When generating AI avatars, avoid generic emotional prompts like "the character is sad." To achieve more realistic and controllable results, describe the specific muscle movements, shifts in body language, and transitions in tone associated with that emotion. This gives the model concrete physical instructions, leading to more nuanced performances.
AI models are revolutionizing the initial creation of assets, much like smartphones did for capturing photos. However, the need for professional post-production tools like Adobe persists for editing, refining, and achieving high-fidelity control. AI becomes the first step in the creative workflow, not the entire process.
The quality and vision of an AI-generated video are determined more by the source reference images and videos than by the text prompt itself. Providing a strong visual reference gives the model a clear understanding of taste, style, and desired outcome, acting as a more powerful input than descriptive text alone.
Seedance V2's multi-input capability—combining images, videos, and audio—makes it function more like an advanced video editor than a simple text-to-video tool. This reframes its use case from pure creation to complex modification and composition, enabling tasks like character and background replacement within existing footage.
Even as a single AI model like Seedance V2 becomes the best overall tool, a market will remain for specialized models. Fine-tuned models like "Enhancer V4" can offer a unique aesthetic (e.g., less cinematic) or be optimized for a specific task (e.g., talking heads), making them preferable for certain use cases.
Optimal results from AI vision models require model-specific prompting. Seedance V2 thrives on highly detailed prompts, especially for preserving character identity and motion. In contrast, models like Kling 3 can perform better with more straightforward, less verbose instructions, demonstrating there's no one-size-fits-all approach to prompting.