As evidenced by the experimental results of Meta AI Research Institute in 2024, correct text prompts can reduce the motion coherence error rate (Δ value) of the generated video by image to video ai from 12.7% in the original condition to 3.1%, and improve the keyframe alignment accuracy to ±2 pixels (the industry norm is ±5 pixels). For example, if the prompt words “The top-down Angle of the drone rotates evenly around the city skyline at a rate of 5° per second” are inputted, in the 8-second video generated by Runway ML’s ai video generator, the perspective deformation rate of the building complex is only 0.8%. The control group with no labeled prompts’ deformation rate was up to 9.3% (data from the SIGGRAPH 2024 technical paper). In the field of e-commerce, inserting the text “Lipstick 360 degrees rotation under soft light background, color temperature 5600K±50 per frame” can reduce the product video return rate by 18% (case used from Sephora’s Q3 2024 operation report).
Technical parameter adjustment relies on quantitative explanation of prompt words. MIT Media Lab experiments show that prompt words with parameters such as “4K HDR, peak brightness 1000 nits, BT.2020 color gamut coverage 90%” can improve the PSNR (peak signal-to-noise ratio) of the image to video output from 32dB to 41dB, level with that of professional cameras. Adobe Firefly Video Enterprise Edition users confirmed that when “24 frames per second, shutter Angle 172.8°” was set in the prompt, motion blur accuracy reached up to 92%, 37% higher than in the default mode (data is available in Adobe’s 2024 technical white paper). In film and television industrial applications, “Star Wars: “The production team of “Jedi Legends” reduced AI-made Star Wars scene post-correction time from 120 hours to 9 hours with instructions such as “dark noise ≤ISO 800, particle effect density 1.2 million/cubic meter”, but an additional computing power cost of 0.15 US dollars per second was paid (the case is quoted from the ILM 2024 Technology Summit).
Multimodal prompts significantly enhance creative agency. The Google DeepMind Lumiere Pro model supports the joint prompt of “image + audio + text”. When the synchronized prompt of the drum rhythm (BPM=128) is input, the frame alignment error between dance video movements and the music reduces from ±300ms to ±28ms. TikTok creators’ actual tests prove that if combined with the visual cue phrase words “Camera movement: Dolly Zoom, slow in and slow out speed curve”, completion rate of the video is enhanced by 41% because the AI-generated camera movement is more in sync with human visual inertia (August 2024 edition of “Social Media Today” data). In medical education, Harvard Medical School used the command “anatomical section slice depth 0.2mm/frame, annotation font size 24pt” to enable the accuracy rate of surgical teaching videos produced by the ai video generator to increase from 78% to 95%. Production cost is 94% lower than 3D modeling (the case can be viewed in the New England Journal of Medicine in October 2024).
It is indicated that the project is reconfiguring the production process. The user research of OpenAI in 2024 shows that prompt words containing 3 to 5 quantitative parameters (such as “focal length 35mm, aperture f/2.8, vigo intensity 0.3”) can increase the output compliance rate of image to video ai from 48% to 89%. But if prompt words length exceeds 20 words, The memory use of GPU is boosted by 23%, and the lag during generation is raised by 0.7 seconds per frame. The auto advertisement market has confirmed that by using the prompt “Rainy road surface, water splash height 30cm, fluid simulation accuracy Level 4” can increase the actual shooting replacement rate from 35% to 82%, and reduce the production cost of a single advertisement by 64,000 US dollars (the case is cited from BMW’s 2024 Digital Marketing report). With Prompt word standardization, NVIDIA’s NeMo Prompt Optimizer tool can bring down the manual debugging time from 4 hours per project to 6 minutes, and compress the variance of aesthetic scores of AI videos simultaneously from ±15% to ±3.2% (Data source: Demonstration at GTC 2024 Conference).