Combining live camera feed with both ARCore and GPT (Generative Pre-trained Transformer) can create a powerful augmented reality experience with intelligent interactions.

Here's how the combination could work:

1. Live Camera Feed: The application uses the device's camera to capture the real-world environment in real-time.

2. ARCore Integration: ARCore is a platform developed by Google that enables augmented reality experiences on Android devices. It provides tools for motion tracking, scene understanding, and light estimation to seamlessly blend virtual objects with the real world. The live camera feed serves as the background, and ARCore overlays virtual objects onto it, creating a mixed reality experience.

3. GPT Integration: GPT is a deep learning model designed for various natural language processing tasks, including text generation and understanding. By integrating GPT into the application, it becomes capable of understanding the text-based inputs from the user, such as voice or text commands.

4. Intelligent Interaction: The combined system allows users to interact with virtual objects in the AR environment using voice or text-based commands. The GPT model processes these commands, providing a natural language understanding capability. For example, a user could say "Place a virtual chair in front of the table," and the GPT model would generate an appropriate AR object placement command based on the input.

5. Real-time Object Recognition: With the assistance of GPT, the application can potentially recognize objects in the live camera feed and provide relevant AR information in response. For example, if the user points the camera at a plant, GPT can analyze the image and identify it as a specific type of plant, display related information, or even generate AR effects around the plant.

In summary, combining live camera feed with ARCore and GPT allows for a highly interactive and intelligent augmented reality experience. Users can interact with virtual objects using natural language commands, and the system can also process and respond to real-world objects recognized in the live camera feed. It will have relevant in filming and CGI/VFX time processing in video editing.