Phase 2: Model Enhancement and Scaling

Objective: Refine the AI model and prepare for scalability.

1. Advanced Model Refinement:

• Continuously fine-tune the model using feedback loops and iterative training to improve image quality and coherence with text descriptions.

• Explore advanced techniques such as self-attention mechanisms, progressive growing GANs, or contrastive learning for further enhancement.

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2. Scalability and Parallel Processing:

• Develop strategies for distributed training and parallel processing to handle larger datasets and accelerate training time.

• Investigate model distillation and compression techniques to optimize the AI model for deployment on various devices and platforms.

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3. Quality Assurance and Validation:

• Implement robust testing protocols to ensure the reliability and accuracy of generated images.

• Perform extensive validation and quality checks to assess the model’s capability to handle diverse text inputs.