

Further, employing these AIs, we can develop interactive virtual reality experiences. Here, users can take part in simulated tours wherein they can 'interact' with AI-generated digital animals or explore a recreated natural environment.

How to build with Clevis

Text Input

Ask the user to enter their desired wildlife or nature destination

Prompt ChatGPT

Prompt ChatGPT to generate interesting facts and information about the selected destination

HTTP Request

Fetch images of the selected destination from a wildlife and nature API

Generate Image (DALL-E)

Generate an artistic representation of the destination using DALL-E

Display Output

Display the information, images, and artistic representation of the destination to the user

This is a simplified summary of an example application, 'Virtual Wildlife and Nature Tours,' which can be built using an AI tool named Clevis. The power of Clevis is that it allows users to create similar applications within the same domain easily.

The application begins by asking the user to provide an input on their desired wildlife or nature destination. To achieve this, we use the Text Input step. Then, we employ the ChatGPT tool, a language prediction model developed by OpenAI, to generate engaging facts and details about the provided destination. The input prompt for this step will include the user's previous output, e.g., 'Tell me some interesting facts about {previous_step_output}'.

Next, the Http Request step is used to fetch vivid images of the selected destination from a wildlife and nature API. It takes the user's previous output as input and sends it as a parameter in the HTTP request. Following this, an AI model named DALL-E, also developed by OpenAI, is used to create an imaginative representation of the destination.

Finally, we use the Display Output step to present all gathered information, including images and artistic creatives, to the user, creating a comprehensive virtual tour experience.

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