Pricing & FAQ

AIGC stands for Artificial Intelligence Generated Content. It refers to technology that automatically generates content such as text, videos, and audio based on instructions like text or images, using generative AI models (e.g., GANs, diffusion models). Its core principle is that AI models learn patterns from massive amounts of data and convert input “demand instructions” into logical and aesthetically pleasing content, without the need for manual creation of each element.

Yes. Currently, mainstream AIGC video tools (e.g., Pika Labs, Runway) have achieved “no-code” operation. Users only need to describe their needs in natural language (e.g., “A cat playing with a ball of yarn in the snow, animation style, 10 seconds long”), and the tool can automatically generate the corresponding video. There is no need to master programming or video editing skills, and some tools even provide template functions to further lower the threshold.

There are potential risks, which need to be avoided through compliant operations. First, confirm the agreement of the AIGC tool used: commercial tools (e.g., Adobe Firefly) usually stipulate that users can use the generated content for commercial purposes, but avoid generating elements with others’ intellectual property rights (e.g., well-known IP images). Second, prioritize tools with compliant training data (e.g., models stated to be trained with legitimate materials). For high-value commercial scenarios, it is advisable to consult legal professionals to confirm copyright ownership.

The core reason is the high difficulty of “spatiotemporal dimension modeling” for videos. A video is a continuous sequence of frames, and AI needs to ensure both the quality of individual frames and the coherence between frames. “Object distortion” mostly occurs because AI lacks sufficient modeling of the spatial structural consistency of objects (e.g., abnormal number of fingers on a person). “Frame stuttering” is due to defects in temporal dimension modeling (e.g., sudden breaks in the movement trajectory of objects). Currently, problems in short-duration (10-30 seconds) and simple scenarios have been significantly improved, while complex scenarios still require technical iteration.

The key differences among the three lie in the “creator” and “efficiency-cost”: UGC (User Generated Content) is created by ordinary users, relying on personal experience with low output; PGC (Professional Generated Content) is created by professional institutions/practitioners, requiring professional skills with high costs and long cycles; AIGC is created by AI models, which can quickly generate a large amount of content based on a small number of instructions, breaking the limitations of manpower and time. For example, 10 marketing short videos of different styles can be generated within 10 minutes.

Quality can be improved through three approaches: ① Optimize instruction descriptions: add details (e.g., “1080P resolution, cinematic lighting, Hayao Miyazaki animation style, smooth movements of the protagonist without stuttering”) and avoid vague expressions; ② Choose suitable tools: select tools supporting 4K (e.g., Sora) for high-definition needs, and tools good at specific styles (e.g., Pika Labs for animation style) for stylized needs; ③ Post-production adjustments: use video editing tools (e.g., CapCut, Premiere) to fix slight stuttering, or AI enhancement tools (e.g., Topaz Video AI) to improve clarity.