2.3 Multi-modal AI Training Framework

representations:

1. Text-to-Image: Uses DALL-E 2 fine-tuned on monster concepts for initial visual creation.

2. Image-to-3D: Employs a custom Neural Radiance Field (NeRF) model to generate 3D representations from 2D images.

3. Physics-based Simulations: Utilizes PyBullet for real-time physics simulations of monster movements and interactions.

Example of multi-modal integration:

from models.dalle2 import DALLE2
from models.nerf import MonsterNeRF
from simulations.pybullet_wrapper import PhysicsSimulation

def create_interactive_monster(text_description):
    # Generate 2D image
    dalle_model = DALLE2.load("monster_dalle.pth")
    monster_image = dalle_model.generate(text_description)

    # Convert to 3D
    nerf_model = MonsterNeRF.load("monster_nerf.pth")
    monster_3d = nerf_model.image_to_3d(monster_image)

    # Add physics
    physics_sim = PhysicsSimulation()
    physics_sim.add_monster(monster_3d)

    return physics_sim

# Usage
interactive_monster = create_interactive_monster("A six-legged cybernetic monster with plasm