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Dynamic AI
Co-Creation

A Human-Centered Approach.

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Chapter 6: AI Cinema

1. Multimodal AI

The integration of multimodal AI in cinema leverages cutting-edge generative models to streamline and augment every stage of the video production pipeline. Key AI tools include:

  • ChatGPT - For developing storylines, writing scripts, storyboarding, and generating detailed shot descriptions to prompt other AI systems.
  • Midjourney/DALL-E - Creating concept art, set designs, character models, props, and visual world-building using text-to-image generation.
  • RunwayML - Generating short video clips and animations, applying stylized effects and filters, rendering 3D environments and characters.
  • ElevenLabs/Anthropic - Generating realistic voice performances for characters, narration, and audio dialogue.
  • Stability AI - Procedurally generating soundtracks, Foley effects, ambiance, and audio textures.

This multimodal approach allows filmmakers to iterate fluidly across all production phases using AI as a complementary creative force. For example, a scriptwriter could prompt ChatGPT to generate a rough narrative premise, then feed that into Midjourney to visualize key characters and environments. Those visuals could drive prompts into RunwayML to render animation previsualization clips with ElevenLabs providing scratch character vocals to set the tone.

2. AI Scriptwriting

IMAGE of PROMPT next to script

AI scripting tools transcend basic text generation by integrating with visual world-building and storytelling systems. A creator can have ChatGPT generate not just plot outlines but detailed shot list descriptions structured as multimedia prompts - feeding both text and visual references to other generative models. This facilitates a back-and-forth iteration between textual and visual ideation that evolves the narrative with each AI-to-AI handoff.

For example, prompting ChatGPT with a basic premise like "A boy finds a mysterious orb in the woods" could yield a few paragraphs breaking that down into potential shots and sequences. Those textual shot descriptions could populate visual prompts into Midjourney rendering concept imagery of the boy, woods, and orb designs. Reviewing those outputs, the creator could re-prompt ChatGPT with new narrative branches inspired by the visuals. The cyclic AI-facilitated process nurtures an expanding web of story and aesthetic interconnections.

3. AI Production

RunwayML video

On the production front, Midjourney and RunwayML become powerful tools for crafting virtually any cinematic element out of text prompts and uploaded references:

  • World-Building - Generating lavish concept art, matte paintings, and design plates for entire civilizations, geographies, and eras.
  • Characters - Designing characters of any species or genre with rich physical and cultural detailing, then rigging and animating them.
  • Props/Sets - Creating fully dressed environments, vehicles, machinery, and custom set pieces with specific materials and lighting.
  • Cinematography - Experimenting with unique lenses, film stocks, photographic techniques, and stylized color treatments.
  • VFX - Generating visual effect shorts like pyrotechnics, energy blasts, force fields, and more for easy compositing in post.

This AI-driven production workflow enables creators to rapidly prototype spectacular animated visuals with unparalleled creative freedom. What might take teams of artists months can be spun up by a single person collaborating with AI - radically accelerating the turnaround from first ideation to final renders.

4. AI Post-Production

RunwayML video

AI ushers in similarly accelerated workflows for video editing, scoring, and post-production audio:

  • Video Editing - While human editors are still essential for high-level creative decisions, AI tools like RunwayML can automate tedious tasks like transcoding, assembling rough cut sequences, applying effects, and color grading using text prompts.
  • Voiceovers/Dialogue - Running scripts and storyboards through ElevenLabs generates rich character performances, narration, and lip-synced dialogue animation.
  • Sound Design - Tools like Stability AI procedurally generate layered Foley effects, ambiences, creatures, vocalizations, and even full scores based on text prompts and reference tracks. AI audio reactors can analyze and embody characteristics from sample sound libraries then remix and recombine those characteristics into new patterns based on text descriptions. A prompt like "ethereal underwater textures for mysterious deep sea sequences" could produce hours of usable underwater ambiences in seconds.

5. AI Effects

VIDEO DEMO

CHANGE While visual effects have relied on filming live plates or 3D graphics for decades, RunwayML and similar tools enable completely new AI-native VFX workflows:

  • Shot Synthesis - Creating final shots holistically from text prompts without any live footage thanks to advances in AI video and 3D rendering.
  • Seamless Compositing - Integrating AI-generated elements into footage with automated rotoscoping/matting using machine learning.
  • Physical Simulations - Running complex sims for natural phenomena like water, fire, smoke, cloth just from text instructions.
  • Style Transfer - Applying stylized filters and treatments automatically to match any desired photographic aesthetic or painterly rendering.

These AI VFX capabilities open new frontiers for directors to realize their boldest visions unconstrained by live action requirements. Entire movies could theoretically be authored as text streams generating shots, characters, and environments in perfect unison.

6. Unit Exercise

In this exercise, you will create a 1-2 minute video piece dramatizing a key narrative moment or short vignette from your AI-generated world. Leveraging the multimodal AI toolkit (ChatGPT, Midjourney, RunwayML, ElevenLabs, etc.), you will:

Export the final video and write a brief reflection analyzing how the AI toolset enabled (or constrained) your creative vision for this world's narrative. The goal is to produce a polished video piece that brings your imagined world vividly to life through synthesized visuals, performances, and audio design - all facilitated by collaborative AI co-creation across the whole production lifecycle.

7. Discussion Questions

Some key discussion points around using multimodal AI for filmmaking:

8. Bibliography

Some key texts for further study of this topic could include readings on the latest developments in generative AI for media, filmmaking case studies, emerging best practices, and ethical/legal considerations.