Generative AI has revolutionized the marketing landscape, offering unprecedented tools to bring visions to life. From text-to-image technologies that transform written descriptions into stunning visuals, to text-to-video capabilities that craft engaging multimedia content from simple prompts – the possibilities are boundless.
Text-to-code functionalities streamline web development, while video-to-code and image-to-video conversions open new avenues for content and interactive experiences. These innovations empower marketers to produce new types of assets, personalize content at scale, and explore novel forms of storytelling.
By harnessing generative AI, brands can create more immersive campaigns, and enhance customer engagement, leveraging these technologies to outthink, outpace, and ultimately outgrow their competition. As these technologies continue to evolve, they’re not just transforming how marketing content is created—they’re redefining the very boundaries of creative expression.
Text to Film: Runway and Sora
Runway and Sora stand at the forefront of multimodal AI, pushing the boundaries of what AI can create. Runway is a creative platform that enables users to experiment with AI-powered tools for video editing, music generation, and text-to-image generation.
Sora is a cutting-edge diffusion model designed for video generation. It starts with an initial state resembling static noise and progressively refines this into a coherent video. It has the unique ability to generate videos in their entirety or to extend existing ones, ensuring consistent representation of subjects throughout, even when they temporarily exit the scene.
Leveraging a transformer architecture similar to that used in GPT models, Sora achieves enhanced scalability. Videos and images are broken down into patches, similar to tokens in GPT, allowing for training across a vast spectrum of visual data, including various durations, resolutions, and aspect ratios. Drawing upon research from DALL-E and GPT models, particularly employing DALL-E 3’s recaptioning technique, Sora excels in adhering to textual instructions and producing videos that are remarkably aligned with user prompts. It can animate still images or extend and enrich existing videos with unprecedented detail. This model is paving the way for AI’s capability to understand and replicate the complexity of the real world, marking a significant step toward achieving AGI.
Sora can create mid-length films of a minute in duration, showcasing unbelievable fidelity and photorealistic accuracy, demonstrating the profound advances in AI’s ability to generate complex, dynamic visual content.
Source: OpenAI’s Sora
Text to Video: Diffusion Transformers – OpenAI’s Sora
Sora prompts: Extreme close-up of a 24-year-old woman’s eye blinking, standing in Marrakech during magic hour. Drone view of waves crashing against the rugged cliffs along Big Sur’s Garay Point beach. A litter of golden retriever puppies playing in the snow. The camera follows behind a white vintage SUV with a black roof rack as it speeds up a steep dirt road.
A drone camera circles around a beautiful historic church on a rocky outcropping along the Amalfi coast. Tour of an art gallery with many beautiful works of art in different frames. Beautiful, snowy Tokyo city is bustling. The camera moves through the bustling city street, following a couple.
And then there is lip-synching. Early in 2024, Alibaba showcased a new image-to-video algorithm called EMO that could bring to life photographed individuals, animating them into speaking words or singing songs. This presented a new standard in the technology available to create natural cognitive assistants.
Source: ilumine_ai, X (Formerly Twitter)
Image to Film
With diffusion models being used to generate images that are then loaded into text-to-video models to create a film based on the image.
With a new feature from Runway Gen-3 that allows users to set the film to end with the last frame matching the uploaded image. See example.
Video to Video
Generative AI video-to-video technology allows users to take an existing video asset and transform it into something entirely new by applying AI-driven enhancements and edits.
This capability uses deep learning models to analyze the video’s elements—such as visuals, audio, motion, and even styles—while enabling intelligent adjustments and creative augmentations.
Source: Ror_Fly, X (Formerly Twitter)
Whether it’s modifying the background, changing color schemes, adding new visual effects, or completely reimagining the scene, this technology offers an advanced, automated way to elevate or reinvent video content.
Source: iamneubert, X (Formerly Twitter)
With video-to-video generative AI, creators can save time on manual editing and unlock new possibilities for content innovation. Capabilities include altering weather conditions, adjusting lighting, adding or removing objects, transforming characters, and even shifting the video’s overall aesthetic to match different styles. This enables businesses and creators to rapidly generate multiple variations of a single video asset, tailored to different platforms, audiences, or use cases—enhancing scalability and creative flexibility.
